Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliability of a Protocol to Elicit Peak Measures Generated by the Lower Limb for Semi-recumbent Eccentric Cycling

Semi-recumbent eccentric (ECC) cycling is increasingly used in studies of exercise with healthy and clinical populations. However, workloads are generally prescribed using measures obtained during regular concentric cycling. Therefore, the purpose of the study was to quantify the reliability of measures derived from a protocol that elicited peak ECC torque produced by the lower limb in a semi-recumbent position. Experiments were carried out on a dynamometer in a seated, semi-recumbent position identical to that of a custom-built ECC cycle, a modified Monark recumbent cycle. Thirty healthy participants completed two testing sessions. Each session comprised three series of six repetitions of a peak ECC torque protocol (PETP) on an isokinetic dynamometer. Absolute and relative reliability of peak torque, power, angle of peak torque, and work (recorded for each repetition) was determined using coefficient of variation (CV) and intraclass correlation coefficient (ICC), respectively. Ratings of perceived exertion (RPE), muscle soreness, and perceived effort (PE) were recorded pre-PETP, immediately post-PETP, and 1-min post each PETP. The protocol showed absolute reliability values <15% for mean peak (CV = 10.6–12.1) torque, power (CV = 10.4–12.3), angle of peak torque (CV = 1.2–1.4), and work (CV = 9.7–12.1). Moderate to high between-test relative reliability is reported for mean and highest torque (ICC = 0.84–0.95; ICC = 0.88–0.98), power (ICC = 0.84–0.94; ICC = 0.89–0.98), and work (ICC = 0.84–0.93; ICC = 0.88–0.98), respectively. Within-session peak torque, peak power, and peak work showed high relative reliability for mean (ICC = 0.92–0.95) and highest (ICC = 0.92–0.97) values. Overall, the PETP test provides a reliable way of determining peak ECC torque specific to semi-recumbent ECC cycling that may be used to prescribe workloads for this form of exercise.
Male-to-Female Gender-Affirming Surgery: 20-Year Review of Technique and Surgical Results

Purpose: Gender dysphoria (GD) is an incompatibility between biological sex and personal gender identity; individuals harbor an unalterable conviction that they were born in the wrong body, which causes personal suffering. In this context, surgery is imperative to achieve a successful gender transition and plays a key role in alleviating the associated psychological discomfort. In the current study, a retrospective cohort, we report the 20-years outcomes of the gender-affirming surgery performed at a single Brazilian university center, examining demographic data, intra and postoperative complications. During this period, 214 patients underwent penile inversion vaginoplasty. Results: Results demonstrate that the average age at the time of surgery was 32.2 years (range, 18–61 years); the average of operative time was 3.3 h (range 2–5 h); the average duration of hormone therapy before surgery was 12 years (range 1–39). The most commons minor postoperative complications were granulation tissue (20.5 percent) and introital stricture of the neovagina (15.4 percent) and the major complications included urethral meatus stenosis (20.5 percent) and hematoma/excessive bleeding (8.9 percent). A total of 36 patients (16.8 percent) underwent some form of reoperation. One hundred eighty-one (85 percent) patients in our series were able to have regular sexual intercourse, and no individual regretted having undergone GAS. Conclusions: Findings confirm that it is a safety procedure, with a low incidence of serious complications. Otherwise, in our series, there were a high level of functionality of the neovagina, as well as subjective personal satisfaction.
Herpesviruses in Reptiles

