Miracle-dz/UniFAR-FTUs huggingface dataset:
A statistical method for language-independent representation of the topical content of text segments

Where there are texts in more than one language, it would be desirable if users could give queries or examples in the language in which they are most competent and obtain relevant text passages in any language. We have developed and tested a prototype system that makes this possible. The system is based entirely on a statistical technique that requires no humanly constructed dictionary, thesaurus, or term bank. The language-independent representation of text has two steps. In the rst, done just once for a subject area, a sample collection of parallel texts|paragraph-by-paragraph translations in two or more languages|is analyzed by a mathematical technique called Singular Value Decomposition. Each word in the sample is assigned a vector value determined by the total pattern of usage of all the words in all the sample paragraphs. In the second step, a new document or query in any of the original languages is assigned a vector value that is an average of the values of the words it contains. Tests on a French-English corpus showed that the method works well. Key-words: Interlingua, IR, information retrieval, statistical techniques, LSI, SVD, semantics, translation, multilingual lters
Compressive Sensing of a Taylor-Fourier Multifrequency Model for Synchrophasor Estimation

Synchrophasor measurements, performed by phasor measurement units (PMUs), are becoming increasingly important for power system network monitoring. Synchrophasor standards define test signals for verification of PMU compliance, and set acceptance limits in each test condition for two performance classes (P and M ). Several PMU algorithms have been proposed to deal with steady-state and dynamic operating conditions identified by the standard. Research and discussion arising from design, implementation, testing and characterization of PMUs evidenced that some disturbances, such as interharmonic interfering signals, can seriously degrade synchrophasor measurement accuracy. In this paper, a new compressive sensing (CS) approach is introduced and applied to synchrophasor measurements using a CS Taylor-Fourier (TF) multifrequency (CSTFM) model. The aim is to exploit, in a joint method, the properties of CS and the TF transform to identify the most relevant components of the signal, even under dynamic conditions, and to model them in the estimation procedure, thus limiting the impact of harmonic and interhamonic interferences. The CSTFM approach is verified using composite tests derived from the test conditions of the synchrophasor standard and simulation results are presented to show its potentialities.
Natriuretic peptides and cyclic guanosine 3',5'-monophosphate in asymptomatic and symptomatic left ventricular dysfunction.

BACKGROUND: Screening for patients with asymptomatic left ventricular dysfunction is of considerable importance because they may benefit from early treatment with angiotensin converting enzyme inhibitors. It has been suggested that atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP), and cyclic guanosine 3',5'-monophosphate (cGMP) might be useful markers for screening. OBJECTIVE: To compare directly the power of the three immunoreactive forms of ANP (CT-ANP, beta-ANP, NT-ANP) and BNP and cGMP to detect asymptomatic left ventricular dysfunction. METHODS AND RESULTS: Radionuclide ventriculography was used to study left ventricular ejection fraction in 37 patients with asymptomatic left ventricular dysfunction, 32 patients with mild to moderate congestive heart failure, and 38 controls. CT-ANP, NT-ANP, beta-ANP, BNP, and cGMP were measured at rest and 3 minutes after exercise. Plasma BNP was the most sensitive marker for patients with asymptomatic left ventricular dysfunction but it reached only a sensitivity of 58% and a specificity of 76% at rest and a sensitivity of 65% and a specificity of 84% after exercise. Combined measurements of all natriuretic peptides and cGMP did not improve the power to detect asymptomatic left ventricular function above that of a single BNP measurement. CONCLUSIONS: Although natriuretic peptides and cGMP measured at rest and three minutes after ergometry may be useful for monitoring left ventricular dysfunction they are unlikely to be suitable for more general routine screening for completely asymptomatic left ventricular dysfunction.
Self-immobilizing recombinant antibody fragments for immunoaffinity chromatography: generic, parallel, and scalable protein purification.

We present the directed immobilization of recombinant antibody fragments as ligands for general immunoaffinity chromatography methods. It is based on fusion proteins of scFv fragments with several chitin-binding domains which can be immobilized directly from a crude bacterial lysate on inexpensive chitin beads for the purification of proteins without any gradient or detector. It has been used with a positive pressure manifold, allowing the parallel processing of 24 different samples on a milligram scale, as convenient as plasmid isolation. The method is demonstrated with several anti-protein antibodies. In addition, methods are presented of using an anti-His tag antibody either alone or directly coupled to IMAC to obtain very pure protein. As those methods are scalable, they should prove very useful in the parallel purification of natural and recombinant proteins on small scales (for proteomics), medium scales (for crystallography and NMR), and very large scales (for therapeutic proteins).
Simulating a $ 2 M Commercial Server on a $ 2 K PC T

