Unpacking insanity defence standards: an experimental study of rationality and control tests in criminal law

The present study investigated the impact of different legal standards on mock juror decisions concerning whether a defendant was guilty or not guilty by reason of insanity. Undergraduate students (N = 477) read a simulated case summary involving a murder case and were asked to make an insanity determination. The cases differed in terms of the condition of the defendant (rationality deficit or control deficit) and the legal standard given to the jurors to make the determination (Model Penal Code, McNaughten or McNaughten plus a separate control determination). The effects of these variables on the insanity determination were investigated. Jurors also completed questionnaires measuring individualism and hierarchy attitudes and perceptions of facts in the case. Results indicate that under current insanity standards jurors do not distinguish between defendants with rationality deficits and defendants with control deficits regardless of whether the legal standard requires them to do so. Even defendants who lacked control were found guilty at equal rates under a legal standard excusing rationality deficits only and a legal standard excluding control and rationality deficits. This was improved by adding a control test as a partial defence, to be determined after a rationality determination. Implications for the insanity defence in the Criminal Justice System are discussed.

Brain emotional learning based control of a SDOF structural system with a MR damper

This paper describes the application of a Brain Emotional Learning (BEL) controller to improve the response of a SDOF structural system under an earthquake excitation using a magnetorheological (MR) damper. The main goal is to study the performance of a BEL based semi-active control system to generate the control signal for a MR damper. The proposed approach consists of a two controllers: a primary controller based on a BEL algorithm that determines the desired damping force from the system response and a secondary controller that modifies the input current to the MR damper to generate a reference damping force. A parametric model of the damper is used to predict the damping force based on the piston motion and also the current input. A Simulink model of the structural system is developed to analyze the effectiveness of the semi-active controller. Finally, the numerical results are presented and discussed.

Towards a predictive model of Ca²⁺ puffs

We investigate key characteristics of Ca²⁺ puffs in deterministic and stochastic frameworks that all incorporate the cellular morphology of IP[subscript]3 receptor channel clusters. In a first step, we numerically study Ca²⁺ liberation in a three dimensional representation of a cluster environment with reaction-diffusion dynamics in both the cytosol and the lumen. These simulations reveal that Ca²⁺ concentrations at a releasing cluster range from 80 µM to 170 µM and equilibrate almost instantaneously on the time scale of the release duration. These highly elevated Ca²⁺ concentrations eliminate Ca²⁺ oscillations in a deterministic model of an IP[subscript]3R channel cluster at physiological parameter values as revealed by a linear stability analysis. The reason lies in the saturation of all feedback processes in the IP[subscript]3R gating dynamics, so that only fluctuations can restore experimentally observed Ca²⁺ oscillations. In this spirit, we derive master equations that allow us to analytically quantify the onset of Ca²⁺ puffs and hence the stochastic time scale of intracellular Ca²⁺ dynamics. Moving up the spatial scale, we suggest to formulate cellular dynamics in terms of waiting time distribution functions. This approach prevents the state space explosion that is typical for the description of cellular dynamics based on channel states and still contains information on molecular fluctuations. We illustrate this method by studying global Ca²⁺ oscillations.

Mesoscale Optoelectronic Design of Wire-Based Photovoltaic and Photoelectrochemical Devices

The overarching theme of this thesis is mesoscale optical and optoelectronic design of photovoltaic and photoelectrochemical devices. In a photovoltaic device, light absorption and charge carrier transport are coupled together on the mesoscale, and in a photoelectrochemical device, light absorption, charge carrier transport, catalysis, and solution species transport are all coupled together on the mesoscale. The work discussed herein demonstrates that simulation-based mesoscale optical and optoelectronic modeling can lead to detailed understanding of the operation and performance of these complex mesostructured devices, serve as a powerful tool for device optimization, and efficiently guide device design and experimental fabrication efforts. In-depth studies of two mesoscale wire-based device designs illustrate these principles—(i) an optoelectronic study of a tandem Si|WO3 microwire photoelectrochemical device, and (ii) an optical study of III-V nanowire arrays.

The study of the monolithic, tandem, Si|WO3 microwire photoelectrochemical device begins with development and validation of an optoelectronic model with experiment. This study capitalizes on synergy between experiment and simulation to demonstrate the model’s predictive power for extractable device voltage and light-limited current density. The developed model is then used to understand the limiting factors of the device and optimize its optoelectronic performance. The results of this work reveal that high fidelity modeling can facilitate unequivocal identification of limiting phenomena, such as parasitic absorption via excitation of a surface plasmon-polariton mode, and quick design optimization, achieving over a 300% enhancement in optoelectronic performance over a nominal design for this device architecture, which would be time-consuming and challenging to do via experiment.

