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Seroprevalence studies assessing community exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Ghana concluded that population-level immunity remained low as of February 2021. Thus, it is important to demonstrate how increasing vaccine coverage reduces the economic and public health impacts associated with SARS-CoV-2 transmission. To that end, this study used a Susceptible-Exposed-Presymptomatic-Symptomatic-Asymptomatic-Recovered-Dead-Vaccinated compartmental model to simulate coronavirus disease 2019 (COVID-19) transmission and the role of public health interventions in Ghana. The impact of increasing vaccination rates and decline in transmission rates due to nonpharmaceutical interventions (NPIs) on cumulative infections and deaths averted was explored under different scenarios. Latin hypercube sampling-partial rank correlation coefficient (LHS-PRCC) was used to investigate the uncertainty and sensitivity of the outcomes to the parameters. Simulation results suggest that increasing the vaccination rate to achieve 50% coverage was associated with almost 60,000 deaths and 25 million infections averted. In comparison, a 50% decrease in the transmission coefficient was associated with the prevention of about 150,000 deaths and 50 million infections. The LHS-PRCC results indicated that in the context of vaccination rate, cumulative infections and deaths averted were most sensitive to vaccination rate, waning immunity rates from vaccination, and waning immunity from natural infection. This study's findings illustrate the impact of increasing vaccination coverage and/or reducing the transmission rate by NPI adherence in the prevention of COVID-19 infections and deaths in Ghana. [ABSTRACT FROM AUTHOR]

Introduction: This study aimed to assess the learning curves of peribulbar anesthesia and estimate the number of blocks needed to attain proficiency. Methods: Anonymized records of sequential peribulbar blocks performed by first-year anesthesia residents were analyzed. The block sequential number and the outcomes were extracted from each record. Success was defined as a complete sensory and motor block of the eye, and failure was defined as an incomplete block requiring supplemental local anesthetic injections or general anesthesia. Learning curves using the LC-CUSUM method were constructed, aiming for acceptable and unacceptable failure rates of 10% and 20%, and 10% probability of type I and II errors. Simulations were used to determine the proficiency limit h0. Residents whose curves reached h0 were considered proficient. The Sequential Probability Ratio Test Cumulative Sum Method (SPRT-CUSUM) was used for follow-up. Results: Thirty-nine residents performed 2076 blocks (median = 52 blocks per resident; Interquartile Range (IQR) [range] = 27–78 [4–132]). Thirty residents (77%) achieved proficiency after a median of 13 blocks (13–24 [13–24]). Conclusions: The LC-CUSUM is a robust method for detecting resident proficiency at peribulbar anesthesia, defined as success rates exceeding 90%. Accordingly, 13 to 24 supervised double-injection peribulbar blocks are needed to attain competence at peribulbar anesthesia.

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Aspiration of gastric contents during induction of general anesthesia remains a significant cause of mortality and morbidity in anesthesia. Recent data show that pulmonary aspiration still accounts for many cases with implications on mortality despite technical and technological evolution. Practical, ethical, and methodological issues prevent high-quality research in the setting of aspiration and rapid sequence induction/intubation, and significant controversy is ongoing. Patients’ position, drugs choice, dosing and timing, use of cricoid force, and a reliable risk assessment are widely debated with significant questions still unanswered. We focus our discussion on three approaches to promote a better understanding of rapid sequence induction/intubation and airway management decision-making. Firstly, we review how we can use qualitative and quantitative assessment of fasting status and gastric content with the point-of-care ultrasound as an integral part of preoperative evaluation and planning. Secondly, we propose using imaging-based mathematical models to study different patient positions and aspiration mechanisms, including identifying aspiration triggers. Thirdly, we promote the development of a global data collection system aiming to obtain precise epidemiological data. Therefore, we fill the gap between evidence-based medicine and experts’ opinion through easily accessible and diffused computer-based databases. A better understanding of aspiration epidemiology obtained through focused global data gathering systems, the widespread use of ultrasound-based prandial status evaluation, and development of advanced mathematical models might potentially guide safer airway management decision making in the 21st century.

ABSTRACT Objective Gouty arthritis is characterized by painful inflammation due to the deposition of monosodium urate crystals in joint tissues. Despite available treatments, many patients experience ineffective management and adverse effects. This study evaluated a manual therapy protocol involving passive joint mobilization at the peak of inflammation in a gouty arthritis model using functional and inflammatory parameters. Methods Twenty male Wistar rats, 12 weeks old, were divided into two groups (n=10 each): Gouty Arthritis and Control Groups, which were further subdivided into treated and untreated groups (n=5 each). The Gouty Arthritis Group received intraarticular knee injection of 50µL of monosodium urate crystals, while the Control Group received 50µL of phosphate buffered saline. The treatment involved a 9-minutes session of grade III joint mobilization (according to Maitland). Nociception, grip strength, and edema were evaluated before induction (EV0), 7 hours after assessment (EV1), immediately after treatment (EV2), and 1 hour after treatment (EV3). The animals were euthanized, and synovial fluid was collected to analyze leukocyte migration. Results The model mimicked the signs of the Gouty Arthritis Group, with a decrease in the threshold of nociception and strength and an increase in edema and leukocyte count. The mobilization protocol significantly increased the nociceptive threshold and grip strength and reduced edema; however, it did not reverse the increase in leukocyte count. Conclusion Our results suggest that mobilization promotes analgesia and may modulate the inflammatory process owing to reduced edema and subtle attenuation of cell migration, which contributes to strength gain.

ABSTRACT Purpose: To evaluate the effects of the experimental subcutaneous Walker-256 tumor and L-glutamine supplementation, an antioxidant, on the glomerular morphology of rats. Methods: Twenty Wistar rats were distributed into four groups (n = 5): control (C); control treated with 2% L-glutamine (CG); rats with Walker-256 tumor (WT); and rats with Walker-256 tumor treated with 2% L-glutamine (WTG). Renal histological samples were submitted to periodic acid-Schiff and Masson’s Trichrome staining to analyze glomerular density, morphometry of glomerular components and glomerulosclerosis; and to immunohistochemistry for fibroblast growth factor-2 (FGF-2). Results: WT showed 50% reduction in body mass gain and cachexia index > 10%, while WTG demonstrated reduction in cachexia (p < 0.05). WT revealed reduction of glomerular density, increase in the glomerular tuft area, mesangial area, matrix in the glomerular tuft, decrease in the urinary space and synechia, and consequently higher glomerulosclerosis (p < 0.05). L-glutamine supplementation in the WTG improved glomerular density, and reduced glomerular tuft area, urinary space, mesangial area, and glomerulosclerosis compared to WT(p < 0.05). WT showed higher collagen area and FGF-2 expression compared to C (p < 0.05). WTG presented lower collagen fibers and FGF-2 expression compared to WT (p < 0.05). Conclusions: L-glutamine supplementation reduced cachexia and was beneficial for glomerular morphology of the rats, as well as it reduced kidney damage and improved the remaining glomeruli morphology.

