(1) Polycyclic aromatic hydrocarbons (PAHs) are hazardous organic compounds with known carcinogenic and toxic properties. Exposure to PAHs occurs through various sources, including diet, inhalation, and skin contact, and they can transfer into breast milk following maternal exposure, potentially endangering breastfeeding infants. (2) This study aimed to determine the PAH content in breast milk samples from 50 Hungarian mothers using high-performance liquid chromatography with fluorescence detection (HPLC/FLD). The carcinogenic risk to infants was estimated using the Incremental Life Risk Calculation (IRCL) model. (3) Total PAH concentrations ranged from 0 to 78 ng/mL, with fluorene (5.3 ng/mL), phenanthrene (3.2 ng/mL), and pyrene (2.5 ng/mL) being the most abundant. PAHs were detected in 48 of the 50 samples, with phenanthrene present in 92% of samples. Dibenzo (a,h)anthracene was not detected. (4) Based on IRCL calculations, 10% of the samples were classified as safe, while 88% presented an acceptable carcinogenic risk for infants. Statistical analysis of questionnaires completed by the mothers indicated that factors such as diet, residence, and education may influence PAH levels in breast milk.

This research investigates the relationship among human knowledge, behavior, and risk as they relate to urban chicken husbandry in the U.S. Concern over zoonotic diseases has been on the rise, especially with increasing contact. In particular, avian influenza, or bird flu, Salmonella enterica (salmonella), and Escherichia coli (E. coli), can all cross species lines between people and poultry. This study analyzed knowledge and practices in urban chicken husbandry to assess how they relate to risk of disease acquisition, hypothesizing that certain practices associated with a lessened knowledge base may heighten the risk. This study used social surveys to examine the self-reported knowledge base of individuals involved in chicken husbandry as they relate to beliefs and behaviors associated with the care of these animals. These results identify key factors that may heighten the risk of disease transmission, and demonstrate that an increased knowledge base could act to lessen this risk.

Despite significant prevention efforts, the numbers of physically inactive individuals, chronic illnesses, exhaustion syndromes and sick leaves are increasing. A still unresolved problem with exercise promotion is the low participation of sedentary persons. This collective term covers heterogeneous subgroups. Their engagement with movement campaigns and resistance to change are influenced by numerous factors. Our aim was to analyse survey data on health, performance, lifestyle habits and the approachability to physical activity campaigns obtained from the Germany-wide ActIv survey. From 2,888 study participants aged 50-60 years, 668 persons were categorised into the subgroups "never-athletes", "sports-dropouts", "always-athletes" and "sports-beginners". Large and significant group differences were found for BMI, assessment of quality of life, health and fitness, risk factors and health problems. 42.5% of "never-athletes" and 32.5% of "sports-dropouts" did not state any barriers to sport. There are substantial disparities between the non-athlete groups in terms of their motivation to exercise. In contrast, there are comparatively minor differences in motivation between "sports-dropouts" and "sports-beginners", whose health and fitness are the primary motivators for sport. Our analyses suggest that (i) negative health and performance trends cannot be compensated by appeals for voluntary participation in exercise programmes and (ii) powerful incentive systems are required.

This research paper is mainly aimed to elaborate the initial risk management and measures which government of Pakistan took towards Novel Corona Virus (COVID-2019). This initial response and planning was devised after the early outbreak of COVID-2019 in Wuhan, China in early time of January 2020. Pakistan devised a comprehensive plan that not to evacuate their student from Wuhan, China. The government of Pakistan in compliance with the National Institute of Health (NIH) devised and documented comprehensive plans such as the flight operations postponed related to Umerah pilgrims, which were intended to go to sacred places of KSA (The Kingdom of Saudi Arabia). The process of visa, immigration policy totally changed and the government of Pakistan notified it officially that, no new visas of visit, student, and business would be issued in due course of uncertainty due to COVID-2019. The government of Pakistan also announced medical emergency and notified through the country’s provinces the process of testing and treatment of COVID-2019. The government of Pakistan also allocated funds for medical supplies and named out the particular country’s best laboratories. The government of Pakistan also locked down all the cities with the emergency announcement that people should stay inside the home in quarantine or self-isolation. NIH (The National Institute of Health) played a vital role in executing the planning to cope with COVID – 2019). The National Institute of Health responded as “The Centre for Disease Control”. In aid to the government, the national army of Pakistan responded in a proactive manner towards planed execution. The medical corps of Pakistan army dedicated themselves to treat the suspected patients of COVID – 2019. Due to plans, policies being documented, implemented in such a way productive way that from February 28, 2020 to till date there is not much critical situation and issues are not present. There are much productive results as there is not much boom in a rise of COVID-2019 patients. This lockdown under the authority of the provinces resulted in fruitful outcomes. Background: On January 02, 2020, authorities of the People Republic of China elaborated that they have encountered with a novel type of infectious viral disease 2019. Later on January 12, the authorities from China elaborated the related sequence of Corona Virus diseases 2019 names as COVID – 2019. When COVID-2019 being identified in Wuhan, Hubei China, as an early response the Government of Pakistan in support of the National Institute of Health (Field Epidemiology & Disease Surveillance Division) published a health advisory about novel coronavirus. Methods: According to Global Health Security Index, Pakistan is ranked as 105th country among 195 countries in GHS index. Overall Score of Pakistan is 35.5. The score of Early Detection and Reporting for Epidemics of Potential International Concern is 41.7. A Graphical depiction of the COVID-19 cases placed until April 10, 2020 as well as a graph trend line of recovered as well as death rate is also depicted. According to the graphical facts of Government of Pakistan and World meters, the recovery rate of COVID-19 is about 98 percent and 2.1 percent death rate is reported against the total cases. Trend analysis with line graph was drawn based on available data from official dashboard web portal of the government of Pakistan and worldometers.info. Data figures were incorporated from March to August 18, 2020 in MS Excel and then subsequently deployed to draw trend analysis from managing risk to recovery. Results: The line graph showed a slowdown in the COVID-19 cases and high rate of recoveries from COVID-19 in Pakistan. On March 11, 2020, there were 20 confirmed cases of coronavirus reported in Pakistan. No death was recorded in very first seven days, on March 18, 2020 only two deaths were reported. On August 18, 2020, there were 272128 recoveries, 6201 deaths, total confirmed cases 290445, and total test were 2340072 in Pakistan. As a results, we can report that due to early measures taken by government of Pakistan no mass scale destruction in terms of death and cases been recorded in Pakistan. Conclusions: To till date, the government of Pakistan tried its level best to minimize the coronavirus cases as much as they can. However, the ending of the potential attack of an outbreak would depend upon the well organized and coordinated approach at all levels such as true directed decisions, fully preparedness, as well implementation and evaluation of continuous decisions. As the recovery rate of the cases is 98 percent and merely death rate is 2.1 percent, concluded that in future it would be a good sign to stop the potential outbreak. Also, lock down as well as precautionary measurement taken by the provincial governments resulted a decline number of COVID-19 cases in the country. Another good sign is that merely 4 percent population of Pakistan is of more than 60 years of old it can be concluded that there are less chances of mass death due to outbreak of COVID-19.

Preoperative assessment is crucial in surgical care, traditionally relying on physical examinations and paper-based questionnaires. The emergence of digital tools like Pathpoint® ePOA represents a significant advancement, aiming to enhance the efficiency, accuracy, and standardisation of preoperative evaluations. Pathpoint® ePOA is a cloud-based platform designed to integrate seamlessly with Electronic Health Records (EHRs), providing a comprehensive, data-driven approach to preoperative assessments. It supports improved risk stratification, optimised resource allocation, and enhanced patient engagement through features such as customisable templates and real-time data integration.Current research highlights that digital preoperative tools like ePOA offer notable advantages, including increased clinical capacity, better complexity stratification, and improved patient follow-up. Despite these benefits, gaps remain in comparative studies, detailed clinical outcomes, and patient engagement strategies, indicating areas for further exploration. Pathpoint® ePOA adheres to rigorous safety standards and risk management protocols, ensuring reliability and data security while contributing to improved surgical outcomes. The benefit-risk ratio for ePOA is favourable, underscoring its potential to advance preoperative care by optimising clinical workflows and enhancing patient safety.

Background Popular movement-based injury risk screens have been shown to lack predictive precision, leading to interest in multifactorial models. Furthermore, there is a lack of research regarding injury risk assessment for those currently or planning to be recreationally active. This study aims to provide injury risk insights by analyzing multifactorial injury risk models and as-sociated clinical measures in the U.S. population. Methods Data related to injury, inflammatory markers, physical functioning, body composition, physical activity, and other variables from 21,033 respondents were extracted from NHANES. Odds ratios for self-reported injury were calculated for single predictors and risk models. Case-control and principal component analyses (PCA) were conducted to elucidate confounders and identify risk factor clusters, respectively. Receiver operating characteristic analysis was used to test the precision of a risk factor cluster to identify pain points and functional difficulties. Results Sociodemographic, individual, and lifestyle factors were strongly associated with higher odds of injury. Increases in fibrinogen and C-reactive protein were significantly associated with all risk groups. Membership to the high-risk group (age over 40, obesity, no muscle-strengthening activities, sedentary lifestyle, and low back pain) predicted at least one functional difficulty with 67.4% sensitivity and 87.2% specificity. In the injury group, bone turnover markers were higher, yet confounded by age and there was a significantly higher prevalence of self-reported osteoporosis compared to the control. In males, low testosterone was associated with injury, and higher estradiol was associated with pain and functional difficulties. In females, higher levels of follicle-stimulating hormone were associated with functional difficulties. PCA revealed four high-risk profiles, with markers and activities showing distinct loadings. Conclusion A comprehensive approach to injury risk assessment should consider the nexus of aging, lifestyle, and chronic disease to enhance tailored injury prevention strategies, fostering safe and effective physical activity participation and reducing the burden of musculoskeletal disorders.

Aim: Utilizing the subjective experience of nurse executives who have supervised nurses during a major disaster in a hospital setting, this study aims to describe the subjective experience of nurse executives (NE) who have supervised nurses’ response to major disaster. This paper will focus on strategies to support nursing response to disaster, specifically to strengthen resiliency and the ability to maintain function despite the shock of disaster, including those caused by climate changes. Methods: Semi-structured interviews were conducted with 11 hospital-based nurse executives who supervised nurses during some of the worst natural and human-made disasters in different regions of the United States. A phenomenological approach was used to analyze and describe emerging themes from qualitative data. Results: Three Nurse Executives demonstrated theme saturation for mitigation steps to augment traditional disaster readiness activities: 1.) Assessment of Human Infrastructure: Daily Skills Needed During Disaster Response, 2.) Identification and Study of Failure Points & Metrics, 3.) Strengthening Human Infrastructure: Rectifying Deficiencies), and 4.) Monitoring Metrics & Making Corrections During Conventional Periods. Conclusion: Mitigation steps may improve outcomes in hospital function during conventional times; therefore, may improve resiliency and the ability to maintain functions during major disasters, including climate change.

Intermediate CAG expansions in the gene ataxin-2 (ATXN2) are a known risk factor for ALS, but little is known about their role in FTD risk. Moreover, their contribution to the risk and phenotype of patients might vary in populations with different genetic background. The aim of this study was to assess the relationship of intermediate CAG expansions in ATXN2 with the risk and phenotype of ALS and FTD in the Spanish population. Repeat-Primed PCR was performed in 620 ALS and 137 FTD patients in three referral centers of Spain to determine the exact number of CAG repeats. In our cohort, ≥27 CAG repeats in ATXN2 was associated with a higher risk of developing ALS (odds ratio [OR] = 2.666 [1.471-4.882]; p = 0.0013), but not FTD (odds ratio [OR] = 1.446 [0.558-3.574]; p = 0.44). Moreover, ALS patients with ≥27 CAG repeats in ATXN2 showed shorter survival rate compared to those with <27 repeats (hazard ratio [HR] 1.74 [1.18, 2.56], p = 0.005), more frequent limb onset (odds ratio [OR] = 2.34 [1.093-4.936]; p = 0.028), as well as family history of ALS (odds ratio [OR] = 2.538 [1.375-4.634]; p = 0.002). Intermediate CAG expansions of ≥27 repeats in ATXN2 are associated with ALS risk, but not with FTD, in the Spanish population. ALS patients carrying an intermediate expansion in ATXN2 show more frequent limb onset, but worse prognosis than those without expansions. In patients carrying C9orf72 expansions, the intermediate ATXN2 expansion might increase the penetrance and modify the phenotype.

This study aimed to quantify the extent of heavy metal, non-metal and metalloid level of Campomanesia adamantium pulp obtained from area crossed by road of the high large vehicle traffic and intensive agriculture modern farm, and for monitoring the health risks associated with pulp human consumption. For this purpose, three spots located between this area, ripe fruits were collected in roadside, bush and margin-farm. Pulp samples were digested by microwave-assisted equipment, and mineral elements were quantified by ICP OES. The mineral elements average demonstrated no statistical difference observed between this pulp (p > 0.05). The heavy metals and metalloid concentrations that exceeded FAO/WHO standards are ordered Pb > As > Mo > Co > Ni > Mn > Cr. Therefore, among these metalloid and heavy metals, As, Pb and Cr were found higher in farm-margin > roadside > bush (1.5 × 10^-3, 1.1 × 10^-3 and 6.2 × 10^-4) respectively. Therefore, As is the most important metalloid with higher levels in farm-margin, roadside and bush (1.5 × 10^-3, 1.1 × 10^-3 and 6.2 × 10^-4 > 10^-6–10^-4 and 3.33, 2.30 and 1.34 > 1) respectively, to total cancer risk and hazard quotient, if 100 g daily of pulp are consumed.

