Cognitive wireless sensor network platform for cooperative communications

Nowadays, Wireless Ad Hoc Sensor Networks (WAHSNs), specially limited in energy and resources, are subject to development constraints and difficulties such as the increasing RF spectrum saturation at the unlicensed bands. Cognitive Wireless Sensor Networks (CWSNs), leaning on a cooperative communication model, develop new strategies to mitigate the inefficient use of the spectrum that WAHSNs face. However, few and poorly featured platforms allow their study due to their early research stage. This paper presents a versatile platform that brings together cognitive properties into WAHSNs. It combines hardware and software modules as an entire instrument to investigate CWSNs. The hardware fits WAHSN requirements in terms of size, cost, features, and energy. It allows communication over three different RF bands, becoming the only cognitive platform for WAHSNs with this capability. In addition, its modular and scalable design is widely adaptable to almost any WAHSN application. Significant features such as radio interface (RI) agility or energy consumption have been proven throughout different performance tests.

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.

Cognitive strategies for reducing energy consumption in wireless sensor networks

El consumo energético de las Redes de Sensores Inalámbricas (WSNs por sus siglas en inglés) es un problema histórico que ha sido abordado desde diferentes niveles y visiones, ya que no solo afecta a la propia supervivencia de la red sino que el creciente uso de dispositivos inteligentes y el nuevo paradigma del Internet de las Cosas hace que las WSNs tengan cada vez una mayor influencia en la huella energética. Debido a la tendencia al alza en el uso de estas redes se añade un nuevo problema, la saturación espectral. Las WSNs operan habitualmente en bandas sin licencia como son las bandas Industrial, Científica y Médica (ISM por sus siglas en inglés). Estas bandas se comparten con otro tipo de redes como Wi-Fi o Bluetooth cuyo uso ha crecido exponencialmente en los últimos años. Para abordar este problema aparece el paradigma de la Radio Cognitiva (CR), una tecnología que permite el acceso oportunista al espectro. La introducción de capacidades cognitivas en las WSNs no solo permite optimizar su eficiencia espectral sino que también tiene un impacto positivo en parámetros como la calidad de servicio, la seguridad o el consumo energético. Sin embargo, por otra parte, este nuevo paradigma plantea algunos retos relacionados con el consumo energético. Concretamente, el sensado del espectro, la colaboración entre los nodos (que requiere comunicación adicional) y el cambio en los parámetros de transmisión aumentan el consumo respecto a las WSN clásicas. Teniendo en cuenta que la investigación en el campo del consumo energético ha sido ampliamente abordada puesto que se trata de una de sus principales limitaciones, asumimos que las nuevas estrategias deben surgir de las nuevas capacidades añadidas por las redes cognitivas. Por otro lado, a la hora de diseñar estrategias de optimización para CWSN hay que tener muy presentes las limitaciones de recursos de estas redes en cuanto a memoria, computación y consumo energético de los nodos. En esta tesis doctoral proponemos dos estrategias de reducción de consumo energético en CWSNs basadas en tres pilares fundamentales. El primero son las capacidades cognitivas añadidas a las WSNs que proporcionan la posibilidad de adaptar los parámetros de transmisión en función del espectro disponible. La segunda es la colaboración, como característica intrínseca de las CWSNs. Finalmente, el tercer pilar de este trabajo es teoría de juegos como algoritmo de soporte a la decisión, ampliamente utilizado en WSNs debido a su simplicidad. Como primer aporte de la tesis se presenta un análisis completo de las posibilidades introducidas por la radio cognitiva en materia de reducción de consumo para WSNs. Gracias a las conclusiones extraídas de este análisis, se han planteado las hipótesis de esta tesis relacionadas con la validez de usar capacidades cognitivas como herramienta para la reducción de consumo en CWSNs. Una vez presentada las hipótesis, pasamos a desarrollar las principales contribuciones de la tesis: las dos estrategias diseñadas para reducción de consumo basadas en teoría de juegos y CR. La primera de ellas hace uso de un juego no cooperativo que se juega mediante pares de jugadores. En la segunda estrategia, aunque el juego continúa siendo no cooperativo, se añade el concepto de colaboración. Para cada una de las estrategias se presenta el modelo del juego, el análisis formal de equilibrios y óptimos y la descripción de la estrategia completa donde se incluye la interacción entre nodos. Con el propósito de probar las estrategias mediante simulación e implementación en dispositivos reales hemos desarrollado un marco de pruebas compuesto por un simulador cognitivo y un banco de pruebas formado por nodos cognitivos capaces de comunicarse en tres bandas ISM desarrollados en el B105 Lab. Este marco de pruebas constituye otra de las aportaciones de la tesis que permitirá el avance en la investigación en el área de las CWSNs. Finalmente, se presentan y discuten los resultados derivados de la prueba de las estrategias desarrolladas. La primera estrategia proporciona ahorros de energía mayores