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Phthalate esters (PAEs) are an emerging pollutant due to widespread distribution in environmental mediums that have attracted widespread attention over recent years. However, there is little information about tea plantation soil PAEs. A total of 270 soil samples collected from 45 tea plantations in the major high-quality tea-producing regions of Jiangsu, Zhejiang, and Anhui provinces in China were analyzed for seven PAEs. The detection frequency of PAEs in tea plantation soil was 100%. DBP, DEHP, and DiBP were the main congeners in tea plantation soil. The PAEs concentrations in the upper soil were significantly higher than those in the lower soil. The concentration of tea plantation soil PAEs in Jiangsu Province was significantly lower than those in Zhejiang and Anhui provinces. Intercropping with chestnuts can effectively reduce the contamination level of PAEs in tea plantation soil. Correlation analysis, redundancy analysis, partial correlation analysis, and structural equation modeling methods further confirmed the strong direct influence of factors such as chestnut–tea intercropping, temperature, and agricultural chemicals on the variation of PAEs in tea plantation soil. The health and ecological risk assessments indicated that non-carcinogenic risk was within a safe range and that there was a high carcinogenic risk via the dietary pathway, with DBP posing the highest ecological risk.

Background Previous studies have found associations between monocyte count, high-density lipoprotein cholesterol (HDL-C), and thyroid-stimulating hormone (TSH) with acute coronary syndrome (ACS). However, research on the correlation between the monocyte count to high-density lipoprotein cholesterol ratio (MHR) and the onset of ACS is limited. The association between MHR, TSH, and the onset of ACS in postmenopausal women remains unclear. Objective To explore the predictive value of MHR and TSH for the onset of ACS in postmenopausal women and to investigate the correlation between these indicators and the degree of coronary artery stenosis in patients. Methods A total of 325 postmenopausal women hospitalized in the Department of Cardiology at Northern Jiangsu People's Hospital, from 2020 to 2021 and who underwent coronary angiography were selected as the study subjects. Patient general information was collected through the electronic medical record system. Venous blood was collected upon admission to measure monocyte count, total cholesterol (TC), triglycerides (TG), HDL-C, low-density lipoprotein cholesterol (LDL-C), and TSH. Left ventricular ejection fraction (LVEF) was measured using the biplane Simpson method, and coronary artery lesions were observed through coronary angiography. The Gensini scoring system was used to uniformly measure the extent of coronary artery lesions. Patients meeting the diagnostic criteria for ACS were classified as the ACS group (n=184), and non-ACS patients as the control group (n=141). The ACS group was further divided into subgroups based on the tertiles of the Gensini score: ≤36.5 as the low-risk subgroup (n=59), 36.6-66.5 as the moderate-risk subgroup (n=64), and >66.5 as the high-risk subgroup (n=61). Univariate and multivariate Logistic regression analyses were used to explore the influencing factors of ACS. The receiver operating characteristic (ROC) curve was plotted to evaluate the diagnostic value of TSH, MHR, and combined detection for ACS and to calculate the area under the curve (AUC). Spearman's rank correlation analysis was used to explore the correlation between TSH, MHR, and combined detection indicators with the Gensini score. Results The baseline data of patients in the ACS and control groups showed that BMI, smoking rate, hypertension, diabetes, LDL-C, monocytes, TSH, and MHR in the ACS group were higher than in the control group, while LVEF and HDL-C were lower (P

Automated, secure software development is an important digitalization task, solved with the DevSecOps approach. An important part of the DevSecOps approach is continuous risk assessment, which is necessary to identify and evaluate risk factors. Combining the development cycle with continuous risk assessment creates software development and operation synergies and minimizes vulnerabilities. The article presents the main methods of deploying web applications and ways to increase information security at all stages of product development. It also compares different types of infrastructures and cloud computing providers and analyzes modern tools used to automate processes. The cloud cluster was deployed using Terraform and the Jenkins pipeline, written in the Groovy programming language, which checks program code for vulnerabilities and allows you to fix violations at the earliest stages of developing secure web applications. The developed cluster implements the proposed algorithm for automated risk assessment based on the calculation (modeling) of cloud infrastructure threats and vulnerabilities, which operates in real-time, periodically collecting all information and adjusting the system according to the risk and applied controls. The algorithm for calculating risk and losses is based on statistical data and FAIR information risk assessment methodology. The risk value obtained using the proposed method is quantitative, which allows more efficient forecasting of information security costs in software development.

China is one of the countries in the world with the most frequent occurrence of continental earthquakes and the greatest impacts of earthquake disasters. In particular, the Qinghai-Tibet Plateau is a region characterized by a wide spatial distribution of continental earthquakes, shallow epicenters, complex seismic origins, and significant disaster losses, making it highly susceptible to seismic events. The need for seismic geological survey is becoming increasingly urgent in this area. Based on regional geological eological data，high-precision satellite remote sensing images and DEM elevation data，this paper interprets the active faults in the region of Xigaze. The results show that the active faults in the Xigaze area are mainly concentrated in the rift valleys and their periphery, with tectonic activity varying spatially. The tectonic activity of active faults in the eastern rift is stronger than that in the western rifts. Additionally，the tectonic activity of active faults in each rift also shows a clear segmentation feature. At the same time, this paper comprehensively considers the characteristics of active faults, topography and geomorphology and stratigraphic lithology in the Xigaze area. It preliminarily evaluates the potential risk of earthquake disasters in 204 towns under its jurisdiction. The results show that there are 57 towns with “extremely high risk” “high risk” and “high-medium risk” of earthquake disasters, accounting for about 28% of the total number of towns in the region.

Objective To conduct hazard vulnerability analysis(HVA) in a blood bank, aimed to identify high-risk events and optimize emergency management measures. Methods The risk event evaluation index system was established by referring to the Kaiser model and the situation of Guangzhou Blood Center, and risk events were ranked by risk matrix and Borda count. Results The top five events with the highest risk values identified by Kaiser model were information system emergencies (39.61%), extreme weather (38.03%), major public sentiment (37.86%), public health events (37.37%) and policy changes (37.24%). The results of risk matrix and Borda count revealed 1 extremely high-risk indicator as information system emergency, 5 high-risk indicators with the highest risk being major public sentiment, 11 medium-risk indicators with the highest risk being major medical disputes and 1 low-risk indicator as external fires. Conclusion Conducting HVA in combination with the actual situation of blood banks can effectively identify high-risk events and provide theoretical basis for improving emergency management measures.

Abstract The educational landscape of toxicology is increasingly integrating computational methodologies due to ethical concerns about animal testing and advancements in biotechnological and data analysis tools. This paper examines the evolution and significance of the Toxicology in the 21st century (Tox21) initiative and its impact on computational toxicology education. It contrasts computational toxicology with traditional methods, highlighting the limitations of conventional approaches and the new perspectives offered by computational techniques. The study emphasizes the importance of incorporating computational toxicology into curricula, including case studies that demonstrate how this integration enhances students’ problem-solving abilities, real-time data analysis skills, and innovation capabilities. Furthermore, it outlines effective teaching content and methods, including software tools, online resources, and academic literature. The paper also addresses the challenges and limitations faced in this educational shift and explores prospects for advancing computational toxicology education. By documenting these developments, the study aims to clarify the current advancements in toxicology education and the preparedness of students to address global chemical safety challenges with innovative solutions.

Abstract Background Globorisk is one of the prediction tools for 10-year risk assessment of cardiovascular disease, featuring an office-based (non-laboratory-based) version. This version does not require laboratory tests for determining the CVD risk. The present study aims to determine the 10-year CVD risk using the office-based Globorisk model and factors associated with the 10-year CVD risk. Methods In this study, baseline data from 6810 individuals participating in the Fasa cohort study, with no history of CVD or stroke, were utilized. The risk equation of the office-based Globorisk model incorporates age, sex, systolic blood pressure (SBP), body mass index (BMI), and smoking status. The Globorisk model categorizes the risk into three groups: low risk (

