Atomistic modeling of Ge damage accumulation, amorphization and solid phase epitaxial regrowth

En los últimos años, el Ge ha ganado de nuevo atención con la finalidad de ser integrado en el seno de las existentes tecnologías de microelectrónica. Aunque no se le considera como un canddato capaz de reemplazar completamente al Si en el futuro próximo, probalemente servirá como un excelente complemento para aumentar las propiedades eléctricas en dispositivos futuros, especialmente debido a su alta movilidad de portadores. Esta integración requiere de un avance significativo del estado del arte en los procesos de fabricado. Técnicas de simulación, como los algoritmos de Monte Carlo cinético (KMC), proporcionan un ambiente atractivo para llevar a cabo investigación y desarrollo en este campo, especialmente en términos de costes en tiempo y financiación. En este estudio se han usado, por primera vez, técnicas de KMC con el fin entender el procesado “front-end” de Ge en su fabricación, específicamente la acumulación de dañado y amorfización producidas por implantación iónica y el crecimiento epitaxial en fase sólida (SPER) de las capas amorfizadas. Primero, simulaciones de aproximación de clisiones binarias (BCA) son usadas para calcular el dañado causado por cada ión. La evolución de este dañado en el tiempo se simula usando KMC sin red, o de objetos (OKMC) en el que sólamente se consideran los defectos. El SPER se simula a través de una aproximación KMC de red (LKMC), siendo capaz de seguir la evolución de los átomos de la red que forman la intercara amorfo/cristalina. Con el modelo de amorfización desarrollado a lo largo de este trabajo, implementado en un simulador multi-material, se pueden simular todos estos procesos. Ha sido posible entender la acumulación de dañado, desde la generación de defectos puntuales hasta la formación completa de capas amorfas. Esta acumulación ocurre en tres regímenes bien diferenciados, empezando con un ritmo lento de formación de regiones de dañado, seguido por una rápida relajación local de ciertas áreas en la fase amorfa donde ambas fases, amorfa y cristalina, coexisten, para terminar en la amorfización completa de capas extensas, donde satura el ritmo de acumulación. Dicha transición ocurre cuando la concentración de dañado supera cierto valor límite, el cual es independiente de las condiciones de implantación. Cuando se implantan los iones a temperaturas relativamente altas, el recocido dinámico cura el dañado previamente introducido y se establece una competición entre la generación de dañado y su disolución. Estos efectos se vuelven especialmente importantes para iones ligeros, como el B, el cual crea dañado más diluido, pequeño y distribuido de manera diferente que el causado por la implantación de iones más pesados, como el Ge. Esta descripción reproduce satisfactoriamente la cantidad de dañado y la extensión de las capas amorfas causadas por implantación iónica reportadas en la bibliografía. La velocidad de recristalización de la muestra previamente amorfizada depende fuertemente de la orientación del sustrato. El modelo LKMC presentado ha sido capaz de explicar estas diferencias entre orientaciones a través de un simple modelo, dominado por una única energía de activación y diferentes prefactores en las frecuencias de SPER dependiendo de las configuraciones de vecinos de los átomos que recristalizan. La formación de maclas aparece como una consecuencia de esta descripción, y es predominante en sustratos crecidos en la orientación (111)Ge. Este modelo es capaz de reproducir resultados experimentales para diferentes orientaciones, temperaturas y tiempos de evolución de la intercara amorfo/cristalina reportados por diferentes autores. Las parametrizaciones preliminares realizadas de los tensores de activación de tensiones son también capaces de proveer una buena correlación entre las simulaciones y los resultados experimentales de velocidad de SPER a diferentes temperaturas bajo una presión hidrostática aplicada. Los estudios presentados en esta tesis han ayudado a alcanzar un mejor entendimiento de los mecanismos de producción de dañado, su evolución, amorfización y SPER para Ge, además de servir como una útil herramienta para continuar el trabajo en este campo. In the recent years, Ge has regained attention to be integrated into existing microelectronic technologies. Even though it is not thought to be a feasible full replacement to Si in the near future, it will likely serve as an excellent complement to enhance electrical properties in future devices, specially due to its high carrier mobilities. This integration requires a significant upgrade of the state-of-the-art of regular manufacturing processes. Simulation techniques, such as kinetic Monte Carlo (KMC) algorithms, provide an appealing environment to research and innovation in the field, specially in terms of time and funding costs. In the present study, KMC techniques are used, for the first time, to understand Ge front-end processing, specifically damage accumulation and amorphization produced by ion implantation and Solid Phase Epitaxial Regrowth (SPER) of the amorphized layers. First, Binary Collision Approximation (BCA) simulations are used to calculate the damage caused by every ion. The evolution of this damage over time is simulated using non-lattice, or Object, KMC (OKMC) in which only defects are considered. SPER is simulated through a Lattice KMC (LKMC) approach, being able to follow the evolution of the lattice atoms forming the amorphous/crystalline interface. With the amorphization model developed in this work, implemented into a multi-material process simulator, all these processes can be simulated. It has been possible to understand damage accumulation, from point defect generation up to full amorphous layers formation. This accumulation occurs in three differentiated regimes, starting at a slow formation rate of the damage regions, followed by a fast local relaxation of areas into the amorphous phase where both crystalline and amorphous phases coexist, ending in full amorphization of extended layers, where the accumulation rate saturates. This transition occurs when the damage concentration overcomes a certain threshold value, which is independent of the implantation conditions. When implanting ions at relatively high temperatures, dynamic annealing takes place, healing the previously induced damage and establishing a competition between damage generation and its dissolution. These effects become specially important for light ions, as B, for which the created damage is more diluted, smaller and differently distributed than that caused by implanting heavier ions, as Ge. This description successfully reproduces damage quantity and extension of amorphous layers caused by means of ion implantation reported in the literature. Recrystallization velocity of the previously amorphized sample strongly depends on the substrate orientation. The presented LKMC model has been able to explain these differences between orientations through a simple model, dominated by one only activation energy and different prefactors for the SPER rates depending on the neighboring configuration of the recrystallizing atoms. Twin defects formation appears as a consequence of this description, and are predominant for (111)Ge oriented grown substrates. This model is able to reproduce experimental results for different orientations, temperatures and times of evolution of the amorphous/crystalline interface reported by different authors. Preliminary parameterizations for the activation strain tensors are able to also provide a good match between simulations and reported experimental results for SPER velocities at different temperatures under the appliance of hydrostatic pressure. The studies presented in this thesis have helped to achieve a greater understanding of damage generation, evolution, amorphization and SPER mechanisms in Ge, and also provide a useful tool to continue research in this field.

