Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of the Thermal Environment on Work Rate and Physiological Strain during a UCI World Tour Multistage Cycling Race

ABSTRACT Purpose This study aimed to characterize the thermal and cardiovascular strain of professional cyclists during the 2019 Tour Down Under and determine the associations between thermal indices and power output, and physiological strain. Methods Gastrointestinal temperature (Tgi), heart rate (HR), and power output were recorded during the six stages (129–151.5 km) of the Tour Down Under in ≤22 male participants. Thermal indices included dry-bulb, black-globe, wet-bulb, and wet-bulb-globe (WBGT) temperature; relative humidity (RH), Heat Index; Humidex; and universal thermal climate index. The heat stress index (HSI), which reflects human heat strain, was also calculated. Results Dry-bulb temperature was 23°C–37°C, and RH was 18%–72% (WBGT: 21°C–29°C). Mean Tgi was 38.2°C–38.5°C, and mean peak Tgi was 38.9°C–39.4°C, both highest values recorded during stage 3 (WBGT: 27°C). Peak individual Tgi was ≥40.0°C in three stages and ≥39.5°C in 14%–33% of cyclists in five stages. Mean HR was 131–147 bpm (68%–77% of peak), with the highest mean recorded in stage 3 (P ≤ 0.005). Mean power output was 180–249 W, with the highest mean recorded during stage 4 (P < 0.001; 21°C WBGT). The thermal indices most strongly correlated with power output were black-globe temperature (r = −0.778), RH (r = 0.768), universal thermal climate index (r = −0.762), and WBGT (r = −0.745; all P < 0.001). Mean Tgi was correlated with wet-bulb temperature (r = 0.495), HSI (r = 0.464), and Humidex (r = 0.314; all P < 0.05), whereas mean HR was most strongly correlated with HSI (r = 0.720), along with Tgi (r = 0.599) and power output (r = 0.539; all P < 0.05). Conclusions Peak Tgi reached 40.0°C in some cyclists, although most remained <39.5°C with an HR of ~73% of peak. Power output was correlated with several thermal indices, primarily influenced by temperature, whereas Tgi and HR were associated with the HSI, which has potential for sport-specific heat policy development.
Revised Clinical Practice Guidelines of the Korean Pancreatobiliary Association for Acute Pancreatitis

Acute pancreatitis can range from a mild, self-limiting disease requiring no more than supportive care, to severe disease with life-threatening complications. With the goal of providing a recommendation framework for clinicians to manage acute pancreatitis, and to contribute to improvements in national health care, the Korean Pancreatobiliary Association (KPBA) established the Korean guidelines for acute pancreatitis management in 2013. However, many challenging issues exist which often lead to differences in clinical practices. In addition, with newly obtained evidence regarding acute pancreatitis, there have been great changes in recent knowledge and information regarding this disorder. Therefore, the KPBA committee underwent an extensive revision of the guidelines. The revised guidelines were developed using the Delphi method, and the main topics of the guidelines include the following: diagnosis, severity assessment, initial treatment, nutritional support, convalescent treatment, and the treatment of local complications and necrotizing pancreatitis. Specific recommendations are presented, along with the evidence levels and recommendation grades.
Deep Forest With Multi-Channel Message Passing and Neighborhood Aggregation Mechanisms for Brain Network Classification

As a novel deep learning method, deep forest has achieved excellent classification performance on many small-scale datasets, thus providing a new opportunity to accurately classify brain networks (BNs) on limited fMRI data. Though there are a few explorations about classifying BNs using deep forest, they only adopt sliding windows to extract adjacent features of BNs and fail to use prior knowledge to strengthen the features more relevant to brain diseases. In this paper, we propose a deep forest framework with multi-channel message passing and neighborhood aggregation mechanisms (DF-MCMPNA) to extract and aggregate long-range multi-channel topological features. Firstly, we use the three intrinsic connectivity networks (ICNs) and the whole-brain to form four feature extraction channels. Secondly, we present a multi-channel message passing mechanism and a channel-shared neighborhood aggregation mechanism to recursively extract long-range multi-channel topological features, where the first mechanism can learn local topological features in each channel and the second mechanism can fuse multi-channel topological features. Finally, the extracted features are fed into the casForst to perform further feature learning and classification. Experimental results on ABIDE I, ABIDE II, and ADHD-200 datasets show that the DF-MCMPNA outperforms several state-of-the-art methods on classification performance and accurately identifies abnormal brain regions.
A retrotransposon insertion in MUTL-HOMOLOG 1 affects wild rice seed set and cultivated rice crossover rate.