Despite ample warning and significant lead time, global society has not acted sufficiently to combat climate change, and global carbon dioxide emissions are now about 60% higher today than in 1990 [1]. This paper uses marine fisheries as an analog model to compare with the many similar management issues faced with global climate change. Both marine fisheries and global climate change are complex systems that have similar properties that make management very difficult. A simple fishery prototype model is used to educate citizens about similar issues of dynamic complexity found in climate change models. We highlight how our slow reaction time to global climate change can be thought of as a mismatch between our cognitive abilities and the nature of global collective problems. Understanding the history and system structure of marine fisheries can provide insight into managing global climate change. We suggest ways to improve communication between science and citizens for updating mental models and changing climate policy.

The Internet-of-Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state-of-the-art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.

Decomposed fuzzy sets are the resent extension of intuitionistic fuzzy sets by incorporating functional and dysfunctional points of views to the definition of membership functions. This paper extends the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) method to the Decomposed Fuzzy TOPSIS (DF TOPSIS) method and applies it to a multi-criteria risk-based supplier selection problem under fuzziness. DF TOPSIS involves finding a positive ideal solution and a negative ideal solution and measuring the distance of each alternative to these solutions. The final ranking is obtained based on the proportion of distances to the positive and negative ideal solutions. The developed DF TOPSIS method incorporates the accuracy and consistency of expert judgments, enhancing the decision-making process. A sensitivity analysis is also presented in order to show the robustness of the obtained rankings by DF TOPSIS.

Objectives: COVID-19, a respiratory disease caused by SARS-COV2 and transmitted from person-to-person through viral droplets remains a global pandemic. There is a need to understand the transmission modes, populations at risk, and how to mitigate the spread and case fatality in the United States (US) and globally. The current study aimed to assess the global COVID-19 transmission and case fatality, examine similar parameters by countries and determine evidence-based practice in extreme epidemiology response in epidemic curve flattening and case fatality reduction. Methods: A cross-sectional ecologic design was used to assess the preexisting data on confirmed COVID-19 cases and mortality in March 2020 from the CDC, WHO, Worldodomter, and STATISTA. A rapid assessment between March 23^rd and 31^st, 2020, was utilized for the extreme epidemiology response. The case fatality, termed fatality proportion, was examined using mortality in relation to confirmed cases involving the world, United States of America (USA), United Kingdom (UK), Italy, France, Spain, China, Germany, India and South Korea. Results: The COVID-19 is a global pandemic, with the US as the epicenter for transmission, representing 20.9% of all confirmed cases worldwide, while Italy is the epicenter for case fatality, 30.6% of mortality as at 03/31/ 2020. The fatality proportion (FP) in Italy was 11.4%, Spain (8.8%), France (6.8%) and UK (6.4%). Despite the increased number of confirmed cases, the lowest FP was observed in Germany (0.96%) and South Korea (1.66%). There is increasing linear tends in transmission in the US, R²=0.97 as well as positive daily percentage change, ranging from 1.27% to 20.5%. Conclusions: The USA remains the epicenter for COVID-19 transmission, while Italy is the epicenter for case fatality. The observed relatively low case fatality in Germany and South Korea is due to an “extreme epidemiology” response through the application of Wuhan, China’s early data on COVID-19 transmission control measures and optimized patient care. These data are suggestive of relaxing the clinical guidelines in the United States in COVID-19 testing, application of contact tracing and testing, case isolation and most importantly enhancing resources for case management and social and physical distancing globally, hence epidemic curve flattening and case fatality reduction.

The normative and safeguarding role of ethics and law in the development of biomedical science and technology, as well as their importance in promoting the progress of the industry, analyzed the key role of ethics and law in the field of biomedical science and technology, by restricting scientific research behavior, protecting the rights and safety of subjects, providing a solid guarantee for scientific research activities, and promoting the healthy development of biomedical science and technology. At the same time, the positive role of ethics and law in promoting international cooperation and exchange of biomedical science and technology is also discussed, which will inject strong impetus into the global development of biomedical science and technology. In addition, through case analysis, the paper demonstrates the key role of ethical review in the field of biomedical science and technology, as well as the importance of law in maintaining market order, protecting subjects' rights and interests, and fairness and justice. The successful practice of ethics and law in the development of biomedical science and technology is emphasized, which proves that following ethical principles and legal framework is the key factor to promote the progress of biomedical science and technology. This paper explores the important role of ethics and law in the development of biomedical science and technology, and provides valuable reference and guidance for practitioners in the industry. By following ethical principles and legal norms, we will jointly promote the prosperity and development of biomedical science and technology, and contribute to the common progress of human health.

Risk management for technological hazards mainly focuses on the consequences on human lives. Although technological risk analysis evaluates environmental vulnerability, it does not reflect the consequences on environmentally exposed elements, such as rivers, water springs, flora, and fauna. This paper's objective was to propose a conceptual framework and create a multidisciplinary evaluation model for environmental risk analysis in the oil and gas industry. Initially, the problem was approached from a global perspective to justify the necessity of a holistic environmental risk analysis methodology in the oil industry, using environmental risk factors as well as underlying factors, such as environmental fragility and lack of resilience. The holistic assessment was carried out based on probabilistic risk analysis methodologies to obtain a holistic environmental risk index, HERI. This methodology was applied to an oil and gas industry company in Colombia. This allowed greater disaggregation of the results to establish priorities for risk reduction actions and identify the company's weaknesses.

In the context of seismic risk, studying the characteristics of urban soils and of the built environment means adopting a holistic vision of the city taking a step forward compared to the current microzonation approach. Based on this principle, CLARA WebGIS aims to collect, organise, and disseminate the available information on soils and buildings in the urban area of Matera. The geodatabase is populated with i) 488 downloadable geological, geotechnical, geophysical, surveys; ii) geological, geomorphological, and seismic homogeneous microzones maps and iii) a new Digital Surface Model. The CLARA WebGIS (https://smartcities-matera-clara.imaa.cnr.it/) is the first publicly available database reporting for the whole urban area the spatial distribution of the fundamental frequencies for soils and the overlying 4043 buildings, along with probability levels of soil-building resonance. The WebGIS is addressed to a broad target of end users (local government, engineers, and geologists, etc.) as a support to the implementation of seismic risk mitigation strategies in terms of urban planning, seismic retrofitting, and management of post-earthquake crises. We recommend that the database be managed by local administrators, who would also have the task of deciding on future developments and continuous updating as new data becomes available.

Understanding the vulnerability of areas and the likelihood of specific disasters, particularly earthquakes, is one of the most important issues in Iran. One of the major concerns in Iran is the resilience of rural communities. The present study is devoted to spatial analysis of risk in rural areas and the evaluation of preparedness in the rural districts of the city of Abhar. In particular, this study evaluates the resilience to earthquakes. The research was conducted in two parts in which the first part has used the VIKOR Multiple criteria decision making model as well as the employment of this model in the ArcGis. The second part of the study used field studies, in the form of questionnaires, to evaluate the readiness of the local population against the risks of earthquakes. Four indicators, individual, physical, economic abilities and access, were assessed. The population included rural districts, where statistical samples were villagers. Results of the spatial analysis indicated that 15 villages are in the high-risk areas, 24 villages were in the medium-risk areas and all other villages were in low-risk areas. In terms of readiness of the locals, the results indicated a lack of planning with regards to the four mentioned indicators.

CD4 count recovery is the main goal for an HIV patient who initiated ART. Some patients respond positively to ART and attain CD4 count recovery, some patients might fail to recover their CD4 count due to non-adherence, treatment resistance, and virological failure, leading to HIV-related complications and death. The purpose of this study is to find the determinants of death in patients who failed to recover their CD4 count after initiating antiretroviral therapy. The data used in this study was obtained from KwaZulu-Natal, South Africa, where 2528 HIV-infected patients with a baseline CD4 count of 200 cells/ were initiated on ART. We used a Fine-Gray sub-distribution hazard and cumulative incidence function to estimate potential confounding factors of death, where CD4 count recovery was a competing event for failure due to death. Patients who were not suffering from tuberculosis were 1.33 times at risk of dying before attaining CD4 count recovery [aSHR 1.33; 95% CI (0.96-1.85] compared to those who had no tuberculosis. Rural patients had a higher risk of not recovering and leading to death [aSHR 1.97; 95%CI (1.57-2.47)] than those from urban areas. The patient’s tuberculosis status, viral load, regimen, baseline CD4 count, and location were significant contributors to death before CD4 count recovery. Intervention programs targeting HIV testing in rural areas for early ART initiation and promoting treatment adherence are recommended.

Limited knowledge is available about the association between autistic spectrum disorder (ASD) and precocious puberty. Our study examined the association between the two medical conditions, and the effect modification by sex and neuropsychiatric comorbidities in a nationwide population. To compare the risk of precocious puberty between ASD and non-ASD cases, we conducted Cox regression analysis, using ASD as exposure and time-to-precocious puberty as outcome. We adjusted for sex, attention-deficit/hyperactivity disorder (ADHD), tics disorder, obsessive–compulsive disorder (OCD), anxiety disorder, intellectual disability, and epilepsy. We performed a moderation analysis to examine the potential moderating effects by sex or comorbidities. Patients with ASD were prone to have precocious puberty, with an adjusted hazard ratio (aHR) of 1.80 (95% CI: 1.61-2.01). For the effect modification, sex, specifically females, moderated the association between ASD and precocious puberty, with relative excess risk due to interaction (RERI) 7.35 (95% CI 4.90-9.80). No significant effect modification was found for any of the comorbidities within the scope of additive effect modification. We found that patients with ASD were prone to precocious puberty, regardless of sex or comorbid neuropsychiatric disorders. Girls with ASD are at particularly higher risk to develop precocious puberty.

Although it’s been some forty years since we started to teach combined modified Fault Tree / Event Tree acyclic digraphs, as much simpler Bow Tie diagrams, their popularity seems undimmed; as their pictorial and focussed discussion prompts, fulfil a valuable function in the safe design and operation of hazardous plants and installations. An excellent review of the current state of the art and an authoritative treatise on the terminology and issues involved has been produced as an internationally recognised standard for using the approach. But just as this model has augmented and helped formalise previous pictorial tools, (such as “Dominoes” and holey “Cheese” slices), this paper suggests and sets out to show how we can build on even this current cornerstone of practice and augment its versatility; with the ability to obtain, what engineers rely on, some more quantitative insights from these pictures. “Layers Of Protection Analysis” (LOPA), has already demonstrated a way of pulling together more quantitative predictions from the pictures. This paper would go further and by concentrating on the function not the physicality of a barrier, outlines a methodology that can extend, not just the quantification ability of the LOPA extension, but present a much more holistic view of how the Barriers, as functions, need to work together, interact and interdepend; often in nonlinear, unexpected ways, to give system designers and operators a much clearer view of actual performance predictions.

Earthquake events present a high risk in urban areas. Nador City is a Mediterranean city located in a dynamic zone with seismologic movement and a frequency of earthquake events per year. This worrying rate shows that earthquake risks can hinder the urban area and damage citizens and goods if urban risk management is not taken. This study defines the areas most threatened by seismic events to protect them as a priority. Using Geographic Information System, Corine Land Cover, seismic intensity, and socioeconomic vulnerability index, we mapped the urban vulnerability index. The adopted model determines urban vulnerability levels from urban land cover, topography, geologic factors, and geomorphologic factors. These approaches reveal that $70\%$ of Nador is under the damage of a seismic disaster. In addition, the main objective is to apply a new set of guidelines to map the intensity of risks and explain the distinct risk exposure level in Nador’s urban context.

For most people, using social media to research products has become common. Despite previous research, there is a gap in understanding reviewers' product-related comments and how they lead to purchase intentions. In terms of contributions, this study analyses people's dependence on social media for product information in purchase intention while considering the moderating impact of risk and trust on the link between purchase intention and social media. The data were collected quantitatively using surveys. The sample consisted of 384 students. The study hypotheses were tested using the PROCESS macro after exploratory factor analysis and correlation analysis were conducted. Among those surveyed, it was confirmed that most people sought product-related comments on social media when seeking information about a product they might be interested in purchasing. It was also observed that the risk factor reduced the impact of other variables in the model presented in this study. In conclusion, this investigation is more reliable, and its outcomes benefit scholars, supervisors, merchants, and webmasters, for instance, in establishing a study for future research efforts and providing practical guidance that could boost promotional efforts and marketing activities, especially in this era of artificial intelligence.

Background and Objectives: Peripheral vertigo is one of the most common symptoms for which patients are seen by a neurologist in the emergency room. Symptoms of peripheral vertigo can range from lightheadedness to an illusion of spinning. On average, vertigo is diagnosed for older patients as its predicting factors from medical history are yet to be determined. The objective of the study was to predict peripheral vertigo based on medical history and risk factors. Materials and Methods: A prospective case-control study at the Neurology Department of Lithuanian University Hospital was conducted. 71 patients diagnosed with vertigo and 43 controls was included. They completed questionnaires and underwent evaluation by neurologists or otolaryngologists, with statistical analysis performed using IBM SPSS Statistics. Results: 58% of vertigo patients were diagnosed with peripheral vertigo, with significant predictors including age (>60), motion sickness, height intolerance, gastroesophageal reflux disease and dyslipidemia, leading to the development of a risk assessment table for the peripheral vertigo prediction. Conclusions: This study suggest that early identification of these predictors could enhance peripheral vertigo management, while further research with larger cohorts is needed to validate and expand upon these findings, emphasizing the importance of considering medical history and risk factors for predicting peripheral vertigo and improving patient care.

