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Ocean alkalinity enhancement (OAE), one of the marine carbon dioxide removal strategies, is gaining recognition in its ability to mitigate climate change and ocean acidification (OA). OAE is based on adding alkalinity to open-ocean and coastal marine systems through a variety of different approaches, which raises carbonate chemistry parameters (such as pH, total alkalinity, aragonite saturation state) and enhances the uptake of carbon dioxide (CO2) from the atmosphere. There are large uncertainties in both short- and long-term outcomes related to potential environmental impacts, which would ultimately have an influence on the social license and success of OAE as a climate strategy. This paper represents a synthesis effort, leveraging on the OA studies and published data, observed patterns, and generalizable responses. Our assessment framework was developed to predict the sensitivity of marine calcifiers to OAE by using data originating from OA studies. The synthesis was done using raw experimental OA data based on 68 collected studies, covering 84 unique species and capturing the responses of 11 biological groups (calcifying algae, corals, dinoflagellates, mollusks, gastropods, pteropods, coccolithophores, annelids, crustacean, echinoderms, and foraminifera), using regression analyses to predict biological responses to NaOH or Na2CO3 addition and their respective thresholds. Predicted responses were categorized into six different categories (linear positive and negative, threshold positive and negative, parabolic and neutral) to delineate responses per species. The results show that 34.4 % of responses are predicted to be positive (N=33), 26.0 % negative (N=25), and 39.2 % (N=38) neutral upon alkalinity addition. For the negatively impacted species, biological thresholds, which were based on 50 % reduction of calcification rate, were in the range of 50 to 500 µmol kg−1 NaOH addition. Thus, we emphasize the importance of including much lower additions of alkalinity in experimental trials to realistically evaluate in situ biological responses. However, it is important to note our results do not consider equilibration with the atmosphere and are thus only applicable to short-term and near-field application. The primary goal of the research was to provide an assessment of biological rates and thresholds predicted under NaOH / Na2CO3 addition that can serve as a tool for delineating OAE risks. This will help guide and prioritize future OAE biological research and regional monitoring efforts and will also aid in communicating risks to stakeholders. This is important given the fact that at least some of the current OAE approaches do not always assure safe biological space. With 60 % of responses being non-neutral, a precautionary approach for OAE implementation is warranted, identifying the conditions where potential negative ecological outcomes could happen, which is key for scaling up and avoiding ecological risks.

A protocol for detecting the potential occurrence of spontaneous combustion (SC) in stored cottonseeds and peanuts using a micro-incubator is described. The protocol indicates how to quantify CO2 production rates and final CO2 levels in wet versus dry cottonseed and peanut samples, which can provide crucial data for the early detection of SC risk in storage facilities. The experimental design utilizes a micro-incubator to simulate conditions found in large bulk crop storage. Parameters monitored include CO2 concentration, temperature, and relative humidity. The protocol includes preparation methods, experimental procedures for both control (dry) and wet seed tests, and test termination criteria that allow for safe experimentation of likely pathogenic fungi. The protocol has three replicates for wet and dry conditions. The protocol is intended to facilitate future experimental studies and ultimately contribute to the development of a consistently reliable early warning fire detection system for SC in cottonseed and peanut warehouse facilities. A consistently reliable fire detection system would address a critical need in the cotton and peanut industry for improved fire risk management and insurability of storage facilities.

The removal of plastic contamination from cotton lint is a critical issue for the U.S. cotton industry. One primary source of this contamination is the plastic wrap used on cotton modules by John Deere round module harvesters. Despite rigorous efforts by cotton ginning personnel to eliminate plastic during module unwrapping, fragments still enter the gin’s processing system. To address this, we developed a machine-vision detection and removal system using low-cost color cameras to identify and expel plastic from the gin-stand feeder apron, preventing contamination. However, the system, comprising 30–50 ARM computers running Linux, poses significant challenges in terms of calibration and tuning, requiring extensive technical knowledge. This research aims to transform the system into a plug-and-play appliance by incorporating an auto-calibration algorithm that dynamically tracks cotton colors and excludes plastic images to maintain calibration integrity. We present the image dataset that was used to validate the design, consisting of several key AI Vision-Transformer image classifiers that form the heart of the auto-calibration algorithm, which is expected to reduce setup and operational overhead significantly. The auto-calibration feature will minimize the need for skilled personnel, facilitating the broader adoption of the plastic removal system in the cotton ginning industry.

