Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluid intake, hydration status and body mass changes in U-15 judo athletes during a training day

Despite numerous studies related to dehydration there is still a lack of scientific literature presenting hydration status and fluid intake of judo athletes during different periods. Therefore, the aim of this study was to investigate, fluid intake, hydration status and body weight changes of young judo athletes during a typical day of training in preparation period. Twenty-two young judo athletes (age: 12 ± 0.7 y, experience: 3.5 ± 1.1) voluntarily participated in this study. Hydration status and weight were examined in the morning, before and immediately after the training. All athletes trained 90 min and they consumed fluids ad libitum during the exercise. According to morning urine specific gravity (USG) values, 81.2% of the athletes were dehydrated while only 18.8% of the athletes were euhydrated. Pre-training urine measurements showed that 63.64% of the athletes presented dehydration and 77.27% of the athletes completed the training in dehydrated condition despite fluid availability during the training. Mean body weight loss during training was -0.64 ± 0.66%. It can be concluded that young judo athletes presented high prevalence of dehydration as indicated by USG values. Most of the athletes were dehydrated during a typical training day and completed the training in more dehydrated conditions compared to pre training values despite ad libitum fluid intake. It is of great importance to evaluate hydration status of the athletes before training to refrain from common practice of fluid restriction for weight loss and adverse effects of a persistent state of fluid deficit on physical and health related state.
Inactivation of Polymicrobial Biofilms of Foodborne Pathogens Using Epsilon Poly-L-Lysin Conjugated Chitosan Nanoparticles

A mixed culture (polymicrobial) biofilm provides a favorable environment for pathogens to persist in the food processing environment and to contaminate food products. Inactivation and eradication of such biofilms from food processing environments are achieved by using harsh disinfectants, but their toxicity and environmentally hostile characteristics are unsustainable. This study aims to use food-grade natural nanoparticulated antimicrobials to control mixed-culture biofilms. Chitosan, a natural broad-spectrum antimicrobial biopolymer (polysaccharide) from crustaceans, was derivatized to produce chitosan nanoparticles (ChNP) as a carrier for another broad-spectrum antimicrobial agent, ε-poly-L-lysine (PL), to synthesize ChNP-PL conjugate. The antimicrobial activity of ChNP and ChNP-PL was tested against mixed-culture biofilms. ChNP-PL (~100 nm) exhibited a synergistic antimicrobial and anti-biofilm effect against mono or mixed-culture biofilms of five foodborne pathogens, including Listeria monocytogenes, Staphylococcus aureus, Salmonella enterica serovar Enteritidis, Escherichia coli O157:H7, and Pseudomonas aeruginosa. ChNP-PL treatment prevented biofilm formation by mono or mixed cultures of L. monocytogenes, P. aeruginosa, and E. coli O157:H7, and bacterial counts were either below the detection limit or caused 3.5–5 log reduction. ChNP-PL also inactivated preformed biofilms. In monoculture biofilm, ChNP-PL treatment reduced L. monocytogenes counts by 4.5 logs, S. Enteritidis by 2 logs, E. coli by 2 logs, and S. aureus by 0.5 logs, while ChNP-PL had no inhibitory effect on P. aeruginosa. In vitro mammalian cell-based cytotoxicity analysis confirmed ChNP-PL to have no deleterious effect on intestinal HCT-8 cell line. In conclusion, our results show ChNP-PL has strong potential to prevent the formation or inactivation of preformed polymicrobial biofilms of foodborne pathogens.
Derivation of High-Resolution Meteorological Parameters for Use in Airport Wind Shear Now-Casting Applications

