Miracle-dz/UniFAR-FTUs huggingface dataset:
Weekly Time Course of Neuro-Muscular Adaptation to Intensive Strength Training

Detailed description of the time course of muscular adaptation is rarely found in literature. Thus, models of muscular adaptation are difficult to validate since no detailed data of adaptation are available. In this article, as an initial step toward a detailed description and analysis of muscular adaptation, we provide a case report of 8 weeks of intense strength training with two active, male participants. Muscular adaptations were analyzed on a morphological level with MRI scans of the right quadriceps muscle and the calculation of muscle volume, on a voluntary strength level by isometric voluntary contractions with doublet stimulation (interpolated twitch technique) and on a non-voluntary level by resting twitch torques. Further, training volume and isokinetic power were closely monitored during the training phase. Data were analyzed weekly for 1 week prior to training, pre-training, 8 weeks of training and 2 weeks of detraining (no strength training). Results show a very individual adaptation to the intense strength training protocol. While training volume and isokinetic power increased linearly during the training phase, resting twitch parameters decreased for both participants after the first week of training and stayed below baseline until de-training. Voluntary activation level showed an increase in the first 4 weeks of training, while maximum voluntary contraction showed only little increase compared to baseline. Muscle volume increased for both subjects. Especially training status seemed to influence the acute reaction to intense strength training. Fatigue had a major influence on performance and could only be overcome by one participant. The results give a first detailed insight into muscular adaptation to intense strength training on various levels, providing a basis of data for a validation of muscle fatigue and adaptation models.
Are Changes in Heart Rate Variability in Middle‐Aged and Older People Normative or Caused by Pathological Conditions? Findings From a Large Population‐Based Longitudinal Cohort Study

Background No study to date has investigated longitudinal trajectories of cardiac autonomic modulation changes with aging; therefore, we lack evidence showing whether these changes occur naturally or are secondary to disease or medication use. This study tested whether heart rate variability (HRV) trajectories from middle to older age are largely normative or caused by pathological changes with aging in a large prospective cohort. We further assessed whether HRV changes were modified by socioeconomic status, ethnicity, or habitual physical activity. Methods and Results This study involved 3176 men and 1238 women initially aged 44 to 69 years (1997–1999) from the UK Whitehall II population‐based cohort. We evaluated time‐ and frequency‐domain HRV measures of short‐term recordings at 3 time points over a 10‐year period. Random mixed models with time‐varying covariates were applied. Cross‐sectionally, HRV measures were lower for men than for women, for participants with cardiometabolic conditions, and for participants reporting use of medications other than beta blockers. Longitudinally, HRV measures decreased significantly with aging in both sexes, with faster decline in younger age groups. HRV trajectories were not explained by increased prevalence of cardiometabolic problems and/or medication use. In women, cardiometabolic problems were associated with faster decline in the standard deviation of all intervals between R waves with normal‐to‐normal conduction, in low‐frequency HRV, and in low‐frequency HRV in normalized units. Socioeconomic status, ethnicity, and habitual physical activity did not have significant effects on HRV trajectories. Conclusions Our investigation showed a general pattern and timing of changes in indices of cardiac autonomic modulation from middle to older age. These changes seem likely to reflect the normal aging process rather than being secondary to cardiometabolic problems and medication use.
Sparse Signal Recovery from Quadratic Measurements via Convex Programming

In this paper we consider a system of quadratic equations | |^2 = b_j, j = 1, . , m, where x in R^n is unknown while normal random vectors z_j in R_n and quadratic measurements b_j in R are known. The system is assumed to be underdetermined, i.e., m < n. We prove that if there exists a sparse solution x, i.e., at most k components of x are non-zero, then by solving a convex optimization program, we can solve for x up to a multiplicative constant with high probability, provided that k <= O((m/log n)^(1/2)). On the other hand, we prove that k <= O(log n (m)^(1/2)) is necessary for a class of naive convex relaxations to be exact.
RCATool - A Framework for Detecting and Diagnosing Anomalies in Cellular Networks

