Modeling Analysis Research Articles

How does family support mitigate the impact of childhood adversity on adolescent mental health?

Abstract Background Childhood adversity is associated with increased risk of developing mental health problems over the life course. We investigated how family emotional support in adolescence may mitigate the impact of childhood adversity on adolescent mental health. Methods We used longitudinal data from the UK Millennium Cohort Study on 9,269 children followed to age 17 years. Individuals were assigned to exposure trajectories characterised using group-based trajectory models that included measures of poverty and family adversities (parental mental ill health, parental alcohol misuse and domestic violence) up to age 14 years. Using counterfactual causal mediation analysis and four-way decomposition modelling approach, we evaluated how perceived family emotional support at age 14 (measured using the three-item Short Social Provisions Scale) influences the association of childhood adversity trajectories on mental health at ages 14 and 17, assessing the relative contributions of mediation and interaction simultaneously. Results Compared with children experiencing low adversity and poverty, those exposed to childhood adversity were almost three times more likely to experience poor mental health (RR 2·99, 95% CI 2 ·41 to 3·57) at age 14 and age 17 (RR 2·58, 95% CI 2·09 to 3·06). Perceived emotional support mitigates up to 18% (95% CI: 9% to 26%) of this effect at age 14, and 13% (95% CI: 5% to 22%) at age 17, mainly due to interactive mechanisms. Conclusions Childhood adversity has a strong effect on mental health, which is partially mitigated by perceived family support in adolescence. Policies that support positive family functioning may be particularly beneficial for children who have experienced adversity. Key messages • Socio-economic – associated mental health problems in adolescence differed based on levels of family support. • Approximately 20% of the social inequality in mental health outcomes in adolescence may be mitigated or reduced by improving levels of family support.

Unveiling the germination patterns of Alternaria porri (Ellis) by using regression analysis and hydrothermal time modeling

Purple blotch disease is a major fungal disease of Allium cepa L. plants which is caused by the fungus Alternaria porri. The best conditions for the growth of Alternaria porri are temperatures between 22 °C and 25 °C and relatively high humidity. The Hydrotime, Thermal Time, and Hydrothermal Time models were used to measure different parameters of seed germination; therefore, we used them to measure the interactive effects of temperature and water potential on the germination conidia of Alternaria porri. The laboratory experiments were carried out at five constant temperatures, between 5 and 30 °C, and five different water potentials between 0 MPa and − 6 MPa. The germination of Alternaria porri conidia was highest at 25 °C and 0 MPa and lowest at 5 °C and − 6 MPa. The percentage of conidia germination decreased rapidly after 25 oC. Conidia germination was also affected by different water potentials, decreasing at lower water potential. Models based on HTT showed a reasonable fit to the germination and growth rate datasets. The best fitting model for conidia germination (R2 = 0.98491) was based on variable base and maximum temperature as a function of water potential. Based on the TT, HT, and models, the highest and lowest values for θT1 were observed at -6.0 MPa at 30 °C, and 0 MPa at 5 °C and the highest and lowest θT2 values were recorded at -6.0 MPa at 5 °C and 0 MPa at 30 °C while the lowest and highest θH values were recorded at -6.0 MPa at 5 °C and 0 MPa at 25 °C, respectively, for the HTT model, the predicted θHTT average value is 16.32 (MPa°Ch-1). Based on the statistical analysis, the cardinal hydrothermal time constant (θHTT) accurately explains the interactive effect of T and Ψ on the germination of Alternaria porri conidia under different environmental conditions.

Real-Time Road Safety: A Web and Mobile Application Approach to Mitigating Animal-Vehicle Conflicts in Sri Lanka

This research paper presents a pioneering web and mobile application aimed at mitigating the rising issue of animal-vehicle collisions in Sri Lanka, a concern that poses significant risks to both human safety and wildlife preservation. The application leverages a combination of knowledge-based case studies and crowd- sourcing techniques to enhance real-time road safety by identifying animal habitats and behaviors in proximity to users' locations. Through the web platform, users can input data on observed wildlife interactions and animal- vehicle conflicts, contributing to a comprehensive database for statistical analysis and predictive modelling. This information is used to generate real-time alerts and feedback, enabling drivers to take precautionary measures. The mobile application, utilizing geofencing and geotargeting technologies, provides real-time alerts, facilitates user feedback, and fosters community participation in ensuring safer roads. In addition to mitigating accidents, the application serves as an educational tool, offering guidelines and raising public awareness about the importance of road safety in areas rich in wildlife. By fostering a collaborative effort among users, this solution aims to reduce the frequency of animal-vehicle collisions, thereby promoting safer roads for both humans and animals in Sri Lanka.

