Cross-cultural equivalence and associations among food insecurity and parental influences of children's fruit and vegetable consumption

Over the past several decades, the prevalence of obesity has dramatically increased. Cause for concern has increased because overweight and obesity are major contributors to morbidity and mortality. Intervention research aimed at reducing the prevalence of obesity has identified the family, specifically the parent, as a key component of the home environment. However, findings from dietary behavior change interventions have been disheartening because few studies have reported meaningful change, suggesting methodological and/or measurement issues within the intervention process. A lack of appropriate mediators and cross-cultural equivalence may partially explain the reason for little change.^ The study aims were to (1) evaluate the psychometric properties and assess the cross cultural equivalence of the Food Insecurity Scale (paper 1) and the modified Parent Feeding Practices Questionnaire (paper 2) and to assess the overall relationships among food insecurity, parent mediators, and parent behaviors towards children's dietary behavior (paper 3) through structural equation modeling and tests of invariance. The study aims were accomplished through conducting secondary analyses using baseline data from English- and Spanish-speaking Hispanic women who participated in the Healthy Families: Step by Step (BHF) study.^ Results indicated that although the FIS and the mPFPQ exhibited sound psychometric properties, the instruments exhibited a lack of invariance across language spoken groups. The lack of invariance was more pronounced in the FIS. Results also supported the theoretical framework identifying parent's perceived barriers and self-efficacy as mediators of parent's behaviors toward improving children's health eating. Results did not suggest that the relationships were moderated by food insecurity.^ In conclusion, the identification of differential item functioning in food insecurity and parent feeding practices may be beneficial in enhancing tailored interventions through the incorporation of cultural differences into the change mechanisms. However, future research needs to be conducted to determine if the lack of invariance demonstrates the existence of item bias or if it is a reflection of true difference among the language spoken groups. Additionally, obesity intervention studies targeting parent/family barriers and parent self-efficacy to provide/encourage healthy diets may result in an increase in parent behaviors which promote healthy eating behaviors among children. Future research should also examine a more complete causal pathway to determine whether parental changes in the mediators ultimately lead to an increase in healthy dietary behavior among children.^

Investigating the effects of the 2007 Texas tobacco tax increase on the smoking behavior of adults

Smoking is major cause of premature mortality and morbidity in the United States. The health consequences of tobacco usage are increasingly concentrated in minority and lower socioeconomic groups. One of the most effective means of deterring tobacco consumption and generating revenue to fund prevention activities is the levying of excise taxes. In 2007 the state of Texas increased the excise tax on cigarettes by $1.00 per pack. This study sought to determine if there was a significant effect on smoking prevalence in the state by examining Behavioral Risk Factor Surveillance System (BRFSS) data for two years leading up to the tax increase-2005 and 2006- and two years post tax increase -2007 and 2008. Results were compared against a chi square distribution and three multiple logistic regression models were created to adjust for race/ethnicity, age, education and income. Results from this study show that there was not a significant decrease in smoking prevalence for most of the groups stratified by age, income and ethnicity. There was not a significant decrease in the younger adults aged 18-34 by income, ethnicity, or education. Smoking prevalence increased for some groups, e.g., Hispanic females. In the regression models, the tax effect was not significant. While overall prevalence decreased by 9%, there were not significant reductions among non-White or Hispanic survey participants. Taxed sales dropped by approximately 17% according to the Texas Comptroller. Without BRFSS data measuring daily cigarette consumption among current smokers, now not assessed, it is impossible to determine whether the discrepancy in reported prevalence and taxes sales is attributable to consumption of fewer cigarettes among smokers or tax avoidance.^

