Miracle-dz/UniFAR-FTUs huggingface dataset:
Event-Related Potentials as Indices of Time Processing: A Review

Abstract This review examines ERP data that document the mechanisms and neural bases of time processing in the millisecond-to-minute range. Several types of ERP attest to the existence of timing capacities. Among them, one component of the Contingent Negative Variation (CNV) provides an on-line index of timing. CNV data strengthen the temporal accumulator concept, designed to subtend duration encoding. This conclusion is based on four main results: The positive relationship between temporal estimates and CNV amplitude is an index of the accumulation mechanism; the CNV peak is an index of time-based decision making; the CNV relates to temporal encoding, whereas temporal long-term memory may be linked to shifts of positive polarity; learning effects on CNV amplitude depend on topographic features, thus revealing functional differences among brain regions with respect to timing.
Effect of Lightpath Bit-rate on the Dimensioning of Automatically Switched Optical Networks

We analyze the economic viability of 40 Gb/s deployment for an automatically switched optical network (ASON). We design and analyze a national network delivering a high bandwidth access to every user, and investigate the capital cost of a waveband groomed ASON for 10 Gb/s and 40 Gb/s. Based on this analysis, we show that the 40 Gb/s system is more cost-effective and scalable than the 10 Gb/s system
Ranking Images Based on Aesthetic Qualities

We propose a novel approach for learning image representation based on qualitative assessments of visual aesthetics. It relies on a multi-node multi-state model that represents image attributes and their relations. The model is learnt from pair wise image preferences provided by annotators. To demonstrate the effectiveness we apply our approach to fashion image rating, i.e., comparative assessment of aesthetic qualities. Bag-of-features object recognition is used for the classification of visual attributes such as clothing and body shape in an image. The attributes and their relations are then assigned learnt potentials which are used to rate the images. Evaluation of the representation model has demonstrated a high performance rate in ranking fashion images.
Non-asymptotic fixed-rate Slepian-Wolf coding theorem

Traditionally, Slepian-Wolf (SW) coding theorem relies on source sequences with length tending to infinity. However, in practice, the source sequences are of finite length. Towards closing this gap, we obtain non-asymptotic achievability and non-asymptotic converse for the fixed-rate SW coding by applying the NEP theorem. Furthermore, combining those converse and achievability, we show that the best SW coding rate has a Taylor-type expansion with respect to δn(ϵ) which measures the relative magnitude of the error probability ϵ and block length n. In addition, based on the Taylor-type expansion, we develop some reliable approximations (dubbed SO and NEP) for Rn(ϵ). Numerical comparison with the converse and achievability further shows that while the normal approximation and redundancy approximation reported in the literature can be either below converse or above the achievability in some cases, the SO and NEP approximations are always reliable and can serve as the benchmark for practical SW code design.
A common mutation (G-455--> A) in the beta-fibrinogen promoter is an independent predictor of plasma fibrinogen, but not of ischemic heart disease. A study of 9,127 individuals based on the Copenhagen City Heart Study.

A common mutation (G-455--> A) in the promoter region of the beta-fibrinogen gene has been associated with elevated plasma fibrinogen levels. Whether fibrinogen genotype affects plasma fibrinogen levels and risk of ischemic heart disease in the general population has not been studied. We investigated the association between fibrinogen genotype, plasma fibrinogen levels, and ischemic heart disease in a general population sample (n = 9,127). The A-allele (relative frequency, 0.20) was associated with elevated plasma fibrinogen levels in both genders (P < 0.001). While the effect of the A-allele on fibrinogen level was additive in men, the effect was dominant in postmenopausal women. The A-allele raising effect appeared to be two- to threefold greater in individuals with ischemic heart disease than in those without. An increase of 1 SD in plasma fibrinogen increased the odds ratio for ischemic heart disease by approximately 20% (P < 0.01 for women and < 0.005 for men). However, the frequency of the A-allele was similar in those with and without ischemic heart disease, and genotype was not a predictor of disease. These results demonstrate that the (G-455--> A) mutation in the promoter region of the beta-fibrinogen gene is associated with an increase in plasma fibrinogen in both genders in the general population. This increase does not appear to cause ischemic heart disease.
Automatic Linguistic Feedback in Computer Games

This paper presents a new technology for automatically generating linguistic reports and immediate feedback from actions performed by players during play sessions. These reports allow us to provide players with a more complete and personalized feedback about their behaviors, abilities, attitudes, skills and movements. In order to show and explore the possibilities of this new technology, we incorporate and implement this model into the core of a single computer game.
Museum Atmospherics: The Role of the Exhibition Environment in the Visitor Experience

