Miracle-dz/UniFAR-FTUs huggingface dataset:
Residual force enhancement within the human quadriceps is greatest during submaximal stretch-hold contractions at a very long muscle length

Little is known about how muscle length affects residual force enhancement (rFE) in humans. We therefore investigated rFE at short, long, and very long muscle lengths within the human quadriceps and patellar tendon (PT) using conventional dynamometry with motion capture (rFETQ) and a new, non-invasive shear-wave tensiometry technique (rFEWS). Eleven healthy male participants performed submaximal (50% max.) EMG-matched fixed-end reference and stretch-hold contractions across these muscle lengths while muscle fascicle length changes of the vastus lateralis (VL) were captured using B-mode ultrasound. We found significant rFETQ at long (7±5%) and very long (12±8%) but not short (2±5%) muscle lengths, whereas rFEWS was only significant at the very long (38±27%), but not short (8±12%) or long (6±10%) muscle lengths. We also found significant relationships between VL fascicle length and rFETQ (r=0.63, p=.001) and rFEWS (r=0.52, p=.017), but relationships were not significant between VL fascicle stretch amplitude and rFETQ (r=0.33, p=.126) or rFEWS (r=0.29, p=.201). PT shear-wave speed-angle relationships did not agree with estimated quadriceps muscle force-angle relationships, which indicates that estimating PT loads from shear-wave tensiometry might be inaccurate. We conclude that increasing muscle length rather than stretch amplitude contributes more to rFE during submaximal voluntary contractions of the human quadriceps.
Multi-stage RGB-based Transfer Learning Pipeline for Hand Activity Recognition

First-person hand activity recognition is a challenging task, especially when not enough data are available. In this paper, we tackle this challenge by proposing a new low-cost multi-stage learning pipeline for firstperson RGB-based hand activity recognition on a limited amount of data. For a given RGB image activity sequence, in the first stage, the regions of interest are extracted using a pre-trained neural network (NN). Then, in the second stage, high-level spatial features are extracted using pre-trained deep NN. In the third stage, the temporal dependencies are learned. Finally, in the last stage, a hand activity sequence classifier is learned, using a post-fusion strategy, which is applied to the previously learned temporal dependencies. The experiments evaluated on two real-world data sets shows that our pipeline achieves the state-of-the-art. Moreover, it shows that the proposed pipeline achieves good results on limited data.
Knowledge, Attitude and Practices (KAP) About Coronavirus SARS-CoV-2 among the General Public

Background: A Knowledge, Attitude and Practices (KAP) survey is a quantitative method (predefined questions formatted in standardized questionnaires) that provides qualitative and quantitative information. Measure the extent of a known situation; provides new tangents of a situations reality This has resulted in the public becoming more cautious, thereby minimizing the transmission of the disease to a certain level. Introduction: COVID-19 (COVID-19 is disease caused by a new strain of Coronavirus. ’CO’ stands for corona, ’VI’ for virus, and ‘D’ for disease. the most common symptoms which appear 2-14 days after exposure [1].Headache, abdominal pain, diarrhea, sore throat and muscle weakness are some of the less common symptoms experienced by some people, while some others may not develop any symptoms until later. This study is conducted to understand the extent of awareness among the general public and the importance of preventing the spread of Coronavirus infection in the community. An online questionnaire survey is conducted consisting the essential parameters about the important aspects of disease spread. Objective: To assess Coronavirus awareness among people. To understand the attitude of people towards Coronavirus Results: A total number of 564 participants took part In this study during the study period of 6months. Among which 325 were male and 239 were female. The male participants compromised the majority percentage (57%) of the total number of participants while the female participants comprised only (42.4%) of the participants. The result showed a significant correlation between female gender, higher age, and higher education, with knowledge, attitude, and practice. Conclusion: To adhere to the guidelines released by the Government and the guidelines provided by the WHO have played an extremely vital role in improving the knowledge and awareness among the general population which in turn brought positive effects in people’s attitude and practices towards Coronavirus since the WHO’s declaration of Coronavirus as a pandemic. This has resulted in the public becoming more cautious, thereby minimizing the transmission of the disease to a certain level. Several public health measures which are now being implemented around the world will hopefully diminish the spread of the virus while safe and effective treatments and vaccines are being developed to terminate it.
Suicidal behaviour in Aboriginal and non-Aboriginal young men under custodial youth justice supervision: understanding the role of adverse childhood experiences

