The Impact Chain framework for risk assessment has proven to be a robust and effective It is very useful to set up the conceptual framework associated to a given risk and allows accommodating naturally the different components that shape that However, the operationalization of the impact chain may not be straightforward, in particular due to the inherent uncertainties associated to the selected indicators and the assigned In this paper, we introduce an extension to the Impact Chain framework that allows to consider uncertainties in the different components of the risk In the framework of the UNCHAIN project, a web-based tool has been developed to ease the task of implementing that The tool has been applied to a case study on the loss of tourist attractiveness due to heat stress conditions on the Balearic island, Spain, to illustrate how uncertainties in different components of the impact chain can affect the robustness of the final risk Also, the tool provides an estimate of the sensitivity of the final risk to each component, which can be used to guide risk mitigation Finally, a proposal for the validation of the risk assessment is presented.

BACKGROUND AND AIMS: Cardiovascular disease and colorectal cancer (CRC) are significant health problems and share some risk factors. The aim of our study was to develop and validate a predictive score for advanced colorectal neoplasia (CRN) based on risk factors for cardiovascular disease and CRC. MATERIALS AND METHODS: A cross-sectional study comprising a derivation cohort and an external validation cohort of 1049 and 308 patients respectively. A prediction score for advanced CRN (CRNAS: Colorectal Neoplasia Advanced Score) was developed from a logistic regression model, comprising sex, age, first-degree family history for CRC, systolic and diastolic blood pressure, total cholesterol, HDL-cholesterol, body mass index, diabetes, smoking, and antihypertensive treatment. Other cardiovascular risk scores (Framingham-Wilson, REGICOR, SCORE and FRESCO) were also used to predict the risk of advanced CRN. The discriminatory capacity of each score was evaluated using the area under the curve (AUC). RESULTS: CRN were found in 379 subjects from the derivation cohort (36%) including 228 patients (22%) with an advanced CRN. Male sex, age, diabetes, and smoking were identified as independent risk factors for advanced CRN. The newly created score (CRNAS), showed an AUC of 0.68 (95% CI: 0.64-0.73) for advanced CRN, which was better than cardiovascular risk scores (p

We assessed the association between cirrhosis and severe COVID-19-related outcomes among people with laboratory-diagnosed COVID-19 infection in British Columbia, Canada. We used data from the British Columbia (BC) COVID-19 Cohort, a population-based cohort that integrates data on all individuals tested for COVID-19 with data on hospitalizations, medical visits, emergency room visits, prescription drugs, chronic conditions, and deaths in the Canadian province of BC. We included all individuals, aged ≥ 18 who tested positive for SARS-CoV-2 by real-time reverse transcription-polymerase chain reaction, from January 01, 2021, to December 31, 2021. Multivariable logistic regression models were used to assess the associations between cirrhosis status and COVID-19-related hospitalization and ICU admission. Of the 162,509 individuals who tested positive for SARS-CoV-2 and were included in the analysis, 768 (0.5%) had cirrhosis. In the multivariable models, cirrhosis was associated with increased odds of hospitalization (aOR=1.97, 95% CI: 1.58 – 2.47) and ICU admission (aOR=3.33, 95% CI: 2.56 – 4.35). In the analyses stratified by age, we found that the increased odds of ICU admission among people with cirrhosis were present in all the assessed age-groups. Cirrhosis is associated with increased odds of hospitalization and ICU admission among COVID-19 patients.

The assessment of seismic risk in urban areas with high seismicity is certainly one of the most important problems that territorial managers have to face. A reliable evaluation of this risk is the basis for the design of both specific seismic improvement interventions and emergency management plans. Unappropriate seismic risk assessments may provide misleading results and induce bad decisions with relevant economic and social impact.The seismic risk in urban areas is mainly linked to three factors, namely, “hazard”, “exposure” and “vulnerability”. Hazard measures the potential of an earthquake to produce harm; exposure evaluates the amount of population exposed to harm; vulnerability represents the proneness of considered buildings to suffer damages in case of an earthquake. Estimates of such factors may not always coincide with the perceived risk of the resident population. The propensity to implement structural seismic improvement interventions aimed at reducing the vulnerability of buildings depends significantly on the perceived risk.This paper investigates on the difference between objective and perceived risk and highlights some critical issues. The aim of this study is to calibrate opportune policies, which allow addressing the most appropriate seismic risk mitigation options with reference to current levels of perceived risk. We propose the introduction of a Seismic Policy Prevention index (SPPi). This methodology is applied to a case-study focused on a densely populated district of the city of Catania (Italy).

Since financial institutions faced to fatal scenario like subprime mortgage crisis and COVID-19, the factor-based asset allocation methodology is noticed. Asset-only approach which make to consider restrictive risk volatility as individual assets had limitation of macro factor risk. For instance, an institution which allocated assets by asset-only approach cannot deal with the inflation crisis. We review the problem of the traditional modern portfolio approach that is used by Korean financial institutions. For reasonable investment of institution, we notice improved factor-based allocation approach. The first result of this paper is that Mean-variance approach as considered only return of asset recorded lower performance than multi factor-based portfolio in macro factor crisis. Second, we notice allocation model which can minimize probability passing the liability risk exposed macro factors to investment risk exposed macro factors. There are three steps in multi-macro factor-based asset allocation approach: discovering macro factors and mapping asset classes to individual macro factor. Second, define liability account and mapping as considering income and pay out of institution. Third, minimize correlation of fac-tor-based asset risk with liability volatility. Furthermore, using covariance return of assets to allocate makes Pareto improvement and supports to break Home-bias problems.

Climate change is increasing the occurrence of disastrous events in the world, but several disparities in population vulnerability are being registered. One of the causes of these variances is different public risk perception also due to the degree of education and knowledge of the population. In this study, some of the results obtained in a risk perception survey are presented. The survey was carried out in an area of Calabria (Southern Italy) hit by geo-hydrological events that have occurred in recent years with damage to roads, tourism facilities and private houses. A statistical interpretation of the results highlights the importance of education and knowledge to risk perception on the part of the population investigated.

The hazard and the carcinogenic risks due to the exposure to some potentially toxic elements by the Santiago Island (Cape Verde) population where calculated, considering soil ingestion, inhalation and dermal contact as exposure pathways. The topsoil of Santiago Island is enriched in Co, Cr, Cu, Ni, V, Zn, Mn and Cd to upper crust values. Hazard indices (HI) were calculated for these metals and As exposures, of Santiago Island population and the calculations were performed for children and adults. For children HI are higher than 1 for Co, Cr and Mn. So there is indication of potential non-carcinogenic risk for children, due to the high Co (HI=2.995), Cr (HI=1.329) and Mn (HI=1.126), values in soils. For the other elements and for adults there is no potential non-carcinogenic risk. Cancer risk was calculated for As, Cd, Cr and Ni exposures, for adults and children and the results are always lower than the carcinogenic target risk of 1x10-6, for As, Cd, and Ni. However, cancer risk are higher than the carcinogenic target risk for Cr, for adults. Regarding As, for children the fraction due to Riskingestion represents 51.6%, while Riskinhalation represents 48.0% and Riskdermalcontact represents only 0.4% of total risk. For adults Riskinhalation represents 81.3%, Riskingestion represents 16.6% and Riskdermal contact represents 2.1%. These results reflect the higher daily ingestion dose for children and the higher inhalation rate and higher dermal contact surface for adults. For the other elements and for adults the cancer risk due to Cr, Ni and Cd inhalation is always higher than for children, reflecting the higher inhalation rate for adults.

We present an updated design process for adapting and integrating existing cyber risk assessment approaches for impact assessment for the risk from IoT to the digital economy. The new design process includes a set of changes to the original standards (e.g. NIST) that are adapted for the IoT cyber risk in this paper. This paper also presents a new framework for impact assessment of IoT cyber risk, specific for the digital economy.

Cardiovascular diseases (CVD) are rising rapidly among the postmenopausal woman but they are less likely to identify their risk by an appropriate risk assessment tool. This review evaluates available literature on cardiovascular risk assessment among postmenopausal women to provide a concise view of risk factors and disease burden among them, present risk assessment systems including their drawbacks, emergence of new risk factors and their role in risk prediction, and finally use of hormone replacement therapy during menopause. Results demonstrate that menopause is a transition point for developing CVD not due to physiological changes only but psychosocial factors like depression and marital stress are also responsible. Both conventional and emerging risk factors burden are high among postmenopausal women. Though data regarding CVD risk assessment among postmenopausal population is lacking but existing evidences claimed underestimation or overestimation of risk among women. Moreover application of different tools on same population has revealed significant variation in result. In this regard, recalibration of conventional tools with local data and new risk factors has showed improvement of risk prediction. Hormone replacement therapy during early menopause has reported beneficial to prevent CVD but in secondary prevention it has no role. All of these findings demand further studies on cardiovascular risk assessment, especially in developing countries where women after menopause are not in consideration of health strategy makers.

This article presents a novel sustainable business management technique, emphasizing description and estimation over the outdated profit metric. Due to the intricacies and challenges of implementing the 2019 capital management method based on capital valuation (implemented in 2020–2022), a simpler approach became essential. While it is plausible for organizations to implement capital management based on their valuation, undertaking it with no outside help presents a challenge. The new descriptive method is fundamentally distinct in that detailed monetary valuations of capitals are omitted in favor of description and estimation. This paper establishes the groundwork for applying the new approach in several stages and introduces three new management indicators—the overall accomplishment of management goals index (evaluating management efficacy), the capital level index, and the adjustment (compliance) index—replacing the profit metric. Noteworthy advantages include separating the assessment of management outcomes from the organization's condition, including human and social capital into efficiency evaluations, and removing the profit indicator for management purposes, which prevents resource waste and enhances company efficiency and effectiveness.

This paper is focused on mapping the current evolution of Internet of Things (IoT) and its associated cyber risks for the Industry 4.0 (I4.0) sector. We report the results of a qualitative empirical study that correlates academic literature with 14 - I4.0 frameworks and initiatives. We apply the grounded theory approach to synthesise the findings from our literature review, to compare the cyber security frameworks and cyber security quantitative impact assessment models, with the world leading I4.0 technological trends. From the findings, we build a new impact assessment model of IoT cyber risk in Industry 4.0. We therefore advance the efforts of integrating standards and governance into Industry 4.0 and offer a better understanding of economics impact assessment models for I4.0.

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

Our objective was to evaluate whether pregnancy is prolonged by use of a proteomics-based maternal serum screening test followed by treatment interventions. This is a secondary analysis of the PREVENT-PTB randomized trial comparing screening with the PreTRM test versus no screening. The primary trial analysis found no significant between-group difference in preterm birth rate. Rather than considering a dichotomous outcome (preterm vs term), we treated gestational age at birth as a continuous variable using survival analysis. We also evaluated between-group difference in NICU length of stay and duration of respiratory support. Results indicated that pregnancy was significantly prolonged in subjects screened with PreTRM test compared to controls (adjusted hazard ratio 0.53, 95% confidence interval 0.36-0.78, P <0.01). Newborns of screened subjects had significantly shorter NICU stay but no significant decrease in duration of respiratory support. In the PreTRM screen-positive group, interventions that were associated with pregnancy prolongation included care management and low-dose aspirin but not 17-hydroxyprogesterone caproate. We concluded that screening with the PreTRM test followed by interventions for screen-positive pregnancies can prolong pregnancy and reduce NICU-LOS.

