Miracle-dz/UniFAR-FTUs huggingface dataset:
Bio-inspired robot to study stringed instruments : application to the harp

This paper is a review of a previous musician/harp interaction study leading to the specifications of a configurable excitatory mechanism. Such robotic tools can be valuable to investigate the musician/instrument interaction and th e mechanical behavior of an instrument in a repeatable and realistic musical context. To design a robotised excitator y mechanism for the concert harp, the mechanical descriptors’ typical orders of magnitude defining a musical performance have to be highlighted. For this purpose, two experimental setups have been designed. The first one focuses on the sound-producing gesture (i.e. on the plucking action). A high-speed camera has been used to accurately measure the finger and string motions in a realistic musical context. The second measurement set-up consists in capturing the whole harpist’s body motion through infra-red cameras during a performance. The set of mechanical parameters extracted from these measurements is of great interest to get an insight on an ideal robotic tool to pluck harp strings. Based on these considerations, a highly-configurable and repeatable robotic finger has been designed.
LASTor: A Low-Latency AS-Aware Tor Client

Though the widely used Tor anonymity network is designed to enable low-latency anonymous communication, interactive communications on Tor incur latencies over 5 × greater than on the direct Internet path, and in many cases, autonomous systems (ASs) can compromise anonymity via correlations of network traffic. In this paper, we develop LASTor, a new Tor client that addresses these shortcomings in Tor with only client-side modifications. First, LASTor improves communication latencies by accounting for the inferred locations of Tor relays while choosing paths. Since the preference for shorter paths reduces the entropy of path selection, we design LASTor so that a user can choose an appropriate tradeoff between latency and anonymity. Second, we develop an efficient and accurate algorithm to identify paths on which an AS can compromise anonymity by traffic correlation. LASTor avoids such paths to improve a user's anonymity, and the low runtime of the algorithm ensures that the impact on end-to-end communication latencies is low. Our results show that, in comparison to the default Tor client, LASTor reduces median latencies by 25% while also reducing the false negative rate of not detecting a potential snooping AS from 57% to 11%.
Lipid Accumulation Product Is Associated with Insulin Resistance, Lipid Peroxidation, and Systemic Inflammation in Type 2 Diabetic Patients

Background Lipid accumulation product (LAP) is a novel biomarker of central lipid accumulation related to risk of diabetes and cardiovascular disease. In this study, we assessed the association of LAP with glucose homeostasis, lipid and lipid peroxidation, and subclinical systemic inflammation in diabetic patients. Methods Thirty-nine male and 47 female type 2 diabetic patients were assessed for anthropometrics and biochemical measurements. LAP was calculated as [waist circumference (cm)-65]×[triglycerides (mmol/L)] in men, and [waist circumference (cm)-58]×[triglycerides (mmol/L)] in women. Associations of LAP with fasting glucose, insulin, insulin resistance index, lipid and lipoprotein levels, malondialdehyde, and high-sensitive C-reactive protein (hs-CRP) were assessed. Results Mean age and LAP index were 53.6±9.6 and 51.9±31.2 years, respectively. After adjustments for age, sex and body mass index status, a significant positive correlation was observed between LAP index and fasting glucose (r=0.39, P<0.001), and homeostasis model assessment of insulin resistance (r=0.31, P<0.05). After additional adjustment for fasting glucose levels, antidiabetic and antilipidemic drugs, the LAP index was also correlated to total cholesterol (r=0.45, P<0.001), high density lipoprotein cholesterol (HDL-C) levels (r=-0.29, P<0.05), triglycerides to HDL-C ratio (r=0.89, P<0.001), malondialdehyde (r=0.65, P<0.001), and hs-CRP levels (r=0.27, P<0.05). Conclusion Higher central lipid accumulation in diabetic patients was related to higher insulin resistance, oxidative stress and systemic inflammation.
CSE-TR-GRASP — A New Search Algorithm for Satisfiability

