Individual Differences in the Neural Response to Personal Goal Pursuit Success and Failure: A Developmental Analysis

Regulatory focus theory (RFT) proposes two different social-cognitive motivational systems for goal pursuit: a promotion system, which is organized around strategic approach behaviors and "making good things happen," and a prevention system, which is organized around strategic avoidance and "keeping bad things from happening." The promotion and prevention systems have been extensively studied in behavioral paradigms, and RFT posits that prolonged perceived failure to make progress in pursuing promotion or prevention goals can lead to ineffective goal pursuit and chronic distress (Higgins, 1997).

Research has begun to focus on uncovering the neural correlates of the promotion and prevention systems in an attempt to differentiate them at the neurobiological level. Preliminary research suggests that the promotion and prevention systems have both distinct and overlapping neural correlates (Eddington, Dolcos, Cabeza, Krishnan, & Strauman, 2007; Strauman et al., 2013). However, little research has examined how individual differences in regulatory focus develop and manifest. The development of individual differences in regulatory focus is particularly salient during adolescence, a crucial topic to explore given the dramatic neurodevelopmental and psychosocial changes that take place during this time, especially with regard to self-regulatory abilities. A number of questions remain unexplored, including the potential for goal-related neural activation to be modulated by (a) perceived proximity to goal attainment, (b) individual differences in regulatory orientation, specifically general beliefs about one's success or failure in attaining the two kinds of goals, (c) age, with a particular focus on adolescence, and (d) homozygosity for the Met allele of the catechol-O-methyltransferase (COMT) Val158Met polymorphism, a naturally occurring genotype which has been shown to impact prefrontal cortex activation patterns associated with goal pursuit behaviors.

This study explored the neural correlates of the promotion and prevention systems through the use of a priming paradigm involving rapid, brief, masked presentation of individually selected promotion and prevention goals to each participant while being scanned. The goals used as priming stimuli varied with regard to whether participants reported that they were close to or far away from achieving them (i.e. a "match" versus a "mismatch" representing perceived success or failure in personal goal pursuit). The study also assessed participants' overall beliefs regarding their relative success or failure in attaining promotion and prevention goals, and all participants were genotyped for the COMT Val158Met polymorphism.

A number of significant findings emerged. Both promotion and prevention priming were associated with activation in regions associated with self-referential cognition, including the left medial prefrontal cortex, cuneus, and lingual gyrus. Promotion and prevention priming were also associated with distinct patterns of neural activation; specifically, left middle temporal gyrus activation was found to be significantly greater during prevention priming. Activation in response to promotion and prevention goals was found to be modulated by self-reports of both perceived proximity to goal achievement and goal orientation. Age also had a significant effect on activation, such that activation in response to goal priming became more robust in the prefrontal cortex and in default mode network regions as a function of increasing age. Finally, COMT genotype also modulated the neural response to goal priming both alone and through interactions with regulatory focus and age. Overall, these findings provide further clarification of the neural underpinnings of the promotion and prevention systems as well as provide information about the role of development and individual differences at the personality and genetic level on activity in these neural systems.

Development of miniaturized antennas and adaptive tuning solutions for body sensor network applications