The work on III-V nanowire arrays also starts as a collaboration of experiment and simulation aimed at gaining understanding of unprecedented, experimentally observed absorption enhancements in sparse arrays of vertically-oriented GaAs nanowires. To explain this resonant absorption in periodic arrays of high index semiconductor nanowires, a unified framework that combines a leaky waveguide theory perspective and that of photonic crystals supporting Bloch modes is developed in the context of silicon, using both analytic theory and electromagnetic simulations. This detailed theoretical understanding is then applied to a simulation-based optimization of light absorption in sparse arrays of GaAs nanowires. Near-unity absorption in sparse, 5% fill fraction arrays is demonstrated via tapering of nanowires and multiple wire radii in a single array. Finally, experimental efforts are presented towards fabrication of the optimized array geometries. A hybrid self-catalyzed and selective area MOCVD growth method is used to establish morphology control of GaP nanowire arrays. Similarly, morphology and pattern control of nanowires is demonstrated with ICP-RIE of InP. Optical characterization of the InP nanowire arrays gives proof of principle that tapering and multiple wire radii can lead to near-unity absorption in sparse arrays of InP nanowires.

REAL TIME FUZZY CONTROLLER FOR QUADROTOR STABILITY CONTROL

In this report, we develop an intelligent adaptive neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. An analysis is made into the choice of filters for attitude estimation. These choices are limited by the complexity of the filter and the computing ability and memory constraints of the micro-controller. Simplified Kalman filters are found to be good at estimation of attitude given the above constraints. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers. We then use a combination of the code generation capabilities within MATLAB/Simulink in combination with multiple open-source projects in order to deploy code to an ARM CortexM4 based controller board. We also evaluate this strategy on an ARM-A8 based board, and a much less powerful Arduino based flight controller. We conclude by proving the feasibility of fuzzy controllers on Commercial-off the shelf (COTS) hardware, we also point out the limitations in the current hardware and make suggestions for hardware that we think would be better suited for memory heavy controllers.

Advanced 4DT flight guidance and control software system

The work presented in this thesis has been part of a Cranfield University research project. This thesis aims to design a flight control law for large cargo aircraft by using predictive control, which can assure flight motion along the flight path exactly and on time. In particular this work involves the modelling of a Boeing C-17 Globemaster III 6DOF model (used as study case), by using DATCOM and Matlab Simulink software. Then a predictive control algorithm has been developed. The majority of the work is done in a Matlab/Simulink environment. Finally the predictive control algorithm has been applied on the aircraft model and its performances, in tracking given trajectory optimized through a 4DT Research Software, have been evaluated.

Development of an innovative non rule-based energy management strategy for a Hybrid Electric Vehicle, structured for predictive driving controls based on external information knowledge

Recently, the interest of the automotive market for hybrid vehicles has increased due to the more restrictive pollutants emissions legislation and to the necessity of decreasing the fossil fuel consumption, since such solution allows a consistent improvement of the vehicle global efficiency. The term hybridization regards the energy flow in the powertrain of a vehicle: a standard vehicle has, usually, only one energy source and one energy tank; instead, a hybrid vehicle has at least two energy sources. In most cases, the prime mover is an internal combustion engine (ICE) while the auxiliary energy source can be mechanical, electrical, pneumatic or hydraulic. It is expected from the control unit of a hybrid vehicle the use of the ICE in high efficiency working zones and to shut it down when it is more convenient, while using the EMG at partial loads and as a fast torque response during transients. However, the battery state of charge may represent a limitation for such a strategy. That’s the reason why, in most cases, energy management strategies are based on the State Of Charge, or SOC, control. Several studies have been conducted on this topic and many different approaches have been illustrated. The purpose of this dissertation is to develop an online (usable on-board) control strategy in which the operating modes are defined using an instantaneous optimization method that minimizes the equivalent fuel consumption of a hybrid electric vehicle. The equivalent fuel consumption is calculated by taking into account the total energy used by the hybrid powertrain during the propulsion phases. The first section presents the hybrid vehicles characteristics. The second chapter describes the global model, with a particular focus on the energy management strategies usable for the supervisory control of such a powertrain. The third chapter shows the performance of the implemented controller on a NEDC cycle compared with the one obtained with the original control strategy.

