Miracle-dz/UniFAR-FTUs huggingface dataset:
Muscles in “Concert”: Study of Primary Motor Cortex Upper Limb Functional Topography

Background Previous studies with Transcranial Magnetic Stimulation (TMS) have focused on the cortical representation of limited group of muscles. No attempts have been carried out so far to get simultaneous recordings from hand, forearm and arm with TMS in order to disentangle a ‘functional’ map providing information on the rules orchestrating muscle coupling and overlap. The aim of the present study is to disentangle functional associations between 12 upper limb muscles using two measures: cortical overlapping and cortical covariation of each pair of muscles. Interhemispheric differences and the influence of posture were evaluated as well. Methodology/Principal Findings TMS mapping studies of 12 muscles belonging to hand, forearm and arm were performed. Findings demonstrate significant differences between the 66 pairs of muscles in terms of cortical overlapping: extremely high for hand-forearm muscles and very low for arm vs hand/forearm muscles. When right and left hemispheres were compared, overlapping between all possible pairs of muscles in the left hemisphere (62.5%) was significantly higher than in the right one (53.5% ). The arm/hand posture influenced both measures of cortical association, the effect of Position being significant [p = . 021] on overlapping, resulting in 59.5% with prone vs 53.2% with supine hand, but only for pairs of muscles belonging to hand and forearm, while no changes occurred in the overlapping of proximal muscles with those of more distal districts. Conclusions/Significance Larger overlapping in the left hemisphere could be related to its lifetime higher training of all twelve muscles studied with respect to the right hemisphere, resulting in larger intra-cortical connectivity within primary motor cortex. Altogether, findings with prone hand might be ascribed to mechanisms facilitating coupling of muscles for object grasping and lifting -with more proximal involvement for joint stabilization- compared to supine hand facilitating actions like catching. TMS multiple-muscle mapping studies permit a better understanding of motor control and ‘plastic’ reorganization of motor system.
Fast development of dense linear algebra codes on graphics processors

We present an application programming interface (API) for the C programming language that facilitates the development of dense linear algebra algorithms on graphics processors applying the FLAME methodology. The interface, built on top of the NVIDIA CUBLAS library, implements all the computational functionality of the FLAME/C interface. In addition, the API includes data transference routines to explicitly handle communication between the CPU and GPU memory spaces. The flexibility and simplicity-of-use of this tool are illustrated using a complex operation of dense linear algebra: the Cholesky factorization. For this operation, we implement and evaluate all existing variants on an NVIDIA G80 processor, attaining speedups 7× compared with the CPU implementations.
Using Performance, Energy Consumption, and Resilience Experimental Measures to Evaluate Routing Protocols for Ad Hoc Networks

Ad hoc networks are gaining momentum in contexts of use where the rapid deployment of dynamic networks is critical. It is well-known that these networks are threatened by a variety of accidental and malicious faults. Despite this fact, there exist few critical studies quantifying and analysing the impact of faults on networks' performance, resilience and energy consumption. This practical experience report studies the effect of eleven different types of perturbations (including malicious and accidental faults) on different versions of a well-known ad hoc routing protocol implementation, named olsrd. Experimentation also includes the assessment of the effectiveness of fault prevention (encryption) and detection (watchdog) mechanisms available for the considered protocols versions. During the analysis, emphasis is placed on the influence that context of use has on the interpretation of results. In that sense, reported experimentation is particularised to the domain of wireless mesh networks and mobile ad hoc networks.
Operational lessons drawn from pilot implementation of Xpert MTB/Rif in Brazil.

