Miracle-dz/UniFAR-FTUs huggingface dataset:
What is the Effect of Audio Quality on the Robustness of MFCCs and Chroma Features?

Music Information Retrieval is largely based on descriptors computed from audio signals, and in many practical applications they are to be computed on music corpora containing audio files encoded in a variety of lossy formats. Such encodings distort the original signal and therefore may affect the computation of descriptors. This raises the question of the robustness of these descriptors across various audio encodings. We examine this assumption for the case of MFCCs and chroma features. In particular, we analyze their robustness to sampling rate, codec, bitrate, frame size and music genre. Using two different audio analysis tools over a diverse collection of music tracks, we compute several statistics to quantify the robustness of the resulting descriptors, and then estimate the practical effects for a sample task like genre classification.
News Coverage of Cancer in the United States: A National Sample of Newspapers, Television, and Magazines

A content analysis of cancer news coverage in a sample of local and national newspapers, television, and magazines was conducted for the years 2002 and 2003. Analyses compared proportions of mentions of cancer sites with proportional contribution to cancer incidence and mortality based on available epidemiological estimates. Analyses also examined relative attention provided to prevention, detection, treatment, causes, and outcomes of various cancers. Results indicated that coverage reflected incidence rates more closely than they did mortality rates, but in both cases coverage under-represented the contribution of lung cancer to morbidity and mortality and over-represented the contribution of breast cancer. Of greater public health concern was the limited coverage of prevention and detection even for highly preventable or relatively easily detected cancers. Implications of findings are discussed.
A Sentence-to-Sentence Relation Network for Recognizing Textual Entailment

 Abstract — Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.
Outcomes of children adopted from Eastern Europe

Behavioral problems are frequent among post-institutionalized Eastern European adoptees. However, risk factors related to outcomes have not been fully delineated. We evaluated 50 Eastern European adoptees, age 8—10 years, with their adoptive families for more than five years. Cognitive and behavioral outcomes and parenting stress were evaluated in relation to pre-adoptive risk factors, including arrival age, growth, and facial phenotype related to prenatal alcohol exposure. At follow-up, IQ and achievement scores were ≥ average in most children (≥74%). Behavioral and school problems were common (externalizing 44%, internalizing 18%, behavioral symptoms 50%, attention deficit hyperactivity disorder (ADHD) 46%, learning disabilities 40%, mental health disorders 28%); 38% had multiple problems. Behavioral problems correlated inversely with IQ. Parent stress was high and correlated with child externalizing behaviors and inversely to child full scale IQ. Children with “severe behavioral disturbances” (24%) were more likely to have had smaller head circumferences at arrival. Child's age at adoption related inversely to parent stress, possibly due to the longer duration of time that children resided with their families. “High/intermediate risk” phenotypic facial scores for prenatal alcohol exposure (58%) correlated with head circumference z scores at arrival and follow-up. Otherwise, arrival age, growth, and facial phenotype did not correlate with these specific outcome measures.
Predicting BCI Subject Performance Using Probabilistic Spatio-Temporal Filters

Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI) has become increasingly popular. In this work, we discuss a novel, fully Bayesian–and thereby probabilistic–framework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO) and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO framework allows to analyze which spatio-spectral parameters are common and which ones differ across the subject population. As expected, large variability of brain rhythms is observed between subjects. We have clustered subjects according to similarities in their corresponding spectral characteristics from the BSSFO model, which is found to reflect their BCI performances well. In BCI, a considerable percentage of subjects is unable to use a BCI for communication, due to their missing ability to modulate their brain rhythms–a phenomenon sometimes denoted as BCI-illiteracy or inability. Predicting individual subjects’ performance preceding the actual, time-consuming BCI-experiment enhances the usage of BCIs, e.g., by detecting users with BCI inability. This work additionally contributes by using the novel BSSFO method to predict the BCI-performance using only 2 minutes and 3 channels of resting-state EEG data recorded before the actual BCI-experiment. Specifically, by grouping the individual frequency characteristics we have nicely classified them into the subject ‘prototypes’ (like μ - or β -rhythm type subjects) or users without ability to communicate with a BCI, and then by further building a linear regression model based on the grouping we could predict subjects' performance with the maximum correlation coefficient of 0.581 with the performance later seen in the actual BCI session.
H2A.Z has a function reminiscent of an activator required for preferential binding to intergenic DNA

