Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of structural facial asymmetry in asymmetry of peak facial expressions

Asymmetric facial expression is generally attributed to asymmetry in movement, but structural asymmetry in the face may also affect asymmetry of expression. Asymmetry in posed expressions was measured using image-based approaches in digitised sequences of facial expression in 55 individuals, N=16 men, N=39 women. Structural asymmetry (at neutral expression) was higher in men than women and accounted for . 54, . 62, and . 66 of the variance in asymmetry at peak expression for joy, anger, and disgust expressions, respectively. Movement asymmetry (measured by change in pixel values over time) was found, but was unrelated to peak asymmetry in joy or anger expressions over the whole face and in facial subregions relevant to the expression. Movement asymmetry was negatively related to peak asymmetry in disgust expressions. Sidedness of movement asymmetry (defined as the ratio of summed movement on the left to movement on the right) was consistent across emotions within individuals. Sidedness was found only for joy expressions, which had significantly more movement on the left. The significant role of structural asymmetry in asymmetry of emotion expression and the exploration of facial expression asymmetry have important implications for evolutionary interpretations of facial signalling and facial expressions in general.
Manos Teatrales: an Experiment in Cyber­paleography Project Description

Many historians spend large amounts of time analyzing ancient manuscripts such as notary records, accounting books, or letters. Both before and after Gutenberg, the history of artistic, social, or political events is often recorded in hand‐written drafts of books, comedies, or music scores, and in the correspondence of authors and personalities with the world around them. Piecing together these scraps of paleographic information into a picture of an historical is often the serendipitous result of connecting far flung details. Computational methods can help escalate the rate and effectiveness of paleographic research in many ways, and we propose to conduct a seminal study in a new, multidisciplinary combination of science, technology, and literary historiography that we call cyber‐paleography. First, digital copies of manuscripts can be recorded with multispectral sensors and automatically separated into recto, verso, watermarks, and a description of the paper used. This cancels the effects of ink bleeding through pages, and makes manuscripts much easier to read for both human and computer. The chemistry and texture of the paper provide clues that may otherwise be invisible to the historian. Delicate pages conserved in library vaults become available in rich, digital form to scholars anywhere in the world. Second, the transcription of manuscript text can be enormously facilitated by semiautomatic means. Machine learning algorithms can be trained on sample pages by a given writer, and can subsequently translate text on their own. When in doubt, the algorithm presents an operator a small menu of alternative transcriptions for a highlighted word, and learns from the resulting feedback to improve its own performance. Third, a writer's handwriting style can be captured into a writer profile, a statistical account of the shape properties of letters, words, lines, and pages for that writer, and of the changes that occur over time or when different writing implements are used. Pattern analysis algorithms can then suggest, with a stated degree of confidence, the attribution of unsigned manuscripts to writers. Libraries of writer profiles can be published on the Internet, for anyone to plug into automatic transcription software. Fourth, computational inference systems can link disparate items of information, from both paleographic studies and knowledge of the customs of societies and individuals, into a virtual model of the community related to a set of documents. This model can be published online as a live, editable repository of information, somewhat in the spirit of the Wikipedia. Such a virtual …
Oyaksungisan, a Traditional Herbal Formula, Inhibits Cell Proliferation by Induction of Autophagy via JNK Activation in Human Colon Cancer Cells

Oyaksungisan (OY) is a traditional herbal formula broadly used to treat beriberi, vomiting, diarrhea, and circulatory disturbance in Asian countries from ancient times. The effect of OY on cancer, however, was not reported until now. In this study, we have demonstrated that OY inhibits cell proliferation and induces cell death via modulating the autophagy on human colon cancer cells. In HCT116 cells, OY increased the ratio of LC3-II/LC3-I, a marker of autophagy, and treatment with 3-MA, an inhibitor of autophagy, and considerably reduced the formation of autophagosomes. In addition, OY regulated mitogen-activated protein kinase (MAPK) cascades; especially, JNK activation was closely related with autophagy effect by OY in HCT116 cells. Our results indicate that autophagy induction is responsible for the antiproliferative effect by OY, despite the weak apoptosis induction in HCT116 cells. In conclusion, OY might have a potential to be developed as an herbal anticancer remedy.
Experiencing ones own hand in telexistence manipulation with a 15 DOF anthropomorphic robot hand and a flexible master glove