PROBLEM The World Health Organization has endorsed the Xpert MTB/RIF (Xpert), an automated polymerase-chain-reaction-based assay, for the rapid diagnosis of tuberculosis. However, large-scale use of a new technology calls for preparation and adaptation. APPROACH A pilot implementation study was conducted in two Brazilian cities to explore the replacement of sputum smear microscopy with Xpert. The laboratories included covered 70% of the tuberculosis cases diagnosed, had no overlap in population catchment areas, handled different workloads and were randomly shifted to Xpert. Sputum samples were collected through the same routine procedures. Before the study the medical information system was prepared for the recording of Xpert results. Laboratory technicians were trained to operate Xpert machines and health workers were taught how to interpret the results. LOCAL SETTING The average annual tuberculosis incidence in Brazil is around 90 cases per 100,000 population. However, co-infection with the human immunodeficiency virus and multidrug resistance are relatively infrequent (10% and < 2%, respectively). RELEVANT CHANGES Of the tested sputum samples, 7.3% were too scanty for Xpert and had to be examined microscopically. Ten per cent of Xpert equipment needed replacement, but spare parts were not readily available in the country. Absence of patient identification numbers led to the introduction of errors in the medical information system. LESSONS LEARNT For nationwide scale-up, a local service provider is needed to maintain the Xpert system. Ensuring cartridge availability is also essential. The capacity to perform smear microscopy should be retained. The medical information system needs updating to allow efficient use of Xpert.
Cost-benefit analysis of Cloud Computing versus desktop grids

Cloud Computing has taken commercial computing by storm. However, adoption of cloud computing platforms and services by the scientific community is in its infancy as the performance and monetary cost-benefits for scientific applications are not perfectly clear. This is especially true for desktop grids (aka volunteer computing) applications. We compare and contrast the performance and monetary cost-benefits of clouds for desktop grid applications, ranging in computational size and storage. We address the following questions: (i) What are the performance tradeoffs in using one platform over the other? (ii) What are the specific resource requirements and monetary costs of creating and deploying applications on each platform? (iii) In light of those monetary and performance cost-benefits, how do these platforms compare? (iv) Can cloud computing platforms be used in combination with desktop grids to improve cost-effectiveness even further? We examine those questions using performance measurements and monetary expenses of real desktop grids and the Amazon elastic compute cloud.
Finding shareable informative patterns and optimal coding matrix for multiclass boosting

A multiclass classification problem can be reduced to a collection of binary problems using an error-correcting coding matrix that specifies the binary partitions of the classes. The final classifier is an ensemble of base classifiers learned on binary problems and its performance is affected by two major factors: the qualities of the base classifiers and the coding matrix. Previous studies either focus on one of these factors or consider two factors separately. In this paper, we propose a new multiclass boosting algorithm called AdaBoost.SIP that considers both two factors simultaneously. In this algorithm, informative patterns, which are shareable by different classes rather than only discriminative on specific single class, are generated at first. Then the binary partition preferred by each pattern is found by performing stage-wise functional gradient descent on a margin-based cost function. Finally, base classifiers and coding matrix are optimized simultaneously by maximizing the negative gradient of such cost function. The proposed algorithm is applied to scene and event recognition and experimental results show its effectiveness in multiclass classification.
Characterization of a canine homolog of hepatitis C virus

An estimated 3% of the world's population is chronically infected with hepatitis C virus (HCV). Although HCV was discovered more than 20 y ago, its origin remains obscure largely because no closely related animal virus homolog has been identified; furthermore, efforts to understand HCV pathogenesis have been hampered by the absence of animal models other than chimpanzees for human disease. Here we report the identification in domestic dogs of a nonprimate hepacivirus. Comparative phylogenetic analysis of the canine hepacivirus (CHV) confirmed it to be the most genetically similar animal virus homolog of HCV. Bayesian Markov chains Monte Carlo and associated time to most recent common ancestor analyses suggest a mean recent divergence time of CHV and HCV clades within the past 500–1,000 y, well after the domestication of canines. The discovery of CHV may provide new insights into the origin and evolution of HCV and a tractable model system with which to probe the pathogenesis, prevention, and treatment of diseases caused by hepacivirus infection.
3-Ketoacyl thiolase delays aging of Caenorhabditis elegans and is required for lifespan extension mediated by sir-2.1