Methods for now-casting adverse weather conditions with the potential to cause disruption to aircraft landings often make use of real-time measurements at high temporal resolution. This paper describes processing methodologies developed to derive meteorological parameters from such measurements recorded in the vicinity of Hong Kong International Airport, specifically a radiometer in King’s Park, a wind profiler and surface anemometer on Cheung Chau Island and weather buoys in the Pearl River estuary. These parameters are suitable for use as input to a now-casting application of the computationally efficient airflow model, FLOWSTAR, which has previously been shown to predict mountain waves generated by flow over Lantau Island to the southeast of the airport. Radiosonde data from King’s Park have been used to test the radiometer processing method; the novel approach of using minimum and maximum potential temperature deviations from a series of height-dependent linear profiles to derive radiometer inversion layer parameters generates data that compares well with values derived from corresponding radiosonde profiles. Mountain wave strength depends on the magnitude of wind speed in the inversion layer; wind profiler data can be used to estimate typical and maximum wind speeds and associated wind directions using estimates of inversion layer depth derived from the radiometer data. With estimates of surface sensible heat flux appropriate for the airport’s coastal location calculated using a marine boundary layer scheme, a dataset of meteorological parameters at 20-min resolution has been derived for input into the FLOWSTAR model. The combination of automated meteorological data processing methods and flow field modelling has the potential to form part of a now-casting system for determining strong wind shear conditions at the airport.
Prevalence of Diabetes Insipidus and Other Complications in Early Period After Pituitary Surgery: Analysis of 259 Patients

Eugeniya Galina Moisak. Prevalence of Diabetes Insipidus and Other Complications in Early Period After Pituitary Surgery: Analysis of 259 Patients. Biomed The purpose of this study was to describe complications associated with the endoscopic transsphenoidal approach and to determine a relation between postoperative central diabetes insipidus (DI) and the characteristics of adenomas. Methods: Results:
Daily dynamics of grandiose narcissism: distribution, stability, and trait relations of admiration and rivalry states and state contingencies

On the basis of the Narcissistic Admiration and Rivalry Concept and recent theories on narcissistic pursuit of status, we provide a differentiated analysis of individual differences in the within-person dynamics of grandiose narcissism. In two daily diary studies (Sample 1: 56 days; Sample 2: 82 days; total participants: N = 198; total observations: N = 12,404), we investigated the degree, stability, and trait correlates of individual differences in average narcissism-relevant states (perceived status success, perceived admiration and rejection, positive and negative affect, and assertive and hostile behavior) as well as individual differences in within-person contingencies between these states. The results indicated substantial and stable between-person differences in averaged states that were related to their corresponding narcissism trait self-reports. State contingencies showed substantial strength, significant interindividual differences, and stability across the 56 and 82 days, respectively. We only found weak support for associations between state contingencies and trait narcissism self-reports. These findings support a differentiated approach to the conceptualization and assessment of grandiose state narcissism and call for even more comprehensive and fine-grained investigations.
Methodology to Differentiate Legume Species in Intercropping Agroecosystems Based on UAV with RGB Camera

Mixed crops are one of the fundamental pillars of agroecological practices. Row intercropping is one of the mixed cropping options based on the combination of two or more species to reduce their impacts. Nonetheless, from a monitoring perspective, the coexistence of different species with different characteristics complicates some processes, requiring a series of adaptations. This article presents the initial development of a procedure that differentiates between chickpea, lentil, and ervil in an intercropping agroecosystem. The images have been taken with a drone at the height of 12 and 16 m and include the three crops in the same photograph. The Vegetation Index and Soil Index are used and combined. After generating the index, aggregation techniques are used to minimize false positives and false negatives. Our results indicate that it is possible to differentiate between the three crops, with the difference between the chickpea and the other two legume species clearer than that between the lentil and the ervil in images gathered at 16 m. The accuracy of the proposed methodology is 95% for chickpea recognition, 86% for lentils, and 60% for ervil. This methodology can be adapted to be applied in other crop combinations to improve the detection of abnormal plant vigour in intercropping agroecosystems.
A Content Analysis of Empirical Parent Engagement Literature

