Miracle-dz/UniFAR-FTUs huggingface dataset:
Shared Nearest Neighbors Match Kernel for Bird Songs Identification - LifeCLEF 2015 Challenge

This paper presents a new fine-grained audio classification technique designed and experimented in the context of the LifeCLEF 2015 bird species identification challenge. Inspired by recent works on fine-grained image classification, we introduce a new match kernel based on the shared nearest neighbors of the low level audio features extracted at the frame level. To make such strategy scalable to the tens of millions of MFCC features extracted from the tens of thousands audio recordings of the training set, we used high-dimensional hashing techniques coupled with an efficient approximate nearest neighbors search algorithm with controlled quality. Further improvements are obtained by (i) using a sliding window for the temporal pooling of the raw matches (ii) weighting each low level feature according to the semantic coherence of its nearest neighbors. Results show the effectiveness of the proposed technique which ranked 2nd among the 7 research groups participating to the LifeCLEF bird challenge.
A novel curve lane detection based on Improved River Flow and RANSA

Accurate and robust lane detection, especially the curve lane detection, is the premise of Lane Departure Warning System (LDWS) and Forward Collision Warning System (FCWS). Lane detection on the structural roads under challenging scenarios such as the dashed lane markings and vehicle occlusion is a difficult task because of unreliable lane feature point. In this paper, a robust curve lane detection method based on Improved River Flow (IRF) and RANSAC method is proposed to detect curve lane under challenging conditions. The lane markings are grouped into a near vision field of straight line and a far vision field of curve line. The curve lanes are based on Hyperbola-pair model. To determine the coefficient of curvature, a novel method is proposed based on Improved River Flow method and RANSAC method. In the new method, Improved River Flow method is employed to search feature points in the far vision field guided by the results of detected straight lines in near vision field or the curve lines from last frame, which can connect dashed lane markings or obscured lane markings. So, it is robust on dashed lane markings and vehicle occlusion. Then, RANSAC is utilized to calculate the curvature, which can eliminate noisy feature points obtained from Improved River Flow. The experimental results show that the proposed method can robustly and accurately detect some challenging markings, such as the dashed lane markings and vehicle occlusion.
What drives political consumption in Europe? A multi-level analysis on individual characteristics, opportunity structures and globalization

Political consumption is an individualized form of collective action that varies considerably across Europe. Citizens as consumers participate in boycotts and ‘positive’ buying of goods based on ethical, political and environmental considerations. Overcoming the individualistic bias of past research, the comparative analysis extends actor-centred explanations by focusing on political, cultural and economic opportunity structures and on globalization as contextual factors. Economic opportunities for political consumption are provided by national affluence, retailing structures and the supply of environmental and fair-labelled goods. Political and cultural opportunities are facilitated by ‘statist’ institutions, social movement organizations as well as trust and post-materialist culture. The impact of globalization is measured by international economic exchange. Logistic multi-level models on the first wave of the European Social Survey for 19 countries reveal that economic opportunity structures and political institutions best explain variations, while globalization does not affect citizens’ decisions to voice their interest in consumption. Finally, the effect of individual value orientations is increased by a low-cost context.
Notes on a Chipewyan Dialect

1. In the summer of 1967, while teaching at the University of Alberta, Edmonton, I had the opportunity of visiting Camsell Hospital, where Indians from various parts of western Canada are brought for treatment. It was my hope that a speaker of one of the lesser known northern Athapaskan languages might be in residence. As it turned out, of the two who were considered well enough to be interviewed on the day of my first visit, one was a speaker of Chipewyan, the other of Beaver. In order to acquaint them with what I wanted, I took down a dozen or so words from each of them, starting with the numerals. In looking over my notes I observed that I had recorded the Chipewyan word for three with an initial /k/ instead of the expected /t/. 1 Although it seemed likely that this was a simple error, I remembered that Kiowa-Apache and other
IT-enabled policy analysis: new technologies, sophisticated analysis and open data for better government decisions

For a long time, governments have promoted initiatives to make a great diversity of information available in order to enhance productivity, effectiveness and strategic decision-making. Today, a revitalized wave of open access to data has focused on making government activities more transparent, participatory and collaborative; together, these activities represent "open government. " Some open data initiatives are intensively supported by the use of flexible and powerful information technologies and various analytical methods. This paper argues that there is a new window of opportunity to combine emergent information technologies, sophisticated analytical methods, and a great diversity of datasets in order to improve government capabilities and make better decisions. However, this strategy, which we are now calling IT-enabled policy analysis, would require adequate governance models, individuals with analytical skills, the availability of adequate data, and sophisticated information technologies. The potential benefits of creating organizations with powerful analytical capabilities within governments, universities, and non-government organizations are numerous and the impact on society could be great. However, there are also some important political, organizational, and technical challenges.
Have We Drawn the Wrong Conclusions About the Value of Care Pathways? Is a Cochrane Review Appropriate?

