Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal decomposition: a promising approach to VQ-based speaker identification

In this paper, a new set of features is proposed that has been found to improve the performance of automatic speaker identification systems. The new set of features is referred to as "even targets". The new features have been derived from line spectral frequency (LSF) parameters using the so-called "temporal decomposition" (TD) technique. The number of feature vectors required for both training and testing phases has been reduced by one-fifth compared to that of the traditional mel-frequency cepstrum coefficients (MFCC) features, while the identification results obtained are comparable or even better. Also, this work introduces one more application of TD (speaker recognition) in addition to speech coding, speech segmentation, and speech recognition. It shows that the event targets in TD can convey information about the identity of a speaker.
Correction for Bardy et al., Neuronal medium that supports basic synaptic functions and activity of human neurons in vitro

NEUROSCIENCE Correction for “Neuronal medium that supports basic synaptic functions and activity of human neurons in vitro,” by Cedric Bardy, Mark van den Hurk, Tameji Eames, Cynthia Marchand, Ruben V. Hernandez, Mariko Kellogg, Mark Gorris, Ben Galet, Vanessa Palomares, Joshua Brown, Anne G. Bang, Jerome Mertens, Lena Böhnke, Leah Boyer, Suzanne Simon, and Fred H. Gage, which appeared in issue 20, May 19, 2015, of Proc Natl Acad Sci USA (112:E2725–E2734; first published April 13, 2015; 10.1073/pnas.1504393112). The authors note that the statement in the Acknowledgments “National Institute of Mental Health (to F.H.G.)” should instead appear as “National Institute of Mental Health Grant NIH MH095741 (to F.H.G.). ”
Candidate Self − monitor Self − diagnosis Self − adaptationSelf − testing event Anomalous Fault identificationDeployment fix generation

Existing approaches to software security and reliability h ave proven inadequate in offering a good tradeoff between the assurance, reliability, availability, and performance. We argue that reactive protection mechanisms need to be added to our panoply of defenses. Furthermore, we argue that such m ec anisms need to be much more invasive than previously envisioned. We discus s o r approach to such mechanisms by introducing the concept of self-healing software. We describe the principles behind self-healing software systems and sh owcase the concepts by giving an overview the Worm Vaccine architecture.
A Clustering Algorithm based on Local Accumulative Knowledge

Clustering as an important unsupervised learning technique is widely used to discover the inherent structure of a given data set. For clustering is depended on applications, researchers use different models to defined clustering problems. Heuristic clustering algorithm is an efficient way to deal with clustering problem defined by combining optimization model, but initialization sensitivity is an inevitable problem. In the past decades, a lot of methods have been proposed to deal with such problem. In this paper, on the contrary, we take the advantage of the initialization sensitivity to design a new clustering algorithm. We, firstly, run K-means, a widely used heuristic clustering algorithm, on data set for multiple times to generate several clustering results; secondly, propose a structure named Local Accumulative Knowledge ( LAKE ) to capture the common information of clustering results; thirdly, execute the Single-linkage algorithm on LAKE to generate a rough clustering result; eventually, assign the rest data objects to the corresponding clusters. Experimental results on synthetic and real world data sets demonstrate the superiority of the proposed approach in terms of clustering quality measures.
Mass spectral analysis of urine proteomic profiles of dairy cows suffering from clinical ketosis

Background: Ketosis is an important metabolic disorder in dairy cows during the transition period. The urine proteomics of ketosis has not been investigated using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Objective: The aim is to determine differences between urine proteomic profiles of healthy cows and those with clinical ketosis, and facilitate studies of the underlying physiological and biochemical mechanisms that lead to liver pathology in ketosis. Animals and methods: We analyzed the urine samples of 20 cows with clinical ketosis (group 1) and 20 control cows (group 2) using SELDI-TOF-MS. Results: Thirty-nine peptide peaks differed between both groups. Polypeptides corresponding to 26 of these differential peptide peaks were identified using the SWISS-PROT protein database. We found that the peaks of 11 distinct polypeptides from the urine samples of the ketosis group were significantly reduced, compared with those of the control group as based on the Wilcoxon rank sum test. Among these were VGF (non-acronymic) protein, amyloid precursor protein, serum amyloid A (SAA), fibrinogen, C1INH, apolipoprotein C-III, cystatin C, transthyretin, hepcidin, human neutrophil peptides, and osteopontin. Conclusion: These proteins may represent novel biomarkers of the metabolic changes that occur in dairy cows with ketosis. Our results will help to better understand the physiological changes and pathogenesis observed in cows with ketosis. Clinical importance: The SELDI-TOF-MS can be used to understand the physiological and biochemical mechanisms of ketosis and identify biomarkers of the disease.
Normes d'associations verbales pour 366 noms d'objets concrets