ABSTRACT Early intervention in child mental health is crucial due to the potential for adverse life outcomes when not treated early in development. Parent engagement primarily determines whether a child will attend mental health services until successful completion. Our content analysis explored empirical research studies of parent engagement interventions in child mental health services to address gaps in the current literature. We synthesized the trends and common themes across parent engagement practices to provide implications for the counseling field and recommend future research.
LSTMSPLIT: Effective SPLIT Learning based LSTM on Sequential Time-Series Data

Federated learning (FL) and split learning (SL) are the two popular distributed machine learning (ML) approaches that provide some data privacy protection mechanisms. In the time-series classification problem, many researchers typically use 1D convolutional neural networks (1DCNNs) based on the SL approach with a single client to reduce the computational overhead at the client-side while still preserving data privacy. Another method, recurrent neural network (RNN), is utilized on sequentially partitioned data where segments of multiple-segment sequential data are distributed across various clients. However, to the best of our knowledge, it is still not much work done in SL with long short-term memory (LSTM) network, even the LSTM network is practically effective in processing time-series data. In this work, we propose a new approach, LSTMSPLIT, that uses SL architecture with an LSTM network to classify time-series data with multiple clients. The differential privacy (DP) is applied to solve the data privacy leakage. The proposed method, LSTMSPLIT, has achieved better or reasonable accuracy compared to the Split-1DCNN method using the electrocardiogram dataset and the human activity recognition dataset. Furthermore, the proposed method, LSTMSPLIT, can also achieve good accuracy after applying differential privacy to preserve the user privacy of the cut layer of the LSTMSPLIT.
A 30‐year systematic review reveals success in tephritid fruit fly biological control research

Fruit flies (Diptera: Tephritidae) are among the main pests in horticulture, impacting field crops and export markets. The biological control of fruit flies has become an important method for environmentally friendly crop production. Although biological control is an age‐old practice and the mass‐rearing of some biological agents boomed in the 1990s, efforts in fruit fly control programs still face several challenges. We conducted a systematic review to investigate publications assessing the success or failure of using natural enemies against tephritid fruit flies. Our goal was to compile and summarize information from over 30 years of research on biocontrol efforts, including groups and species of control agents and fruit flies tested, methodological approaches applied, the country where the study was performed, and the scope adopted. We also analyzed effectiveness, efficiency, and success rates in biocontrol studies published from 1990 to 2021. Our review showed 2986 records, of which 225 publications matched the criteria. The most‐studied biocontrol agents for the suppression of fruit flies were parasitoids, fungi, and nematodes. A few studies assessed bacteria, predators, and viruses. We found a total of 55 fruit fly species described as hosts of the biological agents. Natural/conservation biological control was the main scope studied; however, augmentative biological control had a higher rate of successful studies and potential success, followed by classical biological control. The effectiveness and efficiency parameters are discussed to provide support for researchers in future studies.
Fault diagnosis approach based on hidden Markov model and support vector machine

Aiming at solving the problems of machine-learning in fault diagnosis,a diagnosis ap- proach is proposed based on hidden Markov model(HMM)and support vector machine(SVM). HMM usually describes intra-class measure well and is good at dealing with continuous dynamic signals.SVM expresses inter-class difference effectively and has perfect classify ability.This ap- proach is built on the merit of HMM and SVM.Then,the experiment is made in the transmission system of a helicopter.With the features extracted from vibration signals in gearbox,this HMM-SVM based diagnostic approach is trained and used to monitor and diagnose the gearbox's faults.The result shows that this method is better than HMM-based and SVM-based diagnosing methods in higher diagnostic accuracy with small training samples.
Intelligent reflecting surface‐assisted terahertz communication towards B5G and 6G: State‐of‐the‐art