Care pathways are used increasingly worldwide to organize patient care. However, different views exist about their effectiveness. One of the reasons for this is that pathways are complex interventions. A recent Cochrane review was published which reported positive results, but although the Cochrane team performed excellent work with an enormous commitment, the conclusions may be inappropriate. To fully understand the potential and problems of care pathways, it is important to define (a) exactly what we are talking about (b) whether the study methods are appropriate, and (c) whether we can properly define the outcomes.
Impact of 2013 ASCO/CAP HER2 reporting guidelines in breast cancer: An assessment study from Indian oncology centre that primarily performs HER2 IHC testing with special emphasis on IHC equivocal category

The ASCO/CAP guidelines for HER2 reporting in breast cancer published in 2007 and were updated in 2013 to assure that the right patient receives the targeted therapy. The updated guidelines have lowered the threshold for HER2 positivity criteria and altered the equivocal category for both IHC and FISH. This first study from India addresses the impact of these updated guidelines in the various reporting categories at a tertiary care centre. We compared the trend of HER2 IHC reporting 1 year before (Period A) and 1 year after (Period B) the implementation of updated 2013 ASCO/CAP guidelines. All HER2 equivocal IHC cases of post 2013 guidelines were reclassified as per 2007 guidelines to detect additional number of cases that have been put into equivocal category. Reflex FISH correlation was also assessed to detect any additional cases eligible for anti HER2 therapy with implementation of these updated guidelines. With implementation of updated 2013 guidelines, there was significant decrease in the number of cases scored as 1+ (from 30.7% to 20.6%; P value: .0001) while significant increase in number of 2+ cases (from 20.2% to 27.3%; P value: .004). Post 2013 guidelines, 39% (64 cases) of tumors were additionally put into the equivocal category which would have been considered as negative (score 1+) as per 2007 guidelines. The reflex FISH testing in these equivocal cases resulted in detection of only 1.5% of additional cases eligible for anti HER2 therapy. With implementation of updated 2013 guidelines, there is no significant increase in HER2 positivity trend. However, there is appreciable increase in IHC equivocal cases which subsequently led to increased reflex FISH testing without significantly contributing to the detection of additional eligible cases for anti HER2 therapy, but resulted in delaying of definite HER2 status along with financial implications.
Fast and Feasible Deliberative Motion Planner for Dynamic Environments

We present an approach to the problem of differentially constrained mobile robot motion planning in arbitrary time-varying cost fields. We construct a special search space which is ideally suited to the requirements of dynamic environments including a) feasible motion plans that satisfy differential constraints, b) efficient plan repair at high update rates, and c) deliberative goal-directed behavior on scales well beyond the effective range of perception sensors. The search space contains edges which adapt to the state sampling resolution yet aquire states exactly in order to permit the use of the dynamic programming principle without introducing infeasibility. It is a symmetric lattice based on a repeating unit of controls which permits off-line computation of the planner heuristic, motion simulation, and the swept volumes associated with each motion. For added planning efficiency, the search space features fine resolution near the vehicle and reduced resolution far away. Furthermore, its topology is updated in real-time as the vehicle moves in such a way that the underlying motion planner processes changing topology as an equivalent change in the dynamic environment. The planner was originally developed to cope with the reduced computation available on the Mars rovers. Experimental results with research prototype rovers demonstrate that the planner allows us to exploit the entire envelope of vehicle maneuverability in rough terrain, while featuring real-time performance.
Overexpression of NANOG in human ES cells enables feeder-free growth while inducing primitive ectoderm features

Human embryonic stem cells (HESCs) are pluripotent cells derived from the ICM of blastocyst stage embryos. As the factors needed for their growth are largely undefined, they are propagated on feeder cells or with conditioned media from feeder cells. This is in contrast to mouse embryonic stem cells (MESCs) where addition of leukemia inhibitory factor (LIF) replaces the need for a feeder layer. Recently, the transcription factor Nanog was suggested to allow LIF and feeder-free growth of MESCs. Here, we show that NANOG overexpression in HESCs enables their propagation for multiple passages during which the cells remain pluripotent. NANOG overexpressing cells form colonies efficiently even at a very low density, an ability lost upon excision of the transgene. Cells overexpressing NANOG downregulate expression of markers specific to the ICM and acquire expression of a marker specific to the primitive ectoderm (the consecutive pluripotent population in the embryo). Examination of global transcriptional changes upon NANOG overexpression by DNA microarray analysis reveals new markers suggested to discriminate between these populations. These results are significant in the understanding of self-renewal and pluripotency pathways in HESCs, and of their use for modeling early development in humans.
CoCITe—Coordinating Changes in Text

