Risk Framework Research Articles

‘Tis new to thee’: response to Gruenewald, Knijp, Schoenmaker, and van Tilburg

ABSTRACT In ‘Embracing the Brave New World: A Response to Demekas and Grippa’, a response to our article ‘Walking a Tightrope: Financial Regulation, Climate Change, and the Transition to a Low-Carbon Economy’, both published in the Journal of Financial Regulation, Gruenewald, Knijp, Schoenmaker, and van Tilburg claim that climate risk is a clear and present danger to financial stability that justifies imposing higher capital requirements on supervised firms. Until the current prudential risk framework is revised to fully capture climate risk, they advocate ad hoc measures, such as adjustments to risk weights, which, they believe, would have the desired effect. In this article, we argue that these claims are misguided. Given the nature of climate risk, risk assessment models cannot provide a reliable basis for calibrating capital requirements. On the basis of the evidence, prudential tools would have only a negligible impact on the transition. And the idea of adjusting risk weights for climate exposures has been abandoned—for good reasons. Ultimately, there is nothing financial regulation can do about the energy transition that an appropriately designed carbon tax cannot do better. Central banks and financial regulators should resist the pressure to take on additional responsibilities that are essentially political and that they cannot properly discharge.

Picture this! Vulnerable women’s perspectives on SDGs prioritisation

This study examines the most significant development risk women at risk of being left behind in the SDGs implementation experience. It uses the photovoice method and the social amplification of risk framework (SARF) to highlight development risks in participants’ everyday lives that increase their likelihood of being left behind. The findings demonstrate that while the challenges faced by at-risk individuals can be complex, frameworks such as the SARF can assist in understanding the underlying socio-cultural processes that intensify the effects of risks faced by those vulnerable to being left behind. The priorities identified by participants suggest that aside from targeting the needs of the farthest behind, initiatives prioritised in SDGs localisation should also harness the linkages between the SDGs to optimise the limited time and resources available for SDG implementation. The findings are relevant to identifying strategies to operationalise the ‘leave no one behind’ (LNOB) commitment effectively and efficiently in developing contexts. This article was published open access under a CC BY licence: https://creativecommons.org/licences/by/4.0 .

Early warning system for headwater risk in Johor Eco-Park: First development life cycle report

Abstract The headwater phenomenon is common in tropical waterfall and upper stream of Johor Eco-Park and threatens the visitors. Prior to that, an IoT system has been developed to issue early warning alert to the eco-park users on headwater risk. This paper presents the first life cycle report for the early headwater risk system in Gunung Pulai and Gunung Belumut Eco Park. Adapting the spiral development life cycle (SDLC), the system has completed its first complete spiral cycle whereas it has been implemented. This first SDLC report consists of four different parts: (i) problem and risk management, (ii) framework, (iii) system development, and (iv) testing and implementation. The alert on the site was triggered by the warning siren at the strategic locations. Simultaneously, the alert was also triggered in the web system and phone application to the eco-park management and prospective users to prevent from entering the premises. An auto generated report were also issued to provide potential disaster information for further action from the respective authorities. The developed system is subjected to be improved in the 2nd cycle by addressing several drawbacks including telecommunication signals, noise minimization, and threats from wild animals to the devices.

Robust, extended goal programming with uncertainty sets: an application to a multi-objective portfolio selection problem leveraging DEA

AbstractThis study presents a two-phase approach of Data Envelopment Analysis (DEA) and Goal Programming (GP) for portfolio selection, representing a pioneering attempt at combining these techniques within the context of portfolio selection. The approach expands on the conventional risk and return framework by incorporating additional financial factors and addressing data uncertainty, which allows for a thorough examination of portfolio outcomes while accommodating investor preferences and conservatism levels. The initial phase employs a super-efficiency DEA model to streamline asset selection by identifying suitable investment candidates based on efficiency scores, setting the stage for subsequent portfolio optimization. The second phase leverages the Extended GP (EGP) framework, which facilitates the comprehensive incorporation of investor preferences to determine the optimal weights of the efficient assets previously identified within the portfolio. Each goal is tailored to reflect specific financial factors spanning both technical and fundamental aspects. To tackle data uncertainty, robust optimization is applied. The research contributes to the robust GP (RGP) literature by analyzing new RGP variants, overcoming limitations of traditional and other uncertain GP models by incorporating uncertainty sets. Robust counterparts of the EGP models are accordingly developed using polyhedral and combined interval and polyhedral uncertainty sets, providing a flexible representation of uncertainty in financial markets. Empirical results, based on real data from the Tehran Stock Exchange comprising 779 assets, demonstrate the superiority of the proposed approach over traditional portfolio selection methods across various uncertainty settings. Additionally, a comprehensive sensitivity analysis investigates the impact of uncertainty levels on the robust EGP models. The proposed framework offers guidance to investors and fund managers through a pragmatic approach, enabling informed and robust portfolio decisions by considering efficiency, uncertainty, and extended financial factors.