Background/Aim. The Structured Inventory of Malingered Symptomatology (SIMS) is a self-report measure to be used with adults, which may be utilized to assess the potential malingering of psychosis, neurologic impairment, amnesia, low intelligence, or affective disorder. The aim of the study was to examine the discriminant validity of SIMS under conditions of simulating symptoms of neurological and memory disorders, in response to a hypothetical situation, after watching a recording of an actual car accident in which a motorcycle rider sustained head injuries. Methods. The study involved 94 students (35 men and 59 women) from the University of Criminal Investigation and Police Studies in Belgrade and the Faculty of Medicine – Special Education and Rehabilitation in Novi Sad, aged 20–26 [arithmetic mean = 20.69; standard deviation (SD) = 0.80], divided into two groups (n = 4 7), malingerer and control. The malingerer group was instructed to identify with the motorcycle rider hit by the car and malinger symptoms related to neurological difficulties and amnesia in order to obtain greater reimbursement from the insurance company. The control group had instructions to honestly assess the probability of occurrence of the symptoms. Results. The results of the multivariate one-way analysis of variance suggested that the effect of experimental manipulation was statistically significant [F (88, 5) = 91.21, p < 0.001; η2p = 0.838]. Univariate effects were also statistically significant for all five scales. Participants in the malingerer group scored higher on all five scales than participants in the control group. The magnitudes of the effects support the largest differences between the malingerer and control groups on the scales of Memory Disorders and Neuro-logical Disorders, which was also the basic instruction for simulating symptoms given to the participants in the malingerer group. Conclusion. The obtained results support the discriminant validity of the SIMS questionnaire in the situation of simulating symptoms of neurological disorders and memory disorders.

Objective. To summarize the results of research conducted in Costa Rica in which mathematical and statistical methods were implemented to study the transmission dynamics of mosquito-borne diseases. Methods. Three articles with mathematical and statistical analysis on vector-borne diseases in Costa Rica were selected and reviewed. These papers show the value and relevance of using different quantitative methods to understand disease dynamics and support decision-making. Results. The results of these investigations: 1) show the impact on dengue case reports when a second pathogen emerges, such as chikungunya; 2) recover key parameters in Zika dynamics using Bayesian inference; and 3) show the use of machine learning algorithms and climatic variables to forecast the dengue relative risk in five different locations. Conclusions. Mathematical and statistical modeling enables the description of mosquito-borne disease transmission dynamics, providing quantitative information to support prevention/control methods and resource allocation planning.

Objective: Gouty arthritis is characterized by painful inflammation due to the deposition of monosodium urate crystals in joint tissues. Despite available treatments, many patients experience ineffective management and adverse effects. This study evaluated a manual therapy protocol involving passive joint mobilization at the peak of inflammation in a gouty arthritis model using functional and inflammatory parameters. Methods: Twenty male Wistar rats, 12 weeks old, were divided into two groups (n=10 each): Gouty Arthritis and Control Groups, which were further subdivided into treated and untreated groups (n=5 each). The Gouty Arthritis Group received intraarticular knee injection of 50μL of monosodium urate crystals, while the Control Group received 50μL of phosphate buffered saline. The treatment involved a 9-minutes session of grade III joint mobilization (according to Maitland). Nociception, grip strength, and edema were evaluated before induction (EV0), 7 hours after assessment (EV1), immediately after treatment (EV2), and 1 hour after treatment (EV3). The animals were euthanized, and synovial fluid was collected to analyze leukocyte migration. Results: The model mimicked the signs of the Gouty Arthritis Group, with a decrease in the threshold of nociception and strength and an increase in edema and leukocyte count. The mobilization protocol significantly increased the nociceptive threshold and grip strength and reduced edema; however, it did not reverse the increase in leukocyte count. Conclusion: Our results suggest that mobilization promotes analgesia and may modulate the inflammatory process owing to reduced edema and subtle attenuation of cell migration, which contributes to strength gain. [ABSTRACT FROM AUTHOR]

Background: The Theory of Planned Behavior (TPB) has guided the investigation of breastfeeding since the 1980's, incorporating the major constructs of attitudes, subjective norms/normative beliefs, perceived behavioral control, and intentions. The purpose of this research study was to define a TPB-based structural latent variable model so as to explain variance in breastfeeding intentions and behaviors among a cohort of Midwest breastfeeding mothers.Methods: The longitudinal descriptive study utilized questionnaire data collected from a convenience sample of 100 women with low-risk pregnancies with the intention to breastfeed at three separate time points (> 30 weeks antepartum, 10 and 60 days postpartum). Data were coded and analyzed using IBM SPSS, SAS and the lavaan package in R.Results: Participants were predominantly White (94%, n = 94), married (95%, n = 95), college-educated (96%, n = 96), and had previous breastfeeding experience (75%, n = 75). The majority gave birth vaginally (79%, n = 75). Varimax analysis revealed a plurality of factors within each domain. Attempts to fit a structural model, including both hierarchical and bi-factor latent variables, failed, revealing a lack of statistical significance and poor fit statistics.Conclusion(s): These findings illustrate the importance of using methods that fit the phenomena explained. Contributors to poor model fit may include outdated tools lacking cultural relevance, a change in social norms, or a failure to capture the possible influence of social media and formula marketing on breastfeeding behaviors. The null finding is a significant finding, indicating the need to revisit and refine the operationalization and conceptual underpinnings of the TPB through qualitative methods such as exploring the lived experiences of breastfeeding women in the Midwest region. [ABSTRACT FROM AUTHOR]

Abstract Background The Theory of Planned Behavior (TPB) has guided the investigation of breastfeeding since the 1980’s, incorporating the major constructs of attitudes, subjective norms/normative beliefs, perceived behavioral control, and intentions. The purpose of this research study was to define a TPB-based structural latent variable model so as to explain variance in breastfeeding intentions and behaviors among a cohort of Midwest breastfeeding mothers. Methods The longitudinal descriptive study utilized questionnaire data collected from a convenience sample of 100 women with low-risk pregnancies with the intention to breastfeed at three separate time points (> 30 weeks antepartum, 10 and 60 days postpartum). Data were coded and analyzed using IBM SPSS, SAS and the lavaan package in R. Results Participants were predominantly White (94%, n = 94), married (95%, n = 95), college-educated (96%, n = 96), and had previous breastfeeding experience (75%, n = 75). The majority gave birth vaginally (79%, n = 75). Varimax analysis revealed a plurality of factors within each domain. Attempts to fit a structural model, including both hierarchical and bi-factor latent variables, failed, revealing a lack of statistical significance and poor fit statistics. Conclusion(s) These findings illustrate the importance of using methods that fit the phenomena explained. Contributors to poor model fit may include outdated tools lacking cultural relevance, a change in social norms, or a failure to capture the possible influence of social media and formula marketing on breastfeeding behaviors. The null finding is a significant finding, indicating the need to revisit and refine the operationalization and conceptual underpinnings of the TPB through qualitative methods such as exploring the lived experiences of breastfeeding women in the Midwest region.

Background/Aim. In the past two decades, we have witnessed the emergence of new radiation therapy techniques, radiotherapy treatment planning system (TPS) with calculating algorithms for the dosage calculation in a patient, units for multislice computed tomography (CT) and image-guided treatment delivery. The aim of the study was investigating the significant difference in dosimetric calculation of radiotherapy TPS in relation to the values obtained by measuring on the linear accelerator (LINAC), and the accuracy of dosimetric calculation between calculating algorithms Analytical Anisotropic Algorithm (AAA) and Acuros XB in various tissues and photon beam energies. Methods. For End-to-End test we used the hetero-geneous phantom CIRS Thorax002LFC, which anatomically represents human torso with a set of inserts known as relative electron densities (RED) for obtaining a CT calibration curve, comparable to the “reference” CIRS 062M phantom. For the AAA and Acuros XB algorithms and for 6 MV and 16 MV photon beams in the TPS Varian Eclipse 13.6, four 3D conformal (3DCRT), and one intensity modulated (IMRT) and volumetric modulated arc (VMAT) radiotherapy plans were made. Measurements of the absolute dose in Thorax phantom, by PTW-Semiflex ionization chamber, were carried out on three Varian-DHX LINACs. Results. The difference between “reference” and measured CT conversion curves in the bone area was 3%. For 476 phantom measurements, the difference between measured and TPS calculated dose of 3–6%, was found in 30 (6.3%) cases. According to regression analysis, the standardized Beta coefficient for relative errors, 6 MV vs. 16 MV, was 0.337 (33.7%, p < 0.001). Mean relative errors for AAA and Acuros XB, using Mann-Whitney test, for bones were 1.56% and 2.64%, respectively (p = 0.004). Conclusion. End-to-End test on Thorax002LFC phantom proved the accuracy of TPS dose calculation in relation to the one delivered to a patient by LINAC. There was a significant difference for photon energies relative errors (higher values are obtained for 16 MV vs. 6 MV). A statistically significant minor relative error in AAA vs. Acuros XB was found for the bone.