Plastic contamination in cotton lint poses significant challenges to the U.S. cotton industry, with plastic wrap from John Deere round module harvesters being a primary contaminant. Despite efforts to manually remove this plastic during module unwrapping, some inevitably enters the cotton gin’s processing system. To address this, a machine-vision detection and removal system has been developed. This system uses inexpensive color cameras to identify plastic on the gin stand feeder apron, triggering a mechanism that expels the plastic from the cotton stream. However, the system, composed of 30–50 Linux-based ARM computers, requires substantial effort for calibration and tuning and presents a technological barrier for typical cotton gin workers. This research aims to transition the system to a more user-friendly, plug-and-play model by implementing an auto-calibration function. The proposed function dynamically tracks cotton colors while excluding plastic images that could hinder performance. A critical component of this auto-calibration algorithm is the hand intrusion detector, or “HID”, which is discussed in this paper. In the normal operation of a cotton gin, the gin personnel periodically have to clear the machine, which entails running a stick or their arm/hand under the detection cameras. This results in the system capturing a false positive, which interferes with the ability of auto-calibration algorithms to function correctly. Hence, there is a critical need for an HID to remove these false positives from the record. The anticipated benefits of the auto-calibration function include reduced setup and maintenance overhead, less reliance on skilled personnel, and enhanced adoption of the plastic removal system within the cotton ginning industry.

Plastic contamination in marketable cotton bales, predominantly from plastic wraps used in John Deere round module harvesters, poses a significant challenge to the U.S. cotton industry. Despite rigorous manual efforts, the intrusion of plastic into the cotton gin’s processing system persists. We have developed a machine-vision detection and removal system aimed at mitigating this problem. This system employs inexpensive color cameras to detect plastic on the gin-stand feeder apron and subsequently removes it, reducing contamination. This system, built around low-cost ARM computers running Linux, comprises 30–50 machines and requires considerable effort to calibrate and tune. Moreover, its operation represents a technological challenge to typical cotton gin workers. This research presents a solution to this calibration operational hurdle by introducing an auto-calibration algorithm that has potential to simplify the system into a plug-and-play device. The auto-calibration system is designed to dynamically track the cotton color and utilizes frequency statistics to avoid plastic images that could compromise the system’s performance if incorporated into the auto-calibration process. We detail the design of the auto-calibration algorithm, which is expected to significantly reduce the setup overhead and facilitate the system’s continuous use. This innovation minimizes the need for skilled personnel and, therefore, is expected to expedite the system’s adoption across the cotton ginning industry.

Abstract Background The strength of cotton fiber has been extensively studied and significantly improved through selective breeding, but fiber elongation has largely been ignored, even though elongation contributes to determining the energy needed to break fibers. Recent developments to calibrate the high volume instrument (HVI) for elongation has renewed interest in elongation. However, it is not understood how best to utilize yet another fiber property which has the potential to add to the complexity of fiber selection. To explore a practical approach to applying elongation, cotton samples were tested using single fiber methods, the Stelometer, and the HVI. Comparison of strength, elongation, and combined properties such as modulus were explored. Results HVI testing was shown to be sensitive enough to characterize elongation differences but unlike single fiber testing it was unable to capture within-sample variation. Fiber bundle testing, like Stelometer and HVI was shown to reduce bias due to fiber selection. Conclusion The use of secant modulus, an intrinsic material property, allowed for one value to represent both strength and elongation. Secant modulus was shown to contain more useful information than either elongation or work-to-break. Work-to-break was shown to be more influenced by a specific value of breaking force or elongation rather than the intrinsic behavior of the sample being tested. Exploring the influence of genetics and environment on elongation, and its interaction with other fiber properties, requires additional work. Secant modulus, by combining strength and elongation into one value, shows the potential to incorporate elongation values into fiber characterization without increasing the complexity of current fiber selection processes.

