Leadership and Pedagogical Interaction as Predictors of Learning Outcomes in Physical Education

This research aims to understand the relative contribution of leadership styles and teacher-student and student-student pedagogical interaction concerning learning performance and academic achievement in Physical Education. A quantitative methodology was implemented, comprising a sample of 447 students attending a school grouping located in the coastal region of central Portugal. In order to verify the nature, the strength and the direction of the relations among the variables, correlation and multiple regression analyses were used. For this, scales already validated and used in other researches were applied. The results show that the learning performance and the academic achievement are significantly associated with teacher leadership styles and teacher-student and student-student pedagogical interaction. A stronger association was obtained with leadership styles, especially the democratic one. It should be mentioned that these factors provide a higher relative contribution to the learning performance than to the academic achievement. The analysis conducted highlights the importance of the democratic teacher leadership style and of the pedagogical interaction established within the classroom towards the improvement of students’ ability to understand the gains and the effort made in learning.

Leadership and Pedagogical Interaction as Predictors of Learning Outcomes in Physical Education

Problem Statement: This research aims to understand the relative contribution of leadership styles and teacher-student and student-student pedagogical interaction concerning the learning performance and academic achievement in physical education. Research Questions: Are the teacher leadership style and the teacher-student and student-student pedagogical interaction related to the learning performance and academic achievement in physical education in basic schooling? Purpose of Study: There are several factors that contribute for the explanation of learning outcomes, namely teacher leadership styles in the classroom, as well as teacher-student and student-student pedagogical interactions. These factors are considered to be essential in the teaching-learning process and in the subsequent improvement of educational outcomes. Research Methods: A quantitative methodology was implemented, comprising a sample of 447 students attending a School Grouping located in the Central Region of Portugal. In order to verify the nature, the strength and the direction of the relations among the variables, correlation and multiple regression analyses were used. For this, scales already validated and used in other researches were applied. Findings: The results show that the learning performance and the academic achievement are significantly associated with teacher leadership styles and teacher-student and student-student pedagogical interaction. A stronger association was obtained with leadership styles, especially the democratic one. It should be mentioned that these factors provide a higher relative contribution to the learning performance than to the academic achievement. Conclusions: This study sought to deepen the understanding of the explanatory factors of academic success concerning the teaching-learning process in physical education. The analysis conducted highlights the importance of the democratic teacher leadership style and of the pedagogical interaction established within the classroom towards the improvement of students' ability to understand the gains and the effort made in learning.

“Biomarkers in a One Health perspective: current knowledge of their ability to merge human and animal health

Biomarkers are nowadays essential tools to be one step ahead for fighting disease, enabling an enhanced focus on disease prevention and on the probability of its occurrence. Research in a multidisciplinary approach has been an important step towards the repeated discovery of new biomarkers. Biomarkers are defined as biochemical measurable indicators of the presence of disease or as indicators for monitoring disease progression. Currently, biomarkers have been used in several domains such as oncology, neurology, cardiovascular, inflammatory and respiratory disease, and several endocrinopathies. Bridging biomarkers in a One Health perspective has been proven useful in almost all of these domains. In oncology, humans and animals are found to be subject to the same environmental and genetic predisposing factors: examples include the existence of mutations in BR-CA1 gene predisposing to breast cancer, both in human and dogs, with increased prevalence in certain dog breeds and human ethnic groups. Also, breast feeding frequency and duration has been related to a decreased risk of breast cancer in women and bitches. When it comes to infectious diseases, this parallelism is prone to be even more important, for as much as 75% of all emerging diseases are believed to be zoonotic. Examples of successful use of biomarkers have been found in several zoonotic diseases such as Ebola, dengue, leptospirosis or West Nile virus infections. Acute Phase Proteins (APPs) have been used for quite some time as biomarkers of inflammatory conditions. These have been used in human health but also in the veterinary field such as in mastitis evaluation and PRRS (porcine respiratory and reproductive syndrome) diagnosis. Advantages rely on the fact that these biomarkers can be much easier to assess than other conventional disease diagnostic approaches (example: measured in easy to collect saliva samples). Another domain in which biomarkers have been essential is food safety: the possibility to measure exposure to chemical contaminants or other biohazards present in the food chain, which are sometimes analytical challenges due to their low bioavailability in body fluids, is nowadays a major breakthrough. Finally, biomarkers are considered the key to provide more personalized therapies, with more efficient outcomes and fewer side effects. This approach is expected to be the correct path to follow also in veterinary medicine, in the near future.