ABSTRACT The Covid-19 pandemic signaled an alert to all countries about controlling transmission of SARS-CoV-2 to have fewer infected individuals, causing less stress to all health systems, and saving lives. As a result, multiple governments, including national and local levels of government, went through several degrees of social distancing measures. The decision process regarding the flexibilization of social distancing measures requires evidence of incidence decrease, available capacity in the health systems to absorb eventual epidemic waves, and serological prevalence studies designed to estimate the proportion of individuals with antibody protection. The trend criterium usually given by the effective reproduction number might be misguided if there are significant delays for reporting cases. For instance, the reproduction number for Niterói, in the state of Rio de Janeiro, went down from a value of approximately 3 to little more than 1. Even with all measures, the reproduction number did not get below R

Background: In South Korea, the National Immunization Program has included one-dose varicella vaccination for 1-year-olds since 2005. This study examines the potential impact of introducing a two-dose varicella vaccination for children, along with zoster vaccination for adults, using either the zoster vaccine live (ZVL) or recombinant zoster vaccine (RZV)., Methods: The investigation considered four strategies in a base case scenario. The first involved introducing zoster vaccination for 60-year-olds, with a 60 % coverage. The second strategy combined zoster vaccination with a second-dose varicella vaccination for 4-year-olds, with a 90 % coverage. An age-structured model spanning 50 years was employed, assuming a zoster vaccine catch-up campaign over the initial 5 years. Cost-effectiveness analyses were conducted, assessing incremental cost-effectiveness ratios (ICERs), incremental net monetary benefits (INMBs), and net loss under different ages at zoster vaccination (50, 60, 65, and 70 years) and varying willingness-to-pay (WTP) levels from ₩40 million ($34,998) to ₩84 million ($74,000)., Results: All strategies were cost-effective and significantly reduced herpes zoster (HZ) incidence, preventing approximately 3,077,000 to 7,609,000 cases, depending on the chosen strategy. The combined strategy prevented around 4,950,000 varicella and 653,000 HZ cases additionally. RZV outperformed ZVL by preventing twice as many HZ cases and offering greater QALY gains. However, ZVL was more cost-effective due to its lower cost. Probabilistic sensitivity analyses revealed that RZV became more cost-effective at higher WTP thresholds, exceeding ₩60.9 million ($53,193) in terms of ICER and ₩62.5 million ($54,591) for INMBs and net loss. The optimal age for zoster vaccination was 60 years concerning ICER but 50 years regarding INMB., Conclusions: Combining RZV with a two-dose varicella vaccination strategy reduced the disease burden and improved QALY more effectively, though ZVL remained more cost-effective at lower WTP levels. Decisions regarding vaccination policies should be balanced between the public health needs and WTP levels., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

An effective prophylactic vaccine for prevention of Neisseria gonorrhoeae infection would have a major impact on sexual and reproductive health worldwide. Interest in developing gonorrhoea vaccines is growing due to the reported high rates of N. gonorrhoeae infections globally, and the threat of antimicrobial resistance. Several gonorrhoea vaccine candidates are currently under evaluation and various mathematical models have been used to assess the potential population-level impact a gonorrhoea vaccine may have once available. Here we review key aspects of gonorrhoea vaccine mathematical modelling studies, including model structures, populations considered, and assumptions used as well as vaccine characteristics and implementation scenarios investigated. The predicted vaccine impact varied between studies, ranging from as little as ∼17 % reduction in N. gonorrhoeae prevalence after 30 years up to 100 % reduction after 5 years. However, all studies predicted that even a partially effective gonorrhoea vaccine could have a substantial impact in reducing N. gonorrhoeae prevalence or incidence, particularly when high coverage is achieved within either important risk groups or the overall sexually active population. As expected, higher vaccine efficacy against acquisition of N. gonorrhoeae and longer duration of protection were linked to greater reductions in infections. A vaccine that alters onward transmission could also substantially reduce infections. Several gaps and research needs have been identified by researchers in the field and via this narrative literature review. For example, future modelling to inform gonorrhoea vaccine development and implementation should consider additional populations that are at high risk of N. gonorrhoeae infection, especially in low- and middle-income settings, as well as the impact of vaccination on the potential adverse sexual and reproductive health outcomes of infection. In addition, more detailed and robust epidemiological, biological, and behavioural data is needed to enable more accurate and robust modelling of gonorrhoea vaccine impact to inform future scientific and public health decision-making., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Thilini Padeniya reports financial support was provided by National Institutes of Health. Kate Seib reports financial support was provided by National Institutes of Health. Kate Seib reports financial support was provided by National Health and Medical Research Council. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In the centuries following Christopher Columbus's 1492 voyage to the Americas, transoceanic travel opened unprecedented pathways in global pathogen circulation. Yet no biological transfer is a single, discrete event. We use mathematical modeling to quantify historical risk of shipborne pathogen introduction, exploring the respective contributions of journey time, ship size, population susceptibility, transmission intensity, density dependence, and pathogen biology. We contextualize our results using port arrivals data from San Francisco, 1850 to 1852, and from a selection of historically significant voyages, 1492 to 1918. We offer numerical estimates of introduction risk across historically realistic ranges of journey time and ship population size, and show that both steam travel and shipping regimes that involved frequent, large-scale movement of people substantially increased risk of transoceanic pathogen circulation., Competing Interests: Competing interests statement:The authors declare no competing interest.

