Level Of Risk Research Articles

Risk assessment of transmission towers based on variable weight theory and matter-element extension model

Abstract The risk assessment of transmission towers is a critical approach to ensuring the safe and stable operation of power grids. In response to the increasingly frequent and severe impacts of seasonal permafrost on transmission towers in permafrost regions, this paper proposes a novel risk assessment method based on Variable Weight Theory and the Matter-Element Extension Model. By incorporating key influencing factors—such as the number of freeze-thaw cycles, soil moisture content, temperature fluctuations, soil dry density, melting settlement coefficient, and porosity ratio—an indicator system tailored to risk assessment in seasonal permafrost regions is established. Utilizing the Matter-Element Extension Model, this approach applies Variable Weight Theory to integrate both the best-worst method and the entropy weight method for calculating subjective and objective indicator weights. The risk level of the towers is then determined by their proximity to risk thresholds. Finally, a case study involving transmission towers in a specific region of a province in China is presented, where the assessment results are compared with the actual conditions to validate the rationality and effectiveness of the proposed method.

Determination of Operator Potential Risk Level from Pesticide Applications in Hazelnut Orchards

Determination of Operator Potential Risk Level from Pesticide Applications in Hazelnut Orchards

A comprehensive framework for evaluating and predicting investment risks in renewable energy projects: a case study of Maynak hydropower station

ABSTRACT This study introduces a holistic analysis framework designed to evaluate and predict the investment risks associated with foreign renewable energy initiatives. This framework aims to reduce the uncertainties inherent in renewable energy projects. To achieve this, we utilize the variable weight matter-element extension model to establish the project’s fundamental reliability function. We then refine this model by incorporating evidence theory to assess the project’s risk level and derive precise risk index measurements. We utilize the GM model to forecast potential future risks associated with the project. In addition, a case study is presented on the risk assessment and prediction for the Maynak Hydropower Station. Our findings reveals that the project encountered significant investment risks in 2008, 2014, 2020, and 2022. Key risk indicators include political turmoil，policy change，imperfect legislation，cultural risk，exchange rate changes，technical risks and management risks. Furthermore, the investment risk level declined from 2023 to 2027, with our risk measurement outcomes closely aligning with actual conditions, thereby validating the effectiveness and applicability of our model.

A new framework for assessing and dealing with heat risk from an urban resilience perspective

Cities are exposed to increasing environmental threats, having undergone extensive land development and rapid urbanization. Clarifying the effects of urban resilience to risk can provide effective guidance for mitigating heat risk. To our knowledge; however, quantifying these effects from an urban resilience perspective has not been considered in previous studies. Here, we proposed the adaptation-resistance-response heat-related urban resilience assessment system. The system is integrated with the minimum cumulative resistance model to construct a novel heat risk assessment framework. A case study in Shenzhen, China, showed that resilience to heat had a high degree of spatial heterogeneity. More than half of the study area was at a moderate or high level of risk. Our study provided new insights into the differences in heat risk between urban and rural areas. The heat-risk gap between urban and rural areas was lower than that indicated by surface temperatures, due to the diffusion and attenuation of high temperatures. In addition, we discussed the application of resilience to risk governance and emphasize five governance models for risk zoning. The proposed framework facilitated a better understanding of the effect of resilience on risk mitigation, and our results can be used to guide urban planning and risk management.

Childhood maltreatment and adult aggression: The moderating role of neurocognitive ability and substance use

