Miracle-dz/UniFAR-FTUs huggingface dataset:
PROTEIN IN A MULTIPLE CARBOHYDRATE SUPPLEMENT

Wolfe, AS, Brandt, SA, Krause, IA, Mavison, RW, Aponte, JA, and Ferguson-Stegall, LM. Shorter duration time trial performance and recovery is not improved by inclusion of protein in a multiple carbohydrate supplement. J Strength Cond Res 31 (9): 2509–2518, 2017—Ingesting multiple carbohydrate (CHO) types during exercise can improve endurance performance compared with single CHO only. Adding protein to a multiple CHO beverage has been shown to increase cycling time to exhaustion (TTE) compared with a single CHO beverage. However, it is unclear if improvements were due to multiple CHO or protein, and TTE protocols are not representative of typical race events. This study investigated whether adding protein to a multiple CHO beverage improved performance and recovery in 2 same-day cycling time trials (TTs) compared with isocaloric multiple CHO only. Ten cyclists (37.4 6 8.9 years; V_ O2max 54.6 6 6.5 ml$kg21$min21) performed a familiarization and 2 randomized, crossover, double-blinded experimental trials consisting of pretrial leg strength testing, 40-km TT, 30-min recovery, 10-km TT, and posttrial leg strength testing. Seven 275 ml doses of multiple CHO (MCO) or multiple CHO+protein (MCP) were ingested during the protocol. Blood glucose, lactate, heart rate (HR), and rating of perceived exertion (RPE) were also measured. Continuous variables were analyzed with paired t-tests, and repeated measures with repeated-measures analysis of variance. No differences existed between MCO and MCP in 40km TT time (81.6 6 2.8 vs. 81.9 6 2.9 minutes, respectively, p = 0.94), or in 10-km time (24.0 6 0.9 vs. 23.9 6 1.0 minutes, p = 0.97). Blood glucose was higher before 10-km TT in MCO compared with MCP (3.78 6 0.20 vs. 3.31 6 0.19 mmol$L21, p = 0.002). No treatment differences were found for lactate, HR, RPE, or strength recovery. When using a protocol and performance measures that replicate realistic, shorter duration events, adding protein to a multiple CHO beverage does not improve performance compared with mul-
FACTORS AND POPULATION HEALTH RISKS UNDER EXPOSURE TO COMPONENTS DETECTED IN DRINKING WATER WITHIN NATURAL HYDROGEOCHEMICAL PROVINCES IN PERM REGION

Our research goal was to assess health risks for population who consumed drinking water with specific chemical structure systematically and for a long time. Drinking water quality is determined by conditions existing in hydrogeochemical provinces where rocks and soils contain increased concentrations of such hazardous metals as chromium, nickel, lead, manganese, and iron. We showed that low frequency or even absence of nonconformity to hygienic standards for admixtures in drinking water doesn't fully guarantee its safety in complicated hydrogeochemical conditions. When certain carcinogenic admixtures (cadmium, chromium, nickel, arsenic, and lead) occur together in drinking water even in low concentrations, it can cause unacceptable population health risks. Drinking water taken in examined geochemical provinces in Perm region causes individual lifelong carcinogenic risk which is (under the worst exposure scenarios) equal to 4 · 10. It can be ranked as De manifestis Risk and requires immediate measures to be taken by those responsible to reduce it. Unacceptable non-carcinogenic risks are caused by joint concentrations of arsenic, strontium, and some other compounds in drinking water. The highest risks existing on the examined territories were detected in relation to gastrointestinal tract diseases (HI up to 10.9, basic risk factor is chromium and its compounds), musculoskeletal system diseases (HI up to 11.8, strontium as a basic factor), and central nervous system diseases (HI up to 11.8, basic factors are arsenic, manganese, and lead). Contributions made by various elements into overall risks were different in different provinces. In some cases, when a certain element occurs in the crust in hazardous concentrations, its contents in drinking water are not observed. We recommend organizations that deal with water supply and sanitary surveillance bodies to take into account peculiarities of a geochemical province and to include admixtures that are contained in the environment in high quantities into monitoring programs and laboratory research.
Augment Your Business Reality with New Age Web Tools