This report introduces GRASP (Generic seaRch Algorithm for the Satisfiability Problem), an integrated algorithmic framework for SAT that unifies several previously proposed search-pruning techniques and facilitates identification of additional ones. GRASP is premised on the inevitability of conflicts during search and its most distinguishing feature is the augmentation of basic backtracking search with a powerful conflict analysis procedure. Analyzing conflicts to determine their causes enables GRASP to backtrack non-chronologically to earlier levels in the search tree, potentially pruning large portions of the search space. In addition, by “recording” the causes of conflicts, GRASP can recognize and preempt the occurrence of similar conflicts later on in the search. Finally, straightforward bookkeeping of the causality chains leading up to conflicts allows GRASP to identify assignments that are necessary for a solution to be found. Experimental results obtained from a large number of benchmarks, including many from the field of test pattern generation, indicate that application of the proposed conflict analysis techniques to SAT algorithms can be extremely effective for a large number of representative classes of SAT instances. CSE-TR-292-96: GRASP—A New Search Algorithm for Satisfiability 1
A Novel Inference of a Restricted Boltzmann Machine

A deep neural network (DNN) pre-trained via stacking restricted Boltzmann machines (RBMs) demonstrates high performance. The binary RBM is usually used to construct the DNN. However, a continuous probability of each node is used as real value state, although the state of the binary RBM's node should be represented by a random binary variable. One of main reasons of this abuse is that it works. One of others is to reduce a computational cost. In this paper, we propose a novel inference of the RBM, considering that the input of the RBM is the random binary variable. Straight forward derivation of the proposed inference is intractable. Then, we also propose the closed-form approximation of it. We convince that the proposed inference is more reasonable than a conventional algorithm of the RBM. Experimental comparisons demonstrate that the proposed inference improves the performance of the DNN.
Quantitative assessment of the effects of chitosan intervention on blood pressure control

Background Chitosan is a popular dietary fiber often used to reduce dietary fat absorption to control weight and blood lipids. However, its effects on blood pressure (BP) have not been fully elucidated. We evaluated the effects of chitosan administration on systolic blood pressure (SBP) and diastolic blood pressure (DBP) through a pooled analysis of available randomized controlled trials (RCTs). Materials and methods Electronic searches were conducted in Medline, Cochrane Library, Scopus, and EMBASE to identify relevant human placebo-control RCTs. Trials that reported BP changes from baseline to study endpoint in patients receiving treatment of chitosan were included for analysis. Weighted mean difference (WMD) and 95% CIs were pooled using fixed-effects or random-effects models. Statistical heterogeneity, prespecified subgroup, publication bias, sensitivity analysis, and meta-regression assessments were also tested. Results Six hundred and seventeen participants from eight trials with 10 arms were included. Overall, chitosan administration did not significantly lower SBP (WMD: −1.41 mmHg, 95% CI: −3.29 to 0.47; P=0.14) and DBP (WMD: −0.61 mmHg, 95% CI: −1.75 to 0.52; P=0.29). However, our subgroup analyses indicated that chitosan consumption significantly reduced DBP in shorter-term (<12 weeks) and higher-dose (>2.4 g/day) arms. Funnel plots or Egger’s tests analysis (P=0.36 and 0.43 for SBP and DBP, respectively) demonstrated that there was no significant publication bias in this study. Conclusion This meta-analysis indicates that chitosan consumption significantly decreases DBP at higher dosage and in shorter-term interventions, while chitosan has no significant effects on SBP. However, these results should be interpreted cautiously because of the limited eligible RCTs included in this meta-analysis; further large-scale, well-designed RCTs on this topic are urgently needed.
Graph Orientations Optimizing the Number of Light or Heavy Vertices