Background: Handover is a critical process for ensuring quality and safety in healthcare. Considerable research suggests that poor handover results in significant morbidity, mortality, dissatisfaction, and excess financial costs. Despite this, little formal attention, education, and evaluation has been given to handover. There is also paucity of data on the opinions of practitioners on the safety of handover.Objectives: The aim of this study was to measure the perceived risk, degree of patient harm and the systems used to support handover, and to understand how this varied by care setting, type of clinical practice, location, or level of experience. Methods: An open, anonymous and confidential online questionnaire covering: (a) respondent characteristics; (b) peer-to-peer handover; (c) internal referrals; (d) discharges and transfers between organisations; and (e) leading and improving handover was conducted with healthcare practitioners and managers from various settings. Results: We gathered a total of 432 completed responses from 26 countries. The average reported performance of handover was rated as 3.9 out of 5.For each type of handover, 12 - 14% reported errors occurring more than weekly. Of those that knew the outcome of such errors, between 29% and 34% reported that they had witnessed moderate or severe harm. 12% and 17% of respondents believed that handover was high or very high risk (See table 4). These respondents were more likely to have witnessed moderate or severe harm, or to be more senior.A wide combination of handover systems was utilised by respondents. 28% - 32% relied exclusively on EPRs (with or without face-to-face contact). 21% used Office documents such as Word and Excel for peer-to-peer handover, and over 30% used hand-written or manual systems. Conclusions: This study suggests the need to do more — and go further — to improve communication and reduce risk during all types of handovers. Clinical leaders should find ways to train and support handover with effective systems, with less experienced staff being the primary focus. More research is needed to demonstrate the interventions that improve the safety of handover.

Nutrition support is increasingly recognized as a clinically relevant aspect of the intensive care treatment of cardiac surgery patients. However, evidence from adequate large-scale studies evaluating its clinical significance for patients’ mid- to long-term outcome remains sparse. Considering nutrition support as a key component in the perioperative treatment of these critically ill patients, led us to review and discuss our understanding of the metabolic response to the inflammatory burst induced by cardiac surgery. In addition, we discuss how to identify patients who may benefit from nutrition therapy, when to start nutritional interventions, present evidence about the use of enteral and parenteral nutrition and the potential role of pharmaconutrition in cardiac surgery patients. Although the clinical setting of cardiac surgery provides advantages due to its scheduled insult and predictable inflammatory response, researchers and clinicians face lack of evidence and several limitations in the clinical routine, which are critically considered and discussed in this paper.

1. Background: Cardiovascular diseases (CVDs) are India’s leading cause of mortality. This study aimed to recalibrate the original Framingham Risk Score (FRS) equations among adults in Kerala state. 2. Methods: Baseline survey data from the Kerala Diabetes Prevention Program were analyzed: 921 males and 567 females for lipid-based FRS scores and 1042 males and 646 females for BMI-based FRS scores. Recalibration of the original FRS scores was performed using local data on CVD risk factors and CVD mortality. 3. Results: Among males, the median 10-year CVD risk with the recalibrated lipid-based FRS score was 7.34 (IQR 4.33-12.42), compared with the original score of 8.88 (5.23-14.87) (p<0.001). For BMI-based FRS scores, the median 10-year CVD risk was 7.40 (4.27-11.83) with the recalibrated score, compared to 9.32 (5.40-14.80) for the original score (p<0.001). In females, the median 10-year CVD risk was 4.83 (2.90-8.36) with the recalibrated score, compared to 2.85 (IQR 1.71-4.98) with the original score (p<0.001). Similarly, the median 10-year CVD risk was 4.66 (2.74-8.81) with the recalibrated BMI-based FRS score, compared to 2.95 (1.72-5.61) with the original score (p<0.001). 4. Conclusions: Recalibrated FRS scores estimated a significantly lower 10-year CVD risk in males and a higher risk in females than the original FRS scores.

Consumer preference for products made from transgenic technology has been widely studied, yet few studies exist exploring the factors influencing producers’ adoption of transgenic technology. Based on field surveys in Chinese provinces of Shanxi, Henan and Shandong, we employed a gambling experiment to capture producers’ risk preferences by estimating their risk aversion coefficients. We further estimated producers’ risk amplification and risk perception of GM technology. Using ordered logit model and Poisson model we identified the major factors influencing producers’ adoption of transgenic technology. We found the factors impacted the decision of producers from different regions in different ways. The results showed that over 60% of participants amplified the risk of transgenic crops. When there was potential risk, producers might not be rational even if they had high level of knowledge and cognition about the technology. Our results shed light on government policies aiming to increase the adoption of new technologies by producers.

Limited accessibility in some parts of Indonesia causes difficulties in logistic distribution, especially for emergency and medical supplies. Emerging drone cargo technology is a potential solution to improve logistic distribution in those areas. However, implementing drone cargo technology involves unknown risks, both in technical and non-technical aspects. Since data on drone operations in Indonesia is limited, a new method is explored to build a Bayesian Network (BN) model for risk analysis of drone crashes in Indonesia’s outermost and underdeveloped areas. The method optimizes the modelling process, in which significant risk factors are selected based on three drone operator companies’ experiences, which include wind speed, rain intensity, and system component failure or malfunction. Real wind speed and rain probability data are then implemented in the model. The operator’s data shows that wind speed contributes to drone crashes, which can be appropriately modelled in the BN model. The model produced a probability of safe operation of 94.1%, comparable to the annual operator’s data. The result shows that most operations are safe, with a minimum case of crashing and no case of harming human life.

Rising incidences of cutaneous melanoma have fueled the development of statistical models that predict the individual melanoma risk. Our aim was to assess the validity of published prediction models for incident cutaneous melanoma using a standardized procedure based on PROBAST (Prediction model Risk Of Bias ASsessment Tool). We included studies that were identified by a recent systematic review and updated the literature search to ensure that our PROBAST rating included all relevant studies. Six reviewers assessed the risk of bias (ROB) for each study using the published “PROBAST Assessment Form” that consists of four domains and an overall rating of ROB. We further examined a temporal effect regarding changes in overall and domain-specific ROB rating distributions. Altogether 42 studies were assessed, of which a vast majority (n=34; 81%) was rated as having high ROB. Only one study was judged as having low ROB. The main reasons for high ROB ratings were the use of hospital controls in case-control studies and the omission of any validation of prediction models. However, our results of the temporal analysis showed a significant reduction in the number of studies with high ROB for the domain analysis. Nevertheless, the evidence base of high-quality studies that can be used to draw conclusions on the prediction of incident cutaneous melanoma is currently much weaker than the high number of studies on this topic would suggest.

The ongoing COVID-19 pandemic is shaking the foundations of public health governance all over the world. Researchers are challenged by informing and supporting authorities on acquired knowledge and practical implications. This commentary applies established theories of risk perception research to COVID-19 and reflects on the role of risk perceptions in these unprecedented times. Moreover, it calls for utilizing the knowledge on risk perception to improve health risk communication, build trust and contribute to a collaborating governance.

Longevity risk constitutes an important risk factor for life insurance companies and it can be managed through longevity-linked securities. The market of longevity-linked securities is at present far from being complete and does not allow to find a unique pricing measure. We propose a method to estimate the maximum market price of longevity risk depending on the risk margin implicit within the calculation of the technical provisions as defined by Solvency II. The maximum price of longevity risk is determined for a survivor forward (S-forward), an agreement between two counterparties to exchange at maturity a fixed survival-dependent payment for a payment depending on the realized survival of a given cohort of individuals. The maximum prices determined for the S-forwards can be used to price other longevity-linked securities, such as q-forwards. The Cairns-Blake-Dowd model is used to represent the evolution of mortality over time, that combined with the information on the risk margin, enables us to calculate upper limits for the risk-adjusted survival probabilities, the market price of longevity risk and the S-forward prices. Numerical results can be extended for the pricing of other longevity-linked securities.

This article presents a low-cost insurance system developed for small-hold farms in disaster-prone regions, primarily using free Earth Observation (EO) data and Free Open Source Software (FOSS) – collectively termed sustainable geoinformatics - with a proprietary mobile phone app that enables verification. The study examined 30 farms in Risaralda department, Colombia. A Digital Elevation Model (12.5m pixels) from the ALOS PALSAR satellite sensor was used with a Geographical Information System (GIS) to map the terrain, drainage and geohazards of each farming district. Google Earth Engine (GEE) was used to carry out Time Series Analysis of 15 EO and weather datasets for 1998 to 2020. This analysis enabled the levels of risk from hydrometeorological hazards to be determined for each farm of the study, providing key data for the setting of insurance premiums. A parametric insurance product was piloted using GPS-tagged, time-stamped mobile phone photos to verify crop health. Key features of this insurance system are its low operational cost and rapid damage verification, relative to conventional approaches to farm insurance. It is an affordable form of insurance for small-scale farmers, with the rapid verification and payment of claims. This relatively fast, low-cost and affordable approach to insurance for small-scale farming enhances sustainable development by enabling policy-holder farmers to recover more quickly from disasters.

Contamination of soil and crops with heavy metals (HMs) poses a significant environmental challenge in the United States. Hence, this study aimed to assess HM contamination levels from sampled Ohio and West Virginia soils using various pollution indicators analyses, including Enrichment Factor (EF), Geo-accumulation index (lgeo), Contamination Factor (CF), and Pollution Load Index (PLI) and identify the Translocation Factor (TF) of HMs in the edible part of the vegetables and further evaluate health risks associated with dietary exposure through estimations of Estimated Daily Intake (EDI), Hazard Index (HI), Target Hazard Quotient (THQ), Cancer Risk (CR) and Target Cancer Risk (TCR) on adults and children. In this study, Fe was the most predominant contaminant, ranging from 28.41 to 67.36 g/kg in the soil. Cancer risk assessment revealed that Ni poses significant risks. Therefore, regular monitoring of metal concentrations in soil and vegetables grown in these regions might mitigate potential health hazards in the future.

Falls are the third-leading cause of disabilities among the elderly population worldwide. In Pakistan, the prevalence is 44%; out of them, 8% develop injuries, placing them at high risk for hospitalization or even premature death. Interestingly, fall is multifactorial, and fall risk depends on individual characteristics (intrinsic factors) and environmental features (extrinsic factors), which can be different from context to context. Therefore, regular assessment of fall risk factors is required to develop a strategy for fall prevention. This study aimed to identify intrinsic risk factors for falls in Pakistani elders living in the communities, and provide evidence for preventive strategies of falls in elderlies. Data were collected from 140 Muslim elders from two residential areas of Peshawar, Khyber Pakhtunkhwa, from July 2022 to August 25, 2022, after taking permission from Zhengzhou University Ethical Review Board (ZUIRB #202254), and District Health Department Office (DHO #14207).Participants were informed and concern was taken before collect data. Data were collected using the Time Up and Go Test (TUGT), the Mini-Mental Status Examination, and interviews regarding the prayer practice. Factors associated with falls were; age, gender, education, cognitive status, TUGT level, incorrect prayer postures, poor vision, and history of falls with a significance of (P.<0.05). Poor cognition, low vision, poor walking speed, and prayers without body movements have good membership with falls risk prediction as (P<0.005) in Omnibus, Lemeshow score (0.77). Hence, our study provides a road map for future risk assessment for falls by adding the four mentioned risk factors as offered in the proposed model to facilitate taking timely action to prevent fall-related ailments in Pakistani elders.

The pandemic of obesity worldwide has been recognized as a very important challenge. Within its complexity the identification of higher risk patients becomes essential since it seems unsustainable trying to offer access to treatment to all people with obesity. Several new approaches have recently been presented as important tools for risk stratification. This research applied some of these tools in a cross-sectional study involving adults with obesity classes I, II, III and super obesity. The participants had their cardiometabolic risk profile assessed. The study included adults with obesity, aged 18 to 50 years (n=404) who were evaluated for anthropometric, body composition, hemodynamic, physical fitness and biochemical assessments. These variables were used to identify the prevalence of risk factors for cardiometabolic diseases according to the classes of obesity, by gender and age group. The results showed a high prevalence of risk factors, especially among the upper classes of obesity (BMI &gt; 35 kg/m2) using single parameters as the waist circumference with almost 90% above the cut-off point. But there were also smaller numbers as the Glycated Hemoglobin whose prevalence was around 30%. Indexes like the atherogenic index of plasma (AIP) had the highest prevalence, with 100% of the male participants identified with increased risk for cardiovascular diseases.

