Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of contrast bathing and compression therapy on muscular performance.

UNLABELLED Contrast bathing (CB) and compression garments (CG) are widely used to promote recovery. PURPOSE To evaluate CB and CG as regeneration strategies after exercise-induced muscle damage (EIMD). METHODS Baseline values of muscle soreness, serum creatine kinase (CK) and myoglobin (Mb), joint range of motion, limb girth, 10- or 30-m sprint, countermovement jump (CMJ), and five repetition maximum squat were completed by 26 young men who then undertook a resistance exercise challenge (REC) to induce EIMD: 6 x 10 parallel squats at 100% body weight with 5-s one repetition maximum eccentric squat superimposed onto each set. After the REC, subjects were separated into three intervention groups: CB, CG, and control (CONT). Forty-eight hours after REC, the subjects exercise performance was reassessed. CK and Mb were also measured +1, +24, and +48 h post-REC. RESULTS CK was elevated at +24 h ( upward arrow140%; upward arrow161%; upward arrow270%), and Mb was elevated at +1 h ( upward arrow523%; upward arrow458%; upward arrow682%) in CB, CG, and CONT. Within-group large effect sizes for loge[CK] were found for CB at +24 h (0.80) and +48 h (0.84). Area under the [Mb] curve was lower in CB compared with CG and CONT (P < or = 0.05). At +48 h, significant differences from baseline were found in all groups for CMJ (CG, downward arrow5.1%; CB, downward arrow4.4%; CONT, downward arrow8.5%) and soreness ( upward arrow213%; upward arrow284%; upward arrow284%). Soreness transiently fell at +1 h compared with post-REC in the CB group. At +48 h, midthigh girth increased in CB ( upward arrow1.4%) and CONT ( upward arrow1.6%), whereas 30-m sprint time increased in CG ( upward arrow2%). CONCLUSION No hierarchy of recovery effects was found. Neither contrast bathing nor compression acted to promote acute recovery from EIMD any more effectively than passive conditions, although contrast bathing may transiently attenuate postexercise soreness.
A random subspace method with automatic dimensionality selection for hyperspectral image classification

In this paper, a weighted random subspace method (RSM) with automatic subspace dimensionality selection has been proposed for classifying hyperspectral image data. The dimensionality selection method is based on the importance distribution of dimensionality estimated by kernel smoothing technique during the algorithm training. Two feature weighting methods based on normalized re-substitution accuracy and Fisher's LDA separability are introduced for improving the original RSM. Experimental result shows that the proposed algorithm outperforms the original random subspace method.
Interaction between natural compounds and human topoisomerase I

Abstract Eukaryotic topoisomerase I (Top1) is a monomeric enzyme that catalyzes the relaxation of supercoiled DNA during important processes including DNA replication, transcription, recombination and chromosome condensation. Human Top1 I is of significant medical interest since it is the unique cellular target of camptothecin (CPT), a plant alkaloid that rapidly blocks both DNA and RNA synthesis. In this review, together with CPT, we point out the interaction between human Top1 and some natural compounds, such us terpenoids, flavonoids, stilbenes and fatty acids. The drugs can interact with the enzyme at different levels perturbing the binding, cleavage, rotation or religation processes. Here we focus on different assays that can be used to identify the catalytic step of the enzyme inhibited by different natural compounds.
Sensitivity Analysis Techniques for the Performance Assessment of a Radioactive Waste Repository

Sensitivity Analysis (SA) is a key element in the Performance Assessment (PA) of a Radioactive High Level Waste (HLW) Repository. It helps gaining information about the system, understanding the relation between input parameters and output variables and steering new experimental and theoretical research to increase the degree of knowledge about the system. The Integrated Project (IP) PAMINA is devoting a large effort to the research in this area and the dissemination of results among its partners. Among the activities under development are a review of SA methods, a benchmark of SA techniques and the application of different SA techniques to a PA results coming from several national programs. After the end of this activity, PAMINA partners will get a better understanding of the rationale behind every available technique and about their capabilities and shortcomings.
The Multivariate g-and-h Distribution

