Since repetition of actions serve the purpose of skill acquisition and mastery, as development progresses and mastery of skills is attained, RRBs reduce overtime in typically developing children . Specifically, studies have found consistent patterns of certain repetitive behaviors present in the first year, increase until roughly the age of three and start to decline around the fourth year . This reduction in repetitive behaviors over time has been found in studies using parent report measures of children in the first four years of life , as well as observational coding of repetitive behaviors in young children .Studies involving early developmental behaviors face the obstacle of the fluctuations that naturally occur in development, making the measurement of behaviors an important factor to consider. Specifically for RRBs, the type of repetitive behaviors captured, environmental influences such as location or caregiver presence, and the measurement tool used can all influence results. Thelen examined body stereotypies of 20 infants in the first year using live behavioral observations across contexts such as feeding, interactions with caregivers and while the infants were interacting with objects. Thelen collected data on bouts of rhythmical body movements including movements of the legs , torso and arms . While stereotypies decreased over time, contextual triggers impacted the type of body stereotypies observed. Patterns in stereotypies were found to increase when the infants were interacting with their caregivers, dutch buckets system and while in a heightened state of arousal. Understanding contextual dependency and fluctuations within the TD population will help to inform similar behaviors observed in children with ASD.

It has been posited that in the case of caregiver interactions, increased stereotypies may serve a communicative function; that is, kicking and bouncing rhythmically may serve communicative value to express pleasure and excitement. These differences found in frequency of stereotypies when a caregiver is present highlights the importance of measurement, and for many behaviors, parent report may be the most inclusive tool to better understand the presence of atypical behaviors across contexts. Understanding the developmental pattern, frequencies and types of RRBs in typically developing children is informative in determining what constitutes atypicality of RRBs for children with ASD. The repetition of behaviors observed in typically developing infants andtoddlers exhibit overlap with the behaviors indicating developmental concern or impacting diagnostic outcomes in children with ASD. Unfortunately, information is somewhat limited on the presence, severity and developmental pattern of specific RRB subtypes longitudinally. More often, studies have examined the role of RRB presentation in differentiating children with ASD from other clinical or control groups. Findings have indicated that in contrast to the pattern found for TD children of RRBs peaking around 2 and dissipating by 4, children with ASD exhibit a continual increase in the frequency and severity of RRBs through late childhood . The organization, division and measurement of RRBs inevitably influence findings; such methodological inconsistencies have pervaded RRB research and limited understanding of complicated relationships between RRBs and other individual characteristics . A variety of approaches have been taken to organize and operationally define RRBs in ASD. In order to build upon advances made in RRB research, it is essential to consider the methodological approaches taken .The decision to include or exclude certain RRB types significantly influence results, leading to inconsistencies across studies purely based on methodological limitations. Therefore, in order to sufficiently understand and improve this area of research, researchers must evaluate the organization, inclusion and exclusion of RRBs, which vary by study.

As Troyb points out, findings vary based on the behavior included, with inconsistent results between RRBs and, for example, functioning level, based on the RRB types examined. The most commonly used organization, definition, and measurement of RRBs will be described further.Dichotomization of behaviors into low-level and high-level RRBs is one of the most common organizational approaches . An alternative label for these two categories are Repetitive Sensory Motor behaviors for low-level RRBs and Insistence on Sameness for high-level RRBs . This approach of dichotomizing RRBs is nearly identical, therefore low level and RSM can be used interchangeably, and the same applies to high-level and IS behaviors. Low-level RRBs include repetitive motor stereotypies such as hand flicking, body rocking, etc., stereotyped or repetitive speech vocalizations, and repetitive actions with objects such as spinning wheels, repetitively opening and closing containers, etc. These behaviors may also possess sensory components, implying a physiological function may be simultaneously served while children engage in certain RRBs . RRBs conceptualized as low-level are often associated with younger and lower functioning children, yet are also present in early typical development and in other developmental and psychiatric conditions such as Fragile-X syndrome, Rett syndrome and Tourette’s syndrome . High-level behaviors encompass behaviors such as intense preoccupation with a restricted interest, ritualized behavior patterns, and excessive adherence to routines with significant resistance to change . The most commonly described high-level RRBs include behaviors such as rituals and routines, which make up insistence on sameness behaviors . These rigid behavioral patterns were documented in the original description of ASD as a staple of the unique features of the disorder .

High-level behaviors are commonly associated with older and higher functioning children, when children are more likely to be able to communicate and share intense and perseverative interests, commonly referred to as circumscribed interests, with others . It is possible for multiple subtypes, that is, across high and low level RRB classifications to take place simultaneously, further complicating the measurement and recognition of each RRB presentation . Despite the popularity of this simple shorthand to group behaviors, it has been cautioned that this approach is too broad and may obscure important differences between the many types of RRBs . RRBs have been organized in a number of ways; however differences among how studies categorize behaviors reduce comparability of results. Results are dependent upon the measurement tools used to organize and define various RRB subtypes; therefore it is important to understand the strengths, weaknesses, inclusion and utility of common measurement tools in exploring patterns of RRBs among individuals. The diagnostic criteria for autism spectrum disorder has recently been altered to a dyad of impairments in the domain of social communication ability and the presence of atypical restricted and repetitive behaviors ; American Psychiatric Association, 2013. As the manual for defining and diagnosing a range of disorders, the DSM’s definition of ASD symptomology is important to consider in conceptualizing definitions and measures of RRBs in ASD. The DSM-5 categorizes RRBs into four domains, children must manifest at least two of the following: stereotyped or repetitive speech, motor movements, or use of objects; excessive adherence to routines, ritualized patterns of verbal or nonverbal behavior, or excessive resistance to change; highly restricted, fixated interests that are abnormal in intensity or focus; and hyper- or hypo- reactivity to sensory input or unusual interest in sensory aspects of their environment.The methodological inconsistency across studies is often due to the current lack of a consistent and universal measurement of RRBs. Measurement tools dictate the operational definitions employed, methodological variability in data and analysis between studies, and results found between RRBs and related characteristics . Parent reports have been the most prevalent form of measuring RRBs in children with ASD, which vary across studies. Autism Diagnostic Interview- Revised . The ADI-R is a parent report measure designed to capture developmental history as well as current symptom presentation of individuals with ASD. The three domains the ADI-R addresses are: language and communication, reciprocal social interaction, and restricted,repetitive, and stereotyped behaviors. Each of the three domains has a cut-off score, providing a diagnostic algorithm, which is accurate in differentiating an ASD diagnosis from other disorders. Even though the ADI-R is not intended to independently and all-inclusively measure RRBs, a number of studies have characterized RRBs in individuals with ASD using the RRB sub-scale of the ADI-R . The RRB domain of the interview includes information on both what the child has displayed in the past as well as what behaviors the child is currently exhibiting. Most commonly, studies examining RRBs using this measure exclusively use the “current” items only . Notably, evidence for the dichotomy of high and low-level RRBs were derived from studies that used the ADI-R as their measurement of RRBs; therefore, dutch buckets it hasn’t been unanimously established if that organizational approach is applicable to all individuals with ASD, or if the dichotomy is due to the factor structure of the ADI-R . Despite it’s popularity, there is also methodological concern when studies use a measure for multiple purposes; as the intended use for the ADI-R is to measure a continuum of ASD characteristics and determine diagnostic eligibility. Therefore, utilization of a measurement tool solely for the purpose of measuring RRBs with established validity, reliability and inclusion of all subtypes of RRBs would likely produce a stronger tool for quantifying RRBs. Repetitive Behavior Scale- Revised . The RBS-R is a questionnaire that was designed for the purpose of exclusively measuring a variety of RRBs.

The measure includes 43 items that are rated on a four-point Likert scale across 6 sub-scales, which were conceptually derived and reported by the primary caregiver. The original sub-scales include: stereotyped behavior; self-injurious behavior, compulsive behavior, ritualistic behavior, sameness behavior, and restricted behavior. Since it’s conception, several factor analytic studies have been conducted with the RBS-R with varying results, implying that the original factor structure of 6 sub-scales is not statistically supported based on these results . Lam & Aman were the first to independently explore the factor structure of the RBS-R. They examined data from 307 participants and explored a large age range of individuals with ASD . Results indicated that the RBS-R provides five factors, which overlap with five of the six original scales; the Ritualistic sub-scale, originally proposed by Bodfish, et al. , was the only scale not included in the new factor solution. This finding was supported in a subsequent study of 712 individuals ranging from 2 to 62 years old, which explored the five-factor model . Additionally, Mirenda, et al. used a confirmatory factor analysis to compare several different proposed structure models and found the best models were the Lam & Aman five-factor model and a three factor model . Most recently, Bishop, et al. explored the relationship between ADI-R scores and RBS-R relating to the construct validity of using the RSM and IS dichotomy for RRBs in over 1,800 individuals with ASD. Results from the initial exploratory factor analysis of the RBS-R were similar, with slight divergence in items factor loadings from previous investigations and from the original RBS-R factors . In consideration of the varying results across studies, further exploration of the RBS-R factors is warranted. Organization and measurement of RRBs is a complicated undertaking, with inevitable influence on outcomes when examining the relationship between RRBs and other developmental characteristics . Therefore, advances in understanding the complicated relationships between RRB presentation, chronological age, cognitive functioning, and other developmental skills have progressed more gradually. However, incremental advancement is logical given the complexity and difficulty in RRB measurement. Despite the complexity of RRB presentation and the numerous issues in organization and measurement described, careful evaluation of the phenotypic patterns and related characteristics found warrants further consideration.The relationship between age and RRB presentation in ASD has most commonly been examined through the use of cross sectional data analysis . Researchers have found that that younger children with ASD exhibit higher frequency of low-level RRBs such as motor stereotypies and sensory related behaviors; whereas older, higher functioning individuals on the spectrum tend to exhibit more high-level RRBs, with reduction in low-level RRBs . Specifically, Militerni, et al. found that toddlers exhibited significantly fewer RRBs than older children ; though, this was only true for sensory and motor RRBs , which were significantly less prevalent in the older group. However, the older children were not devoid of RRBs, they instead displayed more complex RRBs such as routinized schedules and insistence on sameness. The developmental trajectories of children with ASD are complex in their symptom presentation across time, further complicated by the manifestation of various types of RRBs. There have been several studies to examine RRB presentation overtime, with varying results across studies . The most common finding in regards to age and RRBs has been an overall reduction overtime in RRBs, with a more significant decrease overtime in low-level RRBs such as repetitive object use or motor actions .

In a previous analysis, WGCNA defined a circadian clock subnetwork that was highly connected to transcript abundance profiles in late ripening grapevine berries. To compare the response of the circadian clock in the two different locations, we plotted all of the genes of the model made earlier. Most core clock genes and light sensing and peripheral clock genes had significantly different transcript abundance in BOD berries than that in RNO berries at the same sugar level . All but one of these had higher transcript abundance in BOD berries relative to RNO berries. The transcript abundance of other genes had nearly identical profiles . These data are summarized in a simplified clock model , which integrates PHYB as a key photoreceptor and temperature sensor that can regulate the entrainment and rhythmicity of the core circadian clock, although to be clear it is the protein activity of PHYB, not the transcript abundance that is regulating the clock.The top DEGs in berries from BOD were highly enriched in the GO category for biotic stimuli including genes encoding pathogenesis proteins . The transcript abundance ofsuch genes in BOD berry skins was higher than those in RNO berries . The transcript abundance of PR10 increased with increasing sugar level. This gene responds in Cabernet Sauvignon leaves when infected with powdery mildew. Powdery mildew induced other genes such as a PR3 protein , a PR5 protein and many stilbene synthases . The expression of these genes was also at much higher transcript abundance levels in BOD berries than in RNO berries. MLA10 matches to a fungal protein from E. necator. In that study, grow strawberry in containers it was used as a control probe set to detect the presence of powdery mildew.