Text streams are ubiquitous and contain a wealth of information, but are typically orders of magnitude too large in scale for comprehensive human inspection. There is a need for tools that can detect and group changes occurring within text streams and substreams, in order to find, structure, and summarize these changes for presentation to human analysts. This paper describes a procedure for efficiently finding step changes, trends, bursts, and cyclic changes affecting frequencies of words, or more general lexical items, within streams of documents which may be optionally labeled with metadata. The common phenomenon of over-dispersion is accommodated using mixture distributions. A streaming implementation is described which can process data from a continuous feed. Anomalies can be detected, grouped, and rendered visually for human comprehension.
Metabolism of L-Arginine by Myeloid-Derived Suppressor Cells in Cancer: Mechanisms of T cell suppression and Therapeutic Perspectives

Patients with cancer have an impaired T cell response that can decrease the potential therapeutic benefit of cancer vaccines and other forms of immunotherapy. The establishment of a chronic inflammatory environment in patients with cancer plays a critical role in the induction of T cell dysfunction. The accumulation of myeloid-derived suppressor cells (MDSC) in tumor bearing hosts is a hallmark of malignancy-associated inflammation and a major mediator of the induction of T cell suppression in cancer. Recent findings in tumor bearing mice and cancer patients indicate that the increased metabolism of L-Arginine (L-Arg) by MDSC producing Arginase I inhibits T cell lymphocyte responses. Here, we discuss some of the most recent concepts of how MDSC expressing Arginase I may regulate T cell function in cancer and suggest possible therapeutic interventions to overcome this inhibitory effect.
Receptor Specificity and Transmission of H2N2 Subtype Viruses Isolated from the Pandemic of 1957

Influenza viruses of the H2N2 subtype have not circulated among humans in over 40 years. The occasional isolation of avian H2 strains from swine and avian species coupled with waning population immunity to H2 hemagglutinin (HA) warrants investigation of this subtype due to its pandemic potential. In this study we examined the transmissibility of representative human H2N2 viruses, A/Albany/6/58 (Alb/58) and A/El Salvador/2/57 (ElSalv/57), isolated during the 1957/58 pandemic, in the ferret model. The receptor binding properties of these H2N2 viruses was analyzed using dose-dependent direct glycan array-binding assays. Alb/58 virus, which contains the 226L/228S amino acid combination in the HA and displayed dual binding to both alpha 2,6 and alpha 2,3 glycan receptors, transmitted efficiently to naïve ferrets by respiratory droplets. Inefficient transmission was observed with ElSalv/57 virus, which contains the 226Q/228G amino acid combination and preferentially binds alpha 2,3 over alpha 2,6 glycan receptors. However, a unique transmission event with the ElSalv/57 virus occurred which produced a 226L/228G H2N2 natural variant virus that displayed an increase in binding specificity to alpha 2,6 glycan receptors and enhanced respiratory droplet transmissibility. Our studies provide a correlation between binding affinity to glycan receptors with terminal alpha 2,6-linked sialic acid and the efficiency of respiratory droplet transmission for pandemic H2N2 influenza viruses.
A Partitioning Fuzzy Clustering Algorithm for Symbolic Interval Data based on Adaptive Mahalanobis Distances

The recording of symbolic interval data has become a common practice with the recent advances in database technologies. This paper introduces a fuzzy clustering algorithm to partitioning symbolic interval data. The proposed method furnish a fuzzy partition and a prototype (a vector of intervals) for each cluster by optimizing an adequacy criterion that measures the fitting between the clusters and their representatives. To compare symbolic interval data, the method use a suitable adaptive Mahalanobis disance defined on vectors of intervals. Experiments with real and synthetic symbolic interval data sets showed the usefulness of the proposed method.
Identifying some factors that might predispose drug abuse among learners in a South African township school

Abstract This study inquires into some of the factors that might predispose the use and abuse of drugs among secondary school learners in a township school. The objective of this research is to identify these factors and to offer a few suggestions on how the abuse may be prevented. A quantitative research strategy is used and a document analysis technique has been incorporated to collect the data. Various hypotheses are stated. The independent variables used are: gender; age group; educational category; distance from school; and caregiver. The dependent variables used are: alcohol abuse; marijuana abuse; cigarette smoking; other drug abuse; total number of abuses; and outcomes at school. Statistically significant relationships are found between the following variables: distance from school and cigarette smoking; distance from school and other drug abuse; caregiver and marijuana abuse; and caregiver and total number of abuses.
Finding the positive in loss: stillbirth and its potential for parental empowerment

