Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Different Exercise Training Programs on Cardiorespiratory Fitness in Overweight/Obese Adults With Hypertension: A Pilot Study

The goal of the study was to compare the effects of two supervised aerobic exercise programs (moderate-intensity continuous training [MICT] vs. high-intensity interval training [HIIT]) after 8-, 12-, and 16-week intervention periods on cardiorespiratory fitness (CRF) in overweight/obese adults diagnosed with hypertension. Participants (N = 64) were divided into three intervention cohorts (control group [CG], MICT, and HIIT) and each of these, in turn, into three intervention length cohorts (8, 12, and 16 weeks). Supervised groups exercised twice a week. There were no statistical changes in postintervention periods in CG (g < 0.1). CRF as assessed by peak oxygen uptake (mL kg−1·min−1) increased (p < .001) in exercise groups (MICT, 3.8 ± 3.3, g = 0.6; HIIT, 4.2 ± 4.7, g = 0.7). The effect of exercise interventions compared with CG was substantial (p < .02, g > .8) and mostly consequence of HIIT-related effects. The improvements on CRF occurred after 12 and 16 weeks in exercise interventions, rather than in the 8-week group or CG, where Hedges’s g index indicated small effect. This study may suggest that both MICT and HIIT exert cardioprotector effects on hypertension in the overweight/obese population. However, short-term training duration (<12 weeks) does not seem to improve CRF, and HIIT intervention might generate higher aerobic capacity, which seems to grow as intervention lengthens.
Anisoplanatic Imaging Through Turbulence Using Principal Component Analysis

The performance of optical systems is highly degraded by atmospheric turbulence when observing both vertically (e.g., astronomy, remote sensing) or horizontally (e.g. long-range surveillance). This problem can be partially alleviated using adaptive optics (AO) but only for small fields of view (FOV), described by the isoplanatic angle, for which the turbulence-induced aberrations can be considered constant. Additionally, this problem can also be tackled using post-processing techniques such as deconvolution algorithms which take into account the variability of the point spread function (PSF) in anisoplanatic conditions. Variability of the PSF across the field of view in anisoplanatic imagery can be described using principal component analysis. Then, a certain number of variable PSFs can be used to create new basis functions, called principal components (PC), which can be considered constant across the FOV and, therefore, potentially be used to perform global deconvolution. Our approach is tested on simulated, single-conjugate AO data.
Shilling attack detection for recommender systems based on credibility of group users and rating time series

Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as user ratings and reviews, are used by attackers to manipulate recommendation rankings. Shilling attack detection in recommender systems is of great significance to maintain the fairness and sustainability of recommender systems. The current studies have problems in terms of the poor universality of algorithms, difficulty in selection of user profile attributes, and lack of an optimization mechanism. In this paper, a shilling behaviour detection structure based on abnormal group user findings and rating time series analysis is proposed. This paper adds to the current understanding in the field by studying the credibility evaluation model in-depth based on the rating prediction model to derive proximity-based predictions. A method for detecting suspicious ratings based on suspicious time windows and target item analysis is proposed. Suspicious rating time segments are determined by constructing a time series, and data streams of the rating items are examined and suspicious rating segments are checked. To analyse features of shilling attacks by a group user’s credibility, an abnormal group user discovery method based on time series and time window is proposed. Standard testing datasets are used to verify the effect of the proposed method.
Mitochondrial lineage A2ah found in a pre‐Hispanic individual from the Andean region

The aim of this study was to contribute to the knowledge of pre‐Hispanic Andean mitochondrial diversity by analyzing an individual from the archaeological site Pukara de La Cueva (North‐western Argentina). The date of the discovery context (540 ± 60 BP) corresponds to the Regional Developments II period.
An evolutionarily conserved glycine-tyrosine motif forms a folding core in outer membrane proteins

An intimate interaction between a pair of amino acids, a tyrosine and glycine on neighboring β-strands, has been previously reported to be important for the structural stability of autotransporters. Here, we show that the conservation of this interacting pair extends to nearly all major families of outer membrane β-barrel proteins, which are thought to have originated through duplication events involving an ancestral ββ hairpin. We analyzed the function of this motif using the prototypical outer membrane protein OmpX. Stopped-flow fluorescence shows that two folding processes occur in the millisecond time regime, the rates of which are reduced in the tyrosine mutant. Folding assays further demonstrate a reduction in the yield of folded protein for the mutant compared to the wild-type, as well as a reduction in thermal stability. Taken together, our data support the idea of an evolutionarily conserved ‘folding core’ that affects the folding, membrane insertion, and thermal stability of outer membrane protein β-barrels.
Variance stabilization in Poisson image deblurring

