Miracle-dz/UniFAR-FTUs huggingface dataset:
Levels of Physical Activity in Children with Extremity Fractures a Dutch Observational Cross-Sectional Study

Background: Fractures are common in children and a frequent cause of emergency department (ED) visits. Fractures can cause long-term complications, such as growth problems. Research on fractures can reveal useful areas of focus for injury prevention. Objective: To assess the role of physical activity in the occurrence of fractures, this study investigates physical activity among children with extremity fractures based on the Global Recommendations on Physical Activity for Health. Methods: A multi-center, cross-sectional study was performed at two EDs in Nijmegen, the Netherlands. Patients between 4 and 18 years of age visiting these EDs with a fracture were asked to complete a validated questionnaire. Results: Of the 188 respondents, 51% were found to adhere to the recommendations. Among participants between 13 and 18 years of age, 43% were adequately physically active, compared to participants between 4 and 12 years of age among whom 56% were adequately physically active (p = 0.080). Additionally, more males were found to meet the recommendations (60% versus 40%). The most common traumas were sports-related (57%). Sports-related traumas were cited more often among youth between 13 and 18 years of age, compared to those between 4 and 12 (p < 0.001). Conclusions: A relatively high prevalence of adherence to the Global Recommendations on Physical Activity for Health was observed among children with fractures. Most respondents obtained their fractures during participation in sports. This study emphasizes the need for more injury prevention, especially among youth between 13 and 18 years of age and children participating in sports.
Synchronized Action Framework for Detection of Coordination on Social Media

The study of the coordinated manipulation of conversations on social media has become more prevalent as social media’s role in amplifying misinformation, hate, and polarization has come under greater scrutiny. We discuss how successful generalized coordination detection algorithms could be used to reinforce existing power imbalances, such as those between marginalized groups and government agencies. We propose an alternative method of identifying manipulation—detecting synchronized actions—which reduces this risk. We further consider how responsible coordination detection may be carried out by analyzing synchronized actions. We propose a synchronized action framework for detecting automated coordination by constructing and analyzing multi-view networks. We validate our framework by examining a large Twitter dataset surrounding the Reopen America conversation from 2020. We first discover three simple coordinated campaigns, and then investigate synchronized actions between users discussing the protests that could be consistent with covert coordination. This task is far more complex than examples evaluated in prior work, which demonstrates the need for our multi-view approach. Next, we identify a cluster of suspicious users and detail the activity of three members. These three users amplify protest messages using the same hashtags at very similar times, though they all focus on different states. This analysis highlights the potential usefulness of coordination detection algorithms in investigating amplification, as well as the need to carefully and responsibly deploy such tools.
Minimally Invasive Partial vs. Total Adrenalectomy for the Treatment of Unilateral Primary Aldosteronism: A Systematic Review and Meta-Analysis

Background: This systematic review and metanalysis was conducted to assess differences between perioperative and functional outcomes in patients undergoing minimally-invasive partial (mi-PA) and total adrenalectomy (mi-TA) for unilateral primary aldosteronism (uPHA). Material and Methods: Multiple scientific databases (PUBMED, Web of Science, and Cochrane Library) were searched up to November 2021 for surgical series comparing mi-PA vs. mi-TA for uPHA according to the PRISMA statement. Primary outcomes of interest were perioperative and functional outcomes. Results: Overall, a total of 802 patients from six eligible studies were identified, with mi-PA and mi-TA performed in 40.4% (n = 324) and 59.6% (n = 478) of cases, respectively. No differences were recorded between the two groups according to number of transfusions, EBL and Clavien–Dindo complications ≥2. Similarly, no differences in clinical success, persistence of postoperative hypokalemia and improvement in HTN were reported between mi-PA and mi-TA. Conclusions: In a uPHA setting, mi-PA and mi-TA provide comparable perioperative and functional outcomes despite the use of mi-PA remains limited to patients with small adenoma size, or hereditary/bilateral disease. Due to limited use of standardized reporting criteria in most of current series, the quest for a superiority of mi-PA over mi-TA in the treatment of uPHA still remains open.
The Index of Esophageal Cancer Related Ischemic Stroke: A Retrospective Patient Control Study

