Towards Emotional Interaction: Using Movies to Automatically Learn Users' Emotional States

The HCI community is actively seeking novel methodologies to gain insight into the user’s experience during interaction with both the application and the content. We propose an emotional recognition engine capable of automatically recognizing a set of human emotional states using psychophysiological measures of the autonomous nervous system, including galvanic skin response, respiration, and heart rate. A novel pattern recognition system, based on discriminant analysis and support vector machine classifiers is trained using movies’ scenes selected to induce emotions ranging from the positive to the negative valence dimension, including happiness, anger, disgust, sadness, and fear. In this paper we introduce an emotion recognition system and evaluate its accuracy by presenting the results of an experiment conducted with three physiologic sensors.

Increasing source to image distance for AP pelvis imaging: impact on radiation dose and image quality

Aim - A quantative primary study to determine whether increasing source to image distance (SID), with and without the use of automatic exposure control (AEC) for antero-posterior (AP) pelvis imaging, reduces dose whilst still producing an image of diagnostic quality. Methods - Using a computed radiography (CR) system, an anthropomorphic pelvic phantom was positioned for an AP examination using the table bucky. SID was initially set at 110 cm, with tube potential set at a constant 75 kVp, with two outer chambers selected and a fine focal spot of 0.6 mm. SID was then varied from 90 cm to 140 cm with two exposures made at each 5 cm interval, one using the AEC and another with a constant 16 mAs derived from the initial exposure. Effective dose (E) and entrance surface dose (ESD) were calculated for each acquisition. Seven experienced observers blindly graded image quality using a 5-point Likert scale and 2 Alternative Forced Choice software. Signal-to-Noise Ratio (SNR) was calculated for comparison. For each acquisition, femoral head diameter was also measured for magnification indication. Results - Results demonstrated that when increasing SID from 110 cm to 140 cm, both E and ESD reduced by 3.7% and 17.3% respectively when using AEC and 50.13% and 41.79% respectively, when the constant mAs was used. No significant statistical (T-test) difference (p = 0.967) between image quality was detected when increasing SID, with an intra-observer correlation of 0.77 (95% confidence level). SNR reduced slightly for both AEC (38%) and no AEC (36%) with increasing SID. Conclusion - For CR, increasing SID significantly reduces both E and ESD for AP pelvis imaging without adversely affecting image quality.

Dominant set approach to ECG biometrics

Electrocardiographic (ECG) signals are emerging as a recent trend in the field of biometrics. In this paper, we propose a novel ECG biometric system that combines clustering and classification methodologies. Our approach is based on dominant-set clustering, and provides a framework for outlier removal and template selection. It enhances the typical workflows, by making them better suited to new ECG acquisition paradigms that use fingers or hand palms, which lead to signals with lower signal to noise ratio, and more prone to noise artifacts. Preliminary results show the potential of the approach, helping to further validate the highly usable setups and ECG signals as a complementary biometric modality.

Linking entrepreneural orientation to export performance: the role of intangible resources and dynamic capabilities

Understanding the determinants of international performance, and in particular, export performance is key for the success of international companies. Research in this area focuses mainly on how resources and capabilities allow companies to gain competitive advantage and superior performance in external markets. Building on the Resource-Based View (RBV) and the Dynamic Capabilities Approach (DCA), this study aims at analysing the effect of intangible resources and capabilities on export performance. Specifically, this study focuses on the proposition that entrepreneurial orientation potentiates the attraction of intangible resources, namely relational and informational resources. Moreover, we propose that these resources impact export performance both directly and indirectly through dynamic capabilities.

Cardiorespiratory fitness is negatively associated with metabolic risk factors independently of the adherence to a healthy dietary pattern