Wireless Sensor Networks (WSNs) are currently having a revolutionary impact in rapidly emerging wearable applications such as health and fitness monitoring amongst many others. These types of Body Sensor Network (BSN) applications require highly integrated wireless sensor devices for use in a wearable configuration, to monitor various physiological parameters of the user. These new requirements are currently posing significant design challenges from an antenna perspective. This work addresses several design challenges relating to antenna design for these types of applications. In this thesis, a review of current antenna solutions for WSN applications is first presented, investigating both commercial and academic solutions. Key design challenges are then identified relating to antenna size and performance. A detailed investigation of the effects of the human body on antenna impedance characteristics is then presented. A first-generation antenna tuning system is then developed. This system enables the antenna impedance to be tuned adaptively in the presence of the human body. Three new antenna designs are also presented. A compact, low-cost 433 MHz antenna design is first reported and the effects of the human body on the impedance of the antenna are investigated. A tunable version of this antenna is then developed, using a higher performance, second-generation tuner that is integrated within the antenna element itself, enabling autonomous tuning in the presence of the human body. Finally, a compact sized, dual-band antenna is reported that covers both the 433 MHz and 2.45 GHz bands to provide improved quality of service (QoS) in WSN applications. To date, state-of-the-art WSN devices are relatively simple in design with limited antenna options available, especially for the lower UHF bands. In addition, current devices have no capability to deal with changing antenna environments such as in wearable BSN applications. This thesis presents several contributions that advance the state-of-the-art in this area, relating to the design of miniaturized WSN antennas and the development of antenna tuning solutions for BSN applications.

R-ArcticNet, A Regional Hydrographic Data Network for the Pan-Arctic Region (ISO-image of CD-ROM)

We describe the contemporary hydrography of the pan-Arctic land area draining into the Arctic Ocean, northern Bering Sea, and Hudson Bay on the basis of observational records of river discharge and computed runoff. The Regional Arctic Hydrographic Network data set, R-ArcticNET, is presented, which is based on 3754 recording stations drawn from Russian, Canadian, European, and U.S. archives. R-ArcticNET represents the single largest data compendium of observed discharge in the Arctic. Approximately 73% of the nonglaciated area of the pan-Arctic is monitored by at least one river discharge gage giving a mean gage density of 168 gages per 106 km2. Average annual runoff is 212 mm yr?1 with approximately 60% of the river discharge occurring from April to July. Gridded runoff surfaces are generated for the gaged portion of the pan-Arctic region to investigate global change signals. Siberia and Alaska showed increases in winter runoff during the 1980s relative to the 1960s and 1970s during annual and seasonal periods. These changes are consistent with observations of change in the climatology of the region. Western Canada experienced decreased spring and summer runoff.

Análisis de la producción científica de los arquitectos técnicos docentes universitarios en España. 1980-2015. Estudio de revistas indizadas en WOS-SCOPUS-CSIC (ICYT-ISOC)

Se estudia la producción científica de los Arquitectos Técnicos docentes universitarios en España en los últimos 35 años ya que el cambio del título académico al de Grado, el aumento del número de doctores y el desarrollo de una política académica que ha convertido en parámetro especial para medir la calidad de la Universidad la cantidad y calidad de los artículos publicados han propiciado un cambio sustancial en esta área del conocimiento. Se determina la investigación producida a través del análisis de las bases de datos WOS-SCOPUS-CSIC(ICYT-ISOC) y las revistas más utilizadas por esta disciplina y se analiza el número de publicaciones de este colectivo por Universidades y revistas. El estudio llevado a cabo evidencia un cambio sustancial en la producción científica de los arquitectos técnicos en España.

Robust indoor speaker recognition in a network of audio and video sensors

Situational awareness is achieved naturally by the human senses of sight and hearing in combination. Automatic scene understanding aims at replicating this human ability using microphones and cameras in cooperation. In this paper, audio and video signals are fused and integrated at different levels of semantic abstractions. We detect and track a speaker who is relatively unconstrained, i.e., free to move indoors within an area larger than the comparable reported work, which is usually limited to round table meetings. The system is relatively simple: consisting of just 4 microphone pairs and a single camera. Results show that the overall multimodal tracker is more reliable than single modality systems, tolerating large occlusions and cross-talk. System evaluation is performed on both single and multi-modality tracking. The performance improvement given by the audio–video integration and fusion is quantified in terms of tracking precision and accuracy as well as speaker diarisation error rate and precision–recall (recognition). Improvements vs. the closest works are evaluated: 56% sound source localisation computational cost over an audio only system, 8% speaker diarisation error rate over an audio only speaker recognition unit and 36% on the precision–recall metric over an audio–video dominant speaker recognition method.