Since the 1970s, several species of herpesviruses have been identified and associated with significant diseases in reptiles. Earlier discoveries placed these viruses into different taxonomic groups on the basis of morphological and biological characteristics, while advancements in molecular methods have led to more recent descriptions of novel reptilian herpesviruses, as well as providing insight into the phylogenetic relationship of these viruses. Herpesvirus infections in reptiles are often characterised by non-pathognomonic signs including stomatitis, encephalitis, conjunctivitis, hepatitis and proliferative lesions. With the exception of fibropapillomatosis in marine turtles, the absence of specific clinical signs has fostered misdiagnosis and underreporting of the actual disease burden in reptilian populations and hampered potential investigations that could lead to the effective control of these diseases. In addition, complex life histories, sampling bias and poor monitoring systems have limited the assessment of the impact of herpesvirus infections in wild populations and captive collections. Here we review the current published knowledge of the taxonomy, pathogenesis, pathology and epidemiology of reptilian herpesviruses.
Exploring the Gut-Brain Axis for the Control of CNS Inflammatory Demyelination: Immunomodulation by Bacteroides fragilis’ Polysaccharide A

The symbiotic relationship between animals and their resident microorganisms has profound effects on host immunity. The human microbiota comprises bacteria that reside in the gastrointestinal tract and are involved in a range of inflammatory and autoimmune diseases. The gut microbiota’s immunomodulatory effects extend to extraintestinal tissues, including the central nervous system (CNS). Specific symbiotic antigens responsible for inducing immunoregulation have been isolated from different bacterial species. Polysaccharide A (PSA) of Bacteroides fragilis is an archetypical molecule for host-microbiota interactions. Studies have shown that PSA has beneficial effects in experimental disease models, including experimental autoimmune encephalomyelitis (EAE), the most widely used animal model for multiple sclerosis (MS). Furthermore, in vitro stimulation with PSA promotes an immunomodulatory phenotype in human T cells isolated from healthy and MS donors. In this review, we discuss the current understanding of the interactions between gut microbiota and the host in the context of CNS inflammatory demyelination, the immunomodulatory roles of gut symbionts. More specifically, we also discuss the immunomodulatory effects of B. fragilis PSA in the gut-brain axis and its therapeutic potential in MS. Elucidation of the molecular mechanisms responsible for the microbiota’s impact on host physiology offers tremendous promise for discovering new therapies.
Debugging Transient Faults in Data Centers using Synchronized Network-wide Packet Histories

Data center network faults are hard to debug due to their scale and complexity. With the prevalence of hard-to-reproduce transient faults, root-cause analysis of network faults is extremely difﬁcult due to unavailability of historical data, and inability to correlate the distributed data across the network. Often, it is not possible to ﬁnd the root cause using only switch-local information. To ﬁnd the root cause of such transient faults, we need: 1) Visibility : ﬁne-grained, packet-level and network-wide observability, 2) Retrospection : ability to get historical information before the fault occurs, and 3) Correlation : ability to correlate the information across the network. In this work, we present the design and implementation of S yNDB, a tool with the aforementioned capabilities to enable root cause analysis of network faults. We implement and evaluate S yNDB with realistic topologies using large scale simulation and programmable switches. Our evaluations show that S yNDB can capture and correlate packet records over sufﬁciently large time windows ( ∼ 4 ms), thus facilitating the root cause analysis of various network faults.
On the Use of ML for Blackbox System Performance Prediction

There is a growing body of work that reports positive results from applying ML-based performance prediction to a particular application or use-case (e.g., server configuration, capacity planning). Yet, a critical question remains unanswered: does ML make prediction simpler (i.e., allowing us to treat systems as blackboxes) and general (i.e., across a range of applications and use-cases)? After all, the potential for simplicity and generality is a key part of what makes ML-based prediction so attractive compared to the traditional approach of relying on handcrafted and specialized performance models. In this paper, we attempt to answer this broader question. We develop a methodology for systematically diagnosing whether, when, and why ML does (not) work for performance prediction, and identify steps to improve predictability. We apply our methodology to test 6 ML models in predicting the performance of 13 real-world applications. We find that 12 out of our 13 applications exhibit inherent variability in performance that fundamentally limits prediction accuracy. Our findings motivate the need for system-level modifications and/or ML-level extensions that can improve predictability, showing how ML fails to be an easy-to-use predictor. On implementing and evaluating these changes, we find that while they do improve the overall prediction accuracy, prediction error remains high for multiple realistic scenarios, showing how ML fails as a general predictor. Hence our answer is clear: ML is not a general and easy-to-use hammer for system performance prediction.
Weighed ℓ1 on the Simplex: Compressive Sensing Meets Locality