Background and aim: Cardiorespiratory fitness (CRF) and diet have been involved as significant factors towards the prevention of cardio-metabolic diseases. This study aimed to assess the impact of the combined associations of CRF and adherence to the Southern European Atlantic Diet (SEADiet) on the clustering of metabolic risk factors in adolescents. Methods and Results: A cross-sectional school-based study was conducted on 468 adolescents aged 15-18, from the Azorean Islands, Portugal. We measured fasting glucose, insulin, total cholesterol (TC), HDL-cholesterol, triglycerides, systolic blood pressure, waits circumference and height. HOMA, TC/HDL-C ratio and waist-to-height ratio were calculated. For each of these variables, a Z-score was computed by age and sex. A metabolic risk score (MRS) was constructed by summing the Z scores of all individual risk factors. High risk was considered when the individual had 1SD of this score. CRF was measured with the 20 m-Shuttle-Run- Test. Adherence to SEADiet was assessed with a semi-quantitative food frequency questionnaire. Logistic regression showed that, after adjusting for potential confounders, unfit adolescents with low adherence to SEADiet had the highest odds of having MRS (OR Z 9.4; 95%CI:2.6e33.3) followed by the unfit ones with high adherence to the SEADiet (OR Z 6.6; 95% CI: 1.9e22.5) when compared to those who were fit and had higher adherence to SEADiet.

Waste recovery into activated carbon for water purification from heavy metals

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Química Pela Universidade Nova de Lisboa,Faculdade de Ciências e Tecn

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Distributed Linear Precoding and User Selection in Coordinated Multicell Systems

In this manuscript we tackle the problem of semidistributed user selection with distributed linear precoding for sum rate maximization in multiuser multicell systems. A set of adjacent base stations (BS) form a cluster in order to perform coordinated transmission to cell-edge users, and coordination is carried out through a central processing unit (CU). However, the message exchange between BSs and the CU is limited to scheduling control signaling and no user data or channel state information (CSI) exchange is allowed. In the considered multicell coordinated approach, each BS has its own set of cell-edge users and transmits only to one intended user while interference to non-intended users at other BSs is suppressed by signal steering (precoding). We use two distributed linear precoding schemes, Distributed Zero Forcing (DZF) and Distributed Virtual Signalto-Interference-plus-Noise Ratio (DVSINR). Considering multiple users per cell and the backhaul limitations, the BSs rely on local CSI to solve the user selection problem. First we investigate how the signal-to-noise-ratio (SNR) regime and the number of antennas at the BSs impact the effective channel gain (the magnitude of the channels after precoding) and its relationship with multiuser diversity. Considering that user selection must be based on the type of implemented precoding, we develop metrics of compatibility (estimations of the effective channel gains) that can be computed from local CSI at each BS and reported to the CU for scheduling decisions. Based on such metrics, we design user selection algorithms that can find a set of users that potentially maximizes the sum rate. Numerical results show the effectiveness of the proposed metrics and algorithms for different configurations of users and antennas at the base stations.

Cyclopentadienyl-functionalised N-heterocyclic carbenes: synthesis, coordination to Mo, Ru, Rh

Dissertation presented to obtain the Ph.D degree in Chemistry

New strategies to detect and understand genotype-by-environment interactions and QTL-by-environment interactions

Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco, especialidade em Estatística

Energy-efficient diversity combining for different access schemes in a multi-path dispersive channel

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e Computadores

Microwave imaging of the axilla to aid breast cancer diagnosis

Breast cancer is the most common type of cancer among women all over the world. An important issue that is not commonly addressed in breast cancer imaging literature is the importance of imaging the underarm region—where up to 80% of breast cancer cells can metastasise to. The first axillary lymph nodes to receive drainage from the primary tumour in the breast are called Sentinel Node. If cancer cells are found in the Sentinel Node, there is an increased risk of metastatic breast cancer which makes this evaluation crucial to decide what follow-up exams and therapy to follow. However, non-invasive detection of cancer cells in the lymph nodes is often inconclusive, leading to the surgical removal of too many nodes which causes adverse side-effects for patients. Microwave Imaging is one of the most promising non-invasive imaging modalities for breast cancer early screening and monitoring. This novel study tests the feasibility of imaging the axilla region by means of the simulation of an Ultra-Wideband Microwave Imaging system. Simulations of such system are completed in several 2D underarm models that mimic the axilla. Initial imaging results are obtained by means of processing the simulated backscattered signals by eliminating artefacts caused by the skin and beamforming the processed signals in order to time-align all the signals recorded at each antenna. In this dissertation several image formation algorithms are implemented and compared by visual inspection of the resulting images and through a range of performance metrics, such as Signal-to-Clutter Ratio and FullWidth Half Maximum calculations. The results in this study showed that Microwave Imaging is a promising technique that might allow to identify the presence and location of metastasised cancer cells in axillary lymph nodes, enabling the non-invasive evaluation of breast cancer staging.

