The relationship between Herpes Simplex Virus (HSV) and oral risk habits is still uncertain. This study aimed to investigate the connection between oral risk habits and HSV status in a group of male patients from Sri Lanka who have oral fibroepithelial polyps. We collected 25 fibroepithelial polyps from nine oro-maxillofacial units in six provinces of Sri Lanka. Tissue samples were taken from frozen excisional biopsies to avoid contamination and tested for HSV- DNA using a real-time PCR assay. The results showed that HSV-DNA was present in 44% of the samples, with 66.67% being HSV-1 and 33.33% being HSV-2. However, there was no significant correlation between HSV status and oral risk habits such as betel quid chewing, smoking, and alcohol abuse. The study suggests the need for larger case-control studies to determine any significant associations between different types of Herpes Simplex Virus and oral risk habits.

Wild-grown edible mushrooms are important in world diet, which are also efficient metal accumulators. Yunnan, southwest China is the main producing region with typically high geochemical metals. Environmental factors, bioaccumulation, distribution and human health risk of metals were examined in paired soil and Tricholoma matsutake (n=54). T. matsutake grows on acidified soils (pH=3.95–6.56) and metals showed strong heterogeneity with Fe, Mn, Zn and Cu ranged at 16–201, 0.046–8.58 g kg–1 and 22.6–215, 3.7–155 mg kg–1. High soil Fe content led to its great accumulation in T. matsutake (0.24–18.8 g kg–1). However, though soil Mn content was great higher than Zn and Cu, their concentrations in T. matsutake were comparable (21.1–487 vs. 38.7–329 and 24.9–217 mg kg–1). This suggested that T. matsutake prefers to accumulate Zn and Cu than Mn, and supported by bioaccumulation factor (BAF=0.32–17.1 vs. 0.006–1.69). Fe was mainly stored in stipe, while Mn, Zn and Cu were in cap, with translocation factor (TF) was 0.58 vs. 1.28–1.94. Therefore, stipe Fe showed the highest health risk index (HRI) at 1.28–26.9, followed by cap Cu (1.01–2.33), while 98–100% of Mn and Zn were risk-free. The higher concentration and greater risk of Fe was attributed to the significant effect of soil Fe content (R=0.34) and soil pH (R=–0.57). This study suggested that Fe as an essential mineral may exert toxic effects via T. matsutake consumption from geochemical high background areas.

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.

The application of antimicrobials in aquaculture primarily aims to prevent and treat bacterial infections in fish. Inappropriate use of antimicrobials in fish farming may result in the emergence of zoonotic antibiotic-resistant bacteria and subsequent transmission of resistant strains to humans via food consumption. From recently, AMR emerged as a significant public health concern in the aquaculture ecosystem and fisheries. The aquatic environment serves as a potential reservoir for resistant bacteria, with aquaculture practices providing an ideal breeding ground for AMR due to the excessive use of antimicrobials to prevent and treat diseases. The mutual inter-connection of intensive fish farming systems with terrestrial environments, food processing industry and human population creates pathways for the transmission of resistant bacteria, exacerbating the problem further. One Health concept, which recognizes the interconnectedness of human, animal and environmental health, enables a holistic approach to address the challenges posed by AMR. By understanding the evolution of such approach, the future of aquaculture, being the important source of a global animal protein supply, can be safeguarded. Risk mitigation strategies for AMR should be based on One Health concept to contribute to sustainable aquaculture practices that protect human and animal health, ensure food safety and protection of environment.

Seawater contamination is a global challenge due to its hazardous effects on marine organisms and human health. Twenty-three surface seawater samples were collected from Al Lith intertidal area along the Saudi Red Sea coast to evaluate the ecological risks and document the potential sources of Cr, Cd, Fe, Zn, and Pb. Contamination factor (CF), contamination degree (Cd), water quality index (WQI), and heavy metal pollution index (HPI), as well as multivariate tools were applied. The averages of HMs (μg/L) had the following order: Zn (6.616) > Pb (0.284) > Cd and Cr (0.268) > Fe (0.197). Results of CF showed moderate contamination of seawater with Cd and low contamination for Cr, Fe, Zn, and Pb. However, 26.09% of the samples showed considerable contamination for Cd. Average Cd values revealed low contamination for HMs, while 17.39% of the samples showed moderate contamination. HPI average values indicated medium pollution for Al Lith seawater, meanwhile 13 samples reported high pollution. The higher HPI values were reported in samples characterized by higher concentration of HMs, particularly Cd and Zn. Correlation matrix and principal component analysis suggested anthropogenic sources for Pb and Zn, mostly from industrial and agricultural effluents, landfilling and domestic wastewaters, apart from their natural sources.

Nowadays, considering the growing tendency of companies towards e-commerce as well as green production, and dual-channel green supply chain management has become particularly important. This paper investigates pricing decisions within a dual-channel green supply chain framework while considering the capital constraints faced by risk-averse manufacturer. Simultaneously, the impact of the degree of risk aversion, consumer green preferences, and channel preferences on the optimal decision-making process of green supply chain members is analyzed. We address the issue of financial constraints faced by manufacturer through bank loans and trade credit financing and compare the two cases. Our findings illustrate that trade credit financing outperforms bank loan financing in the dual-channel green supply chain. Moreover, pricing decisions under different models are influenced by consumer preferences and risk aversion. Specifically, the greenness of the product, wholesale price, and sale price exhibit negative correlations with manufacturers' risk aversion but positive correlations with consumer preferences.

While the role of safe riding behavior as a safety contributor for cyclists has been increasingly studied in recent years, there have been few studies analysing cycling behavior in relation to crash-related outcomes in Baltic countries. Indeed, to the best of our knowledge, this is the first time this issue has been addressed in the case of Latvia. Aim: The objective of this study was to assess the relationships among self-repotted cyclists’ behavior, traffic safety literacy, and their cycling crash involvement rates. Method: A total of 299 cyclists aged M=32.8 from across Latvia (42% females) participated in an online survey, which comprised questions regarding respondents’ demographics, frequency of riding, and the number of crashes in the past five years. The Cycling Behavior Questionnaire (CBQ) and the Cyclist Risk Perception and Regulation Scale (RPRS) were applied to assess cyclists' behavior patterns and traffic safety literacy. Results: According to the findings, it can be inferred that cyclists frequently engage in riding errors and traffic violations while cycling. Those who exhibit more antisocial behavior patterns are also more likely to be involved in road crashes. Conversely, cyclists with greater positive behavior rates more often also tend to possess better knowledge of traffic rules and exhibit a heightened risk perception, indicating a greater awareness of road traffic safety. Conclusion: All in sum, this study underscores key age differences, with older individuals significantly less involved in riding crashes, exhibiting fewer driving errors and a higher level of risk perception, which serves as a crucial factor in road safety. At the practical level, these results stress the need to address both traffic safety literacy and protective cycling factors of cyclists, in a manner to improve overall road safety and promote active transport modes in Latvia.

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.

Due to various industrial developments and artificial inputs, there are emerging environmental contaminats(ECs) of serious concern in a wide range of environmental media. With recent advancements in scientific knowledge and industrial technology, the definition of emerging environmental contaminats has expanded. Among them, emerging contaminants are typically present in trace amounts and pose serious ecological risks and potential hazards to human health, animals and plants, with cumulative effects on organisms. However, Traditional treatment techniques have proven ineffective in eliminating and preventing subsequent environmental problems from new pollutants such as microplastics, antibiotics and fluorocarbons. Consequently, extensive research has been conducted to address these issues. Effective removal methods prioritize not only removal efficiency, but also environmental friendliness and regenerative capacity. The purpose of this paper is to summarize the sources, forms of presence, environmental and human health hazards, and removal technologies of ECs, and to provide various examples of different sources.

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.

This review provides a comprehensive and updated information on chalcones, presenting their sources, methods of identification and properties putting emphasis on applications in agricultural industry. Vast exploitation of synthetic pesticides led to the weed and pest resistance issue, causing economic loss but more importantly health risk due to pesticide overuse. Because one of the aim of the European Green Deal 2030 is the Farm to Fork strategy which targets on reducing by 50% the use of chemical pesticides by 2030, and push towards natural pesticides which are more environmentally friendly and restore natural resources, chalcones and their derivatives seem to fit perfectly. They have herbicidal, fungicidal, bactericidal and antiviral properties. Moreover, chalcones are naturally occurring substances, known for their favorable health effect for years, working on many areas. This review is complementary to the previous ones describing chalcones use in agriculture, updates them but additionally shows methods of detection.

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.

Dry periods and drought are inherent natural occurrences. However, due to the increasing pressures of global warming and climate change, these events become more frequent and severe on a global scale. These phenomena can be traced with various indicators and related indices proposed by various scholars. In general, drought risk assessment is done by modelling these indicators and determining the drought occurrence probabilities. The proposed adaptation introduces the "Kaplan-Meier Estimator," a non-parametric statistic traditionally used in medical contexts to estimate survival functions from lifetime data. The study aims to repurpose this methodology to assess drought risk by treating past droughts as "events" and evaluating the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) and map these results for a better understanding of the drought risks within larger spatial scales such as a river basin. The adapted method provides the probability of non-occurrence, with inverted results indicating the likelihood of drought occurrence. As a case study, the method is applied to SPI and SPEI values at different time steps (3, 6, and 12 months) across 27 meteorological stations in the Gediz River Basin, located in Western Turkey—a region anticipated to be profoundly affected by global climate change. The results are represented as the generated drought risk maps and curves, which indicate that (i) drought risks increase as the considered period extends, (ii) drought risks decrease as the utilized indicator timescales increase, (iii) locally plotted drought curves indicate higher drought risks as their initial slope get steeper. The method used enables the generation of historical evidence based spatially distributed drought risk maps which expose more vulnerable areas within the river basin.

Hyperlipidemia is an identified risk factor for metabolic syndrome, obesity and cardiovascular complications characterized by elevated levels of lipids in blood. The present study aimed to inhibit HMG-CoA reductase with 15-oxoursolic acid through in-vivo and in-silico assessments. HFD-induced hyperlipidemia in rats was developed with a marked increase in total cholesterol (58.34 ± 0.21 mg/dl), triglycerides (45.45 ± 0.39 mg/dl), LDL-c (66.12 ± 0.10 mg/dl), VLDL-c (19.34 ± 0.16 mg/dl), and a decrease in HDL-c (10.34 ± 0.18 mg/dl). The oral administration of 15-oxoursolic acid at a concentration of 30 mg/Kg b.w significantly reduced the serum concentration of total cholesterol (42.65 ± 0.54 mg/dl), triglycerides (32.33 ± 0.16 mg/dl), LDL-c (50.34 ± 0.15 mg/dl) and VLDL-c (13.15 ± 0.45 mg/dl) respectively and an increased in the serum HDL-c (18.56 ± 0.34 mg/dl). 15-oxo ursolic acid also caused a decrease in the coronary risk index and atherogenic risk index. In-silico studies of 15-oxoursolic acid with HMG-CoA reductase showed significant interaction capability with binding energy (-9.26805 Kcal/mol). It is concluded that 15-oxoursolic acid could significantly reduce the total cholesterol, triglycerides and LDL levels in HFD-induced hyperlipidemia rats which might lead to new medication with significant hypolipidemic potential.