Toward Risk Frameworks for Autonomous Systems that Take Societal Safety-related Benefits into Account

Current risk frameworks such as probabilistic risk analy-sis methodologies do not take societal safety-related benefits into account. To inform human-AI collaborative system development, this manuscript highlights the need for updated risk frameworks and suggestions for relevant considerations.

The Italian adaptation of the Mini-SIPS, a tool for early detection of individuals at clinical high risk and first episode of psychosis: A preliminary study of implementation in an Italian FEP program.

The study aims are to present the Italian adaptation of the Abbreviated Clinical Structured Interview for DSM-5 Attenuated Psychosis Syndrome (Mini-SIPS) and illustrate its implementation in a clinical setting. The Mini-SIPS was developed from the original extended version as a tool designed to identify, within the clinical high risk (CHR) framework, the DSM-5 Attenuated Psychosis Syndrome (APS) and to be implemented in clinical settings. The Mini-SIPS was translated in Italian by a Yale-certified SIPS trainer, then back-translated in English by a trained psychologist, then approved by the Mini-SIPS authors. Since September 2021, the adapted Italian version of the Mini-SIPS has been implemented at the First Episode Psychosis (FEP) Program in Ferrara, Italy. The Italian version of Mini-SIPS was successfully administered to 15 individuals subsequently referred to the First Episode Psychosis service in Ferrara. Within this sample, the tool has proven to be both an effective and efficient tool for the identification of CHR and FEP, and a valid instrument to help with the differential diagnosis. It also performed as a valuable guide for retrieving information about psychiatric history, to date the onset of APS and/or full-blown psychosis, to track the progression from CHR to psychosis or to symptoms resolution and to describe patients' pathways to care. The Mini-SIPS is an efficient and easy-to-use interview to identify the early stages of psychosis and established psychosis in clinical contexts. The Italian adaptation of this interview could be effectively implemented in other Italian FEP Programs as a screening and monitoring tool. Formal validation of the instrument is needed to assessed validity and reliability in the diagnosis of the CHR and FEP.

Perceived Negative Effects of Adverse Childhood Experiences: Associations with Internalizing Symptoms in Young Adults

ABSTRACT Cumulative exposure to ACEs is associated with internalizing disorders throughout life. Efforts to move beyond the cumulative risk framework call for assessment of various aspects of adversity (e.g., timing) to improve identification of mechanistic outcomes and accuracy in predicting individual health risk following ACEs. Here, we test whether a cumulative ACE score, an average score of perceived negative effect, or their interaction, are associated with internalizing symptoms among young adults. Six hundred undergraduates (M age = 19.05; 75% female; 69% Black) completed questionnaires related to ACEs, anxiety, and depressive symptoms. The perceived negative effect score was independently associated with anxiety and depressive symptoms, whereas a cumulative ACE score was only associated with depressive symptoms. No interactions were detected. The findings highlight the value in assessing perception as one aspect of exposure to ACEs. Future research should consider other contextual factors, and how they may interact with perception to influence health outcomes.

Long-Term Mortality Predictors Using a Machine-Learning Approach in Patients With Chronic Limb-Threatening Ischemia After Peripheral Vascular Intervention.