Wild rice (Oryza rufipogon) has a lower panicle seed setting rate (PSSR) and gamete fertility than domesticated rice (O. sativa), but the genetic mechanisms of this phenomenon remain unknown. Here, we cloned a null allele of OsMLH1, an orthologue of MutL-homolog 1 to yeast and mammals, from wild rice O. rufipogon W1943 and revealed a 5.4-kb retrotransposon insertion in OsMLH1 is responsible for the low PSSR in wild rice. In contrast to the wild type, a near isogenic line NIL-mlh1 exhibits defective crossover formation during meiosis, resulting in reduced pollen viability, partial embryo lethality and low PSSR. Except for the mutant of mismatch repair gene post-meiotic segregation 1 (Ospms1), all other MutL mutants from O. sativa indica subspecies displayed male and female semi-sterility similar to NIL-mlh1, but less severe than those from O. sativa japonica subspecies. MLH1 and MLH3 did not contribute in an additive fashion to fertility. Two types of MutL heterodimers, MLH1-PMS1 and MLH1-MLH3, were identified in rice, but only the latter functions in promoting meiotic crossover formation. Compared to japonica varieties, indica cultivars had greater numbers of crossover events per meiosis. Our results suggest that low fertility in wild rice may be caused by different gene defects, and indica and japonica subspecies have substantially different crossover rates responsible for the discrepancy between the fertility of mlh1 and mlh3 mutants.
EMPIRICAL BAYES ESTIMATION OF FINITE POPULATION VARIANCES

SUMMARY. The Klee-Rao model, a mixed model with random sampling variances, is extended to produce empirical Bayes estimators of several finite population variances. The proposed empirical Bayes estimators do not have a closed form. A second order Laplace approximation is used which works well for moderately large sample sizes. This approximation is specially useful when the uncertainties of the proposed empirical Bayes estimators are measured by the parametric bootstrap technique. A numerical example is considered to demonstrate the method.
Is the injection of tramadol effective at control of pain after impacted mandibular third molar extractions? A systematic review and meta-analysis

Background Third molar extraction is among the most common surgical procedures performed by oral-maxillofacial surgeons. Postoperative pain, swelling and trismus are common, especially in wisdom teeth, due to trauma to local tissues and the duration of the surgical procedure, among other factors. Material and Methods This systematic review was conducted in accordance with the ‘Preferred Reporting Items for Systematic Reviews and Meta-Analyses’ in order to answer the focused question: ‘Is the local submucosal injection of tramadol effective at the control of postoperative pain in patients submitted to impacted mandibular third molar extractions? ’. We analyzed papers published until March 30, 2021 in the MEDLINE|PubMed, Web of Science and Cochrane Library databases. Gray literature was also consulted. Standard pairwise meta-analyses of direct comparisons were performed using a fixed-effect model; I2 ≥ 50 % or ≥ 75 % indicated moderate or high heterogeneity, respectively. Risk of bias was assessed by Cochrane Collaboration’s tool. Results In total, 172 participants (98 males and 74 females, aged 18 or over) from three randomized placebo-controlled trials were considered for analysis. The submucosal injection of 2 ml of tramadol adjacent to the impacted mandibular third molar was effective in controlling pain up to 6-hours after surgery, in increasing the onset of consumption of rescue analgesic and in reducing the total number of rescue analgesics used. Conclusions The submucosal injection of tramadol can be considered a safe and effective procedure for pain control after impacted mandibular third molar extractions. Key words:Tramadol, impacted teeth, third molars, postoperative pain, adverse effects.
AlphaFold, Artificial Intelligence (AI), and Allostery

AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of biological sequence data and artificial intelligence (AI). AlphaFold has appended projects and research directions. The database it has been creating promises an untold number of applications with vast potential impacts that are still difficult to surmise. AI approaches can revolutionize personalized treatments and usher in better-informed clinical trials. They promise to make giant leaps toward reshaping and revamping drug discovery strategies, selecting and prioritizing combinations of drug targets. Here, we briefly overview AI in structural biology, including in molecular dynamics simulations and prediction of microbiota–human protein–protein interactions. We highlight the advancements accomplished by the deep-learning-powered AlphaFold in protein structure prediction and their powerful impact on the life sciences. At the same time, AlphaFold does not resolve the decades-long protein folding challenge, nor does it identify the folding pathways. The models that AlphaFold provides do not capture conformational mechanisms like frustration and allostery, which are rooted in ensembles, and controlled by their dynamic distributions. Allostery and signaling are properties of populations. AlphaFold also does not generate ensembles of intrinsically disordered proteins and regions, instead describing them by their low structural probabilities. Since AlphaFold generates single ranked structures, rather than conformational ensembles, it cannot elucidate the mechanisms of allosteric activating driver hotspot mutations nor of allosteric drug resistance. However, by capturing key features, deep learning techniques can use the single predicted conformation as the basis for generating a diverse ensemble.
Feasibility and patient’s experiences of perioperative telemonitoring in major abdominal surgery: an observational pilot study

ABSTRACT Background Telemonitoring during the perioperative trajectory may improve patient outcomes and self-management. The aim of this study is to assess the feasibility of and patient’s experiences with telemonitoring before and after major abdominal surgery to inform future study design. Methods Patients planned for elective major abdominal surgery wore a sensor and answered well-being questions on a tablet daily for at least 2 weeks preoperatively up to 30-days postoperatively. Feasibility was assessed by participation and completion rate, compliance per day, weekly satisfaction scores, and reasons for nonscheduled contact. Results Twenty-three patients were included (participation rate of 54.5%) with a completion rate of 69.6%. Median compliance with the wearable sensor and well-being questions was respectively: 94.7% and 83.3% preoperatively at home; 100% and 66.7% postoperatively in-hospital; and 95.4% and 85.8% postoperatively at home. Median weekly satisfaction scores for both wearing the sensor and well-being questions were 5 (IQR, 4–5). Contact moments were related to absence of sensor data and technological issues (76.0%) or patient discomfort and insecurity (24.0%). Conclusions In this study, telemonitoring showed high satisfaction and compliance during the perioperative trajectory. Future trial design regarding the effectiveness of telemonitoring requires embedding in clinical practice and support for patients, relatives, and healthcare personnel.
A comprehensive review of fault diagnosis and fault-tolerant control techniques for modular multi-level converters

Background Many faults occur in the modular multi-level converters (MMCs), including unbalancing capacitor voltage, lower and upper arm unbalancing, the line to line voltage unbalancing, sensors and actuators fault, system fault, and sub-modules fault in high as well as medium voltage applications. Introduction Several fault-tolerant approaches are presented to overcome these problems, such as active fault-tolerant control system (AFTCS), passive fault-tolerant control system (PFTCS), hybrid fault-tolerant control system (HFTCS), redundant system technique, special power circuit with the controller, and zero sequence voltage methods, which we will explain extensively in this article. Methodology This review emphasizes the types of faults in the MMCs and discusses the protection methods under failure conditions. The MMC is more popular in high voltage applications because it not only improves the quality of the grid but also has good harmonic performance in high power transmission. There is no need for any isolated dc sources to operate it. When faults are removed, the efficiency and reliability of the system will be increased. Results This extensive explanation of the current literature on MMC fault diagnosis and control techniques will conclude which methods provide a more valuable solution. Finally, this paper discusses the best approach to reduce MMC faults and provides a future research direction to the readers.
Effects of core training on dynamic balance stability: A systematic review and meta-analysis

