Positive self-image and incentives in organizations

This paper investigates the implications of individuals’ mistaken beliefs of their abilities on incentives in organizations using the principal-agent model of moral hazard. The paper shows that if effort is observable, then an agent’s mistaken beliefs about own ability are always favorable to the principal. However, if effort is unobservable, then an agent’s mistaken beliefs about own ability can be either favorable or unfavorable to the principal. The paper provides conditions under which an agent’s over estimation about own ability is favorable to the principal when effort is unobservable. Finally, the paper shows that workers’ mistaken beliefs about their coworkers’ abilities make interdependent incentive schemes more attractive to firms than individualistic incentive schemes.

Positive self-image in tournaments

This paper analyzes the implications of worker overestimation of productivity for firms in which incentives take the form of tournaments. Each worker overestimates his productivity but is aware of the bias in his opponent’s self-assessment. The manager of the firm, on the other hand, correctly assesses workers’ productivities and self-beliefs when setting tournament prizes. The paper shows that, under a variety of circumstances, firms make higher profits when workers have positive self-image than if workers do not. By contrast, workers’ welfare declines due to their own misguided choices.

Microscopy image segmentation by active contour models

In this thesis a semi-automated cell analysis system is described through image processing. To achieve this, an image processing algorithm was studied in order to segment cells in a semi-automatic way. The main goal of this analysis is to increase the performance of cell image segmentation process, without affecting the results in a significant way. Even though, a totally manual system has the ability of producing the best results, it has the disadvantage of taking too long and being repetitive, when a large number of images need to be processed. An active contour algorithm was tested in a sequence of images taken by a microscope. This algorithm, more commonly known as snakes, allowed the user to define an initial region in which the cell was incorporated. Then, the algorithm would run several times, making the initial region contours to converge to the cell boundaries. With the final contour, it was possible to extract region properties and produce statistical data. This data allowed to say that this algorithm produces similar results to a purely manual system but at a faster rate. On the other hand, it is slower than a purely automatic way but it allows the user to adjust the contour, making it more versatile and tolerant to image variations.

Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

Image processing for displacement measurements

Since the invention of photography humans have been using images to capture, store and analyse the act that they are interested in. With the developments in this field, assisted by better computers, it is possible to use image processing technology as an accurate method of analysis and measurement. Image processing's principal qualities are flexibility, adaptability and the ability to easily and quickly process a large amount of information. Successful examples of applications can be seen in several areas of human life, such as biomedical, industry, surveillance, military and mapping. This is so true that there are several Nobel prizes related to imaging. The accurate measurement of deformations, displacements, strain fields and surface defects are challenging in many material tests in Civil Engineering because traditionally these measurements require complex and expensive equipment, plus time consuming calibration. Image processing can be an inexpensive and effective tool for load displacement measurements. Using an adequate image acquisition system and taking advantage of the computation power of modern computers it is possible to accurately measure very small displacements with high precision. On the market there are already several commercial software packages. However they are commercialized at high cost. In this work block-matching algorithms will be used in order to compare the results from image processing with the data obtained with physical transducers during laboratory load tests. In order to test the proposed solutions several load tests were carried out in partnership with researchers from the Civil Engineering Department at Universidade Nova de Lisboa (UNL).

Mobile image processing to support educational geometry games

The mobile IT era is here, it is still growing and expanding at a steady rate and, most of all, it is entertaining. Mobile devices are used for entertainment, whether social through the so-called social networks, or private through web browsing, video watching or gaming. Youngsters make heavy use of these devices, and even small children show impressive adaptability and skill. However not much attention is directed towards education, especially in the case of young children. Too much time is usually spent in games which only purpose is to keep children entertained, time that could be put to better use such as developing elementary geometric notions. Taking advantage of this pocket computer scenario, it is proposed an application geared towards small children in the 6 – 9 age group that allows them to consolidate knowledge regarding geometric shapes, forming a stepping stone that leads to some fundamental mathematical knowledge to be exercised later on. To achieve this goal, the application will detect simple geometric shapes like squares, circles and triangles using the device’s camera. The novelty of this application will be a core real-time detection system designed and developed from the ground up for mobile devices, taking into account their characteristic limitations such as reduced processing power, memory and battery. User feedback was be gathered, aggregated and studied to assess the educational factor of the application.