Purpose: National Institute for Health and Care Excellence (NICE) has recently published quality standards for assessment of fall risk and preventing further falls. According to the standards, multifactorial fall risk assessments should include: identification of falls history; analysis of gait, balance, mobility and muscle strength, among other factors. Despite being based on subjective analysis or simple timing and not being multifactorial, physiotherapists and physicians quite often use these tests as reference scales to differentiate between lower and higher risk of falling. Instrumented TUG has been recently reported to provide important additional information to the overall score. Objective: To explore a case-based approach of fall risk assessment to identify the most relevant and informative risk factors that in combination could better define a person risk profile. Materials and Methods: A multifactorial assessment of fall risk through questionnaires, standard functional tests, tests instrumented with inertial sensors, and force platforms has been studied within a group aged 55-80 years old. Different fall risk factors and fall risk assessment methods were analyzed in a case-based descriptive study. Results & Discussion: Subjects at higher risk of falling were identified based on their detailed profiles. A set of features were obtained from the instrumented standard tests differing significantly between subjects presenting higher or lower fall risk. Therefore, instrumenting conventional tests with wearables containing inertial sensors and force platforms gives more detailed and quantitative insights. This information can be used to better define and tailor fall prevention exercises and to improve the follow-up of the evolution of the subject.

The purpose of this study is to find out the e-reputation management of the hotel industry, as well as the social media channels used as the tools of hotel e-reputation building. This study used a qualitative approach by analyzing the in-depth interviews with hotel marketing communication practitioners of 15 hotel companies in Bandung City. The findings identified that e-reputation is considered a crucial factor in determining hotel performance due to the change of customers’ behaviors today and identified also three types of e-reputation management activities implemented by hotel companies, such as online activities, offline activities, and online/offline activities. The results of this study have implications for the hospitality industry, as a reference for formulating their marketing strategies.

Flying-fox populations are increasingly threatened by heat events, starvation events and other stressors due to habitat clearing and human/flying-fox conflict.These factors are unlikely to resolve, meaning that a well-coordinated and timely approach to flying-fox disasters is imperative for the mitigation of further flying-fox population impacts.

There are potentially promising mitigation activities for epidemic and pandemic scenarios that are not currently the subject of significant research effort. Large epidemics and pandemics pose risks that are important to mitigate, even if the likelihood of the events is low and uncertain. While some efforts are the subject of extensive funding and consideration, other approaches are neglected. Here, we consider such neglected interventions which could significantly reduce the impact of such an epidemic or large-scale pandemic. These are identified via a narrative literature review of extant literature reviews and overviews of mitigations in epidemic and pandemic situations, followed by consideration of the economic value of information of further study of heretofore neglected interventions and approaches.Based on that analysis, we considered several classes of mitigations, and conducted more exploratory reviews of each. Those discussed include mitigations for (1) reducing transmission, such as personal protective equipment and encouraging improved hygiene, (2) reducing exposure by changing norms and targeted changes for high-risk or critical professions and activities, (3) reducing impact for those infected, and (4) increasing large scale resilience using disaster and infrastructure continuity planning.Some proposed mitigations are found to be of low marginal value. Other mitigations are likely to be valuable, but the concepts or applications are underdeveloped. In those cases, further research, resources, or preparation are valuable for mitigating both routine and extreme disease outbreak events. Still more areas of research are identified as having uncertain value based on specific but resolvable uncertainties. In both of the latter cases, there is no guarantee that mitigations identified as worthy of further consideration will be valuable, but the argument for further research is clear.

This study examined the tail dependency structure of sovereign credit risk and three global risk factors in BRICS countries using copulas approach, which is known for its ability to provide the “true” tail correlation based on the correct marginal distribution. The empirical results show that global market risk sentiment comoves with sovereign CDS spreads across BRICS countries under extreme market events, with Brazil having the highest co-dependency followed by China, Russia, and South Africa. Furthermore, oil price volatility is the second biggest risk factor correlated with sovereign CDS spreads for Brazil and South Africa while exchange rate risk exhibits very small co-dependence with sovereign CDS spreads under extreme market conditions dominated by tail events. On the contrary, exchange rate risk is the second largest risk factor co-moving with China and Russia’s sovereign CDS spreads while oil price volatility exhibits the lowest co-dependence to CDS in these countries. Between oil price and currency risk, evidence of single risk factor dominance is found for Russia where exchange rate risk is largely dominant. These results suggest that BRICS policymakers might consider financial sector regulations that mitigate risks spill-over such as targeted capital controls when markets are distressed.

Building a social security system to ensure Singapore residents have peace of mind in funding for retirement has been at the top of Singapore Government’s policy agenda over the last decade. Implementation of the Lifelong Income For the Elderly (LIFE) scheme in 2009 clearly shows that the government spares no effort in improving its pension scheme to boost its residents’ income after retirement. Despite the recent modifications to the LIFE scheme, Singapore residents must still choose between two plans: the Standard and Basic plans. To enhance the flexibility of the LIFE scheme while maintaining its simplicity, we propose some plan modifications such that scheme members do not face a dichotomy of plan choices. Instead, they select two age parameters: the Payout Age and the Life-annuity Age. This paper provides an actuarial framework for determining members’ payouts and bequests based on the proposed age parameters. We analyze the net cash receipts and internal rate of return (IRR) for various plan-parameter configurations. This information helps members make their plan choices. To address cost-of-living increases we propose to extend the plan to accommodate an annual step-up of monthly payouts. By deferring the Payout Age from 65 to 68, members can enjoy an annual increase of about 2% of the payouts for the same first-year monthly benefits.

The population’s mobility in urban areas is a necessary variable in the modeling of risk scenarios caused by atmospheric contamination. The inclusion of this concept makes static models more dynamic while considering people within a city to be an entity with complex mobility processes. We propose a conceptual and methodological tool to make the representation of the social, economic and territorial components, as well as the patterns in the population´s mobility to delimitate risk areas for human health by exposure of contaminants. In the volatile organic compounds (VOC), benzene, ethylbenzene, toluene and xylene (BTEX) are amongst the most dominant substances in fugitive vapor emissions in gas stations (GS). In urban areas, the exposure to BTEX by residential proximity and proximity to other facilities, which cause intra-urban agglomeration, can impact and affect human health. This model seeks to facilitate the focalization, identification and prioritization of risk areas by BTEX environmental contamination. This article goes beyond de conceptual framework. It suggests methodological and instrumental aspects to be applied in other cities. The government agencies must consider these results when establishing rules, permissions and procedures to reduce environmental pollution for managing the risk in a complex urban environment.

This investigation delves into an examination of the growth dynamics observed in Central Taiwan Science Park (CTSP) and Silicon Glen in Scotland, with a specific focus on their energy, environmental, and economic management. The aim is to predict and evaluate the latest advancements and applications of technology. In terms of energy, CTSP focuses on Taiwan's supply security and green transformation challenges, while Silicon Glen emphasizes Scotland's wind energy generation technologies. Both regions are committed to the development of renewable energy and smart grids. Regarding environmental aspects, CTSP and Silicon Glen prioritize environmental protection and sustainable development by implementing measures for environmental monitoring. In terms of economic management, CTSP, and Silicon Glen serve as key technology industry hubs This investigation delves into an examination of the growth dynamics observed in Central Tai-wan Science Park (CTSP) and Silicon Glen in Scotland, with a specific focus on their energy, environmental, and economic management. The aim is to predict and evaluate the latest advancements and applications of technology. In terms of energy, CTSP focuses on Taiwan's supply security and green transformation challenges, while Silicon Glen emphasizes Scotland's wind energy generation technologies. Both regions are committed to the development of renewable energy and smart grids. Regarding environmental aspects, CTSP and Silicon Glen prioritize environmental protection and sustainable development by implementing measures for environmental monitoring. In terms of economic management, CTSP, and Silicon Glen serve as key technology industry hubs in Taiwan and Scotland, respectively, attracting numerous high-tech and startup enterprises. Various means facilitate the growth of industries and foster innovations in different industrial spheres. Important factors contributing to this growth include policy support, availability of research materials, and provision of infrastructure. This research paper compares the successful case studies of two industrial parks, along with their environmental and economic management strategies. It explores the management principles that ensure the sustainable development and economic growth of industrial parks, aiming to assist decision-makers and relevant stakeholders in evaluating the sustainable development planning of industrial parks.

Overcrowding in the emergency department is a problem that generates several implications for bed management, which is deemed one of a hospital's most critical processes. Effective management of hospital production capacity includes bed management processes, which can be improved in order to leverage hospital performance. Thus, this study sought to understand how bed management works and identify the main factors that influence its management. The study was performed through a case study, with data collected from semi-structured interviews and bibliographic research, which were triangulated. Thematic content analysis of the interviews and cross-analysis were performed. As a result, the main factors that influence hospital Bed management were identified: communication between teams and units; definition of performance goals; decisions shared between units; occupation and discharge planning by the teams; length of stay; the role of the nurses; and COVID-19. The greatest difficulties in the management process are related to these factors. Additionally, suggestions are provided to mitigate such reported difficulties.

Managers are often faced with the task of improving the management of the production 17process in order to maintain the sustainability of production efficiency in a highly competitive en-18vironment. The submitted contribution deals with the design of a system that will support them in 19the selection of progressive methods and technologies in order to improve the management of pro-20duction processes. Managers often follow new trends in this issue, but it is not easy to work on the 21knowledge that proven progressive technologies can bring them higher efficiency. The presented system is based on the use of knowledge of existing solutions of manufacturers of automotive components, where companies solve similar problems in production management. The mix of methods and technologies used in the management of production processes brings companies different results in the achieved efficiency. The proposed system for supporting the selection of the production management method and technology is designed from blocks of data collection, benchmarking of the performance of production processes of industrial enterprises, and further from data mining technology to obtain knowledge about the effect on efficiency from already implemented technologies. The last blocks help to examine the differences in the implementation of the same methods and technologies and allow to present the obtained results to the manager in the form of recommendations for choosing a suitable progressive method and technology.

The issue of women’s participation in top management and boardroom positions has received increasing attention in the academic literature and the press. However, the pace of advancement for women managers and directors continues to be slow and uneven. The novel framework of this study organizes the factors at the individual, organizational and public policy level that affect both career persistence and the advancement of women in top management positions; namely, factors affecting 1) career persistence (staying at the organization) and 2) career advancement or mobility (getting promoted within the organization). In the study location, Chile, only 32 percent of women “persist”, or have a career without interruptions, mainly due to issues with work–family integration and organizational environments with opaque and challenging working conditions. Women who “advanced” in their professional careers represent 30 percent of high management positions in the public sector and 18 percent in the private sector. Only 3 percent of general managers in Chile are women. Women in Chile have limited access and are still not integrated into business power networks. Our findings will enlighten business leaders and public policy-makers interested in designing organizations that retain and promote talented women in top positions.

The enterprise software sector is experiencing a significant transformation driven by rapid technological progress and evolving business needs. An effective release management process is crucial for the solution providers and customers, as they incorporate the principles of Industry 4.0 and 5.0. With the growing dependence on software solutions and services, ensuring their quality, reliability, and security is highly necessary. The release management process incorporates strategic planning, regression testing, accurate deployment, and continuous monitoring of software updates. However, the rapid advancements in artificial intelligence (AI) and machine learning (ML) create a unique challenge to the release management process. The existing research needs to address the necessary adaptations for Industry 5.0, mainly in product-based software organizations, to the release management process without a change management system. After working with several software solution stakeholders, based on the responses from SaaS project stakeholders, we have presented a revised software release readiness workflow by incorporating a change management module. The preliminary result based on data over a limited period of time indicates that the revised workflow has the potential to improve the management of slippage, particularly by more effectively addressing NFR-related issues, thereby resulting in more predictable and reliable release cycles.

Considering the increasing rate of energy consumption and its environmental detrimental effects, as well as considering the use of non-renewable energy sources such as fossil fuels, energy management issues have become more important. Given the 40% share of the building industry's total energy consumption, as well as the 80% share of energy consumed during the operation period, attention to the areas of energy management and optimization during the operation period of the buildings can have a major impact on buildings’ energy performance. In this research, through identifying building energy management tools and studying previous studies and assessing the effects of building energy management systems, the economic and environmental impacts of using building energy management systems on the annual energy consumption in an office building in Tehran as a case study has been investigated. The results indicate a 32 percent reduction in energy consumption and a significant reduction in the release of the environmental pollutants in smart mode compared to the base mode. Moreover, considering the social costs associated with the emitted pollutants as well as the return period, it has been attempted to identify the factors contributing to the economic justification of using smart heating and cooling systems. According to the results, the use of smart energy management systems can be considered as an effective step in optimizing and managing energy consumption in the construction sector.