H2A.Z has been shown to regulate transcription in yeast, and that function resides in its C‐terminal region as the reciprocal portion of H2A cannot substitute for the latter. We show that fusion of a transcriptional activating region to the C‐terminal region of H2A, which is substituted for that of H2A.Z, can allow the chimera to fulfil the special role of H2A.Z in positive gene regulation, as well as complement growth deficiencies of htz1Δ cells. We further show that the ‘transcription’ function of H2A.Z is linked to its ability to preferentially localize to certain intergenic DNA regions. Our results suggest that H2A.Z modulates functional interactions with transcription regulatory components, and thus increases its localization to promoters where it helps poise chromatin for gene activation.
Impact of Hypokalemia on Electromechanical Window, Excitation Wavelength and Repolarization Gradients in Guinea-Pig and Rabbit Hearts

Normal hearts exhibit a positive time difference between the end of ventricular contraction and the end of QT interval, which is referred to as the electromechanical (EM) window. Drug-induced prolongation of repolarization may lead to the negative EM window, which was proposed to be a novel proarrhythmic marker. This study examined whether abnormal changes in the EM window may account for arrhythmogenic effects produced by hypokalemia. Left ventricular pressure, electrocardiogram, and epicardial monophasic action potentials were recorded in perfused hearts from guinea-pig and rabbit. Hypokalemia (2.5 mM K+) was found to prolong repolarization, reduce the EM window, and promote tachyarrhythmia. Nevertheless, during both regular pacing and extrasystolic excitation, the increased QT interval invariably remained shorter than the duration of mechanical systole, thus yielding positive EM window values. Hypokalemia-induced arrhythmogenicity was associated with slowed ventricular conduction, and shortened effective refractory periods, which translated to a reduced excitation wavelength index. Hypokalemia also evoked non-uniform prolongation of action potential duration in distinct epicardial regions, which resulted in increased spatial variability in the repolarization time. These findings suggest that arrhythmogenic effects of hypokalemia are not accounted for by the negative EM window, and are rather attributed to abnormal changes in ventricular conduction times, refractoriness, excitation wavelength, and spatial repolarization gradients.
A Nested Case-Control Study of Intrauterine Exposure to Persistent Organochlorine Pollutants in Relation to Risk of Type 1 Diabetes

Background The incidence of type 1 diabetes in Europe is increasing at a rate of about 3% per year and there is also an increasing incidence throughout the world. Type 1 diabetes is a complex disease caused by multiple genetic and environmental factors. Persistent organochlorine pollutants (POPs) have been suggested as a triggering factor for developing childhood type 1 diabetes. The aim of this case-control study was to assess possible impacts of in utero exposure to POPs on type 1 diabetes. Methodology/ Principal Findings The study was performed as a case-control study within a biobank in Malmö, a city located in the Southern part of Sweden. The study included 150 cases (children who had their diagnosis mostly before 18 years of age) and 150 controls, matched for gender and day of birth. 2,2′,4,4′,5,5′-hexachlorobiphenyl (PCB-153) and the major DDT metabolite 1,1-dichloro-2,2-bis (p-chlorophenyl)-ethylene (p,p′-DDE) were used as a biomarkers for POP exposure. When comparing the quartile with the highest maternal serum concentrations of PCB-153 with the other quartiles, an odds ratio (OR) of 0.73 (95% confidence interval [CI] 0.42, 1.27) was obtained. Similar results was obtained for p,p′-DDE (OR 0.56, 95% CI 0.29, 1.08). Conclusions The hypothesis that in utero exposure to POPs will trigger the risk for developing type 1 diabetes was not supported by the results. The risk estimates did, although not statistically significant, go in the opposite direction. However, it is not reasonable to believe that exposure to POPs should protect against type 1 diabetes.
Why Replication Probabilities Depend on Prior Probability Distributions

Killeen (2005) recommended replacing the p values of significance tests with replication probabilities, which he determined as follows: Assume dx, the estimate of the effect size d in study x, is positive and its sampling error, ex 5 dx d, is normally distributed with mean 0 and variance s, that is, N(0, s). It follows that the effect size in a replication, dy5 (d1 ey), can be rewritten as (dx ex 1 ey), where ey is the replication sampling error. Consequently, dy is distributed asN(dx, 2s ), because dx is a constant and ex and ey are independently distributed as N(0, s). The replication probability (prep), the probability that dy > 0, can now be found by integrating the distribution of dy (see Killeen’s Equation 1):
Polymorphisms in the tumour necrosis factor gene are not associated with severity of inflammatory polyarthritis