There was a higher transcript abundance of g343420 in BOD berries than that in RNO berries. These results indicate that there may have been a higher powdery mildew infection in BOD berries along with a higher induction of the phenylpropanoid pathway.There were 71 DEGs that were enriched in the response to ethylene GO category . Ethylene is a stress hormone that responds to many types of biotic and abiotic stresses in addition to its role in fruit development and ripening. Many ethylene related genes had a higher transcript abundance in BOD berries. These included ethylene biosynthesis, ethylene receptors and ERF transcription factors . ERF1 and ERF2 are at the beginning of the ethylene signaling pathway and are direct targets of EIN3. Other ERF transcription factors identified as hubs in the ethylene signaling pathway in Arabidopsis leaves were also differentially expressed in a similar manner as ERF1 and ERF2 between the two locations .Fourteen DEGs were associated with genes enriched in response to iron ion ; Eight examples of DEGs involved in iron homeostasis are shown in Fig. 11. Iron homeostasis genes SIA1 , VIT1 , ATH13 , IREG3 , and ABCI8 have higher transcript abundance in BOD berries than in RNO berries. Iron homeostasis genes YSL3 , FER1 , and NRAMP3 had higher transcript abundance in RNO berries compared to BOD berries. Several other ferritin genes were expressed similarly to FER1 . Average available iron soil concentrations were about 5 times higher in the BOD vineyard soil compared to the RNO vineyard soil .The common gene set for both locations represented approximately 25% of the genes differentially expressed with sugar level or location. Presumably these gene sets represent genes that were not influenced by location but were influenced by berry development or sugar level. This study is limited in that only two locations in one season were investigated. As more locations are compared in the future, these gene sets will likely be reduced in size even further.

The processes involved in these gene sets or modules included the increase of catabolism and the decline of translation and photosynthesis. It is clear that these processes play important roles in berry ripening. Most of the genes in the genome varied in transcript abundance with increasing sugar levels and berry maturation and most of these varied with the vineyard site. Many of the DEGs were enriched with gene ontologies associated with environmental or hormonal stimuli.Plants are exposed to a multitude of factors that influence their physiology even in controlled agricultural fields such as vineyards. The vineyards in BOD and RNO are exposed to very different environments ; these environmental influences were reflected in some of the DEG sets with enriched gene ontologies. The results from this study are consistent with the hypothesis that the transcript abundance of berry skins in the late stages of berry ripening were sensitive to local environmental influences on the grapevine. While most transcript abundances in berries are largely influenced by genetics or genotype, environment also plays a large role. It is impossible with the experimental design of this study to determine the amount that each of the environmental factors contributed to the amount of differential expression in these two locations. There were too many variables and too many potential interactions to determine anything conclusively. Replication in other seasons will not aid this analysis as climate is highly variable and will produce different results. All we can say is that these genes were differentially expressed between the two locations, which were likely due to known and unknown factors . As additional studies are conducted indifferent locations and seasons in the future, meta analyses can be employed to provide firmer conclusions. It is possible that some of the DEGs identified in this study resulted from genetic differences between the different Cabernet Sauvignon clones and rootstock used in the two locations.

Not knowing what these genes might be from previous studies prevents us from drawing any clues. These and other factors most certainly affected the berries to some degree. The data in this study indicated that the grape berry skins responded to multiple potential environmental factors in the two vineyard locations in addition to potential signals coming from the maturing seed. We say potential environmental factors because we did not control for these factors; we associated transcript abundance with the factors that were different in the two locations. The transcript abundance profiles along with functional annotation of the genes gave us clues to factors that were influencing the berries and then associations were made with the known environmental variables. Further experiments are required to follow up on these observations. We were able to associate differences in transcript abundance between the two locations. These DEGs could be associated with temperature, light, moisture, and biotic stress. Additional factors were associated with transcript abundance involved with physiological responses and berry traits such as seed and embryo development, hormone signaling , phenylpropanoid metabolism, and the circadian clock. In the following sections we discuss in more detail some of the possible environmental factors that were reflected in the enriched gene ontologies found in the gene sets from this study.Light regulates the transcript abundance of many genes in plants. It has been estimated that 20% of the plant transcriptome is regulated by white light and this includes genes from most metabolic pathways. Light is sensed by a variety of photo receptors in plants; there are red/far red, blue and UV light receptors. PHYB is a key light sensor, regulating most of the light sensitive genes and sensing the environment through red light to far-red light ratios and temperature. PHYB entrains the circadian clock affecting the rate of the daily cycle and the expression of many the circadian clock genes; PHYB induces morning phase genes and represses evening phase genes. Other photoreceptors can entrain the circadian clock as well. PHYB and the circadian clock are central regulators of many aspects of plant development including seed germination, seedling growth, and flowering. The circadian clock influences the daily transcript abundance of genes involved in photosynthesis, sugar transport and metabolism, biotic and abiotic stress, even iron homeostasis. Light signaling was very dynamic in the berry skin transcriptome in the late stages of berry ripening with a higher transcript abundance of many light signaling genes in BOD berries. Many photo receptors that interact with the circadian clock had a higher gene expression in BOD berries. In the circadian clock model, Circadian Clock Associated 1 is an early morning gene and has its highest expression at the beginning of the day. It is at the start of the circadian core clock progression through the day, hydroponic nft channel whereas the transcript abundance of Timing Of CAB Expression 1 is highest at the end of the day and finishes the core clock progression . In both of these cases, there is a higher transcript abundance of these genes in BOD than in RNO. The evening complex is a multi-protein complex composed of Early Flowering 3 , Early Flowering 4 and Phytoclock 1 that peaks at dusk. None of these proteins, had significant differences in transcript abundance between the two locations .

The transcript abundance of ELF3 increased with sugar level and shortening of the day length . ELF3, as part of the evening complex , has direct physical interactions with PHYB, COP1 and TOC1 linking light and temperature signaling pathways directly with the circadian clock. It is interesting that most of the components of the clock showed significant differences in transcript abundance between BOD and RNO, except for the three proteins that make up the evening clock. The transcript abundance profile of PHYB was similar in both BOD and RNO berries , however the changes in transcript abundance with sugar level occurred in BOD berries at a lower sugar level. There was a gradual decline of PHYB transcript abundance with increasing sugar level until the last measurement at the fully mature stage, where there was a large increase in transcript abundance. A very similar profile is observed for Reveille 1 . RVE1 promotes seed dormancy in Arabidopsis and PHYB interacts with RVE1 by inhibiting its expression. PIF7 , interacts directly with PHYB to suppress PHYB protein levels. Likewise, PIF7 activity is regulated by the circadian clock. PIF7 had higher transcript abundance in the BOD than that of RNO berries and generally increased with increasing sugar level. The transcript abundance of two of the other grape phytochromes did not vary significantly between the two locations or at different sugar levels. PHYC had a higher transcript abundance in RNO berries and did not change much with different sugar levels. Many other light receptors , FAR1 , FRS5 , etc. had higher transcript abundance in BOD berries . Thus, light sensing through the circadian clock is a complicated process with multiple inputs. RVE1 follows a circadian rhythm. It behaves like a morning-phased transcription factor and binds to the EE element, but it is not clear if it is affected directly by the core clock or through effects of PHYB or both. PHYB down regulates RVE1; RVE1 promotes auxin concentrations and decreases gibberellin concentrations. Warmer night temperatures cause more rapid reversion of the active form of PHYB to the inactive form and thus may promote a higher expression/activity of RVE1. Pr appears to accelerate the pace of the clock. It is unclear what role phytochromes might have in seed and fruit development in grapes. Very little is known about the effect of PHY on fruit development in general. In one tomato study, the fruit development of phy mutants was accelerated, suggesting that PHYB as a temperature/light sensor and a regulator of the circadian clock may influence fruit development. Carotenoid concentrations, but not sugar concentrations, also were affected in these mutants. Photoperiod affects the transcript abundance of PHYA and PHYB in grape leaves. In the present study, the transcript abundance of the majority of the photoreceptor genes in berry skins, including red, blue and UV light photoreceptors, had a higher transcript abundance in BOD berries . However, there were clear differences between the two locations; it seems likely that PHYB and the circadian clock are key grape berry sensors of the environment, affecting fruit development and composition.The grape berry transcriptome is sensitive to temperature. Temperature related genes were differentially expressed at the two locations in our study. The RNO berries were exposed to a much larger temperature differential between day and night than BOD berries and were also exposed to chilling temperatures in the early morning hours during the late stages of berry ripening . The transcript abundance of some cold-responsive genes was higher in RNO berry skins than in BOD berry skins , including CBF1.

If you don’t know how to compute the frequency-dependent impedance of heat flow through gaseous helium at 1.5K, then that’s fine, because I don’t either! I only mention it because it’s important to keep in mind that just because your electrical circuit isn’t encountering large phase shifts and high impedance, doesn’t mean the thermal signal is getting to your nanoSQUID without significant impedance. I recommend operating at a relatively low frequency for these reasons, as long as the noise floor is tolerable. In practice this generally means a few kHz. I’d also like to point out that if you are applying a current to your device at a frequency ω, then generally the dominant component of the thermal signal detected by the nanoSQUID will be at 2 · ω, because dissipation is symmetric in current direction . Next you will perform your first thermal scan, 10-20 µm above the surface near your first touchdown point. If you have performed a thermal characterization, then pick a region with high thermal sensitivity, but generally this is unnecessary- I usually simply attempt to thermally navigate with a point that has good magnetic sensitivity. Bias the SQUID to a region with good sensitivity. Check the transfer function. Set the second oscillator on the Zurich to a frequency that is low noise . Connect the second output of the Zurich to the trigger of one of the transport lock-ins and trigger the transport lock-in off of it. Trigger the second transport lock-in off of the first one. Attach the output of one of the lock-ins to the 1/10 voltage divider, then to a contact of the sample. Attach the current input of one of the lock-ins to another contact as the drain. You can attach the voltage contacts somewhere if you want to, this is not particularly important though.

It may be necessary to a apply a voltage to the gates, especially if you are working with semiconducting materials, dutch bucket for tomatoes like the transition metal dichalcogenides.Increase the voltage until you see 1 µA of current. In my experience, members of the nanoSQUID team tend to be a little too timid about applying large currents to these samples because they are very susceptible to damage through electrostatic discharge, and of course it feels pretty bad to damage a device somebody else made for you. Although it’s true that researchers doing transport measurements almost never use currents as high as 1 µA, I can tell you that we have never damaged a heterostructure with high current at all, and certainly not at 1 µA. It is generally pretty safe to go as high as 100 µA, and we have gone considerably higher than that too. Currents greater than 1 µA will saturate the lock-in input, but you can still increase the voltage if you need to . Alternatively you can use the Ithacos adjustable transimpedance amplifier as the sink. If you do so, be careful not to adjust any of the knobs on this device while it is hooked up to the heterostructure, because adjusting those knobs can produce pulses of current large enough to damage devices. While you’re increasing the voltage, keep an eye on the SQUID signal. Increase the time constant if it helps you see the signal . Once you see a signal on the nanoSQUID channel of the Zurich, set up a scan. Check that the auxiliary outputs from the Zurich are going to the right ADC inputs, the right ADC inputs are correctly labelled in the scan window, the right auxiliary outputs are set up in the Zurich ‘Aux’ window and are sampling the right channels, and the right channels are set up and activated in the Zurich window. You should definitely see a thermal gradient if the signal is 3-5x the noise floor. If you don’t, I’d recommend investing some time into making sure the measurement is set up correctlyyou don’t want to just keep increasing current through the sample in response to not seeing features on a scan that isn’t set up right!

If you get really frustrated and want a sanity check, click “Set Position” to each of the corners of the scan range and watch the signal on the Zurich control panelit should change if everything is working. There are a lot of issues that can affect scanning, and it isn’t really possible to cover all of them in this document, so you will have to rely on accumulated experience. Some problems will become obvious if you just sit and think about them- for example, if the thermal gradient is precisely along the x-axis and coarse positioner navigation is failing to find a strong local maximum it likely means that the y-axis scanner is disconnected or damaged. In Andrea’s lab, the basic circuits on the 1.5K and 300 mK systems as currently set up should be pretty close to working, so if there’s a problem I’d recommend observing the relevant circuits and thinking about the situation for at least a few minutes before making big changes. The scanners as currently installed on the 1.5K system do not constitute a healthy right-handed coordinate system, so to navigate you will need a lookup table translating scanner axes into coarse positioner axes. I think this issue is resolved on the 300 mK system, but this is the kind of thing that can get scrambled by upgrades and repair campaigns. In all of our note taking Powerpoints and EndNotes, we have a little blue matrix that relates the scan axes to the coarse positioner axes. Use this to determine and write down the direction you need to move in the coarse positioner axes in your notes. You now have an initial direction in which you can start travelling. We will next perform long distance thermal navigation, at a height of 150 µm above the surface. Retract 150 µm using axis 3 of the coarse positioners. I’d recommend doing this in one or two big steps, because the coarse positioner can slide in response to small excursions. Verify that you can still see the thermal signal on the SQUID. It is Ok if it’s faint or close to the noise floor; it will increase in size, and you know which directions to start travelling. If the resistive encoders are working , then use them to move in 100 um steps, checking the SQUID signal in between movements. There is no need to ground the SQUID in between coarse positioner steps, there will be crosstalk but this is not hazardous for the nanoSQUID. If the resistive encoders are not working, click the Step+ button repeatedly until the SQUID signal increases to a maximum. This might take a few minutes or so of clicking.

