Criminal achievement and offender self-efficacy

La notion de réussite criminelle a essentiellement été définie au moyen de l’indicateur objectif des gains monétaires. Si l’idée selon laquelle l’argent est au coeur de la réussite professionnelle fait l’objet d’un large consensus social, il semble improbable que les gains monétaires permettent à eux seuls d’appréhender la réussite. Pour mieux comprendre certaines dimensions des carrières criminelles telles que la persistance et le désistement, il paraît utile de se pencher sur la manière dont les criminels définissent leur propre réussite. Il a été établi que l’auto-efficacité, soit la croyance que possède un individu en sa capacité à accomplir une tâche, permet de prédire plusieurs dimensions des carrières légitimes. À partir de la théorie sur l’auto-efficacité, ce mémoire examine de quelle manière se forme l’auto-efficacité criminelle. Nous soutenons que les perceptions relatives à la réussite criminelle sont affectées par des facteurs semblables à ceux qui jouent dans le développement de l’auto-efficacité légitime. Nous partons de l’hypothèse que les criminels forgent leur auto-efficacité à partir de quatre sources d’expérience : les réussites personnelles, l’apprentissage vicariant, la persuasion sociale et les états physiologiques. Il est également avancé que certaines caractéristiques individuelles et environnementales ont un impact significatif sur le développement de l’auto-efficacité criminelle. Sur la base d’entrevues auprès de 212 délinquants, nos résultats indiquent que l’auto-efficacité criminelle est une construction complexe fondée sur les caractéristiques individuelles et environnementales, ainsi que sur les expériences criminelles personnelles. Nous discutons de l’impact éventuel de ces conclusions sur l’appréhension de la persévérance et du désistement dans les carrières criminelles.

Molecular mechanisms underlying deficient neurogenesis in Alzheimer’s disease

La neurogenèse est présente, dans le cerveau adulte, dans la zone sous-ventriculaire (ZSV) encadrant les ventricules latéraux et dans le gyrus dentelé (GD) de l’hippocampe, permettant l’apprentissage, la mémoire et la fonction olfactive. Ces micro-environnements possèdent des signaux contrôlant l’auto-renouvellement des cellules souches neurales (CSN), leur prolifération, leur destin et leur différenciation. Or, lors du vieillissement, les capacités régénératives et homéostatiques et la neurogenèse déclinent. Les patients atteints de la maladie d’Alzheimer (MA), comme le modèle animal reproduisant cette maladie (3xTg-AD), montrent une accélération des phénotypes liés au vieillissement dont une diminution de la neurogenèse. Notre hypothèse est que la découverte des mécanismes affectant la neurogenèse, lors du vieillissement et de la MA, pourrait fournir de nouvelles cibles thérapeutiques pour prévenir le déclin cognitif. Les études sur l’âge d’apparition et les mécanismes altérant la neurogenèse dans la MA sont contrastées et nous ont guidé vers deux études. L’examen des changements dans les étapes de la neurogenèse lors du vieillissement et du développement de la neuropathologie. Nous avons étudié la ZSV, les bulbes olfactifs et le GD de souris femelles de 11 et 18 mois, et l’apparition des deux pathologies associées à la MA : les plaques amyloïdes et les enchevêtrements neurofibrillaires. Nous avons découvert que les souris 3xTg-AD possèdent moins de cellules en prolifération, de progéniteurs et de neuroblastes, induisant une diminution de l’intégration de nouvelles cellules dans le GD et les bulbes olfactifs. Notons que le taux de neurogenèse chez ces souris de 11 mois est similaire à celui des souris de phénotype sauvage de 18 mois, indiquant une accélération des changements liés au vieillissement dans la MA. Dans la ZSV, nous avons aussi démontré une accumulation de gouttelettes lipidiques, suggérant des changements dans l’organisation et le métabolisme de la niche. Enfin, nous avons démontré que le déficit de la neurogenèse apparait lors des premières étapes de la MA, avant l’apparition des plaques amyloïdes et des enchevêtrements neurofibrillaires. A l’examen des mécanismes inhibant la neurogenèse lors de la MA, nous voyons que chez des souris de 5 mois, le déficit de la neurogenèse dans la ZSV et le GD est corrélé avec l’accumulation de lipides, qui coïncide avec l’apparition du déclin cognitif. Nous avons aussi découvert que dans le cerveau humain de patients atteints de la MA et dans les 3xTg-AD, des gouttelettes lipidiques s’accumulaient dans les cellules épendymaires, représentant le principal soutien des CSN de la niche. Ces lipides sont des triglycérides enrichis en acide oléique qui proviennent de la niche et pas d’une défaillance du système périphérique. De plus, l’infusion locale d’acide oléique chez des souris de phénotype sauvage permet de reproduire l’accumulation de triglycérides dans les cellules épendymaires, comme dans la MA. Ces gouttelettes induisent un dérèglement de la voie de signalisation Akt-FoxO3 dans les CSN, menant à l’inhibition de leur activation in vitro et in vivo. Ces résultats permettent une meilleure compréhension de la régulation de la neurogenèse par le métabolisme lipidique. Nous avons démontré un nouveau mécanisme par lequel l’accumulation des lipides dans la ZSV induit une inhibition des capacités de prolifération et de régénération des CSN lors de la MA. Les travaux futurs permettront de comprendre comment et pourquoi le métabolisme lipidique du cerveau est altéré dans la MA, ce qui pourrait offrir de nouvelles voies thérapeutiques pour la prévention et la régénération.

