Miracle-dz/UniFAR-FTUs huggingface dataset:
Bilateral Knee Joint Cooling on Anaerobic Capacity and Wheel Cadence during Sprint Cycling Intervals

We compared the effect of bilateral knee joint cooling with or without a pre-cooling warm-up on sprint cycling performance to a non-cooling control condition. Seventeen healthy young males (25 ± 2 years, 174 ± 6 cm, 70 ± 9 kg) performed three conditions in a counterbalanced order (condition 1: warming + cooling + cycling; condition 2: cooling + cycling; condition 3: cycling). For warming, a single set of cycling intervals (a 10 s sprint with maximal effort followed by a 180 s active recovery; resistive load 4% and 1% body mass for sprint and recovery, respectively) was performed. For cycling, five sets of cycling intervals were performed. For cooling, 20 min of bilateral focal knee joint cooling was applied. Peak and average values of anaerobic capacity and wheel cadence during each set across conditions were statistically compared. There was no condition effect over set (condition × set) in anaerobic capacity (F8,224 < 1.49, p > 0.16) and wheel cadence (F8,224 < 1.48, p > 0.17). Regardless of set (condition effect: F2,224 > 8.64, p < 0.0002), conditions 1 and 2 produced higher values of anaerobic capacity (p ≤ 0.05). Similarly (condition effect: F2,224 > 4.62, p < 0.02), condition 1 showed higher wheel cadence (p < 0.02) than condition 3. A bilateral joint cooling for 20 min with or without pre-cooling warm-up may improve overall sprint cycling capacity during five sets of cycling intervals when compared to the non-cooling condition.
Evaluation and Comparison of Load Deflection Rate of Four Arch Wires Used in The Alignment Phase of Fixed Orthodontic Treatment: An In-Vitro Study

the ABSTRACT Aim : Adult patients warrant esthetic replacement for all the components of fixed orthodontic mechanotherapy. One of the latest advents is the esthetic archwire, Everwhite, properties of which have not yet been tested. Purpose of this study was to measure the load-deflection rate of esthetic archwire, Everwhite, and compare the same with that of three different types of archwires used in the alignment stage of fixed orthodontic treatment. Materials and methods: A modified three-point bending test was performed to measure the load deflection rate. Sample consisted of 60 wires 15 each of superelastic Nickel Titanium (NiTi), Everwhite esthetic NiTi, thermal NiTi and multistranded coaxial stainless steel. Force per unit deflection for every sample was measured at 37°C for two different deflections (2 mm and 4 mm). Since the data was normally distributed ANOVA was performed to assess the difference in load deflection rate of four archwires. Tukey HSD post Hoc test was used to evaluate the intergroup difference. Results: Comparison of mean load-deflection values revealed that thermal NiTi wires had lowest value at both 2 and 4mm deflection when compared to other three wires which was statistically significant (p=0.009). Superelastic and esthetic NiTi showed similar values of load deflection ratios at both the deflections whereas co-axial wire showed 1.89N at 2mm and 5.22N at 4mm deflection. Conclusion: The heat-activated NiTi wires are acceptable in severe crowding and periodontally compromised patients. Multistranded co-axial wire is acceptable when we need minimal alignment; whereas esthetic NiTi wires can replace superelastic NiTi based on patient’s need.
An introduction to reliable quantum computation

This is an introduction to software methods of quantum fault tolerance. Broadly speaking, these methods describe strategies for using the noisy hardware components of a quantum computer to perform computations while continually monitoring and actively correcting the hardware faults. We discuss parallels and differences with similar methods for ordinary digital computation, we discuss some of the noise models used in designing and analyzing noisy quantum circuits, and we sketch the logic of some of the central results in this area of research.
Utilizing Multi-Criteria Decision Making to Evaluate the Quality of Healthcare Services

Today’s patients are more informed and quality-conscious than ever before, which is crucial for healthcare practitioners as they interact with people’s lives daily. One of the most important challenges facing the healthcare sector worldwide concerns how to improve the overall quality of hospital care. As a result of the highly competitive nature of the economy in which healthcare services are offered, both public and private hospitals in Saudi Arabia must have their patient satisfaction rates assessed to help consumers make more informed decisions. As a result, we used the analytical hierarchy process (AHP) model to ascertain how patients in Saudi Arabia perceive the quality of the service that is provided by hospitals. The objective of the research work is to identify criteria for enhancing healthcare services using the analytic hierarchy process (AHP) technique to model the five SERVQUAL dimensions along with 2 dimensions and 31 sub-criteria. Three healthcare service organizations were selected for the study and evaluated based on their service quality performance. The AHP-based model has been demonstrated systematically for ranking the hospitals based on the healthcare system. It is observed that hospitals should concentrate the most on reliability, tangibles, and security and the least on consistency. In addition, according to the sub-criteria, the hospitals’ primary priority should be infection prevention and hygiene, with completeness receiving the least attention. Based on a survey of dimensions and their sub-criteria, the best hospital is Abha Private Hospital, followed by AHH, and then Asir General Hospital. Therefore, this study has implications for choices on the efficient monitoring of the overall health system to improve quality service delivery that would boost patient happiness, which is the goal of creating hospitals.
Bayesian AutoML for Databases via the InferenceQL Probabilistic Programming System