Background. Implementing mammogram screening means that clinicians are seeing many breast cancers that will never develop metastases. The purpose of this study was to identify subgroups of breast cancer patients who did not present events related to long-term breast cancer mortality, taking into account diagnosis at breast screening, absence of palpability and axillary involvement, and genomic analysis with PAM50. Patients and Methods. To identify them, a retrospective observational study was carried out selecting patients without palpable tumour, without axillary involvement, and a genomic analysis was performed with PAM50. Results. The probability of distant metastasis-free interval (DMFI) of 337 patients was 0.92 (95% CI, 0.90-0.93) at 20 years and 0.96 (95% CI, 0.92-1.00) in 95 patients (28%) with available PAM50 tests. In 22 (23.15%) luminal A tumours and in 9 (9.47%) luminal B tumours smaller than 1 cm and in HER2 and basal type tumours there were no metastatic events (20-year DMFI of 1.00). Conclusion. Patients with nonpalpable breast cancer found at screening with negative nodes are at very low risk. It is possible to identify subgroups without metastatic events by determining the intrinsic subtype and tumour size less than 1 cm. De-escalation of treatment should be considered.

Background: The association of echocardiographic findings and subsequent risk of left-sided native valve endocarditis (LS-NVE) is undefined. The aim of this study was to determine if transthoracic echocardiographic (TTE) measurements are associated with the subsequent development of LS-NVE in patients without cardiac predisposing conditions. Methods: Institutional databases were evaluated for adults diagnosed with LS-NVE from 2008 to 2020. Patients with prosthetic valves, cardiovascular implantable electronic devices, intracardiac devices, injection drug use, and predisposing cardiac conditions were excluded. Only patients who had a TTE performed 6 months to 3 years before the development of LS-NVE were included as cases. Controls were patients within the same Mayo location with a TTE report and were matched in a 1:3 ratio according to age, gender, Charlson Comorbidity Index, and echocardiography date. Results: There were 148 cases and 431 matched controls. As compared to controls, IE cases had a higher prevalence of diabetes mellitus (46.6% vs. 30.4%) and chronic kidney disease (46.6% vs. 28.1%) (p<0.001). Left ventricular outflow tract velocity (p=0.017), left ventricular ejection fraction (p=0.018), and E: e’ ratio (p=0.050) were associated with LS-NVE. Conclusions: Echocardiographic measurements were associated with subsequent LS-NVE development in this pilot study. A larger cohort of LS-NVE patients, however, is needed to validate these findings.

In modern automobiles, Infotainment High-Performance Computing (HPC) systems play a vital role in enhancing the capabilities of drivers and passengers by providing advanced features consisting of music, navigation, communication, entertainment, etc. However, as the use of information technology in vehicles increases, it results in cybersecurity threats such as data breaches and the loss of sensitive information. To improve the security of the infotainment system in automotive vehicles, the research conducted threat modeling at the component level using Microsoft’s STRIDE tool and performed risk assessment by using SAHARA (Safety-Aware Hazard Analysis and Risk Assessment) and DREAD methodologies to evaluate associated risks. It provides a systematic representation of threats, associated risks, and generic mitigation strategies to counter cybersecurity attacks. Through the threat modeling process, 34 potential security threats were identified. The study also provided a comparative analysis to calculate the risk values of the threats to prioritize for treatment. These identified threats and associated risks need to be considered to avoid potential cyberattacks, before deploying the infotainment HPC system in real-world automotive vehicles.

Introduction: The predictive value of the risk stratification scales in elderly patients with IPAH might differ from that in younger. It is unknown whether young and older IPAH patients have the same survival dependence on PAH-specific therapy numbers. The aim of the study was to evaluate the prognostic relevance of risk stratification scales and PAH medication numbers in elderly in comparison with young IPAH patients. Material and methods: 119 patients from a prospective single-center PAH registry were divided on to group I <60 years old (n=89) and group II ≥60 years old (n=30). ESC/ERS, REVEAL, and REVEAL 2.0 risk stratification scores were assessed at baseline, as well as H2FpEF- score and survival at follow-up. Results: During a mean follow-up period of 2.9 years (1.63; 6.0) 42 (35.3%) patients died; at 1, 2, 3, 5, 7, and 10 years survival was 95%, 88.6%, 78.5%, 61.7%, 48.5% and 33.7%, respectively. No survival difference was observed between the two groups despite the use of monotherapy in elderly patients. The best predictive value exhibited the REVEAL in group II (IPAH patients ≥60 years) - AUC 0.73 (0.56-0.91), p = 0.03; and in patients with LHD comorbidities in the entire cohort - AUC 0.73 (0.59-0.87), p<0.009. Factors independently associated with death in the entire cohort were CKD (p=0.01, HR 0.2), the right-to-left ventricle dimension ratio (p=0.0047, HR 5.97), and NT-proBNP >1400 pg/ml (p=0.008, HR 3.18). Conclusion: Risk stratification in elderly IPAH patients requires a fundamentally different approach than that of younger patients, taking into account the initial limitations in physical performance and comorbidities that interfere with current assessment scores. The REVEAL score reliably stratifies patients at any age and LHD comorbidities. The initial monotherapy seems to be reasonable in patients over 60 years. Selection tools for initial combination PAH therapy in older IPAH patients with comorbidities need to be validated in prospective observational studies.

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.

Telemedicine has been increasingly considered an effective strategy to support patients with several diagnosis and therapies, avoiding the on-site visit and drastically reducing the risks to share infections. In the recent years, a number of different technologies have been developed and applied to clinical studies, with the aim to investigate new ways for increase the early diagnoses and monitor the clinical evolution of the most predictable diseases directly from the patients’ home. Telemedicine refers to all those technological interfaces used to remotely perform clinical procedures. Telemedicine applications could be useful in several medical fields, such as preventive medicine, home patient care, education for healthcare professionals and patients, research, public health, and health management. On the other hand, the synergy of these different technologies has a significant impact on the clinical risks analysis, particularly useful in frail patients. Although Telemedicine shows to have important advantages, undoubtedly important issues still remain. The present work aims to shed light on the main advantages and disadvantages related to of each application’s features, which may serve as a useful tool for researchers.

Background: The increased vascular risk associated to Varicella- Zoster Virus (VZV) reactivation is extensively established in the general population. This retrospective cohort study investigates whether this observation holds true for People Living With HIV (PLWH), a group already con-fronting heightened cardiovascular risk. Methods: Among PLWH who initiated antiretroviral therapy (ART) at our center and have been under our care for > 24 months since January 1st, 2005, individuals with a history of Herpes Zoster (HZ) were identified and compared their features with those of PLWH with no history of HZ. The prevalence of ischemic events (Deep Venous Thrombosis, Stroke, Acute Myocardial Infarction) was calculated and compared using Chi Square. Odds Ratios (O.R.) with 95% Confidence Intervals (C.I.) for ischemic events following HZ were evaluated through univariate and multivariate logistic regression. Results: Overall, 45/581 PLWH reported HZ. Ischemic events followed HZ significantly more often than the other group (13% vs. 5%, p=0.01). Both positive serology for VZV and HZ correlated with increased ischemic risk (O.R. 4.01, 95% C.I. 1.38-11.6, p=0.01 and O.R. 3.14, 95% C.I. 1.12-7.68, p=0.02, respectively), though pre-existing heart disease demonstrated stronger predictive value in multivariate analysis(O.R. 8.68, 95% C.I. 2.49-29.50, p=0.001). Conclusions: VZV potentially exacerbates vascular risk for PLWH, particularly in the presence of other predisposing factors. Further research is needed to confirm our data.

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.

For a long time, the transition to adulthood was seen as a troubled period where good development was synonymous with the absence of problems. Positive Youth Development (PYD) emerged as a holistic and strength-based perspective that focuses on the fact that young people may have the internal and external resources for healthy and successful development through five dimensions (5C’s) that empower them: Perceived Competence, Confidence, Character, Connection, and Caring. The aim of this study was to examine the relationship between the global PYD factor (and the 5C’s) and risk behaviors, in addition to analyzing gender differences. This study showed the results of a cross-sectional study of 1044 emerging adults from 11 Spanish universities in 2021. Data collection was performed by applying an online self-report measure. The results showed that the Character was protective against substance abuse, mainly in women, while the connection was related to the participation of betting money and online betting in men. Caring was protective against money bets in the men’s sample. However, controversial results were found regarding Perceived competence, which had a positive association with substance abuse, money bets, and drunk driving. It seems that high levels of Perceived competence, rather than objective competence, were associated with engagement in various risk behaviors, especially in the absence of other C´s. These results are discussed regarding the promotion of PYD to improve successful development and may suggest the need to foster healthy lifestyles and prevent risky behaviors in youth through the 5C's promotion programs within the university context.

The campuses of Nigerian universities especially the old ones, like the University of Ibadan, comprise old trees which can pose a threat to pedestrians, structures, and roads within the school environments. However, there is no adequate information on these avenue trees thereby impeding their sustainable management. Therefore, this study provides the basic information needed by developing a geodatabase for the avenue trees along Benue, Emotan and Oduduwa roads within the University of Ibadan, Ibadan, Nigeria. The coordinates of all the avenue trees, and some within the selected roads were obtained. Tree growth data collected include; diameter at the breast height (dbh), diameter at the base, middle and at the top, crown height, crown diameter, and total height of all the avenue trees. Tree visual evaluation for diseases (TVED) was carried out for root decay, and termite attack on any part of the tree (stem, leaves and visible part of the root). Risk rate was assessed as low, medium and high, depending on the potential target (human, vehicles, structures). The risk rate depended on the incidence of leaning towards a building or road, cracked branches, root attack by termites, basal decay or branch decay. The growth data were used to compute the tree volume while the avenue trees were georeferenced. The physical health status of the avenue trees was determined using TVED data. The spatial distribution of the avenue trees was developed in GIS while all the analysed data were pulled together to develop a geodatabase for the avenue tress using design templates of BOOTSTRAP, comprising of Hypertext Markup Language, Cascade Style Sheets, JavaScripts and Hypertext Preprocessor. A total of 121 individual avenue trees belonging to 14 species were identified in the study area. The analysis of the geospatial distribution shows that Emotan Road had a lesser spatial distribution of avenue trees compared to Benue and Oduduwa roads. Furthermore, the health risk assessment of the trees in the study area indicated that 17.35% of the individual avenue trees had defects. The database created is user-friendly, suitable and has the ability for easy data storage and quick information retrieval on the avenue trees to enhance their maintenance and risk management. This can be accessed using the link http://159.203.29.155/rebs/rebs.php.