In this article we consider a generalization of the univariate g-and-h distribution to the multivariate situation with the aim of providing a flexible family of multivariate distributions that incorporate skewness and kurtosis. The approach is to modify the underlying random variables and their quantiles, directly giving rise to a family of distributions in which the quantiles rather than the densities are the foci of attention. Using the ideas of multivariate quantiles, we show how to fit multivariate data to our multivariate g-and-h distribution. This provides a more flexible family than the skew-normal and skew-elliptical distributions when quantiles are of principal interest. Unlike those families, the distribution of quadratic forms from the multivariate g-and-h distribution depends on the underlying skewness. We illustrate our methods on Australian athletes data, as well as on some wind speed data from the northwest Pacific.
Emotional identification during mobile RF Radiation

This paper presents emotional identification of 62 healthy subjects under Mobile Radio Frequency Radiation (MRFR). Electroencephalography (EEG) at awake and rest status with eyes closed, particularly on Alpha and Beta wave will be investigated. 31 subjects were strapped with mobile phone at the left ear, and name them as LE (Left Exposure) group, meanwhile, another 31 subjects were named as RE (Right Exposure) group with mobile phone on the right ear. Each group has 3 sessions of EEG recordings, such as Before, During and After Exposure of mobile phone, each session takes 5 minutes and 1 minute rest is applied between sessions. The study proposes index of human brain activities as an indicator of human emotion under mobile RF Radiation using EEG power spectrum, and brainwave signals were employed using nonparametric method. The results of the study established 2 types of indexes according to the trend of Frontal Hemispheric Energy Spectral Density (ESD) between 2 different sessions (from Before session to During session, and from During session to After session) which present human's brain activities.
Psychosexual Adjustment Following Pelvic Exenteration

Fifteen pelvic exenteration patients from 2 institutions participated in semistructured interviews and objective assessment to examine postoperative psychologic, social, and sexual functioning. Analyses of variance indicated significant differences between the sexually active and nonactive patients and the patients with a neovagina and those with no vaginal capacity only in the area of sexual functioning, not in psychologic or social adjustment. Descriptive statistics for the entire group of patients provide a view of psychosocial adjustment for the average pelvic exenteration patient. Long after such patients are asymptomatic and clinically free of disease, they appear mildly distressed and depressed. However, these women report active and satisfactory levels of social and free-time activities. Sexual functioning continues as the area of greatest disruption for these patients and, as a group, they resemble severely sexually dysfunctional healthy women. This investigation provides a substantive look at the post-treatment life circumstances of these patients and offers a data base for future investigations.
RACE, INTELLIGENCE AND EDUCATION

One result was noteworthy: the Negro population scored about one standard deviation-say 15 points of IQ-below the white. No one was surprised; those who believed Negroes to be basically inferior saw it as a "scientific" justification for their prejudice, and those who considered them to be socially disadvantaged accepted the difference as a measure of their deprivation. The first view is untenable for all the reasons that racialist views are untenable; the second seemed reasonable enough, for even the non-verbal tests had components of education and white culture in them. It was assumed that, as tests became less contaminated by 'extraneous factors and more valid measures of intelligence (of which more below), all results from all unselected populations would approach equivalence, and 'everyone would live happily ever after.
Neo-Antigens and Apoptotic Cells Antibodies for Atherosclerosis-Associated The Autoreactivity of Anti-Phosphorylcholine

L. Witztum and Gregg J. SilvermanPeter X. Shaw, Carl S. Goodyear, Mi-Kyung Chang, Josephhttp://www.jimmunol.org/content/170/12/6151J Immunol€2003; 170:6151-6157; ;Referenceshttp://www.jimmunol.org/content/170/12/6151.full#ref-list-1This article cites 35 articles, 23 of which you can access for free at: Subscriptionshttp://jimmunol.org/subscriptionsInformation about subscribing to The Journal of Immunology is online at: Permissionshttp://www.aai. org/ji/copyright.htmlSubmit copyright permission requests at: Email Alertshttp://jimmunol.org/cgi/alerts/etocReceive free email-alerts when new articles cite this article. Sign up at:
Functioning of patients with multifocal motor neuropathy