al 65% comparados con una WSN sin capacidades cognitivas y alrededor del 25% si la comparamos con una estrategia cognitiva basada en el sensado periódico del espectro para el cambio de canal de acuerdo a un nivel de ruido fijado. Este algoritmo se comporta de forma similar independientemente del nivel de ruido siempre que éste sea espacialmente uniformemente. Esta estrategia, a pesar de su sencillez, nos asegura el comportamiento óptimo en cuanto a consumo energético debido a la utilización de teoría de juegos en la fase de diseño del comportamiento de los nodos. La estrategia colaborativa presenta mejoras respecto a la anterior en términos de protección frente al ruido en escenarios de ruido más complejos donde aporta una mejora del 50% comparada con la estrategia anterior. ABSTRACT Energy consumption in Wireless Sensor Networks (WSNs) is a known historical problem that has been addressed from different areas and on many levels. But this problem should not only be approached from the point of view of their own efficiency for survival. A major portion of communication traffic has migrated to mobile networks and systems. The increased use of smart devices and the introduction of the Internet of Things (IoT) give WSNs a great influence on the carbon footprint. Thus, optimizing the energy consumption of wireless networks could reduce their environmental impact considerably. In recent years, another problem has been added to the equation: spectrum saturation. Wireless Sensor Networks usually operate in unlicensed spectrum bands such as Industrial, Scientific, and Medical (ISM) bands shared with other networks (mainly Wi-Fi and Bluetooth). To address the efficient spectrum utilization problem, Cognitive Radio (CR) has emerged as the key technology that enables opportunistic access to the spectrum. Therefore, the introduction of cognitive capabilities to WSNs allows optimizing their spectral occupation. Cognitive Wireless Sensor Networks (CWSNs) do not only increase the reliability of communications, but they also have a positive impact on parameters such as the Quality of Service (QoS), network security, or energy consumption. These new opportunities introduced by CWSNs unveil a wide field in the energy consumption research area. However, this also implies some challenges. Specifically, the spectrum sensing stage, collaboration among devices (which requires extra communication), and changes in the transmission parameters increase the total energy consumption of the network. When designing CWSN optimization strategies, the fact that WSN nodes are very limited in terms of memory, computational power, or energy consumption has to be considered. Thus, light strategies that require a low computing capacity must be found. Since the field of energy conservation in WSNs has been widely explored, we assume that new strategies could emerge from the new opportunities presented by cognitive networks. In this PhD Thesis, we present two strategies for energy consumption reduction in CWSNs supported by three main pillars. The first pillar is that cognitive capabilities added to the WSN provide the ability to change the transmission parameters according to the spectrum. The second pillar is that the ability to collaborate is a basic characteristic of CWSNs. Finally, the third pillar for this work is the game theory as a decision-making algorithm, which has been widely used in WSNs due to its lightness and simplicity that make it valid to operate in CWSNs. For the development of these strategies, a complete analysis of the possibilities is first carried out by incorporating the cognitive abilities into the network. Once this analysis has been performed, we expose the hypotheses of this thesis related to the use of cognitive capabilities as a useful tool to reduce energy consumption in CWSNs. Once the analyses are exposed, we present the main contribution of this thesis: the two designed strategies for energy consumption reduction based on game theory and cognitive capabilities. The first one is based on a non-cooperative game played between two players in a simple and selfish way. In the second strategy, the concept of collaboration is introduced. Despite the fact that the game used is also a non-cooperative game, the decisions are taken through collaboration. For each strategy, we present the modeled game, the formal analysis of equilibrium and optimum, and the complete strategy describing the interaction between nodes. In order to test the strategies through simulation and implementation in real devices, we have developed a CWSN framework composed by a CWSN simulator based on Castalia and a testbed based on CWSN nodes able to communicate in three different ISM bands. We present and discuss the results derived by the energy optimization strategies. The first strategy brings energy improvement rates of over 65% compared to WSN without cognitive techniques. It also brings energy improvement rates of over 25% compared with sensing strategies for changing channels based on a decision threshold. We have also seen that the algorithm behaves similarly even with significant variations in the level of noise while working in a uniform noise scenario. The collaborative strategy presents improvements respecting the previous strategy in terms of noise protection when the noise scheme is more complex where this strategy shows improvement rates of over 50%.