BackgroundAchieving positive intervention outcomes for aggressive behaviour in adulthood is challenging. This difficulty is enhanced by the complex presentations of those engaging in such behaviours and the impact this has on their engagement with interventions. ObjectiveThis study assessed the cumulative impact of childhood maltreatment, substance use, and neurocognitive ability (working memory, cognitive flexibility, decision making, response inhibition, and cognitive control) on aggressive behaviour in adulthood. Participants and settingAdult participants (N = 179; 69 % female) recruited from the community, and clinical and forensic services, aged 18 to 81 (M = 40.5, SD = 15.9). MethodsParticipants completed an online Qualtrics survey and remote neurocognitive testing via Inquisit. ResultsWe implemented an a priori approach, assessing three-way interactions between childhood maltreatment, substance use, neurocognitive ability, and aggression. No three-way interactions were significant. We then utilised a data-driven modelling approach, using automatic linear forward stepwise modelling to identify the most important variables for predicting aggression. Four were significant: physical maltreatment (b = 0.053, p < .001), drug use risk level (b = 0.015, p < .001), poorer response inhibition (b = 0.001, p = .016), and the interaction between poorer response inhibition and physical maltreatment (b = 0.205, p = .017). ConclusionsPhysical maltreatment in childhood, drug use risk level, and response inhibition impact significantly on adult aggression, indicating a need for early intervention for children who have experienced maltreatment. Consideration should be given to how maltreatment in childhood may impact on ability to engage with interventions as an adult, particularly response inhibition difficulties that may hinder skill implementation.

Preventing cardiovascular disease in at-risk patients: Results of a pilot behavioural health programme in general practice

Background The ‘High-Risk Prevention Programme’ (HRPP) involved a six-week health behaviour change programme based in general practices and aimed to address cardiovascular disease (CVD) risk in disadvantaged Irish communities. Objectives This pilot study aimed to establish the HRPP’s likely effectiveness and acceptability to inform the development of a future definitive trial. Methods The HRPP was conducted at six general practices in disadvantaged areas in the Ireland East region. Patients with high CVD risk were recruited by participating practices and were allocated to either a General Practice Nurse (GPN) or Health Promotion Professional (HPP) led programme focusing on positive health behavioural change. Baseline and 12-month follow-up data were collected to capture the HRPP’s likely effectiveness in promoting health outcomes and health behavioural change. Results The HRPP programme was completed by 270 patients. Out of these 270 patients, 245 (90.74%) completed baseline assessments, and 176 (65.19%) completed follow-up assessments at 12 months. Baseline data indicated a high level of CVD risk among patients and follow-up demonstrated positive change in several areas, especially weight (−1.95 kg, p < 0.001), BMI (−0.72, p < 0.001), exercise during the last week ( p <0.001), and consumption of healthy fats in the HPP group (+60%, p < 0.001). Conclusion The HRPP was a much-needed pilot intervention, and positive results were seen in both GPN and HPP arms, especially with regards to weight loss, exercise, and dietary improvements. Future definitive trials of the HRPP are likely to be effective and acceptable in terms of combatting these issues among high-risk patients.

Air Route Design of Multi-Rotor UAVs for Urban Air Mobility

UAVs will present significant air traffic in the urban airspace in the future, which brings new challenges to urban air traffic management and control. This paper presents an air route design scheme for multi-rotor UAVs in urban airspace to enable UAV operations at orderly levels. The air routes include legs and intersections, which are the three-dimensional channels of UAV flight. Based on the concept of structured and layered urban airspace, the cylindrical pipeline flight leg is designed, and the operation concept, characteristic parameters and flight procedures of along-road and roundabout intersections are proposed. By defining UAV conflict risk and intersection service level metrics, the operation situation of UAVs is quantitatively evaluated. Taking an urban transportation scenario as a case, the proposed route design scheme is simulated in different scale UAV operating scenarios. The results show that the number of UAVs at the intersection is positively correlated with the conflict probability, the number of crossing routes is negatively correlated with the intersection passing rate, and the UAV arrival rate is positively correlated with the intersection average passing time. The along-road type intersection is suitable for the area with fewer crossing routes and sparse UAVs, while the roundabout type intersection is adapted for the area with more crossing routes and dense UAVs. This research provides a new idea for urban UAV air route design, which is helpful in promoting the standardized management of UAVs and accelerating the integration of UAVs into urban airspace.