Plastic contamination in US lint bales has increased with the adoption of new cotton harvesters that form cylindrical or round modules on the machine. It is of significant interest to the US cotton industry to reduce this contamination to preserve grower profitability and the reputation of the US as a reliable source of clean cotton fiber. The objective of this work is to describe the design and operation of a system for use on cotton gin module feeders that provides monitoring of plastic accumulation on the dispersing cylinders and video data to help document the module wrap condition and unloading/unwrapping procedures that may have caused the potential contamination event on the dispersing cylinders. In 2020, an integrated plastic contamination monitoring system was installed on module feeders at two commercial cotton gins in Texas. The system is comprised of sub-systems that provide images of plastic accumulation on the dispersing cylinders, a log of the processing sequence for round modules, video data of the unloading/unwrapping process for each module and a software program that integrates the data from the two sub-systems. The system was developed to operate on one computer, store the data in a common location, and simplify the process of extracting module specific data for a given event when plastic accumulates on the module feeder dispersing cylinders. The data provided by the system can be useful to manufacturers in comparing performance among module wrap products as well as to gin managers in training gin employees on module handling procedures to mitigate plastic contamination and improve worker safety.

The removal of plastic contamination from cotton lint is an issue of top priority to the U.S. cotton industry. One of the main sources of plastic contamination showing up in marketable cotton bales is plastic used to wrap cotton modules produced by John Deere round module harvesters. Despite diligent efforts by cotton ginning personnel to remove all plastic encountered during module unwrapping, plastic still finds a way into the cotton gin’s processing system. To help mitigate plastic contamination at the gin, a machine-vision detection and removal system was developed that utilizes low-cost color cameras to see plastic coming down the gin-stand feeder apron, which upon detection, blows plastic out of the cotton stream to prevent contamination. This paper presents the software design of this inspection and removal system. The system was tested throughout the entire 2019 cotton ginning season at two commercial cotton gins and at one gin in the 2018 ginning season. The focus of this report is to describe the software design and discuss relevant issues that influenced the design of the software.

The removal of plastic contamination in cotton lint is an issue of top priority to the U.S. cotton industry. One of the main sources of plastic contamination showing up in marketable cotton bales, at the U.S. Department of Agriculture’s classing office, is plastic from the module wrap used to wrap cotton modules produced by the new John Deere round module harvesters. Despite diligent efforts by cotton ginning personnel to remove all plastic encountered during unwrapping of the seed cotton modules, plastic still finds a way into the cotton gin’s processing system. To help mitigate plastic contamination at the gin; an inspection system was developed that utilized low-cost color cameras to see plastic on the module feeder’s dispersing cylinders, that are normally hidden from view by the incoming feed of cotton modules. This technical note presents the design of an automated intelligent machine-vision guided cotton module-feeder inspection system. The system includes a machine-learning program that automatically detects plastic contamination in order to alert the cotton gin personnel as to the presence of plastic contamination on the module feeder’s dispersing cylinders. The system was tested throughout the entire 2019 cotton ginning season at two commercial cotton gins and at one gin in the 2018 ginning season. This note describes the over-all system and mechanical design and provides an over-view and coverage of key relevant issues. Included as an attachment to this technical note are all the mechanical engineering design files as well as the bill-of-materials part source list. A discussion of the observational impact the system had on reduction of plastic contamination is also addressed.