Transcallosal connectivity of the human cortical motor network

The organizational and architectural configuration of white matter pathways connecting brain regions has ramifications for all facets of the human condition, including manifestations of incipient neurodegeneration. Although diffusion tensor imaging (DTI) has been used extensively to visualize white matter connectivity, due to the widespread presence of crossing fibres, the lateral projections of the corpus callosum are not normally detected using this methodology. Detailed knowledge of the transcallosal connectivity of the human cortical motor network has therefore remained elusive. We employed constrained spherical deconvolution (CSD) tractography - an approach that is much less susceptible to the influence of crossing fibres, in order to derive complete in-vivo characterizations of white matter pathways connecting specific motor cortical regions to their counterparts and other loci in the opposite hemisphere. The revealed patterns of connectivity closely resemble those derived from anatomical tracing in primates. It was established that dorsal premotor cortex (PMd) and supplementary motor area (SMA) have extensive interhemispheric connectivity - exhibiting both dense homologous projections, and widespread structural relations with every other region in the contralateral motor network. Through this in-vivo portrayal, the importance of non-primary motor regions for interhemispheric communication is emphasized. Additionally, distinct connectivity profiles were detected for the anterior and posterior subdivisions of primary motor cortex. The present findings provide a comprehensive representation of transcallosal white matter projections in humans, and have the potential to inform the development of models and hypotheses relating structural and functional brain connectivity.

Scaling up strategies of the chronic respiratory disease programme of the European Innovation Partnership on Active and Healthy Ageing (Action Plan B3: Area 5)

Action Plan B3 of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) focuses on the integrated care of chronic diseases. Area 5 (Care Pathways) was initiated using chronic respiratory diseases as a model. The chronic respiratory disease action plan includes (1) AIRWAYS integrated care pathways (ICPs), (2) the joint initiative between the Reference site MACVIA-LR (Contre les MAladies Chroniques pour un VIeillissement Actif) and ARIA (Allergic Rhinitis and its Impact on Asthma), (3) Commitments for Action to the European Innovation Partnership on Active and Healthy Ageing and the AIRWAYS ICPs network. It is deployed in collaboration with the World Health Organization Global Alliance against Chronic Respiratory Diseases (GARD). The European Innovation Partnership on Active and Healthy Ageing has proposed a 5-step framework for developing an individual scaling up strategy: (1) what to scale up: (1-a) databases of good practices, (1-b) assessment of viability of the scaling up of good practices, (1-c) classification of good practices for local replication and (2) how to scale up: (2-a) facilitating partnerships for scaling up, (2-b) implementation of key success factors and lessons learnt, including emerging technologies for individualised and predictive medicine. This strategy has already been applied to the chronic respiratory disease action plan of the European Innovation Partnership on Active and Healthy Ageing.

Proposing the deep dynamic Bayesian network as a future computer based medical system

The development of new learning models has been of great importance throughout recent years, with a focus on creating advances in the area of deep learning. Deep learning was first noted in 2006, and has since become a major area of research in a number of disciplines. This paper will delve into the area of deep learning to present its current limitations and provide a new idea for a fully integrated deep and dynamic probabilistic system. The new model will be applicable to a vast number of areas initially focusing on applications into medical image analysis with an overall goal of utilising this approach for prediction purposes in computer based medical systems.

Model-driven development of sensor network applications with optimization of non-functional constraints