Resume ; Cet article presente des normes d'associations verbales developpees pour la recherche en psycholinguistique. Il comprend les associations verbales libres de plus de 300 mots en francais, testes sur 89 sujets de langue maternelle francaise, âges de 18 a 25 ans. Ces normes seront utiles pour les chercheurs et les etudiants de nombreux champs de la psychologie, en particulier l'etude du langage et de la memoire, ou le degre d'association entre des paires de mots constitue un facteur important. Il s'agit des premieres normes de grande envergure publiees en francais. La partie principale de l'article presente une liste alphabetique de toutes les reponses associees avec leurs frequences d'associations pour chacun des 366 mots stimuli. ; Mots-cles : normes d'associations verbales.
Experimental analysis of a ring oscillator network for hardware Trojan detection in a 90nm ASIC

The modern integrated circuit (IC) manufacturing process has exposed chip designers to hardware Trojans which threaten circuits bound for critical applications. This paper details the implementation and analysis of a novel ring oscillator network technique for Trojan detection in an application specific integrated circuit (ASIC). The ring oscillator network serves as a power supply monitor by detecting fluctuations in characteristic frequencies due to malicious modifications (i.e. hardware Trojans) in the circuit under authentication. The ring oscillator network was implemented and fabricated in 40 IBM 90nm ASICs with controlled hardware Trojans. This work analyzes the impact of Trojans with varied partial activity, area, and location on the proposed ring oscillator structure and demonstrates that stealthy Trojans can be efficiently detected with this technique even while obfuscated by process variations, background noise, and environment noise.
Finding and Accessing Diagrams in Biomedical Publications

Complex relationships in biomedical publications are often communicated by diagrams such as bar and line charts, which are a very effective way of summarizing and communicating multi-faceted data sets. Given the ever-increasing amount of published data, we argue that the precise retrieval of such diagrams is of great value for answering specific and otherwise hard-to-meet information needs. To this end, we demonstrate the use of advanced image processing and classification for identifying bar and line charts by the shape and relative location of the different image elements that make up the charts. With recall and precisions of close to 90% for the detection of relevant figures, we discuss the use of this technology in an existing biomedical image search engine, and outline how it enables new forms of literature queries over biomedical relationships that are represented in these charts.
Consuming Ambivalences

Consumers handle politicized consumption practices such as food risks in more ambivalent ways than is often assumed in public debate about such issues. This article attempts to show the analytical relevance of clarifying and using the concept of ambivalence in analysis of consumer culture. In particular, this is because societal problems of ambivalence are often framed as personal problems for consumers via campaigns to make consumers discipline their so-called problematic practices. The article argues in favour of working with a concept of ambivalence that is sensitive to a variety of socio-cultural ways of handling ambivalence in consumption practices. Theoretically, the article connects such a concept of ambivalence to an understanding of consumption that is grounded in ‘weak’ constructivist everyday life sociology. Empirically, the article presents examples of experiences of ambivalence from a Danish qualitative study of consumers' handling of environmentally related food risks
An Iterative Structured Judgment Process for Establishing Standards on Competency Tests: Theory and Application

This paper reports the results of research on a judgmental method for establishing standards on competency tests. The research had several objectives: first, to demonstrate the feasibility of a new, and somewhat more complex standardsetting method than has been used in the past; second, to examine the degree of similarity of standards recommended by judges having different types of interest and involvement in secondary education; third, to explore relationships between the background characteristics of judges and their recommended standards; fourth, to search for relationships between the characteristics of test items, and judges' assessments of their importance in contributing to decisions on whether students should
Music compositional intelligence with an affective flavor

The consideration of human feelings in automated music generation by intelligent music systems, albeit a compelling theme, has received very little attention. This work aims to computationally specify a system's music compositional intelligence that tightly couples with the listener's affective perceptions. First, the system induces a model that describes the relationship between feelings and musical structures. The model is learned by applying the inductive logic programming paradigm of FOIL coupled with the Diverse Density weighting metric over a dataset that was constructed using musical score fragments that were hand-labeled by the listener according to a semantic differential scale that uses bipolar affective descriptor pairs. A genetic algorithm, whose fitness function is based on the acquired model and follows basic music theory, is then used to generate variants of the original musical structures. Lastly, the system creates chordal and non-chordal tones out of the GA-obtained variants. Empirical results show that the system is 80.6% accurate at the average in classifying the affective labels of the musical structures and that it is able to automatically generate musical pieces that stimulate four kinds of impressions, namely, favorable-unfavorable, bright-dark, happy-sad, and heartrending-not heartrending.
Curvature-based shading of translucent materials, such as human skin