Prediction of aviation safety incident risk level based on ECSDNN

Prediction of aviation safety incident risk level is an important means of active risk management. Considering the high-dimensional complexity and class imbalance of massive aviation safety incident data, a prediction method for aviation safety incident risk level based on integrated cost-sensitive deep neural network (ECSDNN) is proposed. The feature representation of aviation safety incident data is realized by using the method of embedded coding of categorical attributes and splicing of numerical attributes; the cost-sensitive matrix and cost-sensitive loss function are designed by comprehensively considering the misclassification ratio and fixed cost, and the base classifier model based on cost-sensitive deep neural network (CSDNN) is constructed; the hard voting method is used to integrate multiple base classifiers with different parameters and performances to construct the integrated prediction model ECSDNN for aviation safety incident risk level. The experimental results on the Aviation Safety Incident Reporting System (ASRS) dataset show that compared with the optimal prediction ability of the baseline algorithm, the prediction accuracy of the ECSDNN model is improved 4.51%; compared with the single CSDNN base classifier, the prediction accuracy is improved 3.17%.

Feasibility of Emergency Flood Traffic Road Damage Assessment by Integrating Remote Sensing Images and Social Media Information

In the context of global climate change, the frequency of sudden natural disasters is increasing. Assessing traffic road damage post-disaster is crucial for emergency decision-making and disaster management. Traditional ground observation methods for evaluating traffic road damage are limited by the timeliness and coverage of data updates. Relying solely on these methods does not adequately support rapid assessment and emergency management during extreme natural disasters. Social media, a major source of big data, can effectively address these limitations by providing more timely and comprehensive disaster information. Motivated by this, we utilized multi-source heterogeneous data to assess the damage to traffic roads under extreme conditions and established a new framework for evaluating traffic roads in cities prone to flood disasters caused by rainstorms. The approach involves several steps: First, the surface area affected by precipitation is extracted using a threshold method constrained by confidence intervals derived from microwave remote sensing images. Second, disaster information is collected from the Sina Weibo platform, where social media information is screened and cleaned. A quantification table for road traffic loss assessment was defined, and a social media disaster information classification model combining text convolutional neural networks and attention mechanisms (TextCNN-Attention disaster information classification) was proposed. Finally, traffic road information on social media is matched with basic geographic data, the classification of traffic road disaster risk levels is visualized, and the assessment of traffic road disaster levels is completed based on multi-source heterogeneous data. Using the “7.20” rainstorm event in Henan Province as an example, this research categorizes the disaster’s impact on traffic roads into five levels—particularly severe, severe, moderate, mild, and minimal—as derived from remote sensing image monitoring and social media information analysis. The evaluation framework for flood disaster traffic roads based on multi-source heterogeneous data provides important data support and methodological support for enhancing disaster management capabilities and systems.

Susceptibility to Translational Landslides in Ecuador Caused by Changes in Electrical Permittivity of Andepts Soils Using Software-Defined Radar for Detection

Landslides are widespread and global geological disasters, affecting millions of people and causing numerous deaths each year. Despite technological advances, it is still difficult to accurately prevent landslides. Due to its geography and climatic conditions, Ecuador has been significantly affected by landslides, and the city of Penipe remains one of the most affected. For this reason, a low-cost SDRadar system was designed to detect translational landslide risk levels by measuring the electrical permittivity of Andepts subtype soils. Controlled laboratory tests were performed with soil samples to relate permittivity values to landslide risk levels, and subsequently field tests were carried out in Penipe to determine the efficiency of the methodology. The results showed that moderate humidity is important for soil compaction, regardless of the degree of sloping. However, with permittivity values lower than 1.5 or higher than 20, the risk of landslides is very high on slopes greater than 45°. These results were compared with records of the serious landslides that occurred in June 2024 in Ecuador, in which rainfall intensity values similar to those obtained in this study were recorded, suggesting that this system can prevent future disasters.