TAZ role in lung cancer: resistance to BET inhibitors and functional interaction with lncRNA

Despite extensive research and introduction of innovative therapy, lung cancer prognosis remains poor, with a five years survival of only 17%. The success of pharmacological treatment is often impaired by drug resistance. Thus, the characterization of response mechanisms to anti-cancer compounds and of the molecular mechanisms supporting lung cancer aggressiveness are crucial for patient’s management. In the first part of this thesis, we characterized the molecular mechanism behind resistance of lung cancer cells to the Inhibitors of the Bromodomain and Extraterminal domain containing Proteins (BETi). Through a CRISPR/Cas9 screening we identified three Hippo Pathway members, LATS2, TAOK1 and NF2 as genes implicated in susceptibility to BETi. These genes confer sensitivity to BETi inhibiting TAZ activity. Conversely, TAZ overexpression increases resistance to BETi. We also displayed that BETi downregulate both YAP, TAZ and TEADs expression in several cancer cell lines, implying a novel BETi-dependent cytotoxic mechanism. In the second part of this work, we attempted to characterize the crosstalk between the TAZ gene and its cognate antisense long-non coding RNA (lncRNA) TAZ-AS202 in lung tumorigenesis. As for TAZ downregulation, TAZ-AS202 silencing impairs NSCLC cells proliferation, migration and invasion, suggesting a pro-tumorigenic function for this lncRNA during lung tumorigenesis. TAZ-AS202 regulates TAZ target genes without altering TAZ expression or localization. This finding implies an uncovered functional cooperation between TAZ and TAZ-AS202. Moreover, we found that the EPH-ephrin signaling receptor EPHB2 is a downstream effector affected by both TAZ and TAZ-AS202 silencing. EPHB2 downregulation significantly attenuates cells proliferation, migration and invasion, suggesting that, at least in part, TAZ-AS202 and TAZ pro-oncogenic activity depends on EPH-ephrin signaling final deregulation. Finally, we started to dissect the mechanism underlying the TAZ-AS202 regulatory activity on EPHB2 in lung cancer, which may involve the existence of an intermediate transcription factor and is the object of our ongoing research.

Synthesis and coating of silver nanoparticles and their interaction with cells model

La mia tesi si concentra sulla sintesi e funzionalizzazione di nanoparticelle d’argento studiandone l’interazione, tramite esperimenti in vitro, con cellule sane di fibroblasti murini NIH-3T3 e cellule tumorali da nodulo al seno MCF7. L’utilizzo di polielettroliti quali PDADMAC, PAH e PSS ha permesso la modifica delle proprietà superficiali delle nanoparticelle. Le nuove proprietà chimico-fisiche sono state caratterizzate tramite Dynamic Light Scattering, potenziale zeta e spettroscopia UV-vis. L’effetto della ricopertura con polielettroliti è stato valutato tramite test di vitalità cellulare somministrando le nanoparticelle funzionalizzate alle cellule sopracitate. Successivamente, è stata ottimizzata la procedura per un’ulteriore ricopertura sulle nanoparticelle cariche con BSA (Bovine Serum Albumin) valutando diversi fattori chiave. Le nanoparticelle ricoperte di albumina sono state caratterizzate e la composizione qualitativa della loro protein corona è stata ottenuta tramite analisi SDS-PAGE. Infine, le nanoparticelle ricoperte di BSA sono state somministrate alle due linee cellulari valutando l’effetto dell’albumina sulla risposta biologica tramite analisi di vitalità cellulare e immunofluorescenza.

Novel force control methods in a teleoperation system of a hydraulic slider

The objective of the this research project is to develop a novel force control scheme for the teleoperation of a hydraulically driven manipulator, and to implement an ideal transparent mapping between human and machine interaction, and machine and task environment interaction. This master‘s thesis provides a preparatory study for the present research project. The research is limited into a single degree of freedom hydraulic slider with 6-DOF Phantom haptic device. The key contribution of the thesis is to set up the experimental rig including electromechanical haptic device, hydraulic servo and 6-DOF force sensor. The slider is firstly tested as a position servo by using previously developed intelligent switching control algorithm. Subsequently the teleoperated system is set up and the preliminary experiments are carried out. In addition to development of the single DOF experimental set up, methods such as passivity control in teleoperation are reviewed. The thesis also contains review of modeling of the servo slider in particular reference to the servo valve. Markov Chain Monte Carlo method is utilized in developing the robustness of the model in presence of noise.

Marr's vision: twenty-five years on

It is twenty-five years since the posthumous publication of David Marr's book Vision [1]. Only 35 years old when he died, Man, had already dramatically influenced vision research. His book, and the series of papers that preceded it, have had a lasting impact on the way that researchers approach human and computer vision.

The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design.

Nine for ones in nine: a schizophrenic cyborg love story.