You can work on a software solution instead if you like , but remember that there is always a simple, safe solution available! Once the signal is at a maximum, blueberry grow pot take another scan to verify that you’re centered above the device. You should see a local maximum in the temperature in the middle of your scan region. Ground the SQUID. Ramp the current through the device down to zero. Zero and ground any gates you have applied voltages to. Ground the sample. Make sure the SQUID is grounded to the breakout box by a BNC . Hook up the second little red turbo pump to the sample chamber through a plastic clamp and o-ring, and turn it on. Slowly, over 10-20 minutes, open the valve to the sample chamber and pump it out. Make sure the sand buckets for vibration isolation are set up and the bellows aren’t touching the ground. If there are vibration issues you can often feel them on the bellows and on the table with your hand. Repeat the setup for approaching to contact, and approach to contact. Definitely watch the first few rounds of this approach! You can even watch the whole thing- it’ll take 30-45 mintues, but if you’ve messed something up then the approach will destroy both the SQUID and the device, because you’ve carefully aligned the SQUID with the device! Once you’ve reached the surface, you will set up the SQUID circuit. Attach its output to the input of the feedback box. This output goes through the ground breaker that is clamped to the table in Andrea’s lab; all of these analog electronic circuits are susceptible to noise and ringing, so I’m sure there will be different idiosyncracies in other laboratories with other electromagnetic environments. Attach the output of the feedback box to the BNC labelled FEEDBACK . This is the BNC that should get a resistor in series if you wanted to increase the transfer function. We generally use resistors between 1 kΩ and 10 kΩ for this. To start with, just using nothing is fine . Plug the preamp and feedback box into fresh batteries . Turn the preamp on. Turn the feedback OFF. Hook up the SQUID bias wires to SQUID A and SQUID B. You can tell which they are because of the chunky low pass filters on the end, but of course they are also labelled. Make sure both sides of the SQUID are grounded while hooking it up- there is a BNC T there for a grounding cap for this purpose. Hook up Output 2 of the Zurich to signal input on the feedback box. Apply 1 V to signal input. There’s a good chance you just used this same output and cable to apply avoltage to the device, so be careful not to skip this step and apply this voltage to the device itself! You should see the SQUID array transfer function on the oscilloscope . Turn the rheostat/potentiometer on the preamp until this pattern has maximum amplitude. Turn the Offset rheostat/potentiometer on the feedback box until this passes through zero . There is a more sophisticated procedure for minimizing noise in the SQUID array; this is covered in great detail by documents Martin Huber has provided to the lab. But if you are a beginner this simple procedure will work fine. Flip the On switch on the feedback box, and watch the interference pattern vanish, replaced by a line near V = 0. Turn off the AC voltage going to signal input. You are now ready to characterize the SQUID, although you’ll need to unground it. That includes removing the BNC grounding caps from the T’s downstream of the SQUID bias filters and also flipping the BNC switch on the top of the rack. Click ‘preliminary sweep’ on the nSOT characterizer window. Sweep from 0 to 0.1. If you see a linear slope, a ton of stuff is working! The SQUID bias circuit, the SQUID array, the feedback electronics, all the cryogenics- that’s a really good sign. If you see no signal, don’t panic. Once again, there’s a lot of stuff involved in this circuit and a ton of mistakes you can make. Go back through the list and check everything, then check to make sure the SQUID bias isn’t grounded somewhere. Increase the sweep range until you see a critical current or you get above 3.3 V, which is where the feedback box will fail. If you don’t see a critical current, you have a SHOVET but not a SQUID. If you see a critical current, close the window, switch to the nSOT characterizer, and characterize the SQUID. At this point, you are at the surface and over the device with a working SQUID, and you can begin your imaging campaign, so what comes next is up to you!Anthocyanins constitute a large family of plant polyphenols and are responsible for many of the fruit and floral colors observed in nature. Anthocyanins are water-soluble pigments located in the grape skin vacuoles that, during the fermentation process, are released into the wine. It has been demonstrated that determining the amount of pigments present in the berries is not enough to estimate the concentration of anthocyanin in the final product. This lack of correlation is mainly attributed to the interaction between the pigments and the skin cell walls during the extraction process. Additionally, the adsorption of phenolics to solids in the fermentor after being released, such as grape skins and yeast hulls, has previously been demonstrated.

These are precisely the conditions satisfied by the electron spin degree of freedom that allowed it to produce magnetism! So, under these circumstances- i.e., assuming we can find conditions under which a band in graphene has finite anguluar momentum in its ground state, strong electronic interactions, and a flat-bottomed or flat band- we can expect to find a new form of magnetism, dubbed by theorists ‘orbital magnetism,’ wherein center of mass angular momentum coupling to the electron charge is responsible for the magnetic moment, instead of electron spin. There are many important corollaries of the arguments we’ve just discussed, and many more of them will appear later, but there are a few I’d like to focus some special attention on. We discussed earlier how the orientation of electron spin generally does not interact with electronic band structure unless we invoke relativistic effects in the form of spin-orbit coupling. Carbon atoms are extremely light, and as a result the energy scale of spin-orbit coupling in graphene is quite low. For this reason condensed matter researchers in the distant past na¨ıvely expected not to find magnetic hysteresis ingraphene systems. The type of magnet proposed here does not invoke spin-orbit coupling; in fact, it does not even invoke spin. Instead, the two symmetry-broken states are themselves electronic bands that live on the crystal, and they differ from each other in both momentum space and real space. For this reason, orbital magnetism does not need spin-orbit coupling to support hysteresis, and it can couple to a much wider variety of physical phenomena than spin magnetism can- indeed, anything that affects the electronic band structure or real space wave function is fair game. For this reason we can expect to encounter many of the phenomena we normally associate with spin-orbit coupling in orbital magnets that do not possess it. I would also like to talk briefly about magnetic moments.

It has already been said that magnetic moments in orbital magnets come from center-of-mass angular momentum of electrons, nft growing system which makes them in some ways simpler and less mysterious than magnetic moments derived from electron spin. However, I didn’t tell you how to compute the angular momentum of an electronic band, only that it can be done. It is a somewhat more involved process to do at any level of generality than I’m willing to attempt here- it is described briefly in a later chapter- but suffice to say that it depends on details of band structure and interaction effects, which themselves depend on electron density and, in two dimensional materials, ambient conditions like displacement field. For this reason we can expect the magnitude of the magnetic moment of the valley degree of freedom to be much more sensitive to variables we can control than the magnetic moment of the electron spin, which is almost always close to 1 µB. In particular, the magnetization of an orbital magnet can be vanishingly small, or it can increase far above the maximum possible magnetization of a spin ferromagnet of 1 µB per electron. Under a very limited and specific set of conditions we can precisely calculate the contribution of the orbital magnetic moment to the magnetization, and that will be discussed in detail later as well. Finally, I want to talk briefly about coercive fields. The more perceptive readers may have already noticed that we have broken the argument we used to understand magnetic inversion in spin magnets. The valley degree of freedom is a pair of electronic bands, and is thus bound to the two dimensional crystalline lattice- there is no sense in which we can continuously cant it into the plane while performing magnetic inversion. But of course, we have to expect that it is possible to apply a large magnetic field, couple to the magnetic moment of the valley µ, and eventually reach an energyµ · BC = EI at which magnetic inversion occurs. But what can we use for the Ising anisotropy energy EI ?

It turns out that this model survives in the sense that we can make up a constant for EI and use it to understand some basic features of the coercive fields of orbital magnets, but where EI comes from in these systems remains somewhat mysterious. It is likely that it represents the difference in energy between the valley polarized ground state and some minimal-energy path through the spin and valley degenerate subspace, involving hybridized or intervalley coherent states in the intermediate regime. But we don’t need to understand this aspect of the model to draw some useful insights from it, as we will see later.Real magnets are composed of constituent magnetic moments that can be modelled as infinitesimal circulating currents, or charges with finite angular momentum. It can be shown that the magnetic fields generated by the sum total of a uniform two dimensional distribution of these circulating currents- i.e., by a region of uniform magnetization- is precisely equivalent to the magnetic field generated by the current travelling around the edge of that two dimensional uniformly magnetized region through the Biot-Savart law. It turns out that this analogy is complete; it is also the case that a two dimensional region of uniform magnetization also experiences the same forces and torques in a magnetic field as an equivalent circulating current. The two pictures in fact are precisely equivalent. This is illustrated in Fig. 2.9. It is possible to prove this rigorously, but I will not do so here. One can say that in general, every phenomenon that produces a chiral current can be equivalently understood as a magnetization. All of the physical phenomena are preserved, although they need to be relabeled: Chiral edge currents are uniform magnetizations, and bulk gradients in magnetization are variations in bulk current current density.Condensed matter physicists love to say that particular phenomena are ‘quantum mechanical’ in nature. Of course this is a rather poorly-defined description of a phenomenon; all phenomena in condensed matter depend on quantum mechanics at some level. Sometimes this means that a phenomenon relies on the existence of a discrete spectrum of energy eigenstates. At other times it means that the phenomenon relies on the existence of the mysterious internal degree of freedom wave functions are known to have: the quantum phase. I hope it is clear that Berry curvature and all its associated phenomena are the latter kind of quantum mechanical effect. Berry curvature comes from the evolution of an electron’s quantum phase through the Brillouin zone of a crystal in momentum space. It impacts the kinematics of electrons for the same reason it impacts interferometry experiments on free electrons; the quantum phase has gauge freedom and is thus usually safely neglected, but relative quantum phase does not, so whenever coherent wave functions are being interfered with each other, scattered off each other, or made to match boundary conditions in a ‘standing wave,’ as in a crystal, we can expect the kinematics of electrons to be affected. We will shortly encounter a variety of surprising and fascinating consequences of the presence of this new property of a crystal. Berry curvature is not present in every crystal- in some crystals there exist symmetries that prevent it from arising- but it is very common, and many materials with which the reader is likely familiar have substantial Berry curvature, including transition metal magnets, many III-V semiconductors, nft hydroponic system and many elemental heavy metals. It is a property of bands in every number of dimensions, although the consequences of finite Berry curvature vary dramatically for systems with different numbers of dimensions. A plot of the Berry curvature in face-centered cubic iron is presented in the following reference: [84, 90]. We will not be discussing this material in any amount of detail,the only point I’d like you to take away from it is that Berry curvature is really quite common.

For reasons that have already been extensively discussed, we will focus on Berry curvature in two dimensional systems.Several chapters of this thesis focus on the properties of a particular class of magnetic insulator that can exist in two dimensional crystals. These materials share many of the same properties with the magnetic insulators described in Chapter 2. They can have finite magnetization at zero field, and this property is often accompanied by magnetic hysteresis. The spectrum of quantum statesavailable in the bulk of the crystal is gapped, and as a result they are bulk electrical and thermal insulators. They have magnetic domain walls that can move around in response to the application of an external magnetic field, or alternatively be pinned to structural disorder. And of course they emit magnetic fields which can be detected by magnetometers.In the absence of spin-orbit coupling, every band comes with a twofold degeneracy generated by the spin degree of freedom. Every band can be populated either by a spin up or a spin down electron, and as a result every Bloch state is really a twofold degenerate Bloch state. Adding spinorbit coupling may mix these states but does not break this twofold degeneracy. An important property of the Chern number is that Kramers’ pairs must have opposite-signed Chern numbers equal in magnitude. This is a direct consequence of similar restrictions on Berry curvature within bands. For a magnetic insulator the set of filled bands is a spontaneously broken symmetry, with the system’s conduction and valence bands hysteretically swapping two members of a Kramers’ pair in response to excursions in magnetic field. These two facts together imply that magnetic hysteresis loops of Chern magnets generally produce hysteresis in the total Chern number of the filled bands, precisely following hysteresis in the magnetization of the two dimensional crystal. This hysteresis loop switches the total Chern number of the filled bands between positive and negative integers of equal magnitude. These facts also imply that finite Chern numbers cannot exist in these kinds of systems without magnetism- if both members of a Kramers’ pair are occupied, the system will have a total Chern number of zero.As discussed previously, additional symmetries of the crystalline lattice itself can produce additional degeneracies that can support spontaneous symmetry breaking and magnetism. In most cases similar rules apply to the Chern numbers of these magnets. We will have a lot more to say about the Chern numbers associated with the valley degree of freedom in graphene. We have already mentioned the most important consequence of a finite net Chern number: the presence of chiral edge states in the gap of a magnetic insulator. We have not yet discussed the consequences of this state of affairs, and we will do so next. The quantum states available in the bulk of trivial materials, i.e. Bloch states, are delocalized over the entire crystal, and as a result, when Bloch states are present at the Fermi level, electronic transport between any two points in the crystal can occur through the rapid local occupation and depletion of these quantum states. The edge states that appear in Chern magnets support a lower-dimensional analog of this property: they are delocalized quantum states restricted to the edge of a two dimensional crystal, and as a result they support electronic transport along the edge of the crystal through the rapid local occupation and depletion of these semi-localized quantum states. They do not support electronic transport through the bulk, and edge states that are not simply connected cannot transmit electrons through the bulk region separating them. As mentioned, the Chern number is a signed integer, and we have not yet discussed the physical meaning of the sign of the Chern number. The edge states in Chern magnets are chiral, meaning that electrons populating a particular edge state can only propagate in one direction around the edge of a two-dimensional crystal. The sign of the Chern number determines the direction or chirality with which propagation of the electronic wave function around the crystal occurs. Electronic bands with opposite Chern numbers produce edge states with opposite chiralities. So in summary, a two dimensional crystal that is a Chern magnet supports electronic transport through chiral edge states that live on its boundaries. These systems remain bulk insulators, and edge states separated by the bulk cannot exchange electrons with each other. The sign of the Chern number is determined by the spin state that is occupied, and thus the chirality of the available edge state is hysteretically switchable, just like the magnetization of the two dimensional magnet.