The study aimed to identify football players at high risk (HR) for anterior cruciate ligament (ACL) injury via a four-test battery and assess possible factors affecting classification. Ninety-one professional and semi-professional athletes participated in a field-based preseason screening. Aknowledged inter-limb asymmetry limits for quadriceps and hamstrings isometric strength, and Single Leg Triple Hop for distance, in addition to the Landing Error Scoring System (LESS) comprised the test-battery. Additional assessment of hip adductors and core stability completed the global functional profile of the players. Sixty-one players were identified as HR and 30 as low-risk (LR) for ACL injury. Test-battery classified adequately 78,0% of them (Chi-square= 27,485 p=,000), identifying only 4 misclassified cases in the LR group, this low number being important for avoiding improper treatment of injury-prone athletes. All partcipants were considered healthy, and history of a previously rehabilitated injury did not interfere with the results. LESS seems to be the optimal criterion for classification and also the best predictor of both the initial grouping and the secondary one with the wrong vs correct classification cases. The proposed test-battery provides a promising option for field-based preseason ACL-risk assessment of football players and needs to be studied prospectively.

The aim of this study was to determine the most common maternal and neonatal complications related to cesarean section at Sultan Qaboos University Hospital (SQUH) and to compare the outcomes between emergency and elective cesarean sections. A retrospective cohort study was conducted in the department of Obstetrics and Gynecology at SQUH from 1st January 2016 to 31st December 2016. This comparative study involved 300 women who underwent cesarean section, 150 in elective cesarean section group and 150 in emergency cesarean section group. Data was collected from the delivery ward maternity registry and Electronic Patient Records. SPSS software version 23 was used to analyze the data.The mean maternal age was 29.66 (± 4.96) and 33.22 (± 4.63) years in the elective and emergency cesarean section groups respectively (p=001). The main risk factor for both the groups was maternal diabetes and the most common indication for both was previous cesarean section. Hypotension related anesthetic complication was noted more in elective cesarean section (15.3%) than in emergency cesarean section group (4.0%) with p value=0.002. The most common major intraoperative complication in both groups was postpartum hemorrhage, 66.9% women in emergency group and 63.0% women in elective group. Post-partum fever was seen in 12.0% of women in emergency group as compared to 4% in elective group (p=0.019). Anemia was observed in 79.2% and 65.3% in emergency and elective groups respectively (p=0.011). Respiratory distress syndrome and transient tachypnea of the newborn were the main neonatal complications in both groups. There was no significant difference between emergency and elective cesarean section related maternal and neonatal complications except for transient intraoperative hypotension, maternal postoperative febrile morbidity and anemia. Future prospective studies including larger sample size and multiple centers is recommended.

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.

Background: Falls risk assessment tools are used in hospital inpatient settings to identify pa-tients at increased risk of falls (which may be related to muscle loss/sarcopenia) to guide and target interventions for falls prevention. In 2022, Western Health, Melbourne, Australia, intro-duced a new falls risk assessment tool, the Western Health St. Thomas’ Risk Assessment Tool (WH-STRATIFY), a modified version of The Northern Hospital’s risk tool (TNH-STRATIFY), which replaced the Peninsula Health Risk Screening Tool (PH-FRAT). Aims: To determine the predictive accuracy of three falls risk assessment tools (PH-FRAT, TNH-STRATIFY and WH-STRATIFY) on admission to Geriatric Evaluation Management (GEM) units. Method: A retrospective observational study was conducted on four GEM units. Data was col-lected on 54 consecutive patients who fell during admission and 62 randomly sampled patients who did not fall between December 2020 and June 2021. Participants were scored against three falls risk assessment tools. The event rate Youden (Youden IndexER) indices were calculated and compared using default and optimal cut points to determine which tool was most accurate for predicting falls. Results: Using default cut points to compare falls assessment tools, TNH-STRATIFY had the highest predictive accuracy (Youden IndexER = 0.20, 95% confidence interval CI = 0.07, 0.34). The PH-FRAT (Youden IndexER = 0.01 and 95% CI = -0.04, 0.05) and WH-STRATIFY (Youden IndexER = 0.00 and 95% CI = -0.04, 0.03) were statistically equivalent and not predictive of falls compared to TNH-STRATIFY. When calculated optimal cut points were applied, predictive accuracy im-proved for PH-FRAT (Cut point 17, Youden IndexER = 0.14 and 95% CI = 0.01, 0.29) and WH-STRATIFY (Cut point 7, Youden IndexER = 0.18 and 95% CI = 0.00, 0.35). Overall, all tools had low predictive accuracy for falls. Conclusion: TNH-STRATIFY had the highest predictive accuracy for falls. The predictive accu-racy of WH-STRATIFY improved and was significant when the calculated optimal cut point was applied. The optimal cut points of falls risk assessment tools should be determined and validated in different clinical settings to optimise local predictive accuracy, enabling targeted falls risk mitigation strategies and resource allocation.

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.

Waterlogging induced by rain in urban areas has a potential risk impact on property and safety. This paper focuses on the impact of rain on waterlogging and evaluates the waterlogging risk in the central city of Shanghai. A simplified waterlogging depth model is developed in different areas with different drainage capacity and rainfall in consumption of simplifying the effect of complex terrain characteristics and hydrological situation. Based on urban waterlogging depth and its classification collection, a Rain-induced Urban Waterlogging Risk Model(RUWRM) is further established to evaluate waterlogging risk in the central city. The results show that waterlogging depth is closely linked with rainfall and drainage, with a linear relationship between them. More rainfall leads to higher waterlogging risk, especially in the central city with imperfect drainage facilities. Rain-induced urban waterlogging risk model can rapidly gives the waterlogging rank caused by rainfall with a clear classification collection. The results of waterlogging risk prediction indicate that it is confident to get the urban waterlogging risk rank well and truly in advance with more accurate rainfall prediction. This general study is a contribution that allows the public, policy makers and relevant departments of urban operation to assess the appropriate management to reduce traffic intensity and personal safety or strategy to lead to less waterlogging risk.

Close to half (45.4%) of 2.3 million breast cancers (BC) diagnosed in 2020 were from Asia. While the burden of breast cancer has been examined on the level of broad geographic regions, literature on more in-depth coverage of the individual countries and subregions of the Asian continent is lacking. This review examines the breast cancer burden in 47 Asian countries. Breast cancer screening guidelines and risk-based screening initiatives are discussed.

This paper presents the behavior of decision makers, the possible choices and the strategies 1 resulting from the uncertainties related to the integration of renewable energies. Its uncertainties 2 are the risks associated with the volatility of renewable sources, the dynamics of energy production 3 as well as the planning and operation of the electricity grid. The goal is to model the risk-averse 4 decision-maker’s behavior and the choice of integrating renewable energies into the electrical system. 5 Following a bibliographic approach, we expose a methodology to model the decision-maker’s 6 behavior(risk aversion and predilection for risk) to risk taking. The risk-averse decision maker may 7 adopt nonlinear utility functions. Risk aversion is a behavior that reflects the desire to avoid risk 8 decisions and thus reduces the risk of adverse consequences. A decision support tool is provided to 9 the decision-maker to choose a best-fit strategy based on his preferences. The rational and risk-averse 10 decision-maker would seek to maximize a concave utility function instead of seeking to minimize its 11 cost. Taste or aversion to risk can be modeled by a thematic function of utility.

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).

In this study, I extend the Fama and French five-factor asset pricing model with a sixth factor, namely, carbon risk, to investigate its impact on equity returns. To measure carbon risk, a new factor ‘pollutant minus green,’ is developed using the difference between the weighted average returns of pollutant and green firms across 51 developed and emerging countries across four categories—North America, Europe, Emerging Markets, and the Asia Pacific. The results reveal that North America, Europe, and Asia Pacific markets have a carbon risk premium that gets eliminated in small-cap firms. The carbon risk factor is further tested in left-hand side (LHS) test asset portfolios and found to be more pronounced with size-effect anomaly; specifically, small stock firms report greater declining average returns because of more exposure than the mega-cap stocks to carbon dioxide emissions. Furthermore, size-effect anomaly prevails with profitability and investment factors across firms. Therefore, high profitability, as well as high investment small firms, show a greater decline than the big stock firms in average returns when their carbon dioxide emissions increase. The asset pricing model evaluation is carried out through the Gibbons, Ross, and Shanken test. The six-factor model directed at capturing carbon risk patterns in average equity returns performs better than the three-factor and five-factor models of Fama and French (1993 and 2015) in the majority of categories under 3x3 sorting and compete with both Fama and French model under 2x4x4 sorted LHS portfolios. The finding of this study offers various useful applications for investors, policymakers, brokers, corporations, governmental pollution abatement institutions, and other stakeholders who wish to obtain carbon risk premium.

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.

The association between obesity and the risk of gliomas remains unclear. We sought to evaluate the potential association between general and abdominal obesity and the risk of gliomas based on a nationwide population-based cohort study of Koreans. Using data from the Korean National Health Insurance System cohort, 6,833,744 people older than 20 years who underwent regular national health examination in both 2009 and 2011 were followed until the end of 2017. We documented 4,771 glioma cases based on an ICD-10 code of C71 during the median follow-up period of 7.30 years. Individuals with a body mass index (BMI) ≥ 25.0 kg/m2 were at significantly higher risk of gliomas than those with a BMI < 25.0 kg/m2 (HR 1.08 CI 1.02-1.15). Individuals with a waist circumference (WC) ≥ 90 cm (males)/85 cm (females) also had a significantly higher risk of gliomas than those with a WC < 90 cm (males)/85 cm (females) (HR 1.16 CI 1.09-1.24). In the group with a BMI ≥ 25.0 kg/m2, individuals with abdominal obesity were at significantly higher risk of gliomas (HR 1.18 CI 1.09-1.27) than those without abdominal obesity. The role of abdominal obesity in this association was stronger in women than in men. To our knowledge, this is the first demonstration that obese people may be at higher risk of gliomas, especially centrally obese people from an Asian population with a BMI ≥ 25.0 kg/m2. Loss of visceral fat in people with abdominal obesity may reduce their risk of gliomas.

Cereals and their derivatives are the basis of human nutrition. However, cereals also contribute to the dietary exposure to toxic metals that may pose a risk. Strengthening food security and nutrition information is a high priority challenge for the Cape Verde Government. The toxic metals content (Cr, Ni, Sr, Al, Cd, Pb) has been determined in 126 samples of cereals and derivatives (rice, corn gofio, corn flour, wheat flour, corn, wheat) consumed in Cape Verde. Wheat flour samples stand out for registering the highest Sr (1.60 mg/kg), Ni (0.25 mg/kg) and Cr (0.13 mg/kg). The results show relevant Al levels (1.17 – 13.4 mg/kg) with its highest levels in corn gofio. The mean Pb average content in the cereals is 0.03 – 0.08 mg/kg with the highest level observed in corn gofio. The Al and Pb levels are lower in cereals without husks. A consumption of 100 g/day of corn gofio provide an intake of 1.34 mg Al/day (13.7% of the tolerable weekly intake established at 1 mg/kg bw/week) and 8 µg Pb/day (20% of the BMDL set at 0.63 µg/kg bw/day for nephrotoxic effects). The minimization of the dietary exposure of the Cape Verdean population to toxic metals is through the importation of higher quality cereals.