Enhanced dopamine D2 receptor function in hypothalamus and corpus striatum: their role in liver, plasma and in vitro hepatocyte ALDH regulation in ethahol treated rats

Dopamine D2 receptors are involved in ethanol self- administration behavior and also suggested to mediate the onset and offset of ethanol drinking. In the present study, we investigated dopamine (DA) content and Dopamine D2 (DA D2) receptors in the hypothalamus and corpus striatum of ethanol treated rats and aldehyde dehydrogenase (ALDH) activity in the liver and plasma of ethanol treated rats and in vitro hepatocyte cultures. Hypothalamic and corpus striatal DA content decreased significantly (P\0.05, P\0.001 respectively) and homovanillic acid/ dopamine (HVA/DA) ratio increased significantly (P\0.001) in ethanol treated rats when compared to control. Scatchard analysis of [3H] YM-09151-2 binding to DA D2 receptors in hypothalamus showed a significant increase (P\0.001) in Bmax without any change in Kd in ethanol treated rats compared to control. The Kd of DA D2 receptors significantly decreased (P\0.05) in the corpus striatum of ethanol treated rats when compared to control. DA D2 receptor affinity in the hypothalamus and corpus striatum of control and ethanol treated rats fitted to a single site model with unity as Hill slope value. The in vitro studies on hepatocyte cultures showed that 10-5 M and 10-7 M DA can reverse the increased ALDH activity in 10% ethanol treated cells to near control level. Sulpiride, an antagonist of DA D2, reversed the effect of dopamine on 10% ethanol induced ALDH activity in hepatocytes. Our results showed a decreased dopamine concentration with enhanced DA D2 receptors in the hypothalamus and corpus striatum of ethanol treated rats. Also, increased ALDH was observed in the plasma and liver of ethanol treated rats and in vitro hepatocyte cultures with 10% ethanol as a compensatory mechanism for increased aldehyde production due to increased dopamine metabolism. A decrease in dopamine concentration in major brain regions is coupled with an increase in ALDH activity in liver and plasma, which contributes to the tendency for alcoholism. Since the administration of 10-5 M and 10-7 M DA can reverse the increased ALDH activity in ethanol treated cells to near control level, this has therapeutic application to correct ethanol addicts from addiction due to allergic reaction observed in aldehyde accumulation.