The paper introduces a new approximate method for rendering translucent materials. We represent the surface around a point to be rendered in Monge's form using principal curvatures. The subsurface reflectance equation in the dipole diffusion approximation [Jensen et al. 2001] is then integrated over the surface. The outgoing radiance at the point is expressed as a function of principal curvatures and light vector components along the principal directions. This function can be precomputed as a 2D lookup table, which can be stored as a texture image. The paper presents preliminary results of our work on implementation of the model described.
C2A: Crowd consensus analytics for virtual colonoscopy

We present a medical crowdsourcing visual analytics platform called C2A to visualize, classify and filter crowdsourced clinical data. More specifically, C2A is used to build consensus on a clinical diagnosis by visualizing crowd responses and filtering out anomalous activity. Crowdsourcing medical applications have recently shown promise where the non-expert users (the crowd) were able to achieve accuracy similar to the medical experts. This has the potential to reduce interpretation/reading time and possibly improve accuracy by building a consensus on the findings beforehand and letting the medical experts make the final diagnosis. In this paper, we focus on a virtual colonoscopy (VC) application with the clinical technicians as our target users, and the radiologists acting as consultants and classifying segments as benign or malignant. In particular, C2A is used to analyze and explore crowd responses on video segments, created from fly-throughs in the virtual colon. C2A provides several interactive visualization components to build crowd consensus on video segments, to detect anomalies in the crowd data and in the VC video segments, and finally, to improve the non-expert user's work quality and performance by A/B testing for the optimal crowdsourcing platform and application-specific parameters. Case studies and domain experts feedback demonstrate the effectiveness of our framework in improving workers' output quality, the potential to reduce the radiologists' interpretation time, and hence, the potential to improve the traditional clinical workflow by marking the majority of the video segments as benign based on the crowd consensus.
Endocarditis: effects of routine echocardiography during Gram-positive bacteraemia.

BACKGROUND Despite firm recommendations to perform echocardiography in high-risk patients with Gram-positive bacteraemia, routine echocardiography is not embedded in daily practice in many settings. The aim of this study was to evaluate whether a regime including routine echocardiography results in better outcome. METHODS A total of 115 patients with Gram-positive bacteraemia and at least one risk factor for developing metastatic infection were prospectively included. Routine echocardiography was advocated and facilitated in these patients. Results were compared with a matched historical control group of 230 patients in whom echocardiography was performed at the discretion of the attending physician. Endocarditis was diagnosed according to the Duke criteria. RESULTS Echocardiography was performed more often in the study group (82 vs 27%, p.
Evaluating Readability of Domestic Violence Information Found on Domestic Violence State Coalitions' Websites

ABSTRACT With the popularity of the Internet, more and more individuals are accessing health and mental health information from an array of websites. Yet, health literacy has emerged as barrier despite easier access to health information. The U.S. Department of Education (1986) stated that educational materials should be no higher than 8th grade reading level; yet, the reality is that often information written is above this level. This study examined the grade reading level and readability (as measured by the SMOG, Flesch-Kincaid Grade Level, and the Flesch Reading Ease) of domestic violence materials on the websites of domestic violence state coalitions. Findings indicated that the average grade reading level of the domestic violence materials were statistically significantly higher than the 8th grade standard. This was true regardless of the region where the domestic violence state coalitions were located. Implications for social service providers were discussed.
FACTOR STRUCTURE OF THE GRE GENERAL TEST FOR OLDER EXAMINEES: IMPLICATIONS FOR CONSTRUCT VALIDITY

The aim of this study was to appraise the extent to which the GRE General Test has the same construct validity for older test takers as it has for other examinees by comparing the interrelationships among the test items for subgroups of examinees defined by age. The items in the test were factor analyzed for three samples of examinees, 20-29 years old, 30-39 years old, and 40-49 years old. The same verbal, quantitative, and analytical ability factors were found in each sample, but the intercorrelations of the factors increased slightly, though consistently, with the age of the sample. These results suggest that the convergent validity of the test is similar across these age groups, but the discriminant validity is somewhat different for the older examinees. It was also found, in each sample, that the items in the analytical measure had a substantial amount of specific variance and that the analytical ability factor was highly correlated with the other factors, implying that these items have relatively little in common with each other and overlap excessively with verbal and quantitative ability.
Deceivers and Emotion: The Relationships Among Deceptive Message Type, Relational Qualities, and Guilt and Shame