ABSTRACT Core stability has a strong relationship with dynamic balance stability (DBS). The purpose of this review with meta-analysis was to analyse the effects of core training programmes from different studies on DBS. A literature search was performed using different databases. Subgroups analyses on duration, training frequency, total sessions, chronological age, training status, equipment and movements were performed. A random-effects model for meta-analyses was used. Thirteen studies were selected for the systematic review and 10 for the meta-analysis, comprising 226 participants. A moderate effect was noted for core training on DBS (p < 0.001; ES = 0.634). Greater DBS improvements were found in core training interventions with ≤6 weeks (ES = 0.714), after high volume (ES = 0.787) and more frequent interventions (ES = 0.787), as well as in younger participants (ES = 0.832). In addition, body weight exercises may be better than med ball, swiss ball or band resisted exercises. Core training improves DBS among athletes and a non-trained population, creating a more solid stable base that allows better lower extremity movements. This could be more effective considering different modulators ≤6 weeks intervention, >2 sessions per week, >17 total sessions, body weight core programmes and applied to ≤18.0 years old.
Multivariate analyses of Ethiopian durum wheat revealed stable and high yielding genotypes

Improving crop adaptation and stability across diverse and changing environmental conditions is essential to increasing grain yield per unit area. In turn, this contributes to meeting the increasing global food demand. Nevertheless, a number of factors challenge the efficiency of crop improvement programs, of which genotype-by-environment interaction (GEI) is one of the major factors. This study aimed to evaluate the performance and phenotypic stability of 385 Ethiopian durum wheat landraces and 35 cultivars; assess the pattern of genotype by environment interaction (GEI) effect, and identify stable and high-yielding landraces or cultivars using the additive main effect and multiplicative interaction (AMMI) and genotype main effect plus genotype by environment interaction biplot (GGE-biplot). The experiment was laid out in an alpha lattice design with two replications at five test sites (Akaki, Chefe Donsa, Holeta, Kulumsa, and Sinana). The combined analysis of variance revealed highly significant effects (P ≤ 0.01) of environments (E), genotype (G), and GEI on a phenotypic variation of traits evaluated, including grain yield. For all traits, the amount of phenotypic variance and GEI explained by the GGE biplot was higher than in AMMI2, but both exhibited significant effects of E and GEI on the genotypes. The AMMI model identified G169, G420, G413, G139, G415, G416, G417, and G418 as stable genotypes across testing sites. Whereas, the GGE biplot identified G169, G420, G415, G139, G106, G412, G413, and G417 as both high-yielding and stable across test sites. Hence, genotypes identified as stable and high yielding in the present study could be used in a durum wheat breeding program aimed at identifying genes and molecular markers associated with the crop’s productivity traits as well as developing stable and high-yielding cultivars for use in East Africa and beyond.
The Application of Singular Value Decomposition to Dutch Noun-Adjective Matrices

Automatic acquisition of semantics from text has received quite some attention in natural language processing. A lot of research has been done by looking at syntactically similar contexts. For example, semantically related nouns can be clustered by looking at the collocating adjectives. There are, however, two major problems with this approach : computational complexity and data sparseness. This paper describes the application of a mathematical technique called singular value decomposition, which has been succesfully applied in Information Retrieval to counter these problems. It is investigated whether this technique is also able to cluster nouns according to latent semantic dimensions in a reduced adjective space.
Approaches to the development of new mental well-being screening tools for Indigenous peoples: a systematic mixed studies review protocol