ABSTRACT This review presents atmospherics as a potential model for studying the interplay between visitors and the exhibition environment in informal learning settings such as museums. Atmospherics posits that the environment influences affective, cognitive, and behavioral responses, and that these responses can be shaped by design cues in the environment (Kotler, 1974). Atmospherics and the related model of the servicescape have informed research in a variety of retail, leisure, and entertainment settings (Chang & Horng, 2010; Turley & Milliman, 2000). Applying the atmospherics model to the museum environment has considerable potential for extending our understanding of the role that the exhibition environment plays in the museum visitor experience, and informing the design of informal learning settings.
Robust Human Detection to Pose and Occlusion Using Bag-of-Words

To understand the human action in still images, it is effective to detect the human region. However, since appearance of human is much different due to pose and occlusion, the detection is quite difficult. Here we propose robust human detection method to pose and occlusion using Bag-of-Words (BoW). In general, the location information is helpful in classification. When the human has occlusion and pose changes, the location information makes the feature vector inconsistent. By using BoW which ignores the location information, we can obtain the consistent feature representation even if the local feature appears in different location by pose changes. Furthermore, when the part of human is occluded, BoW can also construct the feature representation from only visible part. Thus, BoW makes feature representation robust to partial occlusion and pose changes. By the comparison with deformable part model (DPM), the effectiveness of our method is demonstrated.
Measurement Design Framework for Network Tomography Using Fisher Information

In this paper, we study the design of measurements to infer link parameters by measuring end-to-end performance along selected paths. While existing work focuses on the inference problem under given path measurements, the accuracy of inference fundamentally hinges on the set of available measurements. To this end, we propose a generic framework to design measurements for link parameter tomography to allow for most accurate inference of link parameters. Given a link model and a set of path measurements, it is known from estimation theory that the Fisher information matrix (FIM) characterizes a lower bound on the error of the optimal unbiased estimator, asymptotically achievable by the maximum likelihood estimator (MLE). We therefore formulate our measurement design problem to minimize a function of the FIM that represents the total estimation error. We apply this framework to inferring link loss rates from path losses.
On the Reliability of AI Planning Software in Real-Time Applications

We define the reliability of a real-time system incorporating AI planning programs as the probability that, for each problem-solving request issued from the environment, the embedded system can successfully plan and execute a response within a specified real-time deadline. A methodology is developed for evaluating the reliability of such systems taking into consideration the fact that, other than program bugs, the intrinsic characteristics of AI planning programs may also cause the embedded system to fail even after all software bugs are removed from the program. The utility of the methodology is demonstrated by applying it to the reliability evaluation of two AI planning algorithms embedded in a real-time multicriteria route finding system. >
Unstructured-grid and conservative electromagnetic particle-in-cell: Application to micromachined slow-wave structures

We present an accurate and efficient electromagnetic particle-in-cell (EMPIC) algorithm on unstructured grids for the analysis and design of axisymmetric slow-wave structures. The use of unstructured grids allows for more fidelity in the modeling of micromachined geometries. The use of a reduced-dimensionality algorithm decreases the computational costs significantly and enables its integration as a forward engine into a design loop. Special gather and scatter steps are employed to yield exact charge conservation on unstructured grids. We provide numerical examples involving travelling-wave tube amplifiers designed to harness bunching effects arisen from Cherenkov radiation.
Cooperation for Social Protection

The welfare state can be seen as a measure of the social protection. A major finding within the comparative welfare state research is the differences in scope, institutionalization, and effectiveness against poverty between the institutionalized forms of social protection among the industrialized Western democracies. The major question in this article is, How can we understand and explain the causal mechanism between such institutions, social norms, and human behavior? A model is presented to show that if voters/taxpayers act out of self-interest, both a selective/minimal and an encompassing/universal welfare state are likely outcomes. The different outcomes cannot be explained by the importance of the ideology of ruling political parties or that citizens in these different countries have different basic values about social justice. Instead, the argument is that the puzzle why structurally similar countries vary so much in their systems of social protection can be solved by institutional theory.
Errorless learning in the rehabilitation of memory impaired people

Abstract We report six experiments comparing errorful and errorless learning in the teaching of new information to neurologically impaired adults with severe memory problems. The first experiment is a group study in which amnesic subjects, young controls, and older controls were required to learn two lists of words under two conditions. One of these required subjects to generate guesses that produced incorrect responses, and the other prevented guessing—permitting only correct responses. Conditions and lists were counterbalanced across subjects. People with amnesia scored significantly higher under the errorless condition. We further explored the principle of errorless learning in five single case studies in which severely memory impaired people were required to learn information analogous to that needed in everyday life. Tasks included learning names of objects and people, learning how to programme an electronic aid, remembering orientation items, and learning new items of general knowledge. In each case.
Hand Gesture Recognition with Batch and Reinforcement Learning