Studies of long-lived Caenorhabditis elegans mutants have identified several genes that function to limit lifespan, i.e., loss-of-function mutations in these genes promote longevity. By contrast, little is known about genes that normally act to delay aging and that when mutated cause premature aging (progeria). To seek such genes, we performed a genetic screen for C. elegans mutants that age prematurely. We found that loss-of-function mutations of the ketoacyl thiolase gene kat-1 result in an increased accumulation of the lipofuscin-like fluorescent aging pigment, shortened lifespan, early behavioral decline, and other abnormalities characteristic of premature aging. These findings suggest that kat-1 acts to delay C. elegans aging. kat-1 encodes a conserved metabolic enzyme that catalyzes the last step of fatty acid oxidation and was previously shown to regulate fat accumulation in worms. We observed that kat-1 is required for the extension of lifespan and enhanced thermotolerance mediated by extra copies of the deacetylase gene sir-2.1. kat-1 acts independently of other known pathways that affect longevity. Our findings suggest that defects in fatty acid oxidation can limit lifespan and accelerate aging in C. elegans and that kat-1-mediated fatty acid oxidation is crucial for overexpressed sir-2.1 to delay aging.
Performance of Multiclass Markovian Queueing Networks Via Piecewise Linear Lyapunov Functions

queueing networks under a stable policy. We propose a general methodology based on Lyapunov functions for the performance analysis of infinite state Markov chains and apply it specifically to Markovian multiclass queueing networks. We establish a deeper connection between stability and performance of such networks by showing that if there exist linear and piecewise linear Lyapunov functions that show stability, then these Lyapunov functions can be used to establish geometric-type lower and upper bounds on the tail probabilities, and thus bounds on the expectation of the queue lengths. As an example of our results, for a reentrant line queueing network with two processing stations operating under a work-conserving policy, we
Detecting Clusters of Fake Accounts in Online Social Networks

Fake accounts are a preferred means for malicious users of online social networks to send spam, commit fraud, or otherwise abuse the system. A single malicious actor may create dozens to thousands of fake accounts in order to scale their operation to reach the maximum number of legitimate members. Detecting and taking action on these accounts as quickly as possible is imperative in order to protect legitimate members and maintain the trustworthiness of the network. However, any individual fake account may appear to be legitimate on first inspection, for example by having a real-sounding name or a believable profile. In this work we describe a scalable approach to finding groups of fake accounts registered by the same actor. The main technique is a supervised machine learning pipeline for classifying {\em an entire cluster} of accounts as malicious or legitimate. The key features used in the model are statistics on fields of user-generated text such as name, email address, company or university; these include both frequencies of patterns {\em within} the cluster (e.g., do all of the emails share a common letter/digit pattern) and comparison of text frequencies across the entire user base (e.g., are all of the names rare? ). We apply our framework to analyze account data on LinkedIn grouped by registration IP address and registration date. Our model achieved AUC 0.98 on a held-out test set and AUC 0.95 on out-of-sample testing data. The model has been productionalized and has identified more than 250,000 fake accounts since deployment.
International Consensus Recommendations on the Management of Patients With Nonvariceal Upper Gastrointestinal Bleeding