Co-simulation Methodologies for Hybrid and Electric Vehicle Dynamics

In recent decades, full electric and hybrid electric vehicles have emerged as an alternative to conventional cars due to a range of factors, including environmental and economic aspects. These vehicles are the result of considerable efforts to seek ways of reducing the use of fossil fuel for vehicle propulsion. Sophisticated technologies such as hybrid and electric powertrains require careful study and optimization. Mathematical models play a key role at this point. Currently, many advanced mathematical analysis tools, as well as computer applications have been built for vehicle simulation purposes. Given the great interest of hybrid and electric powertrains, along with the increasing importance of reliable computer-based models, the author decided to integrate both aspects in the research purpose of this work. Furthermore, this is one of the first final degree projects held at the ETSII (Higher Technical School of Industrial Engineers) that covers the study of hybrid and electric propulsion systems. The present project is based on MBS3D 2.0, a specialized software for the dynamic simulation of multibody systems developed at the UPM Institute of Automobile Research (INSIA). Automobiles are a clear example of complex multibody systems, which are present in nearly every field of engineering. The work presented here benefits from the availability of MBS3D software. This program has proven to be a very efficient tool, with a highly developed underlying mathematical formulation. On this basis, the focus of this project is the extension of MBS3D features in order to be able to perform dynamic simulations of hybrid and electric vehicle models. This requires the joint simulation of the mechanical model of the vehicle, together with the model of the hybrid or electric powertrain. These sub-models belong to completely different physical domains. In fact the powertrain consists of energy storage systems, electrical machines and power electronics, connected to purely mechanical components (wheels, suspension, transmission, clutch…). The challenge today is to create a global vehicle model that is valid for computer simulation. Therefore, the main goal of this project is to apply co-simulation methodologies to a comprehensive model of an electric vehicle, where sub-models from different areas of engineering are coupled. The created electric vehicle (EV) model consists of a separately excited DC electric motor, a Li-ion battery pack, a DC/DC chopper converter and a multibody vehicle model. Co-simulation techniques allow car designers to simulate complex vehicle architectures and behaviors, which are usually difficult to implement in a real environment due to safety and/or economic reasons. In addition, multi-domain computational models help to detect the effects of different driving patterns and parameters and improve the models in a fast and effective way. Automotive designers can greatly benefit from a multidisciplinary approach of new hybrid and electric vehicles. In this case, the global electric vehicle model includes an electrical subsystem and a mechanical subsystem. The electrical subsystem consists of three basic components: electric motor, battery pack and power converter. A modular representation is used for building the dynamic model of the vehicle drivetrain. This means that every component of the drivetrain (submodule) is modeled separately and has its own general dynamic model, with clearly defined inputs and outputs. Then, all the particular submodules are assembled according to the drivetrain configuration and, in this way, the power flow across the components is completely determined. Dynamic models of electrical components are often based on equivalent circuits, where Kirchhoff’s voltage and current laws are applied to draw the algebraic and differential equations. Here, Randles circuit is used for dynamic modeling of the battery and the electric motor is modeled through the analysis of the equivalent circuit of a separately excited DC motor, where the power converter is included. The mechanical subsystem is defined by MBS3D equations. These equations consider the position, velocity and acceleration of all the bodies comprising the vehicle multibody system. MBS3D 2.0 is entirely written in MATLAB and the structure of the program has been thoroughly studied and understood by the author. MBS3D software is adapted according to the requirements of the applied co-simulation method. Some of the core functions are modified, such as integrator and graphics, and several auxiliary functions are added in order to compute the mathematical model of the electrical components. By coupling and co-simulating both subsystems, it is possible to evaluate the dynamic interaction among all the components of the drivetrain. ‘Tight-coupling’ method is used to cosimulate the sub-models. This approach integrates all subsystems simultaneously and the results of the integration are exchanged by function-call. This means that the integration is done jointly for the mechanical and the electrical subsystem, under a single integrator and then, the speed of integration is determined by the slower subsystem. Simulations are then used to show the performance of the developed EV model. However, this project focuses more on the validation of the computational and mathematical tool for electric and hybrid vehicle simulation. For