In this paper, we present a system for real-time recognition of user-defined static hand gestures captured via a traditional web camera. We use SURF descriptors to get the bag-of-visual-words features of the user’s hand, and use these features to train a multi-class supervised learning model. We choose the best learning model from (SVM, Neural Networks, Decision Trees, and Random Forests) and the best model parameters using hyper-parameter optimization algorithm. During test time, we use these bag-of-visual words features to predict the users hand gestures. The user has the ability to give positive or negative feedback for every prediction to the system, and the system updates itself during test time for better accuracy.
Exploring Power and Privilege Using Participatory Learning and Action Techniques

In contexts of extreme inequality in terms of resources, power and privilege, such as South Africa, students preparing to enter caring professions need to develop the capacity to become critical, thinking and caring people. This would include imagination, a desire for learning, respect and recognition, and democratic practice across racial and class differences. A Participatory Learning and Action (PLA) approach provides a valuable basis from which students can engage in experiential learning about differences and inequalities. In addition, the approach can encourage developing health and human service professionals to be critically reflective in relation to social, political and cultural assumptions they may hold about themselves and others, becoming effectors of social change. We examine how the use of PLA techniques in pedagogic practice provides an environment in which students are able to share their locations and histories across differences of race, class and gender. We describe a joint project involving senior undergraduate students of the Social Work and Occupational Therapy Departments at the University of the Western Cape, and Community Psychology at Stellenbosch University in 2006 and 2007. The article describes how the PLA exercises contributed to students' knowledge of self and others towards anti-oppressive professional practice.
Diagnosis of Invasive Pneumococcal Disease among Children in Kenya with Enzyme-Linked Immunosorbent Assay for Immunoglobulin G Antibodies to Pneumococcal Surface Adhesin A

ABSTRACT Diagnostic techniques for invasive pneumococcal disease (IPD) in children are insensitive and underestimate both the burden of disease and the cost-effectiveness of pneumococcal conjugate vaccination (PCV). Consequently, there is little demand for the highly effective PCV outside the United States and Europe. In Kenya, diagnosis of pneumococcal pneumonia in adults was achieved with a sensitivity of 0.70 and a specificity of 0.98 using enzyme-linked immunosorbent assays (ELISAs) of paired plasma samples for immunoglobulin G (IgG) to pneumococcal surface adhesin A (PsaA). We aimed to validate the same technique in children. We assayed paired blood samples from 98 children with IPD, 95 age-matched children with malaria/anemia, and 97 age-matched healthy controls by using an ELISA for anti-PsaA IgG. Sensitivity and specificity were determined in IPD patients and healthy controls. Specificity (0.97; 95% confidence interval [CI], 0.91 to 0.99) and sensitivity (0.42; 95% CI, 0.32 to 0.52) were optimized at a 2.7-fold rise in anti-PsaA antibody concentration. Sensitivity was improved to a maximum of 0.50 by restricting testing to children of <2 years old, by excluding IPD patients who were not sampled on the first day of presentation, and by incorporating high existing antibody concentrations in the analysis. Assay performance was independent of nasopharyngeal carriage of pneumococci at recruitment. This assay improves on existing diagnostic tools for IPD in children but would still leave over half of all cases undetected in epidemiological studies. Effective diagnosis of pneumococcal disease in children is urgently required but poorly served by existing technology.
The prognosis of clinical monoclonal B cell lymphocytosis differs from prognosis of Rai 0 chronic lymphocytic leukaemia and is recapitulated by biological risk factors

Monoclonal B‐cell lymphocytosis (MBL) is an asymptomatic monoclonal expansion of <5·0 × 109/l circulating CLL‐phenotype B‐cells. The relationship between MBL and Rai 0 CLL, as well as the impact of biological risk factors on MBL prognosis, are unknown. Out of 460 B‐cell expansions with CLL‐phenotype, 123 clinical MBL (cMBL) were compared to 154 Rai 0 CLL according to clinical and biological profile and outcome. cMBL had better humoral immune capacity and lower infection risk, lower prevalence of del11q22‐q23/del17p13 and TP53 mutations, slower lymphocyte doubling time, and longer treatment‐free survival. Also, cMBL diagnosis was a protective factor for treatment risk. Despite these favourable features, all cMBL were projected to progress, and lymphocytes <1·2 × 109/l and >3·7 × 109/l were the best thresholds predicting the lowest and highest risk of progression to CLL. Although IGHV status, CD38 and CD49d expression, and fluorescence in situ hybridization (FISH) karyotype individually predicted treatment‐free survival, multivariate analysis identified the presence of +12 or del17p13 as the sole independent predictor of treatment requirement in cMBL (Hazard ratio: 5·39, 95% confidence interval 1·98–14·44, P = 0·001). Overall, these data showed that cMBL has a more favourable clinical course than Rai 0 CLL. Given that the biological profile can predict treatment requirement, stratification based on biological prognosticators may be helpful for cMBL management.
Research on Radio-Map Construction in Indoor WLAN Positioning System