Although health professionals and consumers often hear messaging on a single berry or nut, the potential benefits of increasing consumption of the broader category may be obscured or lost. This challenges the ability to maintain consistent messaging and align better with translatable dietary guidance. Future interventions that combine nuts and berries with one or more other foods within a food matrix at dietary achievable doses and in more diverse populations are warranted. To date, multi-omics technologies have provided valuable insights into exposure-disease relationships. Coupled with artificial intelligence, predictive modeling and continuous, personalized monitoring, these data-intensive outcomes can provide further insights about the health benefits associated with regular intake of nuts or berries. Use of highly personalized data collection devices will require secure data repositories. One of the challenges of similar foods being studied in differing formats and by various research groups is the utility of the data as a combined set. Differences in test materials and experimental designs make integration of data difficult. The proper curation of combined data, whether physiologic, metabolomic, or genomic, is critical to ensure that combined datasets provide synergy, statistical power, and enhanced usefulness. Novel Markers of Health Outcomes The cardiometabolic benefits from regular consumption of nuts or berries are widely reported and include improved vascular function, reduction of cardiovascular disease risk factors, improved insulin sensitivity, hydroponic growing and reduced risk of type 2 diabetes mellitus. Antioxidant and anti-inflammatory capacity and activity have also been noted. Metabolic outcomes may be context-specific and related to the physiologic state of the individual and host microbiome composition, among other factors.

Examples include findings of ellagitannin and ellagic acid rich foods resulting in differential responses in healthy individuals compared to those with prediabetes, who are dependent on gut microbial-derived metabolite profiles. Many factors contribute to inter individual variability in response to diet that can extend to context-specific aspects influencing the magnitude of health benefits and reinforces the importance for further research aimed at advancing discoveries in precision nutrition. Additional health outcomes related to nut or berry intake are outlined below.Adding nuts or berries to the daily diet may be advantageous for weight management for several physiological reasons. One is that these foods produce feelings of satiety, helping to reduce the desire to consume calorie-rich snacks that are low in vitamins, minerals, and fibers, ultimately improving body composition over time. A second possibility is due to urolithins, secondary metabolites produced from ellagitannins in nuts and berries. Urolithins increase the activation of the adenosine monophosphate-activated protein kinase pathway, resulting in anti-obesogenic properties in vitro and in animal models. Phosphorylation of AMPK may also decrease cholesterol synthesis and lipogenesis by down regulating 3-hydroxy-3-methylglutaryl coenzyme A reductase activity and sterol regulatory-element binding protein expression. In clinical studies exploring the relationship between food and body composition, the incorporation of nuts and berries into the diet was associated with weight loss or maintenance.Regular consumption of nuts or berries has been reported to support brain health and cognitive function, motor control, mood, and executive function at physiologically relevant intakes. Middle-aged and older adults experienced improvements in balance, gait, and memory, and children experienced higher executive function and positive affect after acute and regular intake of both strawberries and blueberrie.

These beneficial effects may be the result of direct effects on brain signaling or indirect effects through oxidant defense and anti-inflammatory properties of polyphenols and other bio-active compounds in nuts and berry foods. The gut-brain axis is an emerging area of research. Most studies are preclinical in nature using animal models but are suggestive of a significant role of gut microbial-derived ellagitannin metabolites on brain health and neuroprotection.The influence of nuts and berries on skin health and appearance is an emerging area of research. Regular intake of almonds, a good source of fatty acids and polyphenols, has been associated with a significant decrease in facial hyperpigmentation and wrinkle severity. A walnut protein hydrolysate administered to rats exposed to ultraviolet radiation significantly reduced skin photoaging and enhanced skin elasticity. Supplementation with ellagic acid, a compound found in many berries, prevented ultraviolet B -related inflammation and collagen degradation related to skin wrinkling and aging in a murine model. More human studies, using objective measures of skin wrinkles, skin elasticity and response to low-dose UVB radiation exposure are warranted. Monitoring skin responses to a UVB radiation challenge has been used as a marker of whole-body antioxidant status in response to almond consumption. The response to a UVB challenge has also been used to monitor oxidant defenses and changes in skin microbiome following the intake of pomegranate juice.Age-related macular degeneration is the third leading cause of vision loss worldwide . Anthocyanins, carotenoids, flavonoids, and vitamins C and E, found in many berries, have been shown to reduce risk of eye-related diseases. Goji berries, containing the highest amount of zeaxanthin of any known food, hold particular promise since this compound binds to receptors in the macula to offer protection from blue and ultraviolet light.

Regular supplementation with 28 g/d of goji berries for 3 mo increased macular pigment optical density, a biomarker for AMD, as well as the skin carotenoid index. Nuts may also be protective against AMD since they are a rich source of vitamin E and essential fatty acids. Regular intake of nuts has been associated with a reduced risk and slower progression of AMD in 2 epidemiological studies, thought to be due to the beneficial role of polyunsaturated fatty acids.Identification of new cultivars with traits desirable for growers, processors, and consumers is a continuous effort. As researchers continue to produce new varieties by both conventional and molecular-driven approaches, assessing these varieties for nutritional value is a challenge. A combination of broad targeted and untargeted metabolomic approaches, along with defined functional phenotyping could be used for rapid screening and defining of mechanistic pathways associated with health. However, consumer preferences for new cultivars are often driven by size and appearance of the berry or nut and flavor, rather than its nutritional value. This would further confirm the need to balance improvements to nutritional profiles with enhancement of consumer-driven traits, maintaining the marketable nature of the berries and nuts.Biomedical research, particularly for clinical studies, is expensive and resource intensive. Although the USDA competitive grants program offers funding for outstanding research projects, budget limitations favor animal or in vitro study proposals. Compelling pilot data is needed to be competitive for clinical studies funded by the USDA or NIH, so many researchers submit their initial ideas to commodity groups representing specific nuts or berries. Commodity groups represent farmers, processors, and distributors and have been instrumental in supporting fundamental and applied research focused on their specific berry or nut. The perception that studies funded by nut and berry commodity groups are inherently biased in favor of the test food is an issue sometimes raised by critics, journalists, and the general public. As in all nutrition research, ethical considerations regarding the structure of research questions, hypotheses, study design, outcome measures, interpretation of data, and conclusions must be rigorously considered. The food and beverage industries have played a key role in providing funds and supporting nutrition research on individual foods and beverages, including berries and nuts. Although this draws scrutiny regarding scientific integrity and data reporting, collaboration between academia and industry compared to exclusive corporate funding may help offset some of these concerns. For example, in multiple reported studies, matching funds were also provided by nonindustry sources, hydroponic grow kit including institutional and federal agencies. In other cases, while the food industry provided the test agents, key research personnel and staff were not supported by the same funding source. The academia-industry collaboration has also led to the formation of scientific advisory committees that evaluate and recommend proposals for funding, a peer review process that helps ensure rigorous study designs, data reporting, and dissemination of results. Human studies of sufficient statistical power are expensive, labor-intensive efforts requiring sophisticated and costly laboratory equipment and supplies. In order for research proposals to be competitive for funding from the USDA or NIH, pilot data is required, and for nuts and berries, the only realistic source of funding for these exploratory trials is from industry sources. Critics of industry support for nutrition research have yet to propose realistic alternatives for funding needed to generate initial data.

Further, ongoing industry funding of nuts and berries research has yielded important insights into the molecular and physiological understanding of mechanisms of action. Without industry support, provided in an ethical and transparent manner, advances in our understanding of the role of nuts and berries in a healthy dietary pattern would be limited. A risk-of-bias study of 5675 journal articles used in systematic reviews published between 1930 and 2015, representing a wide variety of nutrition topics, concluded that ROB domains started to significantly decrease after 1990, and particularly after 2000. Another study examined the incidence of favorable outcomes reported in studies funded by the food industry in the 10 most-cited nutrition and dietetics journals in 2018 . Of the 1461 articles included in the analysis, 196 reported industry support, with processed food and dietary supplement manufacturers supporting 68% of the studies included. Studies supported by any nut or berry commodity group were not considered due to an incidence lower than 3% of qualifying articles. Studies with food industry support reported favorable results in 56% of their articles, compared to 10% of articles with no industry involvement. The authors offer a number of suggestions to help minimize real or perceived bias, calling on research institutions to enforce strict, regularly updated, and transparent oversight of all research projects involving industry. Suggestions in support of research transparency and integrity have also been advanced from guidelines adapted from the International Life Sciences Institute North America. This served as the basis for the development of consensus guiding principles for public-private partnerships developed by a group of representatives from academia, scientific societies and organizations, industry scientists, and the USDA, NIH, US Centers for Disease Control, and the US Food and Drug Administration. These provisions include full disclosure of funding and confirmation of no direct industry involvement in the study design, data and statistical analyses, and interpretation of the results and only minimal, if any, involvement of industry coauthor, often given as a courtesy to acknowledge funding and logistical support by the investigators with no intellectual involvement by the study sponsor. This is in contrast to industry-initiated research, where the industry office or commodity group sets predetermined research objectives, provides intellectual collaboration, and often has input on the study design, interpretation of results, and decisions regarding publication. Although some critics may argue that repeated industry funding in support of research groups that report favorable results on a particular nut or berry shows a bias toward positive outcomes, other interpretations are also possible. First, few labs have the infrastructure, detailed methodology and analytical equipment, and trained personnel to conduct clinical studies in an efficient and timely manner. Industry funded studies conducted at major universities have layers of review and accountability within their organizations to guard against malfeasance, and while these layers may not focus directly on precise elements of research design and interpretation of results, faculty members at such institutions generally have a level of integrity and accountability, knowing that administrative review exists. Calls for industry-funded research are often broad in scope, which allows researchers to generate proposals, research questions, and hypotheses that do not have preconceived outcomes. A third consideration is that the nuts or berries under study may simply have sufficient bio-activity to produce favorable outcomes, independent of potential researcher bias.When I started my work at UCSB, it was not at all clear what form the scientific narrative of my graduate career would take. Instead, the primary ambition of our team was to construct a set of scanning nanoSQUID-on-tip microscopes for investigating two dimensional crystals; the scientific content of my PhD would then be composed entirely of targets of opportunity that presented themselves within this space once we had command of the technique. This happened, thankfully, and the resulting chain of experiments and discoveries will together be the subject of the rest of this thesis, but in the interest of avoiding historical anachronism I’d like to dedicate just a little time to discussing the nanoSQUID magnetometry technique in the context of the rest of the field. In doing so I hope I will provide some insight into why our plan seemed to us like a good idea at the time we chose to pursue it.

