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.

Background and objectives: Due to resistance and lack of treatment options, hospital-acquired Acinetobacter baumannii (A. baumannii) infections are associated with high mortality. The aim of this study was to identify the characteristics and outcomes of patients with infections caused by multidrug resistant A. baumannii in a tertiary-care teaching hospital and to determine the risk factors for in-hospital mortality. Materials and methods: A retrospective cohort study including 196 patients with A. baumannii strains isolated from different clinical specimens in the Hospital of the Lithuanian University of Health Sciences in 2016, 2017 and 2020, 2021 was conducted. Data on patients’ characteristics, comorbid diseases, treatment, length of hospital and ICU stay, outcome were collected. To determine risk factors for in-hospital mortality, logistic regression analysis was performed. Results: There were 60 (30.6%) women 136 (69.4%) men with a mean age of 61.7 ± 16.6 years (range, 52–74). More than three-fourths (76.5%, n = 150) of the patients had at least one comorbid disease. The highest number of A. baumannii strains were isolated from patients hospitalized in ICUs (43.4%, n = 85). A. baumannii strains producing three types of β-lactamases were more frequently isolated from women than men (77.8 % vs. 22.2%, p = 0.006). Infections caused by A. baumannii strains producing two types of β-lactamases were significantly more often treated with combination therapy than infections caused by strains producing one type of β-lactamase (78.9% vs. 60.0%, p = 0.019). Patients with A. baumannii strains producing two different types of β-lactamases (AmpC plus KPC, AmpC plus ESBL, or ESBL plus KPC) stayed significantly shorter at the ICU compared to patients with A. baumannii strains not producing β-lactamases (median of 9, IQR 2–18, vs. median of 26, IQR 7–38, p = 0.022). Death occurred in 58.7% (n = 115) of patients. Logistic regression analysis showed that combination therapy, length of hospital stay of < 10 days after A. baumannii infection, age of > 58 years, and absence of co-infection were independent predictors of in-hospital mortality. Conclusions: Patients with infection caused by A. baumannii strains producing two different types of β-lactamases were more frequently treated with combination therapy. Mortality of patients with multidrug resistant A. baumannii infection was high, and it was associated with patient’s age, length of hospital stay after the diagnosis of A. baumannii infection, absence of co-infection, and combination treatment.

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.

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by the loss of dopaminergic neurons and the buildup of misfolded alpha-synuclein proteins. While its exact cause remains unknown, several factors may influence its development. This review examines how factors like chronic constipation, head injuries, cholesterol and uric acid levels, pesticide exposure, smoking, NSAIDs, and caffeine intake may affect PD risk. Chronic constipation appears to be linked to a higher risk of PD, potentially serving as an early warning sign. Head injuries, especially mild-to-moderate ones, may also play a role in increasing PD risk. Surprisingly, higher levels of cholesterol seem to protect against PD, while lower levels of uric acid might increase the risk in the presence of some differences according to gender type. Exposure to certain pesticides is associated with a higher PD risk. NSAIDs, on the other hand, may or may not have a protective effect, with conflicting evidence. Interestingly, caffeine and tobacco smoking appear to lower the PD risk. Further studies are needed to fully understand the complex interplay between these factors and PD. It's also important to remember that these are just general trends, and individual risk factors will vary depending on a person's unique genetic makeup, medical history, and overall health.

OBJECTIVE: To investigate the value of serum inflammatory factor levels in acute ischemic stroke patients after revascularization therapy in assessing acute prognosis. METHODS: 94 patients with acute ischemic stroke who underwent revascularization therapy admitted to our hospital from January 01, 2022 to January 01, 2024 were studied. The main evaluation index was modified Rankin Scale score (mRS) after 3 months, and patients with mRS score >2 were categorized into the poor prognosis group, and the rest were the good prognosis group. As well as the treatment of revascularization in all patients was used as a division into a thrombus extraction group and an intravenous thrombolysis group. Logistic regression analysis was applied to explore the independent risk factors for the prognosis of patients treated with recanalization for acute ischemic stroke. RESULTS: Two groups with good (59 cases) and poor (35 cases) prognosis were divided according to the mRS score. There were some differences in age, gender, emergency GLU, INR, whether they had diabetes or hypertension and other contents between the two groups, but the differences were not statistically significant. The NIHSS score, hospitalization days, previous cardiac history, hospitalization days, LDL, fasting glucose, IL-6, and TNF-a at the time of admission were lower than those in the poor prognosis group, and the difference was statistically significant. In the patients in the embolization group, there were some differences in age, gender, emergency GLU, INR, whether they had diabetes or hypertension and other contents between the two groups, but the differences were not statistically significant. The pre-hospital NHISS score, IL-6, and TNF-a of patients in the good prognosis group were lower than those in the poor prognosis group, and the difference was statistically significant. CONCLUSION: IL-6 and TNF-α may be used as predictors of prognosis after revascularization therapy for acute ischemic stroke, and this conclusion also applies to patients in the embolization group.

This paper introduces the exponential time differencing (ETD) technique as a numerical method to solve efficiently American vulnerable options pricing. We address several challenges, including removing cross-derivative terms through appropriate transformations, treating early-exercise opportunities using the penalty method, and substituting fixed boundary conditions with corresponding one-sided finite differences. The proposed method is shown to be both accurate and efficient through numerical experiments, which also compare the results with existing methods and analyse the numerical stability and convergence rate.

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.

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.

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.

The sinking of cavities in urban areas is a very important geological risk to which many towns in Puglia are exposed. The study, mapping, geological and speleological description, classification and cataloging of forms and types of cavities is of fundamental importance for each urban center because it is linked to past local anthropic and natural processes, unique to each site. All this could lead to an enhancement of existing underground cavities in urban areas through conservation and continuous monitoring. Unfortunately in many cases these underground cavities have been used as landfills and subsequently abandoned. One of these cavities at the end of March 2007 collapsed in the inhabited center of Gallipoli causing damage to the structures and fortunately not to human lives. In the area relating to the collapsed cavity, a series of geophysical investigations were undertaken with the use of ground penetrating radar methodology in an attempt to delimit the area of collapse and understand the possible types of interventions for restoring the area. In the same area the measures were repeated 16 years later (December 2022) due to another collapse. The results show a much more widespread danger situation.

We present a hierarchical reinforcement learning (RL) architecture that employs various low-level agents to act in the trading environment, i.e. the market. The highest level agent selects among a group of specialised agents, and then the selected agent decides when to sell or buy a single asset for some period. This period can be variable according to a termination function. We hypothesized that due to different market regimes, more than one single agent is needed when trying to learn from such heterogeneous data, and instead, multiple agents will perform better, with each one specialising in a subset of the data. We use $k-means$ clustering to partition the data and train each agent with a different cluster. Partitioning the input data also helps model-based RL (MBRL), where models can be heterogeneous. We also add two simple decision-making models to the set of low-level agents, diversifying the pool of available agents and thus increasing overall behaviour flexibility. We perform multiple experiments showing the strengths of a hierarchical approach and test various prediction models at both levels. We also use a risk-based reward at the high level, which transforms the overall problem into a risk-return optimization. This type of reward shows a significant reduction in risk while minimally reducing profits. Overall, the hierarchical approach shows significant promise, especially when the pool of low-level agents is highly diverse.

Temporomandibular joint disorders (TMD) are characterized by their multifactorial etiology and pathogenesis. A 3-year prospective study was conducted in a Portuguese TMD department to study the prevalence of different TMD signs and symptoms and their association with risk factors and comorbidities. Five hundred ninety-five patients were included using an online database: EUROTMJ. Most patients were female (80.50 %), with a mean age of 38.20±15.73 years. The main complaints were temporomandibular joint (TMJ) clicking (13.26%), pain (12.49%), and masticatory muscle tension (12.15%). The main clinical findings were myalgia (74%), TMJ clicking (60-62%) and arthralgia (31-36%). Risk factors such as clenching (60%) and bruxism (30%) were positively associated with TMJ pain and myalgia. Orthodontic treatment (20%) and wisdom tooth removal (19%) were positively associated with TMJ clicking, while jaw trauma (6%) tracheal intubation (4%) and orthognathic surgery (1%) were positively associated with TMJ crepitus, limited man-dibular range of motion and TMJ pain, respectively. 42.88% of TMD patients had other associated chronic diseases, most of them were mental behavioral or neurodevelopmental disorders (33.76%), namely, anxiety (20%) and depression (13%). The authors also observed a positively association of mental disorders with the degree of TMJ pain and myalgia. Online database seems to be a relevant scientific instrument for healthcare providers who treat TMD. The authors expect that EUROTMJ database can serve as a milestone for other TMD departments.

Aortic dissection (AD) is a critical heart condition with potentially severe outcomes. Our study aims to investigate the existence of a "weekend effect" in AD by examining the correlation between patient outcomes and the timing of their treatment during weekdays vs weekends. Specifically, we assessed prospectively the effects of the timing of treatment on patient outcomes for acute aortic dissection, both before surgical intervention and during hospitalization, as well as during the follow-up period. The mean age of the study population used here was 62.5 years with a high degree of variability. We recorded a rate of mortality before surgery of 8.65% for the weekend group and 15% for the weekday group, with no significant differences noted in the results of statistical tests. During hospitalization, mortality was found to be 50% (n=52) in the weekend group and 25% (n=5) in the weekday group, again with no significant differences observed in the results of the same statistical tests. Patient mortality after discharge was 9.61% (n=10) in the weekend group and 5% (n=1) in the weekday group. Our findings suggest that there is no significant difference in mortality rates between patients admitted to the hospital on weekends versus weekdays. Therefore, the period of the week when a patient presents to the hospital with aortic dissection appears to not affect their mortality outcomes.

The long-term laboratory aspects of the effects of COVID-19 on liver function are still not well understood. Therefore, this study aimed to evaluate the hepatic clinical-laboratory profile of patients with up to 20 months of long-term COVID-19. A total of 243 patients of both sexes aged 18 years or older hospitalised in the acute phase of COVID-19 were included in this study. Liver function analysis was performed. Changes were identified in the mean levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), gamma-glutamyl transferase (GGT), and ferritin. Inflammatory markers such as ferritin > 300 U/L were observed in the group that presented more changes in liver function markers (ALT, AST, and GGT). Age ≥ 60 years, male sex, AST > 25 U/L, and GGT ≥ 50 or 32 U/L were associated with ALT > 29 U/L. There was a correlation between ALT and AST, LDH, GGT, and ferritin. Our findings suggest that ALT and AST levels may be elevated in patients with long-term COVID, especially in those hospitalised in the acute phase. In addition, ALT > 29 U/L was associated with other markers of liver injury, such as LDH, GGT, and ferritin.

The perception in pair trading is to recognize two stocks that move together, and their prices will converge to a mean value in future. However, finding the mean-reverted point at which the value of the pair will converge, and optimal boundaries of the trade is not easy. As uncertainty and model misspecifications may lead to losses. To cater for the problems, this study employs the novel entropic approach that utilizes entropy as penalty function for the misspecification of the model. The use of entropy as a measure of risk in pair trading is a nascent idea and this study utilizes daily data for 64 companies listed on PSX for the years 2017, 2018, and 2019, respectively to compute the returns based on the entropic approach. These companies cover the major sectors including Cement, Chemical, Automobile Assembler, Food and Personal Care Products, Oil and Gas Marketing Companies, Oil and Gas Exploration Companies Ltd, Power Generation and Distribution, Refinery and Pharmaceuticals. The returns to these stocks are then evaluated and compared with the Buy and Hold strategy. The results show positive and significant returns from pair trading using an entropic approach.

Antibiotic resistance is a pressing global and planetary health challenge. Links between climate change, antibiotic use and the emergence of antibiotic resistance have been well documented, but less attention has been given to the impact(s) of earth systems on specific bacterial livestock diseases at a more granular level. Understanding the precise impacts of climate change on livestock health – and in turn the use of antibiotics to address that ill-health – is important in providing an evidence base to tackle such impacts and to develop practical, implementable and locally acceptable solutions within and beyond current antibiotic stewardship programmes. In this paper, we set out the case for better integration of earth scientists and their specific disciplinary skill set (specifically, problem-solving with incomplete/fragmentary data; the ability to work across four dimensions and at the interface between the present and deep/geological time) into planetary health research. We then discuss a methodology that makes use of risk mapping, a common methodology in earth science but less frequently used in health science, to map disease risk against changing climatic conditions at a granular level. This will enable predictions of future disease risk and risk impacts based on predicted future climate conditions, and thus provide an evidence base for planetary health activists to influence policy and develop mitigations. Our case study – of climate conditions’ impact on livestock health in Karnataka, India – clearly evidences the benefit of integrating earth scientists into planetary health research.