Flooding in Nigeria has recently acquired a new dimension and turned into a significant concern in terms of the total amount of property destroyed and the number of people affected. Flooding is one of the top ten natural disasters in the globe. The frequent flooding in Nigeria, which is often related to climate change and poor urban design, is a major worry from the standpoint of the country's development. Flooding and other related threats are becoming more likely to affect infrastructure and population.Neighbourhoods around the nation are increasingly more significantly impacted. Populations and infrastructure are significantly impacted by urban facilities encroaching on floodplains and low implementation of physical planning requirements for floodplain management and waterway development. Because of this, livelihoods are less able to repair after a storm. The nation's rapid urbanisation and population growth have raised the danger of flooding to both people and properties. Critically, a major obstacle to risk control is a lack of understanding of the risk. As a result, there is a significant knowledge vacuum regarding how to improve current efforts to solve the problems caused by Nigeria's floods as efforts to address the threat appear to be limited.

As people's consumption habits change, loan plays a crucial role in our modern society. It provides individuals who do not have sufficient money with funds to purchase residential property or start a business. However, for avoiding unpleasant loan defaults, all financial institutions will first assess the borrower's risk index. By predicting the default risk of the borrower to decide whether to lend money. Machine learning algorithms, including random forest, linear regression and so on, have been benefited most of the real-world applications. With the development of machine learning methods, this paper, based on the personal history loan data of an institution studies the loan default risk, and uses the random forest classification model to predict the possibility of loan default. The result showed that the accuracy of this method was 85.62%, which show its application ability of real-world loan prediction and benefits the manager to decide the degree of risk for loan grant.

Commercial development of tidal stream energy is hampered by technical and financial challenges, and impeded by uncertainty about potential environmental effects that drive environmental risk assessments and permitting (consenting) processes. The effect of greatest concern for operational tidal stream energy devices is the potential for marine animals to collide with turbine blades, resulting in injury or death. Due to the turbulent and often turbid waters that frequently characterize tidal turbine sites, there is an absence of empirical evidence about collisions with marine animals. This paucity of observations often leads to risk-averse permitting decisions that further restrict the deployment of tidal energy devices that are needed to collect this evidence. This paper relies on the framework of stressors and receptors that is used widely in marine energy studies and outlines a stepwise probabilistic methodology that applies existing knowledge to further elucidate the risk to marine animals from operational tidal turbines. A case study using striped bass from the Bay of Fundy, Canada, accompanies the methodology, to partially demonstrate its application.

Understanding how the public perceives various risks and hazards associated with our well-being and health is crucial for government and policymakers. The present research aimed to assess the public's perception of various risks and hazards associated with their well-being and health. The study combined two well-known approaches to risk assessment, namely, the analytical hierarchical process (AHP) and the psychometric paradigm. Seven risk attributes were chosen from the risk perception literature to evaluate 27 risks and hazard activities using a survey questionnaire developed based on the psychometric paradigm literature. The collected data was then analyzed using AHP to determine the priority weight for each risk attribute. The results showed that the most important risk attribute was voluntariness of risk, followed by chronic-catastrophic and newness of risk. Furthermore, the study found that natural hazards were ranked the highest, followed by refugee influx and fire hazards. In contrast, the mobile phone was perceived as the lowest type of risk. The findings can be used by policymakers to develop effective and sustainable risk communication strategies. Policymakers can use the research findings to create effective and sustainable risk communication strategies that help the government to inform and educate the public about potential risks, improve coordination among agencies and stakeholders, and enhance public trust in government decision-making.

Background: Current European guidelines support transcatheter aortic valve implantation (TA-VI) in intermediate to low-risk patients ≥75 years-old but its prognostic relevance is unknown. Methods: Intermediate-to-low-risk (Society of Thoracic Surgeon score <8%) patients enrolled in the HORSE registry were included. We compared the population with less versus more than 75 years old. The primary endpoint was all-cause mortality. Results: A total of 2685 patients were included, 280 (8.6%) <75 and 2405 ≥75 years. Through a mean follow-up of 437 ± 381 days, 198 (8.2%) and 23 (8.2%) patients died in the two arms, without statistically significant differences (log-rank p=0.925). At Cox regression analysis, age did not predict the occurrence of all-cause death, neither as a continuous variable (HR 1.01, 95% CI 0.99-1.04, p=0.294) nor dichotomizing according to the prespecified cutoff of 75 years (HR 0.97, 95% CI 0.63-1.51p=0.924). Time-to-event ROC curves showed low accuracy of age to predict all-cause mortality (area under the curve of 0.54 for both 1-year and 2-year outcomes). Conclusions: TAVI has comparable benefits across age strata in intermediate-to-low risk patients. The age cut-off suggested by current guidelines is not predictive of the risk of adverse events during hospital stay, neither of all-cause mortality through a mid-term follow-up.

Directive 2018/844/EU on energy efficiency claims almost 80% of final energy consumption in EU is used within the buildings. Subsequent Directive (EU) 2023/1791 introduced in 2023 expected 68% of the World population living in urban areas. Both Directives enhanced the role of energy management (EM) applied on the city buildings. The study introduces the development of energy management in Czech municipalities between the years 2009 and 2023. The main goal of this article is to present selected results of the unique national survey focused on the energy management in Czech municipalities conducted in 2023 and compare it with results of national surveys implemented in 2009 and 2018. The main method is the evaluation of deep survey conducted among the municipal representatives or energy managers in the past with the new survey conducted in 2023. The results show that EM became notably more important issue for the most Czech municipalities. The number of cities implementing EM significantly grew and the number of city energy managers increased too. On the other hand, the used potential of energy savings triggered by establishing EM is insufficient. This article should be applied to stress power of municipal EM in performing energy efficiency and RES projects and encouraging government to support municipal energy managers in their complex role.

The efficient and sustainable management of hospitals is an increasingly relevant challenge in the healthcare sector. With limited financial resources, regulatory pressures and increasing demands for quality services, hospitals are faced with the want to approve sound policies to certify financial and operational sustainability. Management accounting is critical in this instance. In Portugal the DL nº 284, of July 26, 1999, allow us to confirm the need to reinforcement of profitability and efficiency in the provision of healthcare. Management accounting is an essential tool for monitoring and controlling costs, making strategic decisions, efficiently allocating resources and evaluating performance in the hospital environment. It allows a comprehensive view of financial and operational aspects, providing valuable information for management and strategic planning. However, the sustainability of hospital management accounting is a critical and complex topic that deserves special attention. Hospitals face several challenges, such as the complexity of hospital costs, the integration of information systems and the measurement of healthcare value. These challenges can compromise the effectiveness of management accounting and its ability to provide relevant and reliable information for decision making. As a result, it is required to address the sustainability of hospital management accounting by identifying the specific challenges faced in this area and exploring opportunities to overcome them. By addressing these challenges and seizing opportunities, hospitals can strengthen their position in the healthcare sector, improve their operational efficiency, optimize resource allocation and ensure the provision of quality services to patients. In this article, the challenges faced by hospital management accounting will be analysed, such as the complexity of costs, the integration of information systems and the measurement of value in healthcare. Additionally, opportunities to improve financial and operational management will be highlighted through the adoption of advanced technologies, an emphasis on value-based management and collaborative partnerships. By exploring these themes, this essay aims to make a contribution. to the advancement of hospital management accounting and the sustainability of hospitals in the current healthcare scenario.

The restrictions imposed by the Covid-19 pandemic left many older adults isolated and confined. Under active aging theory, self-management is crucial for well-being among older adults coping with aging. The current study examines how (a) initial self-management, and (b) changes in self-management due to independent physical training, affect psychological outcomes in a sample of care home residents following outbreak of the pandemic. 64 older adults (53 females, 11 males), mean age is 82.23, reported on their self-management abilities, then embarked on six months of training in chair exercises (one session per week). The training exercises were halted after 22 sessions due to the pandemic, but some residents continued to practice independently. Eight weeks after the outbreak of the pandemic, residents who had continued to practice at least once per week (n = 35) and those who had not continued to practice (n = 29) were questioned again about their self-management, and about five psychological outcomes: anxiety, traumatic stress, satis-faction, general mood, and post-traumatic growth (PTG). Self-management improved among older adults who independently practiced the exercises, and declined among those who did not. Pre-pandemic self-management significantly predicted post-outbreak traumatic stress symptoms, anxiety, general mood, and satisfaction with life, but not PTG. However, the difference in self-management between the pre-pandemic and post-outbreak measures was associated with PTG, and made a unique contribution to prediction of the other effects. Self-management abilities among older adults can be seen as a protective factor against adverse psychological outcomes at times of trauma. Further, the improvement in self-management among older adults who independently practiced physical excises made a unique contribution beyond initial self-management abilities.

During the Covid-19 pandemic in Taiwan, analytical tools of PEST (political, economic, social-cultural, and technological), SWOT (strength, weakness, opportunity, threat), nine building blocks of a business model canvas, and knowledge management were combined to develop a theoretical framework, and used to assess business, smart and sustainable management of two case companies: Tung Sheng Company Limited and its subsidiary, Strong Basic Enterprise Limited. A heuristic inquiry research design was adopted. In addition to secondary data from the two case companies, major top managers were interviewed to reveal constructive questions about the existing business models and to re-interpret strategy. The results showed that case companies own capabilities of R &amp; D (research and development) as a foundation to further apply new smart ICT (information and communication technology) and execute green manufacturing. Additionally, strong key partnerships are used to diversify business investment for leveraging on limited resources given current insufficient qualified employees. Resilient practices adopted new and green technology to help mitigate the negative impacts of the Covid-19 pandemic. This study provides a useful framework and practical information about how to examine business models, smart and sustainable management processes of the two case companies and to make adjustments in strategies for the future.

The contribution deals with the selection of progressive methods and technologies to improve the management of production processes in the industrial area. The first chapter of the contribution summarises the theoretical starting points for the management of production processes and their progressive concepts. Chapter 2 deals with the analysis of the current state of play in the use of methods and technologies in production management and summarise its problem areas. Chapter 3 presents the design of a system for selecting the appropriate method and technology to improve the management of the production process. The system presented is designed from data collection blocks, a benchmark for the performance of industrial enterprises' production processes, and data mining to gain knowledge of the impact of the methods and technologies used on the performance of production processes. The last block of the system allows the presentation of the obtained results, which sets out the recommendation for the choice of progressive method and technology. The system is partially verified in the last chapter of the contribution.

During software development requirement gathering is an important phase. Requirements are the basis of software development. The success or failure of any software depends upon level of understanding developed in requirements. During software development requirements keeps on changing due to different reasons. Hence requirements are such a critical phase that leads to the total project failure. So, to understand the impacts and to identify the conflicts with existing requirements, it is important to manage and analyze the requirements well. Requirement change management is the interest of this paper. Different requirement change management techniques has been discussed in this paper and analyzed them well and finally conclude the results accordingly.

There has been a growing call for reform of the U.S. biomedical community in recent years. As a community, we face a growing list of issues including excessive waste, reproducibility, bias, inadequate training, and the absence of sustainable long-term planning that detract from the overall goal of advancing human health. In response to this debate, biomedical stakeholders have taken positive steps forward to remedy these issues. However, we must continually improve upon these steps to promote the long-term stability of the biomedical enterprise. Given the widespread interest of the scientific community in addressing these issues, there exists a unique opportunity to come together and create a new era of biomedical discovery. The completion of this exciting task requires reflection on our view and management of the system, and what the best route to sustainable change may be. Importantly, a coordinated approach that considers the collective make-up of the biomedical system and how processes and people influence collective output and create value for patients is needed. Here, these three areas and the concepts of systems theory, total quality management, and organizational development and their contribution to the management and effectiveness of biomedical discovery are discussed. Importantly recommendations are made concerning overall management strategy, process efficiency and quality research, administrative tasks, organizational cultural challenges, individual and team development, and funding strategy.