Extended Abstract Background: Human activities, climate variability, and environmental stress have strongly affected forest ecosystems worldwide. Forest fires are among the major factors of global ecosystem destruction. Fires in the forest, whether of human or natural origin, have been raised as a serious crisis in recent years. Hence, fire risk assessment plays an important role in forest fire management because knowing where the highest risk is essential to minimize threats to resources, lives, and property. Integration of spatial information from different sources using statistical analysis in the GIS environment is a suitable tool for managing and spreading forest fires, which is one of the main natural hazards in northern Iran. Therefore, it is necessary to prepare a fire risk assessment map for the planning and protection of forests. Methods: The current practical research concerning its nature is a combination of documentary, descriptive, and quantitative model-based methods regarding the research method. In this study, fuzzy and hierarchical (AHP) logic models were combined to investigate the risk of forest fire in Mazandaran province in five classes, very high, high, medium, low, and very low, respectively, using four main criteria and nine sub-criteria, namely topography (height, slope, direction, and rivers), climatic factors (peak temperature and precipitation), human factors (residential areas and the network of communication roads), and biological factors (vegetation). To obtain the net vegetation cover, the Normalized Difference Vegetation Index (NDVI) was applied to the Sentinel-2 satellite image set in a 5-year period (2017-2022) in the GEE web system. The height, slope, and slope direction maps of the study area were prepared from the digital elevation model (DEM) of 12.5 m from the ALOS AVNIR-2 dataset. The distance from rivers, residential areas, and the road network was calculated using the Euclidean distance tool in ArcMAP software. The geographic location of meteorological synoptic stations was obtained from the Meteorological Organization, and its information was used as meteorological input data. In the ArcMap environment, a map of average annual precipitation and maximum temperature was prepared from synoptic stations through interpolation for the period from 2007 to 2021. Based on this modeling method, experts' opinions were used for the relative importance and priority of criteria and sub-criteria in the risk of forest fire in the study area to obtain the fuzzy weight of criteria and sub-criteria. Based on the weighting coefficients applied in the present plan, the final weights of the criteria and sub-criteria affecting forest fire from the highest to the lowest weights belong to the topographical, biological, climatic, and human criteria. Among the sub-criteria, the highest and lowest weights belong to vegetation and slope, respectively. The consistency rate (CR) for the matrices of the affecting factors is equal to 6.25%, which is less than 10%, actually indicating that the weight of the criteria is proportionate and reliable. The highest weights were obtained for the vegetation cover and the slope direction, and the lowest weights belonged to the distance from the river and the slope. Finally, the fire risk assessment map was prepared by combining the fuzzy maps of the sub-criteria in GIS. Results: Overall, medium to very high fire risk potential was found in 72% of the studied area. From a total area of about 2373189 hectares, very low (8.4%), low (18.3%), medium (23.66%), high (25.62), and very high (24%) vulnerability rates were identified in Mazandaran province. Higher fire potential was detected in the East and Southeast parts than in other parts of the study area. The aforementioned fuzzy layers clearly show that the height, slope, and amount of precipitation are low and the density of residential areas and the network of communication roads are high in these parts, with high temperatures. In fact, these factors have increased the risk of fire in these areas. In the present study, the highest fire potential was observed at low altitudes, which could have resulted from the concentration of human activities at low altitudes. Moreover, most fires occurred on low slopes in the studied area. The distance layer from waterways also plays a dual role in the occurrence of fire. The results of the model show an inverse correlation between the distance from roads and fire potential. Based on the results of the fuzzy AHP model, the probability of fire increased with the decrease in precipitation and the increase in annual temperature. A decrease in the amount of precipitation causes a decrease in soil moisture and vegetation, elevating the possibility of fire. On the other hand, the increase in temperature causes the drying of vegetation and reduces humidity, thereby increasing the possibility of fire. Conclusion: It can be concluded that preparing a fire risk assessment map can help managers and planners in identifying areas with high potential and in crisis management in vulnerable areas. The obtained fire risk assessment map can be used as a decision-making support system to predict future fires in the study area.

Shang-Yu Lu,1,* Han-Yao Sun,1,* Yan Zhou,2 Xi Luo,3 Sheng Liu,1 Wei-Zhong Zhou,1 Hai-Bin Shi,1 Wei Yang,1 Wei Tian1 1Department of Interventional Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People’s Republic of China; 2Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People’s Republic of China; 3The First Affiliated Hospital of Soochow University, Suzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wei Yang; Wei Tian, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, 210029, People’s Republic of China, Tel +86-18705164897 ; +86-13770615508, Email youngwei1988@163.com; tianwei@jsph.org.cnPurpose: Hepatocellular carcinoma (HCC) represents a significant global health problem, requiring precise prognostic tools for optimal treatment stratification. This study aimed to develop a new risk prediction score, called AD score, based on the serum markers alpha-fetoprotein (AFP) and des-γ-carboxy prothrombin (DCP), to offer an objective and accurate preoperative assessment of HCC in patients undergoing transarterial chemoembolization (TACE).Patients and Methods: This was a retrospective study that included 295 HCC patients who were subjected to TACE (training set, n=147; testing set, n=148). Serum AFP and DCP levels were log-transformed to construct the AD score. Multivariate Cox regression analysis on cirrhosis subgroups validated the objectivity of the model. Performance comparison of established models (Child Pugh, BCLC, ALBI, Up-to-seven, Six-and-twelve, Four and seven, HAP score, mHAP-II, FAIL-T score), was assessed through time-dependent receiver operating characteristic (ROC) curves and risk stratification.Results: The AD score, incorporating lgAFP and lgDCP, demonstrated superior predictive accuracy than the existing models. Time-dependent ROC curve revealed the consistent superiority of the AD score over a 5-year period. The risk stratification into low, intermediate, and high group based on the AD score showed a significant survival difference in both training and testing set.Conclusion: For HCC patients undergoing TACE, the AD score serves as an objective and straightforward prognostic tool, enhancing predictive accuracy and showcasing its clinical utility. It demonstrates potential significance as a crucial addition to preoperative risk assessment for TACE.Keywords: hepatocellular carcinoma, transarterial chemoembolization, prognostic model, risk assessment, AD score

Idiopathic nephrotic syndrome （INS） is the most common and challenging glomerular disease in childhood and most children respond favorably to glucocorticoid therapy. However， up to half of INS patients present with steroid-dependent or frequently-relapsing nephrotic syndrome so that selecting proper treatment regimens has remained one great clinical challenge. Rituximab （RTX） for nephrotic syndrome is generally efficacious. However， clinical outcomes vary greatly at different centers. This review summarized the effectiveness and risk of different RTX protocols for children with steroid-dependent or frequently-relapsing nephrotic syndrome.

Objective: to perform a comprehensive analysis of the clinical, functional and hemodynamic status of patients with idiopathic pulmonary hypertension (IPAH) to compare the "portrait" of historical and modern subgroups. Materials and methods. The study included 120 patients with IPAH observed in the Department of Pulmonary Hypertension and Heart Diseases, E.I. Chazov National Medical Research Center of Cardiology. The pts were divided into 2 subgroups depending on the time of diagnosis and were comparable in terms of the initial functional class (WHO). A comparative analysis of clinical, functional, and hemodynamic parameters was carried out. The diagnosis was established according to the algorithm of the Eurasian (2019) and Russian guidelines for the diagnosis and treatment of pulmonary hypertension (PH) (2020). Results. The median time from the onset of PH symptoms to diagnosis in the historical and modern cohorts was 24 months and 13.5 months, respectively, and from the first visit to the diagnosis of IPAH – 13 months and 3.5 months. The median age of patients was 31 years and 40.5 years. In both subgroups, the number of women dominated – up to 86.6 % of patients in the modern cohort. Clinical, laboratory, functional and instrumental tests did not differ significantly between the subgroups. In the structure of concomitant pathology, comorbidity with cardiovascular pathology is most common, in a larger percentage in the modern cohort of patients: hypertension – up to 31.6 %, obesity – up to 25 % and diabetes mellitus – up to 5 %. According to various risk assessment scales, most patients in both subgroups demonstrated intermediate risk at the time of diagnosis, but in the modern cohort, a large proportion of high-risk patients was noted (20.0 %). Conclusion. Nowadays, IPAH remains a late-diagnosed disease, which contributes to a later treatment prescription. The clinical "portrait" of patients with IPAH has changed over the years towards older and more comorbid patients, especially with cardiovascular diseases. Timely detection and treatment of concomitant pathology, timely risk assessment are the key to prescribing the most effective treatment regimens, improving the quality of life and prognosis of patients with IPAH.

The management of socio-economic infrastructure projects in developing countries, including roads, bridges, tunnels, railways, ports, airports, dams and others, presents multifaceted challenges, particularly in environments marked by complexity and uncertainty. Despite the efforts of governments in these countries, these types of projects still face numerous risks, including political, technological, regulatory, financial, and market risks. The objective of the study was to examine the practices related to the problem of the decision-making process and risk assessment in the management of socio-economic infrastructure projects in developing countries, focusing on the example of the Algerian experience. This research used a qualitative analysis of the decision-making process through 15 semi-structured interviews conducted with representatives of various institutions and administrations responsible for supervising the East-West highway project in Algeria and several focus groups conducted or observations noted at the meetings where the author participated as a principal engineer at the Ministry of Public Works (project owner) during the different phases of the implementation of this mega-project. This made it possible to carry out a global assessment of current practices and to identify the major risks that can impact the decision-making process to improve the management of socio-economic infrastructure projects in Algeria and also in developing countries. The results of the study reveal the risks related to the complexity of the external and internal environment of the projects, in which among the 13 major risks identified, 61.54% have a high criticality, 30.77% have a medium criticality, and 7.69% have a low criticality. The results show that several important aspects need to be improved, including: 1) strengthening financial stability; 2) political risk mitigation; 3) implementing economic stability measures; 4) clarifying contractual aspects; 5) promoting cultural sensitivity and communication; 6) improving cost and quality control measures. This study provides valuable guidance to governments, businesses, managers, and other individuals or groups interested in promoting the management of socio-economic infrastructure projects in developing countries.