The removal of plastic contamination in cotton lint is an issue of top priority for the U.S. cotton industry. One of the main sources of plastic contamination appearing in marketable cotton bales is plastic used to wrap cotton modules on cotton harvesters. To help mitigate plastic contamination at the gin, automatic inspection systems are needed to detect and control removal systems. Due to significant cost constraints in the U.S. cotton ginning industry, the use of low-cost color cameras for detection of plastic contamination has been successfully adopted. However, some plastics of similar color to background are difficult to detect when utilizing traditional machine learning algorithms. Hence, current detection/removal system designs are not able to remove all plastics and there is still a need for better detection methods. Recent advances in deep learning convolutional neural networks (CNNs) show promise for enabling the use of low-cost color cameras for detection of objects of interest when placed against a background of similar color. They do this by mimicking the human visual detection system, focusing on differences in texture rather than color as the primary detection paradigm. The key to leveraging the CNNs is the development of extensive image datasets required for training. One of the impediments to this methodology is the need for large image datasets where each image must be annotated with bounding boxes that surround each object of interest. As this requirement is labor-intensive, there is significant value in these image datasets. This report details the included image dataset as well as the system design used to collect the images. For acquisition of the image dataset, a prototype detection system was developed and deployed into a commercial cotton gin where images were collected for the duration of the 2018–2019 ginning season. A discussion of the observational impact that the system had on reduction of plastic contamination at the commercial gin, utilizing traditional color-based machine learning algorithms, is also included.

Physical activity rates have prevailed as a worldwide health concern. The WHO’s 'Global Action Plan on Physical Activity 2018–2030' articulated the need to test effective communication strategies that deliver information to enhance physical activity behaviors. The Comprehensive Messaging Strategy for Sustained Behavior Change (CMSSBC) is a promising approach that advocates tailoring messages to one’s stage of change and framing them intrinsically rather than extrinsically. This study examined adults’ decisions to read and engage with physical activity messages aligned with CMSSBC, considering the role of the message frame, stage of change of the message, stage of change of the participant, as well as the participants goal orientation. Participants ('nmale' = 91; 'nfemale' = 103) aged 25 to 65 ('x̅' = 39.53; 'SD' = 10.80) completed an online survey including; demographic questions, assessments of their physical activity goals and stage of change, decision to read eight messages, and a follow-up question providing the option to complete a behavior change task embedded within the messages they chose to read. Results indicated that participants were more likely to choose to read a message if it fit their goal orientation, and overall, they were significantly more likely to read intrinsic as opposed to extrinsic messages. Further, findings demonstrated that participants were more likely to complete the optional behavior change activity contained within the message if they had an intrinsic goal orientation. These findings demonstrate that physical activity information should be framed intrinsically and recognizes that one’s goal orientation may significantly influence how people respond to messages.

Considerable research guided by the Self Determination Theory has demonstrated that people who are motivated by more self-determined reasons (e.g., enjoyment, core beliefs, or personally meaningful benefits) are more likely to be physical activity. However, far less is known about the role ones’ stage of change (readiness for physical activity) plays in this relationship. The purpose of the present study was to (a) determine if the six forms of motivation and indices of physical activity varied across the stages of change, and (b) investigate if composite scores of self-determined and non-self-determined motivation were differentially related to physical activity indices depending on the stage of change of the individual. In total, 700 adults aged 18–65 ('M'age = 32.59; 'SD' = 12.82) completed an online survey consisting of demographics, and assessments of stages of change, motivation, and physical activity. Results demonstrated that participants at more advanced stages of change reported significantly higher self-determined motives, moderate activity, vigorous activity, and frequency of physical activity, and lower amotivation, with introjected regulation peaking at the implementation phase. Moderation analyses indicated that stages of change moderated the relationship between self-determined motives and moderate to vigorous physical activity, as well as physical activity frequency, but did not moderate the relationship between non-self-determined motives and indices of physical activity. Findings suggested that participants’ self-determined motives play a critical role in physical activity and becomes more important at more advanced stages of change, which is important to consider for program and intervention development.

Abstract Background Producing rainfed cotton (Gossypium hirsutum L.) with high fiber quality has been challenging in the Texas High Plains because of extended periods of insufficient rainfall during sensitive boll developmental stages. Genetic variation created by Ethyl MethaneSulfonate (EMS) mutagen has successfully improved fiber quality of cotton. However, little is known about the effect of water deficit environments on fiber quality. Three EMS treated populations were advanced from the first to the fourth generation (M1 to M4) as bulk harvested populations. In 2014, single-plant divergent selection was applied based on perceived morphological and agronomic differences seen during and at the end of the season. Results Analyses from these selections in 2014–2016 showed significant (P