Identification of Problem-based learning components and their effects on graduates' competencies

This study investigated the relationship between higher education and the requirement of the world of work with an emphasis on the effect of problem-based learning (PBL) on graduates' competencies. The implementation of full PBL method is costly (Albanese & Mitchell, 1993; Berkson, 1993; Finucane, Shannon, & McGrath, 2009). However, the implementation of PBL in a less than curriculum-wide mode is more achievable in a broader context (Albanese, 2000). This means higher education institutions implement only a few PBL components in the curriculum. Or a teacher implements a few PBL components at the courses level. For this kind of implementation there is a need to identify PBL components and their effects on particular educational outputs (Hmelo-Silver, 2004; Newman, 2003). So far, however there has been little research about this topic. The main aims of this study were: (1) to identify each of PBL components which were manifested in the development of a valid and reliable PBL implementation questionnaire and (2) to determine the effect of each identified PBL component to specific graduates' competencies. The analysis was based on quantitative data collected in the survey of medicine graduates of Gadjah Mada University, Indonesia. A total of 225 graduates responded to the survey. The result of confirmatory factor analysis (CFA) showed that all individual constructs of PBL and graduates' competencies had acceptable GOFs (Goodness-of-fit). Additionally, the values of the factor loadings (standardize loading estimates), the AVEs (average variance extracted), CRs (construct reliability), and ASVs (average shared squared variance) showed the proof of convergent and discriminant validity. All values indicated valid and reliable measurements. The investigation of the effects of PBL showed that each PBL component had specific effects on graduates' competencies. Interpersonal competencies were affected by Student-centred learning (β = .137; p < .05) and Small group components (β = .078; p < .05). Problem as stimulus affected Leadership (β = .182; p < .01). Real-world problems affected Personal and organisational competencies (β = .140; p < .01) and Interpersonal competencies (β = .114; p < .05). Teacher as facilitator affected Leadership (β = 142; p < .05). Self-directed learning affected Field-related competencies (β = .080; p < .05). These results can help higher education institution and educator to have informed choice about the implementation of PBL components. With this information higher education institutions and educators could fulfil their educational goals and in the same time meet their limited resources. This study seeks to improve prior studies' research method in four major ways: (1) by indentifying PBL components based on theory and empirical data; (2) by using latent variables in the structural equation modelling instead of using a variable as a proxy of a construct; (3) by using CFA to validate the latent structure of the measurement, thus providing better evidence of validity; and (4) by using graduate survey data which is suitable for analysing PBL effects in the frame work of the relationship between higher education and the world of work.

The Human in the Loop: User Participation in Self-Adaptive Software

Self-adaptive software provides a profound solution for adapting applications to changing contexts in dynamic and heterogeneous environments. Having emerged from Autonomic Computing, it incorporates fully autonomous decision making based on predefined structural and behavioural models. The most common approach for architectural runtime adaptation is the MAPE-K adaptation loop implementing an external adaptation manager without manual user control. However, it has turned out that adaptation behaviour lacks acceptance if it does not correspond to a user’s expectations – particularly for Ubiquitous Computing scenarios with user interaction. Adaptations can be irritating and distracting if they are not appropriate for a certain situation. In general, uncertainty during development and at run-time causes problems with users being outside the adaptation loop. In a literature study, we analyse publications about self-adaptive software research. The results show a discrepancy between the motivated application domains, the maturity of examples, and the quality of evaluations on the one hand and the provided solutions on the other hand. Only few publications analysed the impact of their work on the user, but many employ user-oriented examples for motivation and demonstration. To incorporate the user within the adaptation loop and to deal with uncertainty, our proposed solutions enable user participation for interactive selfadaptive software while at the same time maintaining the benefits of intelligent autonomous behaviour. We define three dimensions of user participation, namely temporal, behavioural, and structural user participation. This dissertation contributes solutions for user participation in the temporal and behavioural dimension. The temporal dimension addresses the moment of adaptation which is classically determined by the self-adaptive system. We provide mechanisms allowing users to influence or to define the moment of adaptation. With our solution, users can have full control over the moment of adaptation or the self-adaptive software considers the user’s situation more appropriately. The behavioural dimension addresses the actual adaptation logic and the resulting run-time behaviour. Application behaviour is established during development and does not necessarily match the run-time expectations. Our contributions are three distinct solutions which allow users to make changes to the application’s runtime behaviour: dynamic utility functions, fuzzy-based reasoning, and learning-based reasoning. The foundation of our work is a notification and feedback solution that improves intelligibility and controllability of self-adaptive applications by implementing a bi-directional communication between self-adaptive software and the user. The different mechanisms from the temporal and behavioural participation dimension require the notification and feedback solution to inform users on adaptation actions and to provide a mechanism to influence adaptations. Case studies show the feasibility of the developed solutions. Moreover, an extensive user study with 62 participants was conducted to evaluate the impact of notifications before and after adaptations. Although the study revealed that there is no preference for a particular notification design, participants clearly appreciated intelligibility and controllability over autonomous adaptations.

Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques

Die zunehmende Vernetzung der Informations- und Kommunikationssysteme führt zu einer weiteren Erhöhung der Komplexität und damit auch zu einer weiteren Zunahme von Sicherheitslücken. Klassische Schutzmechanismen wie Firewall-Systeme und Anti-Malware-Lösungen bieten schon lange keinen Schutz mehr vor Eindringversuchen in IT-Infrastrukturen. Als ein sehr wirkungsvolles Instrument zum Schutz gegenüber Cyber-Attacken haben sich hierbei die Intrusion Detection Systeme (IDS) etabliert. Solche Systeme sammeln und analysieren Informationen von Netzwerkkomponenten und Rechnern, um ungewöhnliches Verhalten und Sicherheitsverletzungen automatisiert festzustellen. Während signatur-basierte Ansätze nur bereits bekannte Angriffsmuster detektieren können, sind anomalie-basierte IDS auch in der Lage, neue bisher unbekannte Angriffe (Zero-Day-Attacks) frühzeitig zu erkennen. Das Kernproblem von Intrusion Detection Systeme besteht jedoch in der optimalen Verarbeitung der gewaltigen Netzdaten und der Entwicklung eines in Echtzeit arbeitenden adaptiven Erkennungsmodells. Um diese Herausforderungen lösen zu können, stellt diese Dissertation ein Framework bereit, das aus zwei Hauptteilen besteht. Der erste Teil, OptiFilter genannt, verwendet ein dynamisches "Queuing Concept", um die zahlreich anfallenden Netzdaten weiter zu verarbeiten, baut fortlaufend Netzverbindungen auf, und exportiert strukturierte Input-Daten für das IDS. Den zweiten Teil stellt ein adaptiver Klassifikator dar, der ein Klassifikator-Modell basierend auf "Enhanced Growing Hierarchical Self Organizing Map" (EGHSOM), ein Modell für Netzwerk Normalzustand (NNB) und ein "Update Model" umfasst. In dem OptiFilter werden Tcpdump und SNMP traps benutzt, um die Netzwerkpakete und Hostereignisse fortlaufend zu aggregieren. Diese aggregierten Netzwerkpackete und Hostereignisse werden weiter analysiert und in Verbindungsvektoren umgewandelt. Zur Verbesserung der Erkennungsrate des adaptiven Klassifikators wird das künstliche neuronale Netz GHSOM intensiv untersucht und wesentlich weiterentwickelt. In dieser Dissertation werden unterschiedliche Ansätze vorgeschlagen und diskutiert. So wird eine classification-confidence margin threshold definiert, um die unbekannten bösartigen Verbindungen aufzudecken, die Stabilität der Wachstumstopologie durch neuartige Ansätze für die Initialisierung der Gewichtvektoren und durch die Stärkung der Winner Neuronen erhöht, und ein selbst-adaptives Verfahren eingeführt, um das Modell ständig aktualisieren zu können. Darüber hinaus besteht die Hauptaufgabe des NNB-Modells in der weiteren Untersuchung der erkannten unbekannten Verbindungen von der EGHSOM und der Überprüfung, ob sie normal sind. Jedoch, ändern sich die Netzverkehrsdaten wegen des Concept drif Phänomens ständig, was in Echtzeit zur Erzeugung nicht stationärer Netzdaten führt. Dieses Phänomen wird von dem Update-Modell besser kontrolliert. Das EGHSOM-Modell kann die neuen Anomalien effektiv erkennen und das NNB-Model passt die Änderungen in Netzdaten optimal an. Bei den experimentellen Untersuchungen hat das Framework erfolgversprechende Ergebnisse gezeigt. Im ersten Experiment wurde das Framework in Offline-Betriebsmodus evaluiert. Der OptiFilter wurde mit offline-, synthetischen- und realistischen Daten ausgewertet. Der adaptive Klassifikator wurde mit dem 10-Fold Cross Validation Verfahren evaluiert, um dessen Genauigkeit abzuschätzen. Im zweiten Experiment wurde das Framework auf einer 1 bis 10 GB Netzwerkstrecke installiert und im Online-Betriebsmodus in Echtzeit ausgewertet. Der OptiFilter hat erfolgreich die gewaltige Menge von Netzdaten in die strukturierten Verbindungsvektoren umgewandelt und der adaptive Klassifikator hat sie präzise klassifiziert. Die Vergleichsstudie zwischen dem entwickelten Framework und anderen bekannten IDS-Ansätzen zeigt, dass der vorgeschlagene IDSFramework alle anderen Ansätze übertrifft. Dies lässt sich auf folgende Kernpunkte zurückführen: Bearbeitung der gesammelten Netzdaten, Erreichung der besten Performanz (wie die Gesamtgenauigkeit), Detektieren unbekannter Verbindungen und Entwicklung des in Echtzeit arbeitenden Erkennungsmodells von Eindringversuchen.