The purpose of the study is introduce a two-phase flow model to simulate water penetration into pharmaceutical tablets. This model was built by integrating Darcy's law with the continuity principle, on the premise that water penetration was driven by capillary actions. Notably, this model concerned both the ingress of water (wetting phase) and simultaneous displacement of air (non-wetting phase). Due to the interference of the two fluids, the relative permeability and capillary pressure vary during water penetration. Evolution of these parameters was incorporated in the model. Calibration of the model by water penetration experiments of the microcrystalline cellulose (MCC) tablet yielded an average pore radius of 42 nm. This derived result was corroborated by FIB-SEM analysis revealing the presence of extensive microporosity within MCC particles with an average radius of ∼30 nm. Further validation was achieved through close resemblance between the simulated and experimental water penetration profiles of MCC tablets possessing different porosities. Overall, this study underscored the advantage of the two-phase flow model over single-phase flow models, by capturing the dependence of permeability and capillary pressure on water saturation. Therefore it holds promise for an enhanced description of water penetration into tablets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The push-pull osmotic pump tablet is a promising drug delivery approach, offering advantages over traditional dosage forms in achieving consistent and predictable drug release rates. In the current study, the drug release process of push-pull osmotic pump tablets is modelled for the first time using the discrete element method (DEM) incorporated with a microscopic diffusion-induced swelling model. The effects of dosage and formulation design, such as delivery orifice size, drug-to-polymer ratio, tablet surface curvature, friction between particles and cohesion of polymer particles, on the drug release performance are systematically analysed. Numerical results reveal that an enlarged delivery orifice significantly increases both the total drug release and the drug release rate. Moreover, the larger the swellable particle component in the tablet, the higher the drug release rate. Furthermore, the tablet surface curvature is found to affect the drug release profile, i.e. the final drug release percentage increases with the increasing tablet surface curvature. It is also found that the drug release rate could be controlled by adjusting the inter-particle friction and the cohesion of polymer particles in the formulation. This DEM study offers valuable insights into the mechanisms governing drug release in push-pull osmotic pump tablets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Green infrastructure (GI), as one type of ecological stormwater management practices, can potentially alleviate water problems and deliver a wide range of environmental benefits in urban areas. GIs are often planned and designed to reduce runoff and mitigate pollution. However, the influence of GI on groundwater hydrology and that of shallow groundwater on GI performance was seldom considered. This study utilized a calibrated surface-subsurface hydrological model, i.e., Storm Water Management Model coupled with USGS's modular hydrologic model (SWMM-MODFLOW) to consider the interaction between GI and groundwater into the process of GI planning. The optimal implementation ratio, aggregation level and upstream-downstream location of bioretention cells (BC, one type of GI) under different planning objectives and hydrogeologic conditions was explored. The consideration of groundwater management exerted a significant impact on the optimal spatial allocation of BCs. The results showed that when groundwater management was more concerned than runoff control, BCs were recommended to be allocated more apart from each other and more upstream in the catchment because more-distributed and upstream BCs can result in lower groundwater table rise which is beneficial. BCs were overall recommended to be allocated in areas of deeper groundwater tables, coarser soils, and flatter topographies. However, the spatial features of BCs are related to each other, the choice of them are affected by various hydrogeologic factors simultaneously. The exact location of BCs should be determined by considering the trade-off between runoff control efficiency and groundwater impact. The findings obtained in this study can provide guidance on GI planning in shallow groundwater areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

DC circuit breakers (DCCBs) with high breaking capacity and low cost are necessary for quick fault clearance in DC networks. The assembly DC circuit breakers (ADCCBs) have a main breaking section (MBS) and a sub-breaking sections (SBS) for each line, which greatly reduce the cost. But in conventional operation, it bears high voltage for a long time when there is a main switch grounding process in any line fault action. To address this problem, a multiport assembly circuit breaker based on current injection (CI-MPACB) is proposed, which is able to generate a resonant current with increasing amplitude by controlling the duty cycle of Integrated Gate-Commutated Thyristors (IGCTs). Then the resonant current is injected into the SBS to generate current zero crossing and arc extinction. A complex frequency domain circuit analysis is performed on the MBS to describe the action logic as well as the commutation characteristics. In addition, the parameters of each component of the MBS are subject to multiple constraints and reasonable design to ensure the fault current could be cut off quickly and reliably. The cost of existing design is greatly reduced due to the design idea of resonant current injection device parameter selection. Finally, a PSCAD/EMTDC simulation confirms the opening viability of CI-MPACB and the accuracy of the parameter design. The test results show that the designed CI-MPACB can cut off DC fault lines., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Cui et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Modern urban dynamics are increasingly shaped by the interplay between economic policy and urban planning, yet often lack an integrated approach. This study bridges this gap by examining the dynamic equilibrium between these two realms using the "Oscillation and Wave Framework." Specifically, we focus on the impact of variations in congestion parameter λ on urban sectoral spatial distribution and population dynamics. Our approach utilizes an advanced agent-based model to simulate interactions within an urban economic landscape, offering a detailed analysis of the relationship between agglomeration economies and congestion diseconomies. The results highlight the significant influence of congestion parameter adjustments on urban patterns, particularly in terms of cluster density and development. Therefore, this study not only provides a deeper understanding of the intricate balance between economic and urban planning factors but also emphasizes the necessity of incorporating these insights into urban planning and policy formulation for sustainable urban development. The findings also have important practical implications for addressing the dynamic complexities of urban environments, especially the interactions between different industries and their role in shaping urban structures., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Complex health interventions (CHIs) are increasingly used in public health, clinical research and education to reduce the burden of disease worldwide. Numerous theories, models and frameworks (TMFs) have been developed to support implementation of CHIs. This systematic review aims to identify and critique theoretical frameworks concerned with three features of implementation; adaptability, scalability and sustainability (ASaS). By dismantling the constituent theories, analysing their component concepts and then exploring factors that influence each theory the review team hopes to offer an enhanced understanding of considerations when implementing CHIs., Methods: This review searched PubMed MEDLINE, CINAHL, Web of Science, and Google Scholar for research investigating the TMFs of complex health interventions. Narrative synthesis was employed to examine factors that may influence the adaptability, scalability and sustainability of complex health interventions., Results: A total of 9763 studies were retrieved from the five databases (PubMed, MEDLINE, CINAHL, Web of Science, and Google Scholar). Following removal of duplicates and application of the eligibility criteria, 35 papers were eligible for inclusion. Influencing factors can be grouped within outer context (socio-political context; leadership funding, inter-organisational networks), inner context; (client advocacy; organisational characteristics), intervention characteristics (supervision, monitoring and evaluation), and bridging factors (individual adopter or provider characteristics)., Conclusion: This review confirms that identified TMFS do not typically include the three components of adaptability, scalability, and sustainability. Current approaches focus on high income countries or generic "whole world" approaches with few frameworks specific to low- and middle-income countries. The review offers a starting point for further exploration of adaptability, scalability and sustainability, within a low- and middle-income context., Trial Registration: Not registered., (© 2024. The Author(s).)

This research bears significant implications for river management, flood forecasting, and ecosystem preservation in the Lower Narmada Basin. A more precise estimation of Manning's Roughness Coefficeint (n) will enhance the accuracy of hydraulic models and facilitate informed decision-making regarding flood risk management, water resource allocation, and environmental conservation efforts. Ultimately, this study aspires to contribute to the sustainable management of perennial river systems in India and beyond by offering a robust methodology for optimizing Manning's n tailored to the complex hydrological dynamics of the Lower Narmada Basin. Through a synthesis of empirical evidence and computational modelling, it seeks to empower stakeholders with actionable insights toward preserving and enhancing these invaluable natural resources. Using the new HEC-RAS v 6.0, a one-dimensional hydrodynamic model was developed to predict overbank discharge at different points along the basin. The study analyzes water levels, stream discharges, and river stage, optimizing Manning's n and required flood risk management. The model predicted a strong output agreement with R 2 , NSE, and RMSE for the 2020 event as 0.83, 0.81, and 0.36, respectively, with an optimum Manning's n of 0.03. The lower Narmada Basin part near the coastal zone (validation point) appears inundated frequently. The paper aims to provide insights into optimizing Manning's coefficient, which can ultimately lead to better water flow predictions and more efficient water management in the region., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

A new mathematical model can estimate the number of precursor cells that contribute to regenerating blood cells in mice., Competing Interests: SD, CS No competing interests declared, (© 2024, Duchamp de Chastaigne and Sawai.)