Research has identified emotions as key components of the deception process (Buller & Burgoon, 1996). Yet, examining emotions in conjunction with deception has been branded an under-researched area (Seiter & Bruschke, 2007). The goal of this study was to discover if relational qualities (commitment and satisfaction) and the type of deceptive message communicated (lie, evasion, overstatement, concealment, or collusion) related to feelings of guilt and shame following deception. Participants were asked to recall the most recent time they deceived their romantic partner, describe the lie, and complete relational quality and emotional response measures. Results indicate that the type of deceptive message communicated was not related to relational qualities. Further, feelings of guilt and shame did not differ based on type of deception. However, results indicate positive relationships between the emotional experiences of guilt and shame and relational qualities of commitment and satisfaction. Implications, limitations, and future research are discussed.
Playing push vs pull: models and algorithms for disseminating dynamic data in networks

Consider a network in which a collection of source nodes maintain and periodically update data objects for a collection of sink nodes, each of which periodically accesses the data originating from some specified subset of the source nodes. We consider the task of efficiently relaying the dynamically changing data objects to the sinks from their sources of interest. Our focus is on the following "push-pull" approach for this data dissemination problem. Whenever a data object is updated, its source relays the update to a designated subset of nodes, its push set; similarly, whenever a sink requires an update, it propagates its query to a designated subset of nodes, its pull set. The push and pull sets need to be chosen such that every pull set of a sink intersects the push sets of all its sources of interest. We study the problem of choosing push sets and pull sets to minimize total global communication while satisfying all communication requirements.We formulate and study several variants of the above data dissemination problem, that take into account different paradigms for routing between sources (resp., sinks) and their push sets (resp., pull sets) -- multicast, unicast, and controlled broadcast -- as well as the aggregability of the data objects. Under the multicast model, we present an optimal polynomial time algorithm for tree networks, which yields a randomized O(log n)-approximation algorithm for n-node general networks, for which the problem is hard to approximate within a constant factor. Under the unicast model, we present a randomized O(log n)-approximation algorithm for non-metric costs and a matching hardness result. For metric costs, we present an O(1)-approximation and matching hardness result for the case where the interests of any two sinks are either disjoint or identical. Finally, under the controlled broadcast model, we present optimal polynomial-time algorithms.While our optimization problems have been formulated in the context of data communication in networks, our problems also have applications to network design and multicommodity facility location and are of independent interest.
The design of isotherm face recognition technique based on nostril localization

In this paper, the researchers propose a new approach to identify the physiological thermal infrared image characteristics. First, using color segmentation algorithm to extract the face from the background. Then out of the nose by the dynamic temperature changes, through the nostrils to locate and formalize the length and width of the face image. The hair, glasses, nose and beard neither conducive to the stability of recognition. In this study, the range will be below the nostrils as the regional scope of face recognition. And divide the thermal image into five temperature layers. Finally, the use of statistical methods is to identify the temperature layer of the feature points. The results can also be found in the capture of different faces, and the resulting physical characteristics are not the same. The researchers successfully used this feature for thermal imaging of human face recognition. The proposed identification method is feasible by the field-proven, and the identification of cross-match success rate is 95.6%.
Credit Risk Assessment with Least Squares Fuzzy Support Vector Machines

In this study, the authors discuss a least squares version of fuzzy support vector machine (FSVM) classifiers for designing a credit risk assessment system to discriminate good creditors from bad ones. Relative to the classical FSVM, the least squares FSVM (LS-FSVM) can transform a quadratic programming problem into a linear programming problem thus reducing the computational complexity. For illustration, a real-world credit dataset is used to test the effectiveness of the LS-FSVM
ASD: the Alternative Splicing Database

Alternative splicing is widespread in mammalian gene expression, and variant splice patterns are often specific to different stages of development, particular tissues or a disease state. There is a need to systematically collect data on alternatively spliced exons, introns and splice isoforms, and to annotate this data. The Alternative Splicing Database consortium has been addressing this need, and is committed to maintaining and developing a value-added database of alternative splice events, and of experimentally verified regulatory mechanisms that mediate splice variants. In this paper we present two of the products from this project: namely, a database of computationally delineated alternative splice events as seen in alignments of EST/cDNA sequences with genome sequences, and a database of alternatively spliced exons collected from literature. The reported splice events are from nine different organisms and are annotated for various biological features including expression states and cross-species conservation. The data are presented on our ASD web pages (http://www.ebi.ac.uk/asd).