This study examined the association between adverse childhood experiences (ACEs) and suicidal behaviour in a sample of 1726 young men in an Australian youth justice detention population. Nine ACEs, including child abuse and parental risk factors, were examined. Analyses focused on whether ACEs were associated with suicidal ideation and attempts after controlling for other known correlates including substance use, aggression and out-of-home care exposure. Aboriginal and Torres Strait Islander young men were found to have a higher prevalence and a higher average score of ACEs, but differed very little in relation to reported suicidal behaviour. Higher ACEs scores and specific maltreatment types (i.e. physical and sexual abuse) were positively associated with suicidal behaviour. This relationship was attenuated after controlling for established correlates of suicidal behaviour. The findings underscored the importance of understanding ACEs as major risk factors for suicide in youth justice populations and the need for effective prevention measures.
High-Risk Encounters: Primary Care Experiences of Women Living with Intimate Partner Violence, and Implications for the Patient Centered Medical Home

ABSTRACT Women experiencing intimate partner violence (IPV) often face stigma, uncertainty, and complex emotions when deciding to disclose IPV to primary care providers. As the Patient Centered Medical Home (PCMH) model’s general assumptions and value have been more widely accepted, interest has grown in understanding how well it serves different populations. We interviewed 50 women who had experienced prior-year IPV and received care from 2 Veterans Health Administration (VA) facilities, to explore their health care needs Disclosure of IPV status was revealed as a high-risk moment in medical care for many participants, yet nearly all supported clinical screening and described or envisioned patient-centered screening practices. The PCMH’s interprofessional team-based care model offers strengths for connecting women to services and support. However, if women do not experience trust, genuine care, and respect for their autonomy, they are unlikely to disclose IPV or access extended services. The PCMH model holds intrinsic promise but may fall short in delivering on relational aspects of patient-centered care desired by women experiencing IPV (and possibly others facing similar complex, stigmatized challenges). IPV screening practices should aim to empower the entire care team to be able to build the trusting relationships that open the door to discussions of IPV.
Sensor Fault Detection Combined Data Quality Optimization of Energy System for Energy Saving and Emission Reduction

China’s “dual carbon” goals, energy conservation and emission reduction in the energy system, have become increasingly important. The sensor fault of an energy system will cause unstable operation and increase energy consumption. Therefore, this study proposes a new sensor fault detection strategy based on the data driven method for energy saving and emission reduction. However, for data-driven models, data quality has a greater impact on model performance. This study innovatively uses five machine learning methods to optimize the energy system operating data. Five machine learning methods include the moving average (MA), Lowess, Loess, Rlowess and Rloess methods. Fault detection performances of different data driven models optimized by different approaches are compared and analyzed. Besides, data outliers and parameter selection of data optimization methods are discussed. The results indicate that the MA method has the best optimization performance when the smoothness degree is level 2. The optimized data fluctuation range is controlled within the range of ±1. The fault detection accuracy rate of the model optimized based on the MA method is increased from 32.51% to 83.96% when the evaporation temperature sensor fault is a 5 °C deviation. However, the data will deviate from the original data trend when the smoothing parameter is set too large. Therefore, the smoothness of the data should not be too large. The approach proposed in this study is of great significance to the energy saving and emission reduction of the energy system.
Optimization of Route Planning for Dynamic Environments using Swarm Intelligence

Environments for algorithms can be categorized as static or dynamic.A static environment remains stationary throughout the execution of the algorithm, while in a dynamic environment the environment changes during the execution of the algorithm.The algorithms for planning in static and dynamic environments can be divided into offline and online algorithms.This research implements an online algorithm for an unknown environment and combined exploration and planning in a hybrid architecture. A simulated system of agents based on swarm intelligence is presented for route optimization and exploration.Two versions of the system are implemented and compared for performance- i.e., a simulated ant agent system and a simulated niche based particle swarm optimization. A simulated ant agent system is presented to address the issues involved during route planning in dynamic and unknown environments cluttered with obstacles and objects. A simulated ant agent system (SAAS) is proposed using a modified ant colony optimization algorithm for dealing with online route planning. The SAAS generates and optimizes routes in complex and large environments with constraints.The traditional route optimization techniques focus on good solutions only and do not exploit the solution space completely. The SAAS is shown to be an efficient technique for providing safe, short, and feasible routes under dynamic constraints, and its efficiency has been tested in a mine field simulation with different environment configurations.It is capable of tracking a stationary as well as a non-stationary goal and performs equally well as compared to moving target search algorithm. Route planning for dynamic environment is further extended by using another optimization technique for generation of multiple routes.Simulated niche based particle swarm has been used for dynamic online route planning, optimization of the routes, and it has proved to be an effective technique. It efficiently deals with route planning in dynamic and unknown environments cluttered with obstacles and objects.A simulated niche based particle swarm optimization (SN-PSO) is proposed using a modified particle swarm optimization algorithm for dealing with online route planning. The SN-PSO generates and optimizes multiple routes in complex and large environments with constraints. The SN-PSO is shown to be an efficient technique for providing safe, short,and feasible routes under dynamic constraints. The efficiency of the SN-PSO is tested in a mine field simulation with different environment configuration, and it successfully generates multiple feasible routes. Finally, the swarm based techniques are further compared with an evolutionary algorithm (genetic algorithm) for performance and scalability. Statistical results showed that evolutionary techniques perform well in less cluttered environments and their performance degrades with the increase in environment complexity. For small size maps, the evolutionary technique performs well but its efficiency decreases with an increase in map size.
The Dose-Response Associations of Sugar-Sweetened Beverage Intake with the Risk of Stroke, Depression, Cancer, and Cause-Specific Mortality: A Systematic Review and Meta-Analysis of Prospective Studies