Influence of spin-off decision on financing risk: Empirical insight from Indonesian Islamic banks

Background Spin-offs play a significant role in organizational development strategies, particularly in Islamic banking, by fostering entrepreneurship, innovation, and Shariah-compliant management practices. Indonesia stands as a pioneer in implementing the dual banking system and has established a spin-off policy to foster the growth of Islamic banking. This study investigates whether the spin-off decision has a significant impact on financing risk in Indonesian Islamic banks. Methods Financing risk is measured by the non-performing financing ratio, while the spin-off decision is represented by a dummy variable equal to 1 for the post-spin-off period and 0 for the pre-spin-off period. This study utilizes data from semi-annual reports of 35 Indonesian Islamic banks and analyzes it using a dynamic panel model with the Generalized Method of Moments (GMM). Results The findings reveal that spin-offs significantly reduce financing risk, thereby enhancing the financial resilience and boosting investor appeal. Notably, this implies that Islamic banks operating as Islamic windows exhibit a higher level of financing risk compared to fully-fledged Islamic banks. Furthermore, a noteworthy pattern emerges that spin-off Islamic banks with substantial assets demonstrate greater risk in comparison to their counterparts with more modest assets. System GMM also confirmed the result. Conclusions Islamic banks can significantly reduce their financing risks by establishing independent Islamic banks, or spin-offs. Unlike Islamic windows, which are typically integrated within conventional banks and face higher risk levels, standalone Islamic banks offer greater flexibility and control over their operations.

New dietary trends and alternative proteins: the emergence of novel food allergens.

New dietary trends driven by environmental and health considerations will undoubtedly lead to the emergence of novel food allergens. Assessment of the allergenic risk of new or modified protein-containing food sources and ingredients, as well as surveillance of emerging food allergies, is then required. Developments of in silico and in vitro models apprehending protein capacity to cross-react with other homologous proteins and to induce a de novo allergic sensitization are ongoing to better integrate multiple parameters such as 3D structural information or major histocompatibility complex class II (MHC-II) presentation propensity. However, the effects of food matrices and food processing still need to be addressed in these models. Consequently, clinical and postmarket surveillance remain of critical importance to alert on emergent food allergies, which are modulated by regional dietary practices. Monitoring of the emergence of food allergens requires close collaborations between allergologists, consumers, patient associations and food safety authorities. We also need to get a consensus on an acceptable level of allergenic risk that offers the possibility to develop and market innovative and sustainable food products.

Registered sex offenders’ experiences of home visits in England &amp; Wales: are the police expected to integrate “risk” with “desistance”

Purpose In England and Wales, adult male registered sex offenders (RSOs) are risk assessed and managed using a tool known as the Active Risk Management System; a risk assessment designed specifically for police management of RSOs and carried out by a specialist group of police officers known as Management of Violent or Sexual Offenders (MOSOVO) at the RSO’s home, known as “the home visit”. The purpose of this paper is to explore RSOs views of the home visit and risk assessment and to make recommendations to MOSOVO to improve future home visit &amp; risk assessment practice. Design/methodology/approach This study aimed to examine a sample of adult male RSOs’ views of the risk assessment and home visit process. Three police forces in England and Wales agreed to facilitate the sampling of 10 RSOs who varied in their level of risk, namely, low, medium, high and very high. Findings Three themes were developed from the analysis: anxiety and shame; perceptions of the first home visit; and the property search and observations. This paper discusses these experiences in light of the growing call for MOSOVOs to both manage risk and assist desistance and present recommendations for improving both the home visit and risk assessment practice. Originality/value To the best of the authors’ knowledge, this is the first study to understand and explore RSOs views of the home visit and risk assessment process.

Unaccompanied homelessness among high school students across ten states: prevalence and risk in multiple domains

ABSTRACT Unaccompanied homelessness during adolescence is a risk factor for varied poor outcomes, yet enumeration efforts struggle to provide feasible results and few analyses consider how risk might differ for this group. We consider data from the 2019 Youth Risk Behavior Survey from 10 states that asked about unaccompanied homelessness and sleeping arrangement. Students who experienced any form of homelessness were at higher risk for poor outcomes and other risk experiences. Few students reported both unaccompanied homelessness and usually sleeping in a homeless situation. Youth experiencing unaccompanied homelessness had higher risk for alcohol problems and lower risk for severe drug use and poor grades compared to students who experienced other forms of homelessness; otherwise they had similar levels of risk for poor outcomes. Results are consistent with the view that students who experience unaccompanied homeless are a distinguishable subpopulation of students who experience homelessness and are at high levels of risk of poor outcomes.

