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Prediction of buckling damage of steel equal angle structural members using hybrid machine learning techniques
Abstract This article deals with prediction of buckling damage of steel equal angle structural members using a surrogate model combining machine learning and metaheuristic optimization technique. In particular, a hybrid Artificial Intelligence (AI)-based model involving Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) was developed and calibrated for the problem at hand. For this purpose, a database concerning compression tests of steel equal angle structural members was constructed from available resources with geometry variables such as length, width, thickness, mechanical properties of materials such as yield strength and initial imperfections (i.e. residual peak stress and initial geometric imperfections) and critical buckling load of columns. The hybrid PSOANN model was adopted because its prediction capability is higher than the traditional technique – i.e. scaled conjugate gradient (SCG). Indeed, ANN trained by PSO delivered better performance in terms of RMSE, MAE, ErrorStD, R2 and Slope in comparison to ANN trained by SCG, for instance. RMSE decreases from 0.141 to 0.055; MAE decreases from 0.108 to 0.042; R2 increases from 0.749 to 0.959, when switching from ANN alone to hybrid PSOANN, respectively. Moreover, a Partial Dependence (PD) investigation was performed to interpret the “black-box” PSOANN model.
Neurocognitive dynamics and behavioral differences of symmetry and asymmetry processing in working memory: insights from fNIRS
Abstract Symmetry is a ubiquitous property of the visual world. It facilitates cognitive processing and fosters aesthetic appeal. Despite its importance to aesthetic experience and perceptual prominence, the integration of symmetry in working memory remains underexplored. In our study, participants engaged in a novel working memory task involving both symmetrical and asymmetrical stimuli, while their brain activity was monitored using functional Near Infrared Spectroscopy (fNIRS). The study revealed that symmetry significantly enhances memory performance. Symmetry significantly improves task performance, with symmetrical stimuli leading to higher accuracy and faster recall than asymmetrical ones, especially under high cognitive load. This effect varies with the type of symmetry, with diagonal symmetry being the most effective. Neuroimaging data showed distinct brain activation patterns when participants processed symmetrical stimuli, particularly in the memory-straining condition. Significant differences in brain activity were observed in various brain regions, with lateral occipital, posterior parietal, medial and dorsolateral prefrontal cortices reacting to symmetry with decreased oxygenated hemoglobin (HbO), while in left orbitofrontal (HbO) and right ventrolateral prefrontal cortex (HbO and HbR) hemoglobin concentration increased. Overall, our findings highlight the complex, region-specific brain activation patterns in response to visual symmetry, emphasizing the nuanced role of symmetry in cognitive processing during memory tasks and their potential implication for creative thinking.
SARS-CoV-2 infection rates and associated risk factors in healthcare workers: systematic review and meta-analysis
Abstract To protect healthcare workforce during the COVID-19 pandemic, rigorous efforts were made to reduce infection rates among healthcare workers (HCWs), especially prior to vaccine availability. This study aimed to investigate the prevalence of SARS-CoV-2 infections among HCWs and identify potential risk factors associated with transmission. We searched MEDLINE, Embase, and Google Scholar from 1 December 2019 to 5 February 2024. From 498 initial records, 190 articles were reviewed, and 63 studies were eligible. ROBINS-E tool revealed a lower risk of bias in several domains; however, some concerns related to confounding and exposure measurement were identified. Globally, 11% (95% confidence interval (CI) 9–13) of 283,932 HCWs were infected with SARS-CoV-2. Infection rates were associated with a constellation of risk factors and major circulating SARS-CoV-2 variants. Household exposure (odds ratio (OR) 7.07; 95% CI 3.93–12.73), working as a cleaner (OR 2.72; 95% CI 1.39–5.32), occupational exposure (OR 1.79; 95% CI 1.49–2.14), inadequate training on infection prevention and control (OR 1.46; 95% CI 1.14–1.87), insufficient use of personal protective equipment (OR 1.45; 95% CI 1.14–1.84), performing aerosol generating procedures (OR 1.36; 95% CI 1.21–1.52) and inadequate hand hygiene (OR 1.17; 95% CI 0.79–1.73) were associated with an increased SARS-CoV-2 infection. Conversely, history of quarantine (OR 0.23; 95% CI 0.08–0.60) and frequent decontamination of high touch areas (OR 0.52; 95% CI 0.42–0.64) were protective factors against SARS-CoV-2 infection. This study quantifies the substantial global burden of SARS-CoV-2 infection among HCWs. We underscore the urgent need for effective infection prevention and control measures, particularly addressing factors such as household exposure and occupational practices by HCWs, including cleaning staff.
Carbon emission effects of land use change in Nanchang, West of Central China Region
Real-time analysis of initiation regulation systems during the progression of the reconstituted chromosomal replication cycle
Artificial neural network analysis of Jeffrey hybrid nanofluid with gyrotactic microorganisms for optimizing solar thermal collector efficiency
Abstract This article investigates solar energy storage due to the Jeffrey hybrid nanofluid flow containing gyrotactic microorganisms through a porous medium for parabolic trough solar collectors. The mechanism of thermophoresis and Brownian motion for the graphene and silver nanoparticles are also encountered in the suspension of water-based heat transfer fluid. The gyrotactic microorganisms have the ability to move in an upward direction in the nanofluid mixture, which enhances the nanoparticle stability and fluid mixing in the suspension. Mathematical modeling of the governing equations uses the conservation principles of mass, momentum, energy, concentration, and microorganism concentration. The non-similar variables are introduced to the dimensional governing equations to get the non-dimensional ordinary differential equations. The Cash and Carp method is implemented to solve the non-dimensional equations. The artificial neural network is also developed for the non-dimensional governing equations using the Levenberg Marquardt algorithm. Numerical findings corresponding to the diverse parameters influencing the nanofluid flow and heat transfer are presented in the graphs. The thermal profiles are observed to be enhanced with the escalation in the Darcy and Forchheimer parameters. And the Nusselt number enhances with the escalation in the Deborah number and retardation time parameter. Entropy generation reduces with an enhancement in Deborah number and retardation time parameter. Solar energy is the best renewable energy source. It can fulfill the energy requirements for the growth of industries and engineering applications.