this purpose, a detailed study and comparison of different integrators within the MATLAB environment is done. Consequently, the main efforts are directed towards the implementation of co-simulation techniques in MBS3D software. In this regard, it is not intended to create an extremely precise EV model in terms of real vehicle performance, although an acceptable level of accuracy is achieved. The gap between the EV model and the real system is filled, in a way, by introducing the gas and brake pedals input, which reflects the actual driver behavior. This input is included directly in the differential equations of the model, and determines the amount of current provided to the electric motor. For a separately excited DC motor, the rotor current is proportional to the traction torque delivered to the car wheels. Therefore, as it occurs in the case of real vehicle models, the propulsion torque in the mathematical model is controlled through acceleration and brake pedal commands. The designed transmission system also includes a reduction gear that adapts the torque coming for the motor drive and transfers it. The main contribution of this project is, therefore, the implementation of a new calculation path for the wheel torques, based on performance characteristics and outputs of the electric powertrain model. Originally, the wheel traction and braking torques were input to MBS3D through a vector directly computed by the user in a MATLAB script. Now, they are calculated as a function of the motor current which, in turn, depends on the current provided by the battery pack across the DC/DC chopper converter. The motor and battery currents and voltages are the solutions of the electrical ODE (Ordinary Differential Equation) system coupled to the multibody system. Simultaneously, the outputs of MBS3D model are the position, velocity and acceleration of the vehicle at all times. The motor shaft speed is computed from the output vehicle speed considering the wheel radius, the gear reduction ratio and the transmission efficiency. This motor shaft speed, somehow available from MBS3D model, is then introduced in the differential equations corresponding to the electrical subsystem. In this way, MBS3D and the electrical powertrain model are interconnected and both subsystems exchange values resulting as expected with tight-coupling approach.When programming mathematical models of complex systems, code optimization is a key step in the process. A way to improve the overall performance of the integration, making use of C/C++ as an alternative programming language, is described and implemented. Although this entails a higher computational burden, it leads to important advantages regarding cosimulation speed and stability. In order to do this, it is necessary to integrate MATLAB with another integrated development environment (IDE), where C/C++ code can be generated and executed. In this project, C/C++ files are programmed in Microsoft Visual Studio and the interface between both IDEs is created by building C/C++ MEX file functions. These programs contain functions or subroutines that can be dynamically linked and executed from MATLAB. This process achieves reductions in simulation time up to two orders of magnitude. The tests performed with different integrators, also reveal the stiff character of the differential equations corresponding to the electrical subsystem, and allow the improvement of the cosimulation process. When varying the parameters of the integration and/or the initial conditions of the problem, the solutions of the system of equations show better dynamic response and stability, depending on the integrator used. Several integrators, with variable and non-variable step-size, and for stiff and non-stiff problems are applied to the coupled ODE system. Then, the results are analyzed, compared and discussed. From all the above, the project can be divided into four main parts: 1. Creation of the equation-based electric vehicle model; 2. Programming, simulation and adjustment of the electric vehicle model; 3. Application of co-simulation methodologies to MBS3D and the electric powertrain subsystem; and 4. Code optimization and study of different integrators. Additionally, in order to deeply understand the context of the project, the first chapters include an introduction to basic vehicle dynamics, current classification of hybrid and electric vehicles and an explanation of the involved technologies such as brake energy regeneration, electric and non-electric propulsion systems for EVs and HEVs (hybrid electric vehicles) and their control strategies. Later, the problem of dynamic modeling of hybrid and electric vehicles is discussed. The integrated development environment and the simulation tool are also briefly described. The core chapters include an explanation of the major co-simulation methodologies and how they have been programmed and applied to the electric powertrain model together with the multibody system dynamic model. Finally, the last chapters summarize the main results and conclusions of the project and propose further research topics. In conclusion, co-simulation methodologies are applicable within the integrated development environments MATLAB and Visual Studio, and the simulation tool MBS3D 2.0, where equation-based models of multidisciplinary subsystems, consisting of mechanical and electrical components, are coupled and integrated in a very efficient way.