Acute kidney injury (AKI) is a highly prevalent and a critical complication of cardiac surgery (CS). Serum lactate levels (sLac) have consistently shown an association with morbimortality after CS. We performed a cross-sectional study including 264 adult patients that had a cardiac surgery between January and December 2020. Logistic regression analysis was performed to determine factors associated with AKI development. We measured the postoperative levels of sLac to all participants immediately after CS (T0) and after 4 hours (T4) of the surgical intervention. Linear regression model was carried out to identify the factors influencing both levels of sLac. We identified four risk predictors of AKI; one was preoperative (atrial fibrillation), one intraoperative (cardiopulmonary bypass time), and two were postoperative (length of hospital stay and postoperative sLac). T0 and T4 sLac levels were higher among CS-AKI patients than in Non-CS-AKI. Postoperative sLac levels were significant independent predictors of CSA-AKI and the sLac levels are influenced by length of hospital stay, the number of packed red blood cells transfused and the use of furosemide in CS-AKI patients. These findings may facilitate the earlier identification of patients susceptible to AKI after CS.

In the process of climate change mitigation and adaptation, the focus on climate risk driven by transition innovations has received widespread attention from governments, regulators, and investors. Based on the identification of low-carbon patents through the Green and Low-carbon Technology Inventory in China, this study constructs low-carbon innovation measurements of listed firms in China from 2015 to 2021. Then, an empirical model is used to investigate the impact and mechanism of climate transition innovations on the default risk. The baseline regression model shows that low-carbon innovations can mitigate the default risk of listed firms. Moreover, our findings are supported by instrumental variable regressions that use the time costs of innovation. Finally, the mediation effect demonstrates that investor attention, total factor productivity, and technology spillovers are paths through which transition innovations can affect the default risk. This study reveals that low-carbon technological advances have a positive effect on climate transition risks.

The authors present a framework for assessing seasonal events which may influence maritime operations. Most maritime-related research tends to focus on single events, such as a storm, but maritime systems operate within complex systems that have some predictable patterns. These predictable patterns due to natural events, such as weather and water levels, can influence operations, while other factors, such as cargo peaks or cultural activities, could also shape maritime systems. By integrating data from emergency management databases and weather information sources with other inputs, the authors created a matrix of regionally specific predictable events that may occur within a region by time of year. The matrix was vetted with various stakeholder groups to verify the information in the matrix. The main findings were that a seasonal event matrix is helpful as a reference for examining operational patterns in a river for various uses, such as training, operational planning, and emergency response coordination.

Aims. In a male Italian cohort (initially aged 40-59, n=1712) followed-up during 61 years and reaching practical extinction, the natural history of major CVD mortality categories including coronary heart disease (CHD), stroke and other Heart Diseases of Uncertain Etiology (HDUE, including congestive heart failure) were studied along with their risk factor relationships. Methods and Results. Cox models were run with 12 covariates measured at entry as possible predictors. About 93% of all CVD deaths were covered by the 3 major groups selected here (N=751): 37.4% of them were diagnosed as CHD, 30.6% as stroke and 28.5 % as HDUE. CHD declined in the last 20 years of follow-up, while a sharp increase of HDUE mortality was seen. Baseline mean levels of serum cholesterol were 209.6, 204.2 and 198.0 mg/dl respectively for CHD, stroke and HDUE deaths: the multivariable coefficients of serum cholesterol were positive and significant for CHD (p<0.0001) and stroke (p=0.0203) and not significant for HDUE (p=0.3467). In Fine-Gray models, the algebraic signs of cholesterol coefficients were opposite for CHD versus the other mortality categories (t=3.13). The predictive performances of remaining risk factors were varied whereas that of Cox models was not very good, probably due to the attrition phenomenon and possible competing risks. Conclusion. Large differences in natural history and risk factors were found comparing the 3 CVD conditions, potentially indicating different etiologies and pointing to the need of not mixing them up in a grouped CVD category.

Seismic vulnerability assessment in urban areas would in principle require the detailed modeling of each single building and the implementation of complex numerical calculations. This procedure is clearly difficult to apply at urban scale where many buildings have to be considered and therefore it is essential to have simplified, but at the same time reliable, approaches to vulnerability assessment. Among the proposed strategies, one of the most interesting concerns the application of machine learning algorithms, able to classify buildings according to their vulnerability on the basis of training procedures applied to existing datasets. In this paper machine learning algorithms will be applied to a dataset which collects and catalogs the structural characteristics of a large number of buildings and reports the damage observed in L’Aquila territory during the intense seismic activity occurred in 2009. A combination of a trained neural network and a random forest algorithm allows to identify an opportune “a-posteriori” vulnerability score, deduced from the observed damage, which is compared to an “a-priori” vulnerability one, evaluated taking into account characteristic indexes for building’s typologies. By means of this comparison an inverse approach to seismic vulnerability assessment, which can be extended to different urban centers, is proposed.

Background: Hospital-acquired infections (HAI) pose a significant danger to global public health, mainly because their numbers are growing exponentially each year. Additionally, the rise of bacterial strains resistant to current treatment options further exacerbates this threat. The study aimed to examine the occurrences of HAIs identified in public hospitals at the county level. Methods: We conducted a cross-sectional study utilizing data provided to the Mures Public Health Directorate from all the public hospitals within this county. We examined HAIs reported during the period spanning from 2017 to 2021, which amounted to a total of 4603 cases. Results: The medical departments reported the highest prevalence of HAIs at 48.25%. The most common infections in-cluded enterocolitis with Clostridioides difficile (32.61%), COVID-19 (19.83%), bronchopneumonia (16.90%), sepsis, surgical wound infections, and urinary tract infections. The five most frequently identified pathogens were Clostridioides difficile (32.61%), SARS-CoV-2 (19.83%), Acinetobacter baumannii (11.82%), Klebsiella pneumoniae (9.58%), and Pseudomonas aeruginosa (7.95%). Acinetobacter baumannii was the predominant agent causing bronchopneumonia, while Klebsiella pneumoniae was the leading cause of sepsis cases. Escherichia coli was the primary agent behind urinary tract infec-tions, and Staphylococcus aureus MRSA was identified as the main etiology for wound infections and central catheter infections. Throughout the study period, there was a significant rise in Clostridioides difficile cases, accounting for 40.36% of all reported HAIs in 2021. Conclusions: The study identifies Clostridioides difficile increase in HAI cases during COVID-19, highlighting the need for careful antibiotic use, and emphasizing the growing challenge of multi-resistant strains in post-pandemic state hospitals.

Edible insects can diversify diets, improve livelihoods, contribute to food and nutrition security, and have a smaller ecological impact. European Union has categorized insects as novel food, and recently, in 2021 and 2022, two species: Tenebrio molitor and Acheta domesticus have been authorized for commercialization. Acceptance and perception of food risk derived from insect consumption vary depending on factors impacting insect consumption acceptability, including neophobic tendencies, gender differences, familiarity, and gastronomic perceptions. The aim of this work was to evaluate the perception and acceptance of edible insects by exploring those factors. The study was carried out on higher education students from Universities from Valencia (Spain). Students recognize insects for their high nutritional value, particularly protein content, and have varying knowledge levels about specific nutritional components. In terms of labeling and marketing, removing health and sustainability benefits from packaging can improve consumer responses. Most respondents prefer clear labeling of insect derivatives, quality certification seals, and complete information about insect content. Students consider marketing and knowledge as significant influencers of insect consumption. In summary, the text highlights the multifaceted nature of insect consumption acceptability. These insights offer valuable perspectives on insect consumption dynamics.

Cardiovascular diseases (CVD) are prevalent and lead to high morbidity and mortality globally. Physiotherapists regularly interact with patients with or at risk of CVDs (pwCVDs). This study aimed to assess the nature of existing evidence, interventional approaches used, and the population groups included in physiotherapy-led health promotion (PLHP) for pwCVDs. The scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Medline, PubMed, Web of Science, Cochrane Central Register of Controlled Trials, CINAHL, and PEDro databases were searched from inception until June 2023. Two reviewers independently screened the titles, abstracts, full text and conducted data extraction. All conflicts were resolved with a third reviewer. A total of 4992 records were identified, of which 20 full-text articles were included in the review. The studies had varied populations, including those with stroke, coronary artery diseases, peripheral artery diseases, hypertension, diabetes, and multiple CVD risk factors. The interventions ranged from exercise and physical activity programs, dietary interventions, education, and counselling sessions with various supplementary approaches. Most interventions were short-term, with less than 12 months of follow-up. Interventions were personalised and patientcentred to promote adherence and health behaviour change. Among the included studies, 60% employed experimental designs, with the remainder using quasi-experimental designs. Although a wide range of PLHP strategies have been used for pwCVDs, exercise and physical activity were employed in 85% of included studies. Other components of health promotion, such as sleep, smoking, and alcohol abuse, should be investigated within PLHP.

Smartphone Addiction is a social issue caused by excessive smartphone use, affecting decision-making processes. Current research on the risky decision-making abilities of smartphone addicts is limited. This study used the fNIRS brain imaging technique and a Sequential Risk-Taking Task experimental paradigm to investigate the decision-making behavior and brain activity of smartphone addicts under varying risk levels. Using a mixed experimental design, the research assessed decision-making ability and brain activation levels as dependent variables across two groups (addiction and control), two risk amounts (high and low), and two outcomes (gain and loss). The study included 42 participants, with 25 in the addiction group and 17 in the control group. Results indicated that risk level significantly impacted the decision-making ability of smartphone addicts, with high-risk levels leading to weaker decision-making ability and increased risk-taking. However, at low risk levels, decision-making abilities between addicts and healthy individuals showed no significant difference. Furthermore, brain imaging results using fNIRS revealed stronger brain activation in the dlPFC region for smartphone addicts under loss outcome conditions, with no significant differences between the two groups in terms of brain activation at varying risk volumes. These findings are critical in promoting healthy smartphone use, guiding clinical treatment, and advancing brain mechanism research.

Dealing with randomness is a crucial aspect that cost-effectiveness analysis (CEA) tools need to address, but existing stochastic CEA tools have rarely examined risk and return from the perspective of global benefits. This paper proposes a stochastic CEA tool that supports medical decision-making from the perspective of global benefits of risk and return, the risk-adjusted incremental cost-effectiveness ratio (ICER). The tool has a traditional form of ICER but uses the risk-adjusted expected cost. Theoretically, we prove that the tool can provide marginal medical decisions that promote the risk-return level on global benefits within any intervention structure and can also serve as a discriminating condition for the optimal intervention structure. Numerical simulations within a framework of mean-variance support the conclusions in this paper.

Melioidosis, or Whitmore's disease, is an infectious disease initiated by a bacteria known as Burkholderia pseudomallei. This bacteria is commonly found in contaminated soil and water. In Malaysia, the mortality from melioidosis infection was reported to be higher than in other infectious diseases. The research on melioidosis is still limited in Malaysia but slightly increasing. The article's objective was to seek all the melioidosis research related to mortality in Malaysia. The information from the selected papers was then abstracted into two sections; Section 1: Review of literature and Section 2: Findings on mortality from melioidosis in Malaysia. In Section 1, the information on transmission and clinical features of melioidosis, demographic, severity of melioidosis, a clinical signs of melioidosis, diagnosis of melioidosis, management of melioidosis, the economic burden of melioidosis, and incidence of mortality from melioidosis were discussed in this paper. Meanwhile, in Section 2, the findings on mortality of melioidosis in Malaysia were discussed according to eight published articles. It is important to manage patients with melioidosis with appropriate treatment and management to reduce severe complications, high fatality rate, and relapse. More published research on melioidosis will provide input to the clinicians on a more detailed understanding of how to improve the diagnosis of melioidosis and the prognosis factors of this disease.

This study is follow-up of the steel shot transformation under the influence of environmental factors research (Lisin et al., 2022) and is the initial stage of investigating the iron behavior in soils during steel shot corrosion under a number of factors: the metallic lead in soils, atmospheric precipitation, excess organic matter. The results obtained show that corrosion of steel ammunition is a continuous process, including the formation of a poorly soluble rust crust on the surface of the steel and the mineralization of the metal until it is destroyed. As a result, the metal transformed into rust form, is a constant source of iron ions and dispersed rust particles migrating in soil waters and accumulating in soils. In addition, the aggregation of corrosion products of steel ammunition is the cause of a change in physical and mechanical properties of soils, which leads to a violation of the air and water migration regime of soils and an increase in surface runoff from the territories of shooting activity. The highest environmental risks are observed when steel ammunition is used on shooting areas where metallic lead intensifies steel shot corrosion rate, while the deposited steel shot activates the deterioration of previously encapsulated metal and — if steel and lead ammunition are used at the same time — slows down the encapsulation of newly deposited metallic lead, which catalyses the accumulation and migration of lead in environmental components.

Preeclampsia (PE) is associated with an increased risk of cardiovascular disease (CVD) in later life. Postpartum cardiovascular risk screening could identify patients who would benefit most from lifestyle interventions. However, there are no readily available methods to identify these high-risk women. We propose that placental lesions may be useful in this regard. Here, we sought to determine the association between placental lesions and lifetime CVD risk. Placentas from 85 PE women were evaluated for histopathological lesions. At 6 months postpartum, a lifetime cardiovascular risk score was calculated. Placental lesions were compared between CVD risk groups and the association was assessed using odds ratios. Multivariable logistic regression was used to develop prediction models for CVD risk with placental pathology. Placentas from high-risk women had more severe lesions of maternal vascular malperfusion (MVM) and resulted in a 3-fold increased risk of screening high-risk for CVD (OR 3.10[1.20-7.92]) compared to women without these lesions. MVM lesion severity was moderately predictive of high-risk screening (AUC 0.63[0.51,0.75]; sensitivity 71.8%[54.6,84.4]; specificity 54.7%[41.5,67.3]. When clinical parameters were added, the model’s predictive performance improved (AUC 0.73[0.62,0.84]; sensitivity 78.4%[65.4,87.5]; specificity 51.6%[34.8,68.0]. The results suggest that placenta pathology may provide a unique modality to identify women for cardiovascular screening.