Combination treatment, i.e., the use of two or more drugs for the same condition, is frequent in medicine if monotherapy yields an insufficient therapeutic response. We here review and challenge clinical study designs and formats of reporting outcomes for the evaluation of the benefit/risk ratio of combination treatment over monotherapy. We demonstrate that benefits of combination treatment at the group level over-estimate the probability of benefit at the single patient level based on outcome simulations under almost any imaginable setting. Based on these findings we propose that studies testing combination treatment should always report on percentages of responders to monotherapy and combination treatment. We provide equations that allow calculation of the percentage of patients truly benefitting from combination (responders to both monotherapies) and that of patients exposed to risk of harm from adverse effects without a reasonable expectation of individual benefit. These considerations are explained based on real clinical data, mostly from the field of functional urology (male lower urinary tract symptoms).

Abstract – Objective: Ovarian cancer, although not possessing a high incidence, is still the most common cancer-related deaths among women diagnosed with a gynecologic malignancy. The present study aims to highlight the epidemiology, risk factors of this disease and the significance of development of improved early detection strategies. Materials and Methods: This study was conducted using current published English studies by searching PubMed and Google Scholar. The search strategy included the keywords “ovarian cancer”, “diagnosis”, “risk factors”, “screening”, “epidemiology”. Studies on incidence and mortality were also considered. Case reports were excluded.Results: The highest incidence and mortality rates are observed in Central and Eastern Europe, while rates are relatively low in Asia and Africa. These rates are highest among the white population (14.3 per 100,000) and lowest among blacks (10 per 100,000) and Asians (9.7 per 100,000). The risk factors for this disease includes a family history, hormonal factors, nutrition and diet and physical activity, with some of them playing protective roles in reducing risk of ovarian cancers. There are no reliable screening methods for ovarian cancers. The most common diagnosis methods include a transvaginal ultrasound and a blood test to detect CA125 markers.Conclusions: The mortality rate of ovarian cancer is gradually increasing; thus, preventative measures are required to reduce lifetime risk of ovarian cancers and improve mortality rate.

This study is the first to examine whether the performance of credit rating, one of the most important data-based decision-making of banks, can be improved by using banking system log data that is extensively accumulated inside the bank for system operation. This study uses the log data recorded for the mobile app system of Kakaobank, a leading internet bank used by more than 14 million people in Korea. After generating candidate variables from Kakaobank's vast log data, we develop a credit scoring model by utilizing variables with high information values. Consequently, the discrimination power of the new model compared to the credit bureau grades was significantly improved by 1.84% points based on the Kolmogorov–Smirnov statistics. Therefore, the results of this study imply that if a bank utilizes its log data that have already been extensively accumulated inside the bank, decision-making systems, including credit scoring, can be efficiently improved at a low cost.

This paper presents the results of quantitative research regarding the predictive model of citizens' attitudes about the risks of introducing the death penalty in the Republic of Serbia legal system. The research was conducted with the use of a questionnaire that was requested and then collected online from 427 people in June 2021. A multivariate regression analysis was used, identifying the extent to total scores of the main dependent variables (introducing the death penalty; trust in the legal system; advantages of introduction; disadvantages of introduction scores) were associated with five demographic and socio-economic variables: gender, marital, education, income, and age. We tested the central hypothesis of which gender is predicting variables citizens' attitudes about the risks of introducing the death penalty in the legal system of Serbia. The findings revealed that gender and educational level were the most effective predictors of the research variables under question. The majority of respondents support the introduction of the death penalty and the most important predictor of disadvantages of introducing the death penalty in the legal system is age. Based on the findings that there are major differences in the citizens' attitudes about the risks of introducing the death penalty in the legal system, policies, strategies, and regulations must take into account these very important findings.

Several treatment guidelines for sporadic, nonmetastatic nonfunctioning neuroendocrine tumors of the pancreas (NF-pNETs) have recommended resection, however, tumors ≤ 2 cm do not necessarily need surgery. This study aimed to establish a surgical treatment plan for NF-pNETs ≤ 2 cm. From 2000 to 2017, 483 patients who underwent resection for NF-pNETs ≤ 2cm in 18 institutions from Korea and China were enrolled and their medical records were reviewed. Median age was 56 (range 16- 80) years. The 10-year overall survival rate (10Y-OS) and recurrence-free survival rate (10Y-RFS) were 89.8 and 93.1%, respectively. In multivariable analysis, tumor size (> 1.5cm; p = 0.001) and nodal metastasis (p = 0.013) were independent adverse prognostic factors for OS. Perineural invasion (p = 0.008) and high Ki-67 index (≥3%; p < 0.001) were independent prognostic factors for poor RFS. NF-pNETs ≤ 2 cm showed unfavorable prognosis after resection when the tumor was larger than 1.5cm, Ki-67 index ≥ 3%, or nodal metastasis was present. NF-pNET patients with tumors ≤ 1.5cm can be observed if the preoperative Ki-67 index is under 3%, and if nodal metastasis is not suspected in preoperative radiologic studies. These findings support the clinical use to make decision about small NF-pNETs.

The use of multi-gene panels for germline testing in breast cancer enables the estimation of cancer risk and guides risk-reducing management options for tested individuals and their family members. We performed an analysis in our clinical database to identify breast cancer patients undergoing genetic testing with positive reports. We reviewed positive results with respect to the different levels of information provided in the reports; risk estimation and management, cascade family testing, information from secondary findings and actionable information for treatment decision-making. A total of 415 positive test reports were identified with 57.1%, 18.1%, 10.8% and 13.5% of individuals having pathogenic/likely pathogenic variants in high (BRCA1, BRCA2, PALB2, PTEN, TP53), moderate (ATM, CHEK2, NBN), low (BARD1, BRIP1, CHEK2, MLH1, MSH2, MSH6, NF1, RAD51C) and with insufficient evidence for breast cancer risk genes (FANCA, FANCM, NBN, MRE11, PMS2, RAD50, RAD51B, XRCC2, MUTYH), respectively. 6.7% of individuals were double heterozygotes with two pathogenic variants. Germline findings in 92% of individuals are linked to evidence-based treatment information and receive risk estimates for predisposition to breast and/or other cancer types. The use of germline findings for treatment decision making expands the indication of genetic testing to include individuals that could benefit from targeted treatments.

Adversarial Classification (AC) is a major subfield within the increasingly important domain of adversarial machine learning (AML). Most approaches to AC so far have followed a classical game-theoretic framework. This requires unrealistic common knowledge conditions untenable in the security settings typical of the AML realm. After reviewing such approaches, we present alternative perspectives on AC based on Adversarial Risk Analysis.

Background:Peripheral neuropathy (PN) can result in either partial or complete loss of distal sensation resulting in an increased fall risk. Walkasins^® uses a shoe insert to detect the magnitude and direction of sway and sends signals to a leg unit that provides sensory balance cues. The objective of this case report is to describe the long-term influence of the Walkasins^® lower limb sensory neuroprosthesis on balance and gait for an individual with diabetic PN.Case Description:A fifty-one-year-old male with a 3-year history of PN and a 10-year history of type II diabetes mellitus was fitted with Walkasins^® and utilized the shoe inserts 8-10 hours/day for more than 1 year. Although, vibration and tactile thresholds were severely impaired at his 1^st metatarsophalangeal joint and the lateral malleolus bilaterally he could perceive tactile stimuli from the Walkasins^® above the ankles.Outcomes:Following Walkasins^® use, his Activities-specific Balance Confidence Scale (ABC) scores improved from 33% to 80%. His mean Vestibular Activities of Daily Living (VADL) scores decreased from 3.54 to 1. His Functional Gait Assessment (FGA) scores increased from 13/30 to 28/30 and his miniBESTest scores improved from 15/28 to 26/28. Gait speed increased from 0.23 m/sec to 1.5 m/sec. The patient described a decrease in pain and cramping throughout his lower extremities and an increase in function.Discussion:Gait and balance improved with the use of the Walkasins^® and participation in the Neuro Wellness Program. This improvement suggests that the use of sensory substitution devices, such as the Walkasins^®, may replace sensory deficits related to gait and balance dysfunction experienced by patients with PN. Further research is needed to determine if other patients will have a similar response and what the necessary threshold of sensory function is to benefit from use of the Walkasins^®.

Nowadays tourism is growing as a gigantic, global business accounting for 10.4 % of Global GDP and 10% of global employment (Joppe, 2020). This review paper aims to explore the risks borne for tourism sector by the outbreak of corona-virus in 2020. Tourism sector is a highly vulnerable sector and the costs that will be borne from corona-virus pandemic will be devastating, particularly for the countries relying on this sector as a basic source of income. The paper suggests possible solutions and adaptation routes, while at the same time reviews lessons of the past from other pandemics and crisis. This paper is very useful for tourism policy makers and governments in countries where tourism contributes a significant part of their GDP, but also for other economic sectors closely but indirectly connected in the tourism value chain.

This review aimed to update the main aspects of aflatoxin production, occurrence and incidence in selected countries, and associated aflatoxicosis outbreaks. Means to reduce aflatoxin incidence in crops were also presented with an emphasis on the environment-friendly technology using atoxigenic strains of Aspergillus flavus. Aflatoxins are unavoidable widespread natural contaminants of foods and feeds with serious impact on health, agricultural and livestock productivity, and food safety. They are secondary metabolites produced by Aspergillus species distributed on three main sections of the genus (section Flavi, section Ochraceorosei, and section Nidulantes). Poor economic status of a country exacerbates the risk and the extent of crop contamination due to faulty storage conditions that are usually suitable for mold growth and mycotoxin production: temperature of 22 to 29°C and water activity of 0.90 to 0.99. This situation paralleled the prevalence of high liver cancer and the occasional acute aflatoxicosis episodes that have been associated with these regions. Risk assessment studies revealed that Southeast Asian and Sub-Saharan African countries remain at high risk and that, apart from the regulatory standards revision to be more restrictive, other actions to prevent or decontaminate crops are to be taken for adequate public health protection. Indeed, a review of publications on the incidence of aflatoxins in selected foods and feeds from countries whose crops are classically known for their highest contamination with aflatoxins, reveals that despite the intensive efforts made to reduce such an incidence, there has been no clear tendency, with the possible exception of South Africa, towards sustained improvements. Nonetheless, a global risk assessment of the new situation regarding crop contamination with aflatoxins by international organizations with the required expertise is suggested to appraise where we stand presently.

Downpours are increasing in frequency and severity due to climate change. Cities are particularly susceptible to downpours because of their large share of impervious surfaces. Minimising pluvial flood risk requires all involved stakeholders to collaborate and overcome probable barriers. Simultaneously, an increase in citizen engagement in climate adaptation is preferred, whereas experiences with inclusive decision-making are still limited. The aim of this paper is to obtain a deeper understanding of how the capacity to govern pluvial flood risk can be developed through citizen engagement. We scrutinised the capacity of local actors to govern pluvial flood risk in the city of Utrecht, the Netherlands. For the analysis of Utrecht’s problem-solving capacity, the Governance Capacity Framework provided a consistent assessment of governance components. The results indicate that Utrecht’s capacity to govern pluvial flooding is relatively well-developed. Collaboration between public authorities is advanced, sufficient financial resources are available and smart monitoring enables high levels of evaluation and learning. However, citizen awareness and engagement in policy making is rather low. Accordingly, citizens’ willingness to pay for flood adaptation is limited. Stimulating flood risk awareness by combining financial incentives with more advanced arrangements for active citizen engagement is key for Utrecht and other cities.

Improving the efficiency of the supply process in prefabricated components is challenging and requires accounting for a variety of risks involved in the management of the suppliers. The purpose of this study is to present a method to account for the systematic trade-offs between several supplier alternatives. A novel framework is presented for the whole assessment of supplier alternatives by taking advantage of the information extracted from customized building information modeling (BIM) and a database required for assessment of impacts. A data library related to assessment criteria for supply alternatives is built to facilitate the storage and sharing of information. Analytic hierarchy process (AHP) is used to select the optimal supplier that is able to provide the most satisfaction for the determined criteria. The proposed framework was also illustrated by the implementation in a mega project. The study implication is that BIM-enabled supplier selection can indeed lead to more benefits and higher values for all stakeholders.