The DNS protocol has proved to be a valuable means for identifying and dissecting large-scale anomalies in omnipresent Over The Top (OTT) Internet services. In this paper, we present and evaluate a framework for detecting and diagnosing traffic anomalies via DNS traffic analysis. Detection of such anomalies is achieved by monitoring different DNS-related symptomatic features, flagging a warning as soon as one or more of them show a significant change. The investigation of the root causes for such deviations is done by looking at significant changes in a number of diagnostic features (i.e., device manufacturer and OS, requested host name, error codes, etc.), which convey information directly linked to the potential origins of the detected anomalies. For the purpose of detecting significant changes in the time-series of diagnostic features, we propose two different schemes: the first is based of change point detection applied to the entropy of the considered features, the second considers the full statistical distribution of the traffic features. The proposed solutions are tested and compared using both real and synthetic data from a nationwide mobile ISP, the latter generated from real traffic statistics to resemble the real mobile network traffic. To show the operational value of the proposed framework, we report the results of the diagnosis in two prototypical cases.
Sequential Learning of Reusable Parts for Object Detection

Our long-range goal is detecting instances from a large number of object classes in a computationally efficient manner. Detectors involving a hierarchy of tests based on edges have been used elsewhere and shown to be quite fast online. However, significant further gains in efficiency in representation, error rates and computation can be realized if the family of detectors is constructed from common parts. Our parts are flexible, extended edge configurations; they are learned, not pre-designed. In training, object classes are presented sequentially; the objective is then to accommodate new classes by maximally reusing parts. Ideally, the number of distinct parts in the system would grow much more slowly than linearly with the number of classes. Initial experiments on learning to detect several hundred LTEXsymbols are encouraging.
Land cover characterization and change detection for environmental monitoring of pan-Europe

Environmental studies need up-to-date and reliable information on land use and land cover. Such databases, which can be characterized by a high spatial accuracy and that can be updated easily, are currently not available for Europe as a whole. We investigated the applicability of satellite data for Pan-European Land Cover Monitoring (PELCOM). The main objective was to develop a method by which to obtain a 1 km spatial resolution pan-European land cover database that can be updated easily using National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA AVHRR) satellite data. The database will be used as input for environmental impact studies and climate research. The study takes full advantage of both multi-spectral and multi-temporal 1 km AVHRR data. The proposed methodology for land cover mapping has its limitations in monitoring changes due to the spatial resolution and the limited accuracy of AVHRR-derived land cover data. Therefore, a change detection technique based on the use of thematic fraction images highlights those areas where the proportions of the various land cover types have changed.
ANTAGONISM COMPETENCE OF Trichoderma spp. ISOLATES AGAINST Rhizoctonia solani KUHN

Antagonism test in-vitro of Trichoderma spp. against Rhizoctonia solani Kuhn had been carried out. This study was aimed to clarify the discrepancy antagonistic function inside species biodiversity. Enzyme activities of Trichoderma spp. such as cellulase, chitinase, ligninase, lipase, and protease were observed, while the IAA (indole acetic acid) hormone and phosphate (Ca-phosphate) dissolving capability examined, too. All isolates inhibited R. solani growth with restraint rate between 20.0 to 82.1%. The isolates produced cellulase activity but they did not have any ligninase at all. Forty six isolates produced lipase, 38 isolates of protease, and one isolate of chitinase. Twenty nine isolates released IAA between 0.0958 to 9.2575 ppm and one isolate dissolved phosphate minerals. Every single potential of uniqueness antagonism behavior at each isolate had a chance to future application in agriculture work, particularly to impede population of Rhizoctonia solani as soil born pathogen in the horticulture activity.
Non-negative sparse coding

Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. We briefly describe the motivation behind this type of data representation and its relation to standard sparse coding and non-negative matrix factorization. We then give a simple yet efficient multiplicative algorithm for finding the optimal values of the hidden components. In addition, we show how the basis vectors can be learned from the observed data. Simulations demonstrate the effectiveness of the proposed method.
Sparse Support Vector Infinite Push