Wireless sensor networks (WSNs) differ from conventional distributed systems in many aspects. The resource limitation of sensor nodes, the ad-hoc communication and topology of the network, coupled with an unpredictable deployment environment are difficult non-functional constraints that must be carefully taken into account when developing software systems for a WSN. Thus, more research needs to be done on designing, implementing and maintaining software for WSNs. This thesis aims to contribute to research being done in this area by presenting an approach to WSN application development that will improve the reusability, flexibility, and maintainability of the software. Firstly, we present a programming model and software architecture aimed at describing WSN applications, independently of the underlying operating system and hardware. The proposed architecture is described and realized using the Model-Driven Architecture (MDA) standard in order to achieve satisfactory levels of encapsulation and abstraction when programming sensor nodes. Besides, we study different non-functional constrains of WSN application and propose two approaches to optimize the application to satisfy these constrains. A real prototype framework was built to demonstrate the developed solutions in the thesis. The framework implemented the programming model and the multi-layered software architecture as components. A graphical interface, code generation components and supporting tools were also included to help developers design, implement, optimize, and test the WSN software. Finally, we evaluate and critically assess the proposed concepts. Two case studies are provided to support the evaluation. The first case study, a framework evaluation, is designed to assess the ease at which novice and intermediate users can develop correct and power efficient WSN applications, the portability level achieved by developing applications at a high-level of abstraction, and the estimated overhead due to usage of the framework in terms of the footprint and executable code size of the application. In the second case study, we discuss the design, implementation and optimization of a real-world application named TempSense, where a sensor network is used to monitor the temperature within an area.

A spiking neural network implementation of sound localisation

The focus of this paper is the implementation of a spiking neural network to achieve sound localization; the model is based on the influential short paper by Jeffress in 1948. The SNN has a two-layer topology which can accommodate a limited number of angles in the azimuthal plane. The model accommodates multiple inter-neuron connections with associated delays, and a supervised STDP algorithm is applied to select the optimal pathway for sound localization. Also an analysis of previous relevant work in the area of auditory modelling supports this research.

Transmyocardial laser revascularization. Personal experience

Background. Indirect revascularization is a therapeutic approach in case of severe angina not suitable for percutaneous or surgical revascularization. Transmyocardial revascularization (TMR) is one of the techniques used for indirect revascularization and it allows to create transmyocardial channels by a laser energy bundle delivered on left ventricular epicardial surface. Benefits of the procedure are related mainly to the angiogenesis caused by inflammation and secondly to the destruction of the nervous fibers of the heart. Patients and method. From September 1996 up to July 1997, 14 patients (9 males – 66.7%, mean age 64.8±7.9 years) underwent TMR. All patients referred angina at rest; Canadian Angina Class was IV in 7 patients (58.3%), III in 5 (41.7%). Before the enrollment, coronarography was routinely performed to find out the feasibility of Coronary Artery Bypass Graft (CABG): 13 patients (91,6%) had coronary arteries lesions not suitable for direct revascularization; this condition was limited only to postero-lateral area in one patient submitted to combined TMR + CABG procedures. Results. Mean discharge time was 3,2±1,3 days after surgery. All patients were discharged in good clinical conditions. Perfusion thallium scintigraphy was performed in 7 patients at a mean follow-up of 4±2 months, showing in all but one an improvement of perfusion defects. Moreover an exercise treadmill improvement was observed in the same patients and all of them are in good clinical conditions, with significantly reduced use of active drugs. Conclusion. Our experience confirms that TMR is a safe and feasible procedure and it offers a therapeutic solution in case of untreatable angina. Moreover, it could be a hybrid approach for patients undergoing CABGs in case of absence of vessels suitable for surgical approach in limited areas of the heart.

El impacto de la red social twitter en la información local del diario El Tiempo y El Mercurio en el periodo febrero-junio

La red social Twitter da sus comienzos en el año 2006, su idioma inicial fue el inglés, su principal función es la de crear textos de 140 caracteres para dar a conocer información, dentro de una empresa, pero con el pasar del tiempo esta herramienta fue evolucionando hasta convertirse en la primera red de aceptación como apoyo para el periodismo digital. El Periodismo actual se está ayudando de herramientas tecnológicas como el Twitter para poder aportar noticias o acontecimientos que se generan dentro del territorio local, nacional y también a nivel internacional. Los diarios locales como: diario El Tiempo y diario El Mercurio dieron sus inicios a la era digital al mismo tiempo, ambos medios de comunicación poseen sus respectivas versiones electrónicas con las cuales informan a la ciudadanía ecuatoriana y a las personas que viven fuera del país. Los periodistas han aportado con conocimientos y experiencias personales en el manejo de Twitter como herramienta esencial que tiene el periodismo en la actualidad, también están de acuerdo que los periodistas necesitan de la última tecnología para poder sacarle el mayor provecho a esta red social, poseer dispositivos móviles facilita el desempeño periodístico y se puede twittear desde cualquier lugar donde acontecen hechos noticiosos.