Objective. The study examined the main aspects of building an information security system from the point of view of optimizing the resources spent and funds to ensure information security. Method. In this subject area, the possibilities of structural-parametric models and Markov chains for identifying the optimal line for constructing a multi-level information security system are considered. Practice shows that the construction and implementation of a multi-level information security system reduces the possibility for an attacker of compromise and unauthorized access to protected information. Result. An analysis of the functionality of the constructed models was carried out as a means of finding the optimal way to build an information security system. An assessment of information security risks was carried out at the most vulnerable points in the information security processes. An approach to building a multi-level information security system using the functionality of structural-parametric models and Markov chains has been developed and proposed. A pattern has been formulated that makes it possible to determine the correctness of the constructed information security system based on the analysis and assessment of information security risks at the most vulnerable points of a multi-level information security system, in the process of transition from one state to another. Conclusion. Ensuring information security using mathematical modeling methods is a relevant and valuable tool based on the dynamism of threats and their uncertainty at different periods of time. The development, testing and implementation of new approaches based on modeling allows us to predict and prevent the most likely actions and steps of an attacker, thereby reducing the level of risk and possible damage to protected information resources and systems.

Introduction: Fire safety in healthcare centers is crucial due to the limited evacuation capacity of the occupants and the necessity of not disrupting the operation in these centers. In this study, the fire risk of a public hospital was evaluated using the Fire Risk Assessment Method for Engineering (FRAME). Additionally, the factors affecting fire safety in the hospital were analyzed quantitavely, and fire control strategies were presented. Material and Methods: First, the fire risk assessment checklist was filled in all the hospital departments. Then, the values of the factors affecting fire safety were obtained. In the next step, the fire risk for the building, occupants and activities were estimated using Excel software-FRAME. Finally, control strategies and intervention measures were presented based on the value of these factors. Results: In the hospital under study, 22% of the departments posed an undesirable fire risk to the building and its property. On the other hand, 90% of the departments had risk levels that were undesirable for the occupants. The results of the initial risk (R0) showed that a balance between potential fire risk and risk acceptance can be established by implementing manual fire extinguishing systems and automatic detectors in all departments. Conclusion: ased on the condition of the hospital studied, a balance between potential fire risk level and risk acceptance level was not established. Therefore, there is a need for fire control measures, especially fire safety measures for the occupants. The results of this study can be useful for readers and experts in interpreting fire risk assessments and presenting detailed control measures based on the risk assessment and the value of the parameters.

Abstract The presence of BTEX (Benzene, Toluene, Ethylbenzene, and Xylene) compounds in beauty salons has raised concerns about potential health risks. This study aimed to measure the levels of BTEX compounds in the air of beauty salons in Lahijan, Iran and assess the associated health risks. Air samples were collected from 15 beauty salons, and the concentrations of BTEX compounds were measured according to 1501 NIOSH standard method. The results showed that the mean concentrations of benzene (20.62 µg/m3), toluene (18.3 µg/m3), ethylbenzene (38.36 µg/m3), and O and P-xylene (27.35, 23.6 µg/m3) were above the recommended levels. The indoor to outdoor ratios for benzene, toluene, ethylbenzene, O and P-xylene were 3.04, 2.36, 3.75, 4.89, and 6.54, respectively. Also, the toluene/benzene (T/B) ratio in indoor and outdoor was 20.9 and 2.68 respectively. Almost half of the technicians (49.12%) reported adverse health effects, including joint pain, itchy eyes and nose, and respiratory allergies. The IARC guideline suggests that there is a potential risk of cancer development for individuals in all salons with LCR values exceeding 10−6, but the HQ index values indicate no non-carcinogenic risk. The findings suggest that beauty salon workers and customers are at risk of developing health problems from exposure to BTEX compounds. Effective risk management strategies, such as proper ventilation, use of personal protective equipment, and substitution of harmful chemicals with safer alternatives, to minimize exposure and protect the health of salon workers and customers recommended.

Abstract There are many pollutants in the air that can be harmful to human health. Their impact varies based on factors such as the kind of pollutant, duration of exposure, and concentration levels. Volatile organic compounds are particularly significant carcinogens among the various pollutants present in the air. Consequently, people who are exposed to these harmful airborne pollutants suffer permanent consequences. This study examines the properties of BTEX compounds—benzene, toluene, ethylbenzene, and xylene—as well as their sources and risk assessments throughout a one-year period from March 21, 2019, to March 20, 2020, in Karaj, Iran’s largest industrialized city. First, utilizing a geographical information system that covered the entire city, 17 locations within Karaj were chosen for this purpose. Then, samplings were carried out in the spring, summer, autumn, and winter months with the NIOSH 1501 method. During the research period, 68 samples of BTEX compounds were collected. The adsorption of these contaminants on the activated carbon adsorbents was performed using an environmental sampling pump with a flow rate of 0.2 L/min for 1 h. The samples were subsequently prepared using a carbon disulfide solution and injected into a GC-FID for analysis. In this research, the average annual concentration of BTEX compounds in the air of Karaj city was obtained at 33.01 µg/m3. Autumn and spring had the highest and lowest average concentrations of BTEX compounds, respectively. In addition, sites 5 and 8 had the highest average annual concentrations of these pollutants. The sourcing conducted in this study showed that transportation and fuel consumption, as well as industries, were the primary sources of pollution in the city. In addition, the excess lifetime cancer risk was higher than the guideline value in some sites and lower in others. Furthermore, the Hazard Quotients were lower than 1, but in general, the citizens of Karaj were at serious risk from exposure to this group of pollutants.

Abstract Objectives To validate the performance of Mirai, a mammography-based deep learning model, in predicting breast cancer risk over a 1–5-year period in Mexican women. Methods This retrospective single-center study included mammograms in Mexican women who underwent screening mammography between January 2014 and December 2016. For women with consecutive mammograms during the study period, only the initial mammogram was included. Pathology and imaging follow-up served as the reference standard. Model performance in the entire dataset was evaluated, including the concordance index (C-Index) and area under the receiver operating characteristic curve (AUC). Mirai’s performance in terms of AUC was also evaluated between mammography systems (Hologic versus IMS). Clinical utility was evaluated by determining a cutoff point for Mirai’s continuous risk index based on identifying the top 10% of patients in the high-risk category. Results Of 3110 patients (median age 52.6 years ± 8.9), throughout the 5-year follow-up period, 3034 patients remained cancer-free, while 76 patients developed breast cancer. Mirai achieved a C-index of 0.63 (95% CI: 0.6–0.7) for the entire dataset. Mirai achieved a higher mean C-index in the Hologic subgroup (0.63 [95% CI: 0.5–0.7]) versus the IMS subgroup (0.55 [95% CI: 0.4–0.7]). With a Mirai index score > 0.029 (10% threshold) to identify high-risk individuals, the study revealed that individuals in the high-risk group had nearly three times the risk of developing breast cancer compared to those in the low-risk group. Conclusions Mirai has a moderate performance in predicting future breast cancer among Mexican women. Critical relevance statement Prospective efforts should refine and apply the Mirai model, especially to minority populations and women aged between 30 and 40 years who are currently not targeted for routine screening. Key Points The applicability of AI models to non-White, minority populations remains understudied. The Mirai model is linked to future cancer events in Mexican women. Further research is needed to enhance model performance and establish usage guidelines. Graphical Abstract

Abstract Background Cancer survivors have an increased risk of incident heart failure (HF) attributable to shared risk factors and cancer treatment-induced cardiac dysfunction. Selection for HF screening depends on risk assessment, but the optimal means of assessing risk is undefined. We undertook a comparison of HF risk calculators among survivors. Methods In this study from the UK Biobank, cancer and HF diagnoses were determined based on the International Classification of Diseases (ICD)-10 code and non-cancer participants were included as controls. Participants’ risk of incident HF was determined using the Heart Failure Association-International Cardio-oncology Society (HFA-ICOS), the Atherosclerosis Risk in Communities (ARIC-HF) and the Pooled Cohort Equations to Prevent Heart Failure (PCP-HF). The predictive performances of each were compared using the area under the curve (AUC). Results After propensity matching with age and sex, 9,232 survivors from breast cancer or lymphoma (mean age 59.9 years, 87.8% female), and 23,800 survivors from other cancer types (mean age 59.1 years, 85.8% female) were included in the analysis. The discriminative value for HFA-ICOS (AUC 0.753 [95%CI: 0.739–0.766]) and ARIC-HF (0.757 [95%CI: 0.744–0.770]) were similar, and superior to PCP-HF (0.717 [95%CI: 0.702–0.732]). The overall performance for each risk score was better among participants in other cancer types than those with breast cancer and lymphoma. Conclusions HFA-ICOS and ARIC-HF outperformed the PCP-HF among cancer- and non-cancer cohort, although all showed modest discrimination for incident HF to be applied to clinical practice. A cancer-specific HF prediction tool could facilitate HF prevention among survivors.