We consider the restoration of blurred images corrupted by Poisson noise using variance-stabilizing transformations (VST). Although VST are an established tool used extensively for denoising, their adoption in deconvolution problems is problematic because VST are necessarily nonlinear operators, and thus break the linear image-formation model typically adopted in deconvolution. We propose a deblurring framework where the image is 1) deconvolved by a linear regularized inverse filter, 2) transformed by VST into an image which can be treated as corrupted by strong spatially correlated noise with constant variance and known power spectrum, 3) denoised by a filter for additive colored Gaussian noise, 4) returned to the original range via inverse VST. We particularly analyze the stabilization of Poisson variates after linear filtering and characterize the noise power spectrum before and after application of VST. We present an efficient implementation of this original deblurring framework using the BM3D denoising filter, demonstrating state-of-the-art results which are especially appealing in low SNR imaging conditions.
Relationships between internet addiction,coping style and life events among teenagers

Objective To explore the relationships between internet addiction and coping style and life events among teenagers.Methods Totally 560 teenagers were surveyed with a questionnaire for internet addiction,life events and coping style.Results Significant difference was found in mature coping style between the heavy internet users and the light internet users(0.97±0.33 vs 1.12±0.34,P0.001). The heavy internet users had greater scores of interpersonal relationships,study stress,be-punished,health adjustment than that of the light internet users.There was prominent positive correlation between internet addiction and immature coping style.Except for the losing dimension,there were prominent positive correlations between internet addiction and other five dimensions in life events.There were distinct correlations between internet addiction and mature coping style,immature coping style,interpersonal relationships.Conclusion Life event and coping style had important effects on internet addiction.
Multiscale scanning in inverse problems

In this paper we propose a multiscale scanning method to determine active components of a quantity $f$ w.r. t. a dictionary $\mathcal{U}$ from observations $Y$ in an inverse regression model $Y=Tf+\xi$ with linear operator $T$ and general random error $\xi$. To this end, we provide uniform confidence statements for the coefficients $\langle \varphi, f\rangle$, $\varphi \in \mathcal U$, under the assumption that $(T^*)^{-1} \left(\mathcal U\right)$ is of wavelet-type. Based on this we obtain a multiple test that allows to identify the active components of $\mathcal{U}$, i.e. $\left\langle f, \varphi\right\rangle \neq 0$, $\varphi \in \mathcal U$, at controlled, family-wise error rate. Our results rely on a Gaussian approximation of the underlying multiscale statistic with a novel scale penalty adapted to the ill-posedness of the problem. The scale penalty furthermore ensures weak convergence of the statistic's distribution towards a Gumbel limit under reasonable assumptions. The important special cases of tomography and deconvolution are discussed in detail. Further, the regression case, when $T = \text{id}$ and the dictionary consists of moving windows of various sizes (scales), is included, generalizing previous results for this setting. We show that our method obeys an oracle optimality, i.e. it attains the same asymptotic power as a single-scale testing procedure at the correct scale. Simulations support our theory and we illustrate the potential of the method as an inferential tool for imaging. As a particular application we discuss super-resolution microscopy and analyze experimental STED data to locate single DNA origami.
Development and Validation of a Skinfold Model for Estimation of Body Density for a Safe Weight Reduction in Young Iranian Wrestlers

Background: Adverse effects of excessive body mass reduction among wrestlers dictate minimum weight determination through body composition. Although skinfold equations are essential to estimate body composition in the field setting, they are mostly derived from Western societies and may lack generalizability to other populations. Purpose: Previously published skinfold equations lacked external validity in predicting body density of Iranian wrestlers. We aimed to derive a new anthropometric model specific to young Iranian male wrestlers. Study design: Cross-sectional cohort study. Level of evidence: Level 3. Methods: One hundred twenty-six Iranian male wrestlers with at least 1 year of experience and a mean age of 19 ± 4.0 years underwent underwater weight analysis for body density estimation and anthropometric measurements. The previously published equations were validated, followed by new regression modeling, using multivariable fractional polynomials, with body density as the criterion predicted by common anthropometric variables. The final model was validated throughout the modeling procedure using 1000 bootstrap replications. Results: The mean body fat percentage (%BF) was 12.6% (95% CI, 11.9%-13.4%), lower than that of previous studies. Six previously published equations each had significant deviations from the line of identity (all P < 0.001). The new prediction equation combined subscapular, tricipital, and midaxillary skinfolds and body mass index cubed to predict body density. Conclusion: The development of ethnicity-specific equations, using statistically unbiased and comprehensive validation methods, is imperative for body composition estimation to determine the minimum weight for regulation of health in athletes. Clinical Relevance: Using equations without external validation can bias the prediction of minimum weight, leading to unsafe weight reduction by athletes. Compared with a previous study, much lower mean %BF was found using an ethnicity-specific equation (12.6% vs 15.9%). This difference observed in %BF prediction could affect safe fat reduction in athletes.
A Click Sequence Model for Web Search