Fingerprinting ocean acidification (OA) in US West Coast waters is extremely challenging due to the large magnitude of natural carbonate chemistry variations common to these regions. Additionally, quantifying a change requires information about the initial conditions, which is not readily available in most coastal systems. In an effort to address this issue, we have collated high-quality publicly available data to characterize the modern seasonal carbonate chemistry variability in marine surface waters of the US Pacific Northwest. Underway ship data from version 4 of the Surface Ocean CO2 Atlas, discrete observations from various sampling platforms, and sustained measurements from regional moorings were incorporated to provide ∼  100 000 inorganic carbon observations from which modern seasonal cycles were estimated. Underway ship and discrete observations were merged and gridded to a 0.1°  ×  0.1° scale. Eight unique regions were identified and seasonal cycles from grid cells within each region were averaged. Data from nine surface moorings were also compiled and used to develop robust estimates of mean seasonal cycles for comparison with the eight regions. This manuscript describes our methodology and the resulting mean seasonal cycles for multiple OA metrics in an effort to provide a large-scale environmental context for ongoing research, adaptation, and management efforts throughout the US Pacific Northwest. Major findings include the identification of unique chemical characteristics across the study domain. There is a clear increase in the ratio of dissolved inorganic carbon (DIC) to total alkalinity (TA) and in the seasonal cycle amplitude of carbonate system parameters when moving from the open ocean North Pacific into the Salish Sea. Due to the logarithmic nature of the pH scale (pH  =  −log10[H+], where [H+] is the hydrogen ion concentration), lower annual mean pH values (associated with elevated DIC  :  TA ratios) coupled with larger magnitude seasonal pH cycles results in seasonal [H+] ranges that are ∼  27 times larger in Hood Canal than in the neighboring North Pacific open ocean. Organisms living in the Salish Sea are thus exposed to much larger seasonal acidity changes than those living in nearby open ocean waters. Additionally, our findings suggest that lower buffering capacities in the Salish Sea make these waters less efficient at absorbing anthropogenic carbon than open ocean waters at the same latitude.All data used in this analysis are publically available at the following websites: Surface Ocean CO2 Atlas version 4 coastal data, https://doi.pangaea.de/10.1594/PANGAEA.866856 (Bakker et al., 2016a);National Oceanic and Atmospheric Administration (NOAA) West Coast Ocean Acidification cruise data, https://doi.org/10.3334/CDIAC/otg.CLIVAR_NACP_West_Coast_Cruise_2007 (Feely and Sabine, 2013); https://doi.org/10.7289/V5JQ0XZ1 (Feely et al., 2015b); https://data.nodc.noaa.gov/cgi-bin/iso?id=gov.noaa.nodc:0157445 (Feely et al., 2016a); https://doi.org/10.7289/V5C53HXP (Feely et al., 2015a);University of Washington (UW) and Washington Ocean Acidification Center cruise data, https://doi.org/10.5281/zenodo.1184657 (Fassbender et al., 2018);Washington State Department of Ecology seaplane data, https://doi.org/10.5281/zenodo.1184657 (Fassbender et al., 2018);NOAA Moored Autonomous pCO2 (MAPCO2) buoy data, https://doi.org/10.3334/CDIAC/OTG.TSM_LAPUSH_125W_48N (Sutton et al., 2012); https://doi.org/10.3334/CDIAC/OTG.TSM_WA_125W_47N (Sutton et al., 2013); https://doi.org/10.3334/CDIAC/OTG.TSM_DABOB_122W_478N (Sutton et al., 2014a); https://doi.org/10.3334/CDIAC/OTG.TSM_TWANOH_123W_47N (Sutton et al., 2016a);UW Oceanic Remote Chemical/Optical Analyzer buoy data, https://doi.org/10.5281/zenodo.1184657 (Fassbender et al., 2018);NOAA Pacific Coast Ocean Observing System cruise data, https://doi.org/10.5281/zenodo.1184657 (Fassbender et al., 2018).