Background: Whilst lack of concentration is a known symptom of anaemia, its association with post-stroke dementia is unclear. Methods: We used data from a UK regional stroke register. To be eligible, patient must have survived to discharge and had anaemia by WHO criteria. Dementia status and other prevalent co-morbidities were assessed using ICD-10 codes. Patients were followed till May 2015 (mean follow-up 3.7 years, total person years = 27,769). Hazard Ratio for incident dementia was calculated using Cox-proportional hazards model controlling for potential confounders. Fine and Gray model was additionally constructed using mortality as the competing risk. Results: A total of 7,454 stroke patients were included with mean age (SD) of 75.9(12.3) years (50.2% men). Those with anaemia were older, has higher disability and co-morbidity burden prior to stroke. We observed a large amount of variation in the dementia incidence rates over time and that the hazard ratio increased every year. The significant association between anaemia and dementia incidence was lost after controlling for pre-stroke Modified Rankin score (HR1.17(0.97,1.40)). With every 20g/dL increase in Hb was associated with a significant reduction in the risk of dementia after adjustment for age, sex, stroke factors and disability but lost significance after adjustment for vascular risk factors. Competing risk analyses showed similar results. Conclusion: Whilst we found no evidence of anaemia as a risk factor for post-stroke dementia, the findings may be limited by potential under recognition of post stroke dementia.

In mega cities such as Seoul in South Korea, it is very important to protect the city from the flooding even for the short time of period due to the enormous amount of economic damage. In impervious area of the city, stormwater pipe network is commonly applied to discharge rainfall to the outside of catchment. Therefore, the stormwater pipe network in urban catchment should be carefully designed to discharge the runoff quickly and efficiently. In this study, different types of structures in stormwater pipe network were evaluated using the relationship between the peaks rainfall and runoff in urban catchments in South Korea. More than 400 historical rainfall events were applied in five urban catchments to estimate peak runoff from different type of network structures. Linear regression analysis was implemented to estimate peak runoffs. The coefficient of determination of the regressions were higher than 0.9 which means the regression model represent very well the relationship between the two peaks. However, the variation of the prediction becomes large as the peak rainfall increases and the variation become even larger when the network structure is branched. Therefore, it depends on the structure of stormwater pipe network. When the water paths in the pipe network is unique (branched network), the increased amount of rainfall is congested around the rainwater inlets and the uncertainty of peak runoff prediction is increased. If there are many possible water paths depending on the amount of discharge (looped network), the increased rainfall is discharged more quickly through the many water paths. This can be a way to represent the reliability of the stormwater pipe network. The structures of stormwater pipe network is evaluated using drainage density which is the length of pipes over the unit catchment area and 95% confidence interval. As a result, the 95% confidence interval is increased as the drainage density is increased because the accuracy of peak runoff prediction is decreased. As mentioned earlier, because the looped networks have many alternative water flowing paths, elimination time of rainfall from the catchments become short, the 95% confidence interval become narrow, and the reliability of peak runoff prediction become high. Therefore, it is beneficial to install looped stormwater pipe network within the affordable budget. It is important factor to determine the amount of complexity in stormwater pipe network to decrease the risk of urban flooding.

This paper relies on accounting-based measures of country risk to investigate U.S. global banks' exposure to foreign country risk over the 2017 fiscal year as measured by the sum of cross-border risk, foreign office risk, and derivative risk claims. We achieve this using panel linear modeling methods with country level heterogeneity and time fixed effects, along with a constructed panel data of 284 observations on 71 countries distributed across 6 world regional blocks, and observed over 4 consecutive quarters starting from 4th quarter 2016 and ending with 3rd quarter 2017. The results show that on average, over the four quarters, a 1% increase in foreign banking sector's claims significantly increases U.S. global banks cross border risk exposure by 0.34%, while reducing derivative risk exposure by 0.22%, but have no significant impact on foreign office risk exposure. Similar results are observed with public sector claims which significantly increase banks' exposure to cross border risk by 0.21%, while reducing derivative risk exposure by 0.19%. Conversely however, non-bank financial sector claims are found to have no significant affect on cross-border risk exposure, but significantly reduce foreign office risk exposure by 0.09%, while increasing derivative risk exposure by 0.06%. These results indicate the presence of sectoral heterogeneities in U.S. banks' exposure to foreign counterparties' risk, and also that overall, over the course of 2017 the level of U.S. global banks' cross-border risk exposure increased, while their level of derivative risk exposure decreased, and the level of foreign office risk exposure remained relatively unchanged.

In this study, we attempted to verify the hypothesis that total metals bound to dust of different particle sizes may reflect pollution levels, but cannot predict its bioavailability and risks in human health assessments. Dust samples were collected using active sampling method; during the dry season months of November, 2014 to March, 2015 at different locations in Akure (7˚10ʹN and 5˚15ʹE). The samples were sorted into different particle sizes (< 10µm, 10 – 50 µm, >50µm), analyzed for some physicochemical properties and assessed for metals bioavailability using two-step physiological extraction method. The amount of metals (Cd, Cu, Cr, Ni, Pb, Zn and Mn) released in each particle sizes were determined using Perkin-Elmer 6000 Inductively Coupled Plasma - Atomic Emission Spectrometry (ICP-AES) analysis. The results showed that bioavailability of some metals (Cd, Ni, Pb, and Zn) decreases with increasing particle sizes, however, the reverse trend was observed for Mn, Cu and Fe concentrations. This may be attributed to some combination of physicochemical characteristics of the dust and metal speciation. Hence, it was concluded that metal bioaccessibility in dust can best be described by the knowledge of physicochemical characteristics. The exposure dose of the metals showed that cancer risks due to inhalation were very high when compared to other exposure routes (ingestion and dermal contact). The calculated non-cancer (HQ) and cancer risk (HI) for humans in the area showed values higher than unity, indicating possibility of the metals’ body burden.

Regulators require financial institutions to estimate counterparty default risks from liquid CDS quotes for the valuation and risk management of OTC derivatives. However, the vast majority of counterparties do not have liquid CDS quotes and need proxy CDS rates. Existing methods cannot account for counterparty-specific default risks; we propose to construct proxy CDS rates by associating to illiquid counterparty liquid CDS Proxy based on Machine Learning Techniques. After testing 156 classifiers from 8 most popular classifier families, we found that some classifiers achieve highly satisfactory accuracy rates. Furthermore, we have rank-ordered the performances and investigated performance variations amongst and within the 8 classifier families. This paper is, to the best of our knowledge, the first systematic study of CDS Proxy construction by Machine Learning techniques, and the first systematic classifier comparison study based entirely on financial market data. Its findings both confirm and contrast existing classifier performance literature. Given the typically highly correlated nature of financial data, we investigated the impact of correlation on classifier performance. The techniques used in this paper should be of interest for financial institutions seeking a CDS Proxy method, and can serve for proxy construction for other financial variables. Some directions for future research are indicated.

The world is currently experiencing the fourth industrial revolution driven by the newest wave of digitisation in the manufacturing sector. The term Industry 4.0 (I4.0) represents at the same time: a paradigm shift in industrial production, a generic designation for sets of strategic initiatives to boost national industries, a technical term to relate to new emerging business assets, processes and services, and a brand to mark a very particular historical and social period. I4.0 is also referred to as Industrie 4.0 the New Industrial France, the Industrial Internet, the Fourth Industrial Revolution and the digital economy. These terms are used interchangeably in this text. The aim of this article is to discuss major developments in this space in relation to the integration of new developments of IoT and cyber physical systems in the digital economy, to better understand cyber risks and economic value and risk impact. The objective of the paper is to map the current evolution and its associated cyber risks for the digital economy sector and to discuss the future developments in the Industrial Internet of Things and Industry 4.0.

Insurance companies have a risk of bankruptcy if the funds disbursed exceed the reserves owned, or the surplus is negative. The risk of bankruptcy can be predicted using a mathematical model to anticipate the possibility of bankruptcy early on, so the surplus process needs to be observed in its evolution over time, assumed to be discrete time because it refers to the budget year period. The surplus process model is generally determined by three components, namely company capital, total premiums, and total claims. The sharia insurance scheme separates the management of the company's capital account from the premium and claim fund accounts, making it easier to monitor the evolution of its surplus process. This study systematically reviews the surplus process model for the sharia insurance scheme. The systematic review method is carried out by collecting scientific papers published in the Scopus, ScienceDirect, Dimensions, and Google Scholar databases. The PRISMA flowchart selects and then produces three scientific papers that are relevant to the topic. The results of this study provide insight into the form of the surplus process model and four sharia insurance schemes, namely mudharabah, wakalah, hybrid, and waqf. However, the scheme introduced is still a general description, there is no scheme based on needs or social problems in society such as the integration of productive waqf with welfare benefits for groups in need such as fishermen. This research was conducted towards the transition towards sustainable development of sharia insurance.

Coastal ecosystems are crucial in mitigating the impact of coastal hazards on society. However, the paucity of infor-mation about the purpose of these ecosystems in reducing floods in Rivers State, Nigeria. This study aims to assess the contribution of mangrove ecosystems in protecting coastal communities from flooding using the InVEST coastal vulnera-bility model (version 3.10.2). The model analyzes various data inputs and assigns relative numbers, ranging from 1 to 5, indicating different levels of exposure. Data on population, bathymetry, shoreline type, land use land cover, and conti-nental shelf were obtained from relevant websites and the InVEST model package. The findings indicate that the mangrove ecosystems in River State offer minimal protection against coastal flooding due to their degraded state caused by oil spills and over-exploitation. Additionally, sandy beaches provide little to no protection, and the socio-economic conditions in the communities contribute to increased vulnerability to flooding. The study recommends awareness programs to educate the public about the importance of mangroves for coastal protection in addition to their conservation and restoration.

The evolution and acceleration of the effects of climate change on the water cycle demand adaptation and mitigation plans. Consequently, the implementation of public policies (management, governance, and strategy) regarding flood risk management or prevention (such as levee heights and spillway dimensions of dams) is based on the characterization of flood hazards. This requires understanding extreme climate phenomena and conducting a rigorous probabilistic analysis of hydrometric data. This study aims to estimate the flood quantiles for lake Nokoue. To achieve this, the adopted methodology involved fitting the Generalized Extreme Value (GEV) distribution, the Gumbel distribution, and the Generalized Pareto (GPA) distribution to the annual maximum water levels of lake Nokoue from 2015 to 2022. We estimated experimental probabilities using the Weibull formula. The assessment of the fit quality of the theoretical probability distributions to our data sample indicated that the Gumbel distribution was the most suitable, with a root mean square error (RMSE) of 0.0724, compared to 0.0754 and 0.0761 for the GEV and GPA distributions, respectively. The position and scale parameters (φ; α) of the Gumbel distribution were estimated to be 3.802 and 0.249, respectively. This allows for the calculation of the probability of an extreme water level occurring within a return period in a single day. Thus, the extreme water levels (flood quantiles) associated with return periods of 10, 50, and 100 years, as determined by the Gumbel distribution, are 4.36m, 4.77m, and 4.95m, respectively. These values are of crucial importance for the design of flood prevention structures (infrastructure) intended to mitigate flood risk.

Coastal ecosystems are crucial in mitigating the impact of coastal hazards on society. However, the paucity of information about the purpose of these ecosystems in reducing floods in Rivers State, Nigeria. This study aims to assess the contribution of mangrove ecosystems in protecting coastal communities from flooding using the InVEST coastal vulnerability model (version 3.10.2). The model analyzes various data inputs and assigns relative numbers, ranging from 1 to 5, indicating different levels of exposure. Data on population, bathymetry, shoreline type, land use land cover, and continental shelf were obtained from relevant websites and the InVEST model package. The findings indicate that the mangrove ecosystems in River State offer minimal protection against coastal flooding due to their degraded state caused by oil spills and over-exploitation. Additionally, sandy beaches provide little to no protection, and the socio-economic conditions in the communities contribute to increased vulnerability to flooding. The study recommends awareness programs to educate the public about the importance of mangroves for coastal protection in addition to their conservation and restoration.

Background: The early identification of patients at risk of peri-procedural complications and poor prognosis is very important. We conducted our study to determine if there are associations between serum orexigenic neuropeptide Y (NPY) concentration and nutritional status, and prognosis among patients undergoing surgery for colorectal cancer (CRC). Materials and Methods: A cohort study with a 3-month follow-up was conducted with 84 consecutive inpatients who underwent elective surgery in one center between 2016 and 2019 for primary CRC. In all patients, clinical characteristics and nutritional status were assessed. In a long-term follow-up (median; IQR: 1322; 930-1788 days; average 3.6 years), the patients’ survival status was checked during a telephone visit. Results: Before CRC surgery, patients with serum NPY concentration equal to or higher than the median value (661.70 pg/ml) had, in comparison to individuals with lower blood NPY concentration, higher scores in Mini Nutritional Assessment, Barthel, and Instrumental Activities of Daily Living (IADL) questionnaires, greater handgrip strength, a lower score in the Patient-Generated Subjective Global Assessment, almost a three times lower risk of perioperative complications, as well as, at the 3-month follow-up visit, higher Barthel and IADL scores and larger calf circumference. Higher blood NPY concentration was predictive of a low Nutritional Risk Screening 2002 score at the 3-month visit, and significantly influenced patients’ survival during the 1200 days after CRC surgery. Conclusions: Higher blood NPY concentration was associated with lower nutritional risk, more favorable patient nutritional and functional status, and better survival during the 1200 days after CRC surgery.