Association between dietary fiber intake and chronic kidney disease in adults with and without hypertension in the United States: a cross-sectional study of NHANES 2009–2020

While previous research has highlighted the potential advantages of increasing dietary fiber intake (DFI) for managing hypertension and chronic kidney disease (CKD), there is a gap in large-scale empirical studies examining the relationship between DFI and CKD among hypertensive and nonhypertensive cohorts independently. This study involved 22,871 participants sourced from the NHANES database spanning 2009 to 2020, who were divided into hypertensive (n = 9,861) and nonhypertensive (n = 13,010) groups. The analysis revealed a significant inverse correlation between DFI and CKD prevalence across the sample after adjusting for various covariates (OR = 0.98, 95% CI: 0.97–0.99, p = 0.001). Within the subset of hypertensive individuals, this inverse association mirrors the findings of the overall sample, indicating that a higher DFI was associated with a reduced occurrence of CKD (OR = 0.97, 95% CI: 0.96–0.99, p < 0.001). However, this correlation was not detected in the nonhypertensive group (OR = 0.99, 95% CI: 0.98–1.01, p = 0.285). The RCS analysis further confirmed a pronounced nonlinear inverse relationship between DFI and CKD prevalence in both the entire cohort and the hypertensive group but not in the nonhypertensive group. Further scrutiny of the hypertensive group revealed that individuals with a higher DFI had 33% lower odds of CKD progression for the moderate risk level and 36% lower odds for the high to very high risk level. Subgroup analyses confirmed the consistency of these relationships across various demographics. In summary, this investigation revealed a significant inverse relationship between DFI and CKD prevalence in US adults with hypertension, a relationship not observed in nonhypertensive individuals.

Impact of graphical display on the intention to undergo risk-reducing salpingo-oophorectomy and mastectomy in individuals positive for BRCA pathogenic variant

The BRCA1/2 pathogenic variant (PV) increases the risk of breast and ovarian cancer; thus, risk-reducing salpingo-oophorectomy (RRSO) and mastectomy (RRM) are recommended. We evaluated the effects of the graphical display of cancer risk compared with those of numerical presentation on the decision-making for risk-reducing (RR) surgery. A total of 471 women representing the Korean population were recruited. The lifetime risk of breast/ovarian cancer were given numerically followed by graphically in hypothetical BRCA1/2 PV-positive cases. Subsequently, the study participants were asked for their willingness to undergo RRSO/RRM. When the ovarian cancer risk was shown as 44.0%, the percentage of study participants who chose RRSO was 41.0% after numerical presentation versus 39.9% after graphical display, of which the difference was not significant. When the breast cancer risk was presented as 72.0%, 30.4% of the participants opted for RRM under numerical presentation, whereas this increased to 38.6% under graphical display, of which the difference was significant (p < 0.0075). The average levels of the cancer risk which study participants consider RR surgery were 57.1% for ovarian cancer and 60.6% for breast cancer. This suggests that the impacts of different formats of risk communication on decision about RRSO or RRM may be different by the absolute levels of ovarian or breast cancer.

Sex, gender and human rights: essential components of inclusive medical research

ABSTRACT Much of past medical research has been sex and gender ‘blind’ and has failed to take account of gender norms and practices that place men and women at different levels of risk of certain diseases. Further, non-binary, trans and people with intersex characteristics have been especially marginalised in research practices. Other forms of discrimination based on race, disability and socio-economic disadvantage have cut-across and exacerbated these research gaps. This paper considers that medical codes of ethics alone are insufficient to address sex and gender disparities in medical research and suggests that adopting a human rights approach to medical research provides a systematic way to collect, analyse and report on sex and gender data in ways that are person-centred, empowering and participatory.