Hotel water systems colonized with Legionella spp. have been the source of travel-associated Legionnaires’ disease and cases, clusters or outbreaks continue to be reported worldwide each year. A total of 132 hotels linked with travel-associated Legionnaires’ disease, as reported through the European Legionnaires’ Disease Surveillance Network, were inspected and tested for Legionella spp. during 2000–2019 by the public health authorities of the island of Crete (Greece). A total of 3,311 samples were collected: 1,885 (56.93%) from cold water supply systems, 1,387 (41.89%) from hot water supply systems, 37 (1.12%) were swab samples and two (0.06%) were soil. Of those, 685 (20.69%), were collected from 83 (62.89%) hotels, testing positive (≥ 50CFU/L) for Legionella pneumophila) serogroups 1-10, 12-14 and non-pneumophila species (L. anisa, L. erythra, L. tusconensis, L. taurinensis, L. birminghamensis, L. rubrilucens, L. londiniesis, L. oakridgensis, L. santicrusis, L. brunensis, L. maceacherii). The most frequently isolated L. pneumophila serogroups were 1 (27.92%) and 3 (17.08%). Significantly higher isolation rates were obtained from hot water supply systems (25.96%) versus cold water systems (16.98%) and swab samples (13.51%). A Relative Risk (R.R.) > 1 (p < 0.0001) was calculated for hot water temperature <55 °C (R.R.: 4.43), chlorine concentrations <0.2 mg/L (R.R.: 2.69), star rating <4 (R.R.: 1.73) and absence of Water Safety Plan implementation (R.R.: 1.57).

This paper aims to delve into how gender dimensions observed before, during and after a disaster, have been addressed in two internationally recognised frameworks developed for reducing risks of disasters: Hyogo Framework Action (2005-2015) and Sendai Framework for Disaster Risk Reduction (2015-2030). Building on a systematic review, we evaluate 33 scholarly peer-reviewed journal articles, including book chapters and websites in areas of gender, disaster risk reduction and vulnerability. This study documents a comparative picture of these two frameworks and shows the practical implications of the Sendai Framework for Disaster Risk Reduction (SFDRR) by addressing women’s empowerment in the light of their active participation in disaster risk reduction process. The findings of the study suggest that the frameworks have discussed the reduction of women’s socioeconomic vulnerabilities, as well as encouraged their empowerment. Comparing the two frameworks, it appears in the current study that there has been a significant gap in the existing literature that does not explicitly document comparing and contrasting features of a gender lens in the policy documents.

Identifying and assessing risk is one of the most important processes in managing complex systems and requires careful consideration. The need for an effective, efficient approach to risk management is considerably more important for defense industries, because they are exposed to risk already in early stages of development. This paper uses Heterogeneity and Homogeneity analysis between risk factors with Cochran’s Q test and Multidimensional scaling in order to present the complexity of the risk factors relevant to defense SoS, and proposes a methodology for identifying, analyzing and monitoring the risks that they face. Findings from an in-depth analysis of 46 classified defense SoS shows a need to focus on three main risks faced by defense projects: insufficient human resources, changes in the original specifications, and lack of other (non-human) resources. The paper also presents some recommendations for minimizing risk factors in defense SoS.

In public health literature the risk of death or disease associated with a dietary, environmental of behavioral factor is most commonly denoted by odds ratio (OR), hazard ratio (HR) or risk ratio (RR). The ratio indices have several desirable statistical properties. However, the most important question is whether there are some evolved innate norms of perception of risk that people use and what they are. We conducted a simple one question survey of 98 individuals with different age, sex, educational and professional backgrounds. The respondents were asked to judge the relative perceived risk of four different hypothetical habits for which data on the percentage of people affected by the disease with and without the habit was given. They were asked to rank the risks for the four habits. Results showed that the habits that had the highest difference between probability of acquiring the disease were ranked high on risk perception. The probability ratios did not affect risk perception significantly. Further age, sex, profession or formal training in statistics did not affect the response significantly. Even individuals that were formally trained to use OR and HR as risk indicators, preferred using probability differences over ratios for judging their own risk in the perceived context. This preliminary inquiry into intuitive statistical perception suggests that designing statistical indices based on people’s innate perception may be a better strategy than trying to train people to understand the indices designed by expert statisticians.

Identifying and assessing risk is one of the most important processes in managing complex systems and requires careful consideration. The need for an effective, efficient approach to risk management is considerably more important for defense projects based on systems of systems (SoS), because they are exposed to risk already in early stages of development. This paper uses advanced data science tools to present the complexity of the risk factors relevant to defense systems, and proposes a methodology for identifying, analyzing and monitoring the risks that they face. Findings from an in-depth analysis of 46 classified defense projects based on SoS shows a need to focus on three main risks faced by defense projects: uncertainty, the lack of clearly defined goals, and managing a system under constrained conditions. The paper also presents some recommendations for minimizing risk factors in SoS for defense projects.

The complex systems that require safety are the Safety Critical Systems. Maintaining these systems is a big challenge. Now a days, safety is a very critical requirement for the latest systems. Safety critical systems must be safe. Different approaches to ensure quality and safety in safety critical systems has been discussed in this paper. A comparison is also conducted between these various approaches. Safety critical systems must remain more influential in future.

Controlling and managing risk is always a critical point for the managers, investors and even consultants. Having clear and better percepts about future can reduce the risk of fail. In addition it is important for a risk analyzer to consider the stakeholders views and senses about the risk. This research aimed at framing a comprehensive risk management model which builds up on stakeholder requirements and forecasting techniques. This conceptual model attempts to use the stakeholder’s points of view to write prefer and probable scenarios to neglect critical risks and increase the chance of success in long-term plannings. Using futures studies methods prepare decision makers for the possible upcoming events and donate them a powerful tool to handle the uncertainties cover the future.

In last decades, growing migration flows have modified the obstetric clinical care, requiring specific attention by health care systems. The aim was to describe the phenomenon focusing on miscarriage (pregnancy loss at <20 weeks). Patients admitted for care at miscarriage in a six-year period (2012-17) were revised. Miscarriage rates in all ethnic groups, dichotomized in early (within the first 12 weeks of gestation) and late (at <20 weeks) pregnancy loss. Associations between women's characteristics (age, parity, inter-pregnancy interval (IPI)) were explored to elucidate any differences. A total of 1,940 patients were included, segregated in early (n = 1769, 91.2%) and late (n = 171, 8.8%) pregnancy losses. Caucasian ethnicity was the most common (87.9%), leaving the minority groups to 12.1%. Maternal age was higher among Caucasians women than other subgroups, in contrast to Asiatic patients. Nulliparity was observed in 1045 (53.9%) patient, more widespread among Caucasian and Maghrebins. A positive obstetric history counting at least one miscarriage was frequent, ranging from 22.2% to 75%, in particular among Asiatic women, while the recurrence in Caucasians. In Afro-Carribeans the most relevant rate of late miscarriage was found. By multiple regression modelling, maternal age, nulliparity and Afro-Carribean were identified as determinants. Maternal ethnicity should be considered in the management of pregnancy losses in combination with already well-defined risk factors, including age at miscarriare and nulliparity.

Objective:The application of information technology (IT( is fundamental in the hospitals to stay competitive.In this regard, recognizing the main risks to the implementation of IT in hospitals can provide vastopportunities to improve its efficiency and help to make strategic decisions. This study aimed tosearch for the main risks of implementation of IT projects in the hospitals of Tehran. Methods: This was a practical and cross-sectional study which was conducted in the 18 hospitals of Tehran,Iran, 2018; in which a sample of 65 members were studied. The required data were collected using a questionnaire to examine seven main risks, including market, project management, human resources, technical, organizational, financial, strategic risks. The collected data were analyzed using SPSS 19.0. Additionally, the method used to test the risks in this study was structural equation modeling, which was ran using LISREL 9.30. Results: The results showed that among the seven main risks of to the implementation of IT in hospitals, the highest and lowest means were related to the human resource risks and the market risks, respectively. Also, according to the SEM, human resource risks and market risks had the highest and lowest effects, respectively. Conclusion: Announcing the use of IT in the hospitals, holding conferences about new IT developments with employees, suitable training, encouraging them to use IT tools, providing a motivating atmosphere to use IT tools for employees, are a few effective ways of overcoming the human resource risks.

In this paper we analyze the relationship between bankruptcy risk and the corporate life cycle in Pakistan from 2005 to 2014. For this purpose, we run a Hierarchical Linear Mixed Model (HLM) for a sample of 301 non-financial listed firms in 12 different sectors. The empirical outcomes reveal that firms during introduction, growth and, decline stages (mature stage) of life-cycle experience higher (lower) bankruptcy risk. Moreover, in juxtaposition with growth stage, bankruptcy risk is higher at the introduction stage of life-cycle. These findings suggest that financial managers should be cautious about the financial fragility of the firm at each stage of corporate life-cycle. The results also entail that Pakistani firms do not follow a sequential pattern in their life-cycle rather they have the tendency to revert to a previous stage or jump to the next stage of life-cycle. This is the first study that empirically examines the association between firm life-cycle stage and corresponding bankruptcy risk and asserts that managers must incorporate the life-cycle effects into their financial planning and decision making for sustainable working of an enterprise.

Portfolio weights solely based on risk avoid estimation error from the sample mean, but they are still affected from the misspecification in the sample covariance matrix. To solve this problem, we shrink the covariance matrix towards the Identity, the Variance Identity, the Single-index model, the Common Covariance, the Constant Correlation and the Exponential Weighted Moving Average target matrices. By an extensive Monte Carlo simulation, we offer a comparative study of these target estimators, testing their ability in reproducing the true portfolio weights. We control for the dataset dimensionality and the shrinkage intensity in the Minimum Variance, Inverse Volatility, Equal-risk-contribution and Maximum Diversification portfolios. We find out that the Identity and Variance Identity have very good statistical properties, being well-conditioned also in high-dimensional dataset. In addition, the these two models are the best target towards to shrink: they minimise the misspecification in risk-based portfolio weights, generating estimates very close to the population values. Overall, shrinking the sample covariance matrix helps reducing weights misspecification, especially in the Minimum Variance and the Maximum Diversification portfolios. The Inverse Volatility and the Equal-Risk-Contribution portfolios are less sensitive to covariance misspecification, hence they benefit less from shrinkage.

Some of the recent large-scale national projects in South Korea are delayed or suspended due to belated responses to risk occurring on site. Currently, the Far East District (FED) project is being implemented to relocate the US Army bases from Yongsan to Pyeongtaek. Because of lack of experience and understanding about the characteristics of such a project, the deadline of taking over to the US Army Korea has been missed. This study identifies problems of each participant in the Yongsan Relocation Plan (YRP) of the US Army Korea with respect to construction project management and establishes a risk management strategy reflecting characteristics of FED project. To derive significant risk factors influencing YRP, various field data like weekly and monthly reports and other reports on construction condition are analyzed, and experts’ advices are collected and a survey is conducted. Mediators and latent variables are ultimately obtained. Furthermore, a structural equation model is used to both analyze and evaluate complex causal relations among many variables of YRP. The impact of risk factors on the schedule, quality and cost of the project is analyzed. In particular, the case of Site A is examined to see how the project is affected by those risk factors.

Introduction: Ambient air pollution is major global health problem and commercial drivers are particularly exposed to it. No systematic assessment of the health risks associated with occupational exposure to ambient air pollution in this population has been carried out. Methods: We conducted a systematic review using a protocol-driven strategy. Papers published from inception to 20th April 2018 in MEDLINE, EMBASE, CINAHL, African journals online, Cochrane library, ISRCTN and WHO ICTRP databases were screened for inclusion by two independent reviewers. Original articles with at least an available abstract in English or French were included. Results: The initial search retrieved 1454 published articles of which 20 articles were included. 3 Studies reported a significant difference in white blood cells (106/L) among commercial motorcyclists compared to rural inhabitants (5.041±1.209 vs 5.900±1.213,p=0.001), an increased risk of lung cancer (RR=1.6, 95%CI 1.5-1.8) in bus drivers and an increased standardized mortality ratio (SMR) in bus drivers from Hodgkin’s lymphoma (SMR 2.17, 95%CI 1.19-3.87) compared to white collar workers. Other studies also found that drivers had more oxidative DNA damage and chromosome breaks. 4 papers failed to demonstrate that the drivers were more exposed to air pollution than the controls. 3 other studies also reported no significant difference in lung function parameters and respiratory symptoms. The genetic polymorphisms of detoxifying enzymes were not also homogeneously distributed compared to the controls. Conclusion: There is some evidence that occupational exposure to ambient air pollution among commercial drivers is associated with adverse health outcomes but the existing literature is limited with few studies of small sample size, methodological weaknesses and contradictory findings. Further research is recommended.

Uncertainty is the main source of risk of geological hazards in tunnel engineering. Uncertainty information not only affects the accuracy of evaluation results, but also affects the reliability of decision-making schemes. Therefore, it is necessary to evaluate and control the impact of uncertainty on risk. In this study, the problems in existing entropy-hazard model such as inefficient decision-making and failure of decision-making are analysed, and an improved uncertainty evaluation and control process are proposed. Then the tolerance cost, the key factor in the decision-making model, is also discussed. It is considered that the amount of change in risk value (R1) can better reflect the psychological behaviour of decision-makers. Thirdly, common attribute decision models, such as the expected utility-entropy model, are analysed, and then the viewpoint of different types of decision-making issues that require different decision methods is proposed. The well-known Allais paradox is explained by the proposed methods. Finally, the engineering application results show that the uncertainty control idea proposed here is accurate and effective. This research indicates a direction for further research into uncertainty, and risk control, issues affecting underground engineering works.