When Berners Lee invented the Internet, he for sure could not have imagined the beast he unleashed. Today, some years later, the Internet is the single most important tool of communication, leisure, and information gathering. With Web 2.0 and social networks becoming more and more mainstream, we must ask the question about what more is about to come. If ever we will look back and define the current moments in 2010 as Web 3.0, it will for sure be the talk of touch screens, 3D technologies, and most of all, the rise of Augmented Reality (AR). This more sensory Internet leads to an entirely new experience of bridging the off-line with the on-line world. It makes the use more human and easier to use because it simulates various aspects of needs and activities we would demand and use even if we were not computer freaks. This chapter talks about AR and its applications and the way it can change our lives and businesses with the support of cyberspace.
Shape memory alloy actuators for upper limb prostheses

Despite the technological advances of the twentieth century, we are not yet able to produce artificial limbs which "mimic" perfectly their natural counterparts. In general, artificial limbs are not as dextrous as human limbs, the control is unnatural and there is no proper feedback by which the user can assess the status of the prosthesis. In this thesis the problems related to upper limb prostheses are considered. The use of a special material known as Shape Memory Alloy (SMA) is investigated towards producing improved joint actuators for small artificial prostheses such as those required by young children. SMA actuators can be very lightweight, their motion is silent and smooth and yet they are capable of delivering considerable power per unit of weight. The Shape Memory phenomenon and the many challenges involved in its application are discussed. The detailed design of a SMA joint actuator for a hand mechanism in an aboveelbow prosthesis for young children is given. To assist the design and construction of both the artificial hand and the actuator, a mathematical model was developed and incorporated in a computer program simulating the forces and movements within the hand. The model was used to optimise the hand mechanism and specify the required joint actuator. Suitable SMA elements were identified through laboratory tests. The hand mechanism was constructed and the actuator, control systems and power source were attached to it. Tests were performed to investigate the characteristics of the complete device. The results show that, although SMA actuators must be designed and used with great care, they do offer a viable alternative to conventional actuators such as pneumatic devices and electric motors in certain applications.
Optimum Values of the Bandwidth of the Optical and Electrical Filters for a System of High Mode Coupling Optical Fibers

All-optical long-haul network in a rapid development to increase the optical communication systems capacity. As a point in this direction we report the optimum values of the bandwidth of the optical for a system of high mode coupling optical fibers using DPSK modulation format for the input signal with considering the impairments CD, PMD, PDL, and the noise. Furthermore, we did get the optimum electrical filters bandwidth as well.
Expansion of Hindi WordNet using Knowledge Graph Completion Methods: A Survey

WordNet is a valuable resource with wide use-cases in both industry and academic settings. With the introduction of the English WordNet in 1995, WordNets for various languages have been developed over the years. However, these WordNets require frequent update as new words and facts are introduced and suffer from the problem of incompleteness. Link prediction (LP) is a widely known task in the field to counter the incompleteness problem of Knowledge Graphs (KG). In this work, we look at the expansion of the Hindi WordNet as a link prediction task. In this survey paper, we introduce the Hindi WordNet dataset as a KG accounting for test leakage in the dataset. In addition, we also look at various embedding-based Knowledge Graph Completion (KGC) models and evaluate the performance of these models on the dataset. For the evaluation, we look at both overall and relation-category specific performance.
Isometric resistance training increases strength and alters histopathology of dystrophin-deficient 1 mouse skeletal muscle 2 3 Short Title : Isometric training in mdx mice 4 5

3 Short Title: Isometric training in mdx mice 4 5 Authors: Angus Lindsay, Alexie A. Larson, Mayank Verma, James M. Ervasti and Dawn A. Lowe 6 7 Address of Authors 8 1. Division of Rehabilitation Science and Division of Physical Therapy, Department of Rehabilitation 9 Medicine, University of Minnesota, Minneapolis, USA 10 2. Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, 11 USA 12 3. Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, USA 13 4. Medical Scientist Training Program, University of Minnesota Medical School, Minneapolis, USA 14 15
Computation Reuse via Fusion in Amazon Athena

Amazon Athena is a serverless, interactive query service that allows efficiently analyzing large volumes of data stored in Amazon S3 using ANSI SQL. Some design choices in the engine, especially those concerning streaming of intermediate results, can result in suboptimal executions for query patterns that have common expressions. In this paper we build upon recent work and introduce new optimizations in Athena that handle some common expression scenarios without materializing intermediate results or duplicating work. We describe commonalities and differences with previous work, and provide experimental results that validate our approach on TPC-DS data.
Retrospective Evaluation of Clinical and Molecular Characteristics of Patients with Fabry Disease Being Followed-Up in Our Clinic