Socio-ecologic, socio-economic, and socio-technical transitions are opportunities that require fundamental changes in the system. These will encounter matters associated with security, service adoption by end-users, infrastructure and availability. The purpose of this study is to examine and overcome the risks to take advantage of opportunities through the novel Risky-Opportunity Analysis Method (ROAM). A novel quantitative method is designed to determine when, after making some changes, the risks become acceptable so that the opportunity does not deviate from the objectives. The approach provided a quantitative evaluation of the possible changes in parallel with digitization, towards providing a green Service Supply Chain (SSC). The result of ROAM shows that the most cost-effective change to increase the resilience of the system is a solution (SMS) which is different from that identified by a TOPSIS multi-criteria method. Real-word decisions in change management should tackle the complexity of systems and uncertainty of events during and after transition through a careful analysis of the alternatives. A case-study was carried out to evaluate the alternatives of an ancillary service in the Payment Service Providers (PSP). The comparison of the ROAM results with the traditional TOPSIS of the case-study unveils the priority of the ROAM in practice when the alternatives are Risky-Opportunities. The existing risk assessment tools do not take advantage of risky opportunities. To this aim, the current article introduces the term Risky-Opportunity, and two indexes Stress and Strain of the alternatives that are designed to be employed in the new quantitative ROAM approach.

NUMMI was one of the most analyzed case studies in terms of joint ventures, management dysfunction, and international globalization. NUMMI is an acronym for New United Motor Manufacturing, Inc. This manufacturer was a joint venture between automotive US titan GM and Toyota of Japan. GM wanted to further monetize its Fremont factory, but also had limited opportunities during a US economical recession. Toyota wanted to expand manufacturing operations in the US for the very first time, creating an intriguing collaborative partnership between the two. However, various problems lead to dysfunction through cultural, organizational, or managerial differences. This case study is analyzed through its historical analogical scope, ultimately leading to hypothesizing remediation through an ethical data-driven and total quality management (TQM) approach.

The conformity assessment of products or a measured value with the given standards is carried out based on the global risk of producers and consumers calculation. A product may conform to specifications but be falsely rejected as non-conforming. This is about the producer's risk. If a product doesn't meet the requirements but is falsely accepted as conforming, that poses a risk to the consumer. The conventional approach to risk assessment, which yields only a single numerical value for the global risk of producers and consumers, is naturally extended, and utilized for assessing risk in measurement models with linear regression. The outcomes of the two-dimensional extension, along a moderate scale, are the parabolas with an opening upwards. Risk surfaces were obtained through three-dimensional extension over the area limited by the moderate scale and guard band axes. Four models with different ranges of tolerance intervals were used to test this innovative method of risk assessment in linear regression. The corresponding standard measurement uncertainties are determined by applying a simplified measurement model with the use of comprehensive data on the measurement performance and by determining measurement uncertainty derived from consideration of the functional relationship obtained by linear regression analysis. Models that utilize information from linear regression analysis to determine measurement uncertainty are biased towards risks at the edges of the moderate scale. Testing the model's performances with metrics related to the confusion matrix, such as the F1 score, further substantiated this assertion. The diagnostic odds ratio has been proven to be extremely effective in identifying the curve along the guard band axis, along which the global risks of producers and consumers are at their lowest.

The variety of risks due to climate change with a potential impact on Cultural Heritage CH requires a multidisciplinary approach and a preliminary overview of the existing methods for risk analysis and assessment in different fields. Thus, the starting point of the research conducted by the Sapienza PNRR working group consists in a systematic literature review of risk assessment approaches, methods and indicators. As a first outcome, the research has designed a multidisciplinary comprehensive framework consisting of the definition of risk categorization, the framework represented by a measurable index and the main target, according to the classification of Cultural Heritage based on the harmonization of European vocabularies definitions and protocols. The risk assessment framework sets the methodological core of a future multi criteria matrix and digital platform for decision focused on the historic built environment and it is functional to the definition of specific operational guidelines connected to each risk for elaborating descriptive/predictive Architectural Heritage’s transformation scenarios to support the development of mitigation and adaptation strategies.

Arborists commonly investigate the extent of stem decay to assess the likelihood of stem failure when conducting tree risk assessments. Studies have shown that (i) arborists can sometimes judge the extent of internal decay based on external signs; (ii) sophisticated tools can reliably illustrate the extent of internal decay; and (iii) assessing components of tree risk can be highly subjective. We recruited 18 experienced tree risk assessors who held the International Society of Arboriculture’s Tree Risk Assessment Qualification (TRAQ) to assess the likelihood of stem failure due to decay after each of 5 consecutive assessments on 30 individuals of 2 genera. Five assessment techniques, in stepwise order, were 1) visual, 2) sounding the trunk with a mallet, 3) viewing a scaled diagram of the cross-section that revealed sound and decayed wood ascertained from resistance drilling, 4) viewing sonic and electrical resistance tomograms, and 5) consulting with a peer. For each technique, assessors assigned two or more likelihood of failure ratings (LoFRs) for at least 83% of trees, which were proportionally greatest after assessors viewed tomograms; the proportions did not differ among the other four assessment techniques. Covariates that influenced the distribution of LoFRs included percent of the cross-section that was decayed, and assessors’ experience using resistance drilling devices and tomography in regular practice. Practitioners should be aware that disagreement on the likelihood of tree failure exists even among experienced arborists.

We propose a methodology for the quantification of model risk in the context of credit derivatives pricing and CVA, where the uncertain or unmodelled parameter is often the correlation between rates and credit. We take the rates model to be Hull-White (normal) and the credit model to be Black-Karasinski (lognormal). We show how highly accurate analytic pricing formulae, hitherto unpublished, can be derived for CDS and extended to address instruments with defaultable Libor flows which may in addition be capped and/or floored. We also consider the pricing of a contingent CDS with an interest rate swap underlying. We derive explicit expressions showing how to good accuracy the dependence of model prices on the uncertain parameter(s) can be captured in analytic formulae which are readily amenable to computation without recourse to Monte Carlo or lattice-based computation. In so doing, we take into account the impact on model calibration of the uncertain (or unmodelled) parameter.

The efficiency success status of organization built environment assets management needs robust and comprehensive maintenance processes which depends on the efficiency of the contract information documents for the maintenance management within the assets life cycle and achieve positive return of the investments. Therefore, this paper highlights on the appropriate interactive approach to structuring information flow scope of the asset facilities management contract for construction projects based on GIS and BIM integration processes, sustainability standards, and As-built contractual documents of the project to support the organization owner and stakeholder to improve the asset management processes. Using expert interviews with comprehensive understand for the information type in several facility management contracts conducted in common Organization types based on reviewing available international facility management standards manual and contract of procedures for different services types, and required information flow inside international facility management firms. The study classify and build significant integrated information and data flow model contract drafting with measures and indicators of performance efficiency as guideline for monitoring, technically evaluating, and financially procedures for performance efficiency and quality of services provided in the facilities management contract for King Faisal University campus projects as a case study.

The problem of blood delivery has been a critical concern in past decades. However, the unsteady behavior of blood donors, along with the uncertainties associated with demands in a crisis imposes several challenges for resource management. In this research work, we analyze the blood delivery behavior in a crisis modeled by coupled queues of patients and blood sources. Using Markovian modeling and results associated with G-network, we derive two critical probabilities, namely lack of unit of blood (unit of donations) or not having any storage capacity left to accept new donors' blood. We propose a closed-form solution to calculate the optimal blood storage size, and also we suggest sufficient conditions that guarantee the feasibility of the model. Finally, we conduct a sensitivity analysis to investigate the impact of model parameters on storage size and the proportion of time that storage is full.

Bollworm poses a significant threat to cotton crops worldwide, including in the Fergana province of Uzbekistan. This study aims to explore innovative approaches to bollworm control and contribute to the global understanding of integrated pest management strategies (IPM). Using an extensive literature review and field observations, the study evaluates the effectiveness of an integrated protection system in reducing reliance on chemical inputs while increasing overall efficiency. The results highlight the multigenerational life cycle of bollworm, its impact on various crops, and the need for artificial biological control methods and targeted insecticide applications. In addition, the study highlights the need to adopt globally accepted IPM practices to ensure sustainable pest management. The findings underscore the importance of collaboration among researchers, farmers, policymakers, and industry representatives in developing and implementing advanced control measures. Through integrated approaches and the incorporation of scientific advances, bollworm infestations can be contained while safeguarding agricultural productivity and minimizing environmental risks.

Lake Rawapening, Semarang Regency, Indonesia, has incorporated a holistic plan in its management practices. However, despite successful target achievements, some limitations remain that a review of its management plan is needed. This paper identifies and analyzes existing lake management strategies as a standard specifically in Lake Rawapening by exploring various literature, both legal frameworks and scholarly articles indexed in Google Scholar and published in Water by MDPI about lake management in many countries. There are two major types of lake management, namely pillar-based and object-based. While the former is the foundation of a conceptual paradigm that does not comprehensively consider the roles of finance and technology in the lake management, the latter indicates the objects to manage so as to create standards or benchmarks for the implementation of various programs. Overall, Lake Rawapening management should include more programs on erosion-sedimentation control and monitoring of operational performance using information systems.

The compelling effects of climate change on forests may have been underestimated in the past few decades in practical forestry. Although the first attempts to draw attention to this complex problem appeared almost half a century ago, the debate has been conceptual rather than experimental and applicative. At first glance, the con-cerns were mainly related to sustainable forest management (SFM) issues, which obviously needed attention. Over time, the effects of climate change have been mainly considered in the context of the SFM; they started from various and somewhat different scales and goals. Over time, more research and awareness of the im-portance of SFM under the pressure of climate change have led to the development of a clearer field that can be defined as ‘adaptive forest management’ - to climate change. One of the characteristics of this discipline is to be featured by the absence of univocal methods and / or objectives to be pursued but to identify, verify, and adapt methods to the various climatic and forest types and conditions found in the field. Therefore, this work shows some phases of forest planning and management concepts and criteria over time and recalls some innovative and / or adaptive methods related to the approach to forest planning and management under climate change

This paper aims to explore the effect of humble leadership on project success by integrating the mediating role of employee creativity. Top management support moderates the direct relationship (humble leadership and project management effectiveness) and indirect relationships through employee creativity. Time-lagged data were obtained from 332 persons working in the matrix organization across the information technology. The results showed that humble leadership enhance project management effectiveness by mediating and moderating processes. This study provides a solution to an underlying research question that has gone unanswered in prior studies. What are the strategies proposed for humble leadership in fostering the effectiveness of the project?

Stormwater drainage and urban flooding are the popular issues in policy agendas and academia. Although the research on these title increases steadily an integrated review on stormwater drainage and urban flood with a focus on pluvial flooding has yet to be produced. This paper presents a critical review on stormwater drainage and urban flood based on 78 selected journal papers published over the period of 1990 to 2018. The review focus on pluvial flooding to relate urban stormwater drainage management and urban flood disaster management and to show the links between the two. The methods taken to manage urban stormwater drainage and urban flooding as well as the complexity of achieving a comprehensive urban flood disaster management are evaluated and discussed. To better understand the concepts behind urban flood and improve the urban flood risk management strategies, recommendation of future research directions are also provided.

Cloud infrastructure provides computing services where computing resources can be adjusted on-demand. However, the adoption of cloud infrastructures brings concerns like reliance on the service provider network, reliability, compliance for service level agreements (SLAs), etc. Software-defined networking (SDN) is a networking concept that suggests the segregation of a network’s data plane from the control plane. This concept improves networking behavior. In this paper, we present an SDN-enabled resource-aware topology framework. The proposed framework employs SLA compliance, Path Computation Element (PCE) and shares fair loading to achieve better topology features. We also present an evaluation, showcasing the potential of our framework.