Fibrinogen to pre-albumin ratio is an independent prognostic index for patients with pancreatic ductal adenocarcinoma after radical resection

BackgroundThis study aims to elucidate the significance of the preoperative fibrinogen to pre-albumin ratio (FPR) in predicting the prognosis of pancreatic ductal adenocarcinoma (PDAC), a correlation not extensively explored previously.MethodsA cohort of 563 patients diagnosed with PDAC and subjected to radical surgical resection was examined. We meticulously documented a range of inflammatory markers, clinical-pathological features, and oncological outcomes. The prognostic value of preoperative FPR was assessed using Kaplan–Meier survival analysis and Cox proportional hazards regression modeling. Furthermore, the predictive accuracy of FPR was evaluated through time-dependent receiver operating characteristic (ROC) curves and decision curve analyses (DCA).ResultsThe determined optimal threshold for FPR was 14.77, which facilitated the stratification of patients into groups with low and high FPR levels. Notably, patients in the high FPR cohort exhibited significantly reduced recurrence-free survival (RFS) and overall survival (OS) rates compared to their low FPR counterparts. Multivariate Cox regression analysis underscored FPR as an independent prognostic indicator for both RFS and OS. In comparison to the neutrophil-to-lymphocyte ratio (NLR), FPR demonstrated superior prognostic accuracy and clinical utility.ConclusionThe preoperative fibrinogen to pre-albumin ratio serves as an independent prognostic marker for RFS and OS among PDAC patients undergoing radical resection. Our findings suggest that FPR could be a valuable addition to the current prognostic models, potentially guiding therapeutic decision-making and patient management strategies in PDAC.

Mortality rate of percutaneous coronary interventions in st-segment elevation myocardial infarction patients under the public health insurance schemes of thailand

Abstract Background ST-elevation myocardial infarction (STEMI) presents a critical public health challenge internationally, including in Thailand. Currently, standard therapeutic interventions, particularly primary percutaneous coronary interventions (pPCI), are administered to Thai citizens. However, selected healthcare systems restrict access to specific pharmaceuticals and medical devices, causing inequalities in the quality of medical care amongst different healthcare systems. Such inequalities have the potential to significantly impact the quality of life of patients, particularly in the long term. Purpose The primary objective is to compare mortality rates within one year of STEMI patients after treatment with pPCI among the public health insurance schemes of Thailand. The secondary objective is to study prognostic determinants for one-year mortality rates among patients diagnosed with STEMI who have undergone pPCI. Methodology This study is a single-centre retrospective analysis of patients with STEMI treated with pPCI. It involves patients utilising various state health insurance schemes in Thailand from 1 January 2010 to 31 December 2020. Data collection occurred through the hospital's computerised management system and the registration administration office of the Department of Provincial Administration. The data analysis employed the Kaplan-Meier survival analysis, log-rank test, and Cox proportional hazards regression modelling method. Results The study involved 1,077 patients, categorised into three groups based on their state health insurance: Universal Health Coverage (UC) (546 patients, 50.7%), Social Security System (SS) (199 patients, 18.5%), and Civil Service Reimbursement (CS) (332 patients, 62.6%). The one-year mortality rates in these groups were 10.57%, 4.21%, and 6.47%, respectively (p=0.010). In the unadjusted model, the SS group showed a lower risk of one-year mortality rate (HR 0.38, 95% CI 0.18-0.80, p=0.011), and the CS group also demonstrated a lower risk (HR 0.59, 95% CI 0.35-0.99, p=0.047) compared to the UC group. In the adjusted model, only the CS group significantly reduced the risk of one-year mortality. Other factors that affected one-year mortality were age ≥65 years, a Killip score of 3-4, pre-discharge prescription of angiotensin-converting enzyme inhibitors, occlusion in the left anterior descending artery, and pericardial effusion. Conclusion Healthcare schemes play a significant role in influencing one-year mortality rates among STEMI patients treated with pPCI. The use of civil service reimbursement is a protective factor for the one-year mortality rate in STEMI patients. This information would be crucial for developing strategies and programs to aid healthcare policymakers at both regional and international levels in reducing morbidity and mortality.