Cognitive Surveillance Architecture for Scenario Understanding

Uno de los mayores retos para la comunidad científica es conseguir que las máquinas posean en un futuro la capacidad del sistema visual y cognitivo humanos, de forma que, por ejemplo, en entornos de video vigilancia, puedan llegar a proporcionar de manera automática una descripción fiable de lo que está ocurriendo en la escena. En la presente tesis, mediante la propuesta de un marco de trabajo de referencia, se discuten y plantean los pasos necesarios para el desarrollo de sistemas más inteligentes capaces de extraer y analizar, a diferentes niveles de abstracción y mediante distintos módulos de procesamiento independientes, la información necesaria para comprender qué está sucediendo en un conjunto amplio de escenarios de distinta naturaleza. Se parte de un análisis de requisitos y se identifican los retos para este tipo de sistemas en la actualidad, lo que constituye en sí mismo los objetivos de esta tesis, contribuyendo así a un modelo de datos basado en el conocimiento que permitirá analizar distintas situaciones en las que personas y vehículos son los actores principales, dejando no obstante la puerta abierta a la adaptación a otros dominios. Así mismo, se estudian los distintos procesos que se pueden lanzar a nivel interno así como la necesidad de integrar mecanismos de realimentación a distintos niveles que permitan al sistema adaptarse mejor a cambios en el entorno. Como resultado, se propone un marco de referencia jerárquico que integra las capacidades de percepción, interpretación y aprendizaje para superar los retos identificados en este ámbito; y así poder desarrollar sistemas de vigilancia más robustos, flexibles e inteligentes, capaces de operar en una variedad de entornos. Resultados experimentales ejecutados sobre distintas muestras de datos (secuencias de vídeo principalmente) demuestran la efectividad del marco de trabajo propuesto respecto a otros propuestos en el pasado. Un primer caso de estudio, permite demostrar la creación de un sistema de monitorización de entornos de parking en exteriores para la detección de vehículos y el análisis de plazas libres de aparcamiento. Un segundo caso de estudio, permite demostrar la flexibilidad del marco de referencia propuesto para adaptarse a los requisitos de un entorno de vigilancia completamente distinto, como es un hogar inteligente donde el análisis automático de actividades de la vida cotidiana centra la atención del estudio. ABSTRACT One of the most ambitious objectives for the Computer Vision and Pattern Recognition research community is that machines can achieve similar capacities to the human's visual and cognitive system, and thus provide a trustworthy description of what is happening in the scene under surveillance. Thus, a number of well-established scenario understanding architectural frameworks to develop applications working on a variety of environments can be found in the literature. In this Thesis, a highly descriptive methodology for the development of scene understanding applications is presented. It consists of a set of formal guidelines to let machines extract and analyse, at different levels of abstraction and by means of independent processing modules that interact with each other, the necessary information to understand a broad set of different real World surveillance scenarios. Taking into account the challenges that working at both low and high levels offer, we contribute with a highly descriptive knowledge-based data model for the analysis of different situations in which people and vehicles are the main actors, leaving the door open for the development of interesting applications in diverse smart domains. Recommendations to let systems achieve high-level behaviour understanding will be also provided. Furthermore, feedback mechanisms are proposed to be integrated in order to let any system to understand better the environment and the logical context around, reducing thus the uncertainty and noise, and increasing its robustness and precision in front of low-level or high-level errors. As a result, a hierarchical cognitive architecture of reference which integrates the necessary perception, interpretation, attention and learning capabilities to overcome main challenges identified in this area of research is proposed; thus allowing to develop more robust, flexible and smart surveillance systems to cope with the different requirements of a variety of environments. Once crucial issues that should be treated explicitly in the design of this kind of systems have been formulated and discussed, experimental results shows the effectiveness of the proposed framework compared with other proposed in the past. Two case studies were implemented to test the capabilities of the framework. The first case study presents how the proposed framework can be used to create intelligent parking monitoring systems. The second case study demonstrates the flexibility of the system to cope with the requirements of a completely different environment, a smart home where activities of daily living are performed. Finally, general conclusions and future work lines to further enhancing the capabilities of the proposed framework are presented.

Alternative neural circuitry that might be impaired in the development of Alzheimer disease

It is well established that some individuals with normal cognitive capacity have abundant senile plaques in their brains. It has been proposed that those individuals are resilient or have compensation factors to prevent cognitive decline. In this comment, we explore an alternative mechanism through which cognitive capacity is maintained. This mechanism could involve the impairment of alternative neural circuitry. Also, the proportion of molecules such as A? or tau protein present in different areas of the brain could be important.