T he Internet has made database management systems and Web servers integral parts of today’s business and communications infrastructure. These and other commercial transaction-processing applications work with critical personal and business data—storing it, providing access to it, and manipulating it. As dependence on these applications increases, so does the need for them to run reliably and efficiently. Our group at the University of Wisconsin (www.cs.wisc.edu/multifacet/) researches innovative ways to improve the performance of the multiprocessor servers that run these important commercial applications. Execution-driven simulation is a design evaluation tool that models system hardware. These simulations capture actual program behavior and detailed system interactions. They are more flexible and less expensive than hardware prototypes, and they model important system details more accurately than analytic modeling does. However, the combination of large systems and demanding workloads is difficult to simulate, especially on the inexpensive machines available to most researchers. Commercial workloads, unlike simpler workloads, rely heavily on operating system services such as input/output, process scheduling, and interprocess communication. To run commercial workloads correctly, simulators must model these services. In addition, multiprocessor servers introduce the challenges of interactions among processors, large main memories, and many disks. To make effective use of limited simulation resources, researchers must balance three goals:
Minimum mean square error spectral peak envelope estimation for automatic vowel classification

Spectral feature computations continue to be a very difficult problem for accurate machine recognition of vowels especially in the presence of noise or for otherwise degraded acoustic signals. In this work, a new peak envelope method for vowel classification is developed, based on a missing frequency components model of speech recognition. According to this model, vowel recognition depends only on the location of spectral peaks. Also, smoothing and interpolation of the sampled spectra, performed in the cepstral analysis method commonly used in automatic speech recognition results in a loss of valuable information. The new method for feature extraction presented in this paper is based on minimum mean square error curve fitting of cosine-like basis vectors to all peaks in the speech spectrum. A mathematical model for smoothly tracking spectral envelopes using only spectral peak information and ignoring other parts of the spectrum is presented. A software algorithm for the model was developed and tested for various speaker types using a neural network classifier. Vowel classification experiments were conducted based on the features derived from the spectral peaks. The classification rates of the peak method under various signal to noise ratios was also evaluated. The basic conclusion is that the new features perform the same as cepstral features for clean speech, but have advantages when the signal is degraded by noise.
Unequal error protection in distributed source coding for wireless sensor networks

In this paper, we will discuss the unequal error protection (UEP) problem in distributed source coding (DSC) which has been studied and proved to be efficient for scattered applications, especially for wireless sensor networks (WSN). For WSN, non-uniform noise distribution should fall into our consideration when coding and decoding, resulting in UEP problem for source sequence. Using linear-programming approach for non-uniform Low-density parity-check (LDPC) code, we can easily get the optimal degree distribution for parity check matrix. So different parts of source sequence fed into distinct channels can be separately protected. We propose a simpler structure of DSC for pairs of correlated sources based on syndrome (DISCUS) [1], and also consider the rate adaptive property of non-uniform LDPC code. Reasonable coding rates are generated for different channel conditions by changing the maximum variable node degree and one threshold we proposed in the algorithm, which is defined as the probability of setting sub-degree distributions as non-zero number. Simulation results show a beneficial effect based on the assumption that the crossover probability or mean square error is known.
A temporally piece-wise fisher vector approach for depression analysis

Depression and other mood disorders are common, disabling disorders with a profound impact on individuals and families. Inspite of its high prevalence, it is easily missed during the early stages. Automatic depression analysis has become a very active field of research in the affective computing community in the past few years. This paper presents a framework for depression analysis based on unimodal visual cues. Temporally piece-wise Fisher Vectors (FV) are computed on temporal segments. As a low-level feature, block-wise Local Binary Pattern-Three Orthogonal Planes descriptors are computed. Statistical aggregation techniques are analysed and compared for creating a discriminative representative for a video sample. The paper explores the strength of FV in representing temporal segments in a spontaneous clinical data. This creates a meaningful representation of the facial dynamics in a temporal segment. The experiments are conducted on the Audio Video Emotion Challenge (AVEC) 2014 German speaking depression database. The superior results of the proposed framework show the effectiveness of the technique as compared to the current state-of-art.
Tierless Programming and Reasoning for Networks