Introduction: Fall is a common complication of stroke. People must use both their higher cognitive abilities and their motor skills simultaneously in everyday situations. Falling is much more likely to occur when performing multiple tasks requires continuous attention. Implementing a Cognitive Motor Dual Task (CMDT) might give more accurate information regarding how stroke survivors function throughout daily activities. Aim: To identify the walking speed in stroke patients using CMDT and to determine the impact of walking speed on risk of fall. Materials and Methods: In this cross-sectional study, 23 Middle Cerebral Artery (MCA) stroke patients with and without the risk of fall according to morse fall scale were included from Justice KS Hedge Charitable Hospital, Mangaluru, Karnataka, India from March 2023 to March 2024. After which the selected participants performed CMDT, the step count and time taken to complete the test was recorded using a pedometer and stop watch, the total and correct number of cognitive responses was recorded manually. The walking speed was calculated in m/sec. Based on the outcome measures of the present study; the statistical analysis was performed. Data collected was analysed by using the Statistical Package for the Social Sciences (SPSS) software version 29.0. To compare the data Independent sample t-test, One-way Analysis of Variance (ANOVA) was used. Results: The study participants consisted of an average age of 54.6±14.8 years. Individuals categorised as low-risk exhibited a mean walking speed of 0.238±0.014 m/sec, while those in the moderate risk group had a mean walking speed of around 0.211±0.024 m/sec and individuals at high-risk showed a lower mean walking speed of approximately 0.177±0.020 m/sec. The statistical analysis revealed a significant difference in walking speeds among the risk groups, with an F-value of 15.486 and a p-value less than 0.001. Conclusion: The study showed that walking speed will impact the risk of fall in stroke patients while performing CMDT. The time and step count are more in patients with high fall risk compared to patients with low fall risk therefore, walking speed is reduced in patients with high-risk of fall.

Abstract Background Despite successful efforts to eliminate measles in Iran, imported measles cases continue to be reported. Because measles is endemic in neighboring countries. This research aims to evaluate the risk of measles transmission in different regions of Iran. Methods Measles case-based surveillance data of the Expanded Program of Immunization containing 31 provinces and 463 districts from 2019 to 2021 were assessed. The WHO Measles Programmatic Risk Assessment tool was used to evaluate the risk of disease transmission in four domains: population immunity, surveillance quality, program delivery performance, and threat assessment. scores were categorized as low, medium, high, or very high risk. Results During 2019–2021, the average incidence of measles was 1.9 per 1 million. Chabahar and Mashhad with 76 and ./6per million reported the highest and lowest incidence respectively. All 463 districts were categorized as low risk in risk assessment. Andimeshk, Chabahar, and Bojnurd obtained the highest risk scores with 27, 24, and 25 respectively. All districts were classified as low risk for population immunity. The average coverage of (MMR1) and (MMR2) was 95% or higher. All districts received the minimum points for surveillance quality. Conclusion All regions are placed at a low level of disease transmission risk. However, the tool is not able to assess the risk at the rural or peripheral sectors level. The indicators used in this tool are the same for all countries with different epidemiological features (elimination, endemic). Sensitivity analysis can optimize the use of this tool for countries with different disease conditions.

Abstract Background Analytical Quality by Design (AQbD) has emerged as a pivotal paradigm in the realm of analytical chemistry, revolutionizing the approach to method development and validation. This innovative strategy integrates principles of Quality by Design (QbD) into analytical procedures, aiming to ensure the quality and robustness of analytical methods. The traditional approach to method development often involves a trial-and-error process, where parameters are adjusted until satisfactory results are obtained. However, this approach can be time-consuming, resource-intensive, and may lack reproducibility. AQbD addresses these challenges by providing a systematic framework for method development that emphasizes understanding the relationship between critical process parameters (CPPs) and critical quality attributes (CQAs). Discussion Analytical Quality by design (AQbD) presents an innovative approach to creating and validating analytical procedures, aimed at achieving quality measurements within the method operable design region (MODR). The QbD approach to analytical development is proactive, methodical, and risk-based significantly helps in acquiring an in-depth knowledge of how critical process parameters (CPPs) affect analytical performances, measured by critical quality attributes (CQAs). Experiment design (DoE) is an essential part of QbD, functioning to carry out the response surface analysis and screening process, and ultimately to enable the definition of the multidimensional region of the successful operating ranges of the CPPs, known as the design space (DS). The purpose of this article is to offer a thorough description of the QbD approach's method development process and its implementation in analytical procedure validation, to produce high-quality output, employing statistical analysis in conjunction with other designing tools. Conclusion Analytical Quality by design (AQbD) offers a systematic and proactive approach to method development in analytical procedures. By focusing on method resilience and incorporating statistical analysis and experiment design (DoE), AQbD enables the production of high-quality outputs, while minimizing out of trend (OOT) and out of specification (OOS) results. This innovative strategy enhances the reliability and reproducibility of analytical methods, ultimately leading to improved outcomes across various industries.

Abstract Trichlorobenzenes (TCBs), comprising the isomers 1,2,3-, 1,2,4-, and 1,3,5-TCB, disrupt metabolic processes by inducing liver enzymes involved in xenobiotic metabolism, suggesting a broad toxicological impact. Specifically, exposure to TCBs is associated with significant organ-specific toxicities, such as increased liver and kidney weights in rodents and cytotoxic effects in mammalian cells, which include DNA damage without metabolic activation. Used extensively in industrial and agricultural sectors, TCBs are prevalent pollutants in various ecosystems, including air, food, surface water, groundwater, sediment, soil, and sewage. This is a concern because of their tendency to accumulate in lipid-containing tissues of animals and humans and potentially serious risks to human health and ecosystems. Information showing the presence of TCBs in food, drinking water, and even human breast milk underscores the need for ongoing assessment of the extent of these contaminants in food to measure the potential exposure to these chemicals. TCBs are extracted from various food sample matrices, and then instrumental analysis is performed, typically gas chromatography (GC) coupled with a variety of detectors. This review discusses the occurrence and risk assessment of TCBs in foods, as well as the toxicology and analytical methods related to TCBs.

Abstract Objective The objective of this study was to examine the utility of a combination of the modified Caprini score and D-dimer levels for the evaluation and management of lower extremity venous thrombosis following lung cancer surgery. The purpose was to offer insights for developing clinical intervention programs. Methods The study sample consisted of 224 patients who underwent surgery for lung cancer at the First Central Hospital of Baoding City. General patient data and D-dimer levels on the first day post-surgery were collected. The modified Caprini risk assessment score was calculated. All patients underwent ultrasonography of the lower limb veins before and after surgery to identify venous thrombosis in the lower limb veins. Differences in lower extremity venous thrombosis and D-dimer levels among patients in various modified Caprini score groups were compared and analyzed. Results Based on the modified Caprini risk assessment score, all patients were categorized into three groups: the low-risk, medium-risk, and high-risk groups. The groups did not differ significantly in terms of age, but the differences in the rates of lower extremity venous thrombosis in the low, intermediate, and high-risk Caprini risk groups (16.5%, 19.2%, and 37.1%, respectively) were statistically significant. Out of the total 224 patients, 47 (21%) were diagnosed with venous thromboembolisms post-surgery, and all of them had thrombosis of the intermuscular veins of the lower extremity. The difference in the modified Caprini risk assessment score between patients with and without lower extremity venous thrombosis was statistically significant (P = 0.035), as were the postoperative D-dimer levels (1.28 ± 1.64 vs. 2.69 ± 2.77, respectively; P