Threat analysis of IoT networks using artificial neural network intrusion detection system

The Internet of things (IoT) is still in its infancy and has attracted much interest in many industrial sectors including medical fields, logistics tracking, smart cities and automobiles. However, as a paradigm, it is susceptible to a range of significant intrusion threats. This paper presents a threat analysis of the IoT and uses an Artificial Neural Network (ANN) to combat these threats. A multi-level perceptron, a type of supervised ANN, is trained using internet packet traces, then is assessed on its ability to thwart Distributed Denial of Service (DDoS/DoS) attacks. This paper focuses on the classification of normal and threat patterns on an IoT Network. The ANN procedure is validated against a simulated IoT network. The experimental results demonstrate 99.4% accuracy and can successfully detect various DDoS/DoS attacks.

Burned Area Mapping in the North American Boreal Forest Using Terra-MODIS LTDR (2001–2011): A Comparison with the MCD45A1, MCD64A1 and BA GEOLAND-2 Products

An algorithm based on a Bayesian network classifier was adapted to produce 10-day burned area (BA) maps from the Long Term Data Record Version 3 (LTDR) at a spatial resolution of 0.05° (~5 km) for the North American boreal region from 2001 to 2011. The modified algorithm used the Brightness Temperature channel from the Moderate Resolution Imaging Spectroradiometer (MODIS) band 31 T31 (11.03 μm) instead of the Advanced Very High Resolution Radiometer (AVHRR) band T3 (3.75 μm). The accuracy of the BA-LTDR, the Collection 5.1 MODIS Burned Area (MCD45A1), the MODIS Collection 5.1 Direct Broadcast Monthly Burned Area (MCD64A1) and the Burned Area GEOLAND-2 (BA GEOLAND-2) products was assessed using reference data from the Alaska Fire Service (AFS) and the Canadian Forest Service National Fire Database (CFSNFD). The linear regression analysis of the burned area percentages of the MCD64A1 product using 40 km × 40 km grids versus the reference data for the years from 2001 to 2011 showed an agreement of R2 = 0.84 and a slope = 0.76, while the BA-LTDR showed an agreement of R2 = 0.75 and a slope = 0.69. These results represent an improvement over the MCD45A1 product, which showed an agreement of R2 = 0.67 and a slope = 0.42. The MCD64A1, BA-LTDR and MCD45A1 products underestimated the total burned area in the study region, whereas the BA GEOLAND-2 product overestimated it by approximately five-fold, with an agreement of R2 = 0.05. Despite MCD64A1 showing the best overall results, the BA-LTDR product proved to be an alternative for mapping burned areas in the North American boreal forest region compared with the other global BA products, even those with higher spatial/spectral resolution

PICTOAPRENDE: Design and evaluation of a tool that contributes to the personal autonomy of children and youth diagnosed with autism spectrum disorder in Ecuador

This paper presents the development and evaluation of PICTOAPRENDE, which is an interactive software designed to improve oral communication. Additionally, it contributes to the development of children and youth who are diagnosed with autism spectrum disorder (ASD) in Ecuador. To fulfill this purpose initially analyzes the intervention area where the general characteristics of people with ASD and their status in Ecuador is described. Statistical techniques used for this evaluation constitutes the basis of this study. A section that presents the development of research-based cognitive and social parameters of the area of intervention is also shown. Finally, the algorithms to obtain the measurements and experimental results along with the analysis of them are presented.