Patients with multifocal motor neuropathy (MMN) have slowly progressive, predominantly distal asymmetric limb weakness without sensory loss. While previous studies have investigated the impact of MMN on body functions and structures, relatively little is known about the impact of patients' weakness on daily functioning. The aim of the present cross‐sectional study, involving 47 patients with MMN, was to evaluate determinants of patients' functioning. Most patients showed not only muscle weakness but also fatigue, limited dexterity, and limited walking ability. Regression models showed that age, hand aids, and muscle strength scores together explained 54% of the variance in dexterity scores, which in turn explained 8% of the variance in patients' scores for autonomy indoors. Age, the use of walking aids, and muscle strength scores together explained 58% of the variance in walking ability scores, which in turn explained 18% of the variance in patients' scores for autonomy indoors and 7% of the variance in patients' scores for autonomy outdoors. Assessment of determinants of patient functioning may make it possible to tailor interventions to address these aspects and thereby improve patients' functioning in daily life.
Joint 4-D Angle and Doppler Shift Estimation via Tensor Decomposition for MIMO Array

A joint 4-dimensional (4-D) angle and Doppler shift estimation method is proposed for bistatic multiple-input multiple-output (MIMO) uniform rectangular array (URA). The key idea behind the proposed approach is to use tensor decomposition to estimate the target parameter matrices, and use Vandermonde structure enforcing strategy to regress the parameters. This algorithm can effectively estimate all the parameters simultaneously, and requires neither parameter pairing nor multi-dimensional nonlinear peak searching.
Generalized Character Process Models: Estimating the Genetic Basis of Traits That Cannot Be Observed and That Change with Age or Environmental Conditions

Summary. The genetic analysis of characters that change as a function of some independent and continuous variable has received increasing attention in the biological and statistical literature. Previous work in this area has focused on the analysis of normally distributed characters that are directly observed. We propose a framework for the development and specification of models for a quantitative genetic analysis of function‐valued characters that are not directly observed, such as genetic variation in age‐specific mortality rates or complex threshold characters. We employ a hybrid Markov chain Monte Carlo algorithm involving a Monte Carlo EM algorithm coupled with a Markov chain approximation to the likelihood, which is quite robust and provides accurate estimates of the parameters in our models. The methods are investigated using simulated data and are applied to a large data set measuring mortality rates in the fruit fly, Drosophila melanogaster.
Generic nano-imprint process for fabrication of nanowire arrays

A generic process has been developed to grow nearly defect-free arrays of (heterostructured) InP and GaP nanowires. Soft nano-imprint lithography has been used to pattern gold particle arrays on full 2 inch substrates. After lift-off organic residues remain on the surface, which induce the growth of additional undesired nanowires. We show that cleaning of the samples before growth with piranha solution in combination with a thermal anneal at 550 °C for InP and 700 °C for GaP results in uniform nanowire arrays with 1% variation in nanowire length, and without undesired extra nanowires. Our chemical cleaning procedure is applicable to other lithographic techniques such as e-beam lithography, and therefore represents a generic process.
DD genotype of ACE gene is a risk factor for intracerebral hemorrhage

Genetic factors may play a role in susceptibility to stroke. The angiotensin converting enzyme (ACE) gene is a candidate gene for two phenotypically different types of stroke affecting small perforating arteries: spontaneous intracerebral hemorrhage (SIH) and ischemic stroke due to small vessel disease (SVD). The authors report evidence that ACE gene DD homozygosity of the I/D polymorphism in intron 16 is an independent risk factor for SIH, and not for SVD stroke, in a Polish population.
Analysis of Simulated Heart Sounds by Intrinsic Mode Functions