The method of partial differential equations for image inpainting achieves better repair results and is economically feasible with fast repair time. Addresses the inability of Curvature-Driven Diffusion (CDD) models to repair complex textures or edges when the input image is affected by severe noise or distortion, resulting in discontinuous repair features, blurred detail textures, and an inability to deal with the consistency of global image content, In this paper, we have the CDD model of P-Laplace operator term to image inpainting. In this method, the P-Laplace operator is firstly introduced into the diffusion term of CDD model to regulate the diffusion speed; then the improved CDD model is discretized, and the known information around the broken region is divided into two weighted average iterations to get the inpainting image; finally, the final inpainting image is obtained by weighted averaging the two image inpainting images according to the distancing. Experiments show that the model restoration results in this paper are more rational in terms of texture structure and outperform other models in terms of visualization and objective data. Comparing the inpainting images with 150, 1000 and 100 iterations respectively, Total Variation(TV) model and the CDD model inpainting algorithm always has inpainting traces in details, and TV model can't meet the visual connectivity, but the algorithm in this paper can remove the inpainting traces well, TV model and the CDD model inpainting algorithm always have inpainting traces in details, and TV model can't meet the visual connectivity, but the algorithm in this paper can remove the inpainting traces well. Of the images used for testing, the highest PSNR reached 38.7982, SSIM reached 0.9407, and FSIM reached 0.9781, the algorithm not only inpainting the effect and, but also has fewer iterations., Competing Interests: All of authors have declared that no competing interests exist., (Copyright: © 2024 Xiao, Wu. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

When large-scale electric vehicles are connected to the grid for unordered charging, it will seriously affect the stability and security of the power system. To solve this problem, this paper proposes a regional power network optimization scheduling method considering vehicle network interaction. Initially, based on the user behavior characteristics and charging and discharging characteristics of electric vehicles, a charging and discharging behavior model of electric vehicles was established. Based on the Monte Carlo sampling algorithm, the scheduling upper and lower limits of each scheduling cycle of electric vehicles were described, and the scheduling potential of each scheduling cycle of electric vehicles was obtained. Then, the electricity price is then used as an incentive parameter to guide EV users to charge during periods of low electricity prices and participate in discharge during periods of peak electricity prices. Aiming at the highest economic efficiency, the best consumption effect of new energy and the smoothest demand-side power curve of regional power grid, a three-objective optimal dispatching model was established. In the later stage, uncertainty factors are taken into consideration by introducing the concept of interval numbers, and an interval multi-objective optimization dispatching model is established. The two dispatching models are solved by NSGA-II algorithm and improved NSGA-II algorithm, and the Pareto solution set is obtained. Finally, based on the analytic Hierarchy Process (AHP), the optimal scheduling scheme is determined. The Monte Carlo sampling method is used to simulate the user side charging demand, and the effectiveness of this method is verified. In addition, the results of the interval multi-objective optimization model and the deterministic multi-objective optimization model are compared, and it is proved that the solution results of the interval multi-objective model are more adaptive, practical and robust to the uncertain factors., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Hua et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In this research paper, we investigate the existence and uniqueness of solutions for neutral functional differential equations with sequential fractional orders, specifically involving the [Formula: see text]-Caputo operator. To obtain the desired results, we employ the Banach fixed point theorem (BFPT), a nonlinear variation of the Leray-Schauder fixed point theorem (SFPT), and the Krasnoselski fixed point theorem (KFPT). Additionally, we provide illustrative examples that demonstrate the key findings. Furthermore, we address a scenario where an initial value integral condition is considered., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Debbar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Understanding the transport of 137 Cs emitted during the Fukushima accident is challenging because the critical emissions that produced the high-deposition area are not adequately resolved in existing source terms. This paper presents an objective inverse reconstruction of these emissions by fusing atmospheric concentrations with a-priori emissions extracted from total depositions. This extraction, previously considered impossible for complex real-world accidents, is achieved by identifying the critical temporal formation process of depositions in the high-deposition area and estimating the corresponding emissions by using an atmospheric transport model. The reconstructed source term reveals two emission peaks from 10:00-11:00 and 14:00-15:00 on March 15, which agree with the in situ pressure measurements and accident analysis, suggesting that they came from pressure drops in the primary containment vessels of Units 3 and 2, respectively. This finding explains the environmental observations of spherical 137 Cs particles. The source term also objectively and independently confirms the widely used reverse estimate. The corresponding 137 Cs transport simulations better match the various observations than those produced by other source terms, proving that the two-peak emission creates a high-deposition area. The proposed method outperforms the direct fusion of deposition and atmospheric concentration observations, providing a robust tool for multiobservation fusion.

To improve the accuracy of the Hami melon discrete element model, the parameters of the Hami melon seed discrete element model were calibrated by combining practical experiments and simulation tests. The basic physical parameters of Hami melon seeds were obtained through physical experiments, including triaxial size, 100-grain mass, moisture content, density, Poisson's ratio, Young's modulus, shear modulus, angle of repose, suspension speed and various contact parameters. Taking the repose angle of seed simulation as an index, the parameters of each simulation model were significantly screened by the Plackett-Burman test. The results showed that the recovery coefficient, static friction coefficient and rolling friction coefficient of Hami melon seeds had significant effects on repose angle. Based on the steepest climbing test and quadratic regression orthogonal rotation combination test, it was determined that the significant order of the influence of various contact parameters on the angle of repose was static friction coefficient, collision recovery coefficient, and rolling friction coefficient. The optimal parameter combination was obtained through the mathematical regression model between the angle of repose and various contact parameters, namely, the collision recovery coefficient of Hami melon seeds was 0.518, the static friction coefficient of Hami melon seeds was 0.585 and the rolling friction coefficient of Hami melon seeds was 0.337. Under this condition, three static seed-dropping experiments and dynamic rolling accumulation experiments were carried out. The average simulated angle of repose was 31.93°, and the relative error with the actual value was only 1.71%. The average simulated rolling accumulation angle was 51.98°, and the relative error with the actual value was only 1.92%., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Accurately predicting traffic flow is crucial for optimizing traffic conditions, reducing congestion, and improving travel efficiency. To explore spatiotemporal characteristics of traffic flow in depth, this study proposes the MFSTBiSGAT model. The MFSTBiSGAT model leverages graph attention networks to extract dynamic spatial features from complex road networks, and utilizes bidirectional long short-term memory networks to capture temporal correlations from both past and future time perspectives. Additionally, spatial and temporal information enhancement layers are employed to comprehensively capture traffic flow patterns. The model aims to directly extract original temporal features from traffic flow data, and utilizes the Spearman function to extract hidden spatial matrices of road networks for deeper insights into spatiotemporal characteristics. Historical traffic speed and lane occupancy data are integrated into the prediction model to reduce forecasting errors and enhance robustness. Experimental results on two real-world traffic datasets demonstrate that MFSTBiSGAT successfully extracts and captures spatiotemporal correlations in traffic networks, significantly improving prediction accuracy., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Huang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The environmental pollution caused by mineral exploitation and energy consumption poses a serious threat to ecological security and human health, particularly in resource-based cities. To address this issue, a comprehensive investigation was conducted on potentially toxic elements (PTEs) in road dust from different seasons to assess the environmental risks and influencing factors faced by Datong City. Multivariate statistical analysis and absolute principal component score were employed for source identification and quantitative allocation. The geo-accumulation index and improved Nemerow index were utilized to evaluate the pollution levels of PTEs. Monte Carlo simulation was employed to assess the ecological-health risks associated with PTEs content and source orientation. Furthermore, geo-detector and random forest analysis were conducted to examine the key environmental variables and driving factors contributing to the spatiotemporal variation in PTEs content. In all PTEs, Cd, Hg, and Zn exhibited higher levels of content, with an average content/background value of 3.65 to 4.91, 2.53 to 3.34, and 2.15 to 2.89 times, respectively. Seasonal disparities were evident in PTEs contents, with average levels generally showing a pattern of spring (winter) > summer (autumn). PTEs in fine road dust (FRD) were primarily influenced by traffic, natural factors, coal-related industrial activities, and metallurgical activities, contributing 14.9-33.9 %, 41.4-47.5 %, 4.4-8.3 %, and 14.2-29.4 % to the total contents, respectively. The overall pollution and ecological risk of PTEs were categorized as moderate and high, respectively, with the winter season exhibiting the most severe conditions, primarily driven by Hg emissions from coal-related industries. Non-carcinogenic risk of PTEs for adults was within the safe limit, yet children still faced a probability of 4.1 %-16.4 % of unacceptable risks, particularly in summer. Carcinogenic risks were evident across all demographics, with children at the highest risk, mainly due to Cr and smelting industrial sources. Geo-detector and random forest model indicated that spatial disparities in prioritized control elements (Cr and Hg) were primarily influenced by particulate matter (PM 10 ) and anthropogenic activities (industrial and socio-economic factors); variations in particulate matter (PM 10 and PM 2.5 ) and meteorological factors (wind speed and precipitation) were the primary controllers of seasonal disparities of Cr and Hg., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The City of Cape Town (CoCT), South Africa faced a critical situation between 2015 and 2018 in which the municipal water supply was almost completely exhausted. This situation, commonly referred to as Day Zero in South Africa emanated from a decline in rainfall, resulting in one of the most severe droughts in history. The crisis was also aggravated by rapid population growth and urbanization. CoCT was on the verge of becoming the first city in the past decade to experience a complete cessation of water supply for urban and agricultural purposes. In addition to the effects of low rainfall and population surge, urban energy consumption and increased food demand impacted directly the available water resources. To evaluate the interlinkages between water utilization, water production, energy supply and demand, and food production and demand, this study employed a system dynamics modeling (SDM) approach. The model was developed as a stock and flow diagram utilizing Stella Architect and encompassed five interconnected nodes: water, energy, food, land, and population. The findings revealed that by the end of the 20-year modeling period, the volume of accessible and stored water in all the major dams will be approximately 459 million cubic meters, with residential use accounting for about 85 % of urban water use and agriculture accounting for approximately30.37 % of total water demand. The model illustrates the impacts of precipitation rate, runoff, and evaporation on variables such as land-use change and population dynamics. It is anticipated that the outcomes of this study will serve as valuable inputs for decision-making processes, not only within the CoCT as it aims to mitigate or prevent the recurrence of Day Zero, but also for other cities facing similar challenges., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jafaru Musa Egieya reports financial support was provided by the Water Research Commission. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