Parent modeling and child food consumption

Obesity, among both children and adults, is a growing public health epidemic. One area of interest relates to how and why obesity is developing at such a rapid pace among children. Despite a broad consensus about how controlling feeding practices relate to child food consumption and obesity prevalence, much less is known about how non-controlling feeding practices, including modeling, relate to child food consumption. This study investigates how different forms of parent modeling (no modeling, simple modeling, and enthusiastic modeling) and parent adiposity relate to child food consumption, food preferences, and behaviors towards foods. Participants in this experimental study were 65 children (25 boys and 40 girls) aged 3-9 and their parents. Each parent was trained on how to perform their assigned modeling behavior towards a food identified as neutral (not liked, nor disliked) by their child during a pre-session food-rating task. Parents performed their assigned modeling behavior when cued during a ten-minute observation period with their child. Child food consumption (pieces eaten, grams eaten, and calories consumed) was measured and food behaviors (positive comments toward food and food requests) were recorded by event-based coding. After the session, parents self-reported on their height and weight, and children completed a post-session food-rating task. Results indicate that parent modeling (both simple and enthusiastic forms) did not significantly relate to child food consumption, food preferences, or food requests. However, enthusiastic modeling significantly increased the number of positive food comments made by children. Children's food consumption in response to parent modeling did not differ based on parent obesity status. The practical implications of this study are discussed, along with its strengths and limitations, and directions for future research.^

A game theory based strategy for reducing energy consumption in cognitive WSN

Wireless sensor networks (WSNs) are one of the most important users of wireless communication technologies in the coming years and some challenges in this area must be addressed for their complete development. Energy consumption and spectrum availability are two of the most severe constraints of WSNs due to their intrinsic nature. The introduction of cognitive capabilities into these networks has arisen to face the issue of spectrum scarcity but could be used to face energy challenges too due to their new range of communication possibilities. In this paper a new strategy based on game theory for cognitive WSNs is discussed. The presented strategy improves energy consumption by taking advantage of the new change-communication-channel capability. Based on game theory, the strategy decides when to change the transmission channel depending on the behavior of the rest of the network nodes. The strategy presented is lightweight but still has higher energy saving rates as compared to noncognitive networks and even to other strategies based on scheduled spectrum sensing. Simulations are presented for several scenarios that demonstrate energy saving rates of around 65% as compared to WSNs without cognitive techniques.

Improved static analysis and verification of energy consumption and other resources via abstract interpretation