Indoor WLAN based positioning system required the use of a Radio-map to make the current received signal strength related to specific locations. However, the signal strength measurements are time consuming and expensive. This paper presents a Radio-map interpolating algorithm and compares the localization accuracy of measured Radio-map with interpolated Radio-map. The results presented that, although up to half of the reference points are interpolated, there was not a significant loss in localization accuracy.
Fractional-Order PI Control of First Order Plants with Guaranteed Time Specifications

Cardiospheres (CSs) are self-assembling multicellular clusters from the cellular outgrowth from cardiac explants cultured in nonadhesive substrates. They contain a core of primitive, proliferating cells, and an outer layer of mesenchymal/stromal cells and differentiating cells that express cardiomyocyte proteins and connexin 43. Because CSs contain both primitive cells and committed progenitors for the three major cell types present in the heart, that is, cardiomyocytes, endothelial cells, and smooth muscle cells, and because they are derived from percutaneous endomyocardial biopsies, they represent an attractive cell source for cardiac regeneration. In preclinical studies, CS-derived cells (CDCs) delivered to infarcted hearts resulted in improved cardiac function. CDCs have been tested safely in an initial phase-1 clinical trial in patients after myocardial infarction. Whether or not CDCs are superior to purified populations, for example, c-kit
Preservice Teachers' Perceptions of Infusing Computer Technology into Social Studies Instruction

Abstract This paper presents a study of the benefits and obstacles perceived by preservice teachers when considering the use of computer technology in social studies classes. We chose a purposive sample of education students who are in programs at technology rich institutions to begin exploring how emerging teachers would define the benefits and obstacles. We review existing research on teachers' attitudes toward technology, the barriers to technology use, and factors that facilitate technology integration. We then share our own findings, which include preservice teachers' perceptions of the benefits and potential downfalls of using technology. We identified five perceived benefits: data collection; improved student computer skills; dynamic sound and images; instructional variety; and communication tool Obstacles include: accessibility; differing ability levels; dependability; and supervision of students. A discussion of the juxtaposition of these benefits and obstacles, and the implications for teacher educators is presented.
Nine months postpartum weight retention predictors for Brazilian women

Abstract Objective: To identify factors potentially associated with weight retention measured 9 months after childbirth. Design: Prospective study with four follow-up waves in time (0.5, 2, 6 and 9 months postpartum). Setting: Rio de Janeiro, Brazil. Subjects and methods: Two hundred and sixty-six Brazilian women of childbearing age. Analysis was based on hierarchical logistic regression. The dependent variable was weight retention and was defined as the difference between weight at 9 months postpartum and pre-pregnancy weight, with a dichotomised cut-off at 7.5 kg. Covariates included demographic and socio-economic data, obstetric history, anthropometric data, and data on the infant. These data were grouped in blocks and ordered according to their influence on the dependent variable. Results: Of the women studied, 19.2% presented weight retention values ≥7.5 kg. According to the logistic regression analysis, the following variables remained associated with weight retention ≥7.5 kg: total family income, difficulty or inability to read a letter, age category ≥30 years, age at first childbirth <23 years, gestational weight gain ≥12 kg, body fat at baseline ≥30% and infant birth weight <3500 g. Infant hospitalisation was only marginally significant. Conclusions: Determinant factors identified by the analysis highlight the need for nutritional intervention policies during pregnancy and in the first months postpartum as a way of minimising obesity and the diseases resulting from it.
Relevance-weighted-reconstruction of articulatory features in deep-neural-network-based acoustic-to-articulatory mapping

We present a strategy for learning Deep-Neural-Network (DNN)-based Acoustic-to-Articulatory Mapping (AAM) functions where the contribution of an articulatory feature (AF) to the global reconstruction error is weighted by its relevance. We first empirically show that when an articulator is more crucial for the production of a given phone it is less variable, confirming previous findings. We then compute the relevance of an articulatory feature as a function of its frame-wise variance dependent on the acoustic evidence which is estimated through a Mixture Density Network (MDN). Finally we combine acoustic and recovered articulatory features in a hybrid DNN-HMM phone recognizer. Tested on the MOCHA-TIMIT corpus, articulatory features reconstructed by a standardly trained DNN lead to a 8.4% relative phone error reduction (w.r.t. a recognizer that only uses MFCCs), whereas when the articulatory features are reconstructed taking into account their relevance the relative phone error reduction increased to 10.9%.
Can a finite element method perform arbitrarily badly?

In this paper we construct elliptic boundary value problems whose standard finite element approximations converge arbitrarily slowly in the energy norm, and show that adaptive procedures cannot improve this slow convergence. We also show that the L 2 -norm and the nodal point errors converge arbitrarily slowly. With the L 2 -norm two cases need to be distinguished, and the usual duality principle does not characterize the error completely. The constructed elliptic problems are one dimensional.