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.

Even though the rules for free movement of machinery within the European Union market have existed for more than 30 years, accidents related to their activities have constantly been achieving significant value. When designing the machine, a designer must stem from risk assessment, whereas all stages of its life cycle and ways of its use must be taken into consideration. In industrial operations, there is old machinery, which, although fulfilling its function reliably, the safety level is not in accordance with the developing requirements for their safe operation. The proposed methodology of assessment of the machinery safety condition comes out from the presupposition of the right application of steps of risk assessment and their reduction mainly by means of implementation of both effective and efficient preventive measures. The aim of the research applied in 3 operations, was to verify the method of machinery safety management. The created methodology based on 19 requirements for safety evaluates the level of the actual measures by means of the so-called criterion of current status and total efficiency of measures. Its output is the assessment of the efficiency level of implemented safety of each machine as well as of the whole operation.

Malaria is a disease spread by female mosquitos of the Anopheles genus. It is acutely prevalent in Sub-Saharan Africa, where 90% of malaria deaths occur annually. One Sub-Saharan African country historically impacted by malaria is Ethiopia. In the past twenty years, malaria prevalence has decreased throughout Sub-Saharan Africa; yet, anthropogenic environmental changes are changing the landscape of malaria. Scholarly literature has cited a positive relationship between hydroelectric dams and malaria in Sub-Saharan Africa. Ethiopia is currently expanding their hydroelectric infrastructure. The Gilgel Gibe III Dam is located on the Omo River in Southwestern Ethiopia. It began generating electricity in 2015 and its reservoir has a capacity of 14,700 million m3 of water. This research utilized Geographic Information Systems and Remote Sensing to identify populations at an increased risk of malaria due to Gilgel Gibe III Dam. Two different techniques were employed: the proximity approach and the remote sensing approach. The proximity approach was based on distance from the reservoir. It identified all populations living within three kilometers of the reservoir as being at an increased risk. The remote sensing approach evaluated the slope, elevation, water content, and land surface temperature of the study area to create a mosquito breeding habitat risk map. Then, populations living within three kilometers of the two main High-Risk areas were identified. This study suggests that mosquito breeding habitat risk is not equally distributed throughout the Gilgel Gibe III Reservoir. This causes certain populations to be at a heightened risk of malaria.

Coronavirus disease (COVID-19) has caused mankind serious confusion, economic havoc and psychological distress. This study evaluated the level of knowledge, attitude and perception about COVID-19 pandemic, infection control and impact among veterinarians in Nigeria. A cross-sectional online survey was used to collect data from consenting respondents during implementation of lockdown in the country (April 23 - May 31, 2020). Purposive and chain referral sampling techniques were used to recruit 368 respondents from various sectors of the profession. The proportion of respondents surveyed 197/368 (53.5 %) were from the public sector, 35.3 % from private sector, 1.1 % were unemployed and 0.8 % retired. Majority of the respondents were males (72.8 %), within 30 – 39 years (39.7 %) and had 1 – 10 years work experience. Respondents displayed good level of knowledge about COVID-19 (72.4 % ± 9.9 %, range 44.1-91.2 %), with information mostly derived from TV/Radio (81.5%) and social media (81.0 %). The overall attitude level was poor and various determinants for good attitude among respondents were if they were above 60 years (p = 0.013), possessed postgraduate qualification ( p = 0.031), worked over 30 years post DVM (p = 0.001), had household members between 5 and 10 (p = 0.012), and were resident in states on total lockdown (p = 0.024). There was no correlation between the knowledge level score and respondents’ attitude towards the pandemic (p = 0.12). With increasing rate of COVID-19 transmission, research data are needed to develop evidence-driven strategies, policies and effective risk mitigations to reduce the pandemic’s adverse impacts.

Objectives Independent validation of risk scores after hip fracture is uncommon, particularly for evaluation of outcomes other than death. We aimed to assess the Nottingham Hip Fracture Score (NHFS) for prediction of mortality, physical function, length of stay and postoperative complications. Design Analysis of routinely collected prospective data partly collected by follow-up interviews. Setting and Participants Consecutive hip fracture patients were identified from the Northumbria hip fracture database between 2014-2018. Patients were excluded if they were not surgically managed or if scores for predictive variables were missing. Methods C-statistics were calculated to test the discriminant ability of the NHFS, Abbreviated Mental Test Score (AMTS), and ASA grade for in-hospital, 30- and 120-day mortality, functional independence at discharge, 30-days and 120-days, length of stay, and postoperative complications. Results We analysed data from 3208 individuals, mean age 82.6 (SD 8.6). 2192 (70.9%) were female. 194 (6.3%) died during the first 30-days, 1686 (54.5%) were discharged to their own home, 211 (6.8%) had no mobility at 120-days, 141 (4.6%) experienced a postoperative complication. The median length of stay was 18 days (IQR 8-28). For mortality, c-statistics for the NHFS ranged from 0.68-0.69, similar to ASA and AMTS. For postoperative mobility, the c-statistics for the NHFS ranged from 0.74-0.83, similar to AMTS (0.61-0.82) and better than the ASA grade (0.68-0.71). Length of stay was significantly correlated with each score (p<0.001 by Jonckheere-Terpstra test); NHFS and AMTS showed inverted U-shaped relationships with length of stay. For postoperative complications, c-statistics for NHFS (0.54-0.59) were similar to ASA grade (0.53-0.61) and AMTS (0.50-0.58). Conclusions and Implications The NHFS performed consistently well in predicting functional outcomes, moderately in predicting mortality, but less well in predicting length of stay and complications. There remains room for improvement by adding further predictors such as measures of physical performance in future analyses.

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.

The study of the distribution and health risk assessment is meaningful to provide basic data for environmental management．To investigate the pollution of potential toxic organics and their health risk to human beings, water samples were collected at 7 sites of main surface water of Beijing during wet and dry seasons respectively. The targeted 92 organics were detected, including phthalates (PAEs), volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs) and phenols. The results showed that: there were 56 organics detected out, and the number ratios of detected compounds to the total compounds of the same kind increased as the following: VOCs, phthalates, phenols, PAHs. 8 VOCs were detected in wet season, and 3 in dry season. The concentration of 2,2-Dichloropropane was highest as 10.62ug/L, while the concentrations of other VOCs were below 5ug/L; There were 11 phthalates detected during dry season. The content of Bis(2-methoxyethyl) phthalate was highest as 188.47ng/L; 17 phenols were found in samples during wet season, and the highest concentration was 1244.73ng/L for 4-nitrophenol; PAHs could be detected in all samples, and the detected compounds and the corresponding average concentrations were higher in wet seasons than those in dry seasons, which indicated that non-point pollution was possibly the main pollution source. The health risk assessment of the detected 56 pollutants by using a model from US EPA showed that, the risk caused by the four kinds of toxic organics in this study was in the acceptable ranges.

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.

Liver cirrhosis is a chronic disease that is characterized by the presence of fibrosis and regeneration of nodules in the liver whose consequences are the development of portal hypertension and liver failure. Cirrhosis arises from a wide variety of chronic diseases, which progresses slowly after years or decades. Liver cirrhosis is a public health problem. It is usually associated with viral hepatitis, consumption of alcohol, metabolic syndrome, autoimmune processes, storage diseases, toxic substances, and medications. Cirrhosis is the fourteenth most common cause of death in adults throughout the world, the fourth in Europe and the ninth in the United States. The prevalence of this disease is underestimated because it is symptomatic it is not diagnosed in initial stages, and it usually goes to the decompensated stage at a rate of 5 to 7% per year. We review here the epidemiology, pathophysiology, etiology, and diagnosis of liver cirrhosis.

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.

This study examines the effect of market risk on the financial performance of 31 non-financial companies listed on the Casablanca Stock Exchange (CSE) over the period 2000-2016. We utilize three alternative variables to assess financial performance, namely return on assets, return on equity and profit margin. Next, we use the degree of financial leverage, the book-to-market ratio, and the gearing ratio as market risk variables. Besides, we employ the pooled OLS model, the fixed effects model, the random-effects model, the difference GMM and the system GMM models. The results show that market risk indicators have a negative and significant influence on the companies' financial performance. The elasticities are greater following the book-to-market ratio compared to the degree of financial leverage and the gearing ratio, respectively. In most cases, the firm size, the tangibility ratio, and the cash holdings ratio have a positive effect on financial performance, whereas the firms' age, the debt-to-income ratio, stock turnover, and leverage hurt the performance of these non-financial companies. Therefore, decision-makers and managers should mitigate market risk through appropriate strategies of risk management, such as derivatives and insurance techniques.

This research work focused on the risks we are faced with on our day to day activities, either directly or indirectly, which can gradually accumulates and results to communal crisis, religious crisis, socio-economic agitations and tribal crises. Nasarawa Eggon Local Government Area of Nasarawa State was used as case study and a well structure close–ended questionnaire was used for data collection as it relates to Controlled Self Risk Assessment (CSRA) and linear programming technique was used to analyze. The results proved that many of this processes were neglected in these communities, making them to be prone to incessant communal crisis. The study recommend that Government should strongly, as a matter of urgency address the unemployment rate, distribution of political position, schools, primary health care and equip security personnel with the modern technology facilities, which happen to record the highest risk level.

Hyperkalemia burden in non-dialysis CKD under nephrology care is undefined. We prospectively followed 2443 patients with two visits (referral and control with 12-month interval) in 46 nephrology clinics. Patients were stratified in four categories of hyperkalemia (sK≥5.0 mEq/L) by sK at visit 1 and 2: Absent (no-no), Resolving (yes-no), New Onset (no-yes), Persistent (yes-yes). We assessed competing risks of ESKD and death after visit 2. Age was 65±15 y, eGFR 35±17 mL/min/1.73 m2, proteinuria 0.40 (0.14-1.21) g/24h. In the two visits sK was 4.8±0.6 and levels ≥6 mEq/L were observed in  4%. Hyperkalemia was absent in 46%, resolving 17%, new onset 15% and persistent 22%. Renin-angiotensin-system inhibitors (RASI) were prescribed in 79% patients. During 3.6-year follow-up, 567 patients reached ESKD and 349 died. Multivariable competing risk analysis [sub-hazard ratio-sHR, 95%Confidence Interval-CI] evidenced that new onset [sHR 1.34, 95%CI 1.05-1.72] and persistent [sHR 1.27, 95%CI 1.02-1.58] hyperkalemia predicted higher ESKD risk versus absent, independently from main determinants of outcome including eGFR change. Conversely, no effect on mortality was observed. Results were confirmed by testing sK as continuous variable. Therefore, in CKD under nephrology care, mild-to-moderate hyperkalemia status is common (37%) and predicts per se higher ESKD risk but not mortality.