Optimal Unsupervised Learning in Feedforward Neural Networks

We investigate the properties of feedforward neural networks trained with Hebbian learning algorithms. A new unsupervised algorithm is proposed which produces statistically uncorrelated outputs. The algorithm causes the weights of the network to converge to the eigenvectors of the input correlation with largest eigenvalues. The algorithm is closely related to the technique of Self-supervised Backpropagation, as well as other algorithms for unsupervised learning. Applications of the algorithm to texture processing, image coding, and stereo depth edge detection are given. We show that the algorithm can lead to the development of filters qualitatively similar to those found in primate visual cortex.

Explorations of the Practical Issues of Learning Prediction-Control Tasks Using Temporal Difference Learning Methods

There has been recent interest in using temporal difference learning methods to attack problems of prediction and control. While these algorithms have been brought to bear on many problems, they remain poorly understood. It is the purpose of this thesis to further explore these algorithms, presenting a framework for viewing them and raising a number of practical issues and exploring those issues in the context of several case studies. This includes applying the TD(lambda) algorithm to: 1) learning to play tic-tac-toe from the outcome of self-play and of play against a perfectly-playing opponent and 2) learning simple one-dimensional segmentation tasks.

Embodiment and Manipulation Learning Process for a Humanoid Hand

Babies are born with simple manipulation capabilities such as reflexes to perceived stimuli. Initial discoveries by babies are accidental until they become coordinated and curious enough to actively investigate their surroundings. This thesis explores the development of such primitive learning systems using an embodied light-weight hand with three fingers and a thumb. It is self-contained having four motors and 36 exteroceptor and proprioceptor sensors controlled by an on-palm microcontroller. Primitive manipulation is learned from sensory inputs using competitive learning, back-propagation algorithm and reinforcement learning strategies. This hand will be used for a humanoid being developed at the MIT Artificial Intelligence Laboratory.

Student self-assessment a feedback seeking strategy through competence evaluation

There is a body of literature that suggests that student self-assessment is a main goal in higher education (Boud et al., 1995; Tan, 2008); moreover new forms of work organization require a high level of skills and competences. The efforts to deal with competence gaps could be developed at many levels, such as employers, educational institutions, individuals and public agents. Employers could put into practice competence development programs to moderate these gaps. Educational institutions can restructure the curriculum to support students in attaining the competences that are essential in the labour market. Individuals themselves may deploy their resources (time and money) in general or specific competence training. Further, government agencies could fund competence promotion programs. Such challenges for education drive change in learning curricula and method, to properly include the competences required for developing global workers who can move beyond basic competence, to enhanced flexibility and adaptability. In performance assessment methods, there is a shift from the traditional exam-based assessments to more innovative task assessment, which considers performance in multiple different tasks carry out by students. ICTs make it technologically feasible to carry out a complete and complex selfassessment of competences, which provides immediate results to students or other recipients. In the case of students, the evaluation of competences is relevant as developing competences is part - if not all - of the objectives of education. Therefore, it is an important element of the quality of educational organizations (e.g., universities), and of their organizational success. Further, educational organizations may put special emphasis on some differentiating competences, which can be a means of positioning and differentiation from competitors. Competence assessment is an instrument to make students conscious of their strengths and weaknesses, leading to higher motivation to develop their own learning career

A Self-Scoring Exercise On APA Style, Research Language, and Referencing for Undergraduate Students