The predatory beetle is Azya orbigera, in the family Coccinelidae. Without a doubt, this observation can easily lead to the conclusion that the relatively rare scale insect is kept under control by the relatively common coccinellid beetle. But a closer look reveals a dramatic variability: Some bushes are very heavily laden with the scale insects, and some have none at all. There is another classical ecological notion that emerges in this system. Surrounding the tree in which an Azteca nest is located is a region containing coffee plants that are routinely patrolled by the Azteca ants that were described above. The ants harvest the sweet secretions the scale insects produce and, in turn, scare away or kill the natural enemies seeking to attack the scales , a well-known mutualism . Because the coffee bushes located near the shade trees that contain Azteca nests are where the scale insect is at leastpartially protected from the predatory beetle and various parasitoids, this area represents a refuge for the scale insect. It is therefore tempting to conclude that the ant itself is an indirect herbivore on the coffee . Although such is the case at a very local level , because of the complexities induced by the beetle predator, such is not the case at a larger scale. The ants effectively provide an area of high food availability for the beetle. Furthermore, the ants protecting the scale insects also, inadvertently, protect the beetle larvae from its own parasitoids, providing an effective refuge for the beetle as well . Predator–prey systems that contain a refuge are well studied in theoretical ecology , usually with an emphasis on their stabilizing properties. Expanding our view to a larger spatial scale, we deduce an evident contradiction from easily observable patterns. However, round planter pot the ants cannot provide protection if they have not yet created a foraging pattern at the site where the scales are located.

Therefore, the scale insect is unable to form a successful population unless under protection from the ants but is unable to attract the ant protection unless it builds up at least a small population. This pattern is well known in ecology as an Allee effect: An organism cannot form a successful population unless a critical number of individuals first become established, a mechanism generally understood to frequently be involved with the idea of critical transitions. In figure 4, we illustrate the system with a cartoon diagram approximately summarizing a simple population model . On one hand, as the dispersion of scales moves from aposition far removed from the refuge toward it, the adult beetle predators that have already located the scales will tend to move with it, until they encounter the protective ants , as is presented in figure 4a. A snapshot at some particular time therefore might look like the pattern in figure 4b. On the other hand, as the dispersion of scales moves from a position within the refuge away from it, the encounter with the beetle predators will not occur until the scales are far removed from the refuge, as is presented in figure 4c. A snapshot at some particular time therefore might look like the pattern in figure 4d. Finally, combining the pattern of figure 4b with that of figure 4d, we obtain the combined graph presented in figure 4e. Note that there is a broad region in which the scales could be very high while at the same time could be very low, effectively depending on where the scales are dispersing from, a structure typically referred to as hysteresis. Selecting 20 different shade trees containing Azteca nests, we examined all coffee bushes within 2 meters of the nest and a number of bushes further removed . We estimated the activity of Azteca ants on each of the bushes before counting the scale insects, to get an estimate of where the actual refuge was located . Note that the ant activity within 1 meter of the nest was high for almost all bushes surveyed , although positions greater than 1 meter awaty were highly variable, with some bushes having high activity levels and others having none. Further than 4 meters from the nest, ant activity was effectively nonexistant, and bushes further than about 4 meters from the nest were completely out of the refuge.

Plotting the number of bushes with a saturated density of scale insects and those with less than 10 scales, we obtain a pattern corresponding quite closely to what is expected from the hysteretic pattern predicted by the theoretical considerations . A further complication enters with a more complete natural history understanding of the beetles and their larvae. Although the adult beetle can fly and therefore forage over long distances for its food source, the larvae are largely restricted to terrestrial movement; that is, they are restricted in space . Female beetles therefore must choose their oviposition sites in such a way that the larvae will mature in an environment that contains a locally abundant food source. One major food source for predatory beetles is the general kinds of insects that are relatively sessile and suck the juices from plants, precisely the characteristics of the green coffee scale. They are easy targets for predators because they are normally slow moving and have few defenses. The problem for a potential predator is that they are very frequently defended by ants, precisely in areas where they are good sources of food for a beetle larva. Consequently, a whole group of beetles has evolved the habit of seeking out ants and ovipositing in areas where ants are abundant and defending the hemipterans. These myrmecophilous beetles must obviously have a strategy of protecting their larvae from the aggressive action of the ants and of enabling oviposition in sites of high ant activity . In the case of the beetleA. orbigera, the larva is covered with waxy filaments that tend to stick in the ants’ mandibles whenever they try to attack it . But more importantly, female beetles take advantage of an unusual behavioral pattern of the ants in order to oviposit where the scales are abundant . When a phorid fly attacks an ant, that ant exudes a pheromone that effectively says to the other ants in the general vicinity “Look out! Phorids attacking,” and the surrounding sisters all adopt a sort of catatonic posture, heads up, mandibles open, and stationary . Although the phorid is able to detect the alarm pheromones of the ant and is therefore attracted to it, it is unable to actually oviposit on the ant unless it sees some movement . Therefore, not only the ant under potential phorid attack, but also the sisters surrounding her assume this semistationary posture, a result of the very specific pheromone that alerts all ants in the vicinity that a phorid is lurking about. Remarkably, the adult female beetle is able to detect and react to this specific chemical, apparently using it as a cue that the time is propitious to enter into the ant-protected zone to sneak in some ovipositions . Therefore the phorid, in addition to being an important player in the Turing process that forms the basic spatial structure of the system, imposes a trait-mediated indirect interaction , in which the effect of the ant on the beetle is reduced. There is more to this story: first, from simple theoretical considerations and, second, round pot for plants from some evident natural history observations of the system. The theoretical considerations emerge from the knowledge that the refuge is dynamic. That is, past ecological theory has shown that when a prey species is able to retreat from its predator in a fixed refuge space, the basic instabilities of the predator–prey arrangement can be cancelled. But, in the present example, the refuge is effectively a pattern formed by another element in the system , the Azteca ant. And the Azteca ant is dynamic in the system, increasing its numbers in proportion to the resources it gains . If the scale insect population increases, there is more food for the ant, and it will therefore make more nests and expand its territory, creating even more refuge area for the scale insect. However, as the ant expands its area of influence , an increasing fraction of the area becomes refuge and, therefore, not available to the adult beetles . At the extreme, there must be some point at which the beetle is unable to find enough prey to continue its population expansion, because almost all of the area would now be a refuge for the scale insect.

Therefore, theoretically, the inevitable expansion of the refuge would lead to the eventual local extinction of the beetle predator. It could, of course, be the case that this expected instability of the system does not express itself for diverse reasons or perhaps for an excessively long time. However, purely theoretically, it represents a potential problem for persistence of this control agent. The theoretical problem is resolved by some very simple natural history observations. A fungal disease, known as the white halo fungus , almost inevitably becomes epizootic , especially when local population densities of the scale insect become large . The fungus can occasionally be found on isolated scale insects, but almost always is most evident when scale insects have built up a significant local population density, and such a buildup can only happen when they are under the protective custody of the Azteca ant.In the end, we see that the Azteca ant plays a key role in the control of this pest. On one hand it protects the scale insect from its adult beetle predator but only in the area of the refuge of the scale, which is defined by the ant itself . On the other hand, it permits the scale insect to build up such large local populations that the white halo fungus frequently becomes epizootic and drives the scale insect to local extinction. It is a curious inverse application of Gause’s traditional competitive exclusion principle, which might be expected to apply between the fungus and the beetle because they share this same food source. It seems unlikely, however, that the scale could be controlled completely by either the beetle or the fungal disease, except in the context of a spatial pattern generated by the Azteca ant . The massive expansion of the ants that might be expected theoretically never happens, partly because of the local effect of the fungal disease and the beetle larvae together reducing the scale insect population locally. Therefore, the dynamic nature of the ant cluster mosaic , always provides a small set of refuges that allows the beetle predator to be maintained throughout the coffee farm. From the point of view of the beetle, it is perhaps ironic that the beetle itself may be involved in the organization of the spatial pattern that is required for its own persistence . There is yet an additional complication. The fungal disease, once it arrives, multiplies extremely rapidly. But, as was noted above, it does not arrive in the first place unless the scale population is large and locally concentrated. Therefore, once the disease gets there, it increases to epidemic levels and wipes out the entire population of scale insects , creating a classical situation of boom and bust and hysteresis in space . Although it is a somewhat complicated argument that has been made in a couple of different ways elsewhere , the disease can clearly generate a locally chaotic dynamic trajectory. Its population dynamics over time are therefore expected to be both oscillatory and unpredictable. Furthermore, as the relevant population gets closer to the ant nest , the oscillations with its disease are expected to be more and more extreme. Eventually, they become so extreme that they transcend the boundaries of a critical value and both scales and disease completely disappear. Note that chaotic trajectories have boundaries , and the equilibrium point at zero is constrained within a basin of attraction. As the system gets closer to the refuge, the combination of a lower bound on the scale population and the rapidity with which it can increase when under protection from the ants combine to frequently produce chaotic oscillations, and the collision between the boundary of the chaos and the basin edge causes the population to crash, in a basin or boundary collision .

Conversely in 2021, total free anthocyanin concentrations were the highest in D4, C0, and D1 wines. Anthocyanin modifications due to shading treatments were more varied in 2021 compared to 2020. Overall, wines from D4 had the most 3-glucosides and 3-acetylated glucosides, while C0 and D5 consistently had less. Coumarylated anthocyanin concentrations were reduced in D3 and D5 wines compared to C0 wines. This was not consistent with the concentrations observed in 2020. Likewise, there was no statistically significant effect on the anthocyanin hydroxylation ratio in 2021 wines, while shading had an impact on anthocyanin hydroxylation in wines in 2020. Nine flavonol compounds were monitored in wines using HPLC . For all monitored flavonol compounds except myricetin-3- glucuronide, C0 wines consistently had the highest concentrations in 2020 compared to shaded wines, with D4 and D5 wines following in flavonol concentration. Subsequently, C0 also had the highest wine flavonol concentration when calculated as total flavonols in 2020. A similar trend occurred in 2021. C0 wines from 2021 also contained greater concentrations of each flavonol compared to shaded treatments, as well as total flavonol concentration.The wine aroma profiles from the 2020 and 2021 vintages were analyzed with and 29 volatile compounds were identified and categorized into their respective compound classes . The aromas profiles of wines depended highly on vintage, resulting in distinct aroma profiles. Generally, in 2020, total higher alcohols were unaffected by shade treatments, except for isoamyl alcohol and benzyl alcohol. Wines produced from shaded fruit had similar concentrations of isoamyl alcohol while the C0 had the lowest isoamyl alcohol concentration. Benzyl alcohol concentrations were reduced in D3 and D5 wines compared to C0, D1 and D4 wines. In 2021, black plastic plant pots shading treatments did not impact the concentration of higher alcohols in the resulting wines except for benzyl alcohol, which increased in 2021 D3 wines compared to all other treatments.

Acetate esters and fatty acid ethyl esters showed varied effects in wines due to shading in 2020. C0 and D5 had the lowest ethyl acetate concentrations compared to the other shade treatments. Likewise, isoamyl acetate was reduced in C0, D4 and D5 wines compared to D1 and D3 wines. Among the shade film treatments , ethyl hexanoate and ethyl octanoate concentrations were comparable between D1 and D5 wines and were greater than concentrations found in D3 wines. C0 and D5 wines were indistinguishable in ethyl butyrate, ethyl-2-methylbutyrate and ethyl valerate in 2020, with D1 and D3 wines having the highest concentrations of each these ester compounds. Isobutyric acid increased in D4 in 2020. In 2021, there were no significant impacts of shading on acetate esters, fatty acid ethyl esters, ethyl butyrate, ethyl-2-methylbutyrate or ethyl valerate. The effect of shade films on various terpenes and norisoprenoids was highly dependent on vintage conditions. Alpha-terpinene was highest in D5 wines but was significantly reduced in D1 and D3 wines in 2020. The D4 wines had the most cis-rose-oxide while C0 wines had the least. Linalool concentrations were reduced in C0, D4 and D5 wines. Among the shaded treatments, nerol concentrations were enhanced in D5 wines in 2020, while there was no effect of shading on nerol concentration in 2021. D5 did not differ from the C0 in nerol concentration in 2020. Farnesol in D3 was reduced in 2020 whereas farnesol concentrations were not affected in 2021 wines. Conversely, nerolidol was unaffected by shade films in 2020, whereas significant decreases in nerolidol concentrations were observed in D4 and D5 wines in 2021. It was observed that b-damascenone were elevated in 2020 in C0 wines, yet differences in b-damascenone concentrations were nonsignificant between shade film treatments. In 2021, only significant differences in b-damascenone concentrations were observed in wines, with C0 wines containing the most bdamascenone and D5 wines containing the least. b-ionone concentrations were not statistically significant between all treatments in 2020 and 2021.