Health beliefs affect the correct replacement of daily disposable contact lenses:predicting compliance with the Health Belief Model and the Theory of Planned Behaviour

Purpose: To assess the compliance of Daily Disposable Contact Lenses (DDCLs) wearers with replacing lenses at a manufacturer-recommended replacement frequency. To evaluate the ability of two different Health Behavioural Theories (HBT), The Health Belief Model (HBM) and The Theory of Planned Behaviour (TPB), in predicting compliance. Method: A multi-centre survey was conducted using a questionnaire completed anonymously by contact lens wearers during the purchase of DDCLs. Results: Three hundred and fifty-four questionnaires were returned. The survey comprised 58.5% females and 41.5% males (mean age 34. ±. 12. years). Twenty-three percent of respondents were non-compliant with manufacturer-recommended replacement frequency (re-using DDCLs at least once). The main reason for re-using DDCLs was "to save money" (35%). Predictions of compliance behaviour (past behaviour or future intentions) on the basis of the two HBT was investigated through logistic regression analysis: both TPB factors (subjective norms and perceived behavioural control) were significant (p. <. 0.01); HBM was less predictive with only the severity (past behaviour and future intentions) and perceived benefit (only for past behaviour) as significant factors (p. <. 0.05). Conclusions: Non-compliance with DDCLs replacement is widespread, affecting 1 out of 4 Italian wearers. Results from the TPB model show that the involvement of persons socially close to the wearers (subjective norms) and the improvement of the procedure of behavioural control of daily replacement (behavioural control) are of paramount importance in improving compliance. With reference to the HBM, it is important to warn DDCLs wearers of the severity of a contact-lens-related eye infection, and to underline the possibility of its prevention.

Stress-testing centralised model stores

One of the current challenges in model-driven engineering is enabling effective collaborative modelling. Two common approaches are either storing the models in a central repository, or keeping them under a traditional file-based version control system and build a centralized index for model-wide queries. Either way, special attention must be paid to the nature of these repositories and indexes as networked services: they should remain responsive even with an increasing number of concurrent clients. This paper presents an empirical study on the impact of certain key decisions on the scalability of concurrent model queries, using an Eclipse Connected Data Objects model repository and a Hawk model index. The study evaluates the impact of the network protocol, the API design and the internal caching mechanisms and analyzes the reasons for their varying performance.

Challenges in imaging and predictive modeling of rhizosphere processes

Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes.

Entrepreneurship: a long way to go

Entrepreneurship education has emerged as one popular research domain in academic fields given its aim at enhancing and developing certain entrepreneurial qualities of undergraduates that change their state of behavior, even their entrepreneurial inclination and finally may result in the formation of new businesses as well as new job opportunities. This study attempts to investigate the Colombian student´s entrepreneurial qualities and the influence of entrepreneurial education during their studies.

Factores asociados a respuesta de abatacept subcutaneo en artritis reumatoide

INTRODUCCION Dado que la artritis reumatoide es la artropatía inflamatoria más frecuente en el mundo, siendo altamente discapacitante y causando gran impacto de alto costo, se busca ofrecer al paciente opciones terapéuticas y calidad de vida a través del establecimiento de un tratamiento oportuno y eficaz, teniendo presentes aquellos predictores de respuesta previo a instaurar determinada terapia. Existen pocos estudios que permitan establecer aquellos factores de adecuada respuesta para inicio de terapia biológica con abatacept, por lo cual en este estudio se busca determinar cuáles son esos posibles factores. METODOLOGIA Estudio analítico de tipo corte transversal de 94 pacientes con diagnóstico de AR, evaluados para determinar las posibles variables que influyen en la respuesta a terapia biológica con abatacept. Se incluyeron 67 de los 94 pacientes al modelo de regresión logística, que son aquellos pacientes en que fue posible medir la respuesta al tratamiento (respuesta EULAR) a través de la determinación del DAS 28 y así discriminar en dos grupos de comparación (respuesta y no respuesta). DISCUSION DE RESULTADOS La presencia de alta actividad de la enfermedad al inicio de la terapia biológica, aumenta la probabilidad de respuesta al tratamiento respecto al grupo con baja/moderada actividad de la enfermedad; OR 4,19 - IC 95%(1,18 – 14.9), (p 0,027). La ausencia de erosiones óseas aumenta la probabilidad de presentar adecuada respuesta a la terapia biológica respecto aquellos con erosiones, con un OR 3,1 (1,01-9,55), (p 0,048). Niveles de VSG y presencia de manifestaciones extra-articulares son otros datos de interés encontrados en el análisis bivariado. Respecto a las variables o características como predictores de respuesta al tratamiento con abatacept, se encuentran estudios que corroboran los hallazgos de este estudio, respecto al alto puntaje del DAS 28 al inicio de la terapia (9, 12). CONCLUSIONES Existen distintas variables que determinan la respuesta a los diferentes biológicos para manejo de AR. Es imprescindible evaluar dichos factores de manera individual con el fin de lograr de manera efectiva el control de la enfermedad y así mejorar la calidad de vida del individuo (medicina personalizada). Existen variables tales como la alta actividad de la enfermedad y la ausencia de erosiones como predictores de respuesta en la terapia con abatacept.