Resource analysis aims at inferring the cost of executing programs for any possible input, in terms of a given resource, such as the traditional execution steps, time ormemory, and, more recently energy consumption or user defined resources (e.g., number of bits sent over a socket, number of database accesses, number of calls to particular procedures, etc.). This is performed statically, i.e., without actually running the programs. Resource usage information is useful for a variety of optimization and verification applications, as well as for guiding software design. For example, programmers can use such information to choose different algorithmic solutions to a problem; program transformation systems can use cost information to choose between alternative transformations; parallelizing compilers can use cost estimates for granularity control, which tries to balance the overheads of task creation and manipulation against the benefits of parallelization. In this thesis we have significatively improved an existing prototype implementation for resource usage analysis based on abstract interpretation, addressing a number of relevant challenges and overcoming many limitations it presented. The goal of that prototype was to show the viability of casting the resource analysis as an abstract domain, and howit could overcome important limitations of the state-of-the-art resource usage analysis tools. For this purpose, it was implemented as an abstract domain in the abstract interpretation framework of the CiaoPP system, PLAI.We have improved both the design and implementation of the prototype, for eventually allowing an evolution of the tool to the industrial application level. The abstract operations of such tool heavily depend on the setting up and finding closed-form solutions of recurrence relations representing the resource usage behavior of program components and the whole program as well. While there exist many tools, such as Computer Algebra Systems (CAS) and libraries able to find closed-form solutions for some types of recurrences, none of them alone is able to handle all the types of recurrences arising during program analysis. In addition, there are some types of recurrences that cannot be solved by any existing tool. This clearly constitutes a bottleneck for this kind of resource usage analysis. Thus, one of the major challenges we have addressed in this thesis is the design and development of a novel modular framework for solving recurrence relations, able to combine and take advantage of the results of existing solvers. Additionally, we have developed and integrated into our novel solver a technique for finding upper-bound closed-form solutions of a special class of recurrence relations that arise during the analysis of programs with accumulating parameters. Finally, we have integrated the improved resource analysis into the CiaoPP general framework for resource usage verification, and specialized the framework for verifying energy consumption specifications of embedded imperative programs in a real application, showing the usefulness and practicality of the resulting tool.---ABSTRACT---El Análisis de recursos tiene como objetivo inferir el coste de la ejecución de programas para cualquier entrada posible, en términos de algún recurso determinado, como pasos de ejecución, tiempo o memoria, y, más recientemente, el consumo de energía o recursos definidos por el usuario (por ejemplo, número de bits enviados a través de un socket, el número de accesos a una base de datos, cantidad de llamadas a determinados procedimientos, etc.). Ello se realiza estáticamente, es decir, sin necesidad de ejecutar los programas. La información sobre el uso de recursos resulta muy útil para una gran variedad de aplicaciones de optimización y verificación de programas, así como para asistir en el diseño de los mismos. Por ejemplo, los programadores pueden utilizar dicha información para elegir diferentes soluciones algorítmicas a un problema; los sistemas de transformación de programas pueden utilizar la información de coste para elegir entre transformaciones alternativas; los compiladores paralelizantes pueden utilizar las estimaciones de coste para realizar control de granularidad, el cual trata de equilibrar el coste debido a la creación y gestión de tareas, con los beneficios de la paralelización. En esta tesis hemos mejorado de manera significativa la implementación de un prototipo existente para el análisis del uso de recursos basado en interpretación abstracta, abordando diversos desafíos relevantes y superando numerosas limitaciones que éste presentaba. El objetivo de dicho prototipo era mostrar la viabilidad de definir el análisis de recursos como un dominio abstracto, y cómo se podían superar las limitaciones de otras herramientas similares que constituyen el estado del arte. Para ello, se implementó como un dominio abstracto en el marco de interpretación abstracta presente en el sistema CiaoPP, PLAI. Hemos mejorado tanto el diseño como la implementación del mencionado prototipo para posibilitar su evolución hacia una herramienta utilizable en el ámbito industrial. Las operaciones abstractas de dicha herramienta dependen en gran medida de la generación, y posterior búsqueda de soluciones en forma cerrada, de relaciones recurrentes, las cuales modelizan el comportamiento, respecto al consumo de recursos, de los componentes del programa y del programa completo. Si bien existen actualmente muchas herramientas capaces de encontrar soluciones en forma cerrada para ciertos tipos de recurrencias, tales como Sistemas de Computación Algebraicos (CAS) y librerías de programación, ninguna de dichas herramientas es capaz de tratar, por sí sola, todos los tipos de recurrencias que surgen durante el análisis de recursos. Existen incluso recurrencias que no las puede resolver ninguna herramienta actual. Esto constituye claramente un cuello de botella para este tipo de análisis del uso de recursos. Por lo tanto, uno de los principales desafíos que hemos abordado en esta tesis es el diseño y desarrollo de un novedoso marco modular para la resolución de relaciones recurrentes, combinando y aprovechando los resultados de resolutores existentes. Además de ello, hemos desarrollado e integrado en nuestro nuevo resolutor una técnica para la obtención de cotas superiores en forma cerrada de una clase característica de relaciones recurrentes que surgen durante el análisis de programas lógicos con parámetros de acumulación. Finalmente, hemos integrado el nuevo análisis de recursos con el marco general para verificación de recursos de CiaoPP, y hemos instanciado dicho marco para la verificación de especificaciones sobre el consumo de energía de programas imperativas embarcados, mostrando la viabilidad y utilidad de la herramienta resultante en una aplicación real.

An accurate model for simulating energetic behavior of PV grid connected inverters

This paper proposes a new model for characterizing the energetic behavior of grid connected PV inverters. The model has been obtained from a detailed study of main loss processes in small size PV inverters in the market. The main advantage of the used method is to obtain a model that comprises two antagonistic features, since both are simple, easy to compute and apply, and accurate. One of the main features of this model is how it handles the maximum power point tracking (MPPT) and the efficiency: in both parts the model uses the same approach and it is achieved by two resistive elements which simulate the losses inherent to each parameter. This makes this model easy to implement, compact and refined. The model presented here also includes other parameters, such as start threshold, standby consumption and islanding behavior. In order to validate the model, the values of all the parameters listed above have been obtained and adjusted using field measurements for several commercial inverters, and the behavior of the model applied to a particular inverter has been compared with real data under different working conditions, taken from a facility located in Madrid. The results show a good fit between the model values and the real data. As an example, the model has been implemented in PSPICE electronic simulator, and this approach has been used to teach grid-connected PV systems. The use of this model for the maintenance of working PV facilities is also shown.