This paper describes a new type of robust control mechanism for a 15 DOF anthropomorphic robot hand in telexistence manipulations using a flexible fiber based master glove to experience the visual-kinesthetic sensation of one's own hand in remote manipulations. Accordingly, a master-slave telexistence system was constructed with the following: a 14 DOF modified optical fiber based data glove for capturing the complex finger postures of the master operator without any mechanical constraints; a novel finger posture mapping algorithm that is independent from the effects of different finger sizes and digit ratios; and a 15 DOF anthropomorphic slave robot hand for reconstructing the operators finger posture. This paper describes the importance of feeling one's fingers in a telexistence manipulation, control mechanism for accurate finger posture capture/reconstruction where the effectiveness has been verified through a set of experiments and a subjective evaluation.
Preparing Students and Engineers for Global Software Development: A Systematic Review

In recent years, the evolution of Global Software Development (GSD) has grown both rapidly and significantly, and although the efficiency of this new type of development has been proven, some challenging issues must still be confronted. Of all these, our research line is focused on designing the specific training that members of virtual teams must receive. Universities and companies therefore need to design training schemas to deal with the specifics of GSD, which are principally related to communication difficulties and time and cultural differences. In this work we present the findings of a Systematic Literature Review in the field of GSD training and teaching. Our intention is twofold: on the one hand we wish to discover the existing strategies and proposals available up to the present day, and on the other hand we wish to identify the open challenges, that will be helpful for practitioners and researchers in the future.
Can Risk Reducing Policies Reduce Farmer's Risk and Improve Their Welfare?

This paper develops an analytical model able to represent the decisions of an individual risk averse farmer facing variability in both prices and yields. A comprehensive set of stylised risk reducing policy measures is represented. A calibration of the model is used to run Monte-Carlo simulations and to obtain optimal responses. The main focus is the interaction between policy measures and market strategies in terms of impacts on production, welfare and risk. Risk reducing strategies that cover different sources of risk, such as price and yield variability, may be complementary for the farmers. Counter-cyclical area payments create incentives to bring land into production and their capacity to reduce farming risk is mitigated by the potential crowding out of substitutive market strategies. They are found to be more transfer efficient in terms of profit, but the impact on the farmer's welfare depends on the trade-off between optimal farm return and farm income variability reflected in the farmer's risk aversion. The policy package set up by the government matters because measures interact between each other, particularly when market mechanisms are available. In general, it is found that market mechanisms are better suited for reducing the relevant risk of farmers. Optimal policy mix crucially depends on the government objective, and there can be a trade off between risk reduction and farmers' welfare.
Can Faster Growth Save Social Security?

Numerous commissions, individual researchers, and the Trustees of the Social Security system agree that the current Social Security system is not sustainable. The 2003 Trustees' report forecasts that the program's two trust funds (Old Age and Survivors Insurance and Disability Insurance) will be empty in 2042. After 2042, Social Security taxes would only cover about 70 percent of projected benefit costs. Even before the trust funds are exhausted, the combination of rapidly growing Social Security, Medicare, and Medicaid spending is likely to create intolerable budget pressures that will force major changes in policy. The problem lies in demography. The economic burden imposed by these pay-as-you-go programs depends on the number of beneficiaries and the level of benefits that they have been promised. The economic resources available to the programs depend on the number of taxpayers and their ability and willingness to pay taxes. The population of elderly beneficiaries will soar in the future because of increased life expectancy and the retirement of baby boomers - the first boomers will apply for Social Security pensions in 2008. Meanwhile, the population of workers paying payroll taxes will stagnate because of low birth rates experienced since the early 1960s. Although there is a broad consensus that the Social Security system is in trouble, a few dissenters argue that the Trustees are too pessimistic about future economic growth. The dissenters believe that a more realistic growth assumption would allow the trust funds to remain financially sound far longer than now expected. This brief will examine the implications of more rapid economic growth for Social Security and the federal budget as a whole, including a discussion of both the direct and indirect effects of growth.
Random walks and market efficiency in European equity markets

This paper tests for random walks and weak-form market efficiency in European equity markets. Daily returns for sixteen developed markets (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and the United Kingdom) and four emerging markets (Czech Republic, Hungary, Poland and Russia) are examined for random walks using a combination of serial correlation coefficient and runs tests, Augmented Dickey-Fuller (ADF), Phillips-Perron (PP) and Kwiatkowski, Phillips, Schmidt and Shin (KPSS) unit root tests and multiple variance ratio (MVR) tests. The results, which are in broad agreement across the approaches employed, indicate that of the emerging markets only Hungary is characterized by a random walk and hence is weak-form efficient, while in the developed markets only Germany, Ireland, Portugal, Sweden and the United Kingdom comply with the most stringent random walk criteria.
Constrained fairness placement scheme in cooperative dynamic free space optical network