BACKGROUND AND OBJECTIVES A rapidly increasing human population has resulted in the expansion of urban areas and an associated increase in the demand for food. Consequently, urban and peri-urban agriculture, using waste water as a source for irrigation, is increasingly common around the world, particularly in developing countries. In the Kurdistan region of Iraq, the soils within Agriculture areas have the potential to accumulate trace elements originating from various sources of contamination like municipal waste disposal and the use of wastewater for irrigation. The main aim of this study was to assess the levels and sources of trace elements in this specific region and to analyze the potential health hazards linked to toxic elements present in the soil.METHODS: Elemental analyses were conducted on soil samples using the total digestion method, involving the use of Hydrofluoric acid. Subsequently, 118 soil samples, each with a fraction size of less than 2 millimeters, were analyzed. These samples were collected from seven different urban and peri-urban agriculture areas in Sulaimani province. The analysis was carried out using Inductively coupled plasma mass spectrophotometry, which operated in collision cell mode with 7 percent hydrogen in helium to minimize polyatomic interferences.FINDINGS: The study findings indicated that the soils, with a potential hydrogen range of 7.5 to 8.18, are mainly calcareous and have textures that vary from silty loam to sandy or silty clay. Additionally, the organic matter content of these soils ranges from 1.4 percent to 5.47 percent. It was noted that soils subjected to wastewater irrigation do not show significant contamination by trace elements, whereas those affected by waste disposal sites showed high levels of chromium (134 milligrams per kilogram), copper (263 milligrams per kilogram), zinc (773 milligrams per kilogram), cadmium (4.19 milligrams per kilogram) and lead (161 milligrams per kilogram). Evaluation of enrichment factors indicates that the concentrations of trace elements generally remain within the anticipated background levels, with the exception of the municipal waste disposal site. The hazard indices derived for the trace elements indicate that the potential health risks associated with exposure routes are minimal. These indices consistently remain below the internationally recognized threshold of one, which signifies that the health concerns are insignificant fall within acceptable boundaries.CONCLUSION: The concentrations of trace elements exhibited a notable increase in locations allocated for waste disposal, demonstrating a gradual decline in comparison to other agricultural regions. Throughout all the locations examined, the levels of nickel consistently remained elevated, suggesting that the geological attributes of the region have a significant impact.

Enterprise risk management as a key element of the internal control system has become important over the years. The changes in the conditions of companies, especially banks, have increased the scope and complexity of their risk, and this has led to an increase in the demand for using enterprise risk management as an enterprise risk management framework. As the most important financial institution in the money market, the bank faces various risks. The implementation of this system in the bank makes the process of identifying, evaluating and monitoring risks with a comprehensive approach. The purpose of this study is to develop a comprehensive risk management implementation framework in the banking industry. Despite the growing importance of enterprise risk management, its implementation in Iran has received little attention and is facing challenges, and no study has been conducted to investigate its implementation conditions, effective factors, necessary foundations, and existing obstacles. Therefore, the current research has developed a framework for implementing enterprise risk management in the banking industry by using qualitative approach and systematic review and multiple case study methods by examining two banks. The statistical population of this research includes the board of directors, senior managers, members of specialized committees and experienced experts. The results of the research show that the extracted framework of enterprise risk management is not fully implemented in Iranian banks, and the challenges of its implementation include the lack of information technology infrastructure, the lack of sufficient knowledge and government restrictions. The current research can be considered as a suitable model for the banking industry.

Making cities resilient and secure remains a central goal in urban policy strategies, where established methods, technologies, and best experiences are applied or replicated when the knowledge of a threat is already well established. The scientific community and specialized bodies are invited to comprehend and evaluate disastrous events that are still not well explored to broaden the concept of resilient cities. Among these, terrorism in the European-built environment remains an underexplored topic, despite various studies assessing its economic, social, and political dimensions, exploring the radicalist matrix, or examining the post-effects of high-impact disastrous events. Within this framework, this work presents an algorithm for the risk assessment of historic urban open areas (uOAs) in Europe, combining theories of the terrorism phenomenon, the normative experiences, and the phenomenological results of violent acts in uOAs. Specifically, the algorithm is determined by studying physical qualities/properties and elements that usually feature the uOAs, using a limited set of descriptors. The descriptors and their formulation are set starting from their qualification, in compliance with the risk determinant (Hazard, Vulnerability, and Exposure), and discussed starting from participatory methods (Delphi and AHP). The algorithm is finally applied to Italian historic squares, testing the mathematical approach, verifying theories of the phenomenon, and setting up a comprehensive three-dimensional risk matrix for both soft and hard targets. This latest constitutes an operative tool to assess the investigated built environment exposed to terrorist threats aimed at developing more detailed mitigative strategies.

Introduction: Non – Communicable Diseases, driven by factors like increased life expectancy, urbanization and unhealthy lifestyles have become a leading cause of morbidity and mortality worldwide. India is undergoing a health transition, with Cardio Vascular Diseases now representing a significant part of its disease burden. Objectives: To estimate the prevalence of CVD risk and its associated factors using World Health Organization/ International Society of Hypertension risk prediction charts. Method: A community based cross-sectional study was conducted for a period of 18 months among 545 participants in Poonamallee Taluk, Tiruvallur district. Participants were selected using a multistage simple random sampling method. Sociodemographic data were collected through interviews, and blood samples were taken to assess blood sugar and cholesterol levels. Descriptive statistics for background variables were computed using SPSS 21. The association between various factors and cardiovascular disease (CVD) risk was analysed using the chi square test. Multiple logistic regression was performed to identify independent risk factors. Results: The mean age of the study subjects was 54.3+9 years with 60.2% being females. The 10-year CVD risk, based on the WHO/ISH risk prediction chart 30.6% had low risk (5 – 10%) and 30.3% had moderate risk (10 -

Currently, information on the toxicity profile of the majority of the identified e‐waste chemicals, while extensive and growing, is admittedly fragmentary, particularly at the cellular and molecular levels. Furthermore, the toxicity of the chemical mixtures likely to be encountered by humans during and after informal e‐waste recycling, as well as their underlying mechanisms of action, is largely unknown. This review paper summarizes state‐of‐the‐art knowledge of the potential underlying toxicity mechanisms associated with e‐waste exposures, with a focus on toxic responses connected to specific organs, organ systems, and overall effects on the organism. To overcome the complexities associated with assessing the possible adverse outcomes from exposure to chemicals, a growing number of new approach methodologies have emerged in recent years, with the long‐term objective of providing a human‐based and animal‐free system that is scientifically superior to animal testing, more effective, and acceptable. This encompasses a variety of techniques, typically regarded as alternative approaches for determining chemical‐induced toxicities and holds greater promise for a better understanding of key events in the metabolic pathways that mediate known adverse health outcomes in e‐waste exposure scenarios. This is crucial to establishing accurate scientific knowledge on mixed e‐waste chemical exposures in shorter time frames and with greater efficacy, as well as supporting the need for safe management of hazardous chemicals. The present review paper discusses important gaps in knowledge and shows promising directions for mechanistically anchored effect‐based monitoring strategies that will contribute to the advancement of the methods currently used in characterizing and monitoring e‐waste‐impacted ecosystems.

The annual incidence of symptomatic deep venous thrombosis (DVT) and venous thromboembolic (VTE) (DVT plus pulmonary embolism) in the adult population is estimated to be 50–100 and 75–150/100,000, respectively, and the incidence doubles for every 10-year increase in age. Patients admitted to hospitals, both surgical and medical, are at particularly increased risk for VTE, and the problem has been shown to continue after discharge. The risk is increased by age, obesity, malignancy, history of VTE, family history of DVT, stay in the intensive care unit, hereditary or acquired thrombophilia, and more recently, an elevated D-dimer. This risk is also affected by the nature and duration of the operation, type of anesthesia, immobility, dehydration, sepsis, varicose veins, inflammatory bowel disease, hormone replacement therapy, pregnancy, and pregnancy-related complications (stillborn infant, unplanned abortions, placental insufficiency, and growth retarded infant). Several risk assessment scoring systems are now available for clinical use. The ones most commonly used are the Rogers, Caprini, and Chao-Yang in surgical patients and the Padua, International Medical Prevention Registry on Venous Thromboembolism, and IMPROVEDD in acutely ill medical patients. The mandatory use of a risk assessment tool on admission and in high VTE risk patients at discharge as well and implementation of an evidence-based pathway for thromboprophylaxis have made the prevention of many fatal pulmonary emboli after surgery or hospitalization a reality.