Modern network software is implemented across two tiers: the data plane, which contains packet-processing rules implemented efficiently on switching hardware, and the control plane, which implements fundamental algorithms, policies, and business rules that determine what the data plane should do. Thus, programming the network is akin to programming a two-tier, massively distributed system, where each node has heterogeneous processing capabilities. In addition, the persistent store on the controller represents a third tier. This splitting across tiers leads to both correctness and performance errors. In response, we have designed a language, Flowlog, for programming networks in a "tierless" way that unifies descriptions of control, data, and external state. Tierless programming not only simplifies programming but also makes it easier to express and reason about invariants that cross-cut tiers. In this talk I will discuss applications of Flowlog to both Software-Defined Networking and programming Internet of Things networks. I will also discuss a variety of analysis tasks. This talk describes joint work with Tim Nelson, Andrew Ferguson, Michael Scheer, and Rodrigo Fonseca.
Effectiveness of Computer Tailoring Versus Peer Support Web-Based Interventions in Promoting Physical Activity Among Insufficiently Active Canadian Adults With Type 2 Diabetes: Protocol for a Randomized Controlled Trial

Background Type 2 diabetes is a major challenge for Canadian public health authorities, and regular physical activity is a key factor in the management of this disease. Given that less than half of people with type 2 diabetes in Canada are sufficiently active to meet the Canadian Diabetes Association's guidelines, effective programs targeting the adoption of regular physical activity are in demand for this population. Many researchers have argued that Web-based interventions targeting physical activity are a promising avenue for insufficiently active populations; however, it remains unclear if this type of intervention is effective among people with type 2 diabetes. Objective This research project aims to evaluate the effectiveness of two Web-based interventions targeting the adoption of regular aerobic physical activity among insufficiently active adult Canadian Francophones with type 2 diabetes. Methods A 3-arm, parallel randomized controlled trial with 2 experimental groups and 1 control group was conducted in the province of Quebec, Canada. A total of 234 participants were randomized at a 1:1:1 ratio to receive an 8-week, fully automated, computer-tailored, Web-based intervention (experimental group 1); an 8-week peer support (ie, Facebook group) Web-based intervention (experimental group 2); or no intervention (control group) during the study period. Results The primary outcome of this study is self-reported physical activity level (total min/week of moderate-intensity aerobic physical activity). Secondary outcomes are attitude, social influence, self-efficacy, type of motivation, and intention. All outcomes are assessed at baseline and 3 and 9 months after baseline with a self-reported questionnaire filled directly on the study websites. Conclusions By evaluating and comparing the effectiveness of 2 Web-based interventions characterized by different behavior change perspectives, findings of this study will contribute to advances in the field of physical activity promotion in adult populations with type 2 diabetes. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN): ISRCTN15747108; http://www.isrctn. com/ISRCTN15747108 (Archived by WebCite at http://www.webcitation.org/6eJTi0m3r)
Stochastic wire-length model with TSV placement on periphery area

Despite of numerous advantages of three dimensional integrated circuits (3D-ICs), their commercial success remains limited. The reason lies, in part, on the lack of physical design tools about Through-Silicon-Vias (TSVs) and 3D die stacking. In this paper, we propose a novel TSV placement method on the periphery of the dies. Based on this method, we derive a novel mathematical model to estimate 3D-IC wire-length and area with TSVs before floor-planning. We analyze the impact of TSVs on silicon area and wire-length. A case study with ISCAS benchmark circuits demonstrates that the proposed TSV placement method reduces the chip area and alleviates the reliability issues.
A Low-Power, Dual-Wavelength Photoplethysmogram (PPG) SoC With Static and Time-Varying Interferer Removal

This paper presents a low-power, reflectance-mode photoplethysmogram (PPG) front end with up to 100 μA of static interferer current removal and 87 dB attenuation of time-varying interferers. The chip nominally consumes 425 μW including signal chain circuits, red and IR LED drive power, clocks, digitization and I/O. Measured data shows the noise of the PPG signal to be dominated by the photodiode sensor photon shot noise.
Synergistic Effect of TGF-β1 And BMP–7 on Chondrogenesis and Extracellular Matrix Synthesis: An In Vitro Study

Introduction: The purpose of the present study seeks to determine the signal timing of BMP–7 and TGF-β1 from a novel chitosan based hydrogel system that may affect chondrocyte proliferation resulting in the presence of a synergism seen conspicuously in consecutive controlled delivery. Methods: Four groups of cultured chondrocytes were seeded on a novel designed chitosan based hydrogel. The hydrogel was left empty (control) in one group and loaded with BMP–7, TGF-β1 and their combination in the other groups, respectively. Hydrogel structure was analyzed with scanning electron microscope. The release kinetics of Growth Factors (GFs) was determined with ELISA. Chondrocyte viability and toxicity after being tested with MTS and collagen type II synthesis, were quantified with western blotting. Canonical regression analysis was used for measuring statistical evaluation. Results: Chitosan based hydrogel allowed controlled release of GFs in different time intervals for BMP–7 and TGF-β1. Double peak concentration gradient was found to be present in the group loaded with both GFs. In this group, substantially higher chondrocyte growth and collagen synthesis were also detected. Conclusions: We concluded that, chitosan based hydrogel systems may be adjusted to release GFs consecutively during biodegradation at the layers of surface, which may increase the cell number and enhance collagen type II synthesis.
The Social Structure of Scientific Research Teams