A model capable to estimate the mercury (Hg) removal efficiency in the fabric filter of a real Waste-to-Energy plant with dynamic operating conditions has been developed. The mathematical model is based on Langmuir equation and Hg mass balance on mercury, in both gaseous and adsorbed phases, along the growing filter cake and inside the activated carbon particles. The activated carbon properties and the Langmuir isotherm parameters have been obtained by fitting the model to real plant data, characterized by variable mercury inlet concentrations. The model is then validated on another dataset coming from the same plant. The obtained Hg removal efficiency falls within ± 3 % error band and with a mean absolute percentage error equal to 0.87 %. The model is suitable for the development of a data-driven activated carbon feed control strategy to increase the economic and environmental sustainability of the WtE plants as well as in the development of virtual sensors to use as a replacement when the continuous stack mercury monitors fail., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The outbreak of the COVID-19 pandemic led to a sharp increase in disposable surgical mask usage. Discarded masks can release microplastic and cause environmental pollution. Since masks have become a daily necessity for protection against virus infections, it is necessary to review the usage and disposal of masks during the pandemic for future management. In this study, we constructed a dynamic model by introducing related parameters to estimate daily mask usage in 214 countries from January 22, 2020 to July 31, 2022. And we validated the accuracy of our model by establishing a dataset based on published survey data. Our results show that the cumulative mask usage has reached 800 billion worldwide, and the microplastics released from discarded masks due to mismanagement account for 3.27% of global marine microplastic emissions in this period. Furthermore, we illustrated the response relationship between mask usage and the infection rates. We found a marginally significant negative correlation existing between the mean daily per capita mask usage and the rate of cumulative confirmed cases within the range of 25% to 50%. This indicates that if the rate reaches the specified threshold, the preventive effect of masks may become evident., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The presence of pollutants in the earth's atmosphere has a direct impact on human health and the environment. So that pollutants such as carbon monoxide (CO) and particulate matter (PM) cause respiratory diseases, cough headache, etc. Since the amount of pollutants in the air is related to environmental and urban factors, the aim of the current research is to investigate the relationship between the concentration of CO, PM 2.5 and PM 10 with urban-environmental factors including land use, wind speed and wind direction, topography, traffic, road network, and population through a Land use regression (LUR) model. The concentrations of CO, PM 2.5 and PM 10 were measured during four seasons from 26th of March 2022 to 16th of March 2023 at 25 monitoring stations and then the information about pollutant measurement points and Land use data were entered into the ArcGIS software. The annual average concentrations of CO, PM 2.5 and PM 10 were 0.7 ppm, 18.94 and 60.76 µg/m 3 , respectively, in which the values of annual average concentration of CO and PMs were outside the air quality guideline standard. The results of the health risk assessment showed that the hazard quotient values for all three investigated pollutants were lower than 1 and therefore, they were not in adverse conditions in terms of health effects. Among the urban-environmental factors affecting air pollution, the traffic variable is the most important factor affecting the annual LUR model of CO, PM 2.5 and PM 10 , and then the topography variable is the second most effective factor on the annual LUR model of the aforementioned pollutants., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Background: Reference evapotranspiration (ET o ), which is used as the basic data in many studies within the scope of hydrology, meteorology, irrigation and soil sciences, can be estimated by using the evaporation (E pan ) measured from the class-A pan evaporimeter. However, this method requires reliable pan coefficients (K p ). Many empirical models are used to estimate K p coefficients. The reliability of these models varies depending on climatic and environmental conditions. Therefore, they need to be tested in the local conditions where they will be used. In this study, conducted in Kahramanmaraş, which has a semi-arid Mediterranean climate in Turkey during the July-October periods of 2020 and 2021, aimed to determine the usability levels of six K p models in estimating daily and monthly average ET o ., Methods: The K p coefficients estimated by the models were multiplied with the daily E pan values, and the daily average ET o values were estimated on the basis of the model. The daily E pan values were measured using an ultrasonic sensor sensitive to the water surface placed on the class-A pan evaporimeter. The ultrasonic sensor was managed by a programmable logic controller (PLC). To enable the sensor to be managed by PLC, a software was prepared using the CODESYS programming language and uploaded to the PLC. The daily average ET o values determined by the FAO-56 Penman-Monteith equation were accepted as actual values. The ET o values estimated by the K p models were compared with the actual ET o values using the mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE) and determination coefficient (R 2 ) statistical approaches., Results: The Wahed & Snyder outperformed the other models in estimating daily (MAE = 0.78 mm day -1 , MAPE = 14.40%, RMSE = 0.97 mm day -1 , R 2 = 0.82) and monthly (MAE = 0.32 mm day -1 , MAPE = 5.88%, RMSE = 0.32 mm day -1 , R 2 = 0.99) average ET o . FAO-56 showed the nearest performance to Wahed & Snyder. The Snyder model presented the worst performance in estimating daily (MAE = 2.09 mm day -1 , MAPE = 37.53%, RMSE = 2.36 mm day -1 , R 2 = 0.82) and monthly (MAE = 1.83 mm day -1 , MAPE = 31.82%, RMSE = 1.87 mm day -1 , R 2 = 0.99) average ET o . It has been concluded that none of the six K p models can be used to estimate the daily ET o in Kahramanmaraş located in the Mediterranean-Southeastern Anatolian transitional zone, and only Wahed & Snyder and FAO-56 can be used to estimate the monthly ET o without calibration., Competing Interests: The author declares that he has no competing interests., (©2024 Usta.)