Abstract Over the last 20 years, the global production of dimension stones has grown rapidly. Today, seven countries—China, India, Turkey, Iran, Italy, Brazil, and Spain—account for around two-thirds of the world's output of dimension stones. Each one has annual production levels of nine to over twenty-two million tons. Mining operation in general is one of the most hazardous fields of engineering. A large amount of dimensional stone quarries require a special scheme of risk assessment. Risk Breakdown Structure is one of the major stages of risk assessment. In this paper, a detailed structure of risks of the dimension stone quarrying is formed, and divided into 17 main levels and 128 sublevels. The complexity of identifying different parameters made it requisite to use multi-attribute decision-making methods for prioritizing associated risks. As a case study, the main risks of the Ghasre Dasht marble mine are evaluated using the VIKOR method considering 10 major parameters under a Fuzzy environment. The results showed that the economic, Management, and Schedule risks are the most threatening risks of dimensional stone quarrying.

Abstract Background The evaluation of the impact of pesticides on non-target species, like bees, is a crucial factor in registration procedures. Therefore, standardized test procedures have been developed on OECD level assessing the effects of chemicals on honey bees or bumble bees. Unfortunately, these protocols cannot directly be adapted for testing products that contain microorganisms. Interest in the use of microorganisms has increased in recent years due to their specificity to target species while not harming non-target organisms. This study aimed to evaluate optimal conditions to assess the effects of microbial plant protection products on bee species according to currently available test protocols. Some of the most commonly used microorganisms for plant protection, Bacillus thuringiensis subspecies aizawai (B. t. a. ABTS 1857) and Beauveria bassiana (B. b. ATCC 74040) were tested on Apis mellifera, Bombus terrestris, and Osmia bicornis at different temperatures (18, 26, 33 °C) under laboratory conditions. Results Exposure to the product containing B. t. a. ABTS 1857 resulted in higher mortality compared to B. b. ATCC 74040 in all tested bee species. A temperature-dependent effect towards higher mortality at higher temperatures of 26 °C or 33 °C was observed in O. bicornis exposed to both microorganisms. A. mellifera showed variable responses, but for B. terrestris there was mostly no effect of temperature when exposed to microorganisms in high concentrations. However, temperature affected longevity of bee species in the non-exposed control group. A. mellifera mortality increased with decreasing temperatures, while B. terrestris and O. bicornis mortality increased with increasing temperatures. A test duration of 15 or 20 days was found to be suitable for testing these microorganisms. Conclusion In conclusion, 26 °C should be considered the worst-case scenario for testing B. bassiana on all tested bee species. For testing B. thuringiensis, a temperature of 33 °C is recommended for A. mellifera, whereas B. terrestris and O. bicornis should be tested at 26 °C.

Modeling predictions are presented of radionuclide transport processes in the zone of influence of the Zahidne uranium mill tailings situated at the Prydniprovsky Chemical Plant (PChP), Kamianske. The groundwater transport model was developed using the NORMALYSA software. Refined estimates of parameters of water exchange in the zone of uranium mill tailing (obtained from field studies and modeling of groundwater flow processes) were used to parameterize the model for radionuclide transport in groundwater. Calibration of the radionuclide transport model using monitoring data on radioactive contamination of groundwater in 2005 - 2021 allowed to estimate the sorption distribution coefficient (Kd) for the most hazardous contaminants 238,234U isotopes (Kd = 8 ± 2 l/kg) and estimate the rate of uranium migration in groundwater. According to modeling, during the next 800 to 1100 years, uranium concentration in wells in the zone of influence of uranium mill tailing (at 500 - 800 m distance) will be determined mainly by the contamination of the alluvial aquifer, which was formed during the operation period of the uranium mill tailing. According to modeling predictions, usage of groundwater (partial drinking water consumption, irrigation) outside the PChP site downstream of the uranium mill tailing will result in doses exceeding the relevant reference level (annual effective dose > 1 mSv/year) in 380 - 440 years, while the toxicological impact will result in the exceeding of the acceptable hazard index for uranium (HI > 1) in 200 - 260 years. Modeling results indicate the importance of restricting the use of groundwater downstream of the uranium mill tailing within the PChP industrial site and, in the longer term, beyond its boundary. At the same time, contamination of the Konoplyanka River due to the migration of radionuclides from the uranium mill tailing does not pose unacceptable radiological and toxicological risks for the considered scenario (irrigation, fish consumption) due to the dilution of contaminants in surface waters.

Abstract Enterprise risk management (ERM) frameworks convey vital principles that help create a consistent risk management culture, irrespective of employee turnover or industry standards. Enterprise Management System (EMS) are becoming a popular research area for assuring a company’s long-term success. Statistical pattern recognition, federated learning, database administration, visualization technology, and social networking are all used in this field, which includes artificial intelligence (AI), data science, and statistics. Risk assessment in EMS is critical for enterprise decision-making to be effective. Recent advancements in AI, machine learning (ML), and deep learning (DL) concepts have enabled the development of effective risk assessment models for EMS. This special issue seeks groundbreaking research articles that showcase the application of applied probability and statistics to interdisciplinary studies. This study offers Improved Metaheuristics with a Deep Learning Enabled Risk Assessment Model (IMDLRA-SES) for Smart Enterprise Systems. Using feature selection (FS) and DL models, the provided IMDLRA-SES technique estimates business risks. Preprocessing is used in the IMDLRA-SES technique to change the original financial data into a usable format. In addition, an FS technique based on oppositional lion swarm optimization (OLSO) is utilized to find the best subset of features. In addition, the presence or absence of financial hazards in firms is classified using the triple tree seed algorithm (TTSA) with a probabilistic neural network (PNN) model. The TTSA is used as a hyperparameter optimizer to improve the efficiency of the PNN-based categorization. An extensive set of experimental evaluations is performed on German and Australian credit datasets to illustrate the IMDLRA-SES model’s improved performance. The performance validation of the IMDLRA-SES model portrayed a superior accuracy value of 95.70% and 96.09% over existing techniques.

Abstract This article investigates production optimization strategies for carbon dioxide recovery using a natural Carbon dioxide Processing Plant as a case study. The study assesses various optimization techniques including hydraulic fracturing, matrix acidizing, and drilling new wells based on productivity, optimal producing time, financial analysis, risk assessment, and environmental impact assessment. The analysis employs a least summation score ranking method to estimate the most suitable technique. Findings reveal that drilling a new carbon dioxide producing well emerges as the preferred option due to its favorable scores across all criteria, including high productivity, extended optimal producing time, low risk, minimal environmental impact, and positive incremental net present value, signifying its profitability and project viability. The study recommends a five year model verification, improvement and history matching program should be adopted in order to understand reservoir processes taking and detect operational issues together with identifying opportunities to improve reservoir description and data acquisition program.

Abstract Background Retention of apolipoprotein B (apoB)-containing lipoproteins within the arterial wall plays a major causal role in atherosclerotic cardiovascular disease (ASCVD). There is a single apoB molecule in all apoB-containing lipoproteins. Therefore, quantitation of apoB directly estimates the number of atherogenic particles in plasma. ApoB is the preferred measurement to refine the estimate of ASCVD risk. Low-density lipoprotein (LDL) particles are by far the most abundant apoB-containing particles. In patients with elevated lipoprotein(a) (Lp(a)), apoB may considerably underestimate risk because Mendelian randomization studies have shown that the atherogenicity of Lp(a) is approximately 7-fold greater than that of LDL on a per apoB particle basis. In subjects with increased Lp(a), the association between LDL-cholesterol and incident CHD (coronary heart disease) is increased, but the association between apoB and incident CHD is diminished or even lost. Thus, there is a need to understand the mechanisms of Lp(a), LDL-cholesterol and apoB-related CHD risk and to provide clinicians with a simple practical tool to address these complex and variable relationships. How can we understand a patient’s overall lipid-driven atherogenic risk? What proportion of this risk does apoB capture? What proportion of this risk do Lp(a) particles carry? To answer these questions, we created a novel metric of atherogenic risk: risk-weighted apolipoprotein B. Methods In nmol/L: Risk-weighted apoB = apoB - Lp(a) + Lp(a) x 7 = apoB + Lp(a) x 6. Proportion of risk captured by apoB = apoB divided by risk-weighted apoB. Proportion of risk carried by Lp(a) = Lp(a) × 7 divided by risk-weighted apoB. Results Risk-weighted apoB agrees with risk estimation from large epidemiological studies and from several Mendelian randomization studies. Conclusions ApoB considerably underestimates risk in individuals with high Lp(a) levels. The association between apoB and incident CHD is diminished or even lost. These phenomena can be overcome and explained by risk-weighted apoB.