Development of a sensorimotor algorithm able to deal with unforeseen pushes and its implementation based on VHDL

Development of a Sensorimotor Algorithm Able to Deal with Unforeseen Pushes and Its Implementation Based on VHDL is the title of my thesis which concludes my Bachelor Degree in the Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación of the Universidad Politécnica de Madrid. It encloses the overall work I did in the Neurorobotics Research Laboratory from the Beuth Hochschule für Technik Berlin during my ERASMUS year in 2015. This thesis is focused on the field of robotics, specifically an electronic circuit called Cognitive Sensorimotor Loop (CSL) and its control algorithm based on VHDL hardware description language. The reason that makes the CSL special resides in its ability to operate a motor both as a sensor and an actuator. This way, it is possible to achieve a balanced position in any of the robot joints (e.g. the robot manages to stand) without needing any conventional sensor. In other words, the back electromotive force (EMF) induced by the motor coils is measured and the control algorithm responds depending on its magnitude. The CSL circuit contains mainly an analog-to-digital converter (ADC) and a driver. The ADC consists on a delta-sigma modulation which generates a series of bits with a certain percentage of 1's and 0's, proportional to the back EMF. The control algorithm, running in a FPGA, processes the bit frame and outputs a signal for the driver. This driver, which has an H bridge topology, gives the motor the ability to rotate in both directions while it's supplied with the power needed. The objective of this thesis is to document the experiments and overall work done on push ignoring contractive sensorimotor algorithms, meaning sensorimotor algorithms that ignore large magnitude forces (compared to gravity) applied in a short time interval on a pendulum system. This main objective is divided in two sub-objectives: (1) developing a system based on parameterized thresholds and (2) developing a system based on a push bypassing filter. System (1) contains a module that outputs a signal which blocks the main Sensorimotor algorithm when a push is detected. This module has several different parameters as inputs e.g. the back EMF increment to consider a force as a push or the time interval between samples. System (2) consists on a low-pass Infinite Impulse Response digital filter. It cuts any frequency considered faster than a certain push oscillation. This filter required an intensive study on how to implement some functions and data types (fixed or floating point data) not supported by standard VHDL packages. Once this was achieved, the next challenge was to simplify the solution as much as possible, without using non-official user made packages. Both systems behaved with a series of interesting advantages and disadvantages for the elaboration of the document. Stability, reaction time, simplicity or computational load are one of the many factors to be studied in the designed systems. RESUMEN. Development of a Sensorimotor Algorithm Able to Deal with Unforeseen Pushes and Its Implementation Based on VHDL es un Proyecto de Fin de Grado (PFG) que concluye mis estudios en la Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación de la Universidad Politécnica de Madrid. En él se documenta el trabajo de investigación que realicé en el Neurorobotics Research Laboratory de la Beuth Hochschule für Technik Berlin durante el año 2015 mediante el programa de intercambio ERASMUS. Este PFG se centra en el campo de la robótica y en concreto en un circuito electrónico llamado Cognitive Sensorimotor Loop (CSL) y su algoritmo de control basado en lenguaje de modelado hardware VHDL. La particularidad del CSL reside en que se consigue que un motor haga las veces tanto de sensor como de actuador. De esta manera es posible que las articulaciones de un robot alcancen una posición de equilibrio (p.ej. el robot se coloca erguido) sin la necesidad de sensores en el sentido estricto de la palabra. Es decir, se mide la propia fuerza electromotriz (FEM) inducida sobre el motor y el algoritmo responde de acuerdo a su magnitud. El circuito CSL se compone de un convertidor analógico-digital (ADC) y un driver. El ADC consiste en un modulador sigma-delta, que genera una serie de bits con un porcentaje de 1's y 0's determinado, en proporción a la magnitud de la FEM inducida. El algoritmo de control, que se ejecuta en una FPGA, procesa esta cadena de bits y genera una señal para el driver. El driver, que posee una topología en puente H, provee al motor de la potencia necesaria y le otorga la capacidad de rotar en cualquiera de las dos direcciones. El objetivo de este PFG es documentar los experimentos y en general el trabajo realizado en algoritmos Sensorimotor que puedan ignorar fuerzas de gran magnitud (en comparación con la gravedad) y aplicadas en una corta ventana de tiempo. En otras palabras, ignorar empujones conservando el comportamiento original frente a la gravedad. Para ello se han desarrollado dos sistemas: uno basado en umbrales parametrizados (1) y otro basado en un filtro de corte ajustable (2). El sistema (1) contiene un módulo que, en el caso de detectar un empujón, genera una señal que bloquea el algoritmo Sensorimotor. Este módulo recibe diferentes parámetros como el incremento necesario de la FEM para que se considere un empujón o la ventana de tiempo para que se considere la existencia de un empujón. El sistema (2) consiste en un filtro digital paso-bajo de respuesta infinita que corta cualquier variación que considere un empujón. Para crear este filtro se requirió un estudio sobre como implementar ciertas funciones y tipos de datos (coma fija o flotante) no soportados por las librerías básicas de VHDL. Tras esto, el objetivo fue simplificar al máximo la solución del problema, sin utilizar paquetes de librerías añadidos. En ambos sistemas aparecen una serie de ventajas e inconvenientes de interés para el documento. La estabilidad, el tiempo de reacción, la simplicidad o la carga computacional son algunas de las muchos factores a estudiar en los sistemas diseñados. Para concluir, también han sido documentadas algunas incorporaciones a los sistemas: una interfaz visual en VGA, un módulo que compensa el offset del ADC o la implementación de una batería de faders MIDI entre otras.