A new maritime order is emerging – the blue economy – characterised by a plethora of non-traditional security threats. Using the case of the Western Indian Ocean I demonstrate how the creation of spaces of risk in response to traditional security threats by world powers has led to a new, regionally-led governance regime in response to the new maritime order. International efforts to protect shipping lanes from the threat of piracy off the coast of Somalia have evolved into wider environmental and human security measures. I analyse these changes through the lens of governmentality and argue that this case represents an example of a global governmentality in which states are responsibilised to act collaboratively by the international community through discourses of risk. Regional States have turned this to their advantage, acting together to construct and secure a new development frontier - a shared blue economy space in an extensive and difficult-to-govern territory.

In a systematic explorative study of genetic patterns on chromosome 19, we discovered a pattern comprised of 23 SNP alleles that is significantly associated with late-onset Alzheimer’s disease (AD). This association is validated using two independent data sets. The pattern includes THOP1, which has a long and disputatious relationship with AD. It also spans SLC39A3 and SGTA and is upstream from DIRAS1. We utilized population data to observe the frequencies of this genetic pattern for 11 different ancestries and note that it is highly common for Europeans and relatively infrequent for Africans. This research provides a distinct genetic signature for AD risk as well as insights into the complicated relationship between this disease and THOP1.

(1) Background: Hepatoblastoma is the most common primary liver cancer in children. Nowadays, poor outcome occurs essentially for patients with distant metastases; (2) Methods: Starting from Mammalian Metabolic Enzyme Database over expression of metabolic enzymes was searched in hepatoblastoma tumors as compared to noncancerous liver tissue in transcriptome dataset GSE131329. With overexpressed enzymes, Elasticnet machine learning tuning was performed according to metastasis status outcome. With significant enzymes a metabolic expression score was computed and integrated in multivariate clinical-biological logistic model; (3) Results: Forty-one overexpressed enzymes discriminate hepatoblastoma tumors and noncancerous liver tissues. Eighteen of them predict metastasis status (AUC 0.90) with 85.7% of sensibility and 92.3% of specificity. Elasticnet machine learning model tuning highlighted major importance of DNMT3B and PFKFB4 expression to predict metastasis. Role of these two enzymes was confirmed by univariate analyses with respective p-values: 0.0058 and 0.0091. Metabolic score computed with combined expression of DNMT3B and PFKFB4 discriminates metastasis status and high-risk CHIC score by univariate analysis (p-value=0.005). Meta.score was found more sensitive than C1/C2 classifier to predict metastasis status (accuracy: 0.72 versus 0.55). Integration of meta.score (DNMT3B, PFKFB4) with epidemiological parameters: gender, age at diagnosis, histological types, and clinical PRETEXT stages in a multivariate model confirmed independent adverse role of meta.score to predict metastasis status (multivariate p-value=0.003, odds ratio: 2.12); (4) Conclusions: Based on metabolic enzyme expression program of hepatoblastoma, we characterized a dual overexpression of PFKFB4 and DNMT3B in samples of patients at risk of metastasis (High risk CHIC stratification). With combined tumor expression of DNMT3B and PFKFB4 a meta.score was computed and this parameter was confirmed as an independent adverse score to predict metastatic status during hepatoblastoma.

Brucellosis is a zoonoses caused by bacteria of the genus Brucella, which causes economic losses in livestock and threatens public health. A cross-sectional study was conducted to determine the prevalence of Brucella species and risk factors in smallholder dairy cattle in six regions of Tanzania from July 2019 to October 2020. Dairy cattle (n=2048) were sampled from 1371 farms. DNA ex-tracted from blood and vaginal swabs was tested for Brucella using qPCR targeting the IS711 gene and positives were tested for the alkB marker for B. abortus and BMEI1172 marker for B. melitensis. The molecular prevalence was 3.5% (95% CI: 2.8-4.4) with the highest prevalence 8.1% (95%CI: 4.6-13.0) in Njombe region. B. melitensis was the predominant species detected (66.2%). Logistic regression revealed PCR positivity in dairy cattle was higher in the animals with a history of abortion (OR: 3.17, 95%CI: 1.05-9.62) and farms without dogs around (OR: 2.68, 95%CI: 1.12-5.90). Further studies are recommended to understand the source of B. melitensis and the implications to veterinary public health. Livestock keepers should be informed of the risks and biosecurity practices to reduce introduction and control Brucella. Cattle and small ruminant vaccination pro-grams could be implemented to control brucellosis in high-risk populations in the country.

In the context of sustainable development, integrating the work aspect into health promotion systems is essential, ensuring that employees maintain a healthy balance between their professional and personal lives, which respects and amplifies the potential of every individual. Lately, there has been a noticeable shift of medical professionals from the public to the private sector. This trend paints a bleak picture, highlighting the vulnerabilities of a system teetering on the brink of failure, with significant impacts on patient care. Among the myriad reasons behind this shift, burnout stands out prominently. Medical professionals face increasing pressures due to understaffing, limited organizational support, and insufficient resources, leading to feelings of cynicism, exhaustion, and detachment from their roles. Utilizing the Maslach et al. questionnaire, we assessed the risk of burnout among physicians in public hospitals to identify and underscore preventive measures and improvements, correlating our findings with key aspects of organizational empowerment. Our research indicates that enhancing interpersonal relationships and resources—both within teams and between the organization and its physicians—is crucial for the revival of the healthcare system. This approach aims at improving the delivery of healthcare services and offering appropriate recognition to healthcare professionals, aligning with the principles of sustainable employment.

In the European Union, Occupational Safety and Health legislation generally refers to European Regulation (CE) n. 1272/2008 to define and classify carcinogens of concern for occupational risk assessment and exposure assessment. In Europe, the current reference is Directive (UE) 2022/431, regarding carcinogen, mutagen and reprotoxic agents (CMRs) exposure. However, at worldwide level, different classification approaches are used to establish carcinogenicity of substances and it is often difficult to compare the classifications of carcinogenicity (CoCs) proposed by different international bodies. This study aims to investigate a list of carcinogens of concern in occupational settings based on the CLP (Classification Labelling Packaging) CoC, and to create a tool that allows a rapid translation-comparison of some international CoCs with the reference one. CoCs proposed by various sources were consulted and used to apply a translation method, to favor an alignment of different CoCs according to a reference. Results outlined that considering diverse sources, CoCs can result in different classifications of the same chemicals. Overall, this may have implications for the hazard assessment process, which is the base of risk assessment. The proposed tool is expected to help risk assessors in the occupational field when it is needed to have a comparison with different CoC systems.

Climate change is unpredictable and can change rapidly or over time; anthropogenic stressors work synergistically to strengthen their impact on vulnerable ecosystems and the fisheries sector. This study documented the past occurrence of extreme climate change impacts, such as supertyphoon Pablo (ST: Bopha), which severely affected Baganga, Davao Oriental, about ten years ago. A mixed-methods data collection was used, combining semi-structured interviews with small-scale fishers (N=120) in four fishing villages and focus group discussions (N=4, participated by about 4 focus groups) on assessing the impacts and their adaptation after climatic events occurred. Our findings indicate that the four selected fishing villages were exposed to common factors of climate change events that destroyed many lives and their livelihood. Including a decrease in catch per trip and the fishing operations disruption (98%). However, due to the impact of the supertyphoon, small-scale fishers in Baganga developed psychological distress (emotional 44% and physical 24%) due to the extreme event or disaster and economic losses (32%). In order to survive, their adaptation strategies relied on government and non-government-provided provisions and projects, e.g., planting trees, constructing a sea wall with wave breakers, cash for work, and tourism as an alternative livelihood. Despite this, our study revealed that the community had limited knowledge on the impacts of climate change, lack clear management goals especially for fishers, and the widespread use of illegal fishing gears. The local government must strongly implement rules, policies, and adaptation measures that will contribute to better and more resilient communities. This can help them to withstand future shocks and provide sustainable fisheries resources that will benefit all the fishers. The study will be useful to policymakers, disaster management group and organization that will help assist affected communities highly affected by climatic events.

This literature review was aimed to identifying the opportunistic bacterial pathogens that can be transmitted by contaminated food and represent a current threat for patients particularly suscep-tible to infections because of underlying conditions or predisposing factors. The analysis was focused on recent case or outbreak reports, and systematic reviews published in years 2019 - 2023 and resulted in sorting 24 bacterial groups comprising genera or species able to cause a variety of systemic or invasive infections if ingested with food or drinking water. These included both bacteria known to cause mild infections in immunocompetent persons and bacteria considered innocuous that are used in food fermentation or as probiotics. No recent cases from dietary routes were reported for bacteria of critical importance as nosocomial pathogens and widely occurring in food products, primarily, Acinetobacter baumanii and Klebsiella pneumoniae. However, the very first sources of their introduction in the clinical environment still need to be estab-lished. In many instances, risky dietary habits such as eating raw fish, seafood, raw meat, unpasteurized milk and derived products or the lack of control on fermentation processes led to the reported illnesses, pointing out to the necessity to improve the hygiene of production and consumer’s awareness of risks.

Lumpy skin disease (LSD) vaccination and epidemiological distribution remain unknown in some parts of Ethiopia including the Sidama regional state. With this, an assessment of LSD vaccine-related problems and serological study was performed in selected districts of Sidama regional state representing three agroecological zones from September 2021 to June 2022. A cross-sectional study of qualitative and quantitative studies was used. The result showed a few portion of respondents know about LSD (29.2%), and vaccinate their cattle (23.3%). 20.8% of the respondents stated LSD occurrence in their vaccinated cattle while focus group discussion with the professionals stated the possible reasons related to electric power disruption that impacted LSD vaccine cold-chain. The other study was on sero-epedimiology of LSD which showed an overall animal and herd level sero-prevalence of 40.8% and 81%, respectively. Higher and lower sero-prevalence was observed in lowland (48%) and highland (28%) areas, respectively. Furthermore, risk factor analysis showed the existence of a significant association between management systems, breed, and body condition score (BCS) of cattle. In conclusion, both qualitative and quantitative study results showed the need for intervention in terms of community-based awareness creation about LSD clinical signs, vaccination advantages, and options for electric power supply together with the frequently updated information on LSD prevalence.

Modelling and presenting mathematical relationships for human behaviour is one of the most complex issues that researchers have always dealt with. In this article, a bottom-up framework for calculating agricultural needs is presented using the socioeconomic characteristics of farmers (such as education level, age, and dependence on income on agriculture) and how their lands are located concerning each other (interactions between neighbours). The objective function of this framework is to maximize the profit of individual farmers based on the amount of water received. Two scenarios, ABM1 (not considering neighbourhood effects) and ABM2 (all cases of farmers' placement and feeling neighbourhood effects), were investigated. In the first scenario (ABM1), there was a noteworthy reduction in water deficit volumes by approximately 35%, accompanied by a 20% increment in farmers' profits. Interestingly, higher risk-taking tendencies correlated with reduced profit margins. The second scenario (ABM2) underscored the significant role of neighborhood dynamics in cultivating diverse behavioral patterns among farmers, subsequently affecting their profitability. A granular examination revealed that farmers with a higher propensity for risk-taking generally accrued lower profits. Additionally, the study facilitated the calculation of total annual profits and average water consumption for each farmer, offering valuable insights for optimizing water resource management and allocation strategies. These findings are instrumental for planners and water resource managers aiming to promote sustainable agricultural practices and efficient water use.

The spatial and temporal changes in social vulnerability to natural hazards in Mexico are analyzed. To this end, using census data from 2000, 2010, and 2020 and a statistical method, different indices were computed, and with a GIS-based approach, patterns of social vulnerability are examined. In addition, a risk assessment test for severe weather (thunderstorms, hailstorms, and tornadoes) is made out. The results show different common social vulnerability driving factors in the three analyzed years, with root causes that have not been addressed since the beginning of the century. Likewise, a wider gap between Mexico's most and least vulnerable populations is identified. The changes in spatial patterns respond to different historical situations, such as migration, urbanization, and increased population. Also, poverty, ethnicity, and marginalization factors located in very particular regions in Mexico have remained relatively the same in the last few years. These situations have strongly influenced the spatial-temporal distribution of vulnerability in the country. The role of social vulnerability in the disaster risk to extreme events such as thunderstorms, hailstorms, and tornadoes in Mexico is fundamental to understanding changes in disaster distribution at the national level, and it is the first step to generating improvements in integrated risk management.