InferenceQL is a probabilistic programming system for scalable Bayesian AutoML from database tables. InferenceQL is designed to help make Bayesian approaches to data analysis more accessible to broad audiences and to assist experts in auditing and improving the quality of data, models, and inferences. Unlike traditional probabilistic programming systems, InferenceQL provides automation for learning models online using nonparametric Bayesian structure learning of probabilistic programs. Experts can override these models with custom probabilistic programs for specific subsets of variables and conditional distributions. For a broad class of models, InferenceQL can generate realistic synthetic data subject to constraints and can automatically compute exact probabilities and mutual information values. Finally, InferenceQL aims to enable scalable Bayesian model criticism via posterior predictive checks, data quality screening via conditional probability calculation, fairness auditing via conditional probability ratios, and synthetic data generation to enhance privacy. These capabilities are accomplished using constructs that interleave standard database queries with Bayesian inference.
Conventional clustering-based method for event detection on social networks

Social networks are becoming the preferred 001 channel to report and discuss events happening 002 around the world. The information stream such 003 channels contain can be used to detect and de-004 scribe the ongoing events to take informed de-005 cisions in numerous domains. A typical frame-006 work for event detection is to first cluster the 007 stream of tweets, and then analyze the clusters 008 to decide which deal with real-world events. 009 In this context, content representation models 010 and clustering approaches are critical. Classi-011 cal approaches are usually based on TF-IDF 012 for the representation of the text content and 013 on dynamic clustering for the clustering part. 014 In this paper, we propose to compare TF-IDF 015 with recent text representation models and we 016 propose an event detection method based on 017 conventional clustering. We show that, contrary 018 to previous results, language models based on 019 Transformer architectures are competitive with 020 TF-IDF. We also show that our approach outper-021 forms the most used approach of the literature. 022
The Effect of Pythagorean Self-Awareness on Heart Rate Variability, Perceived Stress and Behavior of Preschool Children

Stress is associated with unhealthy habits and non-communicable diseases. It is also linked to communicable diseases due to its impact on immune function. These can be prevented through intervention programs in schools. The aim of this study was to examine the effect of the simplified Pythagorean Self-Awareness Intervention on heart rate variability (HRV) parameters, perceived stress and behaviors of preschool children. The sample of the study consisted of 45 preschool students. A “one group (double) pretest—posttest design” was used, to allow for comparisons of the measurements before and after the intervention. Students were assessed via two questionnaires (“Perceived Stress Scale for Children” (PSS-C) and “Checklist for Screening Behavioral Problems in Preschool Children”) and a photoplethysmographic (PPG) device. The intervention lasted 9 weeks and included practicing of the Pythagorean Self-awareness techniques and the adoption of healthy behaviors. The results showed no statistically significant differences between the two pretests (p > 0.05 for all comparisons) and statistically significant differences between the second pretest and posttest (“Perceived Stress Scale for Children”, (PSS-C) p < 0.0001, “Checklist for Screening Behavioral Problems in Preschool Children” p < 0.0001 and two indices of PPG device: heart rate mean, p < 0.0001, low frequency/very low frequency, p = 0.034). In conclusion, the Pythagorean Self-Awareness Intervention had a beneficial effect on the sample of preschool students examined, as the results showed an improvement in the perceived stress and the HRV parameters tested, and in engaging healthier behaviors, findings that indicate a relaxed psychologic state and a healthier lifestyle.
Scale Difference from the Impact of Disease Control on Pig Production Efficiency