Philippines as an archipelago and tropical country, which is situated near the Pacific ocean, faces uncertain rainfall intensities. This makes environmental, agricultural and economic systems affected by precipitation difficult to manage. Time series analysis of Philippine rainfall pattern has been previously done, but there is no study investigating its probability distribution. Modeling the Philippine rainfall using probability distributions is essential, especially in managing risks and designing insurance products. Here, daily and cumulative rainfall data (January 1961 - August 2016) from 28 PAGASA weather stations are fitted to probability distributions. Moreover, the fitted distributions are examined for invariance under subsets of the rainfall data set. We observe that the Gamma distribution is a suitable fit for the daily up to the ten-day cumulative rainfall data. Our results can be used in agriculture, especially in forecasting claims in weather index-based insurance.

Websites and applications use personalisation services to profile their users, collect their patterns and activities and eventually use this data to provide tailored suggestions. User preferences and social interactions are therefore aggregated and analysed. Every time a user publishes a new post or creates a link with another entity, either another user, or some on-line resource, new information is added to the user profile. Exposing private data does not only reveal information about single users' preferences, increasing their privacy risk, but can expose more about their network that single actors intended. This mechanism is self-evident on \emph{social networks} where users receive suggestions based on their friends' activity. We propose an information theoretic approach to measure the differential update of the anonymity risk for time-varying user profiles. This expresses how privacy is affected when new content is posted and how much third party services get to know about the users when a new activity is shared. We use real Facebook data to show how our model can be applied on a real world scenario.

Adaptation to climate change is being addressed in many domains. This means that there are multiple perspectives on adaptation; often with differing visions resulting in disconnected responses and outcomes. Combining singular perspectives into coherent, combined perspectives that include multiple needs and visions can help to deepen the understanding of various aspects of adaptation and provide more effective responses. Such combinations of perspectives can help to increase the range and variety of adaptation measures available for implementation or avoid maladaptation compared with adaptations derived from a singular perspective. The objective of this paper is to present and demonstrate a framework for structuring the local adaptation responses using the inputs from multiple perspectives. The adaptation response framing has been done by: (i) contextualizing climate change adaptation needs; (ii) analyzing drivers of change; (iii) characterizing measures of adaptation; and (iv) establishing links between the measures with a particular emphasis on taking account of multiple perspectives. This framework was demonstrated with reference to the management of flood risks in a case study Can Tho, Vietnam. The results from the case study show that multiple perspective framing of adaptation responses enhance the understanding of various aspects of adaptation measures, thereby leading to flexible implementation practices.

This review of current research into at-risk programs serves to categorise and characterise existing programs and to evaluate the contribution of these programs to assisting students at-risk from marginalised backgrounds. This characterisation questions the (sometimes) implicit assumptions and the consequences of those assumptions inherent in and behind these various accounts. This involves a synthesis and reformulation, based on epistemological standpoints, both explicit and implied, of the various researchers. Using as a lens the (various and varied) understandings of social justice and the goals of education (Gale & Densmore, 2000; 2003) I identify three sometimes overlapping and sometimes contesting standpoints in relation to at-risk students, characterised as instrumentalist or rational technical, social constructivist or individualist and critical transformative or empowering. I argue that programs ‘which simply seek to achieve change in the individual young people are doomed to failure’ (Stewart, 1998, 4) and that a critical transformative understanding of at-risk may deliver improved outcomes for young people by challenging ‘the school context in which the young people are located’ (Stewart, 1998, 4).

This study investigates the factors influencing consumers' intentions to purchase overseas travel packages via social media in Thailand, with a focus on consumer trust and perceived risks. A mixed-methods approach was employed, combining qualitative and quantitative research techniques. In the qualitative phase, the Fuzzy Set Delphi Method was applied to gather expert consensus from 19 participants. For the quantitative phase, a survey was conducted among 600 individuals who had experience purchasing overseas travel packages on social media in Thailand. First-order and second-order confirmatory factor analyses were used to examine the relationships between eight identified factors: social media influencer, e-WOM, trust, perceived risk, brand image, rating review, personal attitude, and destination image. The results indicate that trust and perceived risk are the most significant factors affecting purchase intention. Trust plays a crucial role in customers' decision-making processes, while perceived risk influences their tendency to avoid purchasing packages if the risk is perceived as high. The insights gained from this study contribute to the understanding of factors influencing purchase intentions for overseas travel packages through social media in Thailand, providing valuable information for travel agencies to develop effective marketing strategies.

AbstractThe Association of Mutual Funds of India (AMFI) under the direction of the Securities and Exchange Board of India (SEBI) provided open access to various risk parameters with respect to MidCap and SmallCap funds on its website in February, 2024. This disclosure of month wise cross-sectional data depicting stress-test and liquidity analysis was hailed as a milestone as it provided a glimpse into inherent risk of mutual funds. The AMFI dataset consisted of 14 variables including stress test results, ownership concentration on both liability & asset sides, standard deviation on portfolio’s returns, portfolio beta, trailing 12-month PE ratio, portfolio turnover etc. Among these, the primary variable identified in grading mutual fund is the stress test parameter, expressed as number of days required to liquidate 50% and 25% of the portfolio respectively on a pro-rata basis under stress condition. A higher number of days to liquidate the portfolio under stress conditions represented higher risk for the investor. The objective of our paper is to test various neural network models which can help in predicting stress levels with the highest accuracy and specificity in MidCap and SmallCap mutual funds based on AMFI’s 14 parameters as predictors.Our study utilizes AMFI datasets available for MidCap and SmallCap mutual funds from February 2024 (inception period) to May 2024. To operationalize the analysis, the derived response variable was binned to represent high and low risk based on the time required for pro-rata liquidation of the portfolio. The study employed feed-forward neural networks, with the logistic regression as the step function, to model the relationships. Results suggest that the simpler neural network models with one hidden layer and two to three nodes show higher accuracy and specificity. Analysis also shows that more complex architectures do not always guarantee better performance as these models might suffer from higher bias. By leveraging advanced computational techniques, this study contributes to the ongoing discourse surrounding risk management and decision-making in the realm of mutual fund investments.

The ISO 2859 and ISO 3951 series provide acceptance sampling procedures for lot inspection, allowing both sample size and acceptance rule to be determined, starting from a specific value either for the consumer or producer risk. However, insufficient resources often make it difficult to implement “ISO sampling plans.” In cases where the sample size is determined by external constraints, the focus shifts from determining sample size to determining consumer and producer risks. Moreover, if the sample size is very low (e.g. one single item), prior information should be included in the statistical analysis. For this reason, it makes sense to work within a Bayesian theoretical framework, such as that described in JCGM 106. Accordingly, the approach from JCGM 106 is adopted and broadened so as to allow application to lot inspection. The discussion is based on a “real-life” example of lot inspection on the basis of a single item. Starting from simple assumptions, expressions for both the prior and posterior distributions are worked out, and it is shown how the concepts from JCGM 106 can be reinterpreted in the context of lot inspection. Conceptual differences regarding the definition of consumer and producer risks in JCGM 106 and in the ISO acceptance sampling standards are elucidated and a numerical example is provided.

Since 2017 Cartagena UNESCO World Heritage has threatened to be categorized as "in Danger" by UNESCO. This research analyzes two main critical aspects, Governance and Current state of the Site. Regarding Governance, the study aims to identify strengths, weaknesses, opportunities and treats in the UNESCO Site. Exemplary heritage management systems are studied to propose an adaptable management approach specifically for Cartagena. On the other hand, a comprehensive analysis is conducted utilizing a photographic report that highlights the major issues arising from inadequate heritage management. Hyperspectral images obtained from a previous study are employed to identify vegetation and asbestos-cement roofs within the cultural heritage Site. The study reveals that the ambiguity surrounding decision-making authority for heritage management, distributed between the Mayor's Office and the Ministry of Culture, is a primary challenge. This fragmentation has resulted in duplicated efforts and a lack of coordinated action, significantly compromising the conservation and protection of the cultural heritage Site. Moreover, twelve current shortcomings of cultural heritage in Cartagena are identified through authors' five-year on-site regular visits, photographic reports and observation. To address the prevailing concerns, a new line of command for cultural heritage management is proposed as the most effective means of tackling these challenges. Additionally, general recommendations are presented to mitigate the existing problems and prevent the classification of Cartagena's heritage as "at risk" by UNESCO in the near future. This research provides a scientific perspective, drawing upon years of experience studying heritage and residing in the city, devoid of political influences or conflicts of interest.

As in many parts of the world, rural-urban, forest-urban interface areas surrounding urban regions expose the natural areas they interact with to a threat of fire risk that can reach various sizes. This risk has been assessed for various regions of the world using many different methods and numerical models so far. Among these, it is seen that machine learning models have successful applications in risk assessment and risk prediction studies. For the fire risk prediction of Istanbul's yet unurbanized regions, but where the city is anticipated to potentially shift, data was collected using the opportunities provided by Geographic Information Systems and Remote Sensing technologies based on fires that occurred between 2000-2021, and the region was examined. Machine learning methods' Random Forest (RF), Extreme Gradient Boosting (XGB), and Light Gradient Boosting (LGB) models were applied for the classification of factors effective in fire. The best result was given by the RF model with 0.93 accuracy, 0.062 F1 score, and 0.753 Area Under Curve (AUC) value. In the classification of factors in the RF model, the grouping between fire-initiating factors and factors effective in spreading is evident, while this distinction is partially noticeable in the other two models.

Land use and land cover change (LULCC) is a critical factor for enhancing the soil erosion risk and land degradation process in the Wabi Shebelle Basin. Up-to-date spatial and statistical data on basin-wide erosion rates can provide an important basis for planning and conservation of soil and water ecosystems. The objectives of this study were to examine the magnitude of LULCC and consequent changes in the spatial extent of soil erosion risk, and identify priority areas for Soil and Water Conservation (SWC) in the Erer Sub-Basin, Wabi Shebelle Basin, Ethiopia. The soil loss rates were estimated using an empirical prediction model of the Revised Universal Soil Loss Equation (RUSLE) outlined in the ArcGIS environment. The estimated total annual actual soil loss at the sub-basin level was 1.01 million tons in 2000 and 1.52 million tons in 2018 with a mean erosion rate of 75.85 t ha^–1 y^–1 and 107.07 t ha^–1 y^–1, respectively. The most extensive soil loss rates were estimated in croplands and bare land cover, with a mean soil loss rate of 37.60 t ha^–1 y^–1 and 15.78 t ha⁻¹ y⁻¹, respectively. The soil erosion risk has increased by 18.28% of the total area, and decreased by 15.93%, showing that the overall soil erosion situation is worsening in the study area. We determined SWC priority areas using the Multi-Criteria Decision Rule (MCDR) approach, indicates that the top three levels identified for intense SWC account for about 2.50%, 2.38%, and 2.14%, respectively. These priority levels are typically situated along the steep slopes in Babile, Fedis, Fik, Gursum, Gola Oda, Haramaya, Jarso, and Kombolcha districts that need emergency SWC measures.

The rapid evolution of financial technology (fintech) has significantly transformed the financial services landscape, creating opportunities for innovation and introducing new risks. Traditional financial institutions and fintech companies operate under different paradigms, resulting in disparate risk management practices. This paper proposes a comprehensive framework for integrating operations and risk management practices between traditional financial institutions and fintech companies. By leveraging advanced technologies such as artificial intelligence (AI) and machine learning (ML), the framework aims to ensure consistent and effective risk assessment across the financial sector. The financial services industry is characterized by rapid innovation, primarily driven by fintech companies offering various services that enhance efficiency, accessibility, and customer satisfaction. However, the growth of fintech brings substantial risks, including cyber threats, data privacy concerns, regulatory compliance challenges, and operational vulnerabilities. Traditional financial institutions prioritize stability, security, and compliance within established risk management frameworks. The divergence in operational models and risk management approaches creates a fragmented risk landscape, posing significant challenges to the financial system's stability and security. This paper identifies the critical need for a unified framework integrating the risk management practices of traditional financial institutions and fintech companies. The proposed framework leverages AI and ML to enhance the accuracy and comprehensiveness of risk assessments, utilizing a centralized data repository for real-time risk assessment. Unified risk management policies covering cybersecurity, operational risk, regulatory compliance, financial crime, and real-time monitoring and reporting tools ensure robust risk management protocols and prompt response to potential risks. Aligning with regulatory requirements and incorporating best practices from both sectors, the integrated risk management approach enhances the financial ecosystem's stability, security, and public confidence.

In the last decade, readily available electronic devices have created unprecedented opportunities for teens to access a wide variety of information and media – both positive and negative – on the internet. Despite the increasing number of initiatives taking place worldwide intended to assess and mitigate the online risks encountered by children and adolescents, there is still a need for a better understanding of how adolescents use the internet and what consequences they may face. We conducted a cross sectional online survey of a convenience sample of 733 8th and 9th grade students in Utah. The survey contained eight questions regarding students’ exposure to three types of online risk scenarios: content risk, contact risk, and commercial risk. Independent variables included students’ online behaviors, use of social media and private messaging apps, and adult supervision of online activities. Logistic and negative binomial regression models indicated that female gender, social media use, and chatting with strangers were associated with exposure to multiple unsafe online scenarios. Our results provide critical information to practitioners involved in the development of educational initiatives by building a profile of potentially risky online behaviors and allow them to tailor their initiatives to meet the needs of more vulnerable populations.