To determine the effects of partial solar shading on wine chemistry, flavonoid composition and aromatic profiles of wines we conducted a principal components analysis for both vintages . In 2020, PCA indicated that PC1 accounted for 30.8%, and PC2 accounted for 22.1% of the total variance. The C0 treatments clustered together, separately from the partial solar shading treatments. The separation along PC1 was explained by the ratio of di- to tri-hydroxylated anthocyanins in wines, norisoprenoids and flavonols, as well as lower CI, alcohol content and TPI. The separation along PC2 was explained by TA, pH, terpenes and the percentage of polymeric anthocyanins in wine samples. In 2021, PCA indicated PC1 accounted for 29.9%, and PC2 accounted for 22.2% of the total variance. The C0 treatments again separated from shade film treatments, but less so than in 2020. The separation in PC1 was again explained by the ratio of di- to tri-hydroxylated anthocyanins, along with the total glucosides, total methylated anthocyanins and total anthocyanins. The separation of C0 was along PC2 and thus was associated with higher concentrations of flavonols, terpenes, norisoprenoids, and polymeric anthocyanins in wine. We analyzed the relationships further between the variables monitored with a correlation analysis in wines . In 2020, CI in wines had the strongest positive correlation with TPI and acids. Alcohol percentage and ketones were also positively correlated to TPI and acids, although less so than CI. Ketones also were very strongly positively correlated with higher alcohols, while higher alcohols were less strongly correlated to acids. Conversely, flavonols were strongly negatively correlated with acetate esters and other esters in wines. Norisporenoids and pH were less negatively correlated to acetate esters. Fatty acid ethyl esters particularly showed to be negatively correlated with TA. In 2021, the strongest positive correlations in wines were between total anthocyanins and total glucosides and total methylated anthocyanins .

Total coumarylated anthocyanins were significantly and positively correlated to total anthocyanins, methylated anthocyanins, and total glucosides. Strong negative correlations were found between hue and ester compounds including fatty acid ethyl esters and acetate esters. Alcohol percentage and norisoprenoids were also negatively correlated witheach other. A strong negative correlation existed between the ration of di- to tri-hydroxylated anthocyanins and total acetylated anthocyanins. Lastly, total higher alcohols and pH were strongly negatively correlated with each other.In hot viticulture regions, there is a desire to reduce excessive alcohol content in wines due to marketability and taxation concerns . Numerous studies have demonstrated that partial solar radiation exclusion is an effective method for reducing the amount of ethanol in wines by reducing TSS in shaded clusters . However, in the present study, C0 wines consistently had the lowest alcohol content and the lowest concentration of residual sugars in 2020 compared to shaded fruit, despite grapes at harvest having similar TSS values across the treatments . This may be due to the composition of sugars in the grape berry being affected by excessive cluster temperatures in C0 fruit. Sepulveda and Kliewer showed that heat stress at 40°C post-veraison decreases glucose and fructose in the grape berry. During heat wave events post-veraison, cluster temperatures in C0 reached a maximum temperature of 58°C, exceeding the point at which glucose and fructose content is altered . Additionally, the production of non-fermentable sugars such as arabinose, raffinose and xylose are known to be present in the grape berry . Genes involved in the production of these sugars have been shown to be upregulated under heat stress conditions in grapevine . While the grape berry is 95-99% glucose and fructose at harvest, these non-fermentable sugars are included in the metric of total soluble solids . As a result, while TSS was unaffected by shade films , the proportion of fermentable to nonfermentable sugars may be impacted, thus leading to 2020 C0 wines with reduced alcohol content. This difference in alcohol content between 2021 wines was not observed most likely due to the 2021 growing season being cooler with less GDDs than 2020 . While C0 wines in this study demonstrated lower alcohol content than shaded wines, black plastic garden pots previous literature corroborates cluster temperature reduction by partial solar radiation exclusion as an effective method to lessen sugar content in the grape berry and thus reduce alcohol content of wines . The effect of partial solar radiation exclusion in semi-arid climates on berry pH and TA is mixed. Previous work demonstrates partial solar radiation exclusion to reduce pH and increase TA in grape berries by reducing the thermal degradation of organic acids . However, in the present study, berry pH and TA at harvest were unaffected in either year by shade films . Nonetheless, there were apparent effects on wine pH and TA that were vintage dependent. In the present study, D3 wines had the lowest pH and highest TA, while C0 wines did not differ from the shade films D1, D4 or D5 in pH or TA in 2020. Differences observed in pH between the wines ultimately affect the colorimetric properties of these wines.

In 2021, D4 and D5 wines showed the highest pH values. It is understood that the pH of the wines can shift the anthocyanin equilibrium in wine solution between the flavylium and quinoidal base forms . In the present study, D4 wines had the highest pH and the highest CI. In many cases, when pH rises, CI will decline as anthocyanin equilibrium shifts away from the flavylium form towards the colorless quinoidal forms . However, this was not the case in the present study. Rather, improved color intensity at elevated wine pH could be attributed to co-pigmentation in the wine matrix. Co-pigmentation refers to non-covalent interactions between anthocyanins and cofactors such as flavonols, flavan-3-ols and proanthocyaninidins, that results in greater absorbance of the wine than color what would be indicated by anthocyanin content and pH conditions . In the hotter 2020 vintage, the total flavonols in grape berries were increased in D4 fruit compared to other treatments . This increased berry flavonol content was transmissible during winemaking, as D4 wines also showed the highest total flavonols with similar concentrations as C0 wines in 2020. TPI was also enhanced in D4 wines. As such, this increased the abundance of cofactors in the wine matrix. Thus, improved color intensity documented in D4 wines in both vintages could be due to the enhancement of absorbance from increased flavonol content by reducing thermal degradation in the vineyard . In the cooler 2021 growing season, shade films produced wines with less flavonols than C0, but greater anthocyanin content, thus leading to improved color intensity in D4 wines. The increase of phenolic cofactors in D4 wines not only enhanced color and hue, but also led to a higher percentage of polymeric anthocyanins when compared to other shade treatments. Phenolic and polyphenolic compounds from grape skins and seeds can form polymeric pigments in wine with anthocyanins . These polymeric anthocyanins are more stable than monomeric anthocyanins and help to stabilize wine color. This occurs as the proportion of monomeric anthocyanins decreases, leaving color to be maintained by polymeric anthocyanins . Across both vintages, the percentage of polymeric anthocyanins was maximized in D4 wines, indicating that these wines may have greater aging potential than wines from C0 and other shading treatments.In the present study, partial solar radiation exclusion modified the composition of anthocyanins in wine. Partial solar radiation exclusion resulted in increased anthocyanin glycosides in wine from shade film treatments except for D4 wines in 2020. In 2021, D4 consistently showed the lowest cluster temperatures post-veraison and as a result, demonstrated the highest concentration of glucosides in resultant wines. Excessive berry temperatures post-veraison in both vintages led to C0 fruit with reduced total anthocyanin content atharvest and this carried over into resultant wines . The reduction of near-infrared radiation by at least 15% produced a cluster temperature conducive to anthocyanin accumulation, as these compounds are susceptible to thermal degradation above 35°C . When comparing total anthocyanin and flavonol concentrations between 2020 and 2021, regardless of treatment, 2020 wines had anthocyanin and flavonol concentrations six to seven times less than those in 2021 wines. As flavonoids are susceptible to thermal degradation, this drastic difference in total flavonoid concentrations may be attributed to hotter vintage air temperatures in 2020 compared to 2021.

The filter papers containing ovisacs were pinned to the underside of the aforementioned infected source plants, which were then kept in a growth chamber until the first instar mealybug crawlers hatched. Approximately 72 h after hatching on the infected source plants, mealybugs were transferred to mature vines in the vineyard and to uninfected vines in the laboratory, for a 48 h inoculation access period. The timing of hatching led us to perform field inoculations on 18 July 2011, which coincided with the emergence of the new Ps. maritimus generation in Napa Valley. Twenty replicate source vines were propagated and used, with one to five recipient test vines inoculated per source plant in each inoculation experiment . All recipient test vines were treated with an insecticide upon completion of the inoculation access period.The experimental field inoculations were located in three rows of a vineyard block of V. vinifera cv. Cabernet Franc clone 01 grafted to 110R rootstock, obtained from Duarte Nursery and planted in Oakville, Napa Valley, CA in 1994. No vines in the experimental area were symptomatic for grapevine leafroll disease prior to our experimental inoculations. To confirm initial GLRaV-3-free status prior to inoculations, three petioles were collected from each experimental vine in July 2011 before inoculations were performed, for diagnostic testing . The block consisted of 8315 vines planted at 588 vines per hectare. Row spacing was 1.8 m, and vine spacing was 1.5 m, with a vertical shoot positioning trellis system and bilateral pruning. Row direction was northwest-southeast. Drip irrigation was provided using one 3.8 – L·h–1 emitter every 1.5 m. A minimum of five buffer vines were left untreated at each end of the rows. Experimental vines were spaced every third vine, and treatments were fully randomized. The three treatments included inoculations with no leaf cages, plastic grow pots inoculations using mesh leaf cages, and negative controls for which no experimental manipulation was performed. Each treatment included 30 replicate vines, for a total of 90 experimental vines.

The experiment comprised an area including 360 total vines, including the 90 experimental vines plus the spacer vines. The spacer vines were monitored periodically throughout the study for symptoms of grapevine leafroll disease. A survey for any signs of mealybugs was performed in October 2012. On 11 October 2012, 15 months postinoculation, a commercial testing service collected and analyzed material from some vines that were symptomatic for grapevine leafroll disease in the experiment and tested for a broad panel of known grape pathogens: GLRaV-1, GLRaV-2, GLRaV-2 strain Red Globe, GLRaV-3, GLRaV-4, GLRaV-4 strain 5, GLRaV-4 strain 6, GLRaV-4 strain 9, GLRaV-7, Syrah virus 1, Grapevine virus A, GVB, Grapevine virus D, Grapevine fanleaf virus, Xylella fastidiosa, GFkV, Rupestris stem pitting-associated virus, Rupestris stem pitting-associated virus strain Syrah, and Grapevine red blotch-associated virus. For inoculations, ten Ps. maritimus first instar insects were gently moved with a paintbrush from leaves of infected source plants onto the underside of one fully expanded mid-height leaf, located on a vertical cane growing from a middle spur on the south cordon of each grapevine. For the caged treatment, a cloth mesh cage was placed over the inoculated leaf and secured at the petiole using a twist tie. For the uncaged treatment, no covering was used on the inoculated vine. The experimental area was commercially treated with spirotetramat insecticide on 20 July 2011, after a 48 h inoculation access period. After inoculations the experimental area was managed following standard commercial practices.Three months after inoculations, the petiole of the inoculated leaf was collected on 14 October 2011 for diagnostic testing. In the instance where that petiole had fallen off the vine or could not be found, a petiole near the inoculated leaf was collected; inoculated petioles were missing from 9 of 60 inoculated vines.

Immediately following the first appearance of symptoms in 2012 and 2013, petioles were collected from each experimental vine and tested for presence of GLRaV-3. Petioles were collected from each experimental vine in September 2014, and tested for the presence of GLRaV-3, GVB, and GFkV. On each sampling date, three petioles were collected from each vine and pooled for diagnostic testing. If a vine had symptomatic leaves at the time of sample collection, symptomatic leaves were preferentially collected over asymptomatic leaves. During each growing season in 2011 through 2014 , experimental vines were surveyed regularly for visible leaf roll disease symptoms, beginning immediately after inoculations. On each survey date vines were marked as either asymptomatic or symptomatic, with surveys beginning in May and continuing through October. Shortly after symptoms first emerged in 2012, a detailed symptom survey of each symptomatic vine was performed to determine possible variation in disease symptom severity among vines and if there was an association between location of inoculation and initial appearance of symptoms within vines. For this survey, the position of each spur and the number of symptomatic and asymptomatic leaves on each spur were recorded. In Year Two, berry quality of all vines was measured three times during the weeks immediately preceding commercial harvest. Degrees Brix , pH, and titratable acidity were measured on 31 August, 21 September, and 3 October 2012, and harvest was 4 October 2012. In Year Three, berry quality of a randomly selected subset of 30 vines was measured on 28 August and 14 September, and harvest was 14 September 2013. The 30 vines were evenly divided between uninfected negative controls, uninfected and infected vines from the caged inoculation treatment, and uninfected and infected vines from the uncaged inoculated treatment. For berry quality analysis, on each sampling date approximately 200 berries were collected from each vine to minimize variance in measurements .