In this paper, a new scheme is proposed to obtain the strategic locations of the cooperative transceivers on free space optical node in last-mile network. The scheme is formulated as bi-level multiple-objective linear integer programming (BL-MO-ILP) problem, and solved by exhaustive search method to obtain the optimal solutions. The scheme leads to an increasing in the immunity of network against severe weather conditions at the efficient cost in terms of number of optical transceivers. The numerical results reveal that improvements are obtained in the network performance, reliability and fairness, specially at low visibility conditions.
The prediction of industrial bond rating changes : a multiple discriminant model versus a statistical decomposition model

The purpose of this study is to investigate the usefulness of statistical decomposition measures in the prediction of industrial bond rating changes. Further, the predictive ability of decomposition measures is compared with multiple discriminant analysis on the same sample. The problem of this study is twofold. It stems in general from the statistical problems associated with current techniques employed in the study of bond ratings and in particular from the lack of attention to the study of bond rating changes. Two main hypotheses are tested in this study. The first is that bond rating changes can be predicted through the use of financial statement data. The second is that decomposition analysis can achieve the same performance as multiple discriminant analysis in duplicating and predicting industrial bond rating changes. To explain and predict industrial bond rating changes, statistical decomposition measures were computed for each company in the sample. Based on these decomposition measures, the two types of analyses performed were (a) a univariate analysis where each decomposition measure was compared with an industry average decomposition measure, and (b) a multivariate analysis where decomposition measures were used as independent variables in a probability linear model. In addition to statistical decomposition analysis, multiple discriminant analysis was used in duplicating and predicting bond rating changes. Finally, a comparison was made between the predictive abilities of decomposition analysis and discriminant analysis.
A comparative study of NMF , DNMF , and LNMF algorithms applied for face recognition

Three techniques called non-negative matrix factorization (NMF), local non-negative matrix factorization (LNMF), and discriminant non-negative matrix factorization (DNMF), have been recently developed for decomposing a data matrix into non-negative factors named basis images and decomposition coefficients. Although these techniques are closely related to each other since they impose certain common non-negative constraints, the decomposition process of each algorithm involves a different objective function. While NMF approximates in the best possible way the data matrix by the product of its decomposition factors imposing only nonnegative constraints, LNMF adds more constraints on the basis images to reduce the redundant information between them and to enlarge their sparseness degree. DNMF imposes more constraints on the coefficients in order to take into account class information. In this paper these methods are used in the context of face recognition to extract features from two image databases (YALE and ORL). Extracted features are further classified by two metric-based classifiers, namely Maximum Correlation Classifier (MCC) and Cosine Similarity Measure (CSM). Besides, Support Vector Machines (SVMs) are also used for classification. Experiments show that when these algorithms are applied along with the aforementioned classifiers, to face recognition task they lead to quite different results, their performance being data dependent.
Phase transition to frequency entrainment in a long chain of pulse-coupled oscillators

A long chain of pulse-coupled oscillators was studied. The oscillators interacted via a phase response curve similar to those obtained from pacemaker cells in the heart. The natural frequencies were random numbers from a distribution with finite bandwidth. Stable frequency-entrained states were shown always to exist above a critical coupling strength. Below the critical coupling, the probability to have such states was shown to be zero if the number of oscillators is infinite. This discontinuity establishes the existence of a phase transition in the thermodynamic limit. For weak coupling, clusters of frequency-entrained oscillators emerged. The cluster sizes were exponentially distributed, even when the critical coupling was approached. At this coupling, the mean cluster size diverged to infinity according to a power law. The standard deviation of the distribution of mean frequencies in the chain converged to zero, also according to a power law.
Requirements Prioritization in Market-Driven Software: A Survey Based on Large Numbers of Stakeholders and Requirements

The launch of commercial off-the-shelf (COTS) software on the market requires careful planning, which incorporates a requirements prioritization process. Although there are numerous prioritization techniques, few satisfy quality criteria such as scalability, efficiency and ease of use. This research presents a survey of COTS software requirements prioritization to be potentially used by thousands of users. The HCV (Hierarchical Cumulative Voting) requirements prioritization technique was addressed and applied through a web questionnaire directly to potential users. At the end, 80 respondents sent the questionnaire and a score of requirements in ratio scale of measurement was obtained. It was found that the technique applied can respond positively to the needs and characteristics of Market-Driven Software Development, in similar situations to those described.
hiCL: an OpenCL abstraction layer for scientific computing, application to depth imaging on GPU and APU