In this paper, we address the problem of embedded feature selection for ranking on top of the list problems. We pose this problem as a regularized empirical risk minimization with p-norm push loss function (p = ∞) and sparsity inducing regularizers. We leverage the issues related to this challenging optimization problem by considering an alternating direction method of multipliers algorithm which is built upon proximal operators of the loss function and the regularizer. Our main technical contribution is thus to provide a numerical scheme for computing the infinite push loss function proximal operator. Experimental results on toy, DNA microarray and BCI problems show how our novel algorithm compares favorably to competitors for ranking on top while using fewer variables in the scoring function.
Discriminative region extraction and feature selection based on the combination of SURF and saliency

The objective of this paper is to provide a possible optimization on salient region algorithm, which is extensively used in recognizing and learning object categories. Salient region algorithm owns the superiority of intra-class tolerance, global score of features and automatically prominent scale selection under certain range. However, the major limitation behaves on performance, and that is what we attempt to improve. By reducing the number of pixels involved in saliency calculation, it can be accelerated. We use interest points detected by fast-Hessian, the detector of SURF, as the candidate feature for saliency operation, rather than the whole set in image. This implementation is thereby called Saliency based Optimization over SURF (SOSU for short). Experiment shows that bringing in of such a fast detector significantly speeds up the algorithm. Meanwhile, Robustness of intra-class diversity ensures object recognition accuracy.
Mutual information in nonlinear communication channel: Analytical results in large SNR limit

Applying quasi-classical perturbation theory in the corresponding Feynman's path-integral rep- resentation, we derive in the limit of the large signal-to-noise ratio the analytical expression for the mutual information of the nonlinear communication channel described by the nonlinear Shrodinger equation (NLSE) with the additive Gaussian noise. The NLSE is one of the fundamental models in nonlinear physics and has a broad range of applications, including fibre-optic communications � the backbone of the Internet. Our analytical result demonstrates that the corrections to the mutual information in the leading nonlinearity order are positive. This result is somewhat counterintuitive, that is, that the impact of nonlinearity may increase the Shannon capacity above the capacity of a corresponding linear channel.
Wnt5a Regulates Ventral Midbrain Morphogenesis and the Development of A9–A10 Dopaminergic Cells In Vivo

Wnt5a is a morphogen that activates the Wnt/planar cell polarity (PCP) pathway and serves multiple functions during development. PCP signaling controls the orientation of cells within an epithelial plane as well as convergent extension (CE) movements. Wnt5a was previously reported to promote differentiation of A9–10 dopaminergic (DA) precursors in vitro. However, the signaling mechanism in DA cells and the function of Wnt5a during midbrain development in vivo remains unclear. We hereby report that Wnt5a activated the GTPase Rac1 in DA cells and that Rac1 inhibitors blocked the Wnt5a-induced DA neuron differentiation of ventral midbrain (VM) precursor cultures, linking Wnt5a-induced differentiation with a known effector of Wnt/PCP signaling. In vivo, Wnt5a was expressed throughout the VM at embryonic day (E)9.5, and was restricted to the VM floor and basal plate by E11.5–E13.5. Analysis of Wnt5a−/− mice revealed a transient increase in progenitor proliferation at E11.5, and a precociously induced NR4A2+ (Nurr1) precursor pool at E12.5. The excess NR4A2+ precursors remained undifferentiated until E14.5, when a transient 25% increase in DA neurons was detected. Wnt5a−/− mice also displayed a defect in (mid)brain morphogenesis, including an impairment in midbrain elongation and a rounded ventricular cavity. Interestingly, these alterations affected mostly cells in the DA lineage. The ventral Sonic hedgehog-expressing domain was broadened and flattened, a typical CE phenotype, and the domains occupied by Ngn2+ DA progenitors, NR4A2+ DA precursors and TH+ DA neurons were rostrocaudally reduced and laterally expanded. In summary, we hereby describe a Wnt5a regulation of Wnt/PCP signaling in the DA lineage and provide evidence for multiple functions of Wnt5a in the VM in vivo, including the regulation of VM morphogenesis, DA progenitor cell division, and differentiation of NR4A2+ DA precursors.
Text Representations for Text Categorization: A Case Study in Biomedical Domain