Breast Cancer Associated Susceptibility Proteins Type 1/2 (BRCA1/2) promote cellular functioning by modulating NRF2-mediated antioxidant signaling. Redox failure in women with BRCA1/2 insufficiency increases the risk for breast/ovarian/uterine cancers. Risk‐reducing salpingo‐oophorectomy (RRSO) is a prophylactic surgery of the reproductive organs, which is frequently conducted by the age of 40 to lower the occurrence of cancer in women with BRCA1/2 mutations. However, abrupt estrogen decline following RRSO causes ovarian failure, which implicates various cellular physiological processes, resulting in increased release of free radicals and subsequent severe onset of menopausal symptoms. Comfort measures (e.g., hormonal replacement therapy (HRT) and mindfulness-based stress reduction (MBSR)) may improve chronological menopause-related quality of life, but their specific effects are not clear in women with gene mutations. Aiming to fill the gap, this study used path analysis to examine the effects of HRT and MBSR on menopausal symptoms among RRSO patients (N = 199, mean age = 50.5 ± 6.7 years). HRT alleviated menopausal symptoms in BRCA2 carriers and women who were physically active, premenopausal at the time of RRSO, had a high BMI, and had no history of breast cancer. It increased the severity of urogenital symptoms in those with a history of cancer. MBSR, on the other hand, was associated with increased intensity of most menopausal symptoms. The results suggest that young women undergoing recent RRSO may benefit from HRT at an individual level while their need for extensive measures to optimize their psychological wellbeing is ongoing. Adverse effects of MBSR, which are captured in the present study imply that MBSR may interfere with redox sensitivity associated with estradiol fluctuations in BRCA1/2 carriers. Investigations are needed to test this hypothesis and elaborate on the underlying mechanisms in those women.

The inaugural AIDS Program in Brazil was established in São Paulo in 1983, with the Instituto Adolfo Lutz appointed for laboratory assistance. Subsequently, research on HIV infections and HIV/HTLV (HIV/HTLV-1 and HIV/HTLV-2) co-infections were conducted. This narrative review focuses on studies from the Immunology Department (1983–2017) that significantly influenced AIDS diagnosis or provided epidemiological data such as prevalence rates, sex, age, and risk factors. Ten studies, encompassing over 8,000 individuals, are discussed. During 1983–1985, nearly all AIDS cases were attributed to homosexual/bisexual men aged 31 years old. Subsequently, heterosexual men and women emerged as risk groups owing to intravenous drug use (IDU) and/or unprotected sexual intercourse with AIDS patients or multiple partners per year. From 1985 onwards, vertical transmission led to child infections. HIV/HTLV co-infection rates decreased over time, initially associated with male IDU, and in the 2010s, with females, IDU, and individuals aged &gt;40 years. Trends in HIV and HIV/HTLV co-infections among younger men and women (&lt;30 years of age) were observed from 2015–2017. The changing characteristics and risk groups for HIV and HIV/HTLV co-infections over the years underscore the necessity for ongoing public policies to prevent retrovirus transmission, particularly among adolescents and young adults.

Cardiovascular comorbidity is a common companion of psoriasis and psoriatic arthritis (PsA). Recently, a significant link has been found between the HLA-Cw6 allele and a better cardiometabolic profile in these patients. We aimed to check this finding in our setting. Cross-sectional observational study (n: 572 psoriasis patients, 30% with PsA). Different study variables were collected in detail, as well as classic cardiometabolic risk factors. The distribution of the HLA-Cw6 allele and the IFIH1/MDA5 gene variants previously linked to disease risk was determined in the study cohort and stratified according to the cardiometabolic comorbidity. Linear and logistic regression models were constructed to analyze these associations. The study cohort included 309 men and 263 women, mean age 46.7 years (SD 14.5), mean disease duration 19.4 years (SD 14.8). We confirmed the known association between HLA-Cw6 and type I psoriasis (familial, severe, early onset). Psoriasis severity (OR: 2.14), female sex (OR: 1.63), and the IFIH1/MDA5 rs1990760 TT genotype (OR: 1.62) were significantly related to PsA, while HLA-Cw6 resulted protective (OR: 0.65). HLA-Cw6 carriers showed lower waist perimeter, lower BMI, and lower risk of both hypertension (OR: 0.52, p<0.001) and diabetes (OR: 0.36, p<0.001), but these findings were no longer apparent upon adjusted regression models. No IFIH1/MDA5 gene variant was associated with any cardiometabolic risk factor. The influence of HLA-Cw6 on the cardiometabolic risk profile of psoriatic patients seems to be explained by other factors (age, sex, duration of the disease or arthritis) and not by this biomarker itself.

Anemonia viridis is an abundant and widely-distributed temperate sea anemone that can form dense congregations of individuals. Despite the potential severity of its sting, few detailed cases have been reported. We report a case of a severe toxic reaction following an A. viridis sting in a 35-year-old oceanographer. She developed severe pain, itching, redness and burning sensation, which worsened one week after treatment with anti-inflammatories, antihistamines and corticosteroids. Prompted by this event, and due to the insufficient risk prevention, lack of training for marine-environment users and lack of research into sting-specific first-aid protocols, we evaluated the cnidocyst response to five different compounds commonly recommended as rinse solutions in first-aid protocols (seawater, vinegar, ammonia, baking soda and freshwater) by means of the Tentacle Solution Assay. Vinegar and ammonia triggered an immediate and massive cnidocyst discharge after their application and were classified as activator solutions. Baking soda and freshwater were also classified as activator solutions, although with a lower intensity of discharge. Only seawater was classified as a neutral solution and therefore recommended as a rinse solution after A. viridis sting, at least until an inhibitory solution is discovered.

Background: This article evaluates the perception of drug use control and strategies in Valencia City (Spain) in a general and clinical population, in two independent studies. Material and Methods: 1071 people participated. In the Study 1 (n= 924) the entire sample came from general population (GP), and in the Study 2 (n=147), 68 were drug users being treated in an Addictive Behaviors Unit (ABU), and 79 people of the GP. The drug use control perception and strategies in both subgroups were compared. The participants filled in the Drug Use Strategies Scale and a Drug Use Survey. Results: A high level of perception of drug control in GP was obtained (72,7% in the Study 1 and 67,5% in the Study 2), and 32.5% in ABU subgroup. People in the PG and drug users in treatment differ in some control strategies. A predictive profile of the perception of control was obtained for the Study 2. Conclusion: The high degree of perception of controlling drug use in the GP, and partially in drug users being treated, and the specific control strategies reported suggests that moderate use and drug control strategies are a great value alternative to bear in mind compared to abstinence.

The prognostic abilities of artificial intelligence and neuroscience in forensics and the criminal justice system stand as a reformatory paradigm for understanding any criminal conduct. While the use of artificial intelligence has been labeled transformational data analytical capabilities, neural predictive approaches also enable an intricate understanding of culpability and criminal propensities. The literature on the complex nature of neuroprediction and artificial intelligence, its ethical deliberations and its usability in curving recidivism are analyzed. This theoretical review elucidates the complex interplay, nuptial relationships and convergence of these relationships in the quest for justice. The consequences of not protecting individual rights in the criminal justice system are surveyed using grounded theory. The degree of acceptability and dependability of AI-generated evidence in legal proceedings are also reviewed. All these topics are yet to be contemplated under one roof to offer an argumentative view. The author expects to prompt readers and new commers to embrace more sociolegal and technological research before incorporating such research in the Indian Judiciary. The review focuses on the question of whether to blame such technology inclusion wholly or rather to prioritize the acquisition of bias-free pretrained datasets and processing models.

This study investigates the complex role of financial risks in the context of public–private partnerships (PPPs) in India and their relationship to the amount and extent of investments made by private partners (s). We hypothesize that subsidies, bid criteria, and risk have a positive relationship with investments made by private partners. A project’s leverage moderates these relationships. Regression was used to analyze the hypotheses using SPSS 24 and PROCESS Macro. Data from the World Bank were collected from 2009 to 2019 for the study variables. Interestingly, our research finds support for these relationships that may seem contrary to some commonly-held notions of risk relationships, such as – the government using ‘viability gap’ funding to attract private investment and ‘leverage’ does not moderate the relationship between risk assumed and private investment. This study is among the first to recognize and elaborate on financial risk relationships, specifically in the context of Indian PPPs. These findings are significant for both private and public participants in terms of financial considerations in PPP projects, especially in emerging markets.

Cold brew coffee has emerged as a new trend during the last decade. However, “cold brew” is an extraction style of ground roasted coffee with water at less than body temperature (typically 8°C or room temperature) rather than a beverage per se. Cold brew extraction poses several challenges including the need of specific optimization depending on the multivariate influences of coffee variety and processing, roast degree, grinding, dosage, water composition, turbulence, brew system (drip, immersion etc.), time and temperature. While cold brew is typically characterized by a floral sweetness, over-extraction may lead to abundant acidity and bitterness. To avoid this, an extraction degree of 70% was suggested using rather shorter times (i.e. 2 h at 15°C with 80 g/L coffee with optimized medium roast profiles). Due to the lack of sterilizing temperatures during preparation, cold brew is special in the coffee sector because hygiene and food safety aspects pose specific challenges for food industry. To avoid microbiological contamination and spoilage, cold brew should be as freshly prepared as possible and shelf-life should be minimized.

Disposable absorbent hygiene products have evolved for superior performance, enhancing the convenience of daily lives. Yet the use of disposable hygiene pads has brought safety concerns on chemical exposure, and significant efforts have been made to assess the potential risks associated with use of hygiene pads. This article intends to overview the safety assessment framework of diapers and feminine pads, which includes hazard identification, hazard characterization, exposure assessment, risk characterization, and postmarket risk management. Risk assessment of various constituents are reviewed for quantification methods and conservative estimation of exposure parameters. By reviewing the up-to-date considerations in risk assessment, we aim to provide insightful discussion on safety evaluation of current versions of disposable absorbent products. More clinical testing and postmarket surveillance are needed for continuous monitoring of potential health impacts of advanced products and constituents.

By using a two-stage physiologically based extraction test (PBET) and (W-PBET), the authors of this paper have estimated the bioaccessibility of metals (Pb and Fe) and their compounds in the GI tract of waterfowl and mammals. It has been shown that the metals (Pb and Fe) have low bioaccessibility; combined with the short time of shot exposition at the GI tract, this eliminates the risk of toxic effects in the case of shot ingestion by waterfowl. It has also been discovered that there is a significant difference in the bioaccessibility of metals and their compounds. A model was proposed and tested to predict the toxic effects of lead on biological objects depending on the threshold mass of consumption. This model takes into account data on the bioavailability of lead and regulatory values indicating dangerous concentrations of lead.

The COVID-19 pandemic has presented an unprecedented challenge to the healthcare system. Identifying the genomics and clinical biomarkers for effective patient stratification and management is critical to controlling the spread of the disease. Omics datasets provide a wealth of information that can aid in understanding the underlying molecular mechanisms of COVID-19 and identifying potential biomarkers for patient stratification. Artificial intelligence (AI) and machine learning (ML) algorithms have been increasingly used to analyze large-scale omics and clinical datasets for patient stratification. In this manuscript, we demonstrate the recent advances and predictive accuracies in AI and ML-based patient stratification modeling linking omics and clinical biomarker datasets, focusing on COVID-19 patients. Our ML model not only demonstrates that clinical features are enough an indicator of COVID-19 severity and survival but also infers what clinical features are more impactful, which makes our approach a useful guide for clinicians for prioritization of best-fit therapeutics for a given cohort of patients. Moreover, with weighted gene network analysis, we are able to provide insights into gene networks that have a significant association with COVID-19 severity and clinical features. Finally, we have demonstrated the importance of clinical biomarkers in identifying high-risk patients and predicting disease progression.

The United States is facing an alarming surge in cyberattacks, with data breaches rising by 72% since 2021, presenting grave national security risks. Notable incidents, including Chinese hackers attempting to access high-level government information and Iranian-linked cyber groups targeting U.S. water systems, highlight the fragility of critical infrastructure. These attacks pose dangers not only to national security but also to economic stability and public health, amplified by the rapid growth of interconnected technologies and global digitalization. In response to these escalating threats, the U.S. must take a multifaceted approach. Key strategies include strengthening cybersecurity education and workforce development, enforcing more rigorous regulatory frameworks, and enhancing preparedness through incident response and recovery planning. Additionally, increased international cooperation is essential to address state-sponsored cyber threats and foster a global framework for cybersecurity defense. As cyber threats continue to evolve, future efforts will rely on technological advancements such as artificial intelligence (AI) for real-time threat detection, the adoption of zero-trust security models, and the development of adaptive, resilient cybersecurity infrastructures. Collaboration between the public and private sectors, coupled with ongoing innovation and education, will be critical to maintaining national security and promoting economic growth in an increasingly interconnected digital landscape.

The aim of this paper is to study the main areas in which Artificial Intelligence (AI) will impact the field of project management that relates to cost, risk and scheduling. The research model was based on a previous study of the ten project management knowledge areas presented in the PMI’s PMBOK 6th edition where project schedule-, cost- and risk management knowledge areas were identified as being the ones most likely to be affected by the development of AI. A group of experts that participated in the study agreed that AI will affect the project management profession in the future. Different elements of the three knowledge areas were considered to be affected more by AI than others. The schedule baseline is the element believed to be affected the most out of the project schedule management elements. For project cost management, the estimation of resource cost is believed to be affected the most. In the case of project risk management, the application of AI will have the strongest impact on the probability and impact format.