By appropriating the images of the schizophrenic and the cyborg from Deleuze and Guattari, and from Donna Haraway respectively, this paper seeks to discuss the relationship between human and computer, composer and performer in a way that undermines and subverts the normal binaries commonly employed, and even implied in the descriptions of these relationships in this paper. “Nine for ones in nine”, despite employing the use of the OpenMusic software in its composition, retains a degree of choice and indeterminacy for the performers; despite employing the use of precise just harmony in its design and intent, the work depends upon the imprecision of human control rather than ceding to the precision of a synthesiser. Given the vast possibilities opened up to composers by the use of computers to calculate and create sound, why then do composers continue to employ performers in the realisation of their designs, and rely on sometimes hundreds of years-old technology to articulate them in real time? The very social and imprecise aspect of the act of performance is key to the messy, compromised, and complicit product that scores such as Nine for ones in nine aim to produce.

Hand gesture recognition system based in computer vision and machine learning : applications on human-machine interaction

Sendo uma forma natural de interação homem-máquina, o reconhecimento de gestos implica uma forte componente de investigação em áreas como a visão por computador e a aprendizagem computacional. O reconhecimento gestual é uma área com aplicações muito diversas, fornecendo aos utilizadores uma forma mais natural e mais simples de comunicar com sistemas baseados em computador, sem a necessidade de utilização de dispositivos extras. Assim, o objectivo principal da investigação na área de reconhecimento de gestos aplicada à interacção homemmáquina é o da criação de sistemas, que possam identificar gestos específicos e usálos para transmitir informações ou para controlar dispositivos. Para isso as interfaces baseados em visão para o reconhecimento de gestos, necessitam de detectar a mão de forma rápida e robusta e de serem capazes de efetuar o reconhecimento de gestos em tempo real. Hoje em dia, os sistemas de reconhecimento de gestos baseados em visão são capazes de trabalhar com soluções específicas, construídos para resolver um determinado problema e configurados para trabalhar de uma forma particular. Este projeto de investigação estudou e implementou soluções, suficientemente genéricas, com o recurso a algoritmos de aprendizagem computacional, permitindo a sua aplicação num conjunto alargado de sistemas de interface homem-máquina, para reconhecimento de gestos em tempo real. A solução proposta, Gesture Learning Module Architecture (GeLMA), permite de forma simples definir um conjunto de comandos que pode ser baseado em gestos estáticos e dinâmicos e que pode ser facilmente integrado e configurado para ser utilizado numa série de aplicações. É um sistema de baixo custo e fácil de treinar e usar, e uma vez que é construído unicamente com bibliotecas de código. As experiências realizadas permitiram mostrar que o sistema atingiu uma precisão de 99,2% em termos de reconhecimento de gestos estáticos e uma precisão média de 93,7% em termos de reconhecimento de gestos dinâmicos. Para validar a solução proposta, foram implementados dois sistemas completos. O primeiro é um sistema em tempo real capaz de ajudar um árbitro a arbitrar um jogo de futebol robótico. A solução proposta combina um sistema de reconhecimento de gestos baseada em visão com a definição de uma linguagem formal, o CommLang Referee, à qual demos a designação de Referee Command Language Interface System (ReCLIS). O sistema identifica os comandos baseados num conjunto de gestos estáticos e dinâmicos executados pelo árbitro, sendo este posteriormente enviado para um interface de computador que transmite a respectiva informação para os robôs. O segundo é um sistema em tempo real capaz de interpretar um subconjunto da Linguagem Gestual Portuguesa. As experiências demonstraram que o sistema foi capaz de reconhecer as vogais em tempo real de forma fiável. Embora a solução implementada apenas tenha sido treinada para reconhecer as cinco vogais, o sistema é facilmente extensível para reconhecer o resto do alfabeto. As experiências também permitiram mostrar que a base dos sistemas de interação baseados em visão pode ser a mesma para todas as aplicações e, deste modo facilitar a sua implementação. A solução proposta tem ainda a vantagem de ser suficientemente genérica e uma base sólida para o desenvolvimento de sistemas baseados em reconhecimento gestual que podem ser facilmente integrados com qualquer aplicação de interface homem-máquina. A linguagem formal de definição da interface pode ser redefinida e o sistema pode ser facilmente configurado e treinado com um conjunto de gestos diferentes de forma a serem integrados na solução final.

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

A study on human error in the interaction with the computer systems

The term human factor is used by professionals of various fields meant for understanding the behavior of human beings at work. The human being, while developing a cooperative activity with a computer system, is subject to cause an undesirable situation in his/her task. This paper starts from the principle that human errors may be considered as a cause or factor contributing to a series of accidents and incidents in many diversified fields in which human beings interact with automated systems. We propose a simulator of performance in error with potentiality to assist the Human Computer Interaction (HCI) project manager in the construction of the critical systems. © 2011 Springer-Verlag.