Evidence shows how food system activities from production to consumption underpin food security. However, studies exploring climate impacts on food security in northern Ghana have overly focused on production systems, neglecting post-production activities that loom large in food security. This paper addresses the research need to comprehensively analyze how climate change affects post-production activities and exacerbates food insecurity risks in northern Ghana. The study collects and analyzes data on climate hazards, impacts, and food system vulnerabilities using questionnaires and participatory engagement with farming households in northern Ghana. Results show that climate-induced food insecurity risks in northern Ghana are not just products of persistent climate impacts on food production in the region. Instead, risks are inextricably connected to the vulnerability contexts within which food is harvested, processed, stored, and marketed. Specifically, the results reveal that climate hazard events such as floods, extreme temperatures, and droughts damage stored grain, disrupt food supply to the market, and cause seasonal volatilities in food prices. However, these impacts are not solely externally generated circumstances. The food system is highly vulnerable; most households lack access to threshing and grinding machines, warehouse storage, post-harvest management information, and transportation services. These underlying characteristics of the post-food-production system of northern Ghana, which is ultimately quite remote from climate change, exacerbate household-level food insecurity risks.

Zoonotic abortive diseases represent a significant health and economic risk for national public health. This cross-sectional survey was conducted from April to October 2021 among 200 selected small ruminant farmers in the three northern regions of Cameroon. Data collection was done through questionnaires administered by exchange with the herder and responses were coded and recorded on an Excel spreadsheet. The data were then analyzed with R software, version 2.13.0. An ANOVA test was used to assess significant differences in mean of Knowledge, Attitudes, Practices and Perception of zoonotic risks (KAPP) scores between regions. Pearson correlations were used to calculate the association between KAPP scores within regions. Small ruminant farmers surveyed had low mean scores for knowledge of abortive Toxoplasmosis and Chla-mydophilosis (0.1 ± 0.2), desirable attitude (0.32 ± 0.07), appropriate practice (0.36 ± 0.13) in managing abortion, and positive perception of zoonotic risks of Toxoplasmosis and Chlamydo-philosis in small ruminants (0.12 ± 0.33), respectively. KAPP was significantly (p<0.01) and posi-tively associated with knowledge (r=0.98) and risk perception (r=0.99). However, attitudes (r=0.06), practices (r=0.05) and risk perception of toxoplasmosis (r=0.07) and Chlamydophilosis (r=0.08) were not associated with farmers' knowledge. This study revealed significant knowledge gaps, low levels of desired attitudes, and high-risk behavioral practices. These results therefore call for capacity building of health professionals and farmers to better integrate the One Health concept in the management of neglected zoonotic diseases.

Cervical cancer is the most common female reproductive tract tumor and is currently the only cancer that can be prevented by vaccination. Early detection and treatment of cervical cancer can be achieved through regular screening for human papillomavirus (HPV). Therefore, in this paper, an electrochemical sensor was designed to detect HPV 16 using a dual signal amplification technique. APTES modified glassy carbon electrode to improve stability. Combining gold nanoparticles and chain amplification reactions for signal amplification purposes. The limit of detection (LOD) was 1.731×10-16 mol/L, and the detection range of this electrochemical sensor was increased in comparison to previous research, with a linear response range from 1.0×10-13 mol/L to 1.0×10-5 mol/L (R2 = 0.99232) for the target detector.In addition, the sensor showed equally good recovery in sophisticated human serum samples. It shows that it has good interference resistance and the designed biosensor can be a powerful and reliable tool for clinical disease diagnosis.

Arsenic (As) contamination of groundwater is a common problem in BDP. The alkaline pH of the groundwater provides favourable condition for geomicrobiochemical processes, where organic matter also plays an important role in mobilization of As. The total arsenic content (AsT) of the groundwater is in the range of 69-178 µgL-1 with mean value of 118.58 µgL-1. The groundwater quality of monitored drinking water wells are related to local land–use pattern and rural sanitation installation and practices (which can have a strong influence on microbial contamination). The study indicates that As heterogeneity, probably a consequence of microbial heterogeneity is a feature of the study area. The excessive total and fecal coliform (TC and FC) count of the ponds possibly suggest uncontrolled surface run offs and sewage leakage, notably from nearby pit-latrine, which increased the microbial contamination in these water sources. The tube wells located in close proximity (~ 2-3 m) of the surveyed ponds are also contaminated with high TC and FC values, due to faulty water supply system, pond water infiltration and cracked tube well platforms. Coliforms may influence geomicrobiological processes in groundwater and thereby, contribute in As release and mobilization. The TC and FC values of monitored tube wells and ponds show seasonal variation, with high TC and FC values during wet season. Attempt has been made to focus on sanitation risk of the monitored wells (based on sanitation and fecal coliform scores) which is usually less explored. The sanitary risk score reveal the need of immediate attention to all the sites, as 25.0 %, 58.3 %, 11.1 % and 5 % of tube wells of the six sites fell under very high risk (sanitary risk score ≥ 9), high risk (sanitary risk score 6-8), intermediate risk (sanitary risk score 3-5) and low risk category (sanitary risk score 0-2), respectively. Fecal coliform score classified all the sites under intermediate risk category (FC count 10-100 per 100 ml of water). The predominance of As heterogeneity particularly in areas under high risk category (showing high TC and FC contamination) is observed along with the similar sinusoidal pattern of TC, FC and AsT content. Finally, this study shed light on the factors responsible for unsafe nature of monitored tube wells and the influence of anthropogenic activities on the microenvironment of the groundwater, which could be a probable reason behind the As heterogeneity in the groundwater of the study area.

Background: The prevalence of physical inactivity has been rising in many countries in recent years, adding to the burden of non-communicable diseases and affecting overall health worldwide. The aim of this study is to determine the impact of physical activity on mortality from ischemic heart disease (IHD) separately for those respondents who were diagnosed with IHD and for those who were not diagnosed with IHD in their baseline health survey. Methods: In the baseline survey (2006–2008), 7100 men and women ages 45–72 were examined within the framework of the international study Health, Alcohol, and Psychosocial Factors in Eastern Europe (HAPIEE). 6770 participants were available for statistical analysis (after excluding 330 respondents due to missing information on study variables). Physical activity was determined by leisure-time physical activities (hours/week). All participants in the baseline survey were followed up for IHD mortality events until December 31, 2018. Results: Using multivariate Cox regression analysis, it was found that moderate and higher levels of physical activity significantly reduced the risk of IHD mortality (HR=0.54 and HR=0.60 respectively) in men who were not diagnosed with IHD at baseline compared with physically inactive subjects. It was found that among men and women who were diagnosed with IHD at baseline, physical activity reduced the risk of mortality from IHD compared with those who were physically inactive (HR=0.54 and HR=0.41 respectively). Using mediation analysis, was found that physical activity directly predicted statistically lower IHD mortality (P&lt;0.05) in men and women. Conclusion: Physical activity was a significant factor that directly predicted statistically lower IHD mortality, regardless of whether subjects had IHD at baseline or not.

: Border management serves as a crucial control checkpoint for governments to regulate the quality and safety of imported food. In 2020, the ensemble learning prediction model EL V.1 was introduced to Taiwan's border food management. This model primarily assesses the risk of imported food by combining five algorithms to determine whether quality sampling should be performed on imported food at the border. In this study, a second-generation ensemble learning prediction model, EL V.2, was developed based on seven algorithms to enhance the "detection rate of unqualified cases" and improve the robustness of the model. The chi-square test was employed to compare the efficacy of "pre-launch (2019) random sampling inspection" and "post-launch (2020–2022) model prediction sampling inspection". For cases recommended for inspection by the ensemble learning model and subsequently inspected, the unqualified rates were 5.10%, 6.36%, and 4.39% in 2020, 2021, and 2022, respectively, which were significantly higher (p=0.000***) compared with the random sampling rate of 2.09% in 2019. The prediction indices established by the confusion matrix were used to further evaluate the prediction effects of EL V.1 and EL V.2, and the EL V.2 model exhibited superior predictive performance compared with EL V.1, and both models outperformed random sampling.

Practitioners who assess the risk associated with urban trees often factor in the presence or absence of visual tree defects when determining whether a tree may fail. While these defects are a main fixture in many tree risk assessment systems and best management practices, the research supporting their usefulness in predicting tree failure during storms is limited. When looking at past research involving populations of storm-damaged trees, there are several defects that have never predicted failure (or have been associated with reduced rates of failure). In this study, we took a closer look at four such defects: codominant branches; branch unions with included bark; multiple stems originating from the same point; and overextended branches. After Hurricane Ian, we revisited 1519 risk assessed trees where one of these four defects was identified as the primary condition of concern. Fourteen of these trees experienced branch failure during the storm (which hit the study area as a downgraded tropical storm). Upon closer inspection, none of these failures occurred at the defect of concern. Our findings indicate that none of the defects assessed appeared to increase the likelihood of tree failure in the species tested. Our results are in line with past research on these defects derived from post-storm assessments and analysis.

COVID-19 had a significant impact on construction projects due to labor shortages and COVID-19 restrictions, yet little is known about the impact it had on construction safety. To address this gap, an Australian construction project was selected to study the impact of COVID-19 on safety performance, safety climate and safety leadership. The study collected data from safety climate surveys, leading and lagging safety indicators and used linear regression to compare safety performance pre and post the onset of COVID-19. Our results showed after the onset of COVID-19 there was a significant reduction (Pr&gt;F at 0.05%) in incident rate, an improvement in supervisor safety leadership and safety climate, and satisfaction with organisational communication. The study identified the increase level of safety awareness due to COVID-19 did not result in an increase in the level of engagement in safety leadership. Interestingly, participation in the safety leadership activities did not improve until a change of Project Manager occurred. The study determined leaders who establish a positive safety climate within a project could negate the safety performance impact of COVID-19. The study confirms the importance of site safety leadership in maintaining engagement in risk management and the value of focused safety communication.

Healthcare workers (HCWs) are regarded as role models regarding health-related issues including vaccination. Therefore, it is essential to identify the predictors for COVID-19 vaccine acceptance among them. A cross-sectional study to assess the risk perception, attitudes and knowledge of HCWs toward COVID-19 vaccination was carried out. A total of 710 responses were received between September 2021 to March 2022, from HCWs in the Northern, Western and Eastern regions of Nigeria. Cross tabulations were performed to determine statistical relations between sociodemographic variables, knowledge, attitudes and risk perceptions concerning COVID-19 vaccine acceptance. Multinomial Logistic Regression analysis was performed to determine the predictive variables for COVID-19 vaccine acceptance. Statistical analyses were performed and P-values less than 0.05 were considered statistically significant at a CI of 95%. Results showed that 59.3% of the participants were amenable to COVID-19 vaccines. Multinomial regression analysis identified 14 variables at α <0.05 as predictors for vaccine acceptance. Male HCWs were 2.8 times more likely to accept the vaccine than their female counterparts. HCWs that were knowledgeable of the different kinds of vaccines, willing to recommend the vaccines to their patients, believe that the timing of COVID-19 vaccination was appropriate and had recent vaccination history within three years were 1.6, 24.9, 4.4 and 3.1 times more likely to take COVID-19 vaccine than those not sure. The study found a relatively high trust (51.3%) in the Nigerian Center for Disease Control (NCDC) for information regarding COVID-19 vaccines. Therefore, the NDCD should disseminate more robust insights regarding the safety profiles of various COVID-19 vaccines.

A thermal load dispatch problem minimizes the number of objectives viz operating cost and emission of gaseous pollutants together while allocating the power demand among the committed generating units subject to physical and technological system constraints. A stochastic thermal load dispatch problem is undertaken while taking into consideration, the uncertainties, errors in data measurements and nature of load demand which is random. Owing to uncertain load demand, variance due to mismatch of power demand termed as risk, is considered as another conflicting objective to be minimized. Generally multiobjective problems generate a set of non-inferior solutions are generated and supplied to a decision maker to select the best solution from the set of non-inferior solutions. This paper proposes opposition-based greedy heuristic search (OGHS) method to generate a set of non-inferior solutions. Opposition-based learning is applied to generate initial population to select good candidates. Migration to maintain diversity in the set of feasible solutions is also based on opposition-based learning. Mutation strategy is implemented by perturbing the genes heuristically in parallel and better one solution is sought for each member. Feasible solutions are achieved heuristically by modifying the generation-schedules in such a manner that violation of operating generation limits are avoided. The OGHS method is simple to implement and provides global solutions derived from the randomness of the population generated without tuning of parameters. Decision maker exploits fuzzy membership functions to decide the final decision. Validity of the method has been demonstrated by analysing systems in different scenarios consisting of six generators and forty generators.