Simple Summary This paper uses the data of fixed observation points in the country’s rural areas, the Data Envelopment Analysis model is used to calculate the production efficiency of pig farmers, which shows the efficiency level of pig breeding in the country. Then, the Tobit model is used to analyze that epidemic prevention and control has a positive effect on production efficiency. Finally, the threshold regression model was used to analyze the results: the effect of disease control on production efficiency was different under different breeding scales. When the breeding scale was less than 6.0002, the disease control had a negative impact on the production efficiency. When the breeding scale was greater than 12.9994, the disease control had a positive impact on the production efficiency. The research results of this paper not only help farmers to correctly understand the relationship between epidemic prevention and production efficiency, guide farmers to expand their breeding scale, and actively participate in epidemic prevention and control, but also provide a reference for the government to formulate policies according to different scales to guide farmers to carry out epidemic prevention and control. Abstract Epidemic disease prevention plays a critical role in ensuring the healthy development of livestock farming, and the subjective willingness of breeders can be affected by the cost of epidemic disease prevention. To correct the misconception that farmers regard the cost of disease control as an ineffective cost, and to promote the healthy development of the pig breeding industry, our study employed the data envelopment analysis super-efficiency model and panel threshold regression model to evaluate the combination of the cost of epidemic disease prevention and swine productivity using data collected from 1998–2018 across 30 provinces in China. The following results were obtained. (1) The cost of epidemic disease prevention generated a non-linear on swine productivity when the swine farming scale was limited; (2) When the number of animals at the beginning of the year was less than 6.0002, swine productivity was impacted negatively; (3) When the number of animals at the beginning of the year ranged between 6.0002 and 12.9994, the impact was insignificant; (4) A strong correlation was observed between the expenses of epidemic disease prevention and animal productivity when the number of animals at the beginning of the year exceeded 12.9994. These results indicate that publicity should be enhanced to elucidate the combination of epidemic disease prevention and swine productivity among breeders. In addition, the government should introduce relevant policies to encourage the development of large-scale pig farming, such as subsidies for the construction of large-scale farms and insurance.
OCTRA - An Innovative Approach to Orthographic Transcription

Octra is an open-source editor for web-based orthographic transcription. It runs in a web browser on any platform, and operates in an online and a local mode. In the local mode, ﬁles are opened via drag & drop on the browser window, in the on-line mode the transcriber logs in and selects the transcription project; the next ﬁle to transcribe is opened immediately. Octra features three different viewers: dictaphone, linear and 2D, and it may access external web services, e.g. for ASR or time-aligning the transcript and the signal. It supports various common ﬁle formats for interoperability, for import and export. In Octra, a transcriber places boundaries in the signal and then transcribes these transcription units. The length of the transcription units is determined by the personal preferences of the transcriber, and may vary with the type of recordings.
Clinical Update on Uses for Mifepristone in Obstetrics and Gynecology

Importance Mifepristone (RU-486) is a selective progesterone receptor modulator that has antagonist properties on the uterus and cervix. Mifepristone is an effective abortifacient, prompting limitations on its use in many countries. Mifepristone has many uses outside of induced abortion, but these are less well known and underutilized by clinicians because of challenges in accessing and prescribing this medication. Objective To provide clinicians with a history of the development of mifepristone and mechanism of action and safety profile, as well as detail current research on uses of mifepristone in both obstetrics and gynecology. Evidence Acquisition A PubMed search of mifepristone and gynecologic and obstetric conditions was conducted between January 2018 and December 2021. Other resources were also searched, including guidelines from the American College of Obstetricians and Gynecologists and the Society of Family Planning. Results Mifepristone is approved by the Food and Drug Administration for first-trimester medication abortion but has other off-label uses in both obstetrics and gynecology. Obstetric uses that have been investigated include management of early pregnancy loss, intrauterine fetal demise, treatment of ectopic pregnancy, and labor induction. Gynecologic uses that have been investigated include contraception, treatment of abnormal uterine bleeding, and as an adjunct in treatment of gynecologic cancers. Conclusions and Relevance Mifepristone is a safe and effective medication both for its approved use in first-trimester medication abortion and other off-label uses. Because of its primary use as an abortifacient, mifepristone is underutilized by clinicians. Providers should consider mifepristone for other indications as clinically appropriate. Target Audience Obstetricians and gynecologists, family physicians. Learning Objectives After completing this activity, the learner should be better able to describe the history of the development of mifepristone, including its mechanism of action and safety profile; and explain the uses for mifepristone in both obstetrics and gynecology.
Detecting Metabolic Thresholds from Nonlinear Analysis of Heart Rate Time Series: A Review

Heart rate time series are widely used to characterize physiological states and athletic performance. Among the main indicators of metabolic and physiological states, the detection of metabolic thresholds is an important tool in establishing training protocols in both sport and clinical fields. This paper reviews the most common methods, applied to heart rate (HR) time series, aiming to detect metabolic thresholds. These methodologies have been largely used to assess energy metabolism and to identify the appropriate intensity of physical exercise which can reduce body weight and improve physical fitness. Specifically, we focused on the main nonlinear signal evaluation methods using HR to identify metabolic thresholds with the purpose of identifying a method which can represent a useful tool for the real-time settings of wearable devices in sport activities. While the advantages and disadvantages of each method, and the possible applications, are presented, this review confirms that the nonlinear analysis of HR time series represents a solid, robust and noninvasive approach to assess metabolic thresholds.
Retrograde binaries of massive black holes in circum-binary accretion discs