Getting a better understanding of user behavior is important for advancing information retrieval systems. Existing work focuses on modeling and predicting single interaction events, such as clicks. In this paper, we for the first time focus on modeling and predicting sequences of interaction events. And in particular, sequences of clicks. We formulate the problem of click sequence prediction and propose a click sequence model (CSM) that aims to predict the order in which a user will interact with search engine results. CSM is based on a neural network that follows the encoder-decoder architecture. The encoder computes contextual embeddings of the results. The decoder predicts the sequence of positions of the clicked results. It uses an attention mechanism to extract necessary information about the results at each timestep. We optimize the parameters of CSM by maximizing the likelihood of observed click sequences. We test the effectiveness of CSM on three new tasks: (i) predicting click sequences, (ii) predicting the number of clicks, and (iii) predicting whether or not a user will interact with the results in the order these results are presented on a search engine result page (SERP). Also, we show that CSM achieves state-of-the-art results on a standard click prediction task, where the goal is to predict an unordered set of results a user will click on.
Sacral epiduroscopic laser decompression for complex regional pain syndrome after lumbar spinal surgery

Rationale: CRPS after a lumbar surgery has symptoms that are similar to PSSS. However, standard criteria for distinguishing CRPS from PSSS do not exist. We present a case report of a 31-year-old female with CRPS symptoms after lumbar spinal surgery treated by performing SELD. Patient concerns: This patient was referred to our pain clinic for left ankle pain. She received a lumbar discectomy for a herniated lumbar disc (L5/S1) but the pain was aggravated after surgery. Diagnoses: The characteristics of the pain were burning, tingling, and cold, and were accompanied by other symptoms such as swelling, color change and mail dystrophy. The patient was diagnosed with CRPS. Interventions: Medications and interventional therapies were not effective in reducing pain. SELD was performed and severe adhesive inflammation was observed in the L4-S1 epidural space. We performed mechanical adhesiolysis and injected hyalurodinase and dexamethasone near the L5 and S1 root. One month after, a second SELD was performed as same manner. Outcomes: After second SELD, the patient's pain markedly decreased. On the second visit in the outpatient clinic, the patient was absent of pain without any other medications. Lessons: CRPS like symptoms can appear after lumbar spinal surgery due to adhesion and inflammation in the epidural space. In such cases, SELD can be considered as diagnostic and therapeutic option.
Streptomycin accumulation by Bacillus subtilis requires both a membrane potential and cytochrome aa3

Cytochrome aa3 concentrations in the cytoplasmic membrane of Bacillus subtilis were altered by growth conditions, and the effects on the membrane potential (delta psi) in whole cells were measured. When cytochrome aa3 was absent, the magnitude of delta psi was not diminished by comparison with the delta psi measured in cells containing normal cytochrome aa3 concentrations. In addition, the energy-dependent uptake of proline and glutamate was comparable at both cytochrome aa3 concentrations. However, in the cytochrome aa3-deficient cell preparation, accumulation of the aminoglycoside antibiotic streptomycin was much lower than that of the cytochrome aa3-sufficient cells. When cells were cultured under conditions that stimulated higher than normal concentrations of cytochrome aa3, delta psi was also increased, and enhanced streptomycin accumulation was observed. Phenazine methosulfate-ascorbate was used both in delta psi measurements and in uptake studies to provide high rates of electron transport and maximal delta psi values. These results, taken together with those previously published (A. S. McEnroe and H. W. Taber, Antimicrob. Agents Chemother. 26:507-512, 1984) suggest that the uptake of streptomycin by B. subtilis requires adequate levels both of delta psi and cytochrome aa3.
A comparative study of simple online learning strategies for streaming data

Since several years ago, the analysis of data streams has attracted considerably the attention in various research fields, such as databases systems and data mining. The continuous increase in volume of data and the high speed that they arrive to the systems challenge the computing systems to store, process and transmit. Furthermore, it has caused the development of new online learning strategies capable to predict the behavior of the streaming data. This paper compares three very simple learning methods applied to static data streams when we use the 1-Nearest Neighbor classifier, a linear discriminant, a quadratic classifier, a decision tree, and the Naive Bayes classifier. The three strategies have been taken from the literature. One of them includes a time-weighted strategy to remove obsolete objects from the reference set. The experiments were carried out on twelve real data sets. The aim of this experimental study is to establish the most suitable online learning model according to the performance of each classifier.
Hydrotherapy outcome measures for people with arthritis: A systematic review