Abstract Background Several hypnotic drugs have been previously identified as modulators of food intake, but exact mechanisms remain unknown. Feeding behavior implicates several neuronal populations in the hypothalamic arcuate nucleus including orexigenic neuropeptide Y and anorexigenic pro-opiomelanocortin producing neurons. The aim of this study was to investigate in mice the impact of different hypnotic drugs on food consumption and neuropeptide Y or pro-opiomelanocortine mRNA expression level in the hypothalamic arcuate nucleus. Methods Saline control, isoflurane, thiopental, midazolam or propofol were administered to C57Bl/6 mice. Feeding behavior was evaluated during 6 h. In situ hybridization of neuropeptide Y and pro-opiomelanocortine mRNAs in the hypothalamus brain region was also performed. Data were analyzed by Kruskal Wallis test and analysis of variance (p

O objetivo deste estudo foi analisar a adaptação transcultural da Escala de Motivação para o Esporte-II (SMS-II). Para tanto, foram realizados três estudos. O primeiro consistiu em traduzir a SMS-II para o português e adaptar seu conteúdo para o contexto brasileiro. No segundo, 364 atletas de modalidades individuais e coletivas responderam à versão adaptada da SMS-II. No estudo 3, 50 atletas responderam à SMS-II em dois momentos. O estudo 1 evidenciou que a versão em português contém questões claras e relevantes (CVC > 0,80). O estudo 2 mostrou que a SMS-II possui boa consistência interna em todas as dimensões (α > 0,70/CC > 0,70), com exceção da regulação introjetada (α > 0,61/CC > 0,56). A análise fatorial confirmatória demonstrou que todos os itens, exceto 1 e 7 (regulação introjetada), apresentaram cargas fatoriais aceitáveis; o modelo final da SMS-II (modificado) teve ajuste satisfatório e a análise multigrupos apontou a invariância entre homens e mulheres. Ademais, o estudo 3 evidenciou a estabilidade temporal da escala (CCI > 0,70). Concluiu-se que a adaptação transcultural da SMS-II para a língua portuguesa apresentou propriedades psicométricas aceitáveis; entretanto, suas limitações devem ser exploradas em futuras pesquisas.

It is known that the steroid sulfatase (STS) and the estrogen sulfotransferase (EST1E1) are commonly expressed in human breast carcinomas. STS and EST1E1 combined action could maintain the equilibrium between sulfated (inactive) and unconjugated (active) estrogens, which might have effects on development of hormone dependent breast cancer. We studied the expression of the STS and EST1E1 in 88 breast carcinomas and 57 adjacent non-malignant tissues by immunohistochemistry. The results were correlated with the tumor expression of estrogen receptor α (ER-α) and β (ER-β), progesterone receptor A (PR-A) and B (PR-B) and the proliferation marker CDC47, the tumoral type and stage and the age at surgery. STS expression was higher in carcinoma specimens than in adjacent normal tissues, although not to a significant level (p = 0.064) and it was positively associated with CDC47 expression (p 0.05). These observations support the hypothesis that STS is overexpressed in breast cancer and associated with a worse prognosis. EST1E1 was observed for the first time in the nuclei of epithelial and tumoral cells. Tumor expression of EST1E1 was positively correlated with ER-β (p 0.01) and PR-B (p 0.05), two steroid receptors already associated with an improve prognosis for breast cancer. Controlling the STS overexpression in carcinomas could be a way to inhibit cancer growth. The significance of the association between EST1E1 and ER-β or PR-B should be further studied since these two receptors are transcription activators and may regulate the expression of protective enzymes like EST1E1.