In vector space model (VSM), textual documents are represented as vectors in the term space. Therefore, there are two issues in this representation, i.e. (1) what should a term be and (2) how to weight a term. This paper examined ways to represent text from the above two aspects to improve the performance of text categorization. Different representations have been evaluated using SVM on three biomedical corpora. The controlled experiments showed that the straightforward usage of named entities as terms in VSM does not show performance improvements over the bag-of-words representation. On the other hand, the term weighting method slightly improved the performance. However, to further improve the performance of text categorization, more advanced techniques and more effective usages of natural language processing for text representations appear needed.
Old French Dependency Parsing: Results of Two Parsers Analysed from a Linguistic Point of View

The treatment of medieval texts is a particular challenge for parsers. I compare how two dependency parsers, one graph-based, the other transition-based, perform on Old French, facing some typical problems of medieval texts: graphical variation, relatively free word order, and syntactic variation of several parameters over a diachronic period of about 300 years. Both parsers were trained and evaluated on the “Syntactic Reference Corpus of Medieval French” (SRCMF), a manually annotated dependency treebank. I discuss the relation between types of parsers and types of language, as well as the differences of the analyses from a linguistic point of view.
Dystrophin-Glycoprotein Complex Is Monomeric and Stabilizes Actin Filaments in Vitro through a Lateral Association*

The native molecular weight of the dystrophin-glycoprotein complex and its effect on actin depolymerization and polymerization were examined. First, we determined that the native molecular weight of purified dystrophin-glycoprotein complex is only large enough (M r 1,200,000) to contain one copy of each protein in the complex, including dystrophin. Using different approaches, we also demonstrated that dystrophin-glycoprotein complex significantly protected a fraction of actin filaments from disassembly, while individual recombinant actin binding fragments of dystrophin or calpain-digested dystrophin-glycoprotein complex had no effect on F-actin depolymerization. The protective effect of dystrophin-glycoprotein complex on F-actin depolymerization saturated at a dystrophin:actin molar ratio of 0.04, corresponding to 1 dystrophin/25 actin monomers, which is highly consistent with the 1:24 stoichiometry of dystrophin-glycoprotein complex binding to F-actin previously measured at equilibrium. However, dystrophin-glycoprotein complex did not bind G-actin or alter the kinetics or extent of actin polymerization. This excluded the possibility that dystrophin-glycoprotein complex inhibited actin depolymerization by capping the ends of actin filaments. It therefore appears that actin binding domains separated on the dystrophin molecule from each other by almost 1,200 amino acids act in concert to protect F-actin from depolymerization. Our data suggest that dystrophin stabilizes F-actin in vitro by binding alongside an actin filament and bridging actin monomers in a manner analogous to the actin side binding protein tropomyosin. It is noteworthy that we did not find any effect of skeletal muscle tropomyosin on dystrophin-glycoprotein complex binding to F-actin. This indicates that dystrophin-glycoprotein complex and tropomyosin may simultaneously bind the same actin filament and identifies another feature that distinguishes dystrophin from the other proteins in the actin-cross-linking superfamily.
Low cellular IRS 1 gene and protein expression predict insulin resistance and NIDDM

We examined the gene and protein expression of IRS 1 (insulin receptor substrate 1) in adipocytes from two groups of healthy individuals with an increased propensity for non‐insulin‐dependent diabetes mellitus (NIDDM): those with two first‐degree relatives with diabetes and another group with massive obesity. A low expression of IRS 1(<50% of the matched control group) was seen in «30% of both groups and these individuals were characterized by insulin resistance and its hallmarks: higher levels of insulin, glucose, and triglycerides. Two individuals with previously unknown NIDDM were diagnosed and both had low IRS 1 expression. Low IRS 1 protein expression was associated with low mRNA levels but not with the common Gly972Arg polymorphism of the IRS 1 gene. Taken together, our present and previous findings show that a low expression of IRS 1 in fat cells predicts insulin resistance and NIDDM. Furthermore, they support the likelihood that an impaired transcriptional activation may play a key role in the pathogenesis of NIDDM. —Carvalho, E. , Jansson, P.‐A. , Axelsen, M. , Eriksson, J. W. , Huang, X. , Groop, L. , Rondinone, C. , Sjostrom, L. , Smith, U. Low cellular IRS 1 gene and protein expression predict insulin resistance and NIDDM. FASEB J. 13, 2173–2178 (1999)
Temperature dependent protein unfolding