Purpose To investigate independent risk factors for esophageal cancer-related ischemic stroke (ECIS) and to use them to develop an index of ECIS to help clinicians identify patients at high risk for ECIS or to identify ECIS from other types of ischemic stroke. Methods We retrospectively enrolled active esophageal cancer (EC) patients with acute ischemic stroke (ECIS group) and patients with active EC without ischemic stroke (EC group), age- and sex-matched with ECIS patients, at seven centers from January 2011 to December 2020. Clinical data and laboratory and imaging findings were collected. Univariate and multivariate analyses were performed to analyze the independent risk factors for ECIS. Optimal cutoffs for sensitivities and specificities were obtained by Youden’s J statistic following a receiver operator characteristic (ROC) analysis of each risk factor and the product of the risk factors. Results A total of 91 ECIS patients and 91 EC patients were included. Elevated levels of carcinoembryonic antigen (CEA) [odds ratio (OR) = 0.105, 95% confidence interval (CI): 1.051–1.174, P < 0.001], D-dimer (DD) (OR = 0.003, 95% CI: 1.002–1.004, P < 0.001), and neutrophil count (OR = 0.857, 95% CI: 1.628–3.407, P < 0.001) were independent risk factors for ECIS. The area under the curve (AUC) of each independent risk factor and the product of the three independent risk factors were calculated by a receiver operator characteristic (ROC) curve, and the cutoff value from the largest AUC was called the ECIS index. Conclusion It was suggested that elevated plasma DD and CEA levels and increased neutrophils in EC patients may altogether contribute to the development of ECIS. The index of ECIS may facilitate clinicians to identify patients at high risk for ECIS or to identify ECIS from other etiologic types of ischemic stroke.
Signal Quality Investigation of a New Wearable Frontal Lobe EEG Device

The demand for non-laboratory and long-term EEG acquisition in scientific and clinical applications has put forward new requirements for wearable EEG devices. In this paper, a new wearable frontal EEG device called Mindeep was proposed. A signal quality study was then conducted, which included simulated signal tests and signal quality comparison experiments. Simulated signals with different frequencies and amplitudes were used to test the stability of Mindeep’s circuit, and the high correlation coefficients (>0.9) proved that Mindeep has a stable and reliable hardware circuit. The signal quality comparison experiment, between Mindeep and the gold standard device, Neuroscan, included three tasks: (1) resting; (2) auditory oddball; and (3) attention. In the resting state, the average normalized cross-correlation coefficients between EEG signals recorded by the two devices was around 0.72 ± 0.02, Berger effect was observed (p < 0.01), and the comparison results in the time and frequency domain illustrated the ability of Mindeep to record high-quality EEG signals. The significant differences between high tone and low tone in auditory event-related potential collected by Mindeep was observed in N2 and P2. The attention recognition accuracy of Mindeep achieved 71.12% and 74.76% based on EEG features and the XGBoost model in the two attention tasks, respectively, which were higher than that of Neuroscan (70.19% and 72.80%). The results validated the performance of Mindeep as a prefrontal EEG recording device, which has a wide range of potential applications in audiology, cognitive neuroscience, and daily requirements.
Soft Exoskeleton With Fully Actuated Thumb Movements for Grasping Assistance

It has been clinically proven that exoskeletons are effective self-training rehabilitation or daily living assistance devices for patients with hand dysfunctions. However, exoskeleton-assisted hand exercises with high degrees-of-freedom are considered as challenging tasks because the digit space, especially the thumb, cannot accommodate enough actuators. In this article, we report a tendon-driven soft hand exoskeleton with a hybrid configuration for thumb actuation. The soft hand exoskeleton system uses the least number of actuators to realize full degrees-of-freedom actuation for all digits. It is tested on a stroke patient with hemiplegia and a healthy subject. The experimental results show that the hand exoskeleton could assist the stroke patient to accomplish various training tasks, such as thumb encircling, grasping, pinching, releasing, and writing. It was found that digit trajectories and joint angle changes of the stroke patient were close to those of the healthy subject. Especially, the range of motion of the stroke patient shows significant improvement with the hand exoskeleton assistance compared to that without the hand exoskeleton assistance. The research in this article paves the way to develop fully actuated soft hand exoskeleton that can be eventually integrated with an electroencephalogram or electromyography for self-training rehabilitation or daily living assistance.
An investigation into the spectral parameters of ultra-low-frequency (ULF) waves in the polar caps and magnetotail