Aim To explore the impact of cardiovascular risk factors on the type and outcome of hypertensive crises. Additionally, to investigate the occurrence of new cardiovascular events in a six-month period for both types of hypertensive crises and to define possible risk factors that may influence this.Method The data from the hospital electronic medical records of patients who presented with hypertensive crises at the Emergency Medicine Clinic of the Clinical Center of the University of Sarajevo over a six-month period were retrospectively collected. Pregnant women were excluded. Patients who died before completing the diagnostic examination as well as patients with incomplete data were also excluded. Data collection encompassed blood pressure levels, age, sex, history of chronic hypertension, smoking status, and presence of diabetes mellitus as cardiovascular risk factors. Outcomes after initial admission and after 6 months follow up were recorded. Results The study included 243 patients: 66 (27.2%) with hypertensive emergencies and 177 (72.8%) with hypertensive urgencies. There was no significant difference between these groups in age, history of chronic hypertension, presence of dyslipidemia, smoking status, and presence of diabetes mellitus (p>0.05). Men predominated in HE, while women predominated in HU group (p<0.05). Diastolic blood pressure values were higher in HE patients (p<0.05). 98.3% of HU patients were discharged, while 92.4% of HE patients were hospitalized. Mortality after initial admission was 3%, all of whom were hypertensive emergencies. After a 6-month follow-up, there was no significant difference in the number of readmissions between these two groups (p>0.05), but mortality was significantly higher in hypertensive emergencies (15.15% vs 6.21%) (p<0.05). There was no significant difference in the investigated risk factors between patients without readmissions, with readmissions without fatal outcomes, and deceased patients (p>0.05) except for age, which was significantly higher in patients with fatal outcomes (p<0.05).Conclusion Male sex and higher diastolic blood pressure (DBP) are identified as risk factors for hypertensive emergency (HE), suggesting a higher likelihood of hospital treatment and increased intrahospital mortality. Patients with HE also exhibit a higher risk of a lethal outcome within six months. Advanced age is associated with an increased risk of six-month readmission and a lethal outcome.

Neonatal mortality remains a public health concern and timely identification and prompt intervention in the delivery room could improve the outcome in neonatal morbidity and mortality. We performed a retrospective study to help us finding the profile of the high-risk newborn regarding the need for NICU admission, necessary to establish a protocol regarding the mobilization of human and material resources for the urgent management of these situations. All deliveries and neonates born in Maternity of Bihor County Emergency Clinical Hospital from Romania were reviewed, including relevant maternal, foetal and perinatal data to identify risk factors that result in birth of newborns needing resuscitation at birth between 2012-2019. The number of births showed a downward trend but around 90% of the births were on term. The incidence of neonatal emergencies is increasing, the most frequently were respiratory, sepsis and other infections, cardiovascular emergencies, and extreme prematurity. It is noted that in 2021 the incidence of these neurological emergencies increased by three times compared to previous years. The neonatal and maternal risk factors associated with admission to the NICU were mother's age over 35 years, low level of education, second/more gestation, weight under 2500 g, Apgar score under 7, premature rupture of membranes, macrosomia and mother's infectious pathology. Accurate identification of risk factors and anticipation at the birth of a high-risk neonate would result in adequate preparation and prompt resuscitation of neonates who need some level of intervention and thus, reducing neonatal morbidity and mortality.

Through processing and organizing the basic data and related literature on brownfield governance of Chinese local governments in recent years, the study constructed a risk evaluation index system for brownfield governance of Chinese local governments based on hierarchical analysis, taking into account the purpose of realizing the sustainable use of soil. Specific indicators were established under the two overall objectives of environmental protection and human health, including the degree of soil pollution, the degree of groundwater pollution, the degree of air pollution, the emission of toxic and hazardous substances, the type of land use, the intensity of land use, the maturity of governance technology, the scope of application of governance technology, the degree of perfection of policies and regulations, the strength of implementation of policies and regulations, the benefits of brownfield reuse, and the satisfaction of the public. In addition, the study takes Qitaihe City, which has already achieved the effect of brownfield management, as an example to further analyze the index system.

This work proposes a simple model to take into account the annual volatility of the mortality level observed on the scale of a country like France in the construction of prospective mortality tables. By assigning a fragility factor to a basic hazard function, we generalize the Lee-Carter model. The impact on prospective life expectancies and capital requirements in the context of a life annuity scheme is analyzed in detail.

Cerebrovascular diseases represent a significant mortality rate worldwide and constitute a major public health and economic challenge. Many African countries such as Cape Verde are going through an epidemiological transition from communicable to non-communicable diseases, demographic and socioeconomic changes and facing an increase in cerebrocardiovascular diseases associated with increased cardiovascular risk. The present study aimed to identify the prevalence of risk factors that predispose to cardiovascular diseases in adult individuals residing on the island of Santiago. Cross-sectional population-based study with individuals over 18 years of age, of both sexes. Data collection took place in October and November 2021, in all municipalities on the island of Santiago. Individuals with Cape Verdean nationality who stayed abroad for more than one year and who arrived on the island of Santiago less than 30 days ago and individuals with any type of disability that could prevent them from participating in the study were excluded from the study. The sample size was calculated based on the projection of the population of the island of Santiago for the year 2021, according to the appropriate epidemiological model. Sociodemographic data were obtained through the application of a questionnaire containing age, sex, race, weight, height, risk factors (presence of diabetes, dyslipidemia, heredity, physical activity, smoking habits, history of cerebrovascular events, control of weight and blood pressure). RESULTS: Study sample is predominantly female (54.8%), the age group with the largest number was 18-27 years (21%); 42.2% with BMI ≥ 25 kg/m2; 65.1% sedentary; Smoking 7.3% and alcoholism 14.4%; 6.5% with diagnosed heart disease; 19.9% with close family members with cardiac pathology; 2.7% had a stroke, 0.1% had a transient ischemic attack; 0.5% acute myocardial infarction; 23.5% had the periodic habit of assessing blood pressure; 32.6% hypertensive; 4.5% with diabetics. CONCLUSIONS: The study showed that there is a high prevalence of cerebrovascular risk factors on Santiago Island, especially in females. Smoking and alcoholism showed a relationship with males. BMI, physical inactivity, diabetes and dyslipidemia were shown to be related to sex. Hypertension and Diabetes revealed a significant relationship with age group. Alcoholism, smoking, hypercholesterolemia and hypertriglyceridemia maintained a significant relationship with the municipalities.

WHO estimates that around 600 million people suffer from high blood pressure which causes high costs for health systems and influences the economy of these countries. In this study, we investigate the sociodemographic characteristics and risk factors related to hypertension among individuals from Huambo, Angola. This cross-sectional study was conducted with 158 participants consulted in the Cardiology services at Hospital Geral do Huambo, between January and July 2023. A total of 67.1% of the studied patients were hypertensive. The mean age of the hypertensive (55.8±11.3) patients was higher than non-hypertensive (53.1±13.4) patients, although no significance was observed (p=0.199). Patients aged between 30 and 40 (OR=1.19, P=0493), male (OR=1.17, P=660), employees (OR=9.94, P=0935), patients consuming alcohol (OR=1.11, P=0.864), and practising physical activity (OR=1.12, P=0.742) presented a high chance of developing hypertension, while those living in urbanized areas (OR=0.78, P=0.59) and with a low educational level (OR=0.43, P=0.194), had a low chance to develop hypertension. There was no statistical significance between demographic or behavioural characteristics with hypertension (P>0.05). Regarding clinical characteristics, body mass index was statistically related to hypertension (p=0.011). Our findings show that hypertension is a major health problem for the young population of Huambo. There is an urgent need to create strategies to improve the prevention, diagnosis, and treatment of hypertension, not only in Huambo but throughout the country. Further studies to understand determinants related to hypertension should be carried out among the young population in Angola.

in our increasingly interconnected world, sensor networks are critical in gathering and sending data for various applications, from environmental monitoring and industrial automation to healthcare and smart cities. However, as sensor networks expand in importance, so does the need to solve the multidimensional concerns of security, privacy, and forensics. This article explores the complex world of sensor network security, the delicate balance between data privacy and utility, and the emerging area of sensor network forensics. This article focuses on risk assessment of a network.

Previous bio-mapping studies of pork processing facilities have indicated a need for mitigation strategies in trim and ground products due to Salmonella prevalence. Lymph nodes have been identified as a source of Salmonella in pork products. The objective of this study was to determine if the removal of glands and lymph nodes in pork would reduce Salmonella and indicator organisms in comminuted products. Samples from a commercial pork facility were divided into three treatment groups; 1) untreated control, 2) topical glands removed before final processing, and 3) topical, jowl, and internal lymph nodes and glands removed before final processing. Samples were evaluated for indicator organisms and quantity of Salmonella using the BioMérieux TEMPO® system and BAX® System Real-Time Salmonella SalQuant™ methodology, respectively. The results of this study indicate that the removal of the topical, internal, and jowl lymph nodes was effective at significantly (P &gt; 0.05) reducing the prevalence of both Salmonella and indicator organisms. Salmonella was reduced from 2.5-Log CFU/Sample and 3.8-Log CFU/Sample of Salmonella in control group ground and trim samples, to less than 1-Log CFU/sample in both matrices from treatment 3. These data indicate that samples from treatment 3 had an average of a 3-Log reduction, and treatment 2 had a 2.5-Log reduction, of Salmonella when compared to the control samples. This indicates that the physical removal of glands and lymph nodes can influence Salmonella and indicator organism prevalence in the final product.

Financial technologies, stemming from the application of artificial intelligence to big data in finance, are continuously expanding, across different markets and financial services. While financial technologies bring many opportunities, such as reduced costs and extended inclusion, they also bring risks, among which cyber risks, which are constantly increasing and are difficult to measure. Among the difficulties in measurement lies the existence of interdependence among different cyber risks. The study of interdependence and possible contagion channels between cyber attacks to different institutions and economic sectors is indeed increasingly important to ensure economic and financial sustainability. Against this backdrop, this paper proposes a multivariate model for count time series of cyber risk events, in which the time-varying intensity parameter determining the probability that a cyber attack occurs evolves according to general autoregressive score models, taking both time and sectorial dependence into account. The model is particularly suitable for studying how the behaviors of different markets or sectors are interconnected and it constitutes a new approach to the multivariate analysis of count time series of cyber loss events.

Objective: To describe the proportion of patients undergoing major abdominal surgery who develop postoperative hypothermia, and the variables associated with its occurrence. Material and Methods: We conducted a prospective cohort study in a tertiary care referral hospital in Mexico City to describe the incidence of perioperative hypothermia and factors associated with postoperative hypothermia. A repeated measures ANOVA model was used to compare preoperative, intraoperative, and postoperative temperatures. Potential variables associated with hypothermia were evaluated with a logistic regression analysis. Results: A total of 110 patients were included in the analysis. Of them, 61% (n=67) were women. The mean age was 56.7 years (SD: 16.3, range: 75). The most frequently involved organ on which surgery was performed was kidney or urinary tract (21.8%), followed by large bowel (14.5%) and exploratory laparotomy (14.5%). The incidence of postoperative hypothermia in patients undergoing major abdominal surgery was 57.3%, while preoperative and intraoperative hypothermia occurred in 55.5% and 79.1%, respectively. Age over 60 years was the only variable associated with postoperative hypothermia after multivariable adjustment for sex, age, and time surgery (OR=18.4, 95% CI:3.79-89.6, p<0.0001). Conclusion: Increasing age was the only variable associated with postoperative hypothermia in patients undergoing major abdominal surgery.

The aim of the article is to present a snapshot in time, of the current state in cryptocurrencies, the values and risks associated to blockchains. With emergence of over 20,000 crypto projects, the first objective of this article is to present the stage as it is in 2023, with historical overview since Satoshi presented the first paper on decentralised blockchains, until today. Second objective of the article is to review the values and risks associated to cryptocurrencies, and to clarify the differences between cryptocurrencies from blockchain technologies. The research questions that drive this article are related determining if the blockchain technology an innovation or its already obsolete technology? Are there any significant risks from cryptocurrencies? And are the potential values to society and economy worth pursuing? Would developed or developing countries benefit more from these technologies? And which blockchain projects will survive in the long run? In other words, where is the money and is there money or just hype. The review discusses the high probability that some crypto projects will fail, and given the vast number of cryptos, the article acknowledges that many of these projects are nothing more than ponzies. These are discussed and acknowledged, then the focus is shifted to the real-world use cases of blockchain projects.