The three heat-induced coffee contaminants acrylamide, furfuryl alcohol (FA) and 5-hydroxymethylfurfural (HMF) were analyzed in a collective of commercial samples as well as in Coffea arabica seeds roasted under controlled conditions from very light Scandinavian style to very dark Neapolitan style profiles. Regarding acrylamide, average contents in commercial samples were lower than in a previous study in 2002 (196 compared to 303 µg/kg). The roasting experiment confirmed the inverse relationship between roasting degree and acrylamide content, i.e. the lighter the coffee the higher the acrylamide content. However, FA and HMF were inversely related to acrylamide and found in higher contents in darker roasts. Therefore, mitigation measures must consider all contaminants and not be focused isolatedly on acrylamide, specifically since FA and HMF are contained in much higher contents with lower margins of exposure compared to acrylamide.

Risk attitudes are relevant factors affecting the production and investment decisions at farm level. They are key factors that are related to farmers’ attitudes towards environment and climate change. Several methodological approaches are available to measure the level of stated risk of an economic agent. The Multiple Price List (MPL) method is one of the methods that is gaining relevance. In this study we apply the MPL and relate the risk outcomes with farmers’ characteristics and their perception towards environment and climate change. Data was collected using a face to face survey carried out for a group of 370 agricultural producers of the irrigation district located in northwest of Mexico. Results showed an average risk of about 0.32, locating the agricultural producers of the region in a group with risk aversion, according to the MPL scale. The heterogeneity analysis showed that the socioeconomic factors and the perceptions towards climate change are related to the farmers´ stated risk level. Farmers who are young women with propensity to use public support to invest were shown to be greater risk lovers. Farmers in the region have perceived climate change to a greater extent like floods, hail, diseases and pests, and changing vegetation.

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.

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.

Background. Increasing evidence demonstrate that concentration of protein in infant formula >1.9g/100Kcal with high levels of insulinogenic aminoacids is associated with accelerated weight gain, increased fat mass accumulation and risk of adiposity. Purpose of this study was to conduct a systematic review to determine the metabolic effects in infants feed with infant formula optimized in protein. Methods. Systematic review was conducted according PRISMA Statement. RCTs with one intervention group (infant formula with 1.6-1.9gr of protein/100Kcal) and at least one comparative control group (infant formula with >1.9gr of protein/100Kcal) were included. Standardized mean differences (SMD), through random model were calculated. Results. 15 RCT were included. Optimized protein in infant formula was associated with less gain of BMI at 24 months of follow-up (SMD -0.25, IC95% -0.36 to -0.13, p 0.01) and less fat mass accumulation (SMD -0.68, IC95% -0.98 to -0.37, p 0.01). Optimized protein was also associated to less gain of weight, weight/age Z-score, weight/length Z-score, BUN (mmol/dL) and IGF1 (ng/ml). No effect on length/age Z-score was observed. Conclusions. Robust evidence showed optimized protein (1.6gr/100Kcal to 1.9gr/100Kcal) in infant formula is associated with metabolic benefits in infants with less weight gain, BMI and fat mass accumulation.

The topic of the article refers to expressions used to address the psychosocial risk linked to the workplace violence. The article bases on the Polish-French comparison, using analysis of definitions, legal acts and public statistics. The purpose is to show social differences, in the context of mobbing and “harcèlement moral”, that surface from ratified definitions of these phenomena and public statistics. The final conclusions are the effect of a compilation of results of analysis and available literature. The choice of the two European, diverse areas of comparison for the diagnosis - Poland and France - is the result of selection of the method of data content analysis, chosen by the author because of the availability of the scientific resources essential for the article and accessible during an academic stay in Centre d'Etudes de l'Emploi in France.

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.

The past is an important lesson for facing the future with greater awareness. In this context, school plays a key role to spread knowledge on natural phenomena and to promote behavior change. Together with researchers, teachers can be strong allies to build more resilient future citizens. The Istituto Nazionale di Geofisica e Vulcanologia (INGV) school training activities provide tools to get ready for the next earthquake and/or tsunamis. About 5000 students from both Middle schools (ISCED 2) and High schools (ISCED 3) were involved in active learning activities based on a flipped-up approach during special online scientific events in the Pandemic. Online lab activities were conducted respectively during the European Researchers’ Night (“Earthquakes: history teaches us the future: researchers for a day with experimentation in didactics for ESL”) and during the World Water Day 2021 and the World Earth Day 2021 (“Tsunamis: history teaches us the future researchers for a day with experimentation in didactics for ESL”). These two Episodes of Situated Learning (ELS) experiences triggered students’ interest, favoring remote learning, developing life skills, focusing on historical seismic studies of both past earthquakes and tsunamis.

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.

Cryptocurrencies have obtained a crucial position in the international financial landscape. The cryptocurrency market has been perceived as a highly volatile market since the inception of Bitcoin. This study investigates the relevant performance of extreme value models (EVM) in estimating the Value-at-Risk (VaR) of Bitcoin and Ethereum returns. The extreme value mixture models, GPD-Normal-GPD (GNG) and GPD-KDE-GPD models are fitted to the returns of Bitcoin and Ethereum and the Kupiec likelihood backtesting procedure is performed on the VaR estimates to assess the fits. Both models’ results showed that the fits were a much more decent representation of the observed data when compared to the Normal distribution. The backtesting results showed that the GPD-KDE-GPD model’s fit was superior to that of the GPD-Normal-GPD for both sets of returns at all VaR risk levels except at the 99% level. The results of this study may assist with understanding the dynamics and risks associated with cryptocurrencies and can serve as a beneficial tool for decision-making and risk management to investors, traders, financial institutions and many other participants in the cryptocurrency ecosystem.

This study investigates Autism Spectrum Disorders (ASD) in Greece, focusing on estimating prevalence and identifying regional disparities in children aged 4 to 7 years. Utilizing a quantitative, descriptive, and exploratory methodology, the research employed a structured questionnaire to gather extensive maternal and child health data. The sample consisted of 517 mothers of children diagnosed with ASD from all over Greece contributing to a nuanced understanding of ASD predictors. The study aims to elucidate the role of prenatal factors in the likelihood of an ASD diagnosis and their impact on the subsequent functionality of children with ASD. The study identified significant predictors of lower functionality in children with ASD, including higher maternal age, delayed ASD diagnosis, lower family income, and higher birth order. Prenatal health issues, such as vaginal bleeding and infections, also influenced functional outcomes. Notably, a family history of neurological or psychiatric conditions appeared protective. The regression model demonstrated robust predictive power, underscoring the complexity of genetic, environmental, and socioeconomic factors in ASD development. The findings advocate for early diagnosis and intervention, systematic screening, and addressing socioeconomic disparities to improve functional outcomes. The results support evidence-based service development and policy adjustments to enhance early identification, intervention, and rehabilitation for children with ASD. Establishing standardized case-recording procedures and an ASD register at national and regional levels is recommended for systematic monitoring and resource evaluation.

The increasing rate of adoption of innovative technological achievements along with the penetration of the Next Generation Internet (NGI) technologies and Artificial Intelligence (AI) in the water sector, are leading to a shift to a Water-Smart Society. New challenges have emerged in terms of data interoperability, sharing, and trustworthiness due to the rapidly increasing volume of heterogeneous data generated by multiple technologies. Hence, there is a need for efficient harmonisation and smart modeling of the data to foster advanced AI analytical processes which will lead to efficient water data management. The main objective of this work is to propose two Smart Data Models focusing on the modeling of the Satellite Imaginary data and the Flood Risk Assessment processes. The utilisation of those models reinforces the fusion and homogenisation of diverse information and data facilitating the adoption of AI technologies for flood mapping and monitoring. Furthermore, a holistic framework has been developed and evaluated via qualitative and quantitative performance indicators revealing the efficacy of the proposed models concerning the usage of the models in real cases. The framework is based on the well-known and compatible technologies on NGSI-LD standards which are customised and applicable easily to support the water data management processes effectively.

A number of epidemiological studies have implicated elevated iron levels with higher risks of cardiometabolic diseases, including the metabolic syndrome (MetS). MetS is a pathologic clustering of metabolic derangements characterized by central obesity, insulin resistance, hypertension, and dyslipidemia, which can all lead to increased cardiovascular disease morbidity and mortality. However, it remains unclear whether a causal association exists between higher iron status and MetS and its associated risk components. Using the data from the Taiwan Biobank (TWB) (19,012 males; 42,340 females) and of the European Whites from the UK Biobank (UKB) (128,549 males; 142,817 females), we first constructed ethnic- and sex-specific hemoglobin-polygenic risk scores (Hb-PRS) as instrumental variable (IV) for iron status with the Hb-associated SNPs we previously identified from genome-wide association studies (GWAS). We then conducted Mendelian randomization (MR) analyses to elucidate the causal role of elevated iron (either Hb-PRS quintiles or continuous Hb-PRS) on various metabolic components. MR-Egger regressions determined the potential pleiotropic effects of the constructed Hb-PRSs, while the causal relationship of Hb-PRS with anemia served as a control in the analyses. The mean Hb concentration range corresponding to the Hb-PRS quintiles is relatively narrow in both UKB (14.91-15.21 g/dL for males and 13.39-13.71 g/dL for females) and TWB (14.79-15.28 g/dL for males and 12.78-13.21 g/dL for females). In these windows of Hb-PRSs, we found differential associations of Hb-PRS with diabetes (T2D) or hyperglycemia (HGY) as compared to other MetS components. The highest quintiles of Hb-PRSs were causally associated with greater risks of hypertension (HTN) and hypertriglyceridemia (DLP) (i.e., [Taiwanese HC males: Q5 vs. Q1 ORHTN = 1.10 (1.00–1.21), p = 0.0473, Q4 vs. Q1 ORDLP = 1.10 (1.00–1.22), p = 0.0485; European White males: ORHTN = 1.05 (1.01–1.09), p = 0.0194, ORDLP = 1.04 (1.00–1.08), p = 0.0468]). Interestingly, we obtained a consistent negative causal association between increasing Hb-PRS quintiles and T2D or HGY risk across all sex subgroups (i.e., [Taiwanese HC females: ORHGY = 0.89 (0.84–0.95), 0.88 (0.83–0.94), 0.87 (0.82–0.93), 0.86 (0.81–0.92) from Q2 to Q5; European White females: ORHGY = 0.92 (0.87–0.98), 0.91 (0.86–0.97), 0.93 (0.87–0.98), 0.87 (0.82–0.93) from Q2 to Q5; all p &lt; 0.05]. The positive causal relationships between Hb-PRSs and diastolic blood pressure (DBP) and triglycerides (TG) but inverse causal association with glucose (GLU) and glycated hemoglobin (HbA1c) further corroborated such findings. There is, however, a lack of causal association with central obesity (CO), while a U-shaped type of causality was observed for gout (GT) or hyperuricemia (HUA). Sensitivity analyses, which excluded subjects based on self-reports of health conditions or medications and hospital episode statistics data, revealed similar results. Our MR studies confirm a modest causal relationship between propensity of elevated iron status and increased risk of HTN and DLP. We have further observed that modestly lower iron levels causally contribute to the development of T2D. Further validation and elucidation of the underlying biological mechanisms are highly warranted.