The associations between sugar-sweetened beverage (SSB) consumption and the risk of stroke, depression, cancer, and cause-specific mortality have not been determined, and the quantitative aspects of this link remain unclear. This meta-analysis therefore conducted a systematic review and dose-response analysis to determine their causal links. The database searches were conducted in PubMed, Cochrane library, Embase, Web of Science up to 10 November 2021. The intervention effects were evaluated by relative risk (RR) with 95% confidences (CI). Thirty-two articles met the inclusion criteria. Higher levels of SSB consumption significantly increased the risk of stroke (RR 1.12, 95% CI 1.03–1.23), depression (1.25, 1.11–1.41), cancer (1.10, 1.03–1.17), and all-cause mortality (1.08, 1.05–1.11) compared with none or lower SSB intake. The associations were dose-dependent, with per 250 mL increment of SSB intake daily increasing the risk of stroke, depression, cancer, and all-cause mortality by RR 1.09 (1.03–1.15), 1.08 (1.06–1.10), 1.17 (1.04–1.32), and 1.07 (1.03–1.11), respectively. The link was curved for depression and cancer risk (pnon-linear < 0.05). Subgroup analysis suggested that higher SSB intake increased ischemic stroke by 10%, CVD-caused mortality by 13%, and cancer-caused mortality by 6.0% than none or lower SSB consumption. It is suggested that SSB accounts for a leading risk factor of stroke, depression, cancer, and mortality, and that the risk rises in parallel with the increment of SSB intake (and is affected by participant characteristics).
Impact of Institutional Investors Investment Decisions on the Pakistan Stock Exchange

Institutional Investors play an important role in the stock price movement of stock markets of a country. The current study explores the factors Heuristic, Risk Aversion (RA), Day-to-day Experience (DTDE) & Corporate Governance (CG) which significantly affect the Investment Decision-marking (IDM) in the Pakistan Stock Exchange. This study addresses this gap and delivers literature concerning the effect of CG & DTDE on the Investment Decision-making (IDM). This study used 215 institutional investors, which are trading in the Pakistan Stock Exchange (PSX). This study used OLS for estimation of models. The findings revealed that DTDE and CG play a vital role in IDM in Pakistan.
All-Atom Molecular Dynamics Investigations on the Interactions between D2 Subunit Dopamine Receptors and Three 11C-Labeled Radiopharmaceutical Ligands

The D2 subunit dopamine receptor represents a key factor in modulating dopamine release. Moreover, the investigated radiopharmaceutical ligands used in positron emission tomography imaging techniques are known to bind D2 receptors, allowing for dopaminergic pathways quantification in the living human brain. Thus, the biophysical characterization of these radioligands is expected to provide additional insights into the interaction mechanisms between the vehicle molecules and their targets. Using molecular dynamics simulations and QM calculations, the present study aimed to investigate the potential positions in which the D2 dopamine receptor would most likely interact with the three distinctive synthetic 11C-labeled compounds (raclopride (3,5-dichloro-N-[[(2S)-1-ethylpyrrolidin-2-yl]methyl]-2-hydroxy-6-methoxybenzamide)—RACL, FLB457 (5-bromo-N-[[(2S)-1-ethylpyrrolidin-2-yl]methyl]-2,3-dimethoxybenzamide)—FLB457 and SCH23390 (R(+)-7-Chloro-8-hydroxy-3-methyl-1-phenyl-2,3,4,5-tetrahydro-1H-3-benzazepine)—SCH)), as well as to estimate the binding affinities of the ligand-receptor complexes. A docking study was performed prior to multiple 50 ns molecular dynamics productions for the ligands situated at the top and bottom interacting pockets of the receptor. The most prominent motions for the RACL ligand were described by the high fluctuations of the peripheral aliphatic -CH3 groups and by its C-Cl aromatic ring groups. In good agreement with the experimental data, the D2 dopamine receptor-RACL complex showed the highest interacting patterns for ligands docked at the receptor’s top position.
Evaluation of BCG Vaccination and Plasma Amyloid: A Prospective, Pilot Study with Implications for Alzheimer’s Disease