We explore the hardening of a massive black hole binary embedded in a circum-binary gas disc when the binary and the gas are coplanar and the gas is counter-rotating. The secondary black hole, revolving in the direction opposite to the gas, experiences a drag from gas-dynamical friction and from direct accretion of part of it. Using two-dimensional (2D) hydrodynamical grid simulations we investigate the effect of changing the accretion prescriptions on the dynamics of the secondary black hole which in turn affect the binary hardening and eccentricity evolution. We find that realistic accretion prescriptions lead to results that differ from those inferred assuming accretion of all the gas within the Roche Lobe of the secondary black hole. Different accretion prescriptions result in different disc's surface densities which alter the black hole's dynamics back. Full 3D SPH realizations of a number of representative cases, run over a shorter interval of time, validate the general trends observed in the less computationally demanding 2D simulations. Initially circular black hole binaries increase only slightly their eccentricity which then oscillates around small values (<0.1) while they harden. By contrast, initially eccentric binaries become more and more eccentric. A semi-analytical model describing the black hole's dynamics under accretion only explores the late evolution stages of the binary in an otherwise unperturbed retrograde disc to illustrate how eccentricity evolves with time in relation to the shape of the underlying surface density distribution.
Analysis of a Queueing Model with MAP Arrivals and Heterogeneous Phase-Type Group Services

Queueing models have proven to be very useful in real-life applications to enable the practitioners to optimize the limited resources to conduct their businesses as well as offer services efficiently. In general, we can group such applications into two sectors: manufacturing and service. These two sectors cover everything we deal with on a day-to-day basis. Queues in which the services are offered in blocks (or groups or batches) are well established in the literature and have a wide variety of applications in practice. In this paper, we look at one such queueing model in which the arrivals occur according to a Markovian arrival process and the services are offered in batches of varying sizes from 1 to a finite pre-determined constant, say, b. The service times are assumed to be of phase type with representation depending on the size of the group. Thus, the distributions considered are heterogeneous from both the representation and rate points of view. The model can be studied as a GI/M/1-type queue or as a QBD-model. The model is analyzed in steady state by establishing results including on the rate matrix and the waiting time distribution and providing a number of illustrative examples.
Suprachiasmatic to paraventricular nuclei interaction generates normal food searching rhythms in mice

Searching for food follows a well-organized decision process in mammals to take up food only if necessary. Moreover, scavenging is preferred during their activity phase. Various time-dependent regulatory processes have been identified originating from the suprachiasmatic nuclei (SCN), which convert external light information into synchronizing output signals. However, a direct impact of the SCN on the timing of normal food searching has not yet been found. Here, we revisited the function of the SCN to affect when mice look for food. We found that this process was independent of light but modified by the palatability of the food source. Surprisingly, reducing the output from the SCN, in particular from the vasopressin releasing neurons, reduced the amount of scavenging during the early activity phase. The SCN appeared to transmit a signal to the paraventricular nuclei (PVN) via GABA receptor A1. Finally, the interaction of SCN and PVN was verified by retrograde transport-mediated complementation. None of the genetic manipulations affected the uptake of more palatable food. The data indicate that the PVN are sufficient to produce blunted food searching rhythms and are responsive to hedonistic feeding. Nevertheless, the search for normal food during the early activity phase is significantly enhanced by the SCN.
Simultaneous Estimation of Hand Joints’ Angles Toward sEMG-Driven Human–Robot Interaction

Human beings have very dexterous hands which help us manipulate a lot of complicated tools. But most researches focus on gesture recognition. This situation leads to the phenomenon that our prosthetic hands lack continuous and natural movement. This paper proposes a method aimed to decode finger movements continuously and simultaneously based on multi-channel surface electromyography signals. This algorithm is useful for surface electromyography(sEMG) decoding controlled for a prosthetic hand, exoskeleton robots for upper-limb rehabilitation, and remote mechanical hand control. Firstly, the feature extractor based on a sliding time window is used to extract 8 kinds of sEMG features (mean absolute value, integral sEMG value, root mean square, waveform length, logarithmic feature, zero-crossing points, and slope symbol change) from the sEMG signals of 8 channels of the forearm. The estimated angle of the metacarpophalangeal joint with large fluctuation is optimized by inputting them to the deep forest regression model; Then, the artificial neural network is used to optimize this estimated angle, to create a comprehensive regression model combining the deep forest regression model and artificial neural network; Finally, the comprehensive regression model is used to continuously and accurately decode the collected surface EMG signal to obtain the prosthetic hand finger joint angle control values, and the other finger joint angles can be obtained through proportional control principle. The experimental results show that the average trajectory tracking accuracy of the proposed method is 42% higher than that of the traditional Gaussian process method, reaching 84.4%, which proves that the proposed method has a very good effect on finger joint angle estimation based on sEMG signal.