Miracle-dz/UniFAR-FTUs huggingface dataset:
Racial Discrimination and African Americans’ Travel Behavior

This study investigated African Americans’ travel behavior using Bourdieu’s concept of habitus. In-depth and face-to-face interviews were conducted with 13 middle-class African Americans. Vignette technique was used during the interviews. The study identified four salient themes: (1) racial discrimination during travel, (2) fear of racism, (3) storytelling and safety instructions: social reproduction of the fear of racism, and (4) race-related travel choices. The findings showed that informants’ travel behavior was linked to an acute fear of racism. They affirmed that African Americans’ travel patterns need to be conceived as a defensive mechanism against potential racial discrimination. Implications for research methods and tourism management are discussed.
Effects of group singing on well-being: empirical findings and methodological considerations

The work in this thesis explores the relationship between singing and well-being. In particular, I focus on investigating the potential for group singing to promote feelings of hedonic, eudaimonic and social well-being. The theoretical evidence suggests that such is possible because music activities are structured to engage mind and body in overcoming a challenge, generating feelings of achievement and pleasure in the process. However, the empirical evidence on such effects is less conclusive, reflecting the novelty of the field. I start by developing a model capable of generating hypotheses and framing the empirical work on the relationship between group singing and well-being. In this model, I integrate a conceptualization of well-being as a multidimensional concept with a conceptualization of group singing as a challenging multifaceted activity. The model suggests that well-being is promoted by group singing through the effects this activity has on its psychological, bodily and social correlates. However, the model also accounts for possible moderating effects of situational factors and individual differences. My empirical work focus first on clarifying that group singing involves the types of experiences that can generate feelings of hedonic, eudaimonic and social well-being. I then show that singing in a group relates to long-term measures of well-being, particularly social and eudaimonic. In the short-term, group singing is also consistently related to correlates of well-being. It is shown to increase positive affect, decrease negative affect, increase feelings of achievement and connection to others. Situational factors such as the social context in which the singing occurs are shown to have a moderating effect on endocrine effects of group singing. However, gender differences do not emerge. I also show that group singing can have effects over and above those of a similar, though non-musical, group activity. Overall, the evidence suggests a meaningful relationship between group singing and well-being.
Towards a Localized Version of Pearson's Correlation Coefficient

Pearson’s correlation coefficient is used to describe dependence between random variables X and Y . In some practical situations, however, we have strong correlation for some values X and/or Y and no correlation for other values ofX and Y . To describe such a local dependence, we come up with a natural localized version of Pearson’s correlation coefficient. We also study the properties of the newly defined localized coefficient. 1 Formulation of the Problem Pearson’s correlation coefficient: reminder. To describe relation between two random variables X and Y , Pearson’s correlation coefficient r is often used. This coefficient is defined as r[X,Y ] def = C[X,Y ] σ[X] · σ(Y ) , (1)
Byzantine Fault-Tolerant Consensus in Wireless Ad Hoc Networks

Wireless ad hoc networks, due to their inherent unreliability, pose significant challenges to the task of achieving tight coordination among nodes. The failure of some nodes and momentary breakdown of communications, either of accidental or malicious nature, should not result in the failure of the entire system. This paper presents an asynchronous Byzantine consensus protocol-called Turquois-specifically designed for resource-constrained wireless ad hoc networks. The key to its efficiency is the fact that it tolerates dynamic message omissions, which allows an efficient utilization of the wireless broadcasting medium. The protocol also refrains from computationally expensive public-key cryptographic during its normal operation. The protocol is safe despite the arbitrary failure of f <; n/3 nodes from a total of n nodes, and unrestricted message omissions. Progress is ensured in rounds where the number of omissions is σ ≤ [n-t/2] (n - k - t) + k - 2, where k is the number of nodes required to terminate and t ≤ f is the number of nodes that are actually faulty. These characteristics make Turquois the first consensus protocol that simultaneously circumvents the FLP and the Santoro-Widmayer impossibility results, which is achieved through randomization. Finally, the protocol was prototyped and subject to a comparative performance evaluation against two well-known Byzantine fault-tolerant consensus protocols. The results show that, due to its design, Turquois outperforms the other protocols by more than an order of magnitude as the number of nodes in the system increases.
Quality management (QM) practices in Facilities Management (FM) organisation: A case study in Malaysia