A study reviewing overheating in historic buildings in the context of extant climate change. Due to global warming, more research is required when considering summertime thermal comfort in the UK, which is a more significant topic of conversation due to the heatwave in 2022. With a large demographic of the UK population residing in dwellings with historic value, this paper aimed to contribute findings that review their specific traits with respect to overheating. This was achieved by monitoring and analysing internal (and external environmental data) in three case studies in the south-east. Upon examination of the literature, many buildings in the UK are consistently subject to temperatures that exceed overheating. It was found that many properties of historic buildings lend themselves to summertime cooling such as higher thermal mass, better ventilation (without the use of mechanical or active systems), and less insulation. This, however, could come at the cost of winter thermal comfort. In all three case studies, the surveyed buildings passed the CIBRE criteria, but users still commented on being ‘too hot’. The high recorded RH levels in all properties, coupled with the inadequate overheating criteria, were deemed the cause. There are new regulations in place to minimise overheating in new buildings but no support for those that are already existing.

Qizhi Diao,1 Yongpei Long,2 Fangyu Yang,3 Cuihui Nong,1 Huamiao Tang,1 Xiangmin Zhou,1 Guoqiang Zhu,4 Qiang Ding5 1Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya, People’s Republic of China; 2Department of Laboratory Medicine, The People’s Hospital of Jianyang City, Sichuan, People’s Republic of China; 3Department of Clinical Laboratory Medicine, University-Town Hospital of Chongqing Medical University, Chongqing, People’s Republic of China; 4Chong Qing King Med Center for Clinical Laboratory Co., Ltd, Chongqing, People’s Republic of China; 5The Sixth People’s Hospital of Chongqing, Chongqing, People’s Republic of ChinaCorrespondence: Guoqiang Zhu; Qiang Ding, Email Guoqiangzhu01@163.com; yung10167086@126.comBackground and Objective: Inadequate risk assessment and a lack of risk monitoring are common deficiencies in clinical laboratory, and are also the main causes of biosafety incidents. Therefore, we summarized the experience of implementing adequate risk assessment and maintaining risk monitoring, and established a procedure for continuously improving biosafety management.Methods: Learning from our laboratory’s experience in implementing risk assessment, risk response, and risk monitoring before and during the COVID-19 epidemic, we summarized the procedures for fully identifying risks, accurately evaluating risks, maintaining risk monitoring, establishing and regular reviewing safety indicators. On this basis, we established a system for continuously improving biosafety management through risk monitoring and reviewing safety indicator.Results: We identified a total of 30 unacceptable risks prior to the COVID-19 pandemic, and developed and implemented appropriate risk control measures. After risk control, residual risks were acceptable, and no biosafety incidents have occurred. During the COVID-19 pandemic, after multiple risk monitoring, we identified ten new risks, three ineffective risk control measures, and multiple control measures for excessive protection. Then, we timely adjusted risk control measures to avoid laboratory personnel infection and excessive protection. Meanwhile, We established eight safety indicators and identified two improvement opportunities through regular reviews.Conclusion: Adequate risk identification and accurate risk assessment are particularly important for effectively controlling biosafety risks. Biosafety management should be continuously improved to deal with ineffective and excessive protection caused by various changes in experimental activities. Continuous improvement of biosafety management can be achieved through risk monitoring, regular review of safety indicators, and management reviews. This study will help laboratory managers to fully and accurately assess risks, as well as update risks and their control measures through risk monitoring, and the continuous improvement procedure established in the study has certain reference value for laboratories to effectively respond to emerging infectious diseases and avoid excessive protection.Keywords: risk assessment, risk monitoring, management review, continuous improvement, biosafety management

People with type 2 diabetes mellitus (T2DM) are at higher risk of developing cardiovascular disease, heart failure, chronic kidney disease, and premature death than people without diabetes. Therefore, treatment of diabetes aims to reduce these complications. Sodium-glucose co-transporter 2 (SGLT2) inhibitors have shown beneficial effects on cardiorenal and metabolic health beyond glucose control, making them a promising class of drugs for achieving the ultimate goals of diabetes treatment. However, despite their proven benefits, the use of SGLT2 inhibitors in eligible patients with T2DM remains suboptimal due to reports of adverse events. The use of SGLT2 inhibitors is particularly limited in older patients with T2DM because of the lack of treatment experience and insufficient long-term safety data. This article comprehensively reviews the risk-benefit profile of SGLT2 inhibitors in older patients with T2DM, drawing on data from prospective randomized controlled trials of cardiorenal outcomes, original studies, subgroup analyses across different age groups, and observational cohort studies.

Hydrogen has emerged as a promising alternative to meet the growing demand for sustainable and renewable energy sources. Underground hydrogen storage (UHS) in depleted gas reservoirs holds significant potential for large-scale energy storage and the seamless integration of intermittent renewable energy sources, due to its capacity to address challenges associated with the intermittent nature of renewable energy sources, ensuring a steady and reliable energy supply. Leveraging the existing infrastructure and well-characterized geological formations, depleted gas reservoirs offer an attractive option for large-scale hydrogen storage implementation. However, significant knowledge gaps regarding storage performance hinder the commercialization of UHS operation. Hydrogen deliverability, hydrogen trapping, and the equation of state are key areas with limited understanding. This literature review critically analyzes and synthesizes existing research on hydrogen storage performance during underground storage in depleted gas reservoirs; it then provides a high-level risk assessment and an overview of the techno-economics of UHS. The significance of this review lies in its consolidation of current knowledge, highlighting unresolved issues and proposing areas for future research. Addressing these gaps will advance hydrogen-based energy systems and support the transition to a sustainable energy landscape. Facilitating efficient and safe deployment of UHS in depleted gas reservoirs will assist in unlocking hydrogen’s full potential as a clean and renewable energy carrier. In addition, this review aids policymakers and the scientific community in making informed decisions regarding hydrogen storage technologies.

Abstract Bridge construction collapse is one of the most common bridge safety accidents. At present, evaluation results are often affected by the ability and experience of the assessor. Therefore, it is difficult to quickly, accurately and effectively evaluate the risk in the process of bridge construction. Moreover, key factors that can prevent accidents can hardly find from the existing bridge construction safety management and evaluation method. This paper analyzes and classifies the artificial and environmental risk factors that affect the bridge construction stage, and establishes 26 risk factors in 5 categories according to the characteristics of bridge construction and the actual situation of the project. Random forest (RF) algorithm is a non-parametric machine learning method based on decision tree, which does not need to be scored by experts in advance and avoids the influence of subjective factors. Compared with other analysis methods, random forest algorithm has the advantages of accurate and robust risk assessment results. Based on the advantages of random forest algorithm and the characteristics of bridge construction risk, this paper uses random forest algorithm to evaluate the bridge construction risk, and ranks the importance of indicators, and identify the index that has a greater influence on the risk. In order to verify the applicability and feasibility of the proposed method, a typical urban complex pedestrian bridge was taken as an example for actual engineering evaluation and verification. The results obtained are basically consistent with the actual risk assessment results of the pedestrian bridge.

Purpose – This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis. Design/methodology/approach – The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making. Findings – Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool. Originality/value – To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.

Abstract This study aimed to develop and validate distinct nomogram models for assessing CVD risk in individuals with prediabetes and diabetes. In a cross-sectional study design, we examined data from 2294 prediabetes and 1037 diabetics who participated in the National Health and Nutrition Examination Survey, which was conducted in the United States of America between 2007 and 2018. The dataset was randomly divided into training and validation cohorts at a ratio of 0.75–0.25. The Boruta feature selection method was used in the training cohort to identify optimal predictors for CVD diagnosis. A web-based dynamic nomogram was developed using the selected features, which were validated in the validation cohort. The Hosmer–Lemeshow test was performed to assess the nomogram's stability and performance. Receiver operating characteristics and calibration curves were used to assess the effectiveness of the nomogram. The clinical applicability of the nomogram was evaluated using decision curve analysis and clinical impact curves. In the prediabetes cohort, the CVD risk prediction nomogram included nine risk factors: age, smoking status, platelet/lymphocyte ratio, platelet count, white blood cell count, red cell distribution width, lactate dehydrogenase level, sleep disorder, and hypertension. In the diabetes cohort, the CVD risk prediction nomogram included eleven risk factors: age, material status, smoking status, systemic inflammatory response index, neutrophil-to-lymphocyte ratio, red cell distribution width, lactate dehydrogenase, high-density lipoprotein cholesterol, sleep disorder, hypertension, and physical activity. The nomogram models developed in this study have good predictive and discriminant utility for predicting CVD risk in patients with prediabetes and diabetes.