Microcrediting and Investment Analysis in the Context of Environmental, Social, and Corporate Governance

This article is devoted to the analysis and development of ranking criteria for microcredit organizations to increase their investment attractiveness. The need to solve problematic issues is associated with the need to minimize risks before the start of the lending process through the correct selection of participants in the credit transaction. This study used the methods of content analysis and interpretation, correlation analysis and regression modeling, ranking, and clustering to assess the factors affecting the effectiveness of microcredit organizations. The most attention is paid to identifying key indicators that help improve the quality of financial services provided and their availability for various categories of borrowers. The results show that factors related to lending volumes and borrower characteristics have a significant impact on the quality of microcredit organizations. Of interest is the interpretation of classical financial indicators of microcredit organizations in the context of the principles of environmental, social, and corporate governance (ESG). The proposed approaches and conclusions can be used to improve the practice of microfinance and develop management and regulation strategies in this area.

Procollagen-lysine 2-oxoglutarate 5-dioxygenases are responsible for 5R-hydroxylysine modification of therapeutic T-cell bispecific monoclonal antibodies produced by Chinese hamster ovary cells

We present a detailed mass spectrometric analysis of three 2 + 1 T-cell bispecific monoclonal antibodies (TCB mAbs), where an unexpected +15.9950 Da mass shift in tryptic peptides was observed. This modification was attributed to the occurrence of 5R-hydroxylysine (Hyl) using a hybrid LC–MS/MS molecular characterization and CRISPR/Cas9 gene deletion approach. The modification was found at various sites within TCB mAbs, with a conspicuous hot spot motif mirroring a prior observation where Hyl was mapped to the CH1–VH Fab domain interface of IgGs. In contrast to the preceding report, our structural modeling analysis on TCB mAbs unveiled substantial differences in the orientation and flexibility of motifs in immediate proximity and across the artificial CH1–VL cross Fab interface and upstream elbow segment. Utilizing a hybrid database search, RNAseq, and a CRISPR/Cas9 knockout methodology in Chinese hamster ovary (CHO) production cell lines, procollagen-lysine, 2-oxoglutarate 5-dioxygenases (PLODs) were conclusively identified as the catalyzing enzymes accountable for the 5R-Hyl modification in TCB mAbs. To quantitatively inhibit Hyl formation in TCB mAbs, the activity of all three Chinese hamster PLOD isoenzymes needs to be depleted via CRISPR/Cas9 gene knockout. Moreover, our investigation identified cell culture iron availability, process duration, and clonal variability in CHO cells as elements influencing the levels of Hyl formation in TCB mAbs. This research offers a solution for circumventing Hyl formation in therapeutic complex mAb formats, such as TCB mAbs, produced in CHO cell culture processes, thereby addressing potential technical and biological challenges associated with unintended Hyl modification.

Cost-utility analysis for sublingual versus intravenous edaravone in the treatment of amyotrophic lateral sclerosis

BackgroundEdaravone has been widely used in amyotrophic lateral sclerosis (ALS) treatment, and a sublingual (SL) tablet has been developed to offer a more convenient alternative for injection. We present a cost-utility analysis to comprehensively evaluate the costs and health outcomes of oral and intravenous edaravone for the treatment of ALS in Chinese medical context.MethodsCost-utility analysis of SL tablets of edaravone versus intravenous edaravone at home was performed by constructing a 20-year Markov model of ALS stage 1–4 and death. The data were extracted from the literature with model assumptions. Typical sensitivity analysis and scenario analysis for administering SL tablets at home versus intravenous tablets at the hospital were performed.ResultsIn the base case analysis, with SL tablets and intravenous injections both at home, the model estimated an additional cost of ¥12,670.04 and an additional 0.034 QALYs over 20 years (life time) of modeling analysis, and the ICER was ¥372,648.24 per QALY. However, in the scenario of intravenous administration at the hospital, SL tablet was demonstrated dominance to intravenous injection.ConclusionsUsing 3 times the GDP per capita of China in 2023 as the threshold, the SL tablet edaravone was not cost-effective in the context of home treatment for both formulationst, but was dominance to intravenous injection in hospital treatment. The results highlighted the importance of treatment context for health economic analysis.