Background: Appendicular skeletal muscle (or lean) mass (ALM) estimated using dual-energy X-ray absorptiometry (DXA) is considered to be a preferred method for sarcopenia studies. However, DXA is expensive, has limited portability, and requires radiation exposure. Bioelectrical impedance analysis (BIA) is inexpensive, easy to use, and portable; thus BIA might be useful in sarcopenia investigations. However, a large variety of models have been commercially supplied by different companies, and for most consumer products, the equations estimating ALM are not disclosed. It is therefore difficult to use these equations for research purposes. In particular, the BIA equation is often age-dependent, which leads to fundamental difficulty in examining age-related ALM loss. The aims of the current study were as follows: (1) to develop and validate an equation to estimate ALM using multi-frequency BIA (MF-BIA) based on theoretical models, and (2) to establish sarcopenia cutoff values using the equation for the Japanese population. Methods: We measured height (Ht), weight, and ALM obtained using DXA and a standing-posture 8-electrode MF-BIA (5, 50, 250 kHz) in 756 Japanese individuals aged 18 to 86-years-old (222 men and 301 women as developing equation group and 97 men and 136 women as a cross validation group). The traditional impedance index (Ht²/Z₅₀) and impedance ratio of high and low frequency (Z₂₅₀/Z₅) of hand to foot values were calculated. Multiple regression analyses were conducted with ALM as dependent variable in men and women separately. Results: We created the following equations: ALM = (0.6947 × (Ht²/Z₅₀)) + (−55.24 × (Z₂₅₀/Z₅)) + (−10,940 × (1/Z₅₀)) + 51.33 for men, and ALM = (0.6144 × (Ht²/Z₅₀)) + (−36.61 × (Z₂₅₀/Z₅)) + (−9332 × (1/Z₅₀)) + 37.91 for women. Additionally, we conducted measurements in 1624 men and 1368 women aged 18 to 40 years to establish sarcopenia cutoff values in the Japanese population. The mean values minus 2 standard deviations of the skeletal muscle mass index (ALM/Ht²) in these participants were 6.8 and 5.7 kg/m² in men and women, respectively. Conclusion: The current study established and validated a theoretical and age-independent equation using MF-BIA to estimate ALM and provided reasonable sarcopenia cutoff values.

Abstract: Interface risks are inherent in every construction project from start to finish. Identifying and managing these risks effectively in every project phase is crucial for actualising project objectives. This paper shows a comprehensive framework showing several relationships between project stakeholders and how the interface risks between them that influence project execution are identified and managed for the overall construction project success. Firstly, literature review on interfaces and interface risks were car-ried out and how organisations managed interface risks were discussed and secondly, the collection of quantitative data was conducted by means of structured online questionnaires. The sample consisted of 205 construction project professionals who were selected randomly. This group included individuals with various roles in the construction industry, The data was analysed using descriptive statistical methods, including factor analysis, reliability assessment, and calculations of frequencies and percentages. Finally, the results showed all the factors, work culture and organisational approaches that influence interface risk management and ways to identify and manage interface risks effectively.

Bonfire night is a worldwide phenomenon given to numerous annual celebrations characterised by bonfires and fireworks. Since Thailand has no national ambient air quality standards for metal particulates, it is important to investigate the impacts of particulate injections on elevations of air pollutants and ecological health impacts resulting from firework displays. In this investigation, Pb and Ba were considered potential firework tracers because their concentrations were significantly higher during the episode and lower than/comparable with minimum detection limits during other periods, indicating that their elevated concentrations were principally due to pyrotechnic displays. Pb/Ca, Pb/Al, Pb/Mg, and Pb/Cu can be used to pin-point emissions from firework displays. Air mass backward trajectories (72 h) from the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicated that areas east and north-east of the study site were the main sources for the air transportation. Although the combined risk associated with levels of Pb, Cr, Co, Ni, Zn, As, Cd, V, and Mn was far below the standards mentioned in international guidelines, the lifetime cancer risks associated with As and Cr levels exceeded US-EPA guidelines, and may expose inhabitants of surrounding areas of Bangkok to elevated cancer risk.

This article examines the integration of artificial intelligence (AI) and robotic process automation (RPA) in financial accounting and management, underscoring their role in driving the digital transformation of corporate finance. It discusses the shortcomings of traditional financial processes and highlights the potential of AI and RPA technologies to enhance efficiency, accuracy, and cost-effectiveness. The paper also explores the limitations of RPA, such as its challenges in processing unstructured data and handling complex decision-making scenarios. Looking forward, it considers the future trends in AI and RPA, emphasizing the benefits of cloud technology in scaling automated systems and addressing associated challenges.

Tegucigalpa, the capital city of Honduras, has the highest number of landslides recorded in the country. In a previous study, landslides were found to be mainly concentrated in areas with colluvium and residual soils. The present study focused on assessing the physical vulnerability of houses and the risk linked to landslides in these types of soils. As an input for this assessment, the study generated landslide risk vulnerability functions based on empirical data. The study's findings suggest that the estimated Annual Average Losses associated with landslides in this region is USD 7.26 million. Moreover, the study developed a novel approach for the spatial and temporal estimation of landslide hazard probability, which overcomes some of the limitations identified in previous landslide risk assessment studies.

Disordered eating is a serious health concern globally. The etiology is complex and multidimensional and differs somewhat for each specific eating disorder. Several risk factors have been identified which include psychological, genetic, biochemical, environmental, and sociocultural factors. Poor body image, low self-esteem, teasing, family dynamics, and exposure to media images have also been identified as risk factors. While it is enticing to consider a single behavioral risk factor, doing so fails to consider the documented environmental, social, psychological, biological, and cultural factors that contribute to the development of an eating disorder in a multidimensional and complex integration that is undoubtedly unique to everyone. Focusing only on any one factor without taking the complex etiology into account is remiss. For example, it has been suggested that the use of dietary supplements may lead to eating disorders, despite a lack of evidence to support this conjecture. Therefore, the purpose of this review is to examine the evidence-based risk factors for eating disorders and discuss why connecting dietary supplements to eating disorder etiology is not supported by the scientific literature and may interfere with treatment. Established, effective prevention and treatment approaches for eating disorders should be the focus of public health initiatives in this domain.

As a result of decades of austerity, the economies of the Eurozone are experiencing under-investment and crumbling infrastructures in an era of extremely severe emergencies as the cli-mate change and aggressive global competition. The private savings glut of the rich and the strict fiscal rules suggest a crowding-in approach in partnership with big finance in a new age of in-fra-structures. If governments mint public infrastructures into investable assets, they can gen-erate steady returns for investors and asset managers who look after pensions and insurances schemes and unlock trillions now devoted to welfare state. For the big finance to accept to be partner, however, governments must take the task of de-risking returns. Innovation technology and macro-financial literacy can synergically act to enhance this new de-risking role to address in a financially sustainable way the intense phenomena of Natural Hazards (NHs) that can severely compromise economic growth. This is precisely the aim of our Public-Private Partnership (PPP) among the Department of Economics, Management and Institutions of the University of Naples and a Knowledge Transfert Management, the Department of Engineering and the Aca-demic Spin-Off “STRAIN”, of the University of Campania. Our PPP has been contributing to the eval-uation and mitigation of NHs such as floods, landslides and earthquakes since 2012. The ex-tremely advanced results of this multi-stakeholder partnership ensure a better knowledge of NHs which, as evidenced in the paper, is the fundamental input for the desired Public-Private In-surance Programmes (PIPPs).

Excessive vibration of temporary grandstand owing to crowd has lateral rhythmic motions can cause human in panic, which attracted increasing attention in recent years. This paper focuses on experiments that a temporary grandstand occupied 20 participants is oscillated by a shaking table with a series of random waves and induced by crowd with rhythmic swaying motions at lateral direction, respectively. And then a series of vibration perception questionnaires about crowd reaction are obtained. Evaluation of annoying level derives in concept of degree of membership and annoying rate method is proposed, then the human health risk of vibration serviceability of temporary grandstand is assessed with acceleration vibration dose value(VDV). From these results it is clear that standing crowd is more tolerant to vibration than seated crowd. The measured vibrations generated by crowd activities on temporary grandstand can cause panic in crowd. New relationship between the annoyance rate and structural acceleration VDV at logarithmic coordinate is proposed. The findings of this study can be utilized to manage the vibration of temporary grandstand and assess the human health risk.

Frass generated during the production of black soldier fly larvae is taking the interest of scientists and horticultural producers because it is a material from the biotransformation of organic waste, it has several nutrients that can be used by plants, and its recent focus on its biostimulant capacity. The thermal-composting process is a stabilization that improves physical and chemical properties of treated wastes, allowing better performance in plants compared to its fresh state. In this research, thermocomposted frass was evaluated as a germination substrate for kale seeds (Brassica olerasea). To achieve this, it was evaluated the phytotoxicity in different concentrations on the seeds, and seedlings were grown in a germination substrates mixed with 20, 40, 60, 80 and 100% of frass. The treatment with 20% frass showed the highest values of seedling height, stem diameter, number of leaves, length, and width of first true leaf and length and width of cotyledons, reduced the content of phenols and tannins antioxidants but the content of flavonoids increased compared to the control and the rest of mixtures.

Human papillomavirus (HPV) infections, primarily transmitted through sexual contact, have been linked to various cancers, including cervical, penile, anal, oropharynx, breast, and prostate cancers. This study presents a unique case of concurrent high-risk HPV35, HPV45, and HPV59 infections in both prostate and bladder cancer tissues from a single patient, representing the first documented instance worldwide with identical HPV types detected in two adjacent organs of the same individual. Employing a multiplex-PCR approach, gel electrophoresis, and Sanger sequencing, we confirmed the presence of these high-risk HPV types. Additionally, Western blot analysis using an HPV E7 antibody demonstrated the active expression of HPV oncoproteins in both cancer types. This discovery underscores the potential for HPV intra-organ transmission and necessitates further exploration of alternative transmission routes. The implications of our results offer new insights into the complex dynamics of HPV transmission in cancer pathogenesis.

Since the 20th century, Japan has experienced a period of very rapid urbanization. Cities have experienced substantial densification and expansion, resulting in gradually elevated flood risk. Urban flooding has also occurred in most large cities in Japan, particularly in Tokyo. In response to this growing problem, much effort and resources have been spent on research and development aimed at understanding, simulating, and managing urban flood risk in Japan. The objective of this review is to summarize, discuss and share key outputs from some of the main research directions in this field, significant parts of which have been uniquely developed in Japan and only published in Japanese. After a general introduction to urban runoff modelling, in the next section, key historical works in Japan are summarized, followed by a description of the situation in Japan with respect to observations of precipitation and water level. Then, the storage function model approach is reviewed, including an extension to urban basins, as well as recent experiments with AI-based emulation in Japanese basins. Subsequently, we review the prospects of detailed hydrodynamic modelling involving high-resolution, vector-based Geographical Information System (GIS) data for the optimal description of the urban environment with applications in Tokyo. We conclude the paper with some future prospects related to urban flood risk modelling and assessment in Japan.

Objectives: The aim of our current study was to analyze whether the use of important measures of methodological quality and reporting of randomized clinical trials published in the field of cardiovascular disease research have changed over time. Further aim was to investigate whether there was an improvement over time in the ability of these trials to provide a good estimate of the true intervention effect. Methods We conducted two searches in the Cochrane Central Register of Controlled Trials (CENTAL) database to identify cardiovascular clinical research trials published in either 2012 or 2017. Randomized clinical trials (RCTs) trials in cardiovascular disease research with adult participants were eligible to be included. We randomly selected 250 RCTs for both publication year 2012 and 2017. Trial characteristics, data on measures of methodological quality and reporting were extracted and risk of bias for each trial was assessed. Results As compared to 2012 in 2017 there were significant improvements in the reporting of the presence of a data monitoring committee (42.0% in 2017 compared to 34.4% in 2012), and a positive tendency of registering cardiovascular disease research RCTs in clinical trial registries (83.6% in 2017 compared to 72.0% in 2012). On the other hand, we also observed that significantly fewer RCTs reported sample size calculation (60.4% in 2017 compared to 98.4% in 2012) in 2017 as compared to 2012. RCTs in 2017 were more likely to have low overall risk of bias ( RoB ) than in 2012 (29.2% in 2017compared to 21.2% in 2012). Conclusion: As compared to 2012 in 2017 there were significant improvement in some, but not all the important measures of methodological quality. Although more trials in the field of cardiovascular disease research had a lower overall RoB in 2017, the improvement over time was not consistently perceived in all RoB domains.

The Western Balkans region is persistently vulnerable to natural hazards, inadequate infrastructure, and limited institutional capacities, necessitating a collaborative approach to disaster risk management. This paper presents a comprehensive project led by the Scientific-Professional Society for Disaster Risk Management (NSD-URVs) in Belgrade, aiming to establish and strengthen a regional network of experts in disaster risk management. The project focuses on building expertise, facilitating knowledge exchange, promoting expert coordination, and enhancing cross-border collaboration. Key activities include developing a web platform, organising an international conference, and advocating for regional policies that integrate best practices and innovations in disaster risk management. The expected outcomes are the establishment of a cohesive network, enhanced expertise and coordination, and improved preparedness and responsiveness to disasters. By leveraging collective expertise and resources, this initiative aims to fortify the region's resilience against potential disasters. Addressing the identified gaps and implementing the proposed policy recommendations can significantly enhance the region's resilience to natural hazards. Future research should focus on the implementation and impact of these recommendations to ensure continuous improvement in disaster preparedness and response.