Soil-transmitted helminthiasis (STH), a neglected tropical disease (NTD) remains a major health problem all over the world including Ghana, which has STH prevalence of 25.4%. To control the disease, the government of Ghana currently concentrates on implementing mass drug administration (MDA) efforts focusing only among school-aged children. However, various studies have suggested that focusing on only a specific group for MDA may not be cost-effective. Moreover, some adults such as teachers and school-workers spend large fraction of their time with children, who shed more parasite in environment due to unhygienic behavior, and thus have a higher risk of getting infected as compared to other adults. In this study we use a mathematical model to evaluate age-structured and risk-based policies for implementing MDA while capturing transmission dynamics of STH in Ghana. A cost model was developed that included various costs related to MDA to study cost-effectiveness of current policies of MDA in Ghana against novel policies to control STH in Ghana. We carry out analysis for five different scenarios— I: no MDA (baseline), II: current MDA policy (focusing children) in Ghana, III: MDA for different age groups (adults and children groups) for unlimited budget, IV: MDA for different age groups with limitations of number of individuals treated, and, V: MDA for different groups based on their risk of getting infected (adults school workers (high-risk group), adults non-school workers and children groups). Our results suggest that it might be more cost-effective to allocate treatment through MDA to at least some proportion of adults along with children. In case of unlimited budget, the best strategy in Scenario IV would be to treat approximately 22% of adults and approximately 45% of children. The most cost-effective among the 5 scenarios is suggested through scenario V, where high-risk adults group and children are provided MDA at higher level than low-risk adults. In conclusion, age-structured and risk-based allocation of treatment and resources is crucial to reducing STH load in developing countries.

In the context of global changes, Nature-Based Solutions (NBSs) increasingly draw attention as a possible way to reduce disaster risk associated with extreme hydro-meteorological events while providing human well-being and biodiversity benefits at the same time. The PHUSICOS platform is dedicated to gather and analyse relevant NBSs used to reduce disaster risk associated with extreme hydro-meteorological events in mountainous and hilly lands. To design the platform, an in-depth review of 11 existing platforms has been performed. The platform currently references 152 literature NBS cases and is continuously enriched with demonstrator sites through the contribution of NBS community. The platform also proposes a qualitative assessment of the NBSs collected according to 15 criteria related with five ambits: disaster risk reduction, technical and economical feasibility, environment, society and local economy. This paper presents the structure of the platform and a first analysis of its content.

Abstract Introduction: Despite the determination to succeed in eliminating neglected tropical diseases, these have been increasing within certain endemicities, particularly in depriving region. Objective: This study aimed to assess the relative burden of neglected tropical diseases in rural and urban slum settings in Eastern Ethiopia. Methods: A comparative cross-sectional study was conducted from February 25 to April 30, 2024 with a multistage random sampling technique used. A survey tool with the integration of the spectrum was employed. Data were entered using Epi-Data version 3.1 and analyzed using STATA 16. Descriptive statistics and multivariable logistic regression analysis was used to identify the risk factors and the level for statistical significance was declared at p-value < 0.05 with 95 % CI. Result: The response rate was 93 % and the mean age of house heads was 31.6 (Range; 18. 63) with 5.7 average family size. The overall prevalence of NTDs among study participants was 22.6 % (95% CI; 20.2, 25.2); urban slum it was 15 % (95% CI; 12.2, 18.4) while it was 29.8 % (95% CI; 26, 33.9) in rural. Though there is no statistically significant difference, the relative prevalence of NTDs in rural to urban was two. The multivariable analysis provided that the risk factors associated with NTDs were government employment (AOR: 12.5 (1.17, 132.4)), good income (AOR: 0.13 (.03, 0.57)), Child playing with soil (AOR: 5.8 (1.52, 22.0)); child hand washing at critical times ( AOR: 11.2 (1.7, 74.9)), presence of flies in the child faces (AOR: 20.3 (4.7, 88.6)) and type of drinking water sources (AOR: 0.11 (0.02, 0.73)). Conclusion: the burden of NTDs was moderate in the study area dominated by STH, Trachoma, and scabies. Socio economic and WASH factors were found to be associated with NTDs. Collaborated efforts among stakeholders are crucial to prevent and control NTDs.

In recent years, the assessment of damage scenarios of urban communities has become one of the central themes in local government policies, aimed at promoting effective seismic risk mitigation and improving the efficiency of rescue systems to manage emergencies. In Italy, the seismic hazard has become a topic issue since the 1982 Irpinia earthquake, and several ventures have been promoted to face the seismic mitigation of complex residential districts. The objective of this research is to define the damage scenarios of the city of Florence, where 97% of the building stock is designed without anti-seismic prescriptions. The urban vulnerability of Florence has been assessed on the basis of the current approaches available in technical literature, and it has been combined with the knowledge provided by the recent investigation on the subsoil. Once the possible damage scenarios have been defined, the resilience of the area has been determined and the population involved in the evacuation has been estimated.

Indoor air quality (IAQ) is a critical determinant of human health, with fungal contamination posing significant risks. In 2023, a total of 160 samples were collected from 40 selected rooms. These samples were cultured on Sabouraud Dextrose Agar (SDA) medium using a portable air sampler and incubated at 28°C for 7 days. Initial identification of fungal isolates was performed based on their morphology. Suspected isolates underwent further analysis using internal transcribed spacer (ITS) rDNA analysis. The results revealed 11 species across 8 genera in various rooms. The most prevalent fungi were Aspergillus niger (183 CFU) , Penicillium chrysogenum (139 CFU) and Cladosporium halotolerans (135 CFU). On the other hand, Curvularia hawaiiensis and A. ustus were rarely isolated (10 and 19 respectively). Effective treatment involves a combination of preventive measures, such as controlling humidity and ensuring proper ventilation, alongside targeted interventions like antifungal treatments and thorough cleaning. Continuous monitoring and management of indoor environments are essential to reduce fungal contamination, enhance air quality, and protect human health from the harmful effects of airborne fungi. This abstract underscore the importance of addressing indoor fungal contamination to promote safer, healthier living and working spaces.

The rapid proliferation of Internet of Things (IoT) devices has transformed various sectors, from smart homes to industrial systems. However, this growth has introduced significant security risks due to the increased attack surface and diverse nature of IoT devices. This paper presents a comprehensive assessment of IoT security risks and explores effective mitigation strategies. We first categorize the primary risks associated with IoT, including data breaches, device manipulation, and network vulnerabilities. Using a multi-layered approach, we analyze these risks in different contexts, such as consumer IoT, industrial IoT, and healthcare. The study then reviews existing security frameworks and protocols, highlighting their strengths and limitations. We propose a hybrid mitigation strategy combining encryption, access control, and anomaly detection to enhance IoT security. Furthermore, we discuss the role of regulatory standards and best practices in reinforcing IoT security. The findings underscore the need for a proactive and adaptive security posture to address evolving threats in the IoT landscape.

The integration of Artificial Intelligence (AI) in the FinTech industry has substantially reshaped operational workflows, product innovation, and risk management, all of which influence company valuation. This study investigates the impact of AI-enhanced multilayer networks on FinTech valuation. Utilizing a novel scalable multilayer network model with AI-driven Copula Nodes, the research reveals that operational efficiency is a significant driver of market value. However, the findings emphasize the necessity of a balanced strategy that integrates AI across all operational layers, particularly in risk management and product innovation, to maximize valuation. This study offers a comprehensive framework that enhances understanding of AI’s complex role in FinTech valuation, providing critical insights for industry stakeholders.

We use Fourier analysis to access risk in financial products. With it we analyze price changes of e.g. stocks. Via Fourier analysis we scrutinize quantitatively whether the frequency of change is higher than a change in (conserved) company value would allow. If it is the case, it would be a clear indicator of speculation and with it risk. The entire methods or better its application is fairly new. However, there were severe flaws in previous attempts; making the results (not the method) doubtful. We corrected all these mistakes by e.g. using Fourier transformation instead of discrete Fourier analysis. Our analysis is reliable in the entire frequency band, even for frequency of 1/1d or higher if the prices are noted accordingly. For the stocks scrutinized we found that the price of stocks changes disproportionally within one week which clearly indicates speculation. It would be an interesting extension to apply the method to crypto currencies as these currencies have no conserved value which makes normal considerations of volatility difficult.

Asbestos, also known by its commercial name of amianthus, has been a widely used material in various industries due to its unique properties. However, its extensive use has led to serious consequences for human health, most notably asbestosis, an irreversible chronic lung disease. Asbestosis increases the risk of lung cancer and malignant meso-thelioma both fatal diseases. To understand the role of asbestos in human health, applied sciences such as microscopy (optical and scanning electron microscopy) and geochemistry are fundamental to characterize the mineral fibers. In previous work we used these technics to characterize the fibers and, in this paper, we explore their issues associated with asbestos and asbestosis, as well as the challenges of science communication strategies to effectively inform society and workers about these risks. The lack of scientific culture, in general, leads to the lack of public awareness of risks, and to address these challenges, it is essential to implement effective communication and outreach plans and strategies, including the visualization of the fibers to understand why there may be a problem if inhaled. Educational campaigns, guidelines and plans that are informative and action-able, targeting workers, communities and the public about asbestos risks are very im-portant. General knowledge of mineralogy and geochemistry is needed and providing proper scientific communication and dissemination may help to cover the knowledge gap. We use examples and experience in Spain and Italy to illustrate this subject.

Lessons learned and risk-based outcomes from modernising the Australian Standard for post-mortem inspection and disposition judgement of beef, sheep, goat and pig carcases are described. Initial Risk Profiles identified priorities for quantitative assessments. The main difficulty encountered was the paucity of quantified performance of current inspection. Resolving this involved acquiring gross abnormality data representing regional production/proportional abattoir volumes, the range of gross abnormalities appearing nationally, proportional occurrence at carcase sites, and seasonality to enable comparisons. Evidence and discussion are provided for associated challenges experienced including preventing contamination, use of food chain information to support amendment, inspection as a part of industry Quality Assurance and opportunities to improve inspector training. Criteria considered by the Competent Authority for determination of equivalence of alternative post-mortem inspection techniques included comparisons of public health risk, non-detection rates for gross abnormalities, and microbial contamination resulting from inspection activities, as appropriate. Most gross abnormalities detected arose from animal health and welfare conditions affecting wholesomeness and did not present as food safety hazards. Non-detection rates between current and alternative inspection (observation) were negligible. A Quantitative Risk Assessment for Cysticercus bovis was conducted. Carcases with multiple gross abnormalities predominantly reflected historic infections (prior septicaemia) where trimming achieved wholesomeness unless cachexic.