One of the main hurdles standing in the way of optimal cleaning of cotton lint isthe lack of sensing systems that can react fast enough to provide the control system withreal-time information as to the level of trash contamination of the cotton lint. This researchexamines the use of programmable graphic processing units (GPU) as an alternative to thePC’s traditional use of the central processing unit (CPU). The use of the GPU, as analternative computation platform, allowed for the machine vision system to gain asignificant improvement in processing time. By improving the processing time, thisresearch seeks to address the lack of availability of rapid trash sensing systems and thusalleviate a situation in which the current systems view the cotton lint either well before, orafter, the cotton is cleaned. This extended lag/lead time that is currently imposed on thecotton trash cleaning control systems, is what is responsible for system operators utilizing avery large dead-band safety buffer in order to ensure that the cotton lint is not undercleaned.Unfortunately, the utilization of a large dead-band buffer results in the majority ofthe cotton lint being over-cleaned which in turn causes lint fiber-damage as well assignificant losses of the valuable lint due to the excessive use of cleaning machinery. Thisresearch estimates that upwards of a 30% reduction in lint loss could be gained through theuse of a tightly coupled trash sensor to the cleaning machinery control systems. Thisresearch seeks to improve processing times through the development of a new algorithm forcotton trash sensing that allows for implementation on a highly parallel architecture.Additionally, by moving the new parallel algorithm onto an alternative computing platform,the graphic processing unit “GPUâ€Â, for processing of the cotton trash images, a speed up ofover 6.5 times, over optimized code running on the PC’s central processing unit “CPUâ€Â, wasgained. The new parallel algorithm operating on the GPU was able to process a 1024x1024image in less than 17ms. At this improved speed, the image processing system’s performance should now be sufficient to provide a system that would be capable of realtimefeed-back control that is in tight cooperation with the cleaning equipment.

In his article, ‘Homeostatic theory of obesity’, Marks suggested that imbalances in homeostatic processes could explain weight gain and obesity. He proposes that over-consumption of high-caloric, low-nutrient and low satiating foods, combined with a stressful environment, is the origin of weight gain. Once weight gain occurs, individuals may develop body dissatisfaction and negative affect, leading to continued over-consumption, which sets in motion a system of feedback loops that leads to a Circle of Discontent and further weight gain. In this article, we attempt to clarify certain problematic aspects of Marks framework and identify specific directions that researchers should pursue to address these shortcomings.

Accepted acoustic testing standards are available; however, they require specialized hardware and software that are typically out of reach economically to the occasional practitioner. What is needed is a simple and inexpensive screening method that can provide a quick comparison for rapid identification of the top candidates. This research reports on the development of an acoustical rapid-test method that achieves these objectives. The method is based upon a reformulation of the well-regarded three-microphone method. The new formulation reduces the number of required microphones to a single microphone and removes the need for simultaneous capture and extensive signal-processing analysis. The study compares the proposed simplified method to two standard methods and the three-microphone method. The results of the correlation analysis between the new method versus the original method produced a coefficient of determination of r2 = 0.994. A simulation study highlighted several unique accuracy advantages of this new proposed method in comparison to the existing standard methods. The proposed new method represents an easy-to-use technique that requires little in the way of equipment and can be set up with minimal training and expense.

A novel new way to achieve chemical-free defoliation of cotton is discussed. The research found that by severing the phloem tissue on the main stalk, via a girdling operation, the operation stimulated the cotton plant to alter its growth into an early senescence pathway that resulted in the plant shedding its leaves and opening up all its bolls, leaving the plant in the perfect state for machine harvesting. Even with follow-up rains, zero regrowth occurred in the treated plants, unlike the untreated control plots where significant regrowth did occur. This report compares the results of greenhouse and field trials where the girdling operation was performed by hand, flame, mechanical and via a CO2 laser to achieve phloem tissue severance. Design parameters for a prototype laser girdling system are also provided. Results suggest that for deficit irrigated cotton, girdling can provide an alternative means to defoliate cotton.

Accurate moisture sensing is an important need for many research programs as well as in control of industrial processes. This paper describes the development of a high accuracy frequency domain sensing probe for use in obtaining dielectric measurements of materials suitable for work ranging from 300 MHz to 1 GHz. The probe was developed to accommodate a wide range of permittivity’s ranging from εr = 2.5 to elevated permittivity’s as high as εr = 40. The design provides a well-matched interface between the soil and the interconnecting cables. A key advantage of the frequency domain approach is that a change of salt concentration has a significantly reduced effect on ε′, versus the traditional time-domain reflectometry, TDR, measured apparent permittivity, Ka.