Abstract This paper reports on PhD research that investigated parental experience of stillbirth. Drawing on in-depth interviews with 10 couples and 12 mothers, it argues that while the experience of stillbirth is, to some extent, a stigmatising one – parents recount feeling like failures and report social difficulties after the loss (Murphy, 2009) – there are positives that may be taken from the experience. These, however, are more likely to emerge in the medium and longer term. Far from being ‘passive victims of prejudice’ (Shih, 2004), some parents may be empowered to take action to improve local and, in some cases, national maternity services, as well as raising people's awareness of stillbirth and breaking the silence that surrounds it.
Extensively hydrolysed casein formula supplemented with Lactobacillus rhamnosus GG maintains hypoallergenic status: randomised double-blind, placebo-controlled crossover trial

Objective To evaluate the hypoallergenicity of an extensively hydrolysed (EH) casein formula supplemented with Lactobacillus rhamnosus GG (LGG). Design A prospective, randomised, double-blind, placebo-controlled crossover trial. Setting Two study sites in Italy and The Netherlands. Study participants Children with documented cow's milk allergy were eligible for inclusion in this trial. Interventions After a 7-day period of strict avoidance of cow's milk protein and other suspected food allergens, participants were tested with an EH casein formula with demonstrated hypoallergenicity (control, EHF) and a formula of the same composition with LGG added at 108 colony-forming units per gram powder (EHF-LGG) in randomised order in a double-blind placebo-controlled food challenge (DBPCFC). After absence of adverse reactions in the DBPCFC, an open challenge was performed with EHF-LGG, followed by a 7-day home feeding period with the same formula. Main outcome measure Clinical assessment of any adverse reactions to ingestion of study formulae during the DBPCFC. Results For all participants with confirmed cow's milk allergy (n=31), the DBPCFC and open challenge were classified as negative. Conclusion The EH casein formula supplemented with LGG is hypoallergenic and can be recommended for infants and children allergic to cow's milk who require an alternative to formulae containing intact cow's milk protein. Trial registration number http://ClinicalTrials.gov Identifier: NCT01181297.
A method for accurate localization of the first heart sound and possible applications

We have previously developed a method for localization of the first heart sound (S1) using wavelet denoising and ECG-gated peak-picking. In this study, an additional enhancement step based on cross-correlation and ECG-gated ensemble averaging (EA) is presented. The main objective of the improved method was to localize S1 with very high temporal accuracy in (pseudo-) real time. The performance of S1 detection and localization, with and without EA enhancement, was evaluated on simulated as well as experimental data. The simulation study showed that EA enhancement reduced the localization error considerably and that S1 could be accurately localized at much lower signal-to-noise ratios. The experimental data were taken from ten healthy subjects at rest and during invoked hyper- and hypotension. For this material, the number of correct S1 detections increased from 91% to 98% when using EA enhancement. Improved performance was also demonstrated when EA enhancement was used for continuous tracking of blood pressure changes and for respiration monitoring via the electromechanical activation time. These are two typical applications where accurate localization of S1 is essential for the results.
Precise vector textures for real-time 3D rendering

Vector graphics representations of images are resolution independent. Direct use of vector images for real-time texture mapping would be desirable to avoid sampling artifacts such as blurring common with raster images. Scalable Vector Graphics (SVG) files are typical of vector graphics image representations. Such representations composite images from layers of paths and strokes defined with lines, elliptical arcs, and quadratic and cubic parametric splines. High-quality texture mapping requires both random access and anisotropic antialiasing. For vector images, these goals can be achieved by computing the distance to the closest primitives from a sample point and then mapping this distance through a soft threshold function. Representing transparency masks in this way is especially useful, since vector mattes can be used to render complex curvilinear geometry as textures on simple geometric primitives. Unfortunately, computing the exact minimum distance to the parametric curves used in vector images is difficult. Previous work has used approximations, but an accurate minimum distance is desirable in order to enable wide strokes and special effects such as embossing. In this paper, a simple algorithm is presented that can efficiently and accurately compute the minimum distance to a parametric curve when the sample point is within its radius of curvature and the curve can be segmented into monotonic regions. This technique can be used in a GPU shader to render antialiased vector images exactly as defined by SVG files.
Bayesian blind separation of audio mixtures with structured priors

In this paper we describe a Bayesian approach for separation of linear instantaneous mixtures of audio sources. Our method exploits the sparsity of the source expansion coefficients on a time-frequency basis, chosen here to be a MDCT. Conditionally upon an indicator variable which is 0 or 1, one source coefficient is either set to zero or given a Student t prior. Structured priors can be considered for the indicator variables, such as horizontal structures in the time-frequency plane, in order to model temporal persistency. A Gibbs sampler (a standard Markov chain Monte Carlo technique) is used to sample from the posterior distribution of the indicator variables, the source coefficients (corresponding to nonzero indicator variables), the hyperparameters of the Student t priors, the mixing matrix and the variance of the noise. We give results for separation of a musical stereo mixture of 3 sources.