Background: Tumour necrosis factor alpha (TNFα) is a powerful inflammatory mediator in rheumatoid and other types of inflammatory arthritis. Polymorphisms within the TNFα gene have previously been investigated to determine their role in the aetiopathogenesis of rheumatoid arthritis (RA), but it is unclear whether reported associations are with susceptibility to, or severity of, disease. Objective: To examine the association between both individual TNFα single nucleotide polymorphisms (SNPs) and haplotypes with the development and severity of erosions by 5 years in patients with inflammatory polyarthritis (IP). Methods: 438 patients from the Norfolk Arthritis Register observational inception cohort of patients with IP were x rayed 5 years after disease onset. They were genotyped for nine SNPs mapping to the TNFα gene, using a SNaPshot primer extension assay. Haplotypes were constructed in patients with IP, who were compared for the presence and extent of erosions at 5 years. Results: No association between individual TNFα SNPs or haplotypes in the patients who developed erosions at 5 years compared with those who remained non-erosive was found. Restricting analysis to patients who satisfied ACR criteria for RA by 5 years did not affect the conclusions. Conclusion: The TNFα gene does not seem to be associated with severity as assessed by erosive outcome at 5 years in patients with IP.
Cost-effectiveness analysis of a rotavirus immunization program for the United States.

CONTEXT Rotavirus is the most common cause of severe diarrhea in children, and a live, oral vaccine may soon be licensed for prevention. OBJECTIVE To estimate the economic impact of a national rotavirus immunization program in the United States. DESIGN Cost-effectiveness was analyzed from the perspectives of the health care system and society. A decision tree used estimates of disease burden, costs, vaccine coverage, efficacy, and price obtained from published and unpublished sources. INTERVENTION The proposed vaccine would be administered to infants at ages 2, 4, and 6 months as part of the routine schedule of childhood immunizations. MAIN OUTCOME MEASURES Total costs, outcomes prevented, and incremental cost-effectiveness. RESULTS A routine, universal rotavirus immunization program would prevent 1.08 million cases of diarrhea, avoiding 34000 hospitalizations, 95000 emergency department visits, and 227000 physician visits in the first 5 years of life. At $20 per dose, the program would cost $289 million and realize a net loss of $107 million to the health care system-$103 per case prevented. The program would provide a net savings of $296 million to society. Threshold analysis identified a break-even price per dose of $9 for the health care system and $51 for the societal perspective. Greater disease burden and greater vaccine efficacy and lower vaccine price increased cost-effectiveness. CONCLUSIONS A US rotavirus immunization program would be cost-effective from the perspectives of society and the health care system, although the cost of the immunization program would not be fully offset by the reduction in health care cost of rotavirus diarrhea unless the price fell to $9 per dose.
Mediating commons: rural Greece

Diffusion of innovation theorizes on how human beings adopt new communication technology, but it fails to take into account the institutional factors involved in the process. In this study involving new communicational technology use in a small Greek rural village, it is determined that the village cafe, as the central socializing element in the community, plays a powerful role in dissemination of new communicational devices, or what this article conceptualizes as `mediating commons'. Such mediating commons social institutions as the village cafe play a significant role in encouraging the adoption of new communication products; without such a mediating commons in a community, adoption rates may reduce significantly and lead to a spreading digital divide.
Accelerometer-Based Method for Extracting Respiratory and Cardiac Gating Information for Dual Gating during Nuclear Medicine Imaging

Both respiratory and cardiac motions reduce the quality and consistency of medical imaging specifically in nuclear medicine imaging. Motion artifacts can be eliminated by gating the image acquisition based on the respiratory phase and cardiac contractions throughout the medical imaging procedure. Electrocardiography (ECG), 3-axis accelerometer, and respiration belt data were processed and analyzed from ten healthy volunteers. Seismocardiography (SCG) is a noninvasive accelerometer-based method that measures accelerations caused by respiration and myocardial movements. This study was conducted to investigate the feasibility of the accelerometer-based method in dual gating technique. The SCG provides accelerometer-derived respiratory (ADR) data and accurate information about quiescent phases within the cardiac cycle. The correct information about the status of ventricles and atria helps us to create an improved estimate for quiescent phases within a cardiac cycle. The correlation of ADR signals with the reference respiration belt was investigated using Pearson correlation. High linear correlation was observed between accelerometer-based measurement and reference measurement methods (ECG and Respiration belt). Above all, due to the simplicity of the proposed method, the technique has high potential to be applied in dual gating in clinical cardiac positron emission tomography (PET) to obtain motion-free images in the future.
Unbalanced-to-Balanced and Balanced-to-Unbalanced Diplexer With High Selectivity and Common-Mode Suppression