Objective: Fabry disease (FD) is an X-linked lysosomal storage disease (LSD), that occurs due to deficient activity of the enzyme alpha-galactosidase A (a-GalA) with multisystemic involvement. The disease can present with a wide range of symptoms, from mild form to the severely affected classical male phenotype with early organ failure and associated morbidity and mortality. Material and Methods: Patients diagnosed with FD at Dr. Sami Ulus Maternity and Child Health Training and Research Hospital were enrolled. Phenotypic and genotypic presentations of 10 cases from three unrelated families have been evaluated. Diagnoses of relatives of index patients were reached by family screening. Clinical, laboratory and molecular genetic analysis of patients were collected. Results: A total of 10 patients including 7 males, (mean age 31.8, range: 14-59 years) and 3 females, (mean age 44.6, range: 40-51 years) were evaluated. Various multisystem manifestations were observed, including cardiac, neurological, cerebrovascular and ophtalmological involvement. Eight out of ten patients had hypohydrosis, 4/10 had angiokeratomas and hearing loss. All male and female patients had abdominal pain and 9/10 had neuropathic pain. Among 7 male patients, 6 had renal complications and 2 of them reached end stage renal disease (ESRD) requiring renal replacement therapy. Concentric left ventricular hypertrophy, was the most common echocardiographic finding along with mitral regurgitation. Conclusion: ERT may slow down the progression of disease if inititated early. To ensure early diagnosis, it is important to recognize the symptoms of FD. Family screening may help patients to be identified at the presymptomatic phase of the disease.
Sportovní datová analýza: Porovnání české a dánské nejvyšší fotbalové soutěže

fans, journalists and, of course, the athletes themselves. In re cent years, football clubs have very often used the services of companies that analyse sports data. With the help of data analysis, it is possible to find out information that cannot be ascertained simply by observing the game. It is no wonder that there is currently a great deal of interest in sports data analysis, especially among football clubs, which make important strategic decisions based on them. Objective: Use statistical analysis to compare two professional European football competitions and identify their main similarities and differences. Methods: Methods of statisti cal data analysis were used to verify the research questions formulated in this research. The database was created based on variables obtained from InStat, which analyses the performance of athletes and sports teams. Statgraphics Centurion XVIII statistical software was used for the calculations. Results: Danish football is based on a compari son with Czech football as less competitive, more creative and more attractive for the spectator in terms of a larger number of goals scored. Danish football has a higher proportion of foreigners among the players. In both analysed competitions, a positive moderate dependence of point gain on the total number of fans at the stadium for the club was demonstrated. With the growth of total attendance, the Czech clubs grew their overall points at the end of the season faster than the Danish clubs. In both analysed competitions, a medium-strong correlation between the market value of players in the field and their performance was demonstrated. For a Czech player in the field, his market value grows faster depending on the game performance than for a player in a Danish competition. Conclusions: The research compared two European football competitions with a high potential for similarity using statistical data analysis. Data analysis in sports can be recommended in decision-making processes, mainly due to its economic and sports benefits.
Usability and applicability of a mindfulness based online intervention developed for people with problematic internet gaming behavior

In this study, the usability and applicability of a mindfulness based online administered gamified short-term intervention for people suffering from internet gaming disorder is investigated in a subclinical sample ( N = 49). Within a four-week intervention program ( Room2Respawn ) participants were randomly allocated to a gamified condition (experimental) or a neutral condition (control). Participants were provided with three intervention sessions per week consisting of psychoeducation on internet gaming disorder and mindfulness-exercises. Most of the intervention content has been adopted from a group-therapy intervention to an online platform. The 39 participants who participated over the course of the whole intervention rated the usability of the online-intervention overall and across all measures as good or very good. There was no evidence for beneficial effects of gamification on motivation when compared with ratings from a control condition. Areas of improvement and study limitations are discussed. Due to an easy applicability and very good usability, Room2Respawn shows potential to develop into a low-threshold treatment option, which, after rework, needs to be put to test on a sample showing clinical symptoms of pathological internet gaming.
Testing Dafny (experience paper)