After the deployment of 5th generation (5G), the beyond 5G (B5G) and 6th generation (6G) communication grabs the critical attention of academia and researchers. In ongoing cellular generation, the selected radio spectrum (i.e., millimeter waves [mm‐Wave]) is unable to achieve the required data rates. Future cellular generations need more data rate and link reliability to serve emerging intelligent applications of B5G and 6G (e.g., autonomous driving, virtual reality, etc.). To handle these limitations of ongoing cellular generation, the researchers are working on key factors to have a smart, high capacity and ultra‐reliable propagation environment. To increase the data rate of the B5G and 6G network systems, the terahertz (THz) band is selected. However, to increase link reliability, the intelligent reflecting surfaces (IRSs) have a crucial impact on wireless network environments. Immense work has been done on the performance analysis of IRS‐assisted wireless communication networks. This treatise imposes a comparison of such IRS‐assisted THz communication systems, and future promising applications.
Performance Analysis of Smart Antenna Array with Mono-and Dual-polarization in TD-LTE System

The performance of TD-LTE system with dual-polarized smart antenna array is investigated.Firstly the beamforming gain depending on the singular value of the channel matrix is analyzed and then calculated for the mono-and dual-polarized smart antenna systems.At last the performance of the TD-LTE systems with mono-and dual-polarized smart antenna is evaluated by Monte Carlo simulation method.Both the analysis and the simulation show that the dual-polarized smart antenna pays a little penalty of slight block error ratio(BLER) loss for great decrease of antenna size and facilitation of the application of antenna array.
Critical Evaluation of Current Hypotheses for the Pathogenesis of Hypertrophic Cardiomyopathy

Hereditary hypertrophic cardiomyopathy (HCM), due to mutations in sarcomere proteins, occurs in more than 1/500 individuals and is the leading cause of sudden cardiac death in young people. The clinical course exhibits appreciable variability. However, typically, heart morphology and function are normal at birth, with pathological remodeling developing over years to decades, leading to a phenotype characterized by asymmetric ventricular hypertrophy, scattered fibrosis and myofibrillar/cellular disarray with ultimate mechanical heart failure and/or severe arrhythmias. The identity of the primary mutation-induced changes in sarcomere function and how they trigger debilitating remodeling are poorly understood. Support for the importance of mutation-induced hypercontractility, e.g., increased calcium sensitivity and/or increased power output, has been strengthened in recent years. However, other ideas that mutation-induced hypocontractility or non-uniformities with contractile instabilities, instead, constitute primary triggers cannot yet be discarded. Here, we review evidence for and criticism against the mentioned hypotheses. In this process, we find support for previous ideas that inefficient energy usage and a blunted Frank–Starling mechanism have central roles in pathogenesis, although presumably representing effects secondary to the primary mutation-induced changes. While first trying to reconcile apparently diverging evidence for the different hypotheses in one unified model, we also identify key remaining questions and suggest how experimental systems that are built around isolated primarily expressed proteins could be useful.
The Functional Interactions between Cortical Regions through Theta-Gamma Coupling during Resting-State and a Visual Working Memory Task

Theta phase-gamma amplitude coupling (TGC) plays an important role in several different cognitive processes. Although spontaneous brain activity at the resting state is crucial in preparing for cognitive performance, the functional role of resting-state TGC remains unclear. To investigate the role of resting-state TGC, electroencephalogram recordings were obtained for 56 healthy volunteers while they were in the resting state, with their eyes closed, and then when they were engaged in a retention interval period in the visual memory task. The TGCs of the two different conditions were calculated and compared. The results indicated that the modulation index of TGC during the retention interval of the visual working memory (VWM) task was not higher than that during the resting state; however, the topographical distribution of TGC during the resting state was negatively correlated with TGC during VWM task at the local level. The topographical distribution of TGC during the resting state was negatively correlated with TGC coordinates’ engagement of brain areas in local and large-scale networks and during task performance at the local level. These findings support the view that TGC reflects information-processing and signal interaction across distant brain areas. These results demonstrate that TGC could explain the efficiency of competing brain networks.
Evaluation and Quantification of Resistant Gene in Antibiotic Resistant ESBL Producing E. coli in UTI Samples with Diabetes Mellitus: A Molecular Study