Protein structure prediction is a central problem in current biophysics. Understanding the energy landscape roughness would shed light on the physics behind protein folding. The theory for extracting energy landscape roughness from temperature dependent unfolding measurements is reviewed. Improvements facilitating temperature dependent single molecule protein unfolding experiments are described. We discuss the automation of AFM stepper motor control, and present an experiment server and an automatic force curve sorting algorithm.
Is it all about the money? A qualitative exploration of the effects of performance-based financial incentives on Zimbabwe's voluntary male medical circumcision program

Background In 2013, Zimbabwe’s voluntary medical male circumcision (VMMC) program adopted performance-based financing (PBF) to speed progress towards ambitious VMMC targets. The $25 USD PBF intended to encourage low-paid healthcare workers to remain in the public sector and to strengthen the public healthcare system. The majority of the incentive supports healthcare workers (HCWs) who perform VMMC alongside other routine services; a small portion supports province, district, and facility levels. Methods This qualitative study assessed the effect of the PBF on HCW motivation, satisfaction, and professional relationships. The study objectives were to: 1) Gain understanding of the advantages and disadvantages of PBF at the HCW level; 2) Gain understanding of the advantages and disadvantages of PBF at the site level; and 3) Inform scale up, modification, or discontinuation of PBF for the national VMMC program. Sixteen focus groups were conducted: eight with HCWs who received PBF for VMMC and eight with HCWs in the same clinics who did not work in VMMC and, therefore, did not receive PBF. Fourteen key informant interviews ascertained administrator opinion. Results Findings suggest that PBF appreciably increased motivation among VMMC teams and helped improve facilities where VMMC services are provided. However, PBF appears to contribute to antagonism at the workplace, creating divisiveness that may reach beyond VMMC. PBF may also cause distortion in the healthcare system: HCWs prioritized incentivized VMMC services over other routine duties. To reduce workplace tension and improve the VMMC program, participants suggested increasing HCW training in VMMC to expand PBF beneficiaries and strengthening integration of VMMC services into routine care. Conclusion In the low-resource, short-staffed context of Zimbabwe, PBF enabled rapid VMMC scale up and achievement of ambitious targets; however, side effects make PBF less advantageous and sustainable than envisioned. Careful consideration is warranted in choosing whether, and how, to implement PBF to prioritize a public health program.
Ectoparasitic Assemblages on Mormoopid Bats (Chiroptera: Mormoopidae) from Puerto Rico

Abstract We performed the first quantitative survey of ectoparasitic assemblages on three species of mormoopid bats living on the Caribbean island of Puerto Rico: Mormoops blainvillii Leach (n = 40), Pteronotus quadridens Gundlach (n = 40), and Pteronotus parnellii Gray (n = 9). We examined bats for parasites primarily on 8–10 May and 24–27 July 2002 at Culebrones Cave, near Arecibo, Puerto Rico. Only 50% of M. blainvillii were infested with at least one parasite, compared with 85–100% for Pteronotus; infested individuals of both species of Pteronotus also harbored a greater number of parasites than did M. blainvillii. The assemblage on M. blainvillii was less diverse than in the other species and more dominated by a single group of parasites, the chiggers. Chirodiscid ear mites and spinturnicid wing mites were common on both species of Pteronotus but absent from M. blainvillii. All P. parnellii harbored streblid flies, but none typically was found on P. quadridens or M. blainvillii. Adult female M. blainvillii and P. quadridens sheltered a greater number of ectoparasites than did males. All host–parasite combinations represented new associations for Puerto Rico.