Improved modeling of photoluminescent and electroluminescent coupling in multijunction solar cells

The performance of tandem stacks of Group III?V multijunction solar cells continues to improve rapidly, both through improved performance of the individual cells in the stack and throughi ncrease in the number of stacked cells. As the radiative efficiency of these individual cells increases, radiative coupling between the stacked cells becomes an increasingly important factor not only in cell design, but also in accurate efficiency measurement and in determining performance of cells and systems under varying spectral conditions in the field. Past modeling has concentrated on electroluminescent coupling between the cells, although photoluminescent coupling is shown to be important for cells operating near their maximum power point voltage or below or when junction defect recombination is significant. Extension of earlier models i sproposed to allow this non-negligible component of luminescent coupling to be included. Therefined model is validated by measurement of the closely related external emission from both single and double junction cells.

Modeling stochastic gene expression: Implications for haploinsufficiency

There is increasing recognition that stochastic processes regulate highly predictable patterns of gene expression in developing organisms, but the implications of stochastic gene expression for understanding haploinsufficiency remain largely unexplored. We have used simulations of stochastic gene expression to illustrate that gene copy number and expression deactivation rates are important variables in achieving predictable outcomes. In gene expression systems with non-zero expression deactivation rates, diploid systems had a higher probability of uninterrupted gene expression than haploid systems and were more successful at maintaining gene product above a very low threshold. Systems with relatively rapid expression deactivation rates (unstable gene expression) had more predictable responses to a gradient of inducer than systems with slow or zero expression deactivation rates (stable gene expression), and diploid systems were more predictable than haploid, with or without dosage compensation. We suggest that null mutations of a single allele in a diploid organism could decrease the probability of gene expression and present the hypothesis that some haploinsufficiency syndromes might result from an increased susceptibility to stochastic delays of gene initiation or interruptions of gene expression.