Urban road traffic is one of the primary sources of carbon emissions. Previous studies have demonstrated the close relationship between traffic flow characteristics and carbon emissions (CO2). However, the impact of dynamic traffic distribution on carbon emissions is rarely empirically studied on the network level. To fill this gap, this study proposes a dynamic network carbon emissions estimation method. The network-level traffic emissions are estimated by combining macroscopic emission models and recent advances in dynamic network traffic flow modeling, namely, Macroscopic Fundamental Diagram. The impact of traffic distribution and the penetration of battery electric vehicles on total network emissions are further investigated using the Monte Carlo method. The results indicate the substantial effect of network traffic distribution on carbon emissions. Using the urban expressway network in Ningbo as an example, in the scenario of 100% internal combustion engine vehicles, increasing the standard deviation of link-level traffic density from 0 to 15 veh/km-ln can result in an 8.9% network capacity drop and a 15.5% reduction in network carbon emissions. This effect can be moderated as the penetration rate of battery electric vehicles increases. Based on the empirical and simulating evidence, different expressway pollution management strategies can be implemented, such as petrol vehicle restrictions, ramp metering, congestion pricing, and perimeter control strategies., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This article focuses on the emergence of cooperation in societies of self-interested agents. In particular, it introduces a mechanism based on indirect-stigmergic-interactions between agents moving in an environment, to express the likeliness of finding cooperative partners. On the one hand, agents that find themselves cooperating with others emit pheromones in their current location, expressing the presence of agents willing to cooperate. On the other hand, agents that sense pheromones tend to move towards regions with a higher pheromone concentration. Results show that this mechanism leads to the emergence of spatial regions where cooperation can be effectively sustained, and in which agents can overall get better payoffs than those agents not taking into account pheromones in their choices., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Zambonelli et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study investigates the thermal conductivity (λ) and volumetric heat capacity (C) of sandy soil samples under a variety of conditions, including freeze-thaw cycles at temperatures both above and below zero and differing moisture levels. To estimate these thermal properties, a novel predictive model, EFAttNet, was developed, which utilizes custom-designed embedding and attention-based fusion networks. When compared to traditional de Vries empirical models and other baseline algorithms, EFAttNet demonstrated superior accuracy. Preliminary measurements showed that λ values increased linearly with moisture content but decreased with temperature, whereas C values exhibited a rising trend with both moisture content and freezing temperature. Following freeze-thaw cycles, both λ and C were positively influenced by moisture content and freezing temperature. The EFAttNet-based model proved highly accurate in predicting thermal properties, particularly effective at capturing nonlinear relationships among the influencing factors. Among these factors, the degree of saturation had the most significant impact, followed by the number of freeze-thaw cycles, subzero temperatures, porosity, and moisture content. Notably, dry density exerted minimal influence on thermal properties, likely due to the overriding effects of other factors or specific soil characteristics, such as particle size distribution or mineralogical composition. These findings have significant implications for construction and engineering projects, especially in terms of sustainability and energy efficiency. The demonstrated accuracy of the EFAttNet-based model in estimating thermal properties under various conditions holds promise for practical applications. Although focused on specific soil types and conditions, the insights gained can guide further research and development in managing soil thermal properties across diverse environments, thereby enhancing our understanding and application in this field., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The complex vibration phenomenon occurs in the downhole environment of the gas-liquid hydrocyclone, which affects the flow field in the hydrocyclone. In order to study the influence of vibration on hydrocyclone separation, the characteristics of the flow field in the downhole gas-liquid hydrocyclone were analyzed and studied under the condition of vibration coupling. Based on Computational Fluid Dynamics (CFD), Computational Solid Mechanics Method (CSM) and fluid-solid coupling method, a fluid-solid coupling mechanical model of a gas-liquid cyclone is established. It is found that under the condition of vibration coupling, the velocity components in the three directions of the hydrocyclone flow field change obviously. The peak values of tangential velocity and axial velocity decrease, and the asymmetry of radial velocity increases. The distribution regularity of vorticity and turbulence intensity in the overflow pipe becomes worse. Among them, the vorticity intensity of the overflow pipe is obviously enhanced, and the higher turbulence intensity near the wall occupies more area distribution range. The gas-liquid separation efficiency of the hydrocyclone will decrease with the increase of the rotational speed of the screw pump, and the degree of reduction can reach more than 10%. However, this effect will decrease with the increase of the rotational speed of the screw pump, so the excitation effect caused by the rotational speed has a maximum limit on the flow field., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