Quality management is known as one of the key approaches adopted by various organisaitons to realise the goal of meeting customer satisfaction. It is also no exception to Facilities Management (FM) organisation. This paper explores the practices of quality management in an FM organisation. The research applies questionnaire distribution approach to seek feedback from occupants who work at, and manage Common User Buildings in Malaysia. The quality management practices that were evaluated consist of people, process and technology components. From the results, it can be concluded that the state of quality management for the case study is high for people and process components and moderate for technology components. The findings suggests that quality management in FM organisation needs strengthening, particularly on the technology aspect. The outcome of the paper provides an insight on the state of the quality management practices in FM organisation in Malaysia.
A Passion to Believe

Foreword (Gary Mesibov) The Prologue: Setting The State Getting Down to Basics The Emerging Portrait of the Facilitator A Portrait of the Client The Drama Unfolds At All Costs: The Messages of F1-C1 An Unreal Reality: The Messages of F2-C2 By Your Hand Alone: The Messages of F3-C3 Getting the Message Loud and Clear Unsettling Reviews From Discordance to Disconnection Behind the Mystique If I Hadnt Believed It, I Wouldnt Have Seen It Beyond the Hype and Circumstance: The FC Culture Unveiled Epilogue: The Reviews Continue to Come In.
"Components separation" method for closure of abdominal-wall defects: an anatomic and clinical study.

Closure of large abdominal-wall defects usually requires the transposition of remote myocutaneous flaps or free-tissue transfers. The purpose of this study was to determine if separation of the muscle components of the abdominal wall would allow mobilization of each unit over a greater distance than possible by mobilization of the entire abdominal wall as a block. The abdominal walls of 10 fresh cadavers were dissected. This demonstrated that the external oblique muscle can be separated from the internal oblique in a relatively avascular plane. The rectus muscle with its overlying rectus fascia can be elevated from the posterior rectus sheath. The compound flap of the rectus muscle, with its attached internal oblique-transversus abdominis muscle, can be advanced 10 cm around the waistline. The external oblique has limited advancement. These findings were utilized clinically in the reconstruction of abdominal-wall defects in 11 patients, ranging in size from 4 x 4 to 18 x 35 cm. This study suggests that large abdominal-wall defects can be reconstructed with functional transfer of abdominal-wall components without the need for resorting to distant transposition of free-muscle flaps.
Handbook of Blind Source Separation: Independent Component Analysis and Applications

Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book reflects recent results in signal processing and numerical analysis, and includes topics such as optimization criteria, mathematical tools, the design of numerical algorithms, convolutive mixtures, and time frequency approaches. This Handbook is an ideal reference for university researchers, RD algebraic identification of under-determined mixtures, time-frequency methods, Bayesian approaches, blind identification under non negativity approaches, semi-blind methods for communicationsShows the applications of the methods to key application areas such as telecommunications, biomedical engineering, speech, acoustic, audio and music processing, while also giving a general method for developing applications
Output-feedback control of nonlinear systems using control contraction metrics and convex optimization

Control contraction metrics (CCMs) are a new approach to nonlinear control design based on contraction theory. The resulting design problems are expressed as pointwise linear matrix inequalities and are and well-suited to solution via convex optimization. In this paper, we extend the theory on CCMs by showing that a pair of “dual” observer and controller problems can be solved using pointwise linear matrix inequalities, and that when a solution exists a separation principle holds. That is, a stabilizing output-feedback controller can be found. The procedure is demonstrated using a benchmark problem of nonlinear control: the Moore-Greitzer jet engine compressor model.
Mendelian Randomization Studies Do Not Support a Causal Role for Reduced Circulating Adiponectin Levels in Insulin Resistance and Type 2 Diabetes

Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics–based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26–0.35) increase in fasting insulin, a 0.34-SD (0.30–0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47–2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI −0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (−0.20 SD; 95% CI −0.38 to −0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75–1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: −0.03 SD; 95% CI −0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95–1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.
Narrowing the Social Gap among People Involved in Global Dialog: Automatic Emotion Detection in Blog Posts

paper, we introduce a new approach to automatic emotion detection in blog posts. The purpose of our research is to develop an effective tool for recognition and interpretation of affect conveyed through written language. The main idea behind the proposed rule-based algorithm is to determine the prevailing emotion in each sentence of diary-like entry and to display the dynamics of emotion changes throughout the whole document by using simplified emotional faces.
Combining Different NLP Methods for HUMINT Report Analysis