The Health Behavior Change Competency Checklist (HBCCC): Instrument development and psychometric evaluation.

More than half of morbidity and mortality in the United States can be attributed to behavior-related disease, such as tobacco use, physical inactivity, poor diet and alcohol consumption. Given the increased prevalence of behaviorally related medical health concerns, physician competence in the implementation of effective behavior change strategies is quickly becoming an essential skill. However, only recently have primary care residency programs begun to systematically teach and evaluate motivational interviewing skills critical to influencing health behavior, and use of standardized, objective assessment tools to assess skillfulness has been largely absent. This paper reports the development of a checklist, the Health Behavior Change Competency Checklist (HBCCC). The instrument captures the theoretical model of behavior change, motivational interviewing, in a practical and versatile manner. Psychometric evaluation demonstrated moderate efficacy. Namely, results indicated the HBCCC possesses good reliability, as evidenced by high internal consistency, and adequate construct validity. It also displayed considerable utility and practical application. While these results provide several reasons for confidence in the HBCCC, item revision and additional testing are required in order to establish it as a meaningful and valuable instrument.

Towards Closed-loop Deep Brain Stimulation: Behavior Recognition from Human STN

Deep brain stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson’s disease (PD). Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and side effects by adjusting stimulation parameters based on patient’s behavior. Thus behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. This thesis proposes novel detection and classification techniques for behavior recognition based on deep brain LFP. Behavior detection from such signals is the vital step in developing the next generation of closed-loop DBS devices. LFP recordings from 13 subjects are utilized in this study to design and evaluate our method. Recordings were performed during the surgery and the subjects were asked to perform various behavioral tasks. Various techniques are used understand how the behaviors modulate the STN. One method studies the time-frequency patterns in the STN LFP during the tasks. Another method measures the temporal inter-hemispheric connectivity of the STN as well as the connectivity between STN and Pre-frontal Cortex (PFC). Experimental results demonstrate that different behaviors create different m odulation patterns in STN and it’s connectivity. We use these patterns as features to classify behaviors. A method for single trial recognition of the patient’s current task is proposed. This method uses wavelet coefficients as features and support vector machine (SVM) as the classifier for recognition of a selection of behaviors: speech, motor, and random. The proposed method is 82.4% accurate for the binary classification and 73.2% for classifying three tasks. As the next step, a practical behavior detection method which asynchronously detects behaviors is proposed. This method does not use any priori knowledge of behavior onsets and is capable of asynchronously detect the finger movements of PD patients. Our study indicates that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from STN. We utilize a non-linear regression method to measure this inter-hemispheric connectivity and to detect the finger movements. Our experimental results using STN LFP recorded from eight patients with PD demonstrate this is a promising approach for behavior detection and developing novel closed-loop DBS systems.

Consumer behavior towards [sic] fuel efficient vehicles. Volume I: executive summary. Final report.

National Highway Traffic Safety Administration, Technology Assessment Division, Washington, D.C.

Consumer behavior towards [sic] fuel efficient vehicles. Volume II. Final report.

National Highway Traffic Safety Administration, Technology Assessment Division, Washington, D.C.

Consumer behavior towards fuel efficient vehicles. Volume IV: operating instructions and programs documentation for the CS Vehicle Choice Simulation Model. Final report.

National Highway Traffic Safety Administration, Technology Assessment Division, Washington, D.C.

Consumer behavior towards fuel efficient vehicles. Executive summary. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Consumer behavior towards fuel efficient vehicles. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Consumer behavior towards fuel efficient vehicles. Volume I: executive summary. Final report.

National Highway Traffic Safety Administration, Technology Assessment Division, Washington, D.C.

Consumer behavior towards fuel efficient vehicles. Volume II: consumer sentiments towards fuel efficient vehicles. Final report.

National Highway Traffic Safety Administration, Technology Assessment Division, Washington, D.C.