The paper is an investigation on the impact of financial markets on the volatility of green bonds credit risk component, measured by the option-adjusted spread/swap curve (OAS) of the Global Bloomberg Barclays MSCI Green Bond Index, for both the non and pandemic periods. For these purpose, after observing the dynamic joint correlations between all the variables through a DCC-GARCH, we adopt GARCH(1,1) and EGARCH(1,1) models, putting the OAS as dependent variable. Our main results show that the conditional variance parameters are significant and persistent in both times, testifying the overall impact of the other markets on the OAS. In more detail, we highlight that the gamma in the two EGARCH models is positive: so the “green” credit risk volatility is more sensitive to positive shocks than negative ones. With reference to the conditional mean, we note that if during the non pandemic time only the stock market is significant, during the pandemic also conventional bonds and gold are impacting. To the best of our knowledge this is the first study that analyzes the specific credit risk component of green bond yields: we deem our findings useful to observe the change of green bonds creditworthiness in a complex market context.

Let us assume that defence mechanisms are so strong that the average outcome of a hacking attack is unsuccessful. How to calculate the costs arising from false positives and false negatives in intruder detection? Is it better for the hacker to make fewer but more effective attacks rather than several but less effective attacks? How to calculate the difference between these alternative strategies?

In the wake of the 2008 financial crisis, the Financial Stability Board (FSB) and the Basel Committee on Banking Supervision (BCBS) created a list of Systemically Important Financial Institutions (SIFIs) with the intention of determining which financial institutions were important enough to the global market that their failure would result in systemic collapse. In this work we create a model that modifies the BCBS's five indicators of size, interconnectedness, cross-jurisdictional activities, complexity, and substitutability and applies these measures of systemic stress to governments. The original application of the model is to track the systemic interdependence of the Eurozone, with particular emphasis on the case of Greece. We anticipate this model can be used in regional fiscal situations beyond the Eurozone.

Missense mutations in the LRRK2 gene were first identified as a pathogenic cause of Parkinson’s disease (PD) in 2004. Soon thereafter, a founder mutation in LRRK2, p.Gly2019Ser (rs34637584), was described, and it is now estimated that there are approximately 100,000 people worldwide that carry this risk variant. While the clinical presentation of LRRK2 parkinsonism has been largely indistinguishable from sporadic PD, disease penetrance and age at onset can be quite variable. In addition, its neuropathological features span a wide range from nigrostriatal loss with Lewy body pathology, lack thereof, or atypical neuropathology including a large proportion of cases with concomitant Alzheimer’s pathology, hailing LRRK2 parkinsonism as the "Rosetta stone" of parkinsonian disorders. These differences may result from interactions between LRRK2 mutant protein and other proteins or environmental factors that modify LRRK2 function, and thereby influence pathobiology. This review explores how potential genetic and biochemical modifiers of LRRK2 function may contribute to the onset and clinical presentation of LRRK2 parkinsonism. We review, which genetic modifiers of LRRK2 influence clinical symptoms, age at onset, and penetrance, what LRRK2 mutations are associated with pleomorphic LRRK2 neuropathology, and which environmental modifiers can augment LRRK2 mutant pathophysiology. Understanding how LRRK2 function is influenced and modulated by other interactors and environmental factors –either increasing toxicity or providing resilience- will inform targeted therapeutic development in the years to come. This will allow developing disease-modifying therapies for PD and LRRK2-related neurodegeneration.

A micro decision-making utility model under uncertainty is presented as a complementary foundation for macro coronavirus models. The micro model consists of two functions, a risk averse utility function depending on wellness and a wellness random output which is a function of the input variable called “treatment” consisting of such elements as social distance, washing hands, wearing a face mask, and others. The decision maker selects a level of treatment that maximizes her/his expected utility, given the probabilities of the respective outputs. The focus is on how changes in a person’s psychological attitude towards the macro determined (announced) probabilities affects the optimum results of the model. Such changes create a micro-macro dynamic interaction which is briefly outlined. A short discussion of the model’s behavioral implications for health policy is also given.

This article presents a comprehensive framework for valuing financial instruments subject to credit risk. In particular, we focus on the impact of default dependence on asset pricing, as correlated default risk is one of the most pervasive threats in financial markets. We analyze how swap rates are affected by bilateral counterparty credit risk, and how CDS spreads depend on the trilateral credit risk of the buyer, seller, and reference entity in a contract. Moreover, we study the effect of collateralization on valuation, since the majority of OTC derivatives are collateralized. The model shows that a fully collateralized swap is risk-free, whereas a fully collateralized CDS is not equivalent to a risk-free one.

The use of risk measures such as the Value at Risk (VaR) or Tail Conditional Expectation (TCE) is required by the Basel Committee on Banking Supervision in determining a bank’s risk profile. However, both measures can be shown to have shortcomings in the information that they provide to regulators and investors. In this paper we present an introduction to risk measure calculations before demonstrating the weaknesses of these measures. Through the exploration of specific cases we show how familiar yet differing risk profiles have identical values for combinations of these measures. From this evidence we recommend that a sequence of several risk measures should be used to give a more accurate representation of the risk contained on banking balance sheet.

Polycyclic aromatic hydrocarbons (PAHs) in street dust pose a serious problem threatening both environment and human health. Street dust were collected from five different land use patterns (traffic areas TRA, urban area URA, residential areas REA, mixed residential commercial areas MCRA and suburban areas SUA) in a Saudi coastal city, Jeddah, and one in rural area (RUA) in Hada Al Sham. This study aimed to investigate the status, profile, sources of PAHs and estimate their human health risk. The results revealed an average concentration of total PAHs of 3320 ng/g in street dust of Jeddah and 223 ng/g in RUA dust. PAHs with high molecular weight represented 83.38% of total PAHs in street dust of Jeddah, while the carcinogenic PAH compounds accounted 57.84%. The highest average concentration of total PAHs in street dust of Jeddah was found in TRA (4980 ng/g) and the lowest in REA (1660 ng/g). PAHs ratios indicated that the principal source of PAHs in street dust of Jeddah is pyrogenic, mainly traffic emission. Benzo(a)anthracene/ chrysene (BaA/CHR) ratio suggests that PAHs in street dusts of Jeddah come mainly from emission of local sources, while PAHs in RUA might be transported from the surrounding urban areas. The estimated Incremental Lifetime Cancer Risk (ILCR) associated with exposure to PAHs in street dusts indicated that both dermal contact and ingestion pathways are major contributed to cancer risk for both children and adults. Based on BaP_equivalence concentrations of total PAHs, ILCR_Ingestion, ILCR_dermal and cancer risk values for children and adults exposed to PAHs in street dust of different areas in Jeddah were found between 10⁻⁶ and 10⁻⁴, indicating potential risk. The sequence of cancer risk was TRA > URA > MCRA > SUA > REA. Only exposure to BaP and DBA compounds had potential risk for both children and adults.

Construction project management and cost management is a difficult process that affects the overall success of construction projects. The success of a construction project can be assessed according to key performance indicators (KPIs). Cost savings and cost optimization over the life of a construction project is one of these KPIs. Cost management is largely performed through intelligent information technology in the construction industry. Information systems and information technologies have seen an increase in use in the management of construction projects. The same goes for cost management. Several studies mentioned in the paper point to this increase in use in recent years also in the management of costs at various stages. Many studies point to the use of information technology and software applications in the field of cost management. Still, to a large extent, there are no surveys focused on the analysis of the impact and impact factor of information technology on cost savings or cost optimization in various phases of construction projects. The research discusses the issue of the impact of information technology on cost management in various phases of a construction project. The main goal of the research is to analyze the influence of information technology factors on cost savings and optimization in individual phases of a construction project. Several statistical methods were used in the research. The resulting model of information technology impact factor was created based on data processing and the use of the AHP method.

This paper addresses pastoral resilience by drawing out the coping strategies and mechanisms utilized by the Maasai Pastoralists through a food system approach, based on the study findings of an anthropological study of pastoralism in Laikipia County, Rift Valley, Kenya. This paper is guided by the specific objectives aimed at establishing actors and their roles, and describing the institutional settings and changes in pastoralism. Using a new institutionalism approach, the paper focuses not only on the actors and their roles in pastoralism but also on how internal and external forces regulate access and use of common pool resources (CPRs) resulting in sustainability of the food system. We argue that this has an impact on the practice of pastoralism that continually defines and redefine the actors’ roles as well as elicit the value of pastoral economies and benefits accrued to a wide range of actors hence reinforcing pastoral resilience. The study also identified institutional settings and changes that lead to pastoral survival resulting from the country’s devolved system of governance. Data collection was through in-depth interviews, key informant interviews, focus group discussions and unstructured observations in the pastoral regions. The findings reveal that actors at the household, state, non-state, and service providers have developed varied coping strategies and mechanisms that sustain pastoralism. The study also identified institutional settings and changes that promote pastoral resilience; notably, private land ownership patterns, co-management of livestock markets, commercialization of herding, decentralization of livestock services, holistic management of pasturelands and the use of water-shed management plans. As a result, increased scholarship and advocacy in regards to the concept of co-management of livestock markets, is recommended as a means of understanding pastoral resilience that the food system exhibits.

Gelatin industry residues are increasingly used as fertilizer and soil conditioner. However, correct residue dosage is critical for grass development and minimizing environmental impacts. This randomized block design study determined adequate dosage of Mixed Gelatin Sludge (MGS) for Marandu grass production in wet/dry seasons in Brazil. Five MGS levels (0%–200% of required nitrogen) were compared to mineral fertilizer. Agronomic/productivity characteristics, bromatological composition, macro/micro-nutrient composition of leaves, and soil chemical attributes were evaluated. Agronomic/productivity characteristics were influenced by MGS dose in both dry/rainy seasons, except for leaf blade pseudostem ratio and percentage of leaves/pseudostem. Bromatological composition was influenced by MGS doses in dry/rainy seasons except for dry/mineral material quantities. Marandu leaf tissue chemical composition was significantly influenced by MGS dose, except for potassium, boron, and iron. Chemical composition of four soil layers between 0–50 cm influenced GMS dose, except for pH, organic matter, magnesium, copper, manganese, and zinc. GMS dose for Marandu production should be 200% of nitrogen (N) requirement. GMS application increased productivity/quality of Marandu grass. Macronutrients (N, phosphorus) and micronutrients (Ca, Mg, S, Cu, and Zn) increased in Marandu grass and in the soil (Ca, S, and Na). Increased sodium (Na) level was not limiting.

Grasslands are at risk of degradation due to unsustainable management practices and climate change. Sustainable grassland soil management can promote ecosystem service delivery and improve the resilience of the entire grassland ecosystem to anthropogenic change. Here, we re-view the principal soil quality indicators (SQIs) and how they have been used to evaluate the sustainability of different grassland management practices globally. We then discuss sustainable grazing management practices, before reviewing some novel grassland species which may im-prove grassland resilience with relevance for grassland management in Europe and the UK. We also give an overview of current sustainable grassland management methods and their assessment at field scale. From this, we suggest that sustainable Grazing Management Plans (GMPs), together with the testing of drought-resistant grass species and appropriate SQIs monitoring, is key to increasing resilience of grassland ecosystems to anthropogenic change.

In the context of the pandemic caused by Covid-19, an important aspect that was affected and changed was the way people communicate. Communication efficiency can be improved by using modern technologies, for example: mobile devices, digital audio and video platforms, text platforms, social media and more. For further economic success, digital skills are needed not only for executives, but also for managers, in order to be able to lead teams and avoid situations of stress and tension in the virtual environment. This scientific paper includes a primary research of how the pandemic affected the communication at the workplace. For this a qualitative analysis was first performed, in which the interview was used as a working tool. Next, on the basis of a questionnaire, a hypothesis was formulated and validated afterwards through multiple linear regression. This research highlighted the particularly important role of communication and, in this context, the role of the remote team leader. In order to keep the team motivated and interested in the virtual environment, the manager must use modern tools to motivate, support and express his appreciation when the team, respectively the members of his team, achieve their goals successfully.