DESCRIPTION A multidisciplinary group of 34 experts from 15 countries developed this update and expansion of the recommendations on the management of acute nonvariceal upper gastrointestinal bleeding (UGIB) from 2003. METHODS The Appraisal of Guidelines for Research and Evaluation (AGREE) process and independent ethics protocols were used. Sources of data included original and published systematic reviews; randomized, controlled trials; and abstracts up to October 2008. Quality of evidence and strength of recommendations have been rated by using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria. RECOMMENDATIONS Recommendations emphasize early risk stratification, by using validated prognostic scales, and early endoscopy (within 24 hours). Endoscopic hemostasis remains indicated for high-risk lesions, whereas data support attempts to dislodge clots with hemostatic, pharmacologic, or combination treatment of the underlying stigmata. Clips or thermocoagulation, alone or with epinephrine injection, are effective methods; epinephrine injection alone is not recommended. Second-look endoscopy may be useful in selected high-risk patients but is not routinely recommended. Preendoscopy proton-pump inhibitor (PPI) therapy may downstage the lesion; intravenous high-dose PPI therapy after successful endoscopic hemostasis decreases both rebleeding and mortality in patients with high-risk stigmata. Although selected patients can be discharged promptly after endoscopy, high-risk patients should be hospitalized for at least 72 hours after endoscopic hemostasis. For patients with UGIB who require a nonsteroidal anti-inflammatory drug, a PPI with a cyclooxygenase-2 inhibitor is preferred to reduce rebleeding. Patients with UGIB who require secondary cardiovascular prophylaxis should start receiving acetylsalicylic acid (ASA) again as soon as cardiovascular risks outweigh gastrointestinal risks (usually within 7 days); ASA plus PPI therapy is preferred over clopidogrel alone to reduce rebleeding.
Kriging Metamodeling in Simulation: A Review

This article reviews Kriging (also called spatial correlation modeling). It presents the basic Kriging assumptions and formulas contrasting Kriging and classic linear regression metamodels. Furthermore, it extends Kriging to random simulation, and discusses bootstrapping to estimate the variance of the Kriging predictor. Besides classic one-shot statistical designs such as Latin Hypercube Sampling, it reviews sequentialized and customized designs. It ends with topics for future research.
Multiplicative weights, equalizers, and P=PPAD

We show that, by using multiplicative weights in a game-theoretic thought experiment (and an important convexity result on the composition of multiplicative weights with the relative entropy function), a symmetric bimatrix game (that is, a bimatrix matrix wherein the payoff matrix of each player is the transpose of the payoff matrix of the other) either has an interior symmetric equilibrium or there is a pure strategy that is weakly dominated by some mixed strategy. Weakly dominated pure strategies can be detected and eliminated in polynomial time by solving a linear program. Furthermore, interior symmetric equilibria are a special case of a more general notion, namely, that of an "equalizer," which can also be computed efficiently in polynomial time by solving a linear program. An elegant "symmetrization method" of bimatrix games [Jurg et al., 1992] and the well-known PPAD-completeness results on equilibrium computation in bimatrix games [Daskalakis et al., 2009, Chen et al., 2009] imply then the compelling P = PPAD.
A Novel Method for Network Anomaly Detection Using Superstatistics

To detect the anomalous events in the time series we propose a new idea that we can view the time series of traffic flows as a nonstationary Poisson process associated with superstatistics theory. According to the superstatistics theory, the complex dynamic system may have a large fluctuationary of intensive quantities on large time scales which causes the system to behave as nonstationarity and nonlinearity which are also the characteristics of network traffic flows. This new idea provides us a novel way to partition the nonstationary traffic time series into small stationary segments which can be modeled by Poisson distribution in sub-second time scales. Different segments follow Poisson distribution with different distribution parameters which are named slow changing parameter compared to the fast changing traffic flows and the series of distribution parameter follows certain distribution too. We use this slow changing parameter of the segments as the key determinant factor of system to describe the network characteristic. To distinguish between the normal traffic and anomalous traffic we calculate hurst parameter of slow changing parameter. By analysing the hurst parameter series we successfully detect some of the anomalous events.
An infrared study of pure and ion irradiated frozen formamide