Soil loss by water erosion is one of the main threats to soil health and food production in intensively used agricultural areas. To assess its significance to overall sediment production, we applied the Water and Tillage Erosion Model/Sediment Delivery model (WaTEM/SEDEM) to the Luoyugou catchment, a subcatchment of the Yellow River Basin within the Chinese Loess Plateau. WaTEM/SEDEM considers rill and interrill erosion and deposition rates to calculate the sediment yield rates leaving the catchment. Terraces were established in the 1990s to reduce soil loss in this area, but no soil erosion modeling has been published regarding the effect of this mitigation measure. Therefore, we applied 1000 Monte Carlo simulations of the WaTEM/SEDEM, and the modeled average soil loss by rill and interrill erosion for 2020 was 12.2 ± 0.5 t ha−1 yr−1, with a sediment yield at the outlet of 53,207.8 ± 11,244.1 t yr−1. The results indicated that the terracing reduced gross soil loss rates (from 51.8 t ha−1 yr−1 in 1986 to 12.2 ± 0.5 t ha−1 yr−1 in 2020), while land cover changes, mainly the conversion of forests and grassland, partly counteracted the mitigation (combined effect: 76% reduction). Modeled sediment loads by rill and interrill erosion accounted for 22.8% of the total long-term sediment production recorded by flow discharge measurements. Other processes not considered by the model, such as landslides, gully erosion, riverbank erosion, and sediment production by construction, seem to predominantly influence the overall sediment yield. Considering years with baseline sediment production only, the measured and modeled sediment yields compared favorably, indicating that the latter processes primarily contribute during extreme events.

Background Cardiovascular disease (CVD) is a major cause of human mortality worldwide, characterized by its insidious onset, intricate and variable course, and poor prognosis. Early identification and active intervention of potentially critically ill patients is essential to improve their prognosis. Objective To conduct a scoping review of the research on early warning assessment tools for cardiovascular disease risk at home and abroad, summarize and analyze their assessment content and application, ultimately providing reference for the selection of appropriate early warning tools for cardiovascular disease patients in China. Methods CNKI, Wanfang Data, VIP, CBM, PubMed, Web of Science, Cochrane Library, Embase, CINAHL, and Scopus were systematically searched from inception to May 2023. Two investigators independently screened literature and extracted data, analyzed in terms of assessment content, study subjects, validation method, reliability and validity, and predictive efficacy. Results A total of 16 papers were included, comprising 7 papers on the development and validation of assessment tools and 9 papers on the localized application of these tools, involving 20 early warning assessment tools for cardiovascular disease risk. The results of the analysis showed that each assessment tool contained 3 to 17 assessment items, with the most frequently mentioned items of age, systolic blood pressure, respiratory rate, oxygen saturation, heart rate, comorbidities, level of consciousness, and gender. The results of the reliability and validity tests for 2 papers indicated robust reliability and validity, while all other studies lacked reliability and validity evaluations. Ten papers reported the area under the curve (AUC), with values ranging from 0.550 to 0.926 9. Conclusion Diverse early warning assessment tools for cardiovascular disease risk are available, however, their overall quality remains to be improved and there is a lack of specific assessment tools. In the future, it is imperative to conduct further validations of the reliability and validity of the existing tools, and develop localized early warning assessment tools specialized for cardiovascular diseases considering the unique characteristics of the disease, which exhibit robust reliability and validity.

This study proposes an IoT data management framework based on blockchain and edge computing and conducts detailed simulation experiment design and performance evaluation for the field of supply chain finance. Previous methods often struggled with high latency, limited scalability, and inadequate risk management, and to address these issues, the experimental platform includes traditional centralized systems, distributed systems, blockchain-based systems, and edge computing + blockchain systems. By monitoring indicators such as data processing delay, data transmission delay, data retrieval time, system throughput, and data integrity of each platform, and introducing evaluation formulas for credit risk, operational risk, and market risk, the performance of different systems in processing supply chain financial data is comprehensively analyzed. The experimental results show that the edge computing + blockchain system performs well in data processing efficiency, security, real-time, and system throughput, especially under high load conditions. Our market risk value is reduced to 0.015. This framework improves the efficiency and security of data transmission and effectively reduces credit risk and operational risk, providing an efficient and reliable solution for data management in supply chain finance.

Chronic wasting disease (CWD) is a fatal prion disease of the family Cervidae that circulates in both wild and captive cervid populations. This disease threatens the health and economic viability of the captive cervid industry, which raises cervids in contained spaces for purposes such as hunting and breeding. Given the high transmissibility and long incubation period of CWD, the introduction and propagation of the infectious prion protein within and between captive cervid farms could be devastating to individual facilities and to the industry as a whole. Despite this risk, there does not yet exist a literature review that summarizes the scientific knowledge, to date, about CWD spread, surveillance, or control measures. Our review, which focused on peer reviewed, primary research conducted in the United States, sought to address this need by searching Google Scholar, Scopus, and Web of Science with a five-term keyword string containing terms related to the (1) location, (2) species affected, (3) disease, (4) captive cervid industry, and (5) topic of focus. Between the three databases, there were 189 articles that were selected for further examination. Those articles were then read to determine if they were about CWD spread, surveillance, and/or control in captive cervid facilities. The 21 articles that met these inclusion criteria were evaluated in detail and discussed, with recommendations for future collaborative work between captive cervid owners, government agencies, and researchers. This work will help to address, inform, and mitigate the rising problem of CWD spread and establishment.

Cardiovascular disease (CVD) is considered to be one of the major groups of diseases which is preventable. The prevalence of such conditions is increasing due to the various lifestyle habits. In the majority of the cases, the disease remains asymptomatic. These CVDs can be prevented by early lifestyle modifications and treatment. CVDs are considered to be one of the major causes of death worldwide. Various risk assessment tools are used to identify patients with high risks, such as high blood pressure, cholesterol levels, age, obesity, and atherosclerosis. These tools are used for calculating the risk of beginning a CVD from various risk factors of the patient obtained from history, physical and general examination along with investigations. The risk assessment tools play an important role in preoperative period for better decision-making and planning for the treatment. The objective is to locate, evaluate, and synthesize current systematic reviews that discuss the role of risk assessment tools in primary CVD prevention. This review article comprises the various risk assessment tools or scores that can be used to calculate the cardiovascular risk in an individual and also the scores relevant in India. They are the Framingham risk score, systemic coronary risk evaluation, Reynolds risk score, JBS3 risk calculator, and many more.

Background: The perception of the risk of sexually transmitted infections (STIs) is a well-researched phenomenon, but not in relation to cyberchondria and health literacy. Therefore, our aim was to examine the association between the assessment of the risk of sexually transmitted diseases and HIV, cyberchondria, and health literacy. Materials and methods: This study was conducted in 2020–2021 in Croatia. The experimental group consisted of patients from the Centre for Voluntary Counselling and Testing for HIV (N = 134). The control group consisted of other patients recruited from daily epidemiological practices (N = 171). The instruments that were used were questionnaires that measure the perception of risk of sexually transmitted infections and HIV, health literacy, and cyberchondria. Results: Out of 305 respondents, 134 (43.9%) were in the STI counselling group, and 171 (56.1%) were in the control group. Generally, the participants in the former perceived the risk of sexually transmitted infections and HIV to be higher (but still low) than those in the latter. There was no difference in health literacy between the STI and control group; the health literacy score was average in both groups. There were differences in almost all the cyberchondria factors, except for Mistrust. Health literacy, belonging to the STI counselling group, and risk behaviours were positively associated with CH in the logistic regression analysis. Conclusions: People with a risk for STIs tend to minimize this risk, have higher cyberchondria levels, and have average health literacy. Cyberchondria is positively associated with health literacy, and more education about excessive health-related internet research is needed.

Background: The growing use of treated wastewater in farming has raised concerns about the potential impacts on public health. Methods: This study assessed the levels of the heavy metals lead (Pb), cadmium (Cd), and arsenic (As) in plants watered in greenhouse settings using both well water and synthetic wastewater. Synthetic wastewater with As at concentrations of 0.1, 0.2, and 0.4 mg/L, Pb at 1, 3, and 5 mg/L, and Cd at 0.01, 0.03, and 0.05 mg/L, as well as well water were used to irrigate radish, coriander, and grass. In the end, 144 vegetable samples were gathered, and inductively coupled plasma-optical emission spectrometry (ICP-OES) was used to determine the heavy metal concentrations in the samples. Risk assessment for consumers was determined based on the measured levels of heavy metals in the vegetables. Results: Even though the concentrations of heavy metals in the wastewater were within the limits for irrigation, the risk assessment showed that consumption of vegetables irrigated with treatment wastewater could pose risks to individuals’ health. The maximum concentration of Pb in radish leaves was observed at the Pb concentration of 5 mg/L, and the maximum concentration of As in cress irrigated with As effluent at the As concentration of 0.02 mg/L. Conclusion: The consumption of vegetables containing Pb can pose a significant non-carcinogenic risk to consumers. However, well water may also be dangerous in the long run. Therefore, it is important to ensure about food safety when using treated wastewater for irrigation.