Fatores de prognóstico para os resultados de sucesso da fisioterapia multimodal em utentes com dor cervical crónica

RESUMO: Introdução: O conhecimento acerca da influência das características dos indivíduos com dor cervical crónica (DCC) no prognóstico dos resultados alcançados com a Fisioterapia é ainda inconsistente, sendo escassos os estudos desenvolvidos neste âmbito. Objetivo: Este relatório pretende determinar se um modelo baseado em fatores de prognóstico é capaz de prever os resultados de sucesso da Fisioterapia, a curto prazo, em utentes com DCC, ao nível da incapacidade funcional, intensidade da dor e perceção global de melhoria. Metodologia: Trata-se de estudo de coorte prospetivo com 112 participantes. Os utentes foram avaliados na primeira semana de tratamento e sete semanas após o início da intervenção. Os instrumentos utilizados foram o Neck Disability Index–Versão Portuguesa (NDI-PT) e a Escala Numérica da Dor (END) nos dois momentos de avaliação, um Questionário de Caracterização Sociodemográfica e Clínica da Amostra na baseline e a Patient Global Impression Change Scale–Versão Portuguesa (PGIC-PT) no follow-up. As características sociodemográficas e clínicas foram incluídas como potenciais fatores de prognóstico e estes foram definidos com base nas diferenças mínimas clinicamente importantes (DMCI) dos instrumentos NDIPT (DMCI≥6) e END (DMCI≥2) e no critério de pontuação ≥5 na PGIC-PT. A análise dos dados foi realizada através do método de regressão logística (backward conditional procedure) para identificar as associações entre os indicadores e as variáveis de resultado (p<0.05). Resultados: Dos 112 participantes incluídos no estudo, 108 completaram o follow-up (média de idade: 51.76±10.19). No modelo multivariado relativo à incapacidade funcional, os resultados de sucesso encontram-se associados a elevados níveis de incapacidade na baseline (OR=1.123; 95% IC 1.056–1.194) e a duração da dor inferior a 12 meses (OR=2.704; 95% IC 1.138–6.424). Este modelo explica 30.0% da variância da melhoria da funcionalidade e classifica corretamente 74.1% dos utentes (sensibilidade: 75.9%; especificidade: 72.0%). O modelo relativo à intensidade da dor identificou apenas a associação do outcome com níveis elevados de intensidade da dor na baseline (OR=1.321; 95% IC 1.047–1.668), explicando 7.5% da variância da redução da mesma e classificando corretamente 68.2% dos utentes (sensibilidade: 94.4%; especificidade: 16.7%). O modelo final referente à perceção global de melhoria apresentou uma associação com a intensidade da dor na baseline (OR=0.621; 95% IC 0.465–0.829), com a presença de cefaleias e/ou tonturas (OR=2.538; 95% IC 0.987–6.526) e com a duração da dor superior a 12 meses (OR=0.279; 95% IC 0.109–0.719). Este modelo explica 27.5% da variância dos resultados de sucesso para este outcome e classifica corretamente 73.1% dos utentes (sensibilidade: 81.8%; especificidade: 59.5%). Conclusões: Utentes com DCC com elevada incapacidade na baseline e queixas de dor há menos de 12 meses apresentam maior probabilidade de obter melhorias ao nível da incapacidade funcional. Elevados níveis de intensidade da dor na baseline predizem resultados de sucesso na redução da dor após sete semanas de tratamento. Utentes com DCC com baixos níveis de dor na baseline, com cefaleias e/ou tonturas e com queixas de dor há mais de 12 meses apresentam maior probabilidade de obter uma melhor perceção de melhoria.