Based on examples provided by 27 graduate psychology faculty, this self-test incorporates many of the more common errors in style, language, and referencing found in student papers. Taking this self-test helps students to recognize common errors and encourages them to refer the APA Publication Manual on a regular basis. In addition, students begin to think about how to use correctly the language of psychological research. This self-test should take about 30 minutes to complete and score. It is composed of three parts: a) a mock Discussion section, where students are asked to act as editors and find the errors, p. 2 (10 minutes). b) a corrected Discussion section, where students find the errors they missed, p. 3 (5 minutes) and, c) a full description of each error with illustrations of correct usage, pp. 4-7 (15 minutes). This exercise assumes some knowledge of APA style. Thus, it is best-suited for advanced undergraduates who need to write research reports and all levels of graduate students. It may be taken at home or in class. Although the self-test is designed to be fully self-directed, instructors may wish to use it at the beginning or end of a classroom discussion on APA style. It could also be used in a pre-test-post-test fashion to evaluate students learning over the course of a term.

Introduction to Matlab - a self-study tutorial

Matlab is a high level language that is very easy to use and very powerful. It comes with a wealth of libraries and toolboxes, that you can use directly, so that you don't need to program low level functions. It enables you to display results very easily on graphs and images. To get started with it, you need to understand how to manipulate and represent data, and how to find information about the available functions. During this self-study tutorial, you will learn: 1- How to start Matlab. 2- How you can find out all the information you need. 3- How to create simple vectors and matrices. 4- What functions are available and how to find them. 5- How to plot graphs of functions. 6- How to write a script. After this (should take about an hour), you will know most of what you need to know about Matlab and should definitely know how to go on learning about it on your own…

Liderazgo y resiliencia organizacional en la crisis financiera global del 2008–2009

Durante la crisis financiera global de 2008 muchas organizaciones y mercados financieros tuvieron que terminar sus operaciones o replantearlas debido a los choques que golpearon el bienestar de sus empresas. A pesar de esta grave situación, en la actualidad se pueden encontrar empresas que se recuperaron y salieron del terrible panorama que les presentó la crisis, incluso encontrando nuevas oportunidades de negocio y fortaleciendo su futuro. Esta capacidad que algunas organizaciones tuvieron y que permitió su salida victoriosa de la crisis se denomina resiliencia, la cual es la capacidad de sobreponerse a los efectos negativos de choques internos o externos (Briguglio, Cordina, Farrugia & Vella 2009). Por tanto en el presente trabajo se estudiará esta capacidad tanto en la organización como en los líderes para hallar factores que mejoren el desempeño de las empresas en crisis como la que ocurrió en el 2008 – 2009. Primero se realizará un estudio sobre los sucesos y el desarrollo de la crisis subprime del año 2008 para tener un entendimiento claro de sus antecedentes, desarrollo, magnitud y consecuencias. Posteriormente se realizará un estudio profundo sobre la teoría de la resiliencia organizacional y la resiliencia en el líder como individuo y los estilos de liderazgo. Finalmente teniendo un sustento teórico tanto de la crisis como del concepto de resiliencia se tomarán casos de estudio de empresas que lograron perdurar en la crisis financiera del 2008 y empresas que no lograron sobrevivir para posteriormente hallar características del líder y del liderazgo que puedan aumentar o afectar la capacidad de resiliencia de las organizaciones con el objetivo de brindar herramientas a los líderes actuales para que manejen de forma eficiente y eficaz las empresas en un mundo complejo y variable como el actual.

Self-study Language Modules Using Blackboard - Julie Watson

This is one of a series of short case studies describing how academic tutors at the University of Southampton have made use of learning technologies to support their students.

Using video markschemes to support self-assessment in Chemistry

A video markscheme was created using a combination of Camtasia screen capture (on a Tablet PC) and 'live action' video taken with a camcorder. The resulting video supported students in the self-assessment of an organic chemistry exercise which had been set over the Easter vacation break. Feedback was collected from the students after the exercise and was overwhelmingly positive. The video won the 2010 award for 'Most Effective Use of Video in an Educational Context' from the Assocation for Learning Technology. DOWNLOAD THE ZIP FOLDER AND EXTRACT THE FILES TO ACCESS THEM.