Digitalization has fundamentally changed the global economy and will continue to do so. This study investigates how the US Federal Reserve and US Treasury may work together to use decentralized finance (DeFi) systems to promote economic growth in local communities. The study looks into the potential for transformation and the difficulties in incorporating DeFi into conventional financial institutions. Research shows that the use of cash as a means of payment is widely expected to decline in the future. As a result, the public’s ability to make transactions using central bank money may decline rapidly. This study's goals are to solve economic issues, promote innovation, and increase financial efficiency. The use of in-depth interviews, theme analysis, case studies, stakeholder perspectives, comparative analysis, and document analysis is suggested as part of a qualitative research methodology. The goal of these approaches is to offer a sophisticated comprehension of the dynamics of collaboration and the consequences of DeFi integration in the context of the Federal Reserve-Treasury relationship. Important data sources that are necessary to answer the research question are indicated, such as US Treasury statistics, Federal Reserve publications, DeFi platforms, and International Monetary Fund economic indicators. Informed decision-making and policy formation may pave the way for a more inclusive and efficient financial ecosystem, which will eventually drive regional economic growth in the United States and promote monetary sovereignty for the aforementioned monetary entities. This can be achieved by investigating creative collaboration tactics between the Federal Reserve and the US Treasury.

The energy transition is a complicated process that involves changing production and consumption habits, boosting the use of renewable energy sources, and reducing greenhouse gas emissions. This article examines the management of risks associated with this shift, focusing on investment, commercial, technological, regulatory, and environmental challenges. The paper proposes an effective way for dealing with new difficulties by assessing risks and the management techniques that accompany them. Furthermore, as a critical component of the energy revolution, the concept of Nearly Zero Energy Buildings (NZEB) is given, with a focus on the ambitions of INGV – Irpina Headquarters and the EU regulatory framework. Finally, the actions and methods employed to achieve the NZEB objectives are discussed, including the utilization of cutting-edge technologies and renewable energy sources. Furthermore, the concept of Nearly Zero Energy Buildings (NZEB) is introduced as an important component of the energy transition, with an emphasis on the European regulatory framework and the ambitions of the INGV – Irpina Headquarters. Finally, the interventions and techniques employed to achieve the NZEB targets are highlighted, such as the employment of advanced technologies and renewable energy resources. This study contributes significantly to understanding the processes and issues associated with the energy transition and the implementation of NZEB, hence boosting sustainability in the construction sector.

Previous reviews have investigated machine learning (ML) models used to predict the risk of developing preeclampsia but have not described how the ML models are intended to be deployed throughout pregnancy or feature performance. The aim of this study is to provide an overview of the existing ML models and their intended deployment patterns and performance along with identified features of high importance. This review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. PubMed, Engineering Village, and the Association for Computing Machinery were searched between January and February 2024. A total of 86 studies were found of which 14 were included. Out of 12 studies, eight showed the intent to use the ML model as a single-use, two intended a dual-use, and two intended multiple-use. A total of seven studies listed the features of the highest importance. Systolic and diastolic blood pressure were listed along with mean arterial pressure to be of high importance. Out of four studies intending to use the ML model more than a single-use, three of them were conducted in the years 2023 and 2024, whereas the remaining study is from 2011. No ML model emerged as superior across the subgroups of PE. Utilizing body mass index and either mean arterial pressure or diastolic blood pressure and systolic blood pressure may benefit the performance. The deployment patterns are mainly single use being within the gestation weeks 11+0 to 14+1.

In this study, a critical review was carried out using the Web of ScienceTM Core Collection database to analyse the scientific literature published to date to identify lines of research and future perspectives on the presence of chemical pollutants in beer brewing. Beer is one of the world's most popular drinks and the most consumed alcoholic beverage. However, a widespread challenge with potential implications for human and animal health is the presence of physical, chemical and/or microbiological contaminants in beer. Biogenic amines, heavy metals, mycotoxins, nitrosamines, pesticides, acrylamide, phthalates, bisphenols, microplastics and, to a lesser extent, hydrocarbons (aliphatic chlorinated and polycyclic aromatic), carbonyls, furan-derivatives, polychlorinated biphenyls and trihalomethanes are the main chemical pollutants found during the beer brewing process. Pollution sources include raw materials, technological process steps, the brewery environment and packaging materials. Different chemical pollutants have been found during the beer brewing process, from barley to beer. Brewing steps such as steeping, kilning, mashing, boiling, fermentation and clarification are critical in reducing the levels of many of these pollutants. As a result, their residual levels are usually below the maximum levels allowed by international regulations.

In recent years, the digital economy has played an increasingly important role in enhancing productivity, fostering growth, and facilitating the emergence of digital banking. With the widespread adoption of digital financial services for financial inclusion, the banking sector is experiencing a demand for digital transformation. It is important to note that despite the many advantages of this change, it also disrupts the familiar banking experience that customers have grown to expect, as well as introducing potential risks to maintaining customer protection at previous levels. Many critics have raised concerns regarding customer protection and potential exposure to various risks that may arise from digital financial services, which may result in both financial and non-financial losses. These risks can impact customer retention as dissatisfied customers may switch to alternative service providers. Additionally, reputation can be affected since merely offering digital financial services may not sufficiently safeguard customers. To remain competitive, financial institutions must deliver a secure experience that aligns with customer expectations while considering economic factors and societal needs. This is why it is essential to comprehend the severity of the risk factors that influence the protection of customers in the realm of digitalized banking services and products. In this study, five factors have been identified that influence customer protection when using digital financial services in Pakistan. Based on the analysis conducted using SmartPLS, it appears that all the factors proposed in this study have a significant and positive impact on the protection of customers. In particular, the information provided remains of paramount importance when it comes to determining the level of protection that a customer is entitled to within digital financial services, followed by responsiveness, privacy, authentication, and encryption mechanisms. Due to these findings, the implementation of enhanced information security management principles becomes imperative for the development and progress of the Pakistani digital banking industry.

Objective: The goal of this review is to provide a succinct, yet comprehensive, guide to the an-tepartum management of multiple gestations. Methods: This narrative review on twins and multiple gestation provides a concise guide for providers with this ever-growing patient population. PubMED was utilized for literature search. Each reference was evaluated and graded for quality of evidence by US Preventative Services Task Force and Cochrane Review guidelines. Screening, surveillance, and management strategies are delineated succinctly and organized by type of multiple gestation being managed from the lowest risk dichorionic twin pair to the increasingly escalating risks of twins and higher order multiples sharing a placenta and/or amniotic sac. Results: The incidence of twin pregnancies has grown over the past several years, due in large part to delayed reproductive timing and surge in assisted reproductive technologies. Twin pregnancies are associated with higher morbidity for both gravidas and offspring, warranting evidence-based approach in counseling and management. Conclusions: We note the important differences among multiples in chorionicity and amnionicity, in the importance of close surveillance and early delivery. Graded clinical pearls and evi-dence-based recommendations are presented to guide obstetric providers.

The effects of climate change health impacts on urban health care systems and vulnerable populations are a researched topic with foundations on urban risk management, urban health methodologies, and sustainable urbanization. As climate change is a dynamic and transformative global issue the gap between adaptation and mitigation efforts and urban planning relies, among other things, in the limitations of previous studies of risk management structures tailored to the existing strategy to calculate the uncertainties and predict their influence on urban systems and subsystems. Moreover, as climate and health is a well-researched issue, it is also complex as the methodologies and strategic approach to minimize health risks of climate change is intrinsically contingent to risk methodologies and policy-making processes that are efficient with support of knowledge-based information. This paper emphasis the need for focusing on urban health risk management methods that serves to identify potential opportunities, and then manage and take action to prevent adverse health effects. It also emphasizes the probability of events and their consequences, which are measurable both qualitatively and quantitatively.

Accurate measurement of systemic financial risk is critical to maintaining the stability of financial markets. Taking China as the subject of investigation, the Chinese Financial Stress Index (CFSI) indicator system was con-structed by integrating six dimensions and employing Gray Relation Analysis (GRA) for dimensionality reduction of the indicators. The CFSI was derived using the Attribute Hierarchy Model (AHM) method with the Criteria Importance Through the Intercriteria Correlation (CRITIC) method, and an Improved Gravitational Search Algorithm (IGSA) optimized Radial Basis Function Neural Network (RBFNN) was proposed for out-of-sample prediction of CFSI trends from 2024 to 2026. By analyzing the trend of financial pressure indicators, the relationship between financial pressure and economic activity can be effectively identified. The research findings indicate that: (1) The CFSI is capable of accurately reflecting the current financial stress situation in China; (2) The IGSA-RBFNN demonstrates good robustness and generalization capabilities, predicting that the CFSI index will reach a peak value of 0.543 by the end of 2024, and there exists a regular pattern of stress rebound towards the end of each year. The novel methodology benefits policymakers and regulatory authorities to formulate preventive measures and risk management by identifying potential risks and vulnerabilities in advance.

This study sought to spatially characterise and explain the differences of peoples’ perceptions on the impact of COVID-19 based on the socio-economic disparities in Gauteng, using choropleth mapping and Geographically Weighted Regression (GWR). Results indicate that respondents from relatively vulnerable municipalities like Merafong, Mogale City and Lesedi reported life being worse, information scant, and overall despondency being high since COVID-19. These are areas that fall under the High to Very High categories in terms of the Socio-economic Risk Index. GWR results, however, did not show a high explanatory power on the COVID-19 variables se-lected for the research, based on R2 values. For instance, the residual in overall satisfaction with life after COVID-19 was the lowest (-0.5 to 0.5) in the less affluent districts of the Rand West City and Sedibeng. Residual variables on life changes after COVID-19 were also the lowest in the southern parts of the same districts, with other low values almost evenly distributed throughout the province for the variable ‘Government information on COVID-19 was scant’. Although overestimation and underestimation existed, most were relatively low falling between -1.5 to -0.5 and distributed evenly across the province. In sum, however, the findings point to the complexity of socio-economic factors in spatially characterising social risk and vulnerability. Additionally, the negative sentiments expressed by people from the more vulnerable locations in the province emphasise the need for more targeted interventions by government to cushion the residents of the province to the continued negative impacts of COVID-19.

Purpose: To identify factors linked with nutritional risk via the Malnutrition Universal Screening Tool scale assessment among critically ill patients from a hospital in Cali (Colombia). Materials and methods: A retrospective, analytical observational study was conducted with patients admitted to an intensive care unit (ICU). Sociodemographic, clinical, hematological, and biochemical parameters were analyzed, as well as their association with nutritional risk and patient mortality. Binary logistic regression was applied to outline nutritional risk. Results: Overall, 28.4% prevalence of elevated nutritional risk was observed. An association was found between nutritional risk and hemoglobin and hematocrit values, primary diseases accounting for ICU admission, gastrointestinal symptoms, and nutritional support route (p < 0.05). Mortality was 11.6% and it was correlated with nutritional risk, hemoglobin, and blood urea nitrogen. Conclusions: Gastrointestinal symptoms and the type of nutritional support received during hospitalization may increase nutritional risk, whereas polycythemia was a protective factor. We found an associative model to determine nutritional risk with high specificity and an adequate diagnostic validity index.