--------------- ABSTRACT:Introduction: The influence of the characteristics of individuals with chronic neck pain (CNP) on the prognosis of physiotherapy outcomes is still inconsistent, there being few studies developed in this context. Aim: This study seeks to determine whether a model based on prognostic factors can predict the short-term physiotherapy successful outcomes in CNP patients, regarding functional disability, pain intensity and perceived recovery. Methodology: This is a prospective cohort study with 112 participants. Patients were assessed during the first week of treatment and seven weeks after the start of the intervention. The instruments used were the Neck Disability Index–Portuguese Version (NDI-PT) and the Numerical Rating Scale (NRS) at both moments of assessment, a Sample Sociodemographic and Clinical Characterization Questionnaire at baseline and Patient Global Impression Change Scale–Portuguese Version (PGIC-PT) at the follow-up. The sociodemographic and clinical characteristics were included as potential predictors of successful outcomes, and these were defined on the basis of minimal clinically important differences (MCID) of NDI-PT (MCID≥6) and END (MCID≥2) and the criteria score ≥5 on the PGIC-PT. Data analysis was performed using logistic regression (backward conditional procedure) to identify associations between predictors and outcomes (p<0.05). Results: Of the 112 participants included in the study, 108 completed the follow-up (mean age: 51.76±10.19). In the multivariate model of functional disability, the successful outcomes are associated with high levels of disability at baseline (OR = 1.123; 95% CI 1.056-1.194), and pain duration shorter than 12 months (OR=2.704; 95% CI 1.138–6.424). This model explains 30.0% of the variance of improved functional capacity and correctly classifies 74.1% of the patients (sensitivity: 75.9%, specificity: 72.0%). The model for pain intensity solely identified an outcome association with high pain intensity at baseline (OR=1.321; 95% CI 1.047-1.668), explaining 7.5% of the variance of pain reduction and correctly classifying 68.2% of the patients (sensitivity: 94.4%, specificity: 16.7%). The final model of perceived recovery showed an association with pain intensity at baseline (OR=0.621; 95% CI 0465-0829), with the presence of headache and/or dizziness (OR=2.538; 95% CI 0.987-6.526) and the duration of pain over 12 months (OR=0.279; 95% CI 0.109-0.719). This model explains 27.5% of the variance of successful outcomes and correctly classifies 73.1% of the patients (sensitivity: 81.8%, specificity: 59.5%). Conclusions: Patients with CNP with high disability at baseline and complaints of pain for less than 12 months are more likely to obtain improvements in functional disability. High levels of pain intensity at baseline predict successful outcomes in pain reduction after seven weeks of treatment. Patients with CNP with low levels of pain at baseline, with headache and/or dizziness and with pain complaints for more than 12 months are more likely to get a better perceived recovery.

La Cène ou la figure du banquet comme image de crise morale chez Zeng Fanzhi

Les yeux et les masques sont prévalents dans les oeuvres du peintre chinois contemporain Zeng Fanzhi (né en 1964), comme métaphore du jeu de pouvoir qui oppose les individus à l’appareil social et politique. Son oeuvre La Cène, d’après Leonard de Vinci, est un exemple frappant de cette préoccupation. Cet essai examine l’utilisation par l’artiste de cette représentation occidentale d’une crise morale (une trahison qui mène à la mort du Christ) pour exprimer la dystopie qui marque la Chine contemporaine. L’interprétation par Zeng de l’oeuvre de Vinci témoigne d’une compréhension profonde de sa signification à la Renaissance comme conflit entre le pouvoir terrestre et spirituel, auquel il surimpose la fonction du banquet dans la culture chinoise comme lieu de lutte politique. Un nihilisme détaché imprègne ce travail, à l’instar de l’interprétation métaphorique du banquet de Platon par Søren Kierkegaard, In Vino Veritas.