Behavioral expression of emotions and non-invasive assessment of physiological correlates in dogs (Canis familiaris)

The aim of this thesis was to validate the use of infrared thermography (IRT) to non-invasively measure emotional reactions to different situations in pet dogs (Canis familiaris). A preliminary test, aimed to evaluate the correlation between eye-temperature and rectal temperature in dog, was performed. Then, in three different situations, negative (veterinary visit), positive (palatable food rewards), and mildly stressing followed by mildly positive (separation from and reunion with the owner), variations in heat emitted from lacrimal caruncle (referred to as eye temperature) were measured with an infrared thermographic camera. In addition, heart rate and heart rate variability parameters were collected using a non-invasive heart rate monitor designed for human use and validated on dogs. All experiments were video recorded to allow behavioral coding. During the negative situation dogs’ level of activity and stress related behaviors varied across compared to the baseline and dogs showed an increase in eye temperature despite having a significant decrease in the level of activity. The positive situation was characterized by a peak in eye temperature and mean HR and dogs engaged in behaviors indicating a positive arousal, focusing on food treats and tail wagging but there were not variations in HRV during stimulation but only an increment in SDNN immediately after the stimulus. In the separation from and reunion with the owner dogs’ eye temperature and mean HR did not vary neither in the stressful nor in the positive situations, RMSSD increased after the positive episode, SDNN dropped during the two stimulations and it increased after the stimulations. During the separation from the owner dogs were mainly directed to the door or to the experimenter while during the reunion with the owner dogs were focused mainly on the owner and on the environment, exhibiting safe base effect. A different approach was used to assess the welfare of shelter dogs. Dogs were implanted with a telemeter and after implantation dogs were housed in sequence in four different situations lasting 1 week: alone, alone with toys and a stretch cot for sleeping, with an unknown, spayed, female, and alone with a daily 2-hours interaction with an experimenter. Two different approaches were tried: partially random extracted fragments from every week, behaviors from 8 a.m. to 4 p.m. were continuous during baseline and the female situation. Results showed different reactions by dogs to the different situations and interestingly not all enrichments were enjoyed by the dogs improving their welfare. Overall results suggest that IRT may represent a useful tool to investigate emotional reactions in dogs. Nevertheless, further research is needed to establish the specificity and sensivity of IRT in this context and to assess how different dogs’ characteristics, breed, previous experience and the valence and arousal elicited by the stimulus could influence the magnitude and type of the response. The role of HRV in understanding emotional valence and the one of telemeters in understanding long-term effects on sheltered dogs’ welfare is also discussed.

bioNMF: a versatile tool for non-negative matrix factorization in biology

Medical imaging has become an absolutely essential diagnostic tool for clinical practices; at present, pathologies can be detected with an earliness never before known. Its use has not only been relegated to the field of radiology but also, increasingly, to computer-based imaging processes prior to surgery. Motion analysis, in particular, plays an important role in analyzing activities or behaviors of live objects in medicine. This short paper presents several low-cost hardware implementation approaches for the new generation of tablets and/or smartphones for estimating motion compensation and segmentation in medical images. These systems have been optimized for breast cancer diagnosis using magnetic resonance imaging technology with several advantages over traditional X-ray mammography, for example, obtaining patient information during a short period. This paper also addresses the challenge of offering a medical tool that runs on widespread portable devices, both on tablets and/or smartphones to aid in patient diagnostics.

The Impact of Transit Oriented Development on the Travel Behaviors of Workers in Denver, Colorado

To combat unsustainable transportation systems characterized by reliance on petroleum, polluting emissions, traffic congestion and suburban sprawl, planners encourage mixed use, densely populated areas that provide individuals with opportunities to live, work, eat and shop without necessarily having to drive private automobiles to accommodate their needs. Despite these attempts, the frequency and duration of automobile trips has consistently increased in the United States throughout past decades. While many studies have focused on how residential proximity to transit influences travel behavior, the effect of workplace location has largely been ignored. This paper asks, does working near a TOD influence the travel behaviors of workers differently than workers living near a TOD? We examine the non-work travel behaviors of workers based upon their commuting mode and proximity to TODs. The data came from a 2009 travel behavior survey by the Denver Regional Council of Governments, which contains 8,000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-automobile transportation. The results of this study indicate that closer proximity of both households and workplaces to TODs decrease levels of car commuting and that non-car commuting leads to more sustainable personal travel behaviors characterized by more trips made with alternative modes.