The mechanisms involved in the generation of heart sounds have always been of interest, mainly for diagnosis purposes. As a result, mathematical models have been proposed for first (S1) and second (S2) heart sounds and different efforts have been made to select the best signal processing tool to analyze them. Different frequency analysis techniques have been used to relate cardiac structure to the vibration they emit. In this work, we applied the empirical mode decomposition (EMD), a recently developed technique, for time-frequency (TF) analysis of heart sounds. EMD has shown interesting properties for biomedical signals related to nonlinear and non-stationary analysis. EMD is an adaptive decomposition since the extracted information is obtained directly from the signal without the use of kernels or mother waveforms. In this paper, EMD is first investigated in simulated scenarios through mathematical models for SI and S2 to validate its performance. Later, a real heart sound acquired over the thoracic surface of a healthy subject is analyzed. The work points out the advantage of EMD for this task
Optimal energy management of hybrid power system with two different battery models

Now a days, wind and solar energy are most commonly used as renewable energy sources (RES). These sources highly depend on environment and geographical conditions of a particular location. Main drawback of RES is randomness in power production due to their inherent uncertainty nature. Hence, energy management is difficult task for these sources. Wind, photovoltaic (PV) and sodium nickel chloride (SNC) battery based hybrid power system (HPS) is used as study system in this paper. Two battery models, i.e., internal resistance (IR) and two time constant (TTC) model are modeled. System operation is carried in two stages for these two battery model separately, in first stage voltage of system is maintained at constant value using voltage source converter (VSC) after that in second stage dynamic programming (DP) is applied to system to get maximum revenue from the system.
Heterogeneous electrochemical CO2 reduction using nonmetallic carbon-based catalysts: current status and future challenges

Electrochemical CO2 reduction (ECR) offers an important pathway for renewable energy storage and fuels production. It still remains a challenge in designing highly selective, energy-efficient, robust, and cost-effective electrocatalysts to facilitate this kinetically slow process. Metal-free carbon-based materials have features of low cost, good electrical conductivity, renewability, diverse structure, and tunability in surface chemistry. In particular, surface functionalization of carbon materials, for example by doping with heteroatoms, enables access to unique active site architectures for CO2 adsorption and activation, leading to interesting catalytic performances in ECR. We aim to provide a comprehensive review of this category of metal-free catalysts for ECR, providing discussions and/or comparisons among different nonmetallic catalysts, and also possible origin of catalytic activity. Fundamentals and some future challenges are also described.
LASER-BASED SLAM WITH EFFICIENT OCCUPANCY LIKELIHOOD MAP LEARNING FOR DYNAMIC INDOOR SCENES

Abstract. Location-Based Services (LBS) have attracted growing attention in recent years, especially in indoor environments. The fundamental technique of LBS is the map building for unknown environments, this technique also named as simultaneous localization and mapping (SLAM) in robotic society. In this paper, we propose a novel approach for SLAMin dynamic indoor scenes based on a 2D laser scanner mounted on a mobile Unmanned Ground Vehicle (UGV) with the help of the grid-based occupancy likelihood map. Instead of applying scan matching in two adjacent scans, we propose to match current scan with the occupancy likelihood map learned from all previous scans in multiple scales to avoid the accumulation of matching errors. Due to that the acquisition of the points in a scan is sequential but not simultaneous, there unavoidably exists the scan distortion at different extents. To compensate the scan distortion caused by the motion of the UGV, we propose to integrate a velocity of a laser range finder (LRF) into the scan matching optimization framework. Besides, to reduce the effect of dynamic objects such as walking pedestrians often existed in indoor scenes as much as possible, we propose a new occupancy likelihood map learning strategy by increasing or decreasing the probability of each occupancy grid after each scan matching. Experimental results in several challenged indoor scenes demonstrate that our proposed approach is capable of providing high-precision SLAM results.
Exploiting Socio-Economic Models for Lodging Recommendation in the Sharing Economy