Aedes aegypti and Aedes albopictus (Diptera: Culicidae): coexistence and susceptibility to temephos, in municipalities with occurrence of dengue and differentiated characteristics of urbanization

INTRODUCTION: The aim of the present study was to verify the coexistence between Aedes aegypti and Aedes albopictus populations in municipalities of the States of Paraná and Santa Catarina with different urbanization profiles where dengue occurs and evaluate their susceptibility to the organophosphate temephos. METHODS: The number of eggs per ovitrap were counted and incubated for hatching to identify the species. Data analysis of the populations was conducted to determine randomness and aggregation, using the variance-to-mean ratio (index of dispersion). Susceptibility to temephos was evaluated by estimation of the resistance ratios RR50 and RR95. Aedes aegypti samples were compared with the population Rockefeller and Aedes albopictus samples were compared with a population from the State of Santa Catarina and with the Rockefeller population. RESULTS: Coexistence between Aedes aegypti and Aedes albopictus and the aggregation of their eggs were observed at all the sites analyzed in the State of Paraná. CONCLUSIONS: All the Aedes aegypti populations from the State of Parana showed alteration in susceptibility status to the organophosphate temephos, revealing incipient resistance. Similarly, all the Aedes albopictus populations (States of Paraná and Santa Catarina) presented survival when exposed to the organophosphate temephos.

Barriers preventing the successful integration of mental health services into Primary Health Care in Nigeria : a mixed methods approach

RESUMO: A Nigéria tem uma população estimada em cerca de 170 milhões de pessoas. O número de profissionais de saúde mental é muito diminuto, contando apenas com 150 psiquiatras o que perfaz aproximadamente um rácio de psiquiatra: população de mais de 1:1 milhão de pessoas. O Plano Nacional de Saúde Mental de 1991 reconheceu esta insuficiência e recomendou a integração dos serviços de saúde mental nos cuidados de saúde primários (CSP). Depois de mais de duas décadas, essa política não foi ainda implementada. Este estudo teve como objetivos mapear a estrutura organizacional dos serviços de saúde mental da Nigéria, e explorar os desafios e barreiras que impedem a integração bem-sucedida dos serviços de saúde mental nos cuidados de saúde primários, isto segundo a perspectiva dos profissionais dos cuidados de saúde primários. Com este objetivo, desenvolveu-se um estudo exploratório sequencial e utilizou-se um modelo misto para a recolha de dados. A aplicação em simultâneo de abordagens qualitativas e quantitativas permitiram compreender os problemas relacionados com a integração dos serviços de saúde mental nos CSP na Nigéria. No estudo qualitativo inicial, foram realizadas entrevistas com listagens abertas a 30 profissionais dos CSP, seguidas de dois grupos focais com profissionais dos CSP de duas zonas governamentais do estado de Oyo de forma a obter uma visão global das perspectivas destes profissionais locais sobre os desafios e barreiras que impedem uma integração bem-sucedida dos serviços de saúde mental nos CSP. Subsequentemente, foram realizadas entrevistas com quatro pessoas-chave, especificamente coordenadores e especialistas em saúde mental. Os resultados do estudo qualitativo foram utilizados para desenvolver um questionário para análise quantitativa das opiniões de uma amostra maior e mais representativa dos profissionais dos CSP do Estado de Oyo, bem como de duas zonas governamentais locais do Estado de Osun. As barreiras mais comummente identificadas a partir deste estudo incluem o estigma e os preconceitos sobre a doença mental, a formação inadequada dos profissionais dos CPS sobre saúde mental, a perceção pela equipa dos CSP de baixa prioridade de ação do Governo, o medo da agressão e violência pela equipa dos CSP, bem como a falta de disponibilidade de fármacos. As recomendações para superar estes desafios incluem a melhoria sustentada dos esforços da advocacia à saúde mental que vise uma maior valorização e apoio governamental, a formação e treino organizados dos profissionais dos cuidados primários, a criação de redes de referência e de apoio com instituições terciárias adjacentes, e o engajamento da comunidade para melhorar o acesso aos serviços e à reabilitação, pelas pessoas com doença mental. Estes resultados fornecem indicações úteis sobre a perceção das barreiras para a integração bem sucedida dos serviços de saúde mental nos CSP, enquanto se recomenda uma abordagem holística e abrangente. Esta informação pode orientar as futuras tentativas de implementação da integração dos serviços de saúde mental nos cuidados primários na Nigéria.------------ABSTRACT: Nigeria has an estimated population of about 170 million people but the number of mental health professionals is very small, with about 150 psychiatrists. This roughly translates to a psychiatrist:population ratio of more than 1:1 million people. The National Mental Health Policy of 1991 recognized this deficiency and recommended the integration of mental health into primary health care (PHC) delivery system. After more than two decades, this policy has yet to be implemented. This study aimed to map out the organizational structure of the mental health systems in Nigeria, and to explore the challenges and barriers preventing the successful integration of mental health into primary health care, from the perspective of the primary health care workers. A mixed methods exploratory sequential study design was employed, which entails the use of sequential timing in the combined methods of data collection. A combination of qualitative and uantitative approaches in sequence, were utilized to understand the problems of mental health services integration into PHC in Nigeria. The initial qualitative phase utilized free listing interviews with 30 PHC workers, followed by two focus group discussions with primary care workers from two Local Government Areas (LGA) of Oyo State to gain useful insight into the local perspectives of PHC workers about the challenges and barriers preventing successful integration of mental health care services into PHC. Subsequently, 4 key informant interviews with PHC co-ordinators and mental health experts were carried out. The findings from the qualitative study were utilized to develop a quantitative study questionnaire to understand the opinions of a larger and more representative sample of PHC staff in two more LGAs of Oyo State, as well as 2 LGAs from Osun State. The common barriers identified from this study include stigma and misconceptions about mental illness, inadequate training of PHC staff about mental health, low government priority, fear of aggression and violence by the PHC staff, as well as non-availability of medications. Recommendations for overcoming these challenges include improved and sustained efforts at mental health advocacy to gain governmental attention and support, organized training and retraining for primary care staff, establishment of referral and supportive networks with neighbouring tertiary facilities and community engagement to improve service utilization and rehabilitation of mentally ill persons. These findings provide useful insight into the barriers to the successful integration of mental health into PHC, while recommending a holistic and comprehensive approach. This information can guide future attempts to implement the integration of mental health into primary care in Nigeria.