Abstract. The present case study is focused on fluctuations at ∼ 1.5 mHz observed on open field lines in both of the polar caps in ground-based geomagnetic data and in the electron concentration in the Northern Hemisphere ionosphere. Coherent pulsations with a relatively narrow narrowband-like spectra and a higher fraction of transversal components in the total spectral power are also observed by the Cluster satellites in the magnetotail magnetic field. Interestingly, the pulsations in the magnetotail started after pulsations over a similar frequency range observed in the solar wind dynamic pressure and interplanetary magnetic field (IMF) had been switched off. This suggests evidence of an internal resonant magnetotail mode which is normally masked by a higher-amplitude broadband ultra-low-frequency (ULF) “noise” of extra-magnetospheric origin.
Social constructionist and essentialist beliefs about gender and race

Social constructionist beliefs posit that sociocultural forces shape power-stratified social categories, whereas essentialist beliefs posit that social categories are defined by an immutable, natural essence shared by category members. Across three studies, we developed and validated the Social Constructionist and Essentialist Beliefs Scale (SCEBS) to assess the latent structure of ontological beliefs about two social categories: gender and race. In Study 1 (N = 598), we found a three-factor structure for SCEBS-Gender and SCEBS-Race, consisting of Social Constructionism, Essentialism, and Realism. In Study 2a (N = 300), we examined factor structure stability and criterion-related validity. We found incremental validity of SCEBS, and social constructionist beliefs particularly, for predicting modern sexism and symbolic racism beyond extant, essentialism-focused measures. In Study 2b (N = 218), we established 4-week test–retest reliability of SCEBS. Our research demonstrates the value of assessing both social constructionist and essentialist beliefs in the study of prejudice.
Flood Season Staging and Adjustment of Limited Water Level for a Multi-Purpose Reservoir

A reasonable flood season delineation can effectively implement staged reservoir scheduling and improve water resource efficiency. Therefore, this study is aimed at analyzing the flood period segmentation and optimizing the staged flood limit water levels (FLWLs) for a multi-purpose reservoir, the Longtan Reservoir, China. The rainfall seasonality index (SIP) and the runoff seasonality index (SIR) are used to evaluate the feasibility and rationality of the flood period staging. The fractal method is then used to segment the flood season. Finally, the design flood is carried out to optimize the staged FLWLs. The results show that the SI is an effective indicator for judging the feasibility and verifying the rationality of flood segmentation. The flood period can be segmented into the pre-flood season (12 April–29 May), the main flood season (30 May–3 September), and the post-flood season (4 September–9 November). The FLWLs in the main flood and the post-flood season can be raised by 2.05 m and 3.45 m, and the effective reservoir capacity is increased by 5.810 billion m3 and 6.337 billion m3, according to the results of the flood season division.
Automatic defect detection for ultrasonic wave propagation imaging method using spatio-temporal convolution neural networks