A Young Child's Anxiety and Math Performance: Enhancing Cognitive Behavioral Intervention with Conjoint Behavioral Consultation

Partnering with families, school personnel, and community resources is an important step to supporting the child and family, especially when children might suffer from debilitating anxiety concerns. However, little research examines the impact of anxiety on math performance for young children participating in school-based interventions enhanced by family components. The following research questions were addressed in the study: 1a) Will a young child with elevated levels of anxiety show a decrease in anxiety symptoms with a Cognitive Behavioral framework intervention program for children? 1b) Will anxiety be reduced with the addition of a Conjoint Behavioral Consultation with the family and teacher? 2a) Will a young child show an increase in math performance after participation in a Cognitive Behavioral framework intervention program for children? 2b) Will math performance be increased with the addition of a Conjoint Behavioral Consultation with the family and teacher? A single-subject staggered baseline across situations intervention study addressed whether the Coping Cat, an evidenced-based child-focused intervention now widely used in schools and clinics to treat childhood anxiety, combined with family and school consultation will decrease elevated anxiety levels and improve math performance in an elementary-aged student. The objective was to support mental health development and math performance with an eight-year-old, female elementary student through a collaborative effort of stakeholders in the student's life. Baseline data was collected with repeated measures of anxiety and math performance, and was compared to two intervention phases: first, a child-focused intervention and second, a family and school consultation. The study tested the theory that the Cognitive Behavioral intervention and Conjoint Behavioral Consultation intervention will influence, positively, the anxiety levels and math performance for an elementary-aged student. Results indicate that the child participant with elevated levels of anxiety showed a reduction in symptoms with the introduction of a Cognitive Behavioral framework intervention when compared to her baseline data. The participant showed further reduction in symptoms across the school and home settings with the implementation of Conjoint Behavioral Consultation when compared to baseline and the first intervention phase. Math performance began to increase with the introduction of the Cognitive Behavioral intervention, and continued to improve with the implementation of the Conjoint Behavioral Consultation. Findings suggest that consultation should begin immediately when an intervention is implemented in order to enhance outcomes.

Comparison of Reading Development Across Socioeconomic Status in the United States

It is well known that higher parental socioeconomic status (SES) predicts better child reading outcomes, but little work has been done to unpack this finding. The main overall question addressed by this project was whether cognitive models of the two main reading outcomes, single word reading (SWR) and reading comprehension (RC), performed similarly across levels of parental SES. The current study predicted a differential relation between parental SES and both predictors and outcomes because of the known large relation between parental SES and child oral language development. Three questions examined the mediating effects of cognitive predictors on the relation between parental SES and reading outcomes, the moderating effects of SES on the developmental trajectories of reading outcomes, and the strength of the relationship between SES and the two reading outcomes. Participants were part of two large and comprehensive datasets: the cross-sectional Colorado Learning Disability Research Center (CLDRC; n=1554) sample, and the International Longitudinal Twin Study (ILTS; n=463 twin pairs) sample. In terms of cognitive predictors, the relation between SES and SWR was disproportionately mediated by two language skills, vocabulary (VOC) and phonological awareness (PA). For the RC models, both SWR and oral listening comprehension (OLC) did not disproportionally mediate the relation between RC and SES; however, full mediation was not exhibited. With regard to the trajectory of reading outcomes, SES moderated the starting values of SWR and RC, and the slopes of SWR development. When performance on the control measures of early reading skills (e.g., print knowledge, vocabulary, and decoding skills) was included the models, the moderating effects of SES were completely accounted for by these measures. In terms of outcomes, SES had a stronger relation to RC than to SWR, especially at later ages. These findings have implications for interventions aimed at improving reading outcomes in children from lower SES families.