Altered cerebral oxygen extraction and metabolism in preterm neonates and the relationship to anemia: A noncontrast MRI study

AbstractObjectiveThe preterm brain is susceptible to structural injuries, which may be related to an imbalance between blood supply and oxygen metabolism. However, the effect of preterm birth on cerebral oxygen metabolism and its underlying mechanism have not been fully elucidated. The present study measured cerebral oxygen extraction and metabolism using noncontrast magnetic resonance imaging (MRI) methods in preterm neonates and examined its relationship with anemia of prematurity.MethodsFifty neonates with a gestational age of 28–42 weeks were enrolled. Cerebral oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2) were measured with T2‐relaxation‐under‐spin‐tagging (TRUST) MRI, together with cerebral blood flow (CBF).ResultsWe showed that CBF (p = 0.00021) and CMRO2 (p < 0.0001) increased with gestational age while OEF increased with postnatal age (p = 0.0013). Higher OEF was also associated with a higher Apgar score at birth (p = 0.039). Furthermore, hematocrit significantly mediates the increase of OEF with postnatal age (p < 0.001). Structural equation modeling analysis suggested a bidirectional relationship between CBF and CMRO2; both contributed to the changes in OEF.InterpretationThese findings demonstrated an altered cerebral oxygen metabolism in preterm brain, suggesting a potential role of MRI–based oxygenation measurement in the assessment of transfusion and intervention for preterm neonates.

Modeling of hybrid renewable resources and comprehensive feasibility analysis of grid interactive energy system for commercial building: a case study

ABSTRACT The growing energy demand in commercial buildings and businesses poses significant environmental challenges due to the dependence on fossil fuel-based energy. To address this issue, increasing the use of renewable energy sources and decreasing reliance on fossil fuels is crucial. Commercial buildings, in particular, have many opportunities to harness energy from renewable resources, such as solar, wind, and biomass. This study analyzed historical energy consumption data from a commercial building using MATLAB to forecast future energy demands. A range of machine learning algorithms were employed to accurately predict energy consumption, including Ensemble Boosting, Ensemble Bagging, Decision Trees, Support Vector Machines (SVM), and Neural Networks (NN). A Hybrid Renewable Energy (HRE) system was designed to meet the building’s energy needs, integrating renewable sources with grid-interactive inverters. Performance metrics for the forecasting models were calculated and documented, followed by a detailed techno-economic and environmental feasibility analysis of the HRE system. Different levels of renewable energy penetration were explored to optimize HRE designs using load-following dispatch algorithms tailored to the commercial building’s specific needs. The study revealed that achieving a renewable energy proportion of 12.6% resulted in the lowest cost of electricity (COE) at $0.135 and a Net Present Cost (NPC) of $8.84 million. Additionally, a reliability study using load flow techniques confirmed the stability of the optimized Hybrid Renewable Energy system. The energy costs for varying levels of renewable penetration, ranging from 10% to 40% is also explored in this research. In summary, transitioning to renewable energy sources in commercial buildings can reduce environmental impact while ensuring a sustainable energy supply.

The LTAR Croplands Common Experiment at the Gulf Atlantic Coastal Plain.