Recent years have witnessed the emergence of sharing economy marketplaces, which enable users to share goods and services in a peer-to-peer fashion. A prominent example in the travel industry is Airbnb, which connects guests with hosts, allowing both to exchange cultural experiences in addition to the economic transaction. Nonetheless, Airbnb guest profiles are typically sparse, which limits the applicability of traditional lodging recommendation approaches. Inspired by recent socio-economic analyses of repurchase intent behavior on Airbnb, we propose a context-aware learning-to-rank approach for lodging recommendation, aimed to infer the user's perception of several dimensions involved in choosing which lodging to book. In particular, we devise features aimed to capture the user's price sensitivity as well as their perceived value of a particular lodging, the risk involved in choosing it rather than other available options, the authenticity of the cultural experience it could provide, and its overall perception by other users through word of mouth. Through a comprehensive evaluation using publicly available Airbnb data, we demonstrate the effectiveness of our proposed approach compared to a number of alternative recommendation baselines, including a simulation of Airbnb's own recommender.
Evaluation of methods for the operation of PMSM without position sensor

This paper presents an analytical evaluation of sensorless methods for the operation of permanent magnet synchronous machines. The influence of position estimation errors on the stability of a current controller and the deviation of the actual current value from the reference current are considered. Taking these effects into consideration, a flux estimator and a signal injection method are analyzed. Accuracy estimations and design guidelines for the implementation of the two methods are given.
Learning classifier systems: a gentle introduction

Learning Classifier Systems were introduced in the 1970s by John H. Holland as highly adaptive, cognitive systems. More than 40 years later, the introduction of Stewart W. Wilson's XCS, a highly engineered classifier system model, has transformed them into a state-of-the-art machine learning system. Learning classifier systems can effectively solve data-mining problems, reinforcement learning problems, and also cognitive, robotics control problems. In comparison to other, non-evolutionary machine learning techniques, their performance is competitive or superior, dependent on the setup and problem. Learning classifier systems can work both online and offline, they are extremely flexible, applicable to a larger range of problems, and are highly adaptive. Moreover, system knowledge can be easily extracted, visualized, or even used to focus the progressive search on particular interesting subspaces. This tutorial provides a gentle introduction to learning classifier systems and their general functionality. It then surveys the current theoretical understanding of the systems. Finally, we provide a suite of current successful LCS applications and discuss the most promising areas for future applications and research directions.
Women in China's Long Twentieth Century

This indispensable guide for students of both Chinese and women's history synthesizes recent research on women in twentieth-century China. Written by a leading historian of China, it surveys more than 650 scholarly works, discussing Chinese women in the context of marriage, family, sexuality, labor, and national modernity. In the process, Hershatter offers keen analytic insights and judgments about the works themselves and the evolution of related academic fields. The result is both a practical bibliographic tool and a thoughtful reflection on how we approach the past.
Ontogeny of Unstable Chromosomes Generated by Telomere Error in Budding Yeast

DNA replication errors at certain sites in the genome initiate chromosome instability that ultimately leads to stable genomic rearrangements. Where instability begins is often unclear. And, early instability may form unstable chromosome intermediates whose transient nature also hinders mechanistic understanding. We report here a budding yeast model that reveals the genetic ontogeny of genome rearrangements, from initial replication error to unstable chromosome formation to their resolution. Remarkably, the initial error often arises in or near the telomere, and frequently forms unstable chromosomes. Early unstable chromosomes may then resolve to an internal "collection site" where a dicentric forms and resolves to an isochromosome (other outcomes are possible at each step). The initial telomere-proximal unstable chromosome is increased in mutants in telomerase subunits, Tel1, and even Rad9, with no known telomere-specific function. Defects in Tel1 and in Rrm3, a checkpoint protein kinase with a role in telomere maintenance and a DNA helicase, respectively, synergize dramatically to generate unstable chromosomes, further illustrating the consequence of replication error in the telomere. Collectively, our results suggest telomeric replication errors may be a common cause of seemingly unrelated genomic rearrangements located hundreds of kilobases away.