Within each grapevine, berries were collected from the top, middle, and bottom of each harvestable cluster of grapes and pooled for laboratory analysis. All samples were processed by Constellation Laboratories in California, USA. Total soluble solids as °Brix were measured using an Atago refractometer, and pH was measured using an Orion pH meter. Titratable acidity of the juice was measured via direct titration with 0.1 N NaOH, using phenolphthalein as an indicator.To test whether the newly infected field vines could be a source of GLRaV-3 one season after mealybug inoculations, a transmission experiment was performed in the laboratory from cuttings of these newly infected fieldvines. Ps. maritimus were not used because of the above mentioned difficulty in obtaining virus-free first in stars for transmission experiments. Instead we used first instars of Planococcus ficus, which are easily maintained in colonies and therefore can be ready for use in transmission studies at any time. Furthermore, Pl. ficus is a known vector of GLRaV-3 . Field cuttings were collected on 4 October 2012 and the stem bases were placed in flasks of water. First instar Pl. ficus were allowed a 24 h acquisition access period on the field cuttings, then transferred to the underside of a leaf of virus- free V. vinifera cv. Pinot noir recipient test vines; ten insects per recipient test vine were confined using a leaf cage for a 24 h inoculation access period. Following inoculations, plants were treated with a contact insecticide and then kept in a greenhouse for four months until petiole sample collection for diagnostic detection of GLRaV-3. For this experiment, a randomly selected subset of experimental field vines of each treatment was tested as a potential GLRaV-3 source. In total, nine symptomatic vines were tested; five from the caged inoculation treatment and four from the open inoculation treatment, and seven recipient test vines were inoculated in the laboratory from each symptomatic field vine. One of these 63 recipient test vines died before petiole sample collection to test for infection with GLRaV-3. Eleven total asymptomatic field vines were tested as a negative control: three from the caged inoculation treatment, three from the open inoculation treatment, big plastic pots and five uninoculated negative control vines. There were no symptomatic negative control vines in the field experiment. For each asymptomatic field vine, three replicate recipient test plants were inoculated, for a total of 33 recipient test vines from asymptomatic field vines. Additionally twenty uninoculated test vines were included with the recipient test vines in the experiment as negative controls, for a total of 116 experimental and control test plants.For each field and laboratory experiment, proportions of resulting successful inoculations from replicate source plants were compared using a Pearson chi-square test; proportions of successful inoculations did not differ, and therefore infected source plants were pooled for further analyses. A chi-square test revealed that caged and uncaged treatments did not differ in the field or laboratory studies, and data from caged and uncaged treatments were therefore pooled for all analyses. For each transmission experiment, proportions of recipient test plants that became infected with GLRaV-3 in each treatment were compared using chi-square tests. We calculated the estimated probability of transmission bya single insect following Swallow . The Swallow estimator can be used to estimate the probability that one insect will transmit a pathogen based on the number of insects used per recipient test plant, the number of recipient plants tested, and the proportion of recipient test plants that become infected. For the detailed symptom survey in Year Two on symptomatic vines only, we tested for a difference in the proportion of leaves that were symptomatic among spurs, using a generalized linear model with a Gaussian distribution; proportion data were arcsine-transformed prior to analysis to better meet the assumptions of the model. All above analyses were conducted using R Version 3.2.0. To assess the effects of GLRaV-3 infection on berry quality, °Brix, pH, and titratable acidity of symptomatic and asymptomatic vines were compared using a repeated measures ANOVA, using SPSS Version 23.

We found no effect of GVB infection on any of the variables measured in our field experiment; therefore the four vines that became infected with both GVB and GLRaV-3 were included with GLRaV-3-infected vines in our analyses.Our vineyard inoculations provide the first mealybugborne GLRaV-3 transmission study under realistic commercial vineyard conditions, providing corroboration that other laboratory transmission studies of GLRaV-3 are predictive of mealybug-borne transmission in commercial vineyards. In the field study, three months after vector inoculation, GLRaV-3 infections were detected in the petiole of the inoculated leaf of approximately two thirds of all vines that ultimately became infected, indicating that early localized infections in commercial vineyards can be detected using diagnostics well before the appearance of disease symptoms. Grapevine leafroll disease symptoms first appeared early in the year of the growing season following mealybug-mediated inoculations, and were present in all infected vines within a two week time frame. Appearance of disease symptoms was more consistent and narrow in timing than was diagnostic detection, which increased for two years following inoculations. Symptoms first appeared without localization to the point of inoculation, indicating that systemic infection had established before the first expression of symptoms. Furthermore, newly infected field vines were effective sources for mealybug-borne transmission one year after inoculation, providing additional evidence of rapid establishment of systemic infection. Berry quality was also affected one year after inoculations, indicating that infection had an effect on vine physiology as early as one growing season following inoculations. Only vines that were infected with GLRaV-3 also tested positive for GVB, indicating that GVB may have some dependence on GLRaV-3 during transmission or establishment in a new host. There were much fewer infections with GVB than with GLRaV-3. There was no evidence that GVB affected disease symptoms or progression compared with vines that were infected only with GLRaV-3. Results of laboratory-based transmission studies can differ from realistic field conditions , and there is considerable variation in estimates of transmission efficiency of GLRaV-3 among laboratory studies . The laboratory and field studies were consistent with each other in that there was no effect of caging the insect vectors on the recipient test vines on virus transmission. There was higher transmission efficiency based on our laboratory experiment compared with our field study. This may have been due in part to the controlled conditions indoors compared with outdoors, and the improved ability of first instar mealybugs to settle and feed on recipient test vines in the laboratory.

However, the present study of three human excised larynges with a larger range of applied adduction forces showed a large impact. In fact, for larynges L1 and L2, the results yielded a decrease in flow rate at equal subglottal pressure for increasing adduction level . This relationship is consistent with results presented by Alipour and colleagues, who performed experiments with excised animal larynges in a full larynx setup. The effect is caused by an increase in the glottal flow resistance computed as RB , and also RA . From an aerodynamic point of view, a high degree of adduction causes a high flow resistance and therefore a high energy transfer from the glottal flow to the vocal fold tissues. This yields a large transglottal pressure drop. As a consequence, high subglottal pressures can be generated at relatively low flow rates for L1 and L2 . Considering the limited lung volume for glottal flow generation, a high adduction level is desirable for effective and economic phonation. In contrast, the results for larynx L3 show the opposite behavior. On increasing the adduction level, the flow resistance RB tends to decrease, as shown in Fig. 4. Thus, at equal subglottal pressure, the glottal flow rate rises for larger adduction levels, as displayed in Fig. 3, which reduces the efficiency of the phonation process. Considering the glottal flow resistance RA based on Alipour et al., it also shows a slightly increasing tendency for rising adduction levels. However, as RA is defined as a derivative of the subglottal flow with respect to the flow rate, flow resistance generated by non-vibrating vocal folds in the low subglottal pressure range is not taken into account by RA. Therefore, garden pots square the authors suggest that RB might better describe the relationship between subglottal pressure and flow rate.

Although the adduction has a large impact on the flowpressure relationship, its influence on the fundamental frequency and the generated SPL is negligible and non-systematic. Similar findings for SPL were presented by Alipour et al. However, on performing a spectral analysis of the generated sound, they found an enhancement of the sound intensity of higher harmonics, especially the second harmonic. This spectral analysis was not possible with our acoustic data due to the high ambient noise level. Local parameters: Displacement and velocity values are in similar ranges to earlier ex-vivo and in-vivo canine hemilarynx studies, in-vivo human investigations, and synthetic models. The displacement ratios for L1 and L2 are up to 2.1, as seen in other studies. In contrast, for L3 , lateral components are much more pronounced. Similar to Boessenecker et al., an increase in subglottal pressure resulted in increased vocal fold velocities. In contrast to assumptions by Boessenecker et al., vocal fold adduction forces appear to influence the absolute values of vocal fold displacements and velocities, especially at high PS. For L1 and L2 the dynamical amplitudes increase, whereas for L3 the dynamic amplitudes decrease. This behavior of L3 might be related to increased tissue stiffness induced by the applied adduction forces, or just greater than normal overall stiffness of the vocal tissue in principle. For assessing mucosal wave propagation, phase delays in the range of 129 to 257 were found between the vocal fold edge and the most inferior suture l1 . Hence, the phase delays correspond to values of 16 /mm to 32 /mm. Similarly high lateral phase delays were found at 182 before. Even higher phase delays were reported for canines, see Table I in Titze et al. They computed phase delays between 24 /mm and 61 /mm where the phase delay was determined over a distance of 2 mm around the vocal fold edge in ex-vivo caninemodels. Also, for an in-vivo canine model, phase delay values between 25 /mm and 59 /mm were computed when converting their values to ours.

Additionally, phase delay values reported in our study coincide with values found for synthetic and computational multi-layer models of human vocal folds. In summary, our computed phase delay values are in the lower region of canines and match previous results for excised humans, synthetic, and computational models. However, the actual and exact positions and distances where these values were obtained were not given. EEFs: Several previous studies have shown that the primary power of the method of EEFs is derived from its data reduction capability . That is, by reducing complex vibratory motion to essential dynamics, fundamental laryngeal vibration patterns are often revealed. For example, previously the method of empirical functions demonstrated physical mechanisms for transferring energy from the glottal airflow to the vocal fold tissues, and for distinguishing aerodynamically and acoustically induced vocal fold vibrations. As displayed in Fig. 8, the trajectories of larynges L1 and L2 exhibit superposed vertical and lateral motion during vibration. Decomposing the oscillatory motion, the two largest EEFs of L1 and L2 describe a balanced vertical-lateral oscillation whose amplitudes increase with increasing adduction. This is accompanied by increased PS for equal airflow rates. Qualitatively, the characteristics of the increasing vertical-lateral motion are described by stronger prominence of the Fig. 8-shape of EEF1, defined by the Min and Max amplitude contours as also reported previously. For larynx L1, the vertical-lateral balanced vibration is a result of the superposition of EEF1 and EEF2 for all three adduction levels. An increasing adduction level for constant airflow results in increasing amplitudes in both the lateral and vertical directions, which is most pronounced in the higher range of subglottal pressure, as depicted in Fig. 6. Furthermore, the amplitude increase for L1 becomes apparent in both EEF1 and EEF2, Fig. 9. In contrast, for larynx L2, the balanced vertical-lateral motion is mainly included in EEF1 whereas EEF2 describes mainly the lateral vibratory motion. In this case, the stronger characteristic of a balanced vertical-lateral motion is generated by an energy transfer from EEF2 to EEF1 during the adduction increase. The reason for the differences in the EEFs of L1 and L2 might be the less periodic oscillation of L1, which results in a homogeneous energy distribution in EEF1 and EEF2. However, this aperiodicity in the case of L1 did not influence the efficiency of the fluid-structure interaction between the glottal flow and the vocal fold tissues because the flow-pressure relationships for L1 and L2 are systematically equivalent. In comparison with L1 and L2, EEF1 and EEF2 of larynx L3 exhibit primarily lateral vibrational components. This is most obvious when comparing the diagrams of vertical and lateral amplitudes in Fig. 6. For both of the EEFs, the amplitudes decrease at constant airflow with increasing adduction and decreasing PS, reflecting the decreasing energy transfer from the glottal flow to the vocal fold tissues. Hence the authors suggest that an effective energy transfer might be favored by a balanced vertical-lateral oscillation pattern which produces the distinctive convergent-divergent shape change in the glottal duct. Furthermore, this seems to be valid also in cases of slightly aperiodic but still balanced vertical-lateral oscillations of the vocal fold. In cases with an overemphasis of just a single direction of motion , square pots the energy transfer might be disturbed, resulting in a low effi- ciency of the fluid-structure interaction between the airflow and vocal fold tissue. As a result, the effort to sustain phonation may increase significantly.The application of topology in condensed matter physics has become widely embraced and has renewed our understanding of electronic band structures of materials. This framework enables the understanding of symmetry-protected features in reciprocal space found in topological insulators and semimetals. Combining nontrivial topology with time-reversal symmetry breaking can lead to large Berry curvatures that enable sizable macroscopic responses such as the anomalous Hall effect and the related anomalous Nernst effect with great potential applications ranging from thermoelectrics to spin-based storage. In fact, the key step to understanding the intrinsic origins of the AHE was in identifying the relationship between the AHE and the Berry curvature of the occupied electronic bands in a crystal. Antiperovskite transition-metal nitrides, especially Mn4N, have a diverse range of magnetic properties and emergent phases which make them interesting for both understanding fundamental physics and for spin-based applications.