Coupling organic substrate removal to methane production in a fully biological microbial electrolysis cell

Microbial electrolysis cells (MECs) are an innovative and emerging technique based on the use of solid-state electrodes to stimulate microbial metabolism for wastewater treatment and simultaneous production of value-added compounds (such as methane). This research studied the performance of a two-chamber MEC in terms of organic matter oxidation (at the anode) and methane production (at the cathode). MEC‟s anode had been previously inoculated with an activated sludge, whereas the cathode chamber inoculum was an anaerobic sludge (containing methanogenic microorganisms). During the experimentation, the bioanode was continuously fed with synthetic solutions in anaerobic basal medium, at an organic load rate (OLR) of around 1 g L-1 d-1, referred to the chemical oxygen demand (COD). At the beginning (Run I), the feeding solution contained acetate and subsequently (Run II) it was replaced with a more complex solution containing soluble organic compounds other than acetate. For both conditions, the anode potential was controlled at -0.1 V vs. standard hydrogen electrode, by means of a potentiostat. During Run I, over 80% of the influent acetate was anaerobically oxidized at the anode, and the resulting electric current was recovered as methane at the cathode (with a cathode capture efficiency, CCE, accounting around 115 %). The average energy efficiency of the system (i.e., the energy captured into methane relative to the electrical energy input) under these conditions was over 170%. However, reactor‟s performance decreased over time during this run. Throughout Run II, a substrate oxidation over 60% (on COD basis) was observed. The electric current produced (57% of coulombic efficiency) was also recovered as methane, with a CCE of 90%. For this run the MEC‟s average energy efficiency accounted for almost 170 %. During all the experimentation, a very low biomass growth was observed at the anode whereas ammonium was transferred through the cationic membrane and concentrated at the cathode. Tracer experiments and scanning electron microscopy analyses were also carried out to gain a deeper insight into the reactor performance and also to investigate the possible reasons for partial loss of performance. In conclusion, this research suggests the great potential of MEC to successfully treat low-strength wastewaters, with high energy efficiency and very low sludge production.