As the world steadily recovers from the COVID-19 pandemic, managing large gatherings becomes a critical concern for ensuring crowd safety. The crowd-crush disaster in Seoul in 2022 highlights the need for effective predictive crowd management techniques. In this study, an empirical analysis of this incident is conducted using data from various sources, and model-based simulations are created to replicate hazardous crowd conditions in high-risk areas. In the empirical analysis, mobile device data indicates a significant increase in population above normal levels in the disaster area just hours before the incident occurred. In the simulations, a hydrodynamic model is employed to simulate a bidirectional collision, which quantitatively demonstrates that the average density during the crush reached 7.57 ped/m2 (with a maximum of (9.95)ped/m2). Additionally, the average crowd pressure peaked at 1,063 N/m (with a maximum of 1,961 N/m), and the maximum velocity entropy was 10.99. Based on these findings, it can be concluded that the primary causes of the disaster were the substantial population, bidirectional collision, and escalating panic. The results of controlled simulations under various management strategies are then presented. By implementing effective crowd management techniques, crowd safety can be enhanced through quantitative comparisons of these key indicators., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Liang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The present examination of mass and heat communication looks at the impact of induced magnetic field, variable thermal conductivity, and activation energy on the flow of second-order liquid across a stretched surface. The mass-heat transfer is also treated using the Model for generalized Fourier and Fick's Laws. The model equations are transformed as needed to produce a system of nonlinear ODEs, which are then numerically solved with the help of BVP4C integrated MATLAB approach. The heat-mass flow parameters are analyzed by the table and graphs. An increment in the estimations of 2nd grade fluid parameter (β) with magnetic field parameter (M) increase the speed sketch. For the stronger estimations of Schmidt number (Sc), parameter of magnetic field (M) and Eckert number (Ec) have the growing behavior on the temperature profile., Competing Interests: he authors have declared that no competing interests exist., (Copyright: © 2024 Nabwey et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Maintaining quality in software development projects is becoming very difficult because the complexity of modules in the software is growing exponentially. Software defects are the primary concern, and software defect prediction (SDP) plays a crucial role in detecting faulty modules early and planning effective testing to reduce maintenance costs. However, SDP faces challenges like imbalanced data, high-dimensional features, model overfitting, and outliers. Moreover, traditional SDP models lack transparency and interpretability, which impacts stakeholder confidence in the Software Development Life Cycle (SDLC). We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. The SPAM-XAI model exhibited improved performance after experimenting with the NASA PROMISE repository's datasets. It achieved an accuracy of 98.13% on CM1, 96.00% on PC1, and 98.65% on PC2, surpassing previous state-of-the-art and baseline models with other evaluation matrices enhancement compared to existing methods. The SPAM-XAI model increases transparency and facilitates understanding of the interaction between features and error status, enabling coherent and comprehensible predictions. This enhancement optimizes the decision-making process and enhances the model's trustworthiness in the SDLC., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Mustaqeem et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Urban last-mile express delivery in China encounters several challenges. This paper presents the establishment of a sharing logistics center aimed at enhancing the overall efficiency of urban last-mile express delivery while optimizing the utilization of essential resources. The successful implementation of shared delivery within sharing logistics center necessitates the creation of a robust collaborative mechanism. Recognizing that cooperative benefit allocation is dynamically influenced by factors such as resource input, operational efficiency, risk management, and other cost-related considerations, this study introduces a multi-weight H-Shapley value method for benefit allocation. By conducting empirical analyses of urban last-mile express delivery in Beijing within a sharing logistics service framework, our findings reveal that the revised benefit allocation model better aligns with the interests of participating entities and positively correlates with their contributions. Analyzing the impact of delivery volume and express operational costs changes, it is found that when the delivery volume and express operational costs of the sharing logistics center change, the benefits of participating enterprises move in the same direction. The benefit allocation model established in this study enriches the existing body of research in the field of shared delivery and offers valuable insights for benefit allocation issues that necessitate consideration of the dynamic effects of multiple parameter variations., Competing Interests: The authors declare no conflict of interest., (Copyright: © 2024 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In hot dry regions, photovoltaic modules are exposed to excessive temperatures, which leads to a drop in performance and the risk of overheating. The present numerical study aims to evaluate the natural air cooling of PV modules by an inclined chimney mounted at the back. The basic equations were solved using the finite volume method. The validity of the model is verified by comparison with the data available in the literature. Thermal and dynamic flow patterns are analyzed for a variety of parameters: Rayleigh numbers from 102 to 106, PV panel tilt angle from 15° to 90°, and channel aspect ratios from 1/20 to 1/5. A critical aspect ratio has been determined to minimize overheating of the PV module. According to the computational results, the tilt angle and modified Rayleigh number increase the mass flow rate and mean Nusselt number. The overheating zone with maximum temperatures is located in the upper part of the photovoltaic panel. The addition of an extension to both channel's inlet and outlet was found to improve the cooling of the photovoltaic panels; however, only the extensions downstream of the channel are truly effective. The critical lengths at which channel performance improves significantly were identified by examining the impact of longer extensions on channel performance. Increasing the extension length from 0 to 3H improves the mass flow rate by 65%, the average Nusselt number by 13.4%, and leads to an 11% decrease in maximum temperature when Ra* = 106. This cooling technique is particularly promising for hot dry regions where water is scarce., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Badi, Laatar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The unit commitment (UC) optimization issue is a vital issue in the operation and management of power systems. In recent years, the significant inroads of renewable energy (RE) resources, especially wind power and solar energy generation systems, into power systems have led to a huge increment in levels of uncertainty in power systems. Consequently, solution the UC is being more complicated. In this work, the UC problem solution is addressed using the Artificial Gorilla Troops Optimizer (GTO) for three cases including solving the UC at deterministic state, solving the UC under uncertainties of system and sources with and without RE sources. The uncertainty modelling of the load and RE sources (wind power and solar energy) are made through representing each uncertain variable with a suitable probability density function (PDF) and then the Monte Carlo Simulation (MCS) method is employed to generate a large number of scenarios then a scenario reduction technique known as backward reduction algorithm (BRA) is applied to establish a meaningful overall interpretation of the results. The results show that the overall cost per day is reduced from 0.2181% to 3.7528% at the deterministic state. In addition to that the overall cost reduction per day is 19.23% with integration of the RE resources. According to the results analysis, the main findings from this work are that the GTO is a powerful optimizer in addressing the deterministic UC problem with better cost and faster convergence curve and that RE resources help greatly in running cost saving. Also uncertainty consideration makes the system more reliable and realistic., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Rihan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Many real-world networks with Scale-Free structure are significantly vulnerable against both intentional attacks and catastrophic cascading failures. On the other hand, it has been shown that networks with narrower degree distributions have strong robustness of connectivity by enhancing loops. This paper numerically reveals that such networks are also tolerant against cascading failures. Our findings will be useful in designing stronger tolerant network infrastructures., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Kusunoki, Hayashi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Whether from environmental and occupational hazards or from topical pharmaceuticals, the human skin comes into contact with various chemicals every day. In vivo experiments not only require large investments of both time and money, but in vivo experiments can also be unethical due to the need to intentionally or incidentally expose humans or animals to toxic chemicals. Comparatively, in vitro experiments offer ethical and financial advantages when combined with the opportunity to selectively choose chemicals for experimentation. With in vivo experimentation being so infeasible, many scientists have chosen to make their in vitro data available publicly. Using these data, a detailed database containing 73 chemicals was created with a robust set of descriptors to be used in connection with mathematical modeling to predict diffusion, permeability, and partition coefficients. This resulting database is tailored to be easily used in various coding languages., (© 2024. The Author(s).)

Distributed power generation systems may necessitate connecting multiple independent energy sources that employ various converter topologies. A recent development in this field is the emergence of impedance source converters, offering the ability to deliver buck-boost functionality within a single stage. The split-source inverter (SSI) has been introduced as a novel choice in between this family. Many control strategies have emerged for electrical power systems control. Among the recent emerging controllers, model predictive control strategies have become an effective technique for control systems. Model predictive controllers (MPCs) offer a number of features compared to the conventional and counterpart models such as enhanced system response and improved system transients with reduced steady-state error. This research suggests a finite control-set MPC for three-phase single-stage SSI supporting a standalone load for remote area applications. Considering the proposed FCS-MPC, the output load current tracks its reference magnitude with minimized error. In addition, the proposed FCS-MPC enhances the proposed SSI system performance with a settling time of 10 μs, and approximately without overshoot in the output current. The system has been validated using Opal-RT OP-4510 and the power loss model of the inverter has been explained. In the end two comparisons have been presented to clarify the main points in the topology structure and the control technique., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Abdelaleem et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Due to the influence of coal rock shape, hardness, working environment and other factors in the cutting process of cantilever roadheader, the cutting head will produce irregular and violent vibration. As the rotary table of key stress components, its operation process stability, dynamic reliability and life affect the cutting efficiency and cutting stability of cantilever roadheader. In order to study the vibration characteristics of the rotary table in the cutting process, firstly, based on the theory of spatial force analysis and calculation, the spatial mechanical model of the rotary table of the cantilever roadheader is established. By solving the balance equation of the rotary table force system, the variation law of the load at the hinge ear of the rotary table with the cutting pitch angle and the horizontal angle is obtained. Secondly, based on the path transfer analysis method of working condition, the vibration data of cutting head, cutting cantilever, cutting lifting and rotary hydraulic cylinder under stable cutting condition are taken as input signals. By constructing the transfer path analysis model of rotary table working condition, the synthetic vibration of rotary table in cutting process is simulated, and the main vibration source of rotary table is determined. Then, the vibration contribution and contribution degree of each vibration excitation point to the hinge ear of rotary table are studied. By building a cutting test bench, the vibration response of rotary table in cutting process is tested to verify the correctness of the theoretical model.Thirdly, based on the frequency domain analysis method of random vibration fatigue life, combined with the S-N curve of the rotary table, the PSD curve at the maximum stress of the rotary table is obtained by modal excitation method, and the load data is imported into ANSYS nCode software to obtain the life cloud diagram and damage cloud diagram of the rotary table, and then the fatigue life of the rotary table under symmetrical cyclic load is solved. Finally, based on the response surface optimization analysis method, the maximum stress and maximum deformation of the rotary table are taken as the optimization objectives, and the aperture of each hinge ear of the rotary table is taken as the optimization variable. Based on Design Expert, a second-order regression model is established to realize the multi-objective optimization design of the key stress parts of the rotary table in the cutting process. The simulation results show that under the same cutting conditions, the maximum stress of the optimized rotary table is reduced by 15.82% year-on-year, and the maximum deformation is reduced by 24.70% year-on-year. The optimized rotary table structure can better adapt to the cutting process, which is beneficial to improve the service life of the rotary table and enhance its operation stability. The research results are beneficial to enrich the relevant research theory in the field of rotary table vibration of cantilever roadheader, and are beneficial to improve the service life of the rotary table and the efficiency of tunneling and mining., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Xie et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)