This paper introduces four graph orientation problems named MaximizeW-Light, MinimizeW-Light, MaximizeW-Heavy, and MinimizeW-Heavy, where W can be any fixed non-negative integer. In each of these problems, the input is an undirected graph G and the objective is to assign a direction to each edge in G so that the number of vertices with outdegree at most W or at least W in the resulting directed graph is maximized or minimized. We derive a number of results on the computational complexity and polynomial-time approximability of these problems for different values of W and various special classes of graphs. In particular, we show that Maximize 0-Light and Minimize 1-Heavy are equivalent to Maximum Independent Set and Minimum Vertex Cover, respectively, so by allowing the value of W to vary, we obtain a new, natural generalization of the two latter problems.
DETERMINATION OF THE INTRINSIC PERMEABILITY OF MICROTOMOGRAPHIC IMAGES BY THE LATTICE BOLTZMANN METHOD

The pore scale low Reynolds flow, in a high resolution tomographic image of a sedimentary rock, was calculated by numerical simulation of the Navier-Stokes equations using the Lattice Boltzmann Method. These results were used to investigate the influence of sample size on the determination of the intrinsic permeability. The size of the representative elementary volume as a function of the autocorrelation length was estimated based on the permeabilities obtained from simulation on several sub-domains. The permeability results of Lattice Boltzmann simulation for the tomographic image and three dimensional reconstructed media from sections of the same sample were compared with experimental results.
Situation-Aware QoS Routing Algorithm for Vehicular Ad Hoc Networks

A wide range of services has been developed for vehicular ad hoc networks (VANETs), ranging from safety to infotainment applications. An essential requirement for such services is that they are offered with quality of service (QoS) guarantees in terms of service reliability and availability. Searching for feasible routes subject to multiple QoS constraints is, in general, an NP-hard problem. Moreover, routing reliability needs to be paid special attention as communication links frequently break in VANETs. In this paper, we propose employing the situational awareness (SA) concept and an ant colony system (ACS)-based algorithm to develop a situation-aware multiconstrained QoS (SAMQ) routing algorithm for VANETs. SAMQ aims to compute feasible routes between the communicating vehicles subject to multiple QoS constraints and pick the best computed route, if such a route exists. To mitigate the risks inherited from selecting the best computed route that may turn out to fail at any moment, SAMQ utilizes the SA levels and ACS mechanisms to prepare certain countermeasures with the aim of assuring a reliable data transmission. Simulation results demonstrate that SAMQ is capable of achieving a reliable data transmission, as compared with the existing QoS routing algorithms, even when the network topology is highly dynamic.
AGE AND VIDEO CAPTIONING

The task of associating images and videos with a natural language description has attracted a great amount of attention recently. Rapid progress has been made in terms of both developing novel algorithms and releasing new datasets. Indeed, the state-of-the-art results on some of the standard datasets have been pushed into the regime where it has become more and more difficult to make significant improvements. Instead of proposing new models, this work investigates the possibility of empirically establishing performance upper bounds on various visual captioning datasets without extra data labelling effort or human evaluation. In particular, it is assumed that visual captioning is decomposed into two steps: from visual inputs to visual concepts, and from visual concepts to natural language descriptions. One would be able to obtain an upper bound when assuming the first step is perfect and only requiring training a conditional language model for the second step. We demonstrate the construction of such bounds on MS-COCO, YouTube2Text and LSMDC (a combination of M-VAD and MPII-MD). Surprisingly, despite of the imperfect process we used for visual concept extraction in the first step and the simplicity of the language model for the second step, we show that current stateof-the-art models fall short when being compared with the learned upper bounds. Furthermore, with such a bound, we quantify several important factors concerning image and video captioning: the number of visual concepts captured by different models, the trade-off between the amount of visual elements captured and their accuracy, and the intrinsic difficulty and blessing of different datasets. 1 ar X iv :1 51 1. 04 59 0v 4 [ cs . C V ] 6 J an 2 01 6 Under review as a conference paper at ICLR 2016
Two new estimation methods for a superpositional intonation model