This research developed an abstract conceptualization of the social structure of scientific research teams and empirically investigated its utility. Two typologies formed the basis of the conceptualization: A typology of teams and a typology of leadership roles. The concepts were operationalized using questions on a self-administered questionnaire and indices derived from those questions. The responses of 150 principal investigators of research teams with annual budgets of more than $100,000 were analyzed by fitting “logit” models to three-variable tables. These models, based on log-linear analysis, employed the two typologies as both independent and dependent variables. When the typologies were treated as independent variables, each of twenty-six other features of team operation was introduced as a dependent variable. The typologies successfully predicted the dependent variable in twenty of these twenty-six analyses.
NARRATIVE TO SUPPORT KNOWLEDGE FLOW IN COLLABORATIVE LEARNING

This paper investigates, by reflecting on a number of meaningful examples from the literature, how narrative can be used to help foster knowledge flow in collaborative learning situations. Narrative is a natural form of communication, easily and effectively used in every culture, by both children and adults, to communicate possibly complex information in simple and compelling way. It provides a powerful frame to represent experience and help make sense of it, as well as to support knowledge creation and sharing. The literature reports increased effectiveness of mental organization when knowledge is presented by means of stories and narrations rather than of abstract modes of thought. For these reasons, narrative is increasingly viewed as a valid learning support in formal and informal learning situations in a variety of contexts, from schools of any order to teacher preparation and up to organizational training, where it is appreciated as a powerful agent of change. In collaborative contexts, narrative appears to support the creation of shared understanding and to add concreteness to joint reflection, hence helping to elicit and explicit tacit knowledge.
Seeking educational inclusion and engagement with girls with experiences of disaffection and exclusion: the impact of voice

Interest in student voice has come to the fore in recent years, stimulated by political concern for the rights of children and young people as well as recognition of them as consumers. Moreover, children and young people are increasingly understood as people with something interesting and worthwhile to say - competent to have an opinion on their lives, learning, participation and engagement (Tangen 2008). For those young people who excluded from (mainstream) education or with a label of behavioural, emotional and social difficulties (BESD), this issue of student voice takes on particular relevance in negotiating access to learning. However, the voice of girls labelled with BESD, and those with experiences of disaffection with, and exclusion from, mainstream learning provision are often hidden, going unheard both in education, and educational research (Osler & Vincent 2003). In this paper, we address the issue of giving voice to girls excluded from mainstream education attending special, girl-only provision. We report on our exploration of finding ways, using digital technologies, to listen as part of formal gathering of the views of stakeholders in the school and in ongoing, informal ways of engaging the girls in curriculum and school development. We particularly attend to how the girls perceive their educational inclusion and exclusion and what they feel works for them. We reflect on the affordances of visual and digital methods and on the core messages of belonging and not belonging through concerns of identity, identification and the relational self enabled via attachments and demonstrated through interaction that we heard in the girls’ accounts.
Phenotypic factors correlated with the absence of virulence among gentamicin-resistant Pseudomonas aeruginosa strains

Previous reports have suggested that clinical strains of gentamicin-resistant Pseudomonas aeruginosa (GRPA) generally produce only superficial infections (wounds, urinary tract infections) in contrast to their more invasive gentamicin-susceptible counterparts (GSPA). In view of this finding, a comparative study of a number of phenotypic properties of 20 GRPA and GSPA strains (10 isolates) was assessed to determine how closely related these two populations are and how their phenotypic properties might reflect virulence. GRPA isolates were found to be more adherent to buccal cells than their susceptible counterparts (P = 0.0001). Motility, however, was generally restricted in the GRPA population when compared with GSPA isolates (P = 0.02), although on the basis of zone diameters, some strains overlapped into the other group. Enzymatically, GSPA isolates produced significantly more lipase activity against C-14 lipids than GRPA strains (P = 0.04). No differences were recorded between the two populations in dye sensitivity or in their ability to grow on minimal media at 37 and 42 degrees C. Only 35% of the GRPA isolates agglutinated in 1 of the 17 monospecific antisera reactive for P. aeruginosa. The results of this study suggest that in vivo-generated GRPA strains possess phenotypic properties intermediate between those described for in vitro-derived GRPA isolates and their progenitor GSPA strains. The increased adherence of clinical GRPA isolates to buccal cells may explain their predilection to produce wound and urinary tract infections, whereas their lack of systemic dissemination may be partially due to decreased motility and to reduced lipase production.