Mn4N has a high N´eel temperature , small saturation magnetization, and high uniaxial magnetic anisotropy, making it particularly appealing for thermoelectric applications based on the ANE . Mn4N is also predicted to host a wealth of realspace magnetic topological features including spin textures, hedgehog-anti-hedgehog pairs and skyrmion tubes. These non-trivial spin structures were found to be mainly stabilized by the frustration induced by the magnetic exchange interaction between fourth-nearest neighbors. More recently, measurements of the AHE and ANE were reported for Mn4N, however, they do not agree on the origin of the AHE in Mn4N, and importantly, do not address how it can be enhanced through experimentally viable routes such as strain. In particular, the microscopic origins of the AHE can either be extrinsic or intrinsic . Recent experimental work studied transport signatures of the AHE in epitaxial Mn4N films of different thickness, and concluded that the AHE has competing contributions from skew scattering, side jump, and intrinsic mechanisms. According to the conventional scaling law ρAHE ∝ ρ γ xx, where ρAHE is anomalous Hall resistivity and ρ γ xx is longitudinal resistivity, γ was found to be larger than 2 for all Mn4N films, indicating that the side jump and intrinsic mechanisms are dominant in these films. On the other hand, Isogami et al. report a dominant intrinsic contribution to AHE and ANE based on transport and ab initio calculations. Surprisingly, we are not aware of a comprehensive study of the electronic origins of the AHE and ANE from the perspective of first-principles based calculations, or nor a discussion of how these properties can be enhanced. Moreover, the range of competing, frustrated magnetic states in ferrimagnetic Mn4N motivates us to explore the range of tunability of the topological responses in this system. The antiperovskite structure of Mn4N can be viewed as Mn3MnN with Mn ions on three inequivalent cation sublattices and N taking the anion site . These three different Mn sublattices have unequal magnetic moments leading to its ferrimagnetic nature and small saturation magnetization. Neutron diffraction experiments identified two different magnetic configurations in Mn4N. In the “Type-A” structure, the spins of Mn II and Mn III are aligned parallel to each other but antiparallel to those of Mn I, whereas in the “Type-B” structure, the spins of Mn I and Mn II are aligned parallel to each other while being antiparallel to the spins of Mn III. Previous theoretical works found the Type-B to be the ground state, though both have been observed in experiment . All first-principles calculations were carried out within the framework of Density Functional Theory as implemented in Vienna Ab-Initio Software Package using the projector augmented-wave potentials.Osmotic Demyelination Syndrome , also known as Central Pontine Myelinolysis, is a serious—and often irreversible—complication of rapid correction of serum sodium. Patients with cirrhosis experience labile serum sodium levels related to portal hypertension and diuretic use, often with rapid correction—intentional or unintentional—during hospitalizations. Studies on ODS in cirrhosis have focused on patients undergoing liver transplantation. These findings may not generalize to the cirrhosis population as a whole, yet the risk of ODS for inpatients with cirrhosis outside of the context of liver transplantation is not well-characterized. Such information is critical to inform management of severe hyponatremia in patients with cirrhosis, a common clinical scenario. Therefore, we aimed to characterize the prevalence and risk factors of ODS in this population.We performed a cross-sectional study to determine overall prevalence of ODS in hospitalized patients with cirrhosis not receiving liver transplants, to compare those with and without ODS, and to determine whether cirrhosis and general illness severity correlated with prevalence of ODS. We used data from the Healthcare Cost and Utilization Project National Inpatient Sample , a nationally representative dataset of a stratified sample of US community hospitals, from years 2009-2013. This study was exempt from the need for informed consent. It was approved by the University of California, San Francisco institutional review board. To develop our study sample, we selected all patients 18 years or older with any discharge diagnosis of cirrhosis using International Classification of Diseases, Ninth Revision codes for cirrhosis, which have been previously validated for identifying inpatients with cirrhosis with a positive predictive power of 90% and a negative predictive value of 87%, as well as validated for identifying individual signs and severity of cirrhotic decompensation. 

Results from the pseudo mixed model indicated the interaction effect was more important than the treatment effect. Thus, “alcohol hotness” will not be included in any further discussion of significant attributes for BA wines. The significant difference in malic acid content in the wines among treatments appears to have had little impact on sensory evaluation given that there was no significant difference in the perception of sourness in the wines. From the PCA generated from BA descriptive analysis results , the control and sort wines appear to be correlated more closely with “alcohol” . Wines made from these treatments were higher in ethanol content, which may explain this trend. However, the small number of significant attributes indicate that BA wines made by different treatments were very similar in sensory properties.Analysis of wine color revealed that there were perceivable differences among treatments for all three varieties . For BA the reject treatments were rated lighter in color compared to the control and sort treatments, whereas a similar trend was observed in the CS treatments. This was expected because berries with less color were removed by the optical sorter and included in the reject fermentations. This agrees with results from Table 6; the rejected treatments were significantly lower in anthocyanin content for BA and CS, which can explain the difference in color perception. For GN wines, the control treatment was perceived to be slightly darker than the sort and reject treatments. Although fermentations were prepared to have similar solid-to-juice ratios in the must among treatments, grow bag for tomato it is possible that variations between replicates may have resulted in the control treatments being slightly more concentrated, which could provide an explanation for this result.

It can be concluded that optical sorting was generally successful in removing berries with less color; however, this did not lead to a large difference in the final color of the wines between the sort and control treatments.Multiple Factor Analysis was performed for each variety using all sensory attributes and only volatile compounds that differed significantly among treatments . This was done to observe the association, if any, of the significant volatile compounds and sensory attributes. For GN wines, the only significant attribute was “SO2”. From Figure 7, isobutanol, which can impart a solvent like aroma in wine, is grouped closely with “SO2”. It is possible that wines with a higher isobutanol concentration were perceived to be higher in “SO2” aroma. For BA wines, there does not appear to be a trend among sensory attributes and volatile compounds . For CS wines, “apple” is grouped closely with ethyl esters , which provides evidence that this may have caused the increased perception of this attribute in the control and sort treatments .Overall, optical sorting had minimal impact on the sensory properties of the three varieties tested. It is possible that the chemical differences noted earlier were too small to result in consistent differences by descriptive analysis. Even though the wines made from reject material contained significantly higher concentrations of higher alcohols, it did not result in a difference in sensory perception. Higher alcohols have a relatively high sensory threshold . It is possible that the concentration of these compounds in the reject wines was below the sensory threshold.The purpose of this study was to determine what effects, if any, optical berry sorting had on wine made from different red grape varieties, and to investigate the potential to use optical sorters to sort for different ripeness levels using color as a main criterion.

Given the observed differences in Brix and final ethanol content, optical sorting seemed to be successful in removing underripe berries for CS and possibly for BA; however, this did not result in a significant difference in the final ethanol content between the sort and control treatments. The removal of underripe berries was also evident by the difference in color among treatments. For BA, the rejected treatments were significantly lighter in color; however, the color of the sort and control treatments was very similar, whereas a similar trend was observed in the CS treatments. Wines made from GN generally did not follow these trends; possibly because sorting parameters were too aggressive for this cultivar, resulting in a high percent rejection of optimal berries. This may have minimized potential differences between reject wine with the other treatments. Another possibility is that color differences in the GN fruit did not correspond to differences in sugar content. From these results, it may be concluded that, when using color as a criterion, optical sorting based on ripeness level was successful but may be dependent on variety and fruit variability. Additionally, the impact on the resulting wine is likely dependent on the initial variability in grape ripeness. The optical sorter was successful in removing MOG. This result was reflected in the phenolic analyses; reject treatments were generally higher in total phenolics and tannin, most likely due to the greater proportion of MOG included in the must. The decrease in anthocyanins is likely due to the higher percentage of green, underripe berries in the reject treatment musts. A study that made wine with the addition of MOG found that this addition significantly increased the phenolic and tannin content in the resulting wines. Despite the differences observed in the phenolic composition of the reject wines, the control and sort treatments were very similar for all three varieties. This is in contrast with some previous studies that have found wine made from optical sorted fruit had significantly different levels of phenolics.

One study found that optical sorting led to wines with higher levels of total phenolics. It should be mentioned that the researchers here did whole cluster pressing for their control wines , whereas the sorted wines were destemmed. It is possible that higher levels of phenolics were extracted due to the damage caused by the destemming process on the seeds and skins. Another study found that wine made from optically sorted grapes that were machine harvested generally had lower levels of phenolics; levels that were similar to the same wines made from a handpick treatment. Given that the rejects were, in general, significantly higher in total phenolics and tannin than the control and sort treatments, it can be suggested that optical sorting has the potential to decrease the phenolic content in wine; however, there was not enough MOG to show a large impact in the current study. Optical sorting likely has a greater impact on mechanically harvest fruit due to generally higher levels of MOG observed from this harvest method. Some differences were found among treatments in the aroma profiles of the wines. Few compounds differed significantly between sort and control treatment and, in general, the reject treatments had greater concentrations of higher alcohols and control and sort treatments had greater concentrations of ethyl esters. The higher ethanol content of the sort and control treatments as well as their lower pH can lead to a higher production of esters. In general, reject treatments contained significantly more suspended solids then the control and sort treatments for all varieties studied. Research has shown that high levels of suspended solids during fermentation can lead to greater production of higher alcohols. Descriptive analysis indicated only one significantly different attribute among GN treatments and only two significantly different attributes among BA treatments. BA control and sort wines were associated with the “alcohol” descriptor which correlated with the higher ethanol levels in these treatments compared to the reject treatment. Similarly, there were only three significant attributes among the CS treatments. “Alcohol hotness” related to ethanol content as previously described. The control and sort treatments were also rated significantly higher in “apple” and “sweet” aromas compared to the reject treatment. Some studies have shown that higher levels of ethanol can increase the perception of sweetness in a wine. However, as King et al. noted, grow bag for blueberry plants there is disagreement in this regard, as other studies have shown that ethanol content can either decrease or have no effect on the perception of sweetness. Thus, this may not be a sufficient explanation as to why the control and sort wines were rated significantly higher in sweetness. Perhaps the higher concentration of total phenolics and tannin in reject wines could explain the difference given that phenolics in wine contribute to bitterness and astringency. From the PCA in Figure 6, it can be noted that “bitter” and “drying” are more associated with reject wines. Although these attributes are not significantly different among the treatments there appears to be a trend which could impact the perception of sweetness.

One study found that increasing bitterness in coffee decreased the perception of sweetness. It is possible that reject wines were rated lower in “sweet” due to the higher concentration of phenolic compounds thus decreasing the perception of sweetness. The higher perception of sweetness in the control and sort wines may also be attributed to the higher intensity of the “apple” aroma, which the judges could have associated with a sweet taste. One study found that retronasal aromaperception of fruity compounds increased with an increasing level of sweetness in a model wine solution. The authors also noted several other studies which found that aroma compounds can enhance the perception of sweetness in different foods and beverages. Another study found that samples described as “fruity” were also often associated with a “sweet” aroma. This provides further evidence that the judges in the current study may have associated these attributes together. The overall sensory differences were minimal, and the wines were determined to be similar. The results from this study largely agree with results from previous studies investigating the effects of optical sorters. It is possible that there was not enough variation in the starting material of the current study for optical sorting to have a large impact. Optical sorters may be used to greater effect during vintages with inconsistent ripening, issues with raisining, or large amounts of berry damage, possibly caused by either birds and/or fungal infections. Future research should investigate the impact of optical sorters in these scenarios.Grapevine has indeterminate growth habits compared to other perennial fruit crops. Latent growth of the dormant grapevine bud may be induced by favorable conditions with little to no dormancy period required . Therefore, semi-tropical regions may raise two crops a year, and in fact, it is not uncommon for the latent bud to produce some fruit when correlative inhibition is removed in temperate regions. Furthermore, the grape berry does not have the same fruit abscission mechanism as apple or peach revealed under carbon starvation. It is therefore possible for grapevine canopy size and crop level manipulations leading to a wider range of source or sink limiting conditions within a growing season. The crop level of a perennial crop is initially determined by organogenesis at the basal buds. The number and size of the flower primordia is associated with number of clusters and berries per cluster through the formation flowers and fruit set . However, fruit set is largely variable among years, weather, location, and cultivars . Poor fruit set may be a limitation to crop yield, although weather is often considered to be the leading cause. However, the mechanism of poor fruit set is not fully understood. Carbon supply or mineral nutrition are related to the amount of fruit set , which is an acclimation mechanism to unfavorable conditions. Ultimately, yield of grapevine is affected by berry size, and within the berry, pulp enlargement is the largest contributor to yield gain rather than skin or seed biomass . Conversely, vegetative growth is far less influenced by latent bud formation, as competition amongst growing buds tends to buffer the impact of growing shoot tips on its length and total leaf area . This is likely due to the great limiting effect of nitrogen among other nutrients or hydraulic pressure . The ratio between leaf area and fruit mass is closely related to the amount of carbohydrates accumulated in the must . Thus, an excessive crop level or less than ideal canopy size may result in over cropping and may lead to delayed ripening . Conversely, in under cropping, where there is excessive vigor or reduced crop level, this is not necessarily deleterious for speed of ripening . However, it may be a wasteful management of resources if there is not a trade-off with farm-gate prices.