Diabetes mellitus (DM) and obesity account for the highest burden of non-communicable diseases. There is increasing evidence showing therapeutic patient education (TPE) as a clinically and cost-effective solution to improve biomedical and psychosocial outcomes among people with DM and obesity. The present systematic review and meta-analysis presents a critical synthesis of development of TPE interventions for DM and obesity and the efficacy of these interventions across a range of biomedical, psychosocial and psychological outcomes. A total of 54 of these RCTs were identified among patients with obesity and diabetes and were thus, qualitatively synthesized. Out of these, 47 were included into quantitative synthesis. There was substantial heterogeneity in reporting of these outcomes (I²= 88.35%, Q= 317.64), with significant improvement (SMD=0.36, 95% CI: 0.23 to 0.49) noted in biomedical outcomes in the intervention group. The effect sizes were comparable across interventions delivered by different modes and delivery agents. These interventions can be delivered by allied health staff, doctors or electronically as self-help programs, with similar effectiveness (P < 0.001). These interventions should be implemented in healthcare and community settings to improve health of patients suffering from DM and obesity.

Solid-state lighting has been replacing conventional lighting in the market, raising concerns for implementing an efficient end-of-life management system. Since LED waste streams have not been quite dominant, characterization studies (product-level characteristics, component-wise information, bill of materials, diversity, and differences) are inconsistent and having substantial gaps. This study investigates the end-of-life LED lamp literature, focusing on the bill-of-materials, and reveals that the characterization procedure suffers from a severe lack of sample representativeness. Consequently, characterization results are widely varied and not generalizable. Moreover, most of the studies did not inform and document the detailed sample characteristics, precluding the possibility of identifying reasons for variation. Combining available information from the recent studies, we present a mass distribution at the component level, exemplifying the prospect for meeting EU regulatory limit and the need for more insight at the lamp and component level. To fill the disconnection between lamp level characteristics and component and material content, we propose a characterization protocol that carefully documents lamp, component, and material level information by establishing a lamp-component–material composition nexus. The protocol may help researchers, policymakers, and industrial stakeholders conduct a systematic characterization, analyze complexities and prepare for a sustainable solution.

Rapid technological advancements in information communication technologies have enabled water resource data collection at greater spatial and temporal scale. However, this water data is often limited to the purposes of its primary collection, and limits decisions made by stakeholders towards sustainable urban water management. This empirically focused research paper examines how water practitioners involved in strategic planning can capture additional values from integrating different water data. Furthermore, the perception of 22 urban water practitioners across Australia are presented, regarding the importance of and difficulty in using water data for strategic planning, and the necessary steps for achieving integrated water management practices. Interviewees perception revealed gaps in available water resource data (i.e. water quality, ground water, stormwater, and urban water use), and limitations of industry guidelines for operating within existing governance frameworks. Overall, the research highlights the Australian urban water sector’s perception of water data’s crucial role in representing stakeholders interest; however, changes made in water data’s collection are required for an integrated water management approach. Implications for future open water data standard are discussed.

The move towards a new Circular Economy (CE) economic model has been advocated and supported in Portugal, however, there is limited research on this topic. To address this gap, a quantitative research based on an online survey was carried out among 99 Portuguese organizations, encompassing a wide range of sectors and sizes. The results show that CE is regarded as a strategic and relevant issue for profitability and value creation. Furthermore, the perception that it requires the adoption of new business models in addition to the classical “reduce, reuse, and recycle” approach is growing. Moreover, based on the hypotheses raised, results suggest that the level of CE adoption is positively impacted by the status of the EMS (Environmental Management System) certification and the willingness to improve the environmental performance and achieve a sustainable business model. However, CE activities are still relatively modest and a friendlier context (fiscal, legal, organizational, etc.) and the stronger support from supply chain agents and consumers are required. Future research should focus on how to design and shape the transition from a linear to a CE economy, and to ascertain if the positive attitude towards CE is materialized in changing the way business is done.

In the contemporary construction management, poor project performance, cost overrun, and low-quality construction have become a central point of attention for improving project performance including information, interaction and communication management. virtual design and construction and building information modelling play indispensable role in improving the project performance. The aim of this study is to propose a Virtual Information Modeling as a novel information and communication technology method with potential to overcome problems in the construction industry. Using one-sample t test with Kolmogorov-Smirnov approach, we analysed data collected from structured questionnaire survey involving project managers working at architecture, engineering and construction industries in Tehran, Iran. The results suggest that the most important benefits and challenges of using Virtual Information Modeling are related to the area of integration, and implementation of Virtual Information Modeling has the greatest impact on this area of project management knowledge. Thus, integration should be considered a top priority for construction companies implementing Virtual Information Modeling in their projects. Policymakers should understand that careful management of virtual information is essential for improving the performance of projects and enhancing the process efficiency.

The Internet-of-Things (IoT) enables enterprises to obtain profits from data but triggers data protection questions and new types of cyber risk. Cyber risk regulations for the IoT however do not exist. The IoT risk is not included in the cyber security assessment standards, hence, often not visible to cyber security experts. This is concerning, because companies integrating IoT devices and services need to perform a self-assessment of its IoT cyber security posture. The outcome of such self-assessment needs to define a current and target state, prior to creating a transformation roadmap outlining tasks to achieve the stated target state. In this article, a comparative empirical analysis is performed of multiple cyber risk assessment approaches, to define a high-level potential target state for company integrating IoT devices and/or services. Defining a high-level potential target state represent is followed by a high-level transformation roadmap, describing how company can achieve their target state, based on their current state. The transformation roadmap is used to adapt IoT risk impact assessment with a Goal-Oriented Approach and the Internet of Things Micro Mart model.

In modern times, sustainability in supply chain management is one of the keys to boosting the performance of the supply chain, and it enables the accomplishment of SSCM. It has been found in recent years that SSCM with assist of industry 4.0 applications, can benefit splendid productivity and efficiency in the supply chain. The numerous industry 4.0 applications that are involved are Artificial intelligence (AI), Machine Learning (ML), Internet of Things (IoT) Big Data Analytics (BDA), etc. Industry 4.0 with SSCM has gained a lot of interest from various authors and scholars across the world. Healthcare is one of the most critical sectors due to its importance in handling public health. More recently, the COVID-19 pandemic and other viruses (SARS and Ebola) have highlighted supply chain vulnerabilities that are further mitigated by their lean and globalized structures. Covid-19 underlined the need for supply chain visibility problems within the healthcare sector. When the need for medical supplies became urgent and global distribution was disrupted, companies faced the consequences of needing the technology, systems, and plans in place to correctly predict the onslaught. One report shows that about 94 percent of Fortune 1000 companies reported supply chain disruptions due to the COVID-19 global outbreak. Existing studies have discussed supply chain issues and the importance of AI in addressing these challenges. AI, like Industry 4.0 in the healthcare supply chain, is proving to be a game-changer. This paper aims to review and present the various aspects of SSCM and industry 4.0 applications to get a comprehensive literature review, which contains the analysis of multiple articles published from 2010-2020. In addition, the various challenges SSCM and industry 4.0 applications face are identified and discussed. Also, the impact of Industry 4.0 and sustainable practices brings together the healthcare supply chain. This study will help in getting a good understanding of the different industry 4.0 technologies that are important for setting up SSCM.

Improving HIV testing efficiency saves financial and material resources for health. We conducted a retrospective secondary data analysis of routinely collected HIV risk screening program data in Uganda, from October to November 2019, to determine the performance characteristics of the adolescent and adult HIV risk screening tool in public health facility settings. A total of 19,854 clients had been screened for HIV testing eligibility and tested for HIV. The overall positivity rate (cluster weighted prevalence of HIV) among those screened was 4.5% (95% CI: 4.1%-4.8%) versus 3.71% (95% CI: 3.06-4.50) among those not screened. The sensitivity and specificity of the risk screening tool were 90.7% (95% CI: 88.4%, 92.7%) and 75.8%, (75.2-76.4) respectively. With screening, the number needed to test to identify one PLHIV was reduced from 27 to 22. Although risk screening would have led to a 24.5% (4,825/19,704) reduction in testing volume, 9.3% (68/732) of PLHIV would have been missed, being misclassified as not eligible for testing. The cost per PLHIV identified fell by 3% from $69 without screening to $66.9 with screening. We recommend the use of scientifically validated HIV risk screening tools, and a need to explore the use of HIV self-testing as a test for tirage.

With the growing of university chemistry experiment projects, scientific research personnel, specialized equipment, laboratory accident is increasing yearly. And accident data lacks a safety platform to store related information and cannot be guaranteed for efficient conditional sharing. To solve these problems, we designed a laboratory accident system to store, share related data and predict risk level. In this paper, we manually collected chemistry laboratory accidents by python software and class assignments, then analyses risk factor variables using Spsspro, finally established a prediction model using Stata. We intended to register laboratory related data into proposed chemistry accident system based on data ownership safety architecture. The chemistry accident system can break data barriers using confirmation and authorization key technology to trace non-tampered data source in real time when emergency accident happens. Meanwhile, our proposed system can use our designed accident risk model to predict risk level of any experiment project. It can also recommend appropriate safety education models.

The novel coronavirus (COVID-19) was first reported in the U.S. on December 29, 2019 and has spread rapidly throughout the country, affecting individuals with varying severity due to their risk status. According to the Centers for Disease Control and Prevention, it is estimated that 45.4% of US adults are at higher risk for complications from coronavirus disease because of cardiovascular disease, diabetes, respiratory disease, hypertension, or cancer. In this study, we developed a mathematical model to assess the impact of a COVID-19 vaccine among low and high risk groups. Numerical simulations shows vaccinating both low and high risk groups simultaneously, rather than prioritizing the vaccine on high risk group only, further reduces the daily mortality. The result supports the need for an aggressive vaccination program, regardless of whether individuals are within the low or high risk population.

Flood is identified as one of the major disasters in the world; it destroys both human and properties across the world, where lives are lost, properties, public infrastructure, farmlands and agricultural produce with farm crops carted away as a result of flood disaster. Studies revealed that the flood in itself is not the danger, but the level of human vulnerability to flooding disaster risk, which enhances its destructive capabilities. However, based on the challenges poses by flood disaster risk, this research identifies Ala river in Akure as a potential cause of flood, considering its location and other human activities around the river. Therefore, the research used Ala-river a case study to identify and mapped out areas susceptible to flood disaster risk. The research made use of both literature review and conducted goe-data gathering with the application GIS-computer database to retrieve georeferencing relevant data from the fieldwork in the study area of Ala-river basin to mapped out locations vulnerable to achieve the research aim. The research adopted a Geo-mapping of the vulnerable area to Ala-River basin using arc-GIS tool in combination with other software such as IKONAS and OLI (Operation Land Imager) for the production of the study area imagery, ER-ITERIM was used for the collection of rainfall data and FAO was applied for digital soil mapping. These applications produced; the land use/land cover map, digital elevation map, buffer map using 30 meters setback, annual rainfall map, soil types map, vulnerability map and soil textural table for the study area. Analysis of the produced and generated maps shows 316 buildings vulnerability to flood disaster risk; the soil texture and types, and alternative use to which the soil types can be useful. The research recommends that demolition of the identified 316 buildings prone to flood disaster and compliance of building construction to 30 meters setback by developers. Others are the conversion of the future land setback for urban agricultural purposes and preservation of water retention areas for agricultural activities during the dry season among others. The study concludes that relevant government agencies in the State and in particular in Akure South Local Government should ensure prompt compliance and implementation of the recommendations to avoid potential flood disaster risks.

Parkinson’s disease (PD) is the most common cause of movement disorder characterized by the progressive loss of dopaminergic neurons in the substantia nigra. It is increasingly recognized as a complex group of disorders presenting widely heterogenous symptoms and pathology. Except for the rare monogenic forms, the majority of the PD cases result from an interaction between multiple genetic and environmental risk factors. The search for these risk factors and the development of preclinical animal models are in progress hand in hand, providing mechanistic insights into the pathogenesis of PD. This review summarizes the studies that capitalize on modeling sporadic (i.e. non-familial) PD using Drosophila melanogaster and discuss their methodology, new findings and future perspective.