Two novel balun diplexers based on stub-loaded resonators are presented and carefully examined in this paper. Besides being diplexers, the two balun diplexers are also interface devices between a single-ended (differential) antenna and differential (single-ended) receiver and transmitter. The stub-loaded resonator not only has an extra degree of freedom to realize the anticipant coupling scheme, but it also can compact the circuit size and enlarge the frequency separation of the first differential- and common-mode resonant frequencies. The design procedure of the balun filter with three 50- Ω ports is introduced based on a symmetric four-port balanced-to-balanced bandpass filter. Two demonstrated balun diplexers, unbalanced-to-balanced and balanced-to-unbalanced diplexers, with Rx and Tx frequencies at 1.84 and 2.45 GHz are designed, fabricated, and measured. The implemented balun diplexers present an excellent in-band balanced performance with common-mode rejection ratio better than 38 dB over the passbands. High selectivity and isolation are also obtained by giving a cross-coupling scheme for both Rx and Tx balun filters.
Extension of HVS semantic parser by allowing left-right branching

The hidden vector state (HVS) parser is a popular method for semantic parsing. It is used in the language understanding module of the statistical based spoken dialog system. This paper presents an extension of the HVS semantic parser. It enables the parser to generate broader class of semantic trees. This modification can be used to improve the performance of the parser by generating not only the right-branching trees (like original HVS parser) but also limited left-branching trees and their combinations. The extension retains simplicity and properties of the original HVS parser. We tested the method on Czech human-human train timetable corpus. The modified HVS parser yields statistically significant improvement. The accuracy of the system increased from 50.4% to 58.3% absolutely.
Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations

We demonstrate that almost all non-parametric dimensionality reduction methods can be expressed by a simple procedure: regularized loss minimization plus singular value truncation. By distinguishing the role of the loss and regularizer in such a process, we recover a factored perspective that reveals some gaps in the current literature. Beyond identifying a useful new loss for manifold unfolding, a key contribution is to derive new convex regularizers that combine distance maximization with rank reduction. These regularizers can be applied to any loss.
Alzheimer's Disease and its Management

Alzheimer’s disease is an irreversible, progressive brain disease that slowly destroyes and thinking skills and eventually even the ability to carry out the simplest tasks. Alzheimer’s disease is the most common cause of dementia among older people. In this review, we have mainly discussed different pharmacological treatments which are helpful in the treatment of Alzheimer’s disease.
Public Sphere 2.0? The Democratic Qualities of Citizen Debates in Online Newspapers

Comments in online news could be the contemporary enactment of the eighteenth-century cafés that founded public sphere. This article assesses to what extent do these forms of digital discussion fit in Habermas’ principles for democratic debate, using his discursive ethics as a demanding normative benchmark. The sample of more than 15,000 comments was selected from the online versions of five national newspapers of record from different political and journalistic contexts: The Guardian (United Kingdom), Le Monde (France), The New York Times (United States), El País (Spain), and La Repubblica (Italy). The ethical guidelines and legal frameworks set up by the newspapers as well as their moderation strategies were considered to understand the different settings of the conversations. Two models of audience participation emerge from the analysis, one where communities of debate are formed based on mostly respectful discussions between diverse points of view and another of homogenous communities, in which expressing feelings about current events dominates the contributions and there is less of an argumentative debate.
Role of Edge Detection in Video Semantics

The semantic gap or semantic chasm is a well-known problem in content-based image and video retrieval. To address this problem, many techniques have been proposed in the literature. A more common approach is the use of low-level features such as colour, texture and shape for semantic analysis. Our focus in this paper is on the edge feature, which has not been exploited to the same extent as other low-level features for semantic analysis. In this paper, we present an algorithm for edge detection, and illustrate the usage of edges for semantic analysis of video content.We first propose an algorithm for detecting edges within video frames directly on the MPEG format without a decompression process. The algorithm is based on a spatial-domain synthetic edge model, which is defined using interrelationship of two DCT edge features: horizontal and vertical. We use a multistep approach to classify video sequences into meaningful semantic segments such as "goal", "foul", and "crowd" in basketball games using the "edgeness" criteria. We then show how an audio feature ("whistle") can be used as a filter to enhance edge-based semantic classification fro sports videos.