The Gulf Atlantic Coastal Plain (GACP) Long-Term Agroecosystem Research (LTAR) Network site is characterized by hot and humid summers with low gradient stream channels surrounded by wetland forests and croplands. Beneath its sandy soils, a confining layer stifles recharge to the deeper aquifer system, so a substantial proportion of streamflow is driven by shallow subsurface baseflow. Agricultural practices in the area consist of forage and livestock production, forestry, and rotational cropping systems dominated by cotton (Gossypium hirsutum) and peanut (Arachis hypogaea). Certain factors impose challenges to the viability of GACP agricultural systems, like changing economics and demographics, as well as pest and disease pressures. The GACP communicates with stakeholders from various backgrounds, who provide their perspectives as agricultural research service scientists execute their research plans. The GACP LTAR common experiment (CE) is carried out via plot- and field-scale studies. The plot-scale CE compares prevailing practices, determined from regional data, with an alternative treatment including winter covers, such as the biofuel feedstock carinata (Brassica carinata, A. Braun), to provide both economic and environmental benefits. The field-scale CE is observational; key variables are monitored for two farms where management practices largely emulate the prevailing treatment. Data collection efforts quantify vegetation, hydrology, soils, and climate data to produce datasets for modeling and statistical analysis. Research teams quantify relationships between land management, environment, and socioeconomic benefits. Ultimately, the GACP LTAR site works to facilitate agricultural system health and wellbeing at local, regional, and national scales by providing long-term science-based solutions.

The Influence of Human Resource Development, Leadership Style, and Competence on the Performance of the Mediating Role of Service Quality

This study aimed to determine the effect of HR Development, Competence, and Leadership Style on Service Quality and teacher performance at SMP and SMA IT AL Utsmani Bangkinang. A questionnaire is used to collect data in this research. The population in this study were all teachers at SMP and SMA IT AL Utsmanai Bangkinang with 81 teachers. The sample of this study used the census method with PLS 3.0 Structural Equation Modeling (SEM) analysis. The results showed that HR development had a positive and insignificant effect on Service Quality. The results showed that HR development had a positive and insignificant effect on Service Quality, Competence had a positive and significant effect on Service Quality, Leadership Style had a positive and significant effect on Service Quality, and Human Resources Development had a positive and significant effect on performance.

Impacts of the coexistence of polystyrene microplastics and pesticide imidacloprid on soil nitrogen transformations and microbial communities

The pollution of agricultural soils by microplastics (MPs) and pesticides has attracted significant attention. However, the combined impact of MPs and pesticides on soil nitrogen transformation and microbial communities remains unclear. In this study, we conducted a 28-day soil incubation experiment, introducing polystyrene microplastics (PS-MPs) at concentrations of 0.1% and 10% (w/w) and pesticide imidacloprid at concentrations of 0.1 mg/kg and 1.0 mg/kg. Our aim was to investigate the individual and combined effects of these pollutants on nitrogen transformations and microbial communities in agricultural soils. Imidacloprid accelerated the decline in soil pH, while PS-MPs slowed the process. Imidacloprid hindered soil nitrification and denitrification processes, however, the presence of PS-MPs mitigated the inhibitory effects of imidacloprid. Based on microbial community and functional annotation analyses, this is mainly attributed to the different effects of PS-MPs and imidacloprid on soil microbial communities and the expression of key nitrogen transformation-related genes. Variance partitioning analysis and partial least squares path modeling analyses revealed that PS-MPs and imidacloprid indirectly influenced the microbial community structure, primarily through changes in soil pH. This study elucidates the mechanism through which the combined stress of MPs and pesticides in agricultural soils influence soil nitrogen transformation and microbial communities. The findings offer valuable insights for the systematic evaluation of the ecological risks posed by the coexistence of these pollutants.

Self-confidence as a mediator in the relationship between executive functioning and depression among ICU survivors: a latent variable analysis