The Relationships Between Child Maltreatment and Exploratory Behavior Implications for Development.

Findings from the fields of attachment theory, physiology, neurology, neurobiology and cognitive theory, when considered together, enhance understanding of the behavior and development of maltreated children. Each field describes from its own vantage how emotional trauma influences the quality and quantity of exploratory behavior. Development in many spheres is influemced by behavior. There is evidence from the field of neurobiology that experience ultimately influences the anatomy of the brain. Therefore, it can be hypothesized that constricted, overly defensive behavior in childhood ultimately compromises the development of the central nervous system itself. The altered neurobiology may help explain some of the developmental delays and failures seen in some maltreated children. Such developmental disruptions may include lowered intellectual performance, impaired ability to learn from experience, behavioral regressions under stress, and characterological abnormalities. This neurobiologic hypothesis has implications for research, intervention and training of professionals.It encourages 1) the identification of those deficit capacities most vulnerable to becoming neurologically based, 2) identification of ways to help the maltreated child explore and be accessible to developmental experiences, 3) more emphasis on the development of cognitive capacities, and 4) more breadth of training for professionals who work with maltreated children and their families.

Development of the DORI-TBI: An Investigation to Develop a New Screening Measure to Determine Consultation with a School-Based Brain Injury Resource Team

Brain injury is the leading cause of disability and death in children in the United States. Student re-entry into the school setting following a traumatic brain injury is crucial to student success. Multidisciplinary teams within the school district comprised of individuals with expertise in brain injury are ideal in implementing student specific treatment plans given their specialized training and wide range of expertise addressing student needs. Therefore, the purpose of this study is to develop and initially validate a quantitative instrument that school personnel can use to determine if a student, identified as having a traumatic brain injury, will benefit from district-level consultation from a brain injury team. Three studies were designed to investigate the research questions. In study one, the planning and construction of the DORI-TBI was completed. Study two addressed the content validity of the DORI-TBI through a comparison analysis with other referral forms, content review with experts in the field of TBI, and cognitive interviews with professionals to test the usability of the new screening tool. In study three, a field administration was conducted using vignettes to measure construct validity. Results produced a valid and reliable new screening instrument that can aid school-based teams to more efficiently utilize district level consultation with a brain injury support team.

Development of The Readiness To Teach Online Scale

Despite the growing importance of online education, faculty acceptance has remained unchanged. Training programs developed for faculty to teach online have often focused on assessing their cognitive rather than affective and behavioral outcomes. The Readiness To Teach Online scale was developed as part of a multiphase mixed method research project to measure faculty perceptions and motivations toward teaching online. Items in the subcategory Teaching and Learning measured perceptions of technology and online teaching, and motivations regarding resources and other external factors. Items in the subcategories Social and Student Engagement, Faculty and Technology Support, Course Development and Instructional Design, and Evaluation and Assessment collected baseline data for current practices. The pilot study of this scale demonstrated strong internal consistency reliability estimates and support for validity, showing moderately to highly correlated significant relationships between faculty perceptions and motivation to teach online; both perception and motivation constructs were moderately to highly correlated with Social and Student Engagement.

Do Methods Matter In Global Leadership Development? A Mixed-Methods Study Of A U.s.-Based International Mba Program

As world communication, technology, and trade become increasingly integrated through globalization, multinational corporations seek employees with global leadership experience and skills. However, the demand for these skills currently outweighs the supply. Given the rarity of globally ready leaders, global competency development should be emphasized in higher education programs. The reality, however, is that university graduate programs are often outdated and focus mostly on cognitive learning. Global leadership competence requires moving beyond the cognitive domain of learning to create socially responsible and culturally connected global leaders. This requires attention to development methods; however, limited research in global leadership development methods has been conducted. A new conceptual model, the global leadership development ecosystem, was introduced in this study to guide the design and evaluation of global leadership development programs. It was based on three theories of learning and was divided into four development methodologies. This study quantitatively tested the model and used it as a framework for an in-depth examination of the design of one International MBA program. The program was first benchmarked, by means of a qualitative best practices analysis, against the top-ranking IMBA programs in the world. Qualitative data from students, faculty, administrators, and staff was then examined, using descriptive and focused data coding. Quantitative data analysis, using PASW Statistics software, and a hierarchical regression, showed the individual effect of each of the four development methods, as well as their combined effect, on student scores on a global leadership assessment. The analysis revealed that each methodology played a distinct and important role in developing different competencies of global leadership. It also confirmed the critical link between self-efficacy and global leadership development.