Human Adenovirus (HAdV) infection occurs in 14-16% of patients in the early months after pediatric hematopoietic cell transplantation (HCT) and this correlates with a higher risk to develop HAdV disease and overall 6-month mortality. The main risk factors for HAdV infection are T-cell depletion of the graft by ex vivo CD34+ selection or in vivo use of alemtuzumab or anti-thymocyte serum, the development of grade III-IV graft versus host disease (GVHD), the type of donor (unrelated donor, cord blood, haploidentical or HLA mismatched parent) and severe lymphopenia (< 0.2 x 109/L). The prevention of HAdV disease is based on early intervention with antivirals in the asymptomatic patient when the permitted viral load threshold on blood (> 102-3 copies/ml) and/or on the stool (109 copies/g stool) is exceeded. Cidofovir, a monophosphate nucleotide analog of cytosine, is the primary drug for preemptive therapy, used at 5 mg/kg/week for 2 weeks followed by 3-5 mg/kg every 2 weeks. The alternative schedule is 1 mg/kg every other day (three times/week). Enhancing virus-specific T-cell immunity in the first months post-HCT by donor-derived or third-party-derived virus-specific T cells represents an innovative and promising way of intervention applicable both in prevention and therapeutic setting.

PM_0.1 (particles diameter ≤ 0.1 µm), nanoparticles (NPs), and ultrafine particles (UFPs), were interchangeably used in the scientific communities. PM_0.1 originated from both natural and human sources. However, investigations of PM_0.1 and its effects on the environment, visibility, and human health risk to understand the levels of air pollution, sources, and impacts in South East Asia (SEA) countries continue to be lacking. The concentration of PM_0.1 in most SEA countries are much worse than those in western countries environment. A further motivation of this reviewed article is to provide a critical synthesis of the current knowledge and study of ambient PM_0.1 in SEA cities. The main influence of characteristics of PM_0.1 appears to be local sources including biomass burning and motor vehicles. Continuous monitoring of PM_0.1 in terms of both mass and number concentration should be further understood. A critical review is of great importance to facilitating air pollution control policies and predicting the behavior of PM_0.1 in SEA.

Cardiorespiratory fitness (CRF) is a strong independent predictor of morbidity and mortality. However, there is no recent information about the impact of CRF on cardiometabolic risk specifically in Central and Eastern Europe, which are characterized by different biological and social determinants of health. Normative CRF values were proposed and the association between CRF and cardiometabolic outcomes was evaluated in an adult Czechian population. In 2054 participants (54.6 % females, median 48 years), the CRF was predicted from a non-exercise equation. Multivariable-adjusted logistic regressions were carried out to determine the associations. Higher CRF quartiles were associated with lower prevalence of hypertension, type 2 diabetes (T2D) and dyslipidaemia. Comparing subjects within the lowest CRF, those within the highest CRF had decreased chances of hypertension (odds ratio [OR] = 0.36; 95% CI: 0.22-0.60); T2D (OR=0.16; 95% CI 0.05-0.47), low HDL-c (OR=0.32; 95% CI 0.17-0.60), high low-density lipoprotein (OR=0.33; 95% CI 0.21-0.53), high triglycerides (OR=0.13; 95 CI 0.07-0.81), and high cholesterol (OR=0.44; 95% CI 0.29-0.69). There was an inverse association between CRF and cardiometabolic outcomes, supporting the adoption of a non-exercise method to estimate CRF of the Czech population. Therefore, more accurate cardiometabolic studies can be performed incorporating the valuable CRF metric.

Introduction: People with schizophrenia have poor cardiometabolic health, with elevated 10-year cardiovascular disease risk (CVD-R) scores and poor quality of life (QOL). There is lack of understanding of these issues in early psychosis. Aims: To quantify CVD-R in people with early psychosis and profile their obesity prevalence, lifestyle behaviours and QOL. Secondary aim was to explore associations between lifestyle behaviours/treatment characteristics and CVD-R/QOL. Method:Baseline data from 81 RCT participants were used to profile cardiometabolic health risks (QRISK®3, BMI and waist circumference). Participants self-reported lifestyle behaviours and QOL. Relationships between modifiable treatment/lifestyle factors and QOL/CVD-R were explored using bivariate analyses. Results: Participants’ relative risk for CVD over 10 years was 1.93 times higher than healthy counterparts; 39% also had an obese BMI and physical QOL was poor. No significant associations were observed between CVD-R or QOL with treatment characteristics and lifestyle factors. Discussion: Despite positive lifestyle behaviours, participants had elevated CVD-R scores and poor physical health related QOL. Quantifying CVD-R with QRISK®3 may highlight the need for health promotion interventions. Implications for practice: Mental health professionals should be alert to elevated cardiometabolic health risks in early psychosis, particularly as these can occur in the context of relatively healthy lifestyle behaviours.

The COVID-19 pandemic affected the whole world, but not all countries were impacted equally. This opens the question of what factors can explain the initial faster spread in some countries compared to others. Many such factors are overshadowed by the effect of the countermeasures, so we studied the early phases of the infection when countermeasures have not yet taken place. We collected the most diverse dataset of potentially relevant factors and infection metrics to date for this task. Using it, we show the importance of different factors and factor categories as determined by both statistical methods and machine learning (ML) feature selection (FS) approaches. Factors related to culture (e.g., individualism, openness), development, and travel proved the most important. A more thorough factor analysis was then made using a novel rule discovery algorithm. We also show how interconnected these factors are and caution against relying on ML analysis in isolation. Importantly, we explore potential pitfalls found in the methodology of similar work and demonstrate their impact on COVID-19 data analysis. Our best models using the decision tree classifier can predict the infection class with roughly 80% accuracy.

Fogo (Fogo island, Cape Verde Republic) is the youngest and most active volcano of the archipelago. The last eruption occurred in 2014–2015. Aiming at studying dust emissions and transport during the eruption period and assessing their impact on air quality and human health, a mineralogical and chemical characterization was undertaken in outdoor dust from all over the island, as well as in the lava resulting from this event. Air quality monitors were used to obtain concentrations of atmospheric particulate matter (PM) and gaseous pollutants. The mineralogical constitution of the samples was analysed by X-ray diffraction and Electron Microprobe, while the chemical characterization was performed through X-ray Fluorescence Spectrometry and ICP-MS. The volcanic rock was found to be tephritic to basanitic, with high potassium content. Several minerals were identified, such as titanian augite with ilmenite, basaltic hornblendes, pyrrhotites, apatites, pyroxenes, basaltic hornblendes and hematites. Concentrations of the particulate matter inhalable fraction (PM10) exceeded the 24-hour mean of 50 µg/m3 recommended by the World Health Organization. Nevertheless, total volatile organic compounds (TVOCs) showed levels lower than the worrying range. The highest levels of CO2 were recorded in more populated villages and farthest from the volcano. The Pollution Load Index (PLI) for outdoor dust collected on rooftops was always above 1, suggesting enrichment, with higher values in the dust size fraction < 63 µm. In the same way, the Contamination Factor pointed to high enrichment of As, Ni and Pb, and very high enrichment of Cd in the same size fraction. The Non-carcinogenic Hazard Quotient and Hazard Index estimated for Children suggest that health problems may arise. The Carcinogenic Risk, for all size fractions, was above the target risk. The element that most contributed to the global risk was As, followed by Pb and Co. Ingestion was the main exposure route for all size fractions. The dust size fraction that represented the highest risk was < 63 µm, mostly due to the As concentration.

Abstract: Seismic performance and loss assessments can have widely varying degrees of uncertainty. An essential issue is whether a particular assessed seismic loss or performance result has sufficient reliability to serve as the basis for risk management decisions and actions, including whether or not a code prescribed performance level is met, or if an assessed loss level is acceptable. A method is developed measuring the reliability of performance and loss assessments for individual buildings and for portfolios. Consideration is given to how well the building investigation and corresponding evaluation process have been performed, the qualifications of the person(s) doing the assessment, the thoroughness of the evaluation, and the technical validity of the assessment procedure or model. The approach characterizes the uncertainty of each component of the assessment procedure for each building in qualitative terms. The resulting reliability measure is likely to be most useful for the cases where an entity is determining whether/or not a building has acceptable life safety performance, or if a portfolio has an acceptably low risk of seismic damage loss over a given period of time. In both cases, the reliability must either be sufficient to warrant action, or serve to indicate need for improved assessment.

Methanol is a natural ingredient with major occurrence in fruit spirits, such as apple, pear, plum or cherry spirits, but also in spirits made from coffee pulp. The compound is formed during fermentation and the following mash storage by enzymatic hydrolysis of naturally present pectins. Methanol is toxic above certain threshold levels and legal limits have been set in most jurisdictions. Therefore, the methanol content needs to be mitigated and its level must be controlled. This article will review the several factors that influence the methanol content including the pH value of the mash, the addition of various yeast and enzyme preparations, fermentation temperature, mash storage, and most importantly the raw material quality and hygiene. From all these mitigation possibilities, lowering the pH value and the use of cultured yeasts when mashing fruit substances is already common as best practice today. Also a controlled yeast fermentation at acidic pH facilitates not only reduced methanol formation, but ultimately also leads to quality benefits of the distillate. Special care has to be observed in the case of spirits made from coffee by-products which are prone to spoilage with very high methanol contents reported in past studies.

This scoping study aims to explore the relationships between urban green spaces (UGSs) and cancer. We followed the PRISMA extension for scoping reviews (protocol published in 2018). Eligibility criteria for papers were: 1) to be concerned with UGSs, 2) reporting effects of UGSs on cancer-related outcomes including direct or indirect measures, 3) reporting randomized controlled trials, prospective cohort studies, case studies, observational studies, non-comparative studies, 4) in English or French. The search covered primary studies in the published and unpublished (grey) literatures searching by hand and electronic databases (MEDLINE, Green File, CINAHL and ScienceDirect). Among 1703 records screened by two reviewers independently, 29 were included for qualitative synthesis. We classify the cancers concerned and the effects reported i.e. protective effect, risk or without association. The most investigated cancers are bladder, breast and lung cancer. Our study also identified contributing factors and their mediating effects between UGSs and cancer. Results highlight the wide variety of possible mediating factors between the use of green spaces and cancer occurrence, remission and/or prevention. Knowledge gaps and future research perspectives should be oriented to qualitative research on protective factors, the role of mental health in recovering from cancer and health inequalities.

This study investigates the country level determinants of liquidity synchronization and degrees of liquidity synchronization during economic growth volatility. As a non-diversifiable risk factor, liquidity co-movement shock spreads market wide and thus disrupts the overall functioning of the financial market. Firms in Asian markets operate in legal and regulatory environments distinct from those of firms analyzed in the previous literature. Comprehensive analyses of liquidity synchronicity in emerging markets are limited. A major knowledge gap pertaining to Asian emerging markets serves as the primary motivation for this study. Seven Asian emerging economies are selected from the MSCI emerging market index: Bangladesh, China, India, Indo-nesia, Malaysia, Pakistan and the Philippines for analysis from 2010 to 2019. The empirical findings show high levels of liquidity synchronicity in weaker economic and financial environments with low GDP growth, high inflation and interest rates and underdeveloped financial systems taking the form of low levels of private credit. Liquidity synchronicity is also affected by poor investor protection, political instability, weak rule of law and government ineffectiveness. Moreover, levels of liquidity synchronicity are higher in period of economic growth volatility.

Life evolved in an euxinic world with subsequent oxic 'invasion' leading to two parallel but interconnected biospheres, hydrogen sulphide (H₂S) and hydrogen peroxide (H₂O₂) exemplify these worlds respectively. Their concentration gradients have informational value in meromictic lakes. Similarly, it is posited, there exists a whole body chemocline in humans in which the two molecules form an inversely coupled oxic/sulphidic oscillator (OSO). The OSO is hormetic and characterised by a range of amplitudes and frequencies in health. Deviations from its baseline profile heralds the onset of SIRS before the appearance of clinical signs. Loss of oscillator status and transition to a steady state causes widespread intercellular and inter-organ communication failure presaging multi-organ dysfunction. The salient clinico-pathophysiological features of SIRS of any aetiology are emergent phenomena related to the OSO profile. Extent of recovery of organ function will mirror the recovery of the OSO profile thereby providing a tool to predict outcomes in SIRS.