Hardware accelerators (HWAs), such as Graphics Processing Units (GPUs) have proven their potential to boost scientific applications performance and have been widely embraced by academia and industry. The OpenCL programming model ensures portability on these HWAs and enables thus to target a large spectrum of HWAs for High Performance Computing (HPC). However, in order to deploy legacy scientific applications on HWAs, OpenCL requires extensive programming efforts and often implies adding a high number of lines of code (LOC) in the original code.
Optimization of Intrusion Detection through Fast Hybrid Feature Selection

Existing intrusion detection techniques emphasize on building intrusion detection model based on all features provided. But all features are not relevant and some of them are redundant and useless. In this paper, we propose and investigate a fast hybrid feature selection method - a fusion of Correlation-based Feature Selection, Support Vector Machine and Genetic Algorithm - to determine an optimal feature set. An appropriate feature set helps to build efficient decision model as well as reduced feature set lights up the training and testing process considerably. We have examined the feasibility of our approach by conducting several experiments using KDD 1999 CUP intrusion dataset. Experimental results indicate the reduction of training and testing time by an order of magnitude while maintaining the detection accuracy within tolerable range.
Evaluation and Comparison of the Biopathology of Collagen and Inflammation in the Extracellular Matrix of Oral Epithelial Dysplasias and Inflammatory Fibrous Hyperplasia Using Picrosirius Red Stain and Polarising Microscopy: A Preliminary Study

Background: The role of tumour inflammation and the dysplastic epithelial-stromal interactions on the nature of collagen fibres in the extracellular matrix of dysplastic epithelium is not fully understood. The present study was aimed to evaluate and compare the inflammation and pathological stromal collagen (loosely packed thin disorganized collagen) present in mild, moderate and severe epithelial dysplasias with that of inflammatory fibrous hyperplasias. The basement membrane intactness of epithelial dysplasias was also evaluated to determine if dysplastic epithelial mesenchymal interaction has any role in the integrity of stromal collagen in epithelial dysplasia. Methods: Oral epithelial dysplasias, inflammatory fibrous hyperplasia and normal oral mucosal samples were used for the study. Packing, thickness and orientation of collagen fibres in mild, moderate and severe grades of oral epithelial dysplasias (n = 24), inflammatory fibrous hyperplasia (n = 8) and normal oral mucosal samples (n = 8) were analysed based on the polarisation of collagen fibres in picrosirius red polarising stain under polarising microscope. Results: All the grades of epithelial dysplasias showed greenish yellow birefringence confirming the presence of loosely arranged pathological collagen in the presence of moderate inflammation. All the cases of inflammatory fibrous hyperplasia showed red polarisation hue and moderate inflammation. A statistically significant difference was found in the packing and orientation of collagen when epithelial dysplasias and inflammatory fibrous hyperplasia were compared (P < 0.01). When the intactness of basement membrane integrity was compared in all the groups of epithelial dysplasia, a statistically significant result was obtained (P < 0.05). Conclusions: Presence of significant amount of loosely packed thin disoriented collagen even in mild epithelial dysplasia suggests that tumourigenic factors are released to connective tissue stroma much earlier than expected. Hence we suggest considering the integrity of extracellular matrix collagen, intactness of basement membrane and inflammation associated with dysplasia along with the anaplasia of epithelial cells in the microscopic assessment of dysplastic epithelium.
Effects of trade liberalization on agriculture in Viet Nam : commodity aspects

This book analyzes commodity aspects of the effects of trade liberalization on agriculture in Viet Nam. The study analyzes the effects of trade liberalization on selected commodities namely rice, coffee, rubber, tea and groundnut, at the national level and the farm level. The analysis includes ex-ante and ex-post welfare gain and loss at the national level and profitability at the farm level.
Understanding Compulsive Use Of Facebook Through The Reinforcement Processes

With over 1 billion active users, Facebook is possibly the biggest phenomenon of the Internet. For the majority of individuals, Facebook represents an incredible social platform for social connection and information sharing. For others, however, the use of Facebook can lead to significant behavioural or psychological problems. Despite a rising concern over this emerging global issue, the theoretical understanding of the problematic use of technologies is lacking in the IS literature. Therefore, the main objective of this study is to propose a research model to theoretically explain the development of compulsive use of Facebook. We tested our research model using an online survey with 209 active Facebook users. Our results suggested that compulsive use of Facebook is mainly determined by negative reinforcement motive (i.e., feeling of withdrawal), but not the positive reinforcement motive (i.e., need for mood alteration). Preference for online social interaction is also found important in determining compulsive use of Facebook. This study provides a theoretical explanation of compulsive use of Facebook, and the results help clinicians, educators, and parents understand the main drivers of Facebook compulsive use.