To ensure sustainability of the future power grid, the rate of expansion of distributed renewable energy resources (DRER) has introduced operational challenges. These includes managing transmission constraints with DRER power injection, dispatching DRER efficiently, managing system frequency and ensuring sufficient reactive power for voltage support. Coupled with the intensification of wildfires, power infrastructure across the United States faces challenges to minimize the impact to maintain system reliability and resiliency. This research embarks on a comprehensive evaluation, beginning with an in-depth historical analysis to delineate regions most susceptible to wildfires. Utilizing a multidimensional approach, the study assesses wildfire-induced risks to power grids, by integrating historical wildfire occurrences, real-time wildfire proximities, Moderate Resolution Imaging Spectroradiometer (MODIS) derived vegetation metrics, and system parameters, by employing Principal Component Analysis (PCA) based optimal weights, leading to the formulation of a novel risk factor model. This risk factor has the potential to be the key to ensuring the resilience of a renewable-rich smart grid when faced with a severe weather event. Our model’s applicability was further verified through an empirical assessment, selecting representative networks from diverse regions, providing insights into the geographical variability of risk factors. Ultimately, this study offers stakeholders and policymakers a comprehensive tool-set, empowering decisions regarding infrastructure investments, grid reinforcements, and strategic power rerouting to ensure consistent energy delivery using risk assessment against wildfire.

HIV diagnosis and poor HIV management have various detrimental impacts on the lives of people living with HIV (PLHIV). As part of a large qualitative study investigating HIV risk factors and impacts, with the suicide topic not being a focus, this paper describes factors contributing to suicidal ideation and attempts that arose naturally in the stories of women living with HIV (WLHIV) in Yogyakarta and Belu districts, Indonesia. The participants were recruited using the snowball sampling technique. Guided by a qualitative data analysis framework, the data were thematically analysed. Findings indicated participants experienced immense psychological challenges due to the infection, spousal transmission, fear of mother-to-child transmission, and losing a child due to AIDS, which triggered suicidal ideation and attempts. The women’s lack of awareness of HIV management strategies resulted in them feeling trapped and overwhelmed. Associated negative thoughts and the anticipation and experience of stigma relating to their HIV status were influencing factors for thoughts of suicide among participants. Lack of social support from family and friends during the early stage of HIV diagnosis, compounded with pre-existing financial difficulties, lack of income, unemployment, and feeling overburdened, also triggered the women’s thoughts of suicide. Other influencing factors for suicidal ideation and attempts among the women were family breakdown following HIV diagnosis and this was reflected in family disputes, husband-wife separation or divorce, mother-child separation by other family members, reported concern about future relationships, and fear of being rejected or abandoned by their partner due to their HIV positive status. The findings indicate the need for a nuanced approach to counselling within HIV care interventions for couples to support the acceptance of each other’s HIV status whilst maintaining psychological wellbeing. Additionally, the findings indicate the importance of HIV education and awareness among community members for the de-stigmatisation of HIV and to increase the acceptance of PLHIV within families and communities.

Machine Learning techniques can be used to identify whether deficits in cognitive functions contribute to antisocial and aggressive behavior. This paper initially presents the results of tests conducted on delinquent and non-delinquent youths to assess their cognitive functions. The dataset extracted from these assessments, consisting of 37 predictor variables and one target. was used to train three algorithms that aim to predict whether the data corresponds to that of a young offender or a non-offending youth. Prior to this, statistical tests were conducted on the data to identify characteristics that exhibited significant differences in order to select the most relevant features and optimize the prediction results. Additionally, other feature selection methods, such as Boruta, RFE, and Filter, were applied, and their effects on the accuracy of each of the three machine learning models used (SVM, RF, and KNN) were compared. 80% of the data were utilized for training, while the remaining 20% were used for validation. The best result was achieved by the K-NN model trained with 19 features selected by the Boruta method, followed by the SVM model trained with 24 features selected by the filter method.

The perception of the impacts of climate risks on health systems in the Grand Lomé region of Togo is diverse. This study was carried out based on information collected in the field. The investigation was based on a questionnaire, individual interviews and field observations. Data collection was carried out in a purposive manner in twenty-four (24) health facilities with a total of 112 health service people and 13 resource people affected. This article presents the results on the perception of the impacts of climate change on health personnel, the environment and buildings. The results show that 92.31% of respondents attest that climate change has impacts on health personnel; 84.62% on the environment and 84.62% on buildings and other health infrastructure. This study shows that climate change has real consequences on human health. It is therefore urgent that those responsible for health systems in the Grand Lomé region, which is home to the capital of Togo, can focus on finding adaptation measures in relation to each health structure and according to its intervention platform.

Patients with advanced chronic liver disease (ACLD) or cirrhosis undergoing surgery have an increased risk of morbidity and mortality in contrast to the general population. Retrospective, observational study of ACLD patients to evaluate the predictive capacity of previous surgical risk scores in a European cohort of patients. ACLD was defined by the presence of thrombocytopenia <150.000/uL and splenomegaly; AST-to-Platelet Ratio Index >2; nodular liver edge by ultrasound; transient elastography >15 kPa and/or signs of portal hypertension. We assessed variables related to 90-day mortality and the discrimination and calibration of current surgical scores (Child-Pugh, MELD-Na, MRS, NSQIP, and VOCAL-Penn). Only patients with ACLD and major surgeries included in VOCAL-Penn were considered (n=512). The mortality rate at 90 days after surgery was 9.8%. Baseline disparities between H. Mar and VOCAL-Penn cohorts were identified. Etiology, obesity, or platelet count not were associated with mortality. The VOCAL-Penn showed the best discrimination (C-statistic90D= 0.876) and overall predictive capacity (Brier90D= 0.054) but calibration was not excellent in our cohort. VOCAL-Penn was suboptimal in patients with diabetes (C-statistic30D= 0.770), without signs of portal hypertension (C-statistic30D= 0.555), or with an abdominal wall (C-statistic30D= 0.608) or urgent (C-statistic180D= 0.692) surgeries. Our European cohort has shown a mortality rate after surgery similar to those described in American studies. However, some variables included in the VOCAL-Penn score were not associated with mortality, and VOCAL-Penn’s discriminative ability decreases in patients with diabetes, without signs of portal hypertension, and with abdominal wall or urgent surgeries. These results should be validated in larger multicenter and prospective studies.

The rapid development of the regional economy in China has led to the rise of local ecological risks. It is very important to provide enjoyable ecosystem services to residents while reducing ecological risks. In order to understand spatial relationships between ecosystem services and ecological risks, we took Chongqing as an example in this study to assess the spatial relationship between ecosystem services and ecological risks at the county scale based on the ES-DPSIR system. The main findings include: (1) significant variation in the spatial distribution of the comprehensive ecosystem service index, where the lowest ecosystem service index (0.013) was found in the main urban area of Chongqing and the scores gradually increased outward from this center, reaching 0.689 in the outermost areas, (2) the increase of the comprehensive ecological risk index from east to west, ranging from -0.134 to 0.333, (3) the spatial relationship between ecosystem services and ecological risks was prominent, with 52.63% of the districts and counties being imbalanced or mild imbalanced, and (4) the significant differences between development trends of ecosystem services-ecological risks, including 60.53% being imbalanced districts and 30.47% mildly balanced. Overall, it was necessary to improve the relationship between ecosystem services and ecological risks in Chongqing by reducing ecological risks., and these research results could provide effective approaches and technical support for improving regional ecological security and enhancing ecosystem service capabilities.

The rapid changes in technology on a global scale, combined with the widespread adoption of business operations in cyberspace, have intensified the need for robust protection against escalating risks posed by cyber threats. This research paper aims to identify fundamental cyber resilience management attributes that enable organizations to manage cybersecurity, sustain, and adapt amidst evolving cyber risks and threats. By integrating resilience theory and security theory, this study establishes the attributes for resilience within cyber domains, making a novel contribution to cyber resilience management in organizations. The study introduces a model featuring seven main variables: Rationale, Reliable, Readiness, Resistance, Robust, Rebound, Reflective, and sub-variables across the Physical, Logical, and Social cyber domains, providing a converged framework for achieving cyber resilience. The findings of the study highlight the significance of fundamental attributes for enhancing cyber resilience management in organizations, such as clarity in purpose, vision, and values for security management, an empowered culture, availability of resources, avoidance of single points of failure, development, and coordination of resources to respond to threats and risks, promotion of continual improvement, and the sharing of information and knowledge. In conclusion, this research paper presents a model for managing cybersecurity in organizations by identifying key attributes for achieving cyber resilience.

Stochastic mortality models seek to forecast future mortality rates; thus, apparently the objective variable should be the mortality rate expressed in the original scale. However, the performance of stochastic mortality models - in terms, that is, of their goodness-of-fit and prediction accuracy - is often based on the logarithmic scale of the mortality rate. In this article, we examine whether the same forecast outcomes are obtained when the performance of mortality models is assessed based on the original and log scales of the mortality rate. We compare four different stochastic mortality models: the original Lee-Carter model, the Lee-Carter model with (log-)normal distribution, the Lee-Carter model with Poisson distribution and the median Lee-Carter model. We show that the preferred model will depend on the scale of the objective variable, the selection criteria measure and the range of ages analysed.

In the overall context of national eco-conservation civilization development and considering the hills in the Beijing-Tianjin-Hebei-Shanxi region, the local forest coverage rate is gradually on the rise, and so is the risk of forest fire. Every year, satellites can monitor and detect hundreds of fire spots on average. In recent years, serious fire took place for several times, leading to loss of life and personal injury. Then the fire-fighting work consumed huge amount of labor and material resources, exerting negative social impacts in many ways. Thus, the analysis of fire climate background in this region and the forecast based on fire weather indexes constitute an important part in the forest fire risk management. Located in the tropical monsoon climate zone, four provinces and municipalities of Beijing, Tianjin, Hebei and Shanxi are similar in terms of climate characteristics. This study tries to analyze the characteristics about fire spots under satellite monitoring, fire climate and fire weather index. The probability distribution analysis of weather index about fire spots in history and key meteorological observation stations as well as the weather index analysis in the early stage of typical fire indicate that the Fine Fuel Moisture Content (FFMC) and the Initial Spread Index (ISI) in the Fire Weather Index (FWI) system is applicable to the fire risk analysis in the Beijing-Tianjin-Hebei-Shanxi region, which can also effectively indicate the fuel moisture and spread conditions. As regards to the average level in Beijing-Tianjin-Hebei-Shanxi, when the FFMC is smaller than 93.5 and the ISI is also smaller than 5.0, there is a low risk of fire; when the FFMC is above 94 and the ISI is larger than 10.0, there is a high risk of fire; and the fire risk will be extremely high if the FFMC is over 96 and the ISI is above 13.0. In the practical fire-fighting management, the fire danger class can be released in reference to the ISI classes and threshold values of key meteorological observation stations under analysis provided by this study.