The role of the social environment in non-suicidal self-injury among LGBTQ youth: A mixed methods study

Non-suicidal self-injury (NSSI), such as cutting and burning, is a widespread social problem among lesbian, gay, bisexual, transgender, queer, and questioning (LGBTQ) youth. Extant research indicates that this population is more than twice as likely to engage in NSSI than heterosexual and cisgender (non-transgender) youth. Despite the scope of this social problem, it remains relatively unexamined in the literature. Research on other risk behaviors among LGBTQ youth indicates that experiencing homophobia and transphobia in key social contexts such as families, schools, and peer relationships contributes to health disparities among this group. Consequently, the aims of this study were to examine: (1) the relationship between LGBTQ youth's social environments and their NSSI behavior, and (2) whether/how specific aspects of the social environment contribute to an understanding of NSSI among LGBTQ youth. This study was conducted using an exploratory, sequential mixed methods design with two phases. The first phase of the study involved analysis of transcripts from interviews conducted with 44 LGBTQ youth recruited from a community-based organization. In this phase, five qualitative themes were identified: (1) Violence; (2) Misconceptions, Stigma, and Shame; (3) Negotiating LGBTQ Identity; (4) Invisibility and Isolation; and (5) Peer Relationships. Results from the qualitative phase were used to identify key variables and specify statistical models in the second, quantitative, phase of the study, using secondary data from a survey of 252 LGBTQ youth. The qualitative phase revealed how LGBTQ youth, themselves, described the role of the social environment in their NSSI behavior, while the quantitative phase was used to determine whether the qualitative findings could be used to predict engagement in NSSI among a larger sample of LGBTQ youth. The quantitative analyses found that certain social-environmental factors such as experiencing physical abuse at home, feeling unsafe at school, and greater openness about sexual orientation significantly predicted the likelihood of engaging in NSSI among LGBTQ youth. Furthermore, depression partially mediated the relationships between family physical abuse and NSSI and feeling unsafe at school and NSSI. The qualitative and quantitative results were compared in the interpretation phase to explore areas of convergence and incongruence. Overall, this study's findings indicate that social-environmental factors are salient to understanding NSSI among LGBTQ youth. The particular social contexts in which LGBTQ youth live significantly influence their engagement in this risk behavior. These findings can inform the development of culturally relevant NSSI interventions that address the social realities of LGBTQ youth's lives.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Modeling magnetar outbursts: flux enhancements and the connection with short bursts and glitches

The availability of a large amount of observational data recently collected from magnetar outbursts is now calling for a complete theoretical study of outburst characteristics. In this Letter (the first of a series dedicated to modeling magnetar outbursts), we tackle the long-standing open issue of whether or not short bursts and glitches are always connected to long-term radiative outbursts. We show that the recent detection of short bursts and glitches seemingly unconnected to outbursts is only misleading our understanding of these events. We show that, in the framework of the starquake model, neutrino emission processes in the magnetar crust limit the temperature, and therefore the luminosity. This natural limit to the maximum luminosity makes outbursts associated with bright persistent magnetars barely detectable. These events are simply seen as a small luminosity increase over the already bright quiescent state, followed by a fast return to quiescence. In particular, this is the case for 1RXS J1708–4009, 1E 1841–045, SGR 1806–20, and other bright persistent magnetars. On the other hand, a similar event (with the same energetics) in a fainter source will drive a more extreme luminosity variation and longer cooling time, as for sources such as XTE J1810–197, 1E 1547–5408, and SGR 1627–41. We conclude that the non-detection of large radiative outbursts in connection with glitches and bursts from bright persistent magnetars is not surprising per se, nor does it need any revision of the glitches and burst mechanisms as explained by current theoretical models.

Overcoming performance and convergence issues of discrete transform based modeling of crosslinking classical and reversible deactivated radical polymerizations

Population balances of polymer species in terms 'of discrete transforms with respect to counts of groups lead to tractable first order partial differential equations when ali rate constants are independent of chain length and loop formation is negligible [l]. Average molecular weights in the absence ofgelation are long known to be readily found through integration of an initial value problem. The extension to size distribution prediction is also feasible, but its performance is often lower to the one provided by methods based upon real chain length domain [2]. Moreover, the absence ofagood starting procedure and a higher numerical sensitivity hás decisively impaired its application to non-linear reversibly deactivated polymerizations, namely NMRP [3].