Sparse manifold learning algorithms combine techniques in manifold learning and sparse optimization to learn features that could be utilized for downstream tasks. The standard setting of compressive sensing can not be immediately applied to this setup. Due to the intrinsic geometric structure of data, dictionary atoms might be redundant and do not satisfy the restricted isometry property or coherence condition. In addition, manifold learning emphasizes learning local geometry which is not reflected in a standard ℓ1 minimization problem. We propose weighted ℓ0 and weighted ℓ1 regularizations that encourage representation via neighborhood atoms suited for dictionary based manifold learning. Assuming that the data is generated from Delaunay triangulation, we show the equivalence of weighted ℓ1 and weighted ℓ0. We discuss an optimization program that learns the dictionaries and sparse co-efficients and demonstrate the utility of our regularization on synthetic and real datasets.
Staying Alive: Connection Path Reselection at the Edge

Internet path failure recovery relies on routing protocols, such as BGP. However, routing can take minutes to detect failures and reconverge; in some cases, like partial failures or severe performance degradation, it may never intervene. For large scale network outages, such as those caused by route leaks, bypassing the affected party completely may be the only effective solution. This paper presents Connection Path Reselection (CPR), a novel system that operates on edge networks such as Content Delivery Networks and edge peering facilities [52, 64] and augments TCP to deliver transparent, scalable, multipath-aware end-to-end path failure recovery. The key intuition behind it is that edge networks need not rely on BGP to learn of path impairments: they can infer the status of a path by monitoring transport-layer forward progress, and then reroute stalled ﬂows onto healthy paths. Unlike routing protocols such as BGP, CPR operates at the timescale of round-trip times, providing connection recovery in seconds rather than minutes. By delegating routing respon-sibilities to the edge hosts themselves, CPR achieves per-connection re-routing protection for all destination preﬁxes without incurring additional costs reconstructing transport protocol state within the network. Unlike previous multipath-aware transport protocols, CPR is unilaterally deployable and has been running in production at a large edge network for over two years.
On the transport of heavy particles through an upward displacement-ventilated space

We explore the transport of heavy particles through an upward displacement-ventilated space. The space incorporates a localised source of buoyancy which generates a turbulent buoyant plume. The plume fluid is contaminated with a small concentration of particles, which are subject to gravitational settling. A constant flow of uncontaminated fluid is supplied at a low level into the space, while an equal amount of fluid is vented from the space at a high level. At steady state, a two-layer density stratification develops associated with the source of buoyancy. New laboratory experiments are conducted to explore how particles are transported by this flow. The experiments identify that the upper layer may either become well-mixed in particles or it may develop a vertical stratification in particle concentration, with the particle concentration decreasing with height. We develop a quantitative model which identifies that such stratification develops for larger particle setting speeds, or smaller ventilation rates. In accord with our experiments, the model predicts that the number of particles extracted from the space through the high-level vent is controlled by the magnitude of the particle stratification in the upper layer, and this in turn depends on the particle settling speed relative to the ventilation speed and also the cross-sectional area and height of the space. We compare the predictions of the model with measurements of the flux of particles vented from the space for a range of operating conditions. We explore the relevance of the model for the removal of airborne contaminants by displacement ventilation in hospital rooms, and we discuss how contamination is propagated in the room as a result of lateral mixing of pathogens in the upper layer.
Bootstrapping Battery-free Wireless Networks: Efficient Neighbor Discovery and Synchronization in the Face of Intermittency