SOCIAL, EMOTIONAL, COGNITIVE, AND PHYSIOLOGICAL CORRELATES OF ELECTRONIC SOCIAL BEHAVIOR

There has been very little research that has studied the capacities that can be fostered to mitigate the risk for involvement in electronic bullying or victimization and almost no research examining positive electronic behavior. The primary goal of this dissertation was to use the General Aggression Model and Anxious Apprehension Model of Trauma to explore the underlying cognitive, emotional, and self-regulation processes that are related to electronic bullying, victimization, and prosocial behavior. In Study 1, we explored several potential interpretations of the General Aggression Model that would accurately describe the relationship that electronic self-conscious appraisal, cognitive reappraisal, and activational control may have with electronic bullying and victimization. In Study 2, we used the Anxious Apprehension Model of Trauma to explore rejection cognitions as the mediator of the relationships among emotionality (emotionality, shame, state emotion responses, and physiological arousal) and electronic bullying and victimization using structural equation modelling. In addition, we explored the role of rejection cognitions in mediating the relationship of moral disengagement with electronic bullying. In Study 3, we examined predictors of electronic prosocial behavior, such as bullying, victimization, time online, electronic proficiency, electronic self-conscious appraisals, emotionality, and self-regulation. All three studies supported the General Aggression Model as a framework to guide the study of electronic behavior, and suggest the importance of cognitive, emotional, and behavioral means of regulation in shaping electronic behavior. In addition, each study has implications for the development of high quality electronic bullying prevention and intervention research.

Role of the cotransporter KCC2 in cortical excitatory synapse development and febrile seizure susceptibility

Le co-transporteur KCC2 spécifique au potassium et chlore a pour rôle principal de réduire la concentration intracellulaire de chlore, entraînant l’hyperpolarisation des courants GABAergic l’autorisant ainsi à devenir inhibiteur dans le cerveau mature. De plus, il est aussi impliqué dans le développement des synapses excitatrices, nommées aussi les épines dendritiques. Le but de notre projet est d’étudier l’effet des modifications concernant l'expression et la fonction de KCC2 dans le cortex du cerveau en développement dans un contexte de convulsions précoces. Les convulsions fébriles affectent environ 5% des enfants, et ce dès la première année de vie. Les enfants atteints de convulsions fébriles prolongées et atypiques sont plus susceptibles à développer l’épilepsie. De plus, la présence d’une malformation cérébrale prédispose au développement de convulsions fébriles atypiques, et d’épilepsie du lobe temporal. Ceci suggère que ces pathologies néonatales peuvent altérer le développement des circuits neuronaux irréversiblement. Cependant, les mécanismes qui sous-tendent ces effets ne sont pas encore compris. Nous avons pour but de comprendre l'impact des altérations de KCC2 sur la survenue des convulsions et dans la formation des épines dendritiques. Nous avons étudié KCC2 dans un modèle animal de convulsions précédemment validé, qui combine une lésion corticale à P1 (premier jour de vie postnatale), suivie d'une convulsion induite par hyperthermie à P10 (nommés rats LHS). À la suite de ces insultes, 86% des rats mâles LHS développent l’épilepsie à l’âge adulte, au même titre que des troubles d’apprentissage. À P20, ces animaux presentent une augmentation de l'expression de KCC2 associée à une hyperpolarisation du potentiel de réversion de GABA. De plus, nous avons observé des réductions dans la taille des épines dendritiques et l'amplitude des courants post-synaptiques excitateurs miniatures, ainsi qu’un déficit de mémoire spatial, et ce avant le développement des convulsions spontanées. Dans le but de rétablir les déficits observés chez les rats LHS, nous avons alors réalisé un knock-down de KCC2 par shARN spécifique par électroporation in utero. Nos résultats ont montré une diminution de la susceptibilité aux convulsions due à la lésion corticale, ainsi qu'une restauration de la taille des épines. Ainsi, l’augmentation de KCC2 à la suite d'une convulsion précoce, augmente la susceptibilité aux convulsions modifiant la morphologie des épines dendritiques, probable facteur contribuant à l’atrophie de l’hippocampe et l’occurrence des déficits cognitifs. Le deuxième objectif a été d'inspecter l’effet de la surexpression précoce de KCC2 dans le développement des épines dendritiques de l’hippocampe. Nous avons ainsi surexprimé KCC2 aussi bien in vitro dans des cultures organotypiques d’hippocampe, qu' in vivo par électroporation in utero. À l'inverse des résultats publiés dans le cortex, nous avons observé une diminution de la densité d’épines dendritiques et une augmentation de la taille des épines. Afin de confirmer la spécificité du rôle de KCC2 face à la région néocorticale étudiée, nous avons surexprimé KCC2 dans le cortex par électroporation in utero. Cette manipulation a eu pour conséquences d’augmenter la densité et la longueur des épines synaptiques de l’arbre dendritique des cellules glutamatergiques. En conséquent, ces résultats ont démontré pour la première fois, que les modifications de l’expression de KCC2 sont spécifiques à la région affectée. Ceci souligne les obstacles auxquels nous faisons face dans le développement de thérapie adéquat pour l’épilepsie ayant pour but de moduler l’expression de KCC2 de façon spécifique.