Exercise has been shown to be effective in decreasing pain, improving function and performance of activities of daily living in people with arthritis. While hydrotherapy is often suggested as an exercise intervention, there is little evidence that it is more effective than other forms of exercise. Scoping the literature identified that a large variety of outcome measures were used. This study aimed to identify the patient reported outcome measures used for assessing the effectiveness of hydrotherapy for people with arthritis. A systematic literature review was conducted following a search of the major health databases. Upon meeting the inclusion criteria each study was quality rated using a modified scoring tool. In the 24 studies identified 35 patient reported outcome measures were used: most common were the visual analogue pain scale and the Western Ontario and McMaster Universities Osteoarthritis Index. Twenty-five patient reported outcome measures were used only once. Six of the patient reported outcome measures were arthritis-specific and eight generic measures had been validated for an arthritic population. Importantly, no patient reported outcome measure had been evaluated specifically for hydrotherapy interventions. The selection of outcome measures for hydrotherapy research appears inconsistent. This may account for the lack of high quality evidence for this intervention. Further research is warranted to develop a valid, reliable and responsive outcome measure specifically for people with arthritis undertaking hydrotherapy.
Repeated Peritoneal Catheter Blockage Caused by Neurocysticercosis Following Ventriculoperitoneal Shunt Placement for Hydrocephalus

ABSTRACT Cerebral cysticercosis is common, but the possibility for repeated occurrence of peritoneal catheter blockage caused by neurocysticercosis (NCC) after two revisions following ventriculoperitoneal shunt placement for hydrocephalus is unusual. Herein, we describe one rare case in which peritoneal catheter revision was performed two times unsuccessfully. Endoscopic cysternostomy rather than peritoneal catheter adjustment was performed successfully, and histopathological examination of excised cystic samples confirmed NCC in our hospital. The present case highlights the need for awareness of NCC as a possible etiology of hydrocephalus, especially in developing countries. Uncommon findings in both lateral ventricles following low-field magnetic resonance imaging scans as well as the rarity of this infection involved in unusual location play important roles in misdiagnosis and incorrect treatment for hydrocephalus; thus, endoscopic cysternostomy, rather than multiple shunt adjustment of the peritoneal end, is recommended in the selected patient. To the best of our knowledge, this is the first report describing the misdiagnosis and inappropriate treatment of hydrocephalus caused by cerebral cysticercosis in China.
Perturbing the acetylation status of the Type IV pilus retraction motor, PilT, reduces Neisseria gonorrhoeae viability

Post‐translational acetylation is a common protein modification in bacteria. It was recently reported that Neisseria gonorrhoeae acetylates the Type IV pilus retraction motor, PilT. Here, we show recombinant PilT can be acetylated in vitro and acetylation does not affect PilT ultrastructure. To investigate the function of PilT acetylation, we mutated an acetylated lysine, K117, to mimic its acetylated or unacetylated forms. These mutations were not tolerated by wild‐type N. gonorrhoeae, but they were tolerated by N. gonorrhoeae carrying an inducible pilE when grown without inducer. We identified additional mutations in pilT and pilU that suppress the lethality of K117 mutations. To investigate the link between PilE and PilT acetylation, we found the lack of PilE decreases PilT acetylation levels and increases the amount of PilT associated with the inner membrane. Finally, we found no difference between wild‐type and mutant cells in transformation efficiency, suggesting neither mutation inhibits Type IV pilus retraction. Mutant cells, however, form microcolonies morphologically distinct from wt cells. We conclude that interfering with the acetylation status of PilTK117 greatly reduces N. gonorrhoeae viability, and mutations in pilT, pilU and pilE can overcome this lethality. We discuss the implications of these findings in the context of Type IV pilus retraction regulation.
Activity and health status monitoring system

Physical activity monitoring represents an important tool in supporting/encouraging vulnerable persons in their struggle to recover from surgery or long term illness promoting a healthy lifestyle. The paper proposes a smart, low power activity monitoring platform capable to acquire data from 4 inertial sensor modules placed on human body, temporarily store it on a mobile phone for real time data display or on a server for long term data analysis.
A high performance QoS supportive protocol for wireless LANs

A QoS supportive adaptive polling (QAP) protocol for wireless LANs is introduced. QAP operates under an infrastructure wireless LAN, where an access point (AP) polls the wireless nodes in order to grant them permission to transmit. The polled node sends data directly to the destination node. We consider bursty traffic conditions, under which the protocol operates efficiently. The polling scheme is based on an adaptive algorithm according to which it is most likely that an active node is polled. Also, QAP takes into account packet priorities, so it supports QoS by means of the highest priority first packet buffer discipline and the priority distinctive polling scheme. Lastly, the protocol combines efficiency and fairness, since it prohibits a single node to dominate the medium permanently. QAP is compared to the efficient learning automata-based polling (LEAP) protocol, and is shown to have superior performance.