Background: Although lower extremity revascularization is commonly performed in hemodialysis patients, poor prognosis remains a major problem. Protein-energy wasting is reportedly associated with chronic inflammation and advanced atherosclerosis in hemodialysis patients. We investigated the association between the geriatric nutritional risk index (GNRI) as a surrogate marker of protein-energy wasting, C-reactive protein (CRP), and their joint roles in the prediction of amputation and/or mortality. Methods: We enrolled 800 patients successfully underwent lower extremity revascularization. Patients were divided into low, middle and high tertile (T1, T2 and T3) according to GNRI and CRP levels, respectively. Results: Amputation-free survival rates for 8 years were 47.0%, 56.9%, and 69.5% in T1, T2, and T3 of the GNRI, and 65.8%, 58.7%, and 33.2% for T1, T2, and T3 of CRP, respectively (p<0.0001 for both). Declined GNRI [adjusted hazard ratio (aHR) 1.78, 95% confidence interval (CI) 1.24-2.59, p=0.0016 for T1 vs. T3] and elevated CRP (aHR 1.86, 95%CI 1.30-2.70, p=0.0007 for T3 vs. T1) were independent predictors of amputation and/or mortality. In the combined setting of both variables, the risk was 3.77-fold higher (95% CI 1.97-7.69, p<0.0001) in the T1 of GNRI with T3 of CRP than in the T3 of GNRI with T1 of CRP. Conclusions: Patients with pre-procedural decreased GNRI and elevated CRP levels frequently experienced amputation and/or mortality, and a combination of both variables could more accurately stratify the risk.

In a context of exponential demographic growth, the imbalance between human resources and public health problems is impelling us to envision other solutions to the difficulties faced in the diagnosis, prevention and large-scale management of the most common diseases. Cardiovascular diseases represent the leading cause of morbidity and mortality worldwide. A large-scale screening program would make it possible to promptly identify patients with high cardiovascular risk in order to manage them adequately. Optical coherence tomography-angiography (OCT-A), as a window into the state of the cardiovascular system, is a rapid, reliable, and reproducible imaging examination that enables prompt identification of at-risk patients through the use of automated classification models. One challenge that limits the development of computer-aided diagnostic programs is the small number of open-source OCT-A acquisitions available. To facilitate the development of such models, we have assembled a set of images of the retinal microvascular system from 499 patients. It consists of 814 angiocubes as well as 2005 en face images. Angiocubes were captured with a swept-source OCT-A device of patients with varying overall cardiovascular risk. To the best of our knowledge, our dataset, RASTA, is the only publicly available dataset comprising such a variety of images from healthy and at-risk patients. This dataset will enable the development of generalizable models for screening of cardiovascular diseases from OCT-A retinal images.

Floods, recognized for their erratic behavior and devastating effects, are a significant threat as a natural disaster. In Brunei Darussalam, the impact of climate change is becoming increasingly evident through higher temperatures and an expected increase in annual rainfall (5.0mm per year from 2021 to 2050), highlighting the critical need for updated flood risk management techniques. In line with the climate resilience and adaptation objectives of WAWASAN 2035, this paper introduces an innovative approach—a cutting-edge flood risk management framework that utilizes the capabilities of big data analytics, sophisticated machine learning algorithms, and smart Internet of Things (IoT) sensors. Traditional methods, which rely on numerical and physical data modeling, often do not provide precise short-term flood forecasts. Our suggested framework uses machine learning to analyze real-time flood forecasting, sensor data and enhance warning systems, addressing the shortcomings of traditional approaches. The key advantage of this approach is its potential to drastically decrease flood-related damages, protect lives, and boost infrastructure resilience. This proposal is not only in aligns with Brunei's vision for a safe and climate-adaptable future but also marks a significant step forward in adopting innovative and sustainable flood risk management solutions amidst an evolving climate.

Background and Objectives: Previous studies revealed anti-angiogenic, antiproliferative and anti-inflammatory effects of Vitamin D on cancer cells. Although this body of evidence supported the correlation of high Vitamin D levels with reduced incidence rates for various malignancies, contradictory results were reported regarding non-melanoma skin cancer (NMSC). Aim of this overview was to summarize the available evidence from the existing pool of systematic reviews and meta-analyses, focusing on Vitamin D serum status, dietary intake, and Vitamin D receptor (VDR) polymorphisms in correlation to NMSC incidence. Materials and Methods: A literature search in electronic databases was conducted from inception to January 2023. Inclusion criteria were systematic reviews and meta-analyses published in peer-reviewed journals, evaluating Vitamin D serum levels, dietary and/or supplementary intake, or VDR gene polymorphisms, and reporting data on NMSC. Results: A total of 10 studies were included in the data analysis models. A positive association between Vitamin D serum levels and NMSC is highlighted. However, dietary/supplementation of Vitamin D doesn’t exhibit a likewise strong linkage to NMSC. Despite the contradictory findings, VDR polymorphisms may play a crucial role in the intricate NMSC pathogenesis. Conclusions: This umbrella review showed that high Vitamin D levels are associated with increased NMSC incidence, potentially due to its direct correlation with increased sun exposure. Further research on VDR polymorphisms is suggested to explore their true effect size on NMSC risk.

Draconian defensive measures have been implemented to combat the COVID-19 pandemic outbreak. These important measures constitute a vital current priority but do little to increase communal immunity and avoid future outbreaks. A longer-term exit strategy for a sustainable return to normalcy has yet to be identified. The development of vaccines or effective therapeutics could largely solve the problem, but their timely development cannot be guaranteed. In this setting, and under the expected societal isolation fatigue from extended social distancing, we here propose the idea that at some point after the outbreak’s peak, hospitals, in addition to providing care for infected people who need it, could also be involved in the development of a controlled exit strategy designed to avoid future outbreaks. We postulate that controlled voluntary deliberate infection in a hospital setting and under continuous and close medical observation may offer a safer alternative compared to random en-masse exposure. We discuss potential risks and benefits, highlighting the need for careful consideration of the associated critical ethical issues.

In this paper, we study a generalised CIR process with externally-exciting and self-exciting jumps, and focus on the distributional properties and applications of this process and its aggregated process. The first and second moments of this jump-diffusion process are used to calculate the insurance premium based on mean-variance principle. The Laplace transform of the aggregated process is derived, and this leads to an application for pricing default-free bonds which could capture the impacts of both exogenous and endogenous shocks. Illustrative numerical examples and comparisons with other models are also provided.

Older adults in low-and middle-income countries experience a disproportionate burden of non-communicable diseases (NCDs). Unintentional injuries are among the major NCDs, and falls are the second leading cause of these injuries and deaths worldwide, including in Thailand. We aimed to culturally adapt the CDC’s Stopping Elderly Accidents, Deaths, and Injuries (STEADI) for Thai older adults and explore the feasibility, appropriateness, and acceptability of using STEADI in primary care via trained community health workers (CHWs) and care managers (CMs). STEADI takes a coordinated care approach that consists of three steps: screening, assessing, and intervening. In Step a, CHWs screened fall risk in 20 community-dwelling older adults using three key questions and found that all of them had fall risk, then CHWs screened with a Stay Independent questionnaire (range 0-14) and found that 100% have high fall risk (total scores 9.7± 2.4). In Step b, CMs assessed balance, vision, footwear, postural hypotension, medications, and CHWs assessed home hazards. They found that 50% had poor balance, 70% took 4+ medications,75% fell on the walkway, and 70% had no bathroom modifications. In Step c, individual participants received fall prevention interventions to mitigate their specific fall risk factors. CHWs and CMs indicated high acceptability (19.20±.1.31 of 20 total), appropriateness (18.80± 1.79 of 20 total), and feasibility (18.60±1.67 of 20 total) of the Thai-STEADI intervention. Our study showed that the community-based multifactorial Thai-STEADI delivered by CHWs and CMs is feasible and acceptable to prevent falls in older adults with limited access to health care.

The core of risk aggregation in the Solvency II Standard Formula is the so-called square root formula. We argue that it should be seen as a means for the aggregation of different risks to an overall risk rather than being associated with variance-covariance based risk analysis. Considering the Solvency II Standard Formula from the viewpoint of linear geometry, we immediately find that it defines a norm and therefore provides a homogeneous and sub-additive tool for risk aggregation. Hence Euler's Principle for the reallocation of risk capital applies and yields explicit formulas for capital allocation in the framework given by the Solvency II Standard Formula. This gives rise to the definition of diversification functions, which we define as monotone, subadditive, and homogeneous functions on a convex cone. Diversification functions constitute a class of models for the study of the aggregation of risk, and diversification. The aggregation of risk measures using a diversification function preserves the respective properties of these risk measures. Examples of diversification functions are given by seminorms, which are monotone on the convex cone of non-negative vectors. Each L^p norm has this property, and any scalar product given by a non-negative positive semidefinite matrix does as well. In particular, the Standard Formula is a diversification function and hence a risk measure that preserves homogeneity, subadditivity, and convexity.

Lifetime cancer risk characterization of ambient PM-bound carcinogenic metals and polycyclic aromatic hydrocarbons (PAHs) were examined in the cities of Los Angeles (USA), Thessaloniki (Greece) and Milan (Italy), which share similar Mediterranean climates but are different in their urban emission sources and governing air quality regulations. The samples in Milan and Thessaloniki were mostly dominated by biomass burning activities whereas the particles collected in Los Angeles were primary impacted by traffic emissions. We analyzed the ambient PM2.5 mass concentration of Cadmium (Cd), Hexavalent Chromium (Cr(VI)), Nickel (Ni), Lead (Pb), as well as 13 PAH compounds in the PM samples, collected during both cold and warm periods at each location. The Pb exhibited the highest annual-average concentration in all 3 cities, followed by Ni, As, Cr(VI), Cd and PAHs, respectively. The cancer risk assessment based on outdoor pollutants was performed based on three different scenarios, with each scenario corresponding to a different level of infiltration of outdoor pollutants into the indoor environment. Thessaloniki exhibited rather high risk value associated with lifetime inhalation of As, Cr(VI) and PAHs. The highest cancer risk values were calculated in Milan where the lifetime risk of exposure to As, Cr(VI) and PAHs exceeded the US EPA standard across all scenarios by a considerable margin. The risk associated with Cr(VI) in Milan, which was the most significant among the investigated elements, ranged from (6.08±0.36)×10-6 to (9.82±0.58) ×10-6. In contrast, the estimated risks associated with metal and PAHs in Los Angeles were mostly comparable to the guideline value, even when the infiltration factor was assumed to be at peak. This observation highlights the impact of local air quality measures in improving the air quality and lowering the cancer risks in Los Angeles compared to the other two cities.

Life is supported by metabolism, a vital physiological activity. It guarantees enough energy available to power every cellular activity. The primary cellular substrate, glucose, is where the majority of the energy needed by the cell to support all other life activities and the growth of living creatures is derived. The quality of life is greatly impacted by any disease or flaw that alters the metabolism of glucose. There is no known cure for the metabolic illness known as diabetes. As diabetes is so varied, the only effective treatments would be based on precision medicine and a molecular strategy. This review covers a wide range of topics, including the ability to recognize the various forms of diabetes, the anthropogenic and genetic influence of the cause of diabetes, the severity of the various forms of diabetes, its potential existential risk, the disease burden, and clinical methods for diagnosing them. The most recent research goes on to recommend ways to ameliorate the disease, including diet-based management, biotherapies, and other individual lifestyle choices. Futuristic therapy using molecular biology approach was suggested. Recent research found a direct correlation between an individual's lifestyle and the rate of gene mutation in diabetes. There is an existential risk associated with the sickness as the rate of the spread of the disease among population globally is faster than the world's population growth rate. It is possible to think of diabetes as a silent pandemic.

Objectives: To develop and validate the Communities Geriatric Mild Cognitive Impairment Risk Calculator (CGMCI-Risk), aimed at aiding community healthcare workers in the early identification of individuals at high risk of Mild Cognitive Impairment (MCI); Methods: Based on nationally representative community survey data, backward stepwise regression was employed to screen the variables, and logistic regression was utilized to construct the CGMCI-Risk. Internal validation was conducted using bootstrap resampling, while external validation was performed using temporal validation. The area under the receiver operating characteristic curve (AUROC), calibration curve, and decision curve analysis (DCA) were employed to evaluate the CGMCI-Risk in terms of discrimination, calibration, and net benefit, respectively; Results: The CGMCI-Risk model included variables such as age, educational level, sex, exercise, garden work, TV watching or radio listening, Instrumental Activity of Daily Living (IADL), hearing, and masticatory function. The AUROC was 0.781 (95% CI = 0.766 to 0.796). Calibration curve showed strong agreement, and the DCA suggested substantial clinical utility. In external validation, the CGMCI-Risk model maintained similar performance with an AUROC of 0.782 (95% CI = 0.763 to 0.801); Conclusions: CGMCI-Risk is an effective tool for assessing cognitive function risk within the community. It uses readily predictor variables, allowing community healthcare workers to identify the risk of MCI in older adults over a three-year span.

Traditional path planning algorithms have drawbacks in unmanned vehicle path planning, such as low efficiency, unsuitability for dynamic environments, and high computational complexity. To address these issues, this paper proposes a dynamic path planning method for unmanned vehicles that combines the A* algorithm with an improved Dynamic Window Approach (DWA). Firstly, a collision risk function is incorporated into the DWA algorithm to evaluate scores based on the braking distance corresponding to the current vehicle speed and the distance to obstacles, determining whether timely braking or obstacle avoidance is feasible. The earlier the braking or obstacle avoidance, the higher the score, thereby enhancing the evaluation algorithm of the DWA. Secondly, the key points extracted by the A* algorithm are used as temporary target points for the DWA algorithm, reducing the eight search directions to five. Finally, the key points of the A* algorithm’s path are set as the temporary end points for the DWA algorithm, integrating the two algorithms to plan a smoother curved path that can avoid unknown and dynamic obstacles. Simulation data demonstrates that compared to traditional artificial potential field methods, RRT, and Dijkstra’s algorithm, the new fusion algorithm reduces time by 11.71 seconds, a decrease of 6.9%, and shortens path length by 3.093 meters, a reduction of 4.16%, while increasing average linear velocity by 2.9%. The proposed algorithm ensures smoother paths while also making paths more rational and efficient