Verification toolchains are widely used to prove the correctness of critical software systems. To build confidence in their results, it is important to develop testing frameworks that help detect bugs in these toolchains. Inspired by the success of fuzzing in finding bugs in compilers and SMT solvers, we have built the first fuzzing and differential testing framework for Dafny, a high-level programming language with a Floyd-Hoare-style program verifier and compilers to C#, Java, Go, and Javascript. This paper presents our experience building and using XDsmith, a testing framework that targets the entire Dafny toolchain, from verification to compilation. XDsmith randomly generates annotated programs in a subset of Dafny that is free of loops and heap-mutating operations. The generated programs include preconditions, postconditions, and assertions, and they have a known verification outcome. These programs are used to test the soundness and precision of the Dafny verifier, and to perform differential testing on the four Dafny compilers. Using XDsmith, we uncovered 31 bugs across the Dafny verifier and compilers, each of which has been confirmed by the Dafny developers. Moreover, 8 of these bugs have been fixed in the mainline release of Dafny.
LSTM-BASED ANOMALY DETECTION ON TIME-SERIES DATA

The complexity of network infrastructure is growing in tandem with the number of connected devices (i.e. PCs, mobile devices, servers, sensors, etc.). Infrastructure monitoring is essential as many managerial-related tasks highly depend on it. These include alerting partial or total system malfunction, outage prevention based on predictive identification of such situations, performance tracking, and, last but not least, security detection of system penetration. However, it has become far from obvious how to achieve timely, reliable, and sound infrastructure monitoring using traditional approaches. The concept of telemetry has been introduced in recent years to streamline this process. Network devices using it generate time series telemetry data that is streamed to a central collector. This streaming time-series data has to be analysed, plausibly by machine learning-based algorithms, to detect indications of abnormal behaviour and notify administrators. This process is called anomaly detection. In this study, we focus on anomaly detection on time-series telemetry data. We rigorously examined state-of-the-art anomaly detection methods. Specifically, we assessed ReRe, a Long Short-Term Memory-based (LSTM-based) algorithm. Although the algorithm was claimed to achieve high efficacy, our experiments revealed several limitations when applied on time-series data. Motivated by these findings, we propose in this study a modified version of ReRe, called Alter-Re 2 , to overcome these limitations. We introduce the concepts of ageing and sliding window as the key enablers of our extensions. The resulted performance improvements are promising, thus we could achieve in average three times better, but never worse performance with Alter-Re 2 compared to ReRe in our evaluations using ten different datasets. Furthermore, we also discuss how the data type being analysed impacts the reliability and precision of ReRe and Alter-Re 2 . We were able to create categories based on specific data patterns and draw conclusions on ReRe for each. We hope to shed new light on time-series anomaly detection and stimulate further research in the field. Our approach is advantageous in application domains where timely and accurate anomaly detection is essential, such as in network telemetry, IoT sensor streams, intrusion, fault, and fraud detection
Quality Assurance and Safety of Crops & Foods

In this study, thiamine, riboflavin and niacin contents of enriched pasta product were analysed during eight months of storage at ambient conditions under daylight, ambient conditions in the dark, and in a refrigerator for investigating the effects of different storage conditions. Thiamine content did not change significantly at different storage periods and conditions. Riboflavin content halved starting from the first month and decreased gradually under daylight conditions. However, in the dark and refrigerated conditions riboflavin content did not change significantly during the storage. Niacin content did not change due to storage under different conditions but gradually decreased during storage. Cooking water analysis indicated that the highest vitamin loss to cooking water was observed in niacin, so that niacin was more easily leached out from the pasta product as compared to other vitamins. Validation studies confirmed that the equipment, method and system performance were suitable for the purposes of the study.
Broadband low-sidelobe beamforming in time domain

In modern active and passive sonar systems, broadband digital beamforming for acoustic arrays is widely used to suppress unwanted interference and to detect interested target signals. A broadband low-sidelobe beamforming procedure in time domain is proposed. The first step of this procedure was to delay the outputs of each element in the acoustic array by digital delay lines to accomplish the integer part of the time delay. Then, finite impulse response (FIR) digital filters were used to implement the fractional part of the time delay. The weighting matrix for all array elements at different frequencies for low-sidelobe beam was also implemented with the FIR digital filters. Finally, the outputs of the digital filters were summed up yielding the time domain beam output. The design of low-sidelobe beam patterns and that of the FIR digital filters are two crucial technical issues in this beamforming procedure. We used the improved adaptive approach for the design of FIR digital filters, and the design requirements of these filters were specified by the weights which formed the low-sidelobe beams of each sub-band over the broad frequency band. The low-sidelobe beams of each sub-band were designed using the optimized beam synthesis approach based on the principle of MVDR beamforming. Results of computer simulation and lake-experiment for a twelve-element arc array showed that the beamforming procedure was not only correct but also promising in practical acoustic environment.