Some herbicides exert hormetic or biphasic non-monotonic dose-response (NMDR), which is one of the major challenges for ecological risk assessment (ERA) of pesticides pollution. In this study, fish embryo toxicity test (FET) with Javanese medaka (Oryzias javanicus) to sublethal concentration of diuron was determined. Inverted U-shape heart rate was observed at 3 days post-exposure (dpe) and 7 dpe. However, at 13 dpe the heart rate (104 ± 2.90 heartbeat/min.) decreased in 10.00 mg.L-1 exposed-embryos. At 20 dpe, hatchability and survival rate were reduced in 5.00 mg.L-1 and 10.00 mg.L-1 exposed groups. Hormetic developmental deformities were observed in embryo-larvae of Javanese medaka. The results revealed a biphasic effect of low concentrations of diuron on some morphological and physiological features of Javanese medaka embryo-larvae, which might be attributed to endocrine disruption of this herbicide. Further studies to support these effects were recommended.

Disease related malnutrition (DRM) is prevalent in hospitals and is associated with increased care needs, prolonged hospital stay, delayed rehabilitation and death. Nutrition care process related activities such as screening, assessment and treatment has been advocated by scientific societies and patient organizations but implementation is variable. We analyzed the cross-sectional nutritionDay database for prevalence of nutrition risk factors, care processes and outcome for medical patients. In 59126 medical patients included between 2006-2015 the prevalence of recent weight loss (45%), history of decreased eating (48%) and low actual eating (53%) was more prevalent than low BMI (8%). Each of these risk factors was associated with a large increase in 30 days hospital mortality. Nutrition care processes increases slightly with presence of risk factors but never done in more than 50% of patients. Only a third of patients not eating in hospital receive oral nutritional supplements or artificial nutrition. We suggest that political action should be taken to raise awareness and formal education on all aspects related to DRM for all stakeholders, to create and support responsibilities within hospitals, and to create adequate reimbursement schemes. Collection of routine and benchmarking data is crucial to tackle DRM.

Microorganisms belonging to the Lactobacillus genus are naturally associated or deliberately added to fermented food products and are widely used in probiotic food additives and supplements. Moreover these bacteria normally colonize mouth, gastrointestinal (GI) tract and female genitourinary tract of humans. They exert multiple beneficial effects and are regarded as safe microorganisms. However, infections caused by lactobacilli, mainly endocarditis, bacteremia and pleuropneumonia occasionally occur. The relevance of Lactobacillus spp. as opportunistic pathogens in humans and related risk factors and predisposing conditions are illustrated in this review article with more emphasis on the species L. rhamnosus, that has been more often involved in infection cases. The methods used to identify this species in clinical samples, to distinguish strains and to evaluate traits that can be associated to pathogenicity, as well as future perspectives for improving the identification of potentially pathogenic strains are outlined.

The purpose of this paper is to evaluate the timing of innovative investment in technology product life cycles using a compound binomial option with management flexibility. Considering the business cycles changes in the macroeconomic will affect consumer purchasing power. The focus is how to evaluate the optimal investment strategy and the project value. It was applied to different product stages (three stages including production innovation, manufacture innovation, and operation innovation) and factored to different risks to build a technology innovation strategy model. An aim of this study is the options premium of the best strategy timing for each innovation stage. Its application of the compound binomial options for the manufacture innovation will only be considered after the execution of the production innovation. The same condition is applied to the operation innovation, which will only be considered after the execution of the manufacture innovation. Then, this paper constructs the dynamic investment sequential decision model, assesses the feasibility of an investment strategy, and makes a decision on the appropriate project value and options premium for each stage under the possible change of Gross Domestic Product (GDP). This paper investigates the product life cycle innovation investment topic by using the compound binomial options method and will provide a more flexible strategy decision compared with other trend forecast criteria.

This work analyzes the severity and risk associated with Automatic Dependent Surveillance-Broadcast (ADS-B) message drop out in Detect and Avoid (DAA) function of Unmanned Aircraft System (UAS). Performance assessment of the Universal Access Transceiver (UAT) ADS-B message implies that in some cases ADS-B fails to update within a specified update interval, which is referred to as drop out in this work. ADS-B is a fundamental surveillance sensor for both class 1 and class 2 DAA systems. Message loss or drop out has been found as one of the common limitations of the ADS-B system. The key feature of this study is incorporating the update rate of real ADS-B data transmitted from the manned aircraft. The data were received from the Grand Forks International Airport, North Dakota. Monte Carlo method has been adopted to resolve encounter scenarios in the presence of drop out. The change in the alert triggered by the UAS DAA in the presence of ADS-B drop out has been investigated. Furthermore, the risk matrices are created to quantify the associated risk with drop out affected alerts. Simulation results depict that both the duration of drop out and DAA look-ahead time affect the alert-triggering function of UAS. With a small look- ahead window and longer duration of drop out, the number of warning alerts increases. Also, alerts are affected more during an overtaking encounter than that of a head-to-head encounter. A system-level analysis is also carried out to recognize the potential reasons behind the ADS-B drop out.

Although the European reports highlight an increase in community-acquired Legionnaires’ disease cases, the risk of Legionella spp. in private houses is underestimated. In Pisa (Italy) we performed a three-year survey on Legionella presence in 121 buildings with an independent hot water production (IB); 64 buildings with a central hot water production (CB); and 35 buildings with a solar thermal system for hot water production (TB). From all the 220 buildings Legionella spp. was researched in two hot water samples collected either at the recirculation point or at on the first floor and on the last floor, while the potable water quality was analyzed in three cold water samples collected at the inlet from the aqueduct network, at the exit from the autoclave, and at the most remove remote? tap. Legionella pneumophila sg1, Legionella pneumophila sg2-16 and not-pneumophila Legionella species were detected in 26% of the hot water networks, mostly in CB and TB. In these buildings we detected correlations between the presence of Legionella and the total chlorine concentration decrease or/and the increase of the temperature. Cold water resulted free from microbiological hazards, with the exception of Serratia liquefaciens and Enterobacter cloacae isolated at the exit from two different autoclaves. We observed an increase in total microbial counts at 22 and 37°C between the samples collected at the most remote taps compared to the ones collected at the inlet from the aqueduct. The study highlights a condition of potential risk for susceptible categories of population and supports the need for measures of risk assessment and control.

The increasing prevalence and heightened severity of extreme weather events, which are consequences of climate change, pose significant challenges to the global property insurance sector. This study examines the concurrent crises faced by insurance companies in maintaining profitability and by property owners in affording coverage, thereby necessitating a reevaluation of current insurance paradigms. We present an innovative approach that utilizes a back-propagation (BP) neural network to forecast insurance losses and guide strategic underwriting decisions in regions prone to perils. Our advanced model combines crucial factors such as the likelihood of extreme meteorological phenomena, insurance risk premiums, and capital adequacy ratios to predict impending losses and inform insurance policy formulation. Through an extensive analysis of nearly two decades of catastrophe data from the United States and New Zealand, we determine the model's effectiveness in anticipating insurance-related losses and providing strategic guidance to insurance entities. The study concludes with recommendations for insurers to enhance risk assessment, innovate products, collaborate with governments, invest in green projects, and establish dedicated climate risk management teams. The study contributes to the discourse on climate change adaptation in the insurance industry and offers practical solutions for navigating the complexities of extreme weather risk.

The issue of climate change represents a significant global risk that demands immediate attention. However, higher education frequently fails to incorporate global perspectives and intricate transdisciplinary matters. In order to integrate global and transdisciplinary aspects into the curriculum of a technical university with a focus on computer science, a Master's programme has been developed. The programme's objective is to situate global risk at the core of the curriculum, thereby encouraging scientists to work beyond the boundaries of their respective disciplines. The paper considers the challenges that science and higher education must address to facilitate pathways towards a peaceful and sustainable future. It argues for a shift in focus from short-term and localised issues to a more holistic approach, emphasising the importance of considering universal problems. The curriculum, as developed, may be regarded as a guide for future university efforts in the fields of global risk and climate change.

Background: Research has consistently shown increased drug use among lesbian, gay, bisexual, transgender, intersex, queer/questioning, and asexual (LGBTQIA+) individuals. This is particularly the case among LGBTQIA+ adolescents. Substance use within this vulnerable community can propagate mental health issues leading to psychiatric disorders, self-harm and even suicide. Therefore, the objective of this scoping review was to evaluate the determinants of drug use among LGBTQIA+ adolescents. Methods: A comprehensive search of mainly primary research was conducted using several databases. Peer-reviewed articles published between 2018 and 2023 were included. The scoping review was conducted using the framework outlined by Joanna Briggs Institute (JBI) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses- Extension for Scoping Reviews (PRISMA-ScR) statement. Results: A total of 29 articles (including 400194 participants) were included in the analysis. The articles reported that the main determinants of drug use among LGBTQIA+ adolescents include homelessness, peer-peer interactions, mental health, and protective factors. The articles reported that mental health issues, which are mainly triggered by rejection, were the main determinants of drug use among LGBTOIA+ adolescents. Conclusion: Findings from this scoping review provide relatively reliable evidence that homelessness, mental health, peer-peer interactions, and protective factors are the main determinants of illicit drug use among LGBTQ+ adolescents. Rigorous studies that include large sample sizes, and systematic reviews are needed to further confirm these findings and assist in developing interventions to combat the unusually high level of drug use among this group.

Research interest in the occurrence, distribution, fate, and toxicity of N-(1,3-Dimethylbutyl)-N’-phenyl-p-phenylenediamine (6PPD) quinone, a derivative of the tire amino antioxidant 6PPD in urban environments, has surged. While several studies have found that 6PPD quinone exhibits acute, reproductive, and behavioral toxicity as well as mutagenicity and hepatotoxicity in aquatic and terrestrial animals, its environmental exposure data are fragmented and lack coherence across the source-to-exposure continuum, making it difficult to use for risk assessment and regulatory purposes. The present work developed an aggregate exposure pathway (AEP) framework to integrate the exposure data. An AEP network was developed for the atmospheric deposition of 6PPD quinone from tire wear in the Pearl River Delta, which led to human exposure. The 6PPD quinone research was organized, visualized, and evaluated with pertinent knowledge gaps identified using the weight of evidence assessment. Eight key exposure states were identified, with only two having high confidence levels and three having low confidence levels. Empirical support for the key transitional relationships decreased from High to Low from the source to the target site, indicating an urgent need for downstream mechanistic data. The proposed AEP framework integrated diverse 6PPD quinone research, facilitating a mechanistic understanding of the source-to-outcome continuum, as well as the development of quantitative predictive models for future research and environmental regulation.

Enhancing residents' purchasing intention of prepared dishes is crucial for the sustainable development of the prepared dishes industry. Understanding how residents' cognition influences their purchasing intentions can provide valuable insights for developing and refining industry policies. Based on the theory of distributed cognition, this study utilizes questionnaire data from urban residents in Beijing and Shanghai, and employs Structural Equation Modeling to explore the influence of cognition on the continuous purchasing intention of Chinese urban residents towards prepared dishes. The study results reveal that: (1) individual and geographical power significantly positively impact on residents' continuous purchasing intentions of prepared dishes, while cultural power perception does not have a significant effect. (2) Risk perception partially mediates the effect of personal and geographical power on continuous purchasing intention and fully mediates the effect of cultural power on continuous purchasing intention. Recommendations include: (1) The government should enhance standardization and supervision to create a favorable consumption environment; (2) Enterprises should provide more objective and transparent information to improve residents' knowledge of prepared dishes and establish a good reputation.

Teledermatology, the dermatological consultation and diagnosis via digital communication technologies, has become increasingly important in modern healthcare. The integration of teledermatology into clinical practice has gained significant interest, especially during the COVID-19 pandemic. Numerous studies have shown the effectiveness and reliability of teledermatology, with high levels of patient satisfaction and diagnostic accuracy. Pathpoint® eDerma is a cloud-based dermatology platform that aims to streamline the documentation and management of dermatological conditions. It offers several clinical benefits, including faster diagnosis, reduced unnecessary procedures, improved access to care, and cost savings. The platform follows a comprehensive risk management plan and complies with safety regulations. It undergoes regular recertification and reviews to ensure its safety and effectiveness. The clinical evaluation of eDerma confirms its ability to deliver significant clinical benefits while effectively mitigating risks. The benefit-risk ratio of eDerma is highly acceptable, supporting its use in clinical settings to enhance dermatological care.