Context. The chemical evolution of formamide (HCONH 2 ), a molecule of astrobiological interest that has been tentatively identified in interstellar ices and in cometary coma, has been studied in laboratory under simulated astrophysical conditions such as ion irradiation at low temperature. Aims. To evaluate the abundances of formamide observed in space or in laboratory, the integrated absorbances for all the principal IR features of frozen amorphous pure formamide deposited at 20 K were measured. Further evidence that energetic processing of ices occurring in space is extremely relevant both to astrochemistry and to astrobiology has been found, showing that new molecular species are synthesized by ion irradiation at a low temperature. Methods. Pure formamide were deposited at 20 K and IR transmission spectra measured for different ice thicknesses. The ice thickness was derived by looking at the interference pattern (intensity versus time) of a He-Ne laser beam reflected at an angle of 45 deg by the vacuum-film and film-substrate interfaces. Samples of formamide ice were irradiated with 200 keV H + ions and IR spectra recorded at different ion fluences. Results. New molecules were synthesized among which are CO, CO 2 , N 2 O, isocyanic acid (HNCO), and ammonium cyanate (NH 4 + OCN - ). Some of these species remain stable after warming up to room temperature.
A Non-Invasive Droplet Digital PCR (ddPCR) Assay to Detect Paternal CFTR Mutations in the Cell-Free Fetal DNA (cffDNA) of Three Pregnancies at Risk of Cystic Fibrosis via Compound Heterozygosity

Introduction Non-invasive prenatal diagnosis (NIPD) makes use of cell-free fetal DNA (cffDNA) in the mother’s bloodstream as an alternative to invasive sampling methods such as amniocentesis or CVS, which carry a 0.5–1% risk of fetal loss. We describe a droplet digital PCR (ddPCR) assay designed to inform the testing options for couples whose offspring are at risk of suffering from cystic fibrosis via compound heterozygosity. By detecting the presence or absence of the paternal mutation in the cffDNA, it is possible to predict whether the fetus will be an unaffected carrier (absence) or whether further invasive testing is indicated (presence). Methods We selected a family in which the parents were known to carry different mutated CFTR alleles as our test system. NIPD was performed for three of their pregnancies during the first trimester (at around 11–12 weeks of gestation). Taqman probes were designed against an amplicon in exon 11 of the CFTR gene, to quantify the proportion of mutant (ΔF508-MUT; FAM) and normal (ΔF508-NOR; VIC) alleles at position c. 1521_1523 of the CFTR gene. Discussion The assay correctly and unambiguously recognized the ΔF508-MUT CFTR allele in the cffDNA of all three proband fetuses and none of the six unaffected control fetuses. In conclusion, the Bio-Rad QX100 was found to be a cost-effective and technically undemanding platform for designing bespoke NIPD assays.
Study Protocol on Hormonal Mediation of Exercise on Cognition, Stress and Immunity (PRO-HMECSI): Effects of Different Exercise Programmes in Institutionalized Elders

Physical activity (PA) in elders has been shown to have positive effects on a plethora of chronic diseases and to improve immunity, mental health, and cognition. Chronic stress has also been shown to have immuno-suppressive effects and to accelerate immunosenescence. Exercise could be a significant factor in ameliorating the deleterious effects of chronic stress, but variables such as the type, intensity, and frequency of exercise that should be performed in order to effectively reduce the stress burden need to be defined clearly. PRO-HMECSI will allow us to investigate which hormonal and immunological parameters are able to mediate the effects of exercise on mucosal immunity, psychological/biological stress, and cognitive functioning in older people. Phase I consists of an observational cross-sectional study that compares elders groups (n = 223, >65 years) by functional fitness levels aiming to identify biomarkers involved in maintaining immune and mental health. Neuroendocrine and immune biomarkers of stress, psychological well-being related to mental health, neurocognitive function, functional fitness, and daily PA will be evaluated. Phase II consists of a 28-week intervention in elders with mild cognitive impairment (MCI) profile (n = 149, >65 years, divided in three groups of exercise and one control group), aiming to investigate whether the positive effect of three different types of chair-based exercise programs on physical and psychological health is mediated by an optimal endocrine environment. Primary outcomes are measures of cognitive function and global health. Secondary outcomes include the evaluation the other dimensions such as immune function, psychological health, and depression. Few studies addressed the effects of different types of exercise interventions in older population samples with MCI. We will also be able to determine which type of exercise is more effective in the immune and hormonal function of this population.