Ultrasonic wave propagation imaging enables the detection of anomalies in various structures; hence, it has been applied as one of the promising techniques for damage identification in structural health monitoring (SHM). The interpretation of imaging data is vital to SHM; however, it relies significantly on expert subjective judgment, rendering the results vulnerable to human errors. Recent advances in the field of computer vision arising from the adoption of deep neural networks have resulted in new perspectives for substituting human roles in laborious data interpretation tasks. This paper presents an effective learning architecture that can characterize the ultrasonic wave propagation videos for automatic non-destructive inspection. The main contribution is threefold: 1. To the best of our knowledge, this is the first study to leverage video content analysis techniques to exploit ultrasonic wave propagation image series. Previous approaches that focused on the still wavefield images are likely to lose critical temporal information, thereby resulting in an inferior performance. 2. We devise a model that progressively aggregates both temporal and spatial information encoded in multiple adjacent snapshots of ultrasonic wave propagation motions for efficient data analysis. We presented the details regarding the system implementation and critical parameter settings. 3. The proposed approach is validated through extensive experimental comparisons with other state-of-the-art computer vision techniques on a real dataset which is publicly available. We hope that this study will encourage further investigations into video-based non-destructive data interpretation, not limited to ultrasonic signals.
Osseointegration at Implants Installed in Composite Bone: A Randomized Clinical Trial on Sinus Floor Elevation

Osseointegration of implants installed in conjunction with sinus floor elevation might be affected by the presence of residual graft. The implant surface characteristics and the protection of the access window using a collagen membrane might influence the osseointegration. To evaluate these factors, sinus floor elevation was performed in patients using a natural bovine bone grafting material. The access windows were either covered with a collagen membrane made of porcine corium (Mb group) or left uncovered (No-Mb group) and, after six months, two mini-implants with either a moderate rough or turned surfaces were installed. After 3 months, biopsies containing the mini-implants were retrieved, processed histologically, and analyzed. Twenty patients, ten in each group, were included in the study. The two mini-implants were retrieved from fourteen patients, six belonging to the Mb group, and eight to the No-Mb group. No statistically significant differences were found in osseointegration between groups. However, statistically significant differences were found between the two surfaces. It was concluded that implants with a moderately rough surface installed in a composite bone presented much higher osseointegration compared to those with a turned surface. The present study failed to show an effect of the use of a collagen membrane on the access window.
Identification of Pseudomonas aeruginosa strains isolated from Dorper sheep milk with subclinical-mastitis infection by uniplex PCR using 16S rRNA, lasI/R, gyrB and ecfX genes

Pseudomonas aeruginosa is an opportunistic and versatile pathogenic bacterium that can adapt in various environmental condition, which play a role in multiple virulence factor and resistance to antibiotics. Moreover, molecular identification techniques using single target gene is more susceptible to error and false positive. Thus, the detection of this strain with high specificity and sensitivity is crucial in order to control this pathogenic bacterium. The aim of this study was to evaluate six bacteria strains (13-1, 66-1, 00-1, 46-1, 10-R and 67-1) isolated from Dorper sheep milk and two P. aeruginosa ATCC strains (ATCC BAA-2108 and ATCC27853) for prompt identification of the strains based on uniplex polymerase chain reaction which targeting PA-SS, PA-GS, lasI/R, gyrB and ecfX genes. In the present study, the Dorper sheep milk’s samples (n = 32) were collected and tested with California mastitis test (CMT). Out of 32 milk’s samples, six of the samples were detected with strong mastitis, and thus were continued with inoculation process on selective media Pseudomonas Agar P (for pyocyanin) or F (fluorescein) and MacConkey agar for differentiation. After extraction of the bacteria chromosomal DNA, uniplex PCR amplification were carried out by using 16S rRNA (PA-SS and PA-GS) primers and specific P. aeruginosa genes (lasI/R, gyrB and ecfX) primers. The specificity of the primers was also examined by non-Pseudomonas species as a control for data comparison. Sequence analysis has revealed that six of the isolated samples were confirmed as P. aeruginosa strains with the respective genes sequence confirmed by BLAST and Clustal Omega. From this study, lasI/R, gyrB and ecfX were highly reliable primers with the percentage of identification of more than 95.0% as compared to PA-SS and PA-GS which were less than 90.0%. This study concludes that highly specific and sensitive assay has been developed using lasI/R, gyrB and ecfX targeted genes for the detection of P. aeruginosa strains isolated from fresh sheep milk samples.
Stock Trading Strategies Based on Deep Reinforcement Learning