BackgroundExecutive dysfunction and depression are common among ICU survivors, yet the mechanisms linking these two factors remain poorly understood. Self-confidence has been implicated as a key mediator in the relationship between cognitive impairments and mental health outcomes. This study aimed to explore the mediating role of self-confidence in the association between executive functioning and depression in ICU survivors.MethodA provisional questionnaire was used in a cross-sectional study to assess quality of life in 395 adult ICU survivors, each with a minimum 72-h stay at one of three ICUs at a Swedish university hospital, six months to three years post-discharge. Responses to questions on executive function, self-confidence, and depression were analysed. Structural equation modelling and confirmatory factor analysis were employed to examine the mediating effect of self-confidence on the relationship between executive function and depression. Model fit was evaluated using established indicators. Reliability of the measures was assessed using McDonald’s Omega and Cronbach’s Alpha.ResultsA significant positive correlation was found between depressive symptoms and both diminished self-confidence (r = 0.80, p < 0.001) and poorer executive function (r = 0.55, p < 0.001). Additionally, a correlation was observed between reduced self-confidence and compromised executive function (r = 0.62, p < 0.001). Age was negatively associated with depression, self-confidence, and executive function, while male gender was positively correlated with higher self-confidence.Mediation analysis revealed that the effect of impaired executive function on depressive symptoms was fully mediated by diminished self-confidence (B = 0.45; 95% CI 0.34–0.59). The direct effect of executive function on depression became non-significant when self-confidence was included in the model (B = 0.07, p = 0.18), suggesting complete mediation. The overall model fit was satisfactory (CFI = 0.962; RMSEA = 0.075), highlighting the robustness of the mediation pathway.ConclusionsSelf-confidence mediates the relationship between executive function and depression among ICU survivors. Interventions aimed at enhancing self-confidence could mitigate depressive symptoms in the ICU survivor population. Longitudinal studies are needed to confirm these findings and further explore the causal pathways involved.Trial registration ClinicalTrials.gov Ref# NCT02767180; Registered 28 April 2016.

Exploring the drivers of experience intentions to co-create value among quarantine greenhouse customers

ABSTRACT Exactly how the quarantine greenhouse creates good quality service experiences has attracted the attention of scholars and practitioners. Some scholars advocate decreasing perceived threats to increase experience intentions to co-create value. However, recent research has not examined quarantine greenhouse service, and a detailed understanding of its potential effects on the customer meal experience and their experience intentions to co-create value is needed. Consequently, this study of the effects of perceived threats on experience intentions to co-create value through post coronavirus disease 2019 (COVID-19) protective behaviors and experience relationship outcomes constructed a comprehensive framework via a literature review. A survey was carried out with respondents who had dined at one quarantine greenhouse in Amsterdam, obtaining 482 valid samples which were analyzed with confirmatory factor analysis and structural equation modeling. The results of this study will also assist quarantine greenhouse management in developing and implementing market-oriented service strategies to decrease the dimensions of perceived threats, increase the dimensions of COVID-19 protective behaviors and experience relationship outcomes, and create experience intentions to co-create value. The theoretical and managerial implications of these results are discussed.

Technology-assisted instruction with teacher prompts on fraction multiplication word problems: A single-case design with visual analysis and Bayesian multilevel modeling

ABSTRACT This study examines the effects of technology-assisted instruction with teacher prompts on the ability to visualize and solve fraction multiplication word problems for four middle school students with learning disabilities. A multiple-probe design across participants, a type of single-case design, showed a functional relationship between the intervention and the targeted mathematical outcomes. Although there were some fluctuations over time, students demonstrated improvements from the baseline to intervention phases (Tau ranged from 0.76 to 1.00 for visualization and was 1.00 for problem-solving). Researchers employed Bayesian cumulative link mixed effects models to examine the moderating effects of word problem question types. Students showed greater maintenance effects on problem-solving than on visualization tasks, as reflected in changes in level (logit coefficient = 2.6) and trend (logit coefficient = 0.22). Students and teachers perceived vocabulary and multiplication fact practices, as well as the cognitive and metacognitive features embedded in the technology-assisted intervention, to be useful in learning targeted mathematics concepts. This study underscores the role of technology integration in enhancing teachers’ instructional approach and in aiding students’ acquisition and retention of mathematical concepts and skills.