Due to their favorable size, cost, and sustainability, battery-free devices are preferable in various applications. However, battery-free devices operate only intermittently since ambient energy sources, such as light and radio-frequency signals, are often too weak to continuously power the devices. This paper addresses the unsolved problem of efﬁcient device-to-device communication in the face of intermittency. We present Find , the ﬁrst neighbor discovery protocol for battery-free wireless networks that uses randomized waiting to minimize discovery latency. We also introduce Flync , a new hardware/software solution that synchronizes indoor light harvesting nodes to powerline-induced brightness variations of widely used lamps, which we exploit to further speed up neighbor discovery. Experiments with an open-source prototype built from off-the-shelf hardware components show that our techniques reduce the discovery latency by 4.3 × (median) and 34.4 × (99th percentile) compared with a baseline approach without waiting.
Genetically predicted serum vitamin D and COVID-19: a Mendelian randomisation study

Objectives To investigate causality of the association of serum vitamin D with the risk and severity of COVID-19 infection. Design Two-sample Mendelian randomisation study. Setting Summary data from genome-wide analyses in the population-based UK Biobank and SUNLIGHT Consortium, applied to meta-analysed results of genome-wide analyses in the COVID-19 Host Genetics Initiative. Participants 17 965 COVID-19 cases including 11 085 laboratory or physician-confirmed cases, 7885 hospitalised cases and 4336 severe respiratory cases, and 1 370 547 controls, primarily of European ancestry. Exposures Genetically predicted variation in serum vitamin D status, instrumented by genome-wide significant single nucleotide polymorphisms (SNPs) associated with serum vitamin D or risk of vitamin D deficiency/insufficiency. Main outcome measures Susceptibility to and severity of COVID-19 infection, including severe respiratory infection and hospitalisation. Results Mendelian randomisation analysis, sufficiently powered to detect effects comparable to those seen in observational studies, provided little to no evidence for an effect of genetically predicted serum vitamin D on susceptibility to or severity of COVID-19 infection. Using SNPs in loci related to vitamin D metabolism as genetic instruments for serum vitamin D concentrations, the OR per SD higher serum vitamin D was 1.04 (95% CI 0.92 to 1.18) for any COVID-19 infection versus population controls, 1.05 (0.84 to 1.31) for hospitalised COVID-19 versus population controls, 0.96 (0.64 to 1.43) for severe respiratory COVID-19 versus population controls, 1.15 (0.99 to 1.35) for COVID-19 positive versus COVID-19 negative and 1.44 (0.75 to 2.78) for hospitalised COVID-19 versus non-hospitalised COVID-19. Results were similar in analyses using SNPs with genome-wide significant associations with serum vitamin D (ie, including SNPs in loci with no known relationship to vitamin D metabolism) and in analyses using SNPs with genome-wide significant associations with risk of vitamin D deficiency or insufficiency. Conclusions These findings suggest that genetically predicted differences in long-term vitamin D nutritional status do not causally affect susceptibility to and severity of COVID-19 infection, and that associations observed in previous studies may have been driven by confounding. These results do not exclude the possibility of low-magnitude causal effects or causal effects of acute responses to therapeutic doses of vitamin D.
Comparison of the Quality of Life and Female Sexual Function Following Laparoscopic Pectopexy and Laparoscopic Sacrohysteropexy in Apical Prolapse Patients