Physical characterization and numerical modeling of a WEST-like tokamak divertor plasma

Il presente elaborato è incentrato sulla modellizzazione del plasma di bordo nei dispositivi per la produzione di energia da fusione nucleare noti come tokamak. La tecnologia che nel corso di tutta la seconda metà del XX secolo fino ad oggi è stata sviluppata a questo fine deve necessariamente scontrarsi con alcuni limiti. Nei tokamak il confinamento del plasma è di tipo magnetico e vincola le particelle a muoversi di moto elicoidale all'interno del vessel, tuttavia il confinamento non risulta perfetto e parte dell'energia si scarica sulle pareti della camera, rischiando pertanto di fondere i materiali. Alcune strategie possono essere messe in atto per limitare questo problema, per esempio agendo sulla geometria del tokamak, oppure sulla fisica, inducendo nel plasma una data concentrazione di impurezze che ionizzino irraggiando parte dell'energia di plasma. Proprio tale meccanismo di perdita è stato simulato in un modello monodimensionale di plasma monofluido di bordo. I risultati del codice numerico relativo al modello dimostrano che per concentrazioni di impurezze crescenti è possibile diminuire in modo significativo flusso di calore e temperatura al divertore. Per di più risulta possibile controllare la posizione del fronte di irraggiamento per mezzo di parametri di controllo del plasma quali la pressione. Si osserva inoltre l'insorgere del cosiddetto fenomeno di biforcazione alle basse temperature di divertore, fenomeno in cui il plasma si comporta in modo instabile a causa di fenomeni fisici tipici delle basse energie ("detachment") e a seguito del quale può improvvisamente spegnersi (disruzione). Infine lo stesso modello è stato migliorato inserendo l'ipotesi di plasma bifluido. Anche per gli ioni viene osservato il fenomeno di biforcazione. I risultati numerici evidenziano le dinamiche dello scambio energetico fra le specie gettando le basi di una progettazione efficiente della chimica del plasma finalizzata al raffreddamento del divertore.

Accounting for residential and non-residential environments to measure contextual effects on health behavior : the case of recreational walking behavior

Thèse réalisée en cotutelle entre l'Université de Montréal et l'Université Pierre et Marie Curie, Paris 06, Sorbonne Universités.

Disturbances of agency and ownership in schizophrenia: An auditory verbal event related potentials study

A ‘sense of self’ is essentially the ability to distinguish between self-generated and external stimuli. It consists of at least two very basic senses: a sense of agency and a sense of ownership. Disturbances seem to provide a basic deficit in many psychiatric diseases. The aim of our study was to manipulate those qualities separately in 28 patients with schizophrenia (14 auditory hallucinators and 14 non-hallucinators) and 28 healthy controls (HC) and to investigate the effects on the topographies and the power of the event-related potential (ERP). We performed a 76-channel EEG while the participants performed the task as in our previous paper. We computed ERPs and difference maps for the conditions and compared the amount of agency and ownership between the HC and the patients. Furthermore, we compared the global field power and the topographies of these effects. Our data showed effects of agency and ownership in the healthy controls and the hallucinator group and to a lesser degree in the non-hallucinator group. We found a reduction of the N100 during the presence of agency, and a bilateral temporal negativity related to the presence of ownership. For the agency effects, we found significant differences between HC and the patients. Contrary to the expectations, our findings were more pronounced in non-hallucinators, suggesting a more profoundly disturbed sense of agency compared to hallucinators. A contemporary increase of global field power in both patient groups indicates a compensatory recruitment of other mechanisms not normally associated with the processing of agency and ownership.

Affective Commitment and Job Satisfaction among Non-family Employees: Investigating the Roles of Justice Perceptions and Psychological Ownership

Due to numerous characteristics often attributed to family firms, they constitute a unique context for non-family employees’ justice perceptions. These are linked to non-family employees’ pro-organizational attitudes and behaviors, which are essential for family firms’ success. Even though scholarly interest in non-family employees’ justice perceptions has increased, more research is still needed, also because the mechanism connecting justice perceptions and favorable outcomes is not fully understood yet. We address this gap by explicitly investigating non-family employees’ justice perceptions and by introducing psychological ownership as a mediator in the relationships between justice perceptions (distributive and procedural) and common work attitudes (affective commitment and job satisfaction). Our analysis of a sample of 310 non-family employees from Germany and German-speaking Switzerland reveals that psychological ownership mediates the relationships between distributive justice and affective commitment as well as job satisfaction. This represents valuable contributions to family business research, organizational justice and psychological ownership literature, and to practice.