Spatial analysis and soft computational modeling for hazard assessment of potential toxic elements in potable groundwater

Swiftly increasing population and industrial developments of urban areas has accelerated the worsening of the water quality in recent years. Groundwater samples from different locations of the Doon valley, Garhwal Himalaya were analyzed to measure concentrations of six potential toxic elements (PTEs) viz. chromium (Cr), nickel (Ni), arsenic (As), molybdenum (Mo), cadmium (Cd), and lead (Pb) using Inductively Coupled Plasma Mass Spectrometer (ICP-MS) with the aim to study the spatial distribution and associated hazards. In addition, machine learning algorithms have been used for prediction of water quality and identification of influencing PTEs. The results inferred that the mean values (in the units of µg L−1) of analyzed PTEs were observed in the order of Mo (1.066) > Ni (0.744) > Pb (0.337) > As (0.186) > Cr (0.180) > Cd (0.026). The levels and computed risks of PTEs were found below the safe limits. The radial basis function neural network (RBF-NN) algorithms showed high level of accuracy in the predictions of heavy metal pollution index (HPI), heavy metal evaluation index (HEI), non-carcinogenic (N-CR) and carcinogenic (CR) parameters with determination coefficient values ranged from 0.912 to 0.976. However, the modified heavy metal pollution index (m-HPI) and contamination index (CI) predictions showed comparatively lower coefficient values as 0.753 and 0.657, respectively. The multilayer perceptron neural network (MLP-NN) demonstrated fluctuation in precision with determination coefficient between 0.167 and 0.954 for the prediction of computed indices (HPI, HEI, CI, m-HPI). In contrast, the proficiency in forecasting of non-carcinogenic and carcinogenic hazards for both sub-groups showcased coefficient values ranged from 0.887 to 0.995. As compared to each other, the radial basis function (RBF) model indicated closer alignments between predicted and actual values for pollution indices, while multilayer perceptron (MLP) model portrayed greater precision in prediction of health risk indices.

Navigating the social media landscape: unraveling the intricacies of safety perceptions

The emergence of social media has greatly enriched the channels and sources of information through which individuals interact. However, there remains a lack of empirical research on its actual impact on personal safety. This study employed both Structural Equation Modeling (SEM) and network analysis to explored the mechanisms by which social media engagement affects safety perceptions. Additionally, it examined gender differences from both micro-level perspectives (including general trust and perceived social support) and macro-level viewpoints (including personal belief in a just world). The findings revealed that perceived social support, general trust, and personal belief in a just world played a fully mediating role. A multi-group analysis indicated that males were more susceptibility to the influence of social media engagement, with their general trust exhibiting negligible impact on perceived safety. Consequently, this study argues that attention should be given not only how social media affects personal beliefs and safety perceptions, but also its impact on behavioral outcomes.

Dynamic Optimization of Exclusive Bus Lane Location Considering Reliability: A Case Study of Beijing

For metropolises like Beijing, heavy congestions cause transit passengers’ unreliable travel time, including in vehicle time and waiting time. Comparing with other managerial measures, designing a lane for bus use only is an effective method to improve travel reliability, for it can eliminate the influence on bus-driving conditions. This paper proposes a reliable and practical method to determine exclusive bus lanes (EBL). A reliability-based optimization model is established, in which the tradeoff among bus and private car passengers’ travel time, reliability, and EBL construction cost are considered. Based on the actual network, a user equilibrium demand assignment model is applied to estimate the dynamic bus flow distribution. Since the model is nonlinear, a two-step method is proposed where tangent lines are introduced to constitute an envelope curve to linearize the model. This work conducts the statistical modeling and fitting analysis with actual bus trajectory data, collected on EBL in Beijing during peak hours. Passenger travel time distributions are fitted to estimate the statistical passenger travel time; Lognormal distribution and Gaussian distribution are the best fit. The optimization results indicate that the passenger travel time reliability can be improved by 5.5% by the optimized EBL location scheme. This study will provide a theoretical basis and methodological support for improving the service level of the public transportation system in large cities through the scientific planning of exclusive bus lanes.

Local structure of Amorphous carbon investigated by X-ray total scattering and RMC modeling

Amorphous carbon is a promising candidate as an energy storage material. In this paper, we performed an X-ray total scattering measurement, RMC modeling, and persistent homology analysis for amorphous carbon samples fabricated at two different heat treatment temperatures. According to the analysis of the nearest-neighbor carbon atoms and their angular histogram, the sample treated at higher temperature shows higher connectivity between carbon atoms than that treated at lower temperature. Furthermore, topological data analysis (persistent homology, PH) reveals quantitative results that relate ring structure and the connectivity between carbon atoms.