Manufacturing firms need to streamline their initiatives in line with 17 sustainable development goals (SDGs) 2030 as a means for improving performance. This research adapts SDG’s goals 8 decent job and economic growth’ as a measure of performance, in examine the effect of corporate sustainability strategies on performance of manufacturing firms. Census sampling technique was used in cross sectional survey of 900 multi-industry managers from one hundred and fifty (150) manufacturing firms in Kano, Nigeria. A five Likert scale, well-structured questionnaire was used in collecting data, analysed by Structural Equation Modelling SEM PLS Package. The study shows positive and significant effect of eco-efficiency, and positive and insignificant effect of both legitimation and risk mitigation strategies on performance respectively. The study concluded that the positive and significant effects of eco efficiency initiatives could be due to benefits derived from total quality management system, energy monitoring, and process safety management reflected in sustainability oriented visionary leadership of the managers. The positive and insignificant effects of legitimation initiatives could be as a result of huge spending on sustainability reporting, and corruption. The positive and insignificant effect of risk mitigation could be due to pro-activeness of the firms’ managers in tackling risk through sustainability oriented visionary leadership. The study recommended firms should adopt conservative eco-efficiency initiatives for improving performance and stop adopting extroverted legitimation and introverted risk mitigation strategies as both have no significant effect on performance. Future researchers should use longitudinal research design using financial metrics adopting the same independent variables in other economic sectors.

Based on a wealth of evidence, aspirin is one of the cornerstones of secondary prevention of cardiovascular disease. However, despite several studies showing efficacy also in primary prevention, an unopposed excess risk of bleeding leading to a very thin safety margin is evident in subjects without a clear acute cardiovascular event. Overall, the variability in recommendations from different scientific societies for aspirin use in primary prevention is a classic example of failure of simple risk stratification models based on competing risks (atherothrombosis vs. bleeding), perceived to be opposed but intertwined at the pathophysiological level. Notably, cardiovascular risk is dynamic in nature and cannot be accurately captured by scores, which do not always consider risk enhancers. Furthermore, the widespread use of other potent medications in primary prevention, such as lipid-lowering and anti-hypertensive drugs, might have reduced the benefit of aspirin in recent trials. Some authors, drawing from specific pathophysiological data, have suggested that specific subgroups might benefit more from aspirin. This includes patient with diabetes and those with obesity, as well as considering sex-based differences. Moreover, molecular analysis of platelet reactivity has been proposed. A beneficial effect of aspirin has also been demonstrated for the prevention of cancer, especially colorectal. This review explores evidence and controversies concerning the use of aspirin in primary prevention, considering new perspectives in order to develop a personalized approach.

Coastal zones experience increasing climatic and human pressures, which lead to growing risks and tipping points (TPs) under future scenarios and natural resource scarcity. To avoid crossing TPs with irreversible coastal losses, this paper proposes the development of adaptation pathways based on advanced coastal oceanography and engineering knowledge that enables an objective assessment of evolving coastal risks. These pathways feature sequential interventions, combining conventional engineering works with nature-based solutions (NbS), steered by simulations and observations as a function of available coastal resources (space and sediment) and risks for infrastructure and socioeconomic assets. Such an adaptation has been developed for urban and peri-urban Mediterranean beaches, considering conventional coastal engineering together with NbS. Both types of interventions are assessed in terms of key physical variables, which serve to evaluate performance and estimate TPs. This analysis supports the new coastal protection and management plan promoted by the local government and the coastal adaptation plan of the central government. The approach and results illustrate the potential of adaptation pathways for beach sustainability, enhancing the compatibility between short/long-term coastal protection objectives under present/future climate and management scenarios. The adaptation pathways development underpins an increasing stakeholder cooperation to achieve shared decisions for coastal sustainability.

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

Purpose: This study aimed to identify the risk factors for acute pancreatitis (AP) and its impact on outcomes in Polish children treated for ALL. Methods: The study group included 2303 children who received intensive chemotherapy for ALL. The group was subdivided into patients with at least one episode of AP and those who did not develop AP following treatment for ALL. Results: The cumulative incidence of AP in the study group was 4.08%. Older age was an independent risk factor for AP development (OR 1.05; 95%CI: 1.006 – 1.098; p=0.03). The overall mortality related to AP was 2.13%. The probabilities of disease-free survival (p-DFS) and event-free survival (p-EFS) were 0.84 vs. 0.86, log-rank: p=0.65 and 0.75 vs. 0.80, log-rank: p=0.12, respectively in both subgroups. A total of 22 out of 94 patients (23.4%) with AP were re-exposed to asparaginase (ASP) during the subsequent phases of the treatment. Only one re-exposed to ASP patient (4.5%) developed a second episode of AP. There were no significant differences in p-DFS and p-EFS between patients re-exposed and not re-exposed to asparaginase (0.78 vs. 0.86, log-rank p=0.27 and 0.63 vs. 0.79, log-rank p=0.09 respectively). Conclusions: The incidence of AP in children with ALL is low and related to the patient’s age. AP development doesn’t seem to impact p-DFS and p-EFS in children with ALL. The recurrence of AP following re-exposure to asparaginase in patients with ALL and a history of AP is low (4.5%). Re-exposure to asparaginase after the first episode of AP doesn’t improve either p-DFS or p-EFS in children with ALL.

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

Background: Autonomic balance measurement (ABM) is a valuable tool in clinical practice for assessing the functioning of the autonomic nervous system (ANS), which controls involuntary bodily functions. Here we summarize the current understanding of the utility of autonomic balance measurement in clinical practice. Methods: A narrative review of relevant literature was conducted, focusing on studies investigating the use of autonomic balance measures in various clinical settings. Results: ABM holds potential benefits in clinical practice, including aiding in diagnosing autonomic dysfunction, monitoring treatment efficacy, and predicting potential health complications. ABM can be crucial for diagnosing various conditions, including cardiovascular diseases (Heart failure, arrhythmias, and hypertension), neurological disorders (Parkinson's disease, Alzheimer's disease, and diabetic neuropathy), in sports medicine athletes can undergo ABM to optimize training regimens, enhance performance, assessing the impact of training stress, preventing overtraining, and promoting overall well-being and probably to assess potential health risks, in metabolic syndromes ABM can aid in the early detection of autonomic neuropathy, a diabetes-related complication, allowing for timely intervention and better management of the disease, and psychiatric disorders (Anxiety, depression, and post-traumatic stress disorder). In addition, ABM can be helpful in monitoring of treatment efficacy, by tracking changes in autonomic balance, clinicians can assess if treatments for conditions impacting the autonomic nervous system are effective. ABM can also be helpful in predicting outcomes by facilitating early recognition of future health complications in certain populations. However, limitations exist, including non-specificity, variability in measurements, and limited evidence for routine use in specific clinical settings. Conclusion: Incorporating autonomic balance measurement into routine clinical assessments provides a more comprehensive understanding of a patient's health. It complements traditional diagnostic methods, offering additional insights into the body's regulatory mechanisms. While autonomic balance measurement offers potential benefits, careful interpretation and consideration of its limitations are crucial for its effective use in clinical practice. ABM remains a valuable and versatile tool in clinical practice for a deeper understanding of the autonomic nervous system, enabling early detection, targeted interventions, and improved management of various medical conditions across different specialties.

Alternative fertilizations are essential to minimize the deteriorating effects of chemical fertilizers on soil and water quality/health. Accordingly, the present work investigated the effects of combined organic-inorganic fertilization (COIF) on wheat and rice yields, soil nutrients, and soil Cd accumulation. Hence, seven different treatments were set up: control (CK); conventional fertilization (CF); optimized fertilization (OF); organic fertilizer replacing 25% (T1) and 50% (T2) of OF; and organic nitrogen (N) replacing 25% (M1) and 50% (M2) of OF-N. Overall, significant increases occurred in the yields of COIF crops. Compared with the CF, the highest wheat and rice yields happened in M1 treatment (approximately by18.5%) (P &lt; 0.05). COIF slightly alleviated soil acidification, and improved the cation exchange capacity (CEC) of the study soils. Besides, COIF treatments significantly increased the contents of total phosphorus, total potassium, available phosphorus, and available potassium by 6.35 to 16.9 %, 3.17 to 10.9 %, 5.53 to 28.7 %, and 2.6 to 12 %, respectively (P &lt;0.05). Nevertheless, negligible increases took place in Cd content of COIF soils compared with the CK. Altogether, our results concluded on 25% replacement of OF-N by organic N (M1) to effectively improve the fertility/ecological sustainability of the study soils.

Background: Healthcare workers are exposed to several hazardous chemicals in the workplace that can result in numerous adverse health effects. Several published studies from many different countries have documented the presence of metabolites from antineoplastic drugs in the urine of healthcare workers and demonstrated contaminated working surfaces with these agents. This study is a literature review that aims to compare the prevalence and degree of exposure to cyclophosphamide (CP), ifosfamide (IFO), and methotrexate (MTX) in physicians, nurses, and pharmacists in the hospital setting. Methods: An extensive search was conducted on PubMed, Google Scholar, HINARI, OARE, and Science Direct where applicable research about healthcare workers and antineoplastic drugs exposure were identified. Medical Subject Headings (MeSH) keywords: occupational exposure, antineoplastic drugs (cytotoxic drugs, cyclophosphamide, ifosfamide, methotrexate), hazardous chemicals, healthcare workers (healthcare professionals, nurses, pharmacists, physicians), hospital setting, and adverse health outcomes were used. Thereafter, relevant articles from 2000 to 2020 were selected to perform this literature review. Results: Review of literature demonstrated that cyclophosphamide was the most prevalent contaminant in the hospital setting. Additionally, pharmacists are among the group of healthcare workers with the highest prevalence of antineoplastic agents in urine samples while nursing stations had the highest rate of surface contamination. Conclusion: There is an urgent need to develop a system to monitor and detect the pathway of environmental exposure to antineoplastic drugs in the healthcare setting, and to evaluate the effectiveness of the existing protective measures. Well designed studies focusing on improving the standard safety precautions is a priority to protect healthcare workers.

Anastomotic Leakage (AL) remains the main cause of post-esophagectomy morbidity and mortality. Early detection can avoid sepsis and reduce morbidity and mortality. This study evaluates the diagnostic accuracy of the NUn-score and its components as early detectors of AL. This single centre observational cohort study included all esophagectomies from 2010-2020. C-reactive Protein (CRP), Albumin (Alb) and White cell count (WCC) were analyzed and Nun-scores calculated. Area under the curves (AUC) were used to assess their predictive accuracy. Seventy-four of the 668 patients (11%) developed an AL. CRP and the NUn-score proved to be good diagnostic accuracy tests on POD2 (CRP AUC:0,859; Nun-score AUC:0,869) and POD4 (CRP AUC:0,924; Nun-score AUC:0,948). A 182mg/L CRP cut-off on POD4 yielded a 87% sensitivity, 88% specificity, a negative predictive value (NPV) of 98% and a positive predictive value (PPV) of 47,7%. A Nun score cut-off&gt;10 resulted in 92% sensitivity, 95% specificity, 99% NPV and 68% PPV. Albumin and WCC have limited value in the detection of post-esophagectomy AL. Elevated CRP and a high NUn score on POD4 provide a high accuracy to predict AL after esophageal cancer surgery. Their high negative predictive value allows to select patients who can safely proceed with enhanced recovery protocols.

The study examines the return performance and resilience to market volatility of the recently introduced Environment, Social/Sustainable, and Governance (ESG) weight-tilted Hang Seng Index (HSIESG) compared to its parent, the Hang Seng Index (HSI). The ESG-infused index has a higher mean return and lower return volatility than the parent index, although the differences are statistically and economically insignificant, a result consistent with the high correlation between the two index returns. Most important, the ESG weighted-tilted index is more resilient to volatility spikes than the parent index and therefore has lower downside risks. The overall results show that stocks with high ESG ratings are less susceptible to trading pressures triggered by volatility-induced turnovers. The paper contributes to the literature by providing significant incremental information on the emerging market for ESG-related equity products in Hong Kong.

This study addresses the escalating threat of data theft ransomware, a form of cyberattack that exfiltrates sensitive information from victim networks and demands ransom for its non-disclosure. Unlike traditional crypto-ransomware, data theft ransomware leverages various infiltration techniques to gain unauthorized access and control over critical data assets. The study introduces a novel Moving Target Defense (MTD) framework, specifically designed for the Windows operating system environment, to counter these sophisticated attacks. MTD increases the unpredictability of the system by dynamically altering its configurations, thereby disrupting the adversary's ability to execute successful attacks. Our research includes the development and empirical evaluation of the MTD framework, demonstrating its effectiveness in reducing ransomware operational capabilities through quantitative analysis, qualitative observations, and statistical significance testing. We also explore the challenges and complexities involved in implementing MTD in real-world scenarios and propose strategies to overcome these barriers. The study concludes with recommendations for future research directions and the potential of MTD in enhancing cybersecurity defense mechanisms.

In this paper, we investigate a financial market in which asset prices evolve based on a multi-dimensional Brownian motion process and a multi-dimensional Poisson process with different credit and deposit rates We proceed to evaluate European options by establishing upper and lower hedging prices through a transition to a suitable auxiliary market. Additionally, we address the minimization of shortfall risk and no-arbitrage price bounds in incomplete markets within this framework.