BCG vaccine has been used for 100 years to prevent tuberculosis. Not all countries, including the United States, adopted the initial World Health Organization recommendation to use BCG. Moreover, many Western countries that had routinely used BCG have discontinued its use. Recent population studies demonstrate lower prevalence of Alzheimer’s disease (AD) in countries with high BCG coverage. Intravesicular instillation of BCG is also used to treat bladder cancer that has not invaded the bladder muscle wall and has been shown to reduce recurrence. Several retrospective studies of bladder cancer patients demonstrated that BCG treatment was associated with a significantly reduced risk of developing AD. Plasma amyloid β assessment has become a fertile area of study for an AD biomarker that is predictive of a positive amyloid PET scan. Mass spectrometry-based plasma amyloid 42/40 ratio has proven to be accurate and robust, and when combined with age and ApoE, is shown to accurately predict current and future brain amyloid status. These parameters, amyloid 42/40 ratio, age and ApoE genotype are incorporated into an Amyloid Probability Score (APS)–a score that identifies low, intermediate or high risk of having a PET scan positive for cerebral amyloid. Community recruitment was used for this open-label pilot study. Forty-nine BCG-naïve, immunocompetent individuals completed our study: prior to BCG prime and boost, as determined by the APS, 34 had low risk (APS 0–35), 5 had intermediate risk (APS 36–57) and 10 had high risk (APS 58–100). The APS range for the participant group was 0 to 94. Follow-up plasma amyloid testing 9 months after vaccination revealed a reduction in the APS in all the risk groups: low risk group (p = 0. 37), intermediate risk group (p = 0.13) and the high-risk group (statistically significant, p = 0.016). Greater benefit was seen in younger participants and those with the highest risk. The small number of participants and the nascent status of plasma amyloid testing will rightfully temper embracement of these results. However, both the favorable direction of change after BCG as well as the utility of the APS—a valuable surrogate AD biomarker—may prompt a definitive large-scale multicenter investigation of BCG and AD risk as determined by plasma amyloid peptide ratios and APS.
Uncertainty and sensitivity analysis applied to hygrothermal simulation of a brick building in a hot and humid climate

This paper presents a statistical approach for uncertainty and sensitivity analyses applied to 14 inputs whose 10 properties associated with brick material, using the four different EnergyPlus wall models. The variability of inputs has been extracted from several characterization works presented in IEA Annexes 14, 24 and 55, being coherent to the lack of knowledge in the early design stage. Besides the methodology, this paper presents the moisture effects on cooling energy demand and indoor air conditions, using a simple building geometry and the humid climate of Singapore. Results are presented in terms of uncertainty quantification, most uncertain parameters and sensitivity indices for all models, illustrating the impact of moisture and the importance of the need to well define moisture-dependent functions. The methodology is well adapted for use in complex interactive models with a low-cost simulation and can be used to reduce uncertainties in the design stage and promote reliability of retrofitting assessment.
Cannibalism and intraguild predation involved in the intra- and inter-specific interactions of the invasive fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae) and lepidopteran maize stemborers

Intra- and interspecific competitions play important role in determing spread and survival/death (cannibalism or intraguild predation) of organisms which share the same resource. However, the trends of relation between cannibalism and intraguild predation, and the costs and benefits of such behaviours are difficult to establish within insect communities and a little is known about how such behaviours are affected by invasive species. The present study was aimed at assessing the interactions between larvae of fall armyworm (Spodoptera frugiperda) and maize stemborers (Busseola fusca, Sesamia calamistis and Chilo partellus) in relation to cannibalism and intraguild predation when they are subjected to utilize the same resource. Experiments involving treatments with either single species of S. frugiperda or any of the stemborers or pairwise species combinations were conducted under laboratory conditions. The experimental insect larvae were reared on maize leaves and monitored until the last developmental stage where larval survival, mortality, and cannibalism and/or intraguild predation were recorded. Results of the intra-specific interaction indicated that S. frugiperda exhibited cannibalism to a larger degree than the stemborers species, especially at the late instars stages. The higher cannibalism trait in S. frugiperda turned however to competitive advantage as it led to a higher degree of intraguild predation when they cohabit with other stemborer species. Overall, interaction with S. frugiperda is thus detrimental for the stemborer species and may be an important factor to explain the invasive success of the pest. Such knowledge is essential in designing successful integrated pest management strategies.