Objective: We sought to compare the surgical outcomes, safety, effectiveness, and mid-term outcomes in patients who had undergone laparoscopic hysterosacropexy and laparoscopic pectopexy due to apical prolapse. Materials and Methods: This prospective randomized study was conducted on a total of 62 women who underwent apical prolapse surgery (32 undergoing a pectopexy and 30 undergoing a sacrohysteropexy) between June 2015 and June 2017. Patients with symptomatic uterine or vaginal vault prolapse with stage 2 or worse were included in the sudy. Before and after the operation, we used the Pelvic Organ Prolapse Quantification System (POP-Q) and questionnaires, which are the Prolapse Quality of Life Questionnaire (P-QOL) and Female Sexual Function Index (FSFI), to evaluated cases. Baseline characteristics, perioperative and postoperative complications, and follow-up results at 12 months were also evaluated. Results: All domains of POP-Q, P-QOL, and FSFI scores improved significantly after surgery both in pectopexy and sacrohysteropexy group. The postoperative complications of both procedures were similar except for constipation after surgery (3.2% in the pectopexy group and 20% in the hysterosacropexy group [P = 0.036]). Conclusion: Both sacrohysteropexy and pectopexy are effective surgical options for apical prolapse patients. The pectopexy is an acceptable alternative to laparoscopic sacrohysteropexy because of its less complexity and not reducing pelvic space for the rectum to exist. We suggest that the laparoscopic pectopexy may be widely used in clinical routine.
Analysis of physicochemical properties during the processing of Yiluxian, a traditional chinese low‐salt fish product

Yiluxian, a traditional Chinese low‐salt fish product, has been produced manually for decades. However, its quality depends on worker experience and varies owing to the lack of specific scientific guidelines for uniform production. This study investigated the changes in physicochemical properties under different salt concentrations and explored the principles underlying the low‐salt pickling process. The NaCl content of gutted fish increased to 3.82% in brining, and it decreased significantly to 1.15% after desalting. The colour of Yiluxian was not significantly different from that of raw fish (P > 0.05). The hardness, springiness, resistance and chewiness decreased by 12%, 9%, 27% and 19%, respectively, while cohesiveness did not change significantly (P > 0.05). Furthermore, Yiluxian is preferred over commonly salted fish for superior sensory profile. Our findings demonstrated the changes in various characteristics during pickling were expected to facilitate the stabilisation and uniformity of the quality and industrial production of this traditional food product.
Multi‐channel interface dipole of hyperbranched polymers with quasi‐immovable hydrion to modification of cathode interface for high‐efficiency polymer solar cells

The single‐junction polymer solar cells (PSCs) with high power conversion efficiency (PCE) are demonstrated by first incorporating two hyperbranched polymers (carboxylic acid functionalized hyperbranched poly(ether ketone) (CHBPEK) and sulfonic acid functionalized hyperbranched poly(ether sulfone) (SHBPES)) with carboxylic and sulfonic acid groups to modify the cathode interface. The effect of cathode modification by CHBPEK or SHBPES for conventional PSCs based on different active‐layer materials is systematically investigated. Compared with traditional LiF/Al, Ca/Al, and PFN/Al devices, significant improvement in short circuit current and fill factors are achieved by employing CHBPEK or SHBPES. In particular, the device with SHBPES as cathode interlayer can be achieved with a highest PCE of 9.12%, which are among the high performance reported for single‐junction PSCs modified with hyperbranched interlayers. Importantly, the influence of the hyperbranched polymer interlayer modification on the cathode interface is also discussed and found to be the formation of the stable multi‐channel interface dipole based on quasi‐immovable counterions in these polymers. The results supply a feasible means to obtain the improved JSC and FF for high efficiency PSCs. Copyright © 2016 John Wiley & Sons, Ltd.
CURRENT ISSUES AND PROSPECTS FOR THE DEVELOPMENT OF SCIENTIFIC RESEARCH

Biosensors based on surface plasmon resonance are unique devices that allow the detection of antigens of various nature: antigens of plant viruses, antigens of animal viruses, SCIENTIFIC COLLECTION «INTERCONF» | No 90 335 polyamine tumor markers. The problems and prospects of using immunosensors for express analysis on a single platform are discussed.
Central finite-difference of numerical solution for three-dimensional atmospheric transport equation

The energy transport equation is fundamental for the meteorological analysis; in this work, we analyze this equation in three dimensions using the methods of central finite differences; the analysis of convergence, consistency, and stability of the scheme shows a strong dependence of space and temporal variables. In conclusion, with the central finite differences was possible to predict the three-dimensional dynamics of the temperature.