ASSESSING FOOD SAFETY AWARENESS AND PRACTICES AMONG STREET FOOD VENDORS IN KATSINA STATE, NORTH WESTERN NIGERIA

Food safety is a critical global issue, with contaminated food posing serious health risks, particularly to vulnerable populations such as children under five, the elderly, and the sick. This study examined food safety practices among street food vendors in major towns of Katsina State. Using structured questionnaires and a multi-stage sampling technique, data were collected from a total of 316 street food vendors to assess vendors' awareness and adoption of food safety measures. Descriptive statistics and traffic light model were used to analyse the data. While vendors demonstrated high awareness of basic hygiene practices like washing utensils and avoiding work when ill, the adoption of other crucial practices, such as using hand gloves and maintaining clean selling locations, was found to be low. This gap between awareness and practice highlights the need for targeted interventions, including training programs and public awareness campaigns, to bridge the knowledge-behaviour gap. The traffic light model categorized food safety risk to levels, revealing that many vendors operate at high to moderate risk levels. These findings underscore the importance of continuous monitoring, feedback, and enforcement of food safety regulations. Recommendations include enhancing access to resources, providing incentives for good practices, and implementing regular health and safety audits. This can significantly reduce foodborne illnesses, ensuring safer food consumption, and supporting national health and economic development through safer trade and tourism activities. This study contributes to the on-going discourse on food safety in developing regions and highlights critical areas for policy and practical interventions to safeguard public health.

Sodium-Glucose Co-transporter-2 Inhibitors in Type 1 Diabetes Mellitus: The Framework for Recommendations for Their Potential Use.

The growing prevalence of overweight/obesity, the persistence of inadequate glycemic control among themajority of affected individuals, and thestill unacceptably high risk of cardiovascular morbidity and mortality among population with type 1 diabetes mellitus (T1D), impose an urgent need for theintroduction of non-insulin glucose-lowering agents in the therapeutic armamentarium. Given thattheir antihyperglycemic mechanism of action is independent of endogenous insulin secretion and thatthe observed cardio-renal benefits are unrelated to their glucose-lowering properties, one can speculate that the use of sodium-glucose co-transporter-2 inhibitors (SGLT2is) could provide benefits in T1D, similar to the ones observed among individuals with type 2 diabetes mellitus, chronic kidney disease (CKD), and heart failure. Available evidence from randomized controlled trials suggests that treatment with SGLT2is as adjunct to insulin in T1D results in modest reductions in glycated hemoglobin and body weight. Additionally, SGLT2is ameliorate albuminuria, and thus delay or prevent thedevelopment of CKD inT1D. However, use of SGLT2is is associated with an increased risk of diabetic ketoacidosis (DKA) in T1D. This commentary aims at providing a framework for practical recommendations regarding the potential use of SGLT2is in adults with T1D, based on the individual's risk level for DKA development, the presence of inadequate glycemic control and related cardio-renal complications.

Sovereign CDS Spread and Term Structure Forecasting Based on Neural Network

The article aims to forecast credit risk for BRICS countries using daily credit default swaps (CDS) spreads obtained from Datastream data base from 2018 to 2023. Our approach consists, first, of forecasting the CDS spread in order to estimate the forecasted CDS term structure. The general regression neural network (GRNN) is used to predict the CDS spread. By checking the accuracy of the prediction, the results show that the GRNN model can be recommended as an effective forecasting tool for CDS spread. Second, the predicted spreads are used to estimate the forecasted CDS term structure using the Nelson–Siegel model. The results show that for Russia, overall, the CDS spreads in the long term are less than those in the short term, which implies that the future outlook is more optimistic, given the events that occurred during the study period, but it still retains the highest level of credit risk compared to other countries. Unlike Brazil, India and South Africa, the future outlook is more pessimistic. For China, the term structure is unstable; in the short term, there is a tendency to reduce the risk, but for longer horizons, the risk will increase. Thus, BRICS countries have different risk profiles depending on investment horizons. The study’s findings help policymakers in developing tailored risk management strategies for BRICS countries and guide investors in making informed credit investment decisions. The use of advanced forecasting tools like GRNN and Nelson–Siegel models emphasizes the importance of sophisticated techniques in enhancing financial market resilience.