In diabetic patients, urinary tract infections (UTIs) are more common and severe often caused by antibiotic resistance and carry worse consequences, due to high blood sugar level and frequent urination. High blood sugar provides favorable environment for the growth of pathogens and some other impairment in immune system, poor metabolic control and incomplete emptying bladder to enhance the risk of UTIs in the diabetic patients. Most of the UTIs are caused by multidrug resistant, Extended Spectrum β lactamase (ESBL) producing bacteria mostly, Escherichiacoli (E. coli). The prevalence of UTIs caused by ESBL producing Multidrug Resistant (MDR) bacteria is a major global public health concern. The aim of this study was to identify the pattern of multidrug resistance and quantification of resistance genes amongst the E. coli isolates which were obtained from UTI patients with diabetes. ESBL producing stains were found 36% by using amoxicillin/clavulanic acid as a β lactamase inhibitor. Out of these stains, following antibiotics resistance rates were achieved with ampicillin, amoxicillin, amikacin, cefotaxime, ceftazidime, chloramphenicol, ciproﬂoxacin, gentamicin, nitrofurantoin, norfloxacin, tetracycline and amoxicillin/clavulanic acid as 100%, and 0%, respectively. The ESBL encoding genes were characterized for CTX-M, TEM and SHV genes. CTX-M gene was found to have resistance in the E. coli isolates, some others genes as TEM and SHV respectively. These characterized genes were analyzed through PCR which is a rapid, sensitive and easy to interpret detection method. Among these isolates, CTX-M was significantly higher 85.4% in the ESBL positive strains (p < 0.05). TEM and SHV were found 12.8% and 6.5%, respectively. Early and proper diagnosis is necessary for the management of UTIs in diabetic patients in order to have an adequate treatment.
"Ethical and Regulatory Issues in Genetic Research Collaboration between Global Pharmaceutical Industry and Low- and Middle-income Countries"

Background:The global pharmaceutical industry (big pharma) is responsible for production, and distribution of drugs. Big pharma revenues have been growing markedly totaling about 1.27 trillion U.S. dollars in 2020. Low- and middle-income countries spend only 1.46% of their Gross Domestic Products (GDP) on research and development necessitating collaboration with big pharma. Genetic research require access to sophisticated laboratories, large-scale genotyping facilities, bioinformatics and statistical expertise which cannot be afforded by low or middle-income countries. Consequently, most of the genetic research is conducted in high-income countries and big pharma. Main body: This paper has three aims: the first aim is to identify ethical and regulatory issues related to genetic research collaboration of big Pharma with low and middle-income countries. The second aim is to explain the impact of non-collaboration of big pharma with low and middle-income countries. The third aim is to propose a future ethical and regulatory framework for genetic research of big pharma with low- and middle-income countries. To accomplish these aims the big pharma revenue and spending was outlined, the necessity of genetic collaboration was highlighted and the resultant ethical and regulatory gaps were elaborated. The COVID-19 mRNA vaccine was mentioned as an illustration for non-collaboration. Then a future ethical and regulatory framework for genetic research of big pharma with low- and middle-income countries at the international, national and research ethics committee levels was proposed.Conclusion:This paper identified several ethical and regulatory issues related to genetic research collaboration and non-collaboration of big Pharma with low and middle-income countries followed by proposing a future ethical and regulatory framework for collaboration at the international, national and research ethics committee levels.
Simulation and Improvement of the Efficiency of the CFTS Solar Cell Using SCAPS-1D

A simulation of the AZO/i-ZnO/CdS/CFTS solar cell was carried out using SCAPS software. The results were obtained (Voc=0.55 V, Jsc=6.2 mA/cm2, FF=39 %, ɳ=1.35 %). Simulation results were compared with experimental research and we got convergence in the results (Voc=0.56 V, Jsc=6.5 mA/cm2, FF=37 %, ɳ=1.37 %). The simulated solar cell is improved by increasing the doping concentration and thickness of the buffer and absorption layers. The efficiency of the solar cell was improved to ɳ=4.29%, fill factor FF=52.92%, open circuit voltage Voc=0.74 V and short circuit current Jsc=10.8 mA/cm2