This work presents two new approaches for parameter estimation of the superpositional intonation model for German. These approaches introduce linguistic and paralinguistic assumptions allowing the initialization of a previous standard method. Additionally, all restrictions on the configuration of accents were eliminated. The proposed linguistic hypotheses can be based on either tonal or lexical accent, which gives rise to two different estimation methods. These two kind of hypotheses were validated by comparison of the estimation performance relative to two standard methods, one manual and one automatic. The results show that the proposed methods far exceed the performance of the automatic method and are slightly beyond the manual method of reference.
Language Model Based on Word Order Sensitive Matrix Representation in Latent Semantic Analysis for Speech Recognition

This paper investigates matrix representation in latent semantic analysis (LSA) framework for a language model. In LSA, word-document matrix is usually used to represent a corpus. However, this matrix ignores word order in the sentence. We propose several word co-occurrence matrices that keep word order to use in LSA. To support this matrix, we define a context dependent class (CDC) language model, which distinguishes classes according to their context in the sentences. Experiments on Wall Street Journal (WSJ) corpus show that the proposed method achieves better performance than the original LSA with word-document matrix.
High sensitivity liquid sensing by optimized slot photonic crystal ring resonator

In this work we present a design to enhance absorption of infrared light by a fluid analyte being in contact with a slot photonic crystal ring resonator (slot-PCRR). For this purpose, we propose a new PCRR design facilitating higher interaction between guided mode and analyte. These types of PCRRs are based on two-dimensional photonic crystals, which consist of an array of holes in a silicon slab being arranged in a hexagonal lattice. The holes will be filled with liquid analyte. A slot is embedded in this hexagonal ring cavity to create a slot-PCRR. The strong confinement of light in the low index region, occupied by the analyte, is the key advantage of the slot- PCRR. We also calculate the relative intensity change in the transmission spectrum due to the absorption in the analyte. The maximum change obtained is given by a mode which has most of the electromagnetic field energy in the region the region filled with the analyte. Furthermore, this mode is well separated from neighboring bands, which has the advantage that impinging light with specified frequency is less likely to spuriously couple to other modes with the same frequency, which would decrease the amount of energy coupled to desired mode. The slot-PCRR yields a higher relative change due to absorption compared to the PCRR without a slot. In this work, the radii of six rods at the outer PhC were tuned to enhance the quality factor of slot-PCRR. Using these optimum values of radii, the Q-factor rises up to 80000.
Four-Dimensional Greybody Factors and the Effective String.

Recently Maldacena and Strominger found that the calculation of greybody factors for {ital D}=5 black holes carrying three U(1) charges gives striking new evidence for their description as multiply wound effective strings. Here we show that a similar result holds for {ital D}=4 black holes with four U(1) charges. In this case the effective string may be thought of as the triple intersection of the 5-branes in {ital M} theory compactified on {ital T}{sup 7}. {copyright} {ital 1996 The American Physical Society. }
CONSTRUCTION AND ANIMATION OF A SYNTHETIC

Literature on human animation [1] [2] [3] [4] [5] generally emphasizes the human modeling and the animation process. In three-dimensional character animation, the complexity of motion may be arbitrarily divided into three main areas: facial animation [6] [7] [8] [9] [10] [11] [12] [13], hand animation [14] [15] [16] and body animation [17] [18] [19] [20] [21] [22] [23]. In a previous paper [24], we have shown how synthetic actors were directed in the film Rendez-vous à Montréal. In this new paper, points which are often ignored in the literature are explained in detail: for example, the planning and preparation of models for digitizing, composition, skeleton installation and the animation process itself.
Uncertainty, phase and oscillatory hippocampal recall

Many neural areas, notably, the hippocampus, show structured, dynamical, population behavior such as coordinated oscillations. It has long been observed that such oscillations provide a substrate for representing analog information in the firing phases of neurons relative to the underlying population rhythm. However, it has become increasingly clear that it is essential for neural populations to represent uncertainty about the information they capture, and the substantial recent work on neural codes for uncertainty has omitted any analysis of oscillatory systems. Here, we observe that, since neurons in an oscillatory network need not only fire once in each cycle (or even at all), uncertainty about the analog quantities each neuron represents by its firing phase might naturally be reported through the degree of concentration of the spikes that it fires. We apply this theory to memory in a model of oscillatory associative recall in hippocampal area CA3. Although it is not well treated in the literature, representing and manipulating uncertainty is fundamental to competent memory; our theory enables us to view CA3 as an effective uncertainty-aware, retrieval system.
Applying a robust heteroscedastic probabilistic neural network toanalog fault detection and classification