The purpose of stock market investment is to obtain more profits. In recent years, an increasing number of researchers have tried to implement stock trading based on machine learning. Facing the complex stock market, how to obtain effective information from multisource data and implement dynamic trading strategies is difficult. To solve these problems, this study proposes a new deep reinforcement learning model to implement stock trading, analyzes the stock market through stock data, technical indicators and candlestick charts, and learns dynamic trading strategies. Fusing the features of different data sources extracted by the deep neural network as the state of the stock market, the agent in reinforcement learning makes trading decisions on this basis. Experiments on the Chinese stock market dataset and the S&P 500 stock market dataset show that our trading strategy can obtain higher profits compared with other trading strategies.
HP‐SPC algorithm with dynamic partially connected structure for mmWave MIMO systems

This article proposes a low complexity hybrid precoding algorithm for the switch network‐based dynamic partially connected (SPC) structure, that is, named as HP‐SPC algorithm. First, via a new defined effective optimal precoding matrix, the analog switch precoding matrix optimization problem is transformed into a sparse representation problem. Thus, invoking that the key characteristic of only one nonzero entry in each row of the analog dynamic switch precoding matrix, the analog dynamic switch precoding matrix can be accurately and effectively solved. Second, the digital precoding matrix optimization problem is modeled as a dictionary update problem by the defined effective optimal precoding matrix and the combining matrix. Further, the digital precoding matrix is easily optimized based on the defined effective optimal precoding matrix, since the measurement vectors are sparsely represented by a single dictionary atom. Third, the analog phase shifter precoding matrix is given by the phase rotation method. Finally, the precoding matrices are alternant updated until convergence, a near optimal solution of the precoding matrix is obtained. Compared with the previous works, the proposed HP‐SPC algorithm provides better hybrid precoding performance, for examples: (1) it avoids complexity computation such as matrix inversion and singular value decomposition, so that it presents a low computational complexity; (2) it has a favorable property of convergence since a stable point can be reached with about 10 loop iterations. Based on the simulation results, the effectiveness of HP‐SPC algorithm is further demonstrated.
The Reproductive Performance of Ongole Grade Cows at Smallholder Farmer with Different Housing Systems

Ongole grade (OG) cows are mostly kept at the smallholder farmer level, carried out traditionally for instance, on the cow's housing system, using individual tie-stall (ITS), or communal tie-stall (CTS) system. The housing system can affect the reproductive performance of the cows. This study aims to determine the better type of housing to be applied at the smallholder farmer level based on reproductive performance. Forty-three OG cows were divided into the ITS (n=20 cows) and CTS (n=23 cows) systems. Post-partum estrus (PPE), post-partum mating (PPM), weaning age (WA), service per conception (S/C), calving interval (CI), and calf crop (CC) as reproductive performance indicator were collected through farmer recording, then were analyzed using the independent sample t-test. The results showed that the type of communal tie-stall was significantly better on S/C, WA, CI, and CC. In conclusion, using a communal tie-stall housing system was better for OG cow's reproductive performance.
Pyk2 Regulates MAMs and Mitochondrial Dynamics in Hippocampal Neurons

Pyk2 is a non-receptor tyrosine kinase enriched in hippocampal neurons, which can be activated by calcium-dependent mechanisms. In neurons, Pyk2 is mostly localised in the cytosol and dendritic shafts but can translocate to spines and/or to the nucleus. Here, we explore the function of a new localisation of Pyk2 in mitochondria-associated membranes (MAMs), a subdomain of ER-mitochondria surface that acts as a signalling hub in calcium regulation. To test the role of Pyk2 in MAMs’ calcium transport, we used full Pyk2 knockout mice (Pyk2−/−) for in vivo and in vitro studies. Here we report that Pyk2−/− hippocampal neurons present increased ER-mitochondrial contacts along with defective calcium homeostasis. We also show how the absence of Pyk2 modulates mitochondrial dynamics and morphology. Taken all together, our results point out that Pyk2 could be highly relevant in the modulation of ER-mitochondria calcium efflux, affecting in turn mitochondrial function.