Abstract : In this paper we present a combined approach to the automatic (pre-) analysis of intelligence reports. The combination encompasses information extraction (IE) and information enrichment by means of ontologies. The combined approach proves to yield superior results compared to standalone IE. For our work we mainly use open standards and open source software. For the purpose of IE, for instance, we use the GATE system, whereas our ontology work is based on the W3C OWL standard and the Protege ontology editor.
Random subspace ensemble artificial neural networks for first-episode schizophrenia classification

Computer-aided schizophrenia diagnosis is a difficult task that has been developing for last decades. Since traditional classifiers have not reached sufficient sensitivity and specificity, another possible way is combining the classifiers in ensembles. In this paper, we take advantage of random subspace ensemble method and combine it with multi-layer perceptron (MLP) and support vector machines (SVM). Our experiment employs voxel-based morphometry to extract the grey matter densities from 52 images of first-episode schizophrenia patients and 52 healthy controls. MLP and SVM are adapted on random feature vectors taken from predefined feature pool and the classification results are based on their voting. Random feature ensemble method improved prediction of schizophrenia when short input feature vector (100 features) was used, however the performance was comparable with single classifiers based on bigger input feature vector (1000 and 10000 features).
Fast Recursive Multi-class Classification of Pairs of Text Entities for Biomedical Event Extraction

Extracting biomedical events from scientific articles to automatically update dedicated knowledge bases has become a popular research topic with important applications. Most existing approaches are either pipeline models of specific classifiers, usually subject to cascading errors, or joint structured models, more efficient but also more costly and complicated to train. This paper proposes a system based on a pairwise model that transforms event extraction into a simple multi-class problem of classifying pairs of text entities. Such pairs are recursively provided to the classifier, allowing to extract events involving other events as arguments. This model facilitates inference compared to joint models while % relying on a single main classifier compared to being more direct and efficient than usual pipeline approaches. This method yields the best results reported so far on the BioNLP 2011 and 2013 Genia tasks.
Isolation of Toxic Marine Cyanobacteria and Detection of Microcystins in Thermaikos Gulf in Central Macedonia in Greece

The presence of toxic marine cyanobacteria and secondary metabolites, microcystins, were studied in Thermaikos Gulf in Central Macedonia in Greece, during the period from March 2013 to March 2014. Toxic marine cyanobacteria were isolated in marine agar and identified with PCR using primers based on 16S rDNA. The presence of microcystins in water extraction was detected by immunoassay (competitive ELISA). The concentration was ranged from 0.15 to 5ppm. It was observed that populations of toxic marine cyanobacteria were increasing during spring and early winter and there was a correlation to the physical and chemical parameters of the water. The percentage of microcystins was 20.8 % and there were significant differences (p<0.05) between the areas and the seasons.
Interactive Isogeometric Volume Visualization with Pixel-Accurate Geometry

A recent development, called isogeometric analysis, provides a unified approach for design, analysis and optimization of functional products in industry. Traditional volume rendering methods for inspecting the results from the numerical simulations cannot be applied directly to isogeometric models. We present a novel approach for interactive visualization of isogeometric analysis results, ensuring correct, i.e., pixel-accurate geometry of the volume including its bounding surfaces. The entire OpenGL pipeline is used in a multi-stage algorithm leveraging techniques from surface rendering, order-independent transparency, as well as theory and numerical methods for ordinary differential equations. We showcase the efficiency of our approach on different models relevant to industry, ranging from quality inspection of the parametrization of the geometry, to stress analysis in linear elasticity, to visualization of computational fluid dynamics results.
Predicting Links and Inferring Attributes using a Social-Attribute Network (SAN)

The eects of social inuence and homophily suggest that both network structure and node attribute information should inform the tasks of link prediction and node attribute inference. Recently, Yin et al. [28, 29] proposed Social-Attribute Network (SAN), an attribute-augmented social network, to integrate network structure and node attributes to perform both link prediction and attribute inference. They focused on generalizing the random walk with restart algorithm to the SAN framework and showed improved performance. In this paper, we extend the SAN framework with several leading supervised and unsupervised link prediction algorithms and demonstrate performance improvement for each algorithm on both link prediction and attribute inference. Moreover, we make the novel observation that attribute inference can help inform link prediction, i.e., link prediction accuracy is further improved by rst inferring missing attributes. We comprehensively evaluate these algorithms and compare them with other existing algorithms using a novel, largescale Google+ dataset, which we make publicly available 1 .
Physical Forcing Mechanisms Controlling the Variability of Chlorophyll-a over the Royal-Charlotte and Abrolhos Banks—Eastern Brazilian Shelf