Role of the cotransporter KCC2 in cortical excitatory synapse development and febrile seizure susceptibility

Le co-transporteur KCC2 spécifique au potassium et chlore a pour rôle principal de réduire la concentration intracellulaire de chlore, entraînant l’hyperpolarisation des courants GABAergic l’autorisant ainsi à devenir inhibiteur dans le cerveau mature. De plus, il est aussi impliqué dans le développement des synapses excitatrices, nommées aussi les épines dendritiques. Le but de notre projet est d’étudier l’effet des modifications concernant l'expression et la fonction de KCC2 dans le cortex du cerveau en développement dans un contexte de convulsions précoces. Les convulsions fébriles affectent environ 5% des enfants, et ce dès la première année de vie. Les enfants atteints de convulsions fébriles prolongées et atypiques sont plus susceptibles à développer l’épilepsie. De plus, la présence d’une malformation cérébrale prédispose au développement de convulsions fébriles atypiques, et d’épilepsie du lobe temporal. Ceci suggère que ces pathologies néonatales peuvent altérer le développement des circuits neuronaux irréversiblement. Cependant, les mécanismes qui sous-tendent ces effets ne sont pas encore compris. Nous avons pour but de comprendre l'impact des altérations de KCC2 sur la survenue des convulsions et dans la formation des épines dendritiques. Nous avons étudié KCC2 dans un modèle animal de convulsions précédemment validé, qui combine une lésion corticale à P1 (premier jour de vie postnatale), suivie d'une convulsion induite par hyperthermie à P10 (nommés rats LHS). À la suite de ces insultes, 86% des rats mâles LHS développent l’épilepsie à l’âge adulte, au même titre que des troubles d’apprentissage. À P20, ces animaux presentent une augmentation de l'expression de KCC2 associée à une hyperpolarisation du potentiel de réversion de GABA. De plus, nous avons observé des réductions dans la taille des épines dendritiques et l'amplitude des courants post-synaptiques excitateurs miniatures, ainsi qu’un déficit de mémoire spatial, et ce avant le développement des convulsions spontanées. Dans le but de rétablir les déficits observés chez les rats LHS, nous avons alors réalisé un knock-down de KCC2 par shARN spécifique par électroporation in utero. Nos résultats ont montré une diminution de la susceptibilité aux convulsions due à la lésion corticale, ainsi qu'une restauration de la taille des épines. Ainsi, l’augmentation de KCC2 à la suite d'une convulsion précoce, augmente la susceptibilité aux convulsions modifiant la morphologie des épines dendritiques, probable facteur contribuant à l’atrophie de l’hippocampe et l’occurrence des déficits cognitifs. Le deuxième objectif a été d'inspecter l’effet de la surexpression précoce de KCC2 dans le développement des épines dendritiques de l’hippocampe. Nous avons ainsi surexprimé KCC2 aussi bien in vitro dans des cultures organotypiques d’hippocampe, qu' in vivo par électroporation in utero. À l'inverse des résultats publiés dans le cortex, nous avons observé une diminution de la densité d’épines dendritiques et une augmentation de la taille des épines. Afin de confirmer la spécificité du rôle de KCC2 face à la région néocorticale étudiée, nous avons surexprimé KCC2 dans le cortex par électroporation in utero. Cette manipulation a eu pour conséquences d’augmenter la densité et la longueur des épines synaptiques de l’arbre dendritique des cellules glutamatergiques. En conséquent, ces résultats ont démontré pour la première fois, que les modifications de l’expression de KCC2 sont spécifiques à la région affectée. Ceci souligne les obstacles auxquels nous faisons face dans le développement de thérapie adéquat pour l’épilepsie ayant pour but de moduler l’expression de KCC2 de façon spécifique.