Factores de riesgo preoperatorios asociados a conversión a técnica abierta en colecistectomía laparoscópica de urgencia

Introducción: la colecistectomía laparoscópica es la técnica de elección en pacientes con indicación de extracción quirúrgica de la vesícula; sin embargo, en promedio 20% de éstos requieren conversión a técnica abierta. En este estudio se evaluaron los factores de riesgo preoperatorios para conversión en colecistectomía laparoscópica de urgencia. Metodología: se realizó un estudio de casos y controles no pareado. Se obtuvo información sociodemográfica y de variables de interés de los registros de historias clínicas de pacientes operados entre el 2013 y 2016. Se identificaron los motivos de conversión de técnica quirúrgica. Se caracterizó la población de estudio y se estimaron asociaciones según la naturaleza de las variables. Mediante un análisis de regresión logística se ajustaron posibles variables de confusión. Resultados: se analizaron los datos de 444 pacientes (111 casos y 333 controles). La causa de conversión más frecuente fue la dificultad técnica (50,5%). Se encontró que la mayor edad, el sexo masculino, el antecedente de cirugía abierta en hemiabdomen superior, el signo de Murphy clínico positivo, la dilatación de la vía biliar, la leucocitosis y la mayor experiencia del cirujano, fueron factores de riesgo para conversión. Se encontró un área bajo la curva ROC= 0,743 (IC95% 0,692–0,794, p= <0,001). Discusión: existen unos factores que se asocian a mayor riesgo de conversión en colecistectomía laparoscópica. La mayoría se relacionan con un proceso inflamatorio más severo, por lo que se debe evitar la prolongación del tiempo de espera entre el inicio de los síntomas y la extirpación quirúrgica de la vesícula.

Blade pitch control malfunction simulation in a wind energy conversion system with MPC five-level converter

This paper is on a wind energy conversion system simulation of a transient analysis due to a blade pitch control malfunction. The aim of the transient analysis is the study of the behavior of a back-to-back multiple point clamped five-level full-power converter implemented in a wind energy conversion system equipped with a permanent magnet synchronous generator. An alternate current link connects the system to the grid. The drive train is modeled by a three-mass model in order to simulate the dynamic effect of the wind on the tower. The control strategy is based on fractional-order control. Unbalance voltages in the DC-link capacitors are lessen due to the control strategy, balancing the capacitor banks voltages by a selection of the output voltage vectors. Simulation studies are carried out to evaluate not only the system behavior, but also the quality of the energy injected into the electric grid.

Distributed non-cooperative robust economic predictive control for dynamically coupled linear systems.

In this thesis, a tube-based Distributed Economic Predictive Control (DEPC) scheme is presented for a group of dynamically coupled linear subsystems. These subsystems are components of a large scale system and control inputs are computed based on optimizing a local economic objective. Each subsystem is interacting with its neighbors by sending its future reference trajectory, at each sampling time. It solves a local optimization problem in parallel, based on the received future reference trajectories of the other subsystems. To ensure recursive feasibility and a performance bound, each subsystem is constrained to not deviate too much from its communicated reference trajectory. This difference between the plan trajectory and the communicated one is interpreted as a disturbance on the local level. Then, to ensure the satisfaction of both state and input constraints, they are tightened by considering explicitly the effect of these local disturbances. The proposed approach averages over all possible disturbances, handles tightened state and input constraints, while satisfies the compatibility constraints to guarantee that the actual trajectory lies within a certain bound in the neighborhood of the reference one. Each subsystem is optimizing a local arbitrary economic objective function in parallel while considering a local terminal constraint to guarantee recursive feasibility. In this framework, economic performance guarantees for a tube-based distributed predictive control (DPC) scheme are developed rigorously. It is presented that the closed-loop nominal subsystem has a robust average performance bound locally which is no worse than that of a local robust steady state. Since a robust algorithm is applying on the states of the real (with disturbances) subsystems, this bound can be interpreted as an average performance result for the real closed-loop system. To this end, we present our outcomes on local and global performance, illustrated by a numerical example.