The problem of distinguishing and classifying the responses of analog integrated circuits containing catastrophic faults has aroused recent interest. The problem is made more difficult when parametric variations are taken into account. Hence, statistical methods and techniques such as neural networks have been employed to automate classification. The major drawback to such techniques has been the implicit assumption that the variances of the responses of faulty circuits have been the same as each other and the same as that of the fault-free circuit. This assumption can be shown to be false. Neural networks, moreover, have proved to be slow. This paper describes a new neural network structure that clusters responses assuming different means and variances. Sophisticated statistical techniques are employed to handle situations where the variance tends to zero, such as happens with a fault that causes a response to be stuck at a supply rail. Two example circuits are used to show that this technique is significantly more accurate than other classification methods. A set of responses can be classified in the order of 1 s.
The Contribution of the PCR-Enzymatic Digestion in the Positive Diagnosis of Proximal Spinal Muscular Atrophy in the Moroccan Population

The proximal spinal muscular atrophy (SMA) is a group of neuromuscular disorders characterized by progressive muscle weakness due to the degeneration and loss of anterior motor neurons of the spinal cord. Depending on the age of onset of symptoms and their evolution, four types of SMA, varying in severity, result in a mutations of the SMN gene (survival of Motor neuron). We have analyzed the DNA of 295 patients referred to our genetic counseling; since January 1996 until October 2014; for suspected SMA. The homozygous deletion of exon 7 of the SMN gene was found in 133 patients; of which, 40.6% were born to consanguineous parents. In countries like Morocco, where the frequency of heterozygotes for SMA is high, genetic testing should be offered as first-line and, after careful clinical assessment, especially in newborns and infants with congenital hypotonia unexplained and prognosis compromise. The molecular diagnosis of SMA allows a quick and certainly diagnosis, provide adequate genetic counseling for families at risk and suggest, for couples who want prenatal diagnosis. The analysis of the SMN gene is a perfect example of genetic testing with an excellent cost/benefit ratio that can be of great interest in public health, especially in low-income countries. We emphasize in this work for the benefit of the generalization of molecular diagnosis of SMA by the technique of PCR-enzymatic digestion in other centers in Morocco. Keywords—Exon7, PCR-digestion, SMA, SMN gene.
Hair keratin pattern in human hair follicles grown in vitro

Abstract: The keratin family includes epithelial (soft) keratins and hair (hard) keratins, and can be divided into acidic type I and basic to neutral type II subfamilies. Recently, nine type I and six type II hair keratin genes have been characterized through the screening of a human PAC library. The expression of these genes in the hair follicle was determined in vivo and a combined catalog of acidic and basic hair keratins was established. In this study, we investigated the expression and localization of most of the human hair keratin members of both types in human hair grown in vitro. We show that in vitro growth of hair follicles for 10 days in complete William's E culture medium did not alter the expression pattern of hair keratins. Similarly to the in vivo situation, each hair keratin was localized in precise and discrete compartments of the follicle, ranging from the matrix to the upper cortex and/or the hair cuticle. This study shows that the increase in length of in vitro grown follicles was accompanied by the proper hair shaft keratinization process. It also shows that hair follicle integrity was maintained in vitro, both in terms of gross morphology and molecular organization despite the complexity of the keratin expression pattern.
Mobile Elements: Drivers of Genome Evolution

Mobile elements within genomes have driven genome evolution in diverse ways. Particularly in plants and mammals, retrotransposons have accumulated to constitute a large fraction of the genome and have shaped both genes and the entire genome. Although the host can often control their numbers, massive expansions of retrotransposons have been tolerated during evolution. Now mobile elements are becoming useful tools for learning more about genome evolution and gene function.