The Abrolhos Bank is part of the so-called Eastern Brazilian Shelf and is an area of high ecological and economic importance. The bank supports the largest and richest coral reefs in the South Atlantic and the largest rhodolith bed in the world. The spatial and seasonal variation of phytoplankton concentration, however, and the dynamic processes controlling that variability have remained poorly known. The present study investigates the seasonal and spatial distributions of chlorophyll-a (Chl-a) and water conditions by analyzing nine years (2003–2011) of level-3 Moderate-resolution Imaging Spectroradiometer (MODIS) derived Chl-a, National Centers for Environmental Prediction (NCEP)/ETA model-derived winds, NCEP model-derived heat fluxes, thermohaline and velocity results from the Hybrid Circulation Ocean Model (HYCOM) 1/12o assimilated simulation. The results show that low/high concentrations occurred in austral spring-summer (wet season)/autumn-winter (dry season), with the highest values observed in the northern portion of the Abrolhos Bank. The typical meteorological and oceanographic conditions during austral summer favor the development of strong stratification. These conditions are 1) N-NE winds that favor an upwelling-type Ekman circulation; 2) coupling between the open ocean and the continental shelf through the western boundary current, which promotes cooler subsurface water to rise onto the shelf break; and 3) positive net heat flux. In contrast, the S-SE winds during autumn are in the opposite direction of the predominant current system over the Abrolhos Bank, thus reducing their speed and inducing an inverse shear. The warmer ocean and a somewhat cool and dry atmosphere promote the evaporative cooling of the surface layer. The above processes drive mixed layer cooling and deepening that reaches its maximum in winter. The blooming of phytoplankton in the Abrolhos Bank waters appears to be regulated by changes in the mixed layer depth, with Chl-a levels that start to increase during autumn and reach their peak in June-July.
Neurophysiological Correlates of Laboratory-Induced Aggression in Young Men with and without a History of Violence

In order to further understand the mechanisms involved in planning an aggressive act, we conducted an event-related potential (ERP) study of young men with and without a history of violence. Participants completed a competitive reaction time task (based on the Taylor aggression paradigm) against a virtual opponent. In "passive" blocks, participants were punished by the opponent when losing the trial but could not punish, when winning, whereas in "active" blocks, participants were able to punish the opponent when winning, but were not punished when losing. Participants selected punishment strength in a decision phase prior to each reaction time task and were informed whether they had won or lost in the outcome phase. Additionally, a flanker task was conducted to assess basic performance monitoring. Violent participants selected stronger punishments, especially in "active" blocks. During the decision phase, a frontal P200 was more pronounced for violent participants, whereas non-violent participants showed an enhanced frontal negativity around 300 ms. The P200 might reflect the decision to approach the opponent at a very early state, the latter negativity could reflect inhibition processes, leading to a more considerate reaction in non-violent participants. During the outcome phase, a Feedback-Related Negativity was seen in both groups. This effect was most pronounced when losing entailed a subsequent inability to retaliate. The groups did not differ in the flanker task, indicating intact basic performance monitoring. Our data suggest that the planning of an aggressive act is associated with distinct brain activity and that such activity is differentially represented in violent and non-violent individuals.
Reliability Estimation of Parameters of Helical Wind Turbine with Vertical Axis

Due to the prolonged use of wind turbines they must be characterized by high reliability. This can be achieved through a rigorous design, appropriate simulation and testing, and proper construction. The reliability prediction and analysis of these systems will lead to identifying the critical components, increasing the operating time, minimizing failure rate, and minimizing maintenance costs. To estimate the produced energy by the wind turbine, an evaluation approach based on the Monte Carlo simulation model is developed which enables us to estimate the probability of minimum and maximum parameters. In our simulation process we used triangular distributions. The analysis of simulation results has been focused on the interpretation of the relative frequency histograms and cumulative distribution curve (ogive diagram), which indicates the probability of obtaining the daily or annual energy output depending on wind speed. The experimental researches consist in estimation of the reliability and unreliability functions and hazard rate of the helical vertical axis wind turbine designed and patented to climatic conditions for Romanian regions. Also, the variation of power produced for different wind speeds, the Weibull distribution of wind probability, and the power generated were determined. The analysis of experimental results indicates that this type of wind turbine is efficient at low wind speed.