Introduction Indigenous peoples' world views are intricately interrelated and interconnected with those of their communities and the environments where they live. Consequently, Indigenous peoples have a holistic view of their health, which contrasts with the dominant Western biomedical paradigm. However, the mental well-being of Indigenous peoples is predominately screened using tools developed using the Western paradigm that may not be culturally appropriate. The objective of this systematic mixed studies review (SMSR) is to assess the extent of the literature related to approaches used to develop new tools to screen the mental well-being of Indigenous adults. Methods and analysis This SMSR will be conducted in accordance with the method proposed by Pluye et al. It will include studies that describe the development of any type of tool or approach to screen for mental well-being in Indigenous adults, globally. Searches will be limited to the English language and literature published since January 2000. Databases to be searched include: CINAHL, Medline, PsycINFO, PubMed and Scopus. Only published studies will be included in the SMSR. Data that answers the research questions will be extracted from the literature and recorded on the associated data charting form. A sequential synthesis method will be used to analyse data from qualitative, quantitative and mixed-method studies. Data will be presented graphically, diagrammatically or in tabular form depending on what approach best conveys its meaning. Ethics and dissemination The SMSR will describe the approach to developing new tools for screening the mental well-being of Indigenous peoples across the globe. It will support researchers, clinicians and practitioners to consider both their approach to new tool development or, if they are using a previously developed tool, how reliable and valid it is for the population that they intend to use it with. Peer-reviewed publications will be used to disseminate SMSR findings.
Preface to the JPCM special issue on physical and chemical properties of reducible oxides

The development of efficient functional materials for solar and chemical energy conversion and storage is extremely relevant to face the challenges posed by the environment and climate emergency. Reducible oxides are a class of compounds in which the cations can quickly and reversibly change their oxidation state, driving interesting physical and chemical properties, such as a remarkable activity for oxidation and reduction reactions, a high oxygen-ion conductivity and a high oxygen storage capacity. The electronic properties of these materials can be largely modified by, for example, defect engineering, playing with dimensionality and shape or coupling with metal atoms or nanoparticles, which lead to efficient electron transfer processes, and in turn to changes in oxygen vacancy formation energies and derived functionalities. Intensive research is being recently oriented towards investigating and tailoring the properties of such materials via an accurate atomic scale understanding, using advanced experimental and theoretical methods, which can drive a knowledge-based optimization of the functionalities. The special issue on ‘Physical and Chemical Properties of Reducible Oxides’ collects studies of systems based on reducible oxides in different forms, which point out the present experimental and theoretical challenges for the development and application of such materials. The most widely investigated reducible oxides are titanium (titania, TiO2) and cerium oxide (ceria, CeO2). Moreover, other transition metal oxides also in the form of more complex ternary oxides are a further subject of intense research in the field.
Small sensory spinal lesions that affect hand function in monkeys greatly alter primary afferent and motor neuron connections in the cord

Small sensory spinal injuries induce plasticity across the neuraxis, but little is understood about their effect on segmental connections or motor neuron (MN) function. Here, we begin to address this at two levels. First, we compared afferent input distributions from the skin and muscles of the digits with corresponding MN pools to determine their spatial relationship, in both the normal state and 4–6 months after a unilateral dorsal root/dorsal column lesion (DRL/DCL), affecting digits 1–3. Second, we looked at specific changes to MN inputs and membrane properties that likely impact functional recovery. Monkeys received a targeted unilateral DRL/DCL, and 4–6 months later, cholera toxin subunit B (CT‐B) was injected bilaterally into either the distal pads of digits 1–3, or related intrinsic hand muscles, to label inputs to the cord, and corresponding MNs. In controls (unlesioned side), cutaneous and proprioceptive afferents from digits 1–3 showed different distribution patterns but similar rostrocaudal spread within the dorsal horn from C1 to T2. In contrast, MNs were distributed across just two segments (C7–8). Following the lesion, sensory inputs were significantly diminished across all 10 segments, though this did not alter MN distributions. Afferent and monoamine inputs, as well as KCC2 cotransporters, were also significantly altered on the cell membrane of CT‐B labeled MNs postlesion. In contrast, inhibitory neurotransmission and perineuronal net integrity were not altered at this prechronic timepoint. Our findings indicate that even a small sensory injury can significantly impact sensory and motor spinal neurons and provide new insight into the complex process of recovery.