Using insecticidal compounds to elucidate the potential role of neurotransmitters in Lepidoptera pupal ecdysis
Knowledge, attitude, and practice toward vitiligo among vitiligo patients: a mediation analysis
Long term effectiveness of intraoperative radiotherapy given as a boost in adjuvant treatment for oral cavity cancers
Rapid landslide detection from free optical satellite imagery using a robust change detection technique
U-shaped association between TC/HDL-C ratio and osteoporosis risk in older adults
Abstract This study aimed to evaluate the association between the total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio and the risk of osteoporosis in older adults. A cross-sectional analysis was conducted using data from 7,465 individuals aged 60 and above from the 2005–2020 National Health and Nutrition Examination Survey (NHANES). The TC/HDL-C ratio was calculated and divided into quartiles. Osteoporosis was defined by self-reported physician diagnosis or dual-energy x-ray absorptiometry (DXA) measurements. Multivariable logistic regression models assessed the association between the TC/HDL-C ratio and osteoporosis prevalence. Restricted cubic splines were used to explore non-linear associations and threshold effects. Among the participants, 1,608 had osteoporosis. A higher TC/HDL-C ratio was inversely associated with osteoporosis (OR: 0.92, 95% CI: 0.86–0.99, p = 0.02). The analysis revealed a U-shaped association (p for nonlinearity = 0.005) with a threshold at 4.66. Below this threshold, the TC/HDL-C ratio was negatively associated with osteoporosis (OR: 0.83, 95% CI: 0.72–0.94, p = 0.010), while no significant association was observed above the threshold. In sex-specific analyses, a U-shaped relationship was found in women, with a threshold at 4.35 (p for nonlinearity = 0.0016), but no significant association was found in men. The TC/HDL-C ratio demonstrates a U-shaped association with osteoporosis risk in older adults, particularly in women. Further longitudinal studies are required to validate these findings and determine optimal lipid management strategies for osteoporosis prevention.
Using new control strategies to improve the effectiveness and efficiency of the hybrid power system based on the battery storage system
Evaluation of an artificial intelligence-based system for real-time high-quality photodocumentation during esophagogastroduodenoscopy
Approaching the general quantification of functional information
Research on glass imitation jade culture in the ancient Chinese Silk Road
Rapid preparation of bioactive composites for transforaminal lumbar interbody fusion
Infiltration of CD8+ cytotoxic T-cells and expression of PD-1 and PD-L1 in ovarian clear cell carcinoma
Exploring microbial players for metagenomic profiling of carbon cycling bacteria in sundarban mangrove soils
Abstract The Sundarbans, the world’s largest tidal mangrove forest, acts as a crucial ecosystem for production, conservation, and the cycling of carbon and nitrogen. The study explored the hypothesis that microbial communities in mangrove ecosystems exhibit unique taxonomic and functional traits that play a vital part in carbon cycling and ecosystem resilience. Using metagenomic analysis to evaluate microbial communities in mangrove and non-mangrove environment, evaluating their composition, functional functions, and ecological relevance. The analysis revealed distinct microbial profiles, in mangrove and non-mangrove environments, with bacteria, proteobacteria, and viruses being the most prevalent groups, with varying abundances in each environment. Functional and taxonomical analysis identified genes involved in carbon regulation, including Triacylglycerol lipase, NarG, DsrB, DNA-binding transcriptional dual regulator CRP, Vanillate O-demethylase oxygenase, succinate-CoA ligase, Tetrahydrofolate ligase, Carboxylase, Ribulose-1,5-bisphosphate carboxylase/oxygenase, Glycine hydroxymethyltransferase, MAG: urease, Endosymbiont of Oligobrachia haakonmosbiensis, Ribulose bisphosphate carboxylase, Aconitate hydratase AcnA, and nitrous oxide reductase, suggesting the metabolic versatility of these microbial communities for carbon cycling. The findings emphasize the key role of microbial activity in preserving mangrove ecosystem health and resilience, highlighting the intricate interplay between microbial diversity, functional capabilities, and environmental factors.
Stroke survivors’ health literacy is not associated with caregiver burden: a cross-sectional study
Abstract Caregivers to stroke survivors often experience a multifaceted strain defined as caregiver burden. Low health literacy among caregivers may contribute to increased caregiver burden but there is limited research specifically examining the association between stroke survivors’ health literacy and caregiver burden. Therefore, the aim here is to explore if there is an association between stroke survivors’ health literacy and caregiver burden one year after stroke. Participants were 50 caregivers and 50 stroke survivors who were followed up in a longitudinal study on care transitions after stroke. Data were collected one year after the stroke survivors’ discharge from hospital and analysed using ordinal logistic regression. Most of the caregivers, median age 71 years, reported being satisfied with their lives (85%) and a low caregiver burden (74%). Stroke survivors’ health literacy was not associated with caregiver burden. However, lower needs of assistance in daily activities, lower levels of depression, higher levels of participation and increased age in stroke survivors were associated with lower caregiver burden. In conclusion, stroke survivors’ health literacy was not associated with caregiver burden one year after stroke. Future studies with larger samples, focusing on populations with lower functioning after stroke and higher caregiver burden, are recommended.