Patients with chronic limb-threatening ischemia (CLTI) face a high long-term mortality risk. Identifying novel mortality predictors and risk profiles would enable individual health care plan design and improved survival. We aimed to leverage a random survival forest machine-learning algorithm to identify long-term all-cause mortality predictors in patients with CLTI undergoing peripheral vascular intervention. Patients with CLTI undergoing peripheral vascular intervention from 2017 to 2018 were derived from the Medicare-linked VQI (Vascular Quality Initiative) registry. We constructed a random survival forest to rank 66 preprocedural variables according to their relative importance and mean minimal depth for 3-year all-cause mortality. A random survival forest of 2000 trees was built using a training sample (80% of the cohort). Accuracy was assessed in a testing sample (20%) using continuous ranked probability score, Harrell C-index, and out-of-bag error rate. A total of 10 114 patients were included (mean±SD age, 72.0±11.0 years; 59% men). The 3-year mortality rate was 39.1%, with a median survival of 1.4 years (interquartile range, 0.7-2.0 years). The most predictive variables were chronic kidney disease, age, congestive heart failure, dementia, arrhythmias, requiring assisted care, living at home, and body mass index. A total of 41 variables spanning all domains of the biopsychosocial model were ranked as mortality predictors. The accuracy of the model was excellent (continuous ranked probability score, 0.172; Harrell C-index, 0.70; out-of-bag error rate, 29.7%). Our random survival forest accurately predicts long-term CLTI mortality, which is driven by demographic, functional, behavioral, and medical comorbidities. Broadening frameworks of risk and refining health care plans to include multidimensional risk factors could improve individualized care for CLTI.

Risk assessments of drug-related problems for cardiac surgery patients.

Patients undergoing cardiac surgery are considered at high risk for developing drug-related problems (DRPs) due to comorbidities and complexity of drug treatment. This study aimed to identify DRPs in patients undergoing cardiac surgery and to develop and implement a framework to reduce potential risks associated with drugtreatment. Prospectively designed quasi-experimental study. This study consisted of observational (risk assessment and framework development) and interventional (framework implementation) periods and was conducted at a department of cardiovascular surgery in a university hospital. An expert panel evaluated the causes of DRPs. Then a framework was developed in consensus to identify safeguards to be implemented during the interventionalperiod. A total of 200 patients (100 patients per study period) were included. During the observational period, a total of 275 DRPs and 487 causes were identified; 74.5% of DRPs were not solved. For the risk analysis, 487causes were evaluated and only 32.6% were considered acceptable risk. By implementing the framework in the interventional period, 215 DRPs and 304 causes were identified and 386interventions were recommended by a clinical pharmacist. Atotal of 342 (88.6%) interventions were accepted by a health care team, and 128 (59.5%) DRPs were completely solved. For the risk analysis, 304 causes were evaluated and 84.9% were considered acceptable risk ( P < .001 compared with the observational period). It is possible to reduce risk levels or prevent occurrence of DRPs by implementing a framework for risk management developed by a multidisciplinary care team in areas such as cardiac surgery where time is limited.

Oil Price Fluctuation and their Impact on the Macroeconomic Variables: The Case of Kuwait

The fluctuations in the international prices of crude oil have been a major concern for many economies who depend mainly on oil exports. Oil price shocks are a major disturbance for the economies of oil producing countries. This study investigates the impact of oil price shocks on selected macroeconomic variables in Kuwait using secondary data covering the period of 2001 to 2022. The study adopted the Vector autoregression (VAR) method to analyze the response of Kuwait macroeconomic variables to shocks in oil prices. Oil price in the study is considered in 2 categories: the linear oil price and the non-linear oil price (positive and negative changes in oil price). Based on the findings, it is observed that oil price shocks significantly impact macroeconomic variables in Kuwait. It is found that positive changes in oil prices have a more positive and significant impact on the macroeconomic variables compared to the negative changes in oil price. It is however concluded that there is a need for more policy developments to better harness periods of positive oil price experiences, and develop hedging risk framework for periods of negative changes in oil price in order to curb the impact of oil price shocks on Kuwait’s macroeconomy.

A40 Brecon bypass landslide: investigation, remediation and asset management for climate resilience

During February 2020, a 300 m 3 slope failure occurred within a trunk road earthwork at Brecon, Wales, leading to the initial closure of all four lanes of the dual carriageway. As part of Welsh Government's strategy for climate resilient infrastructure and in accordance with the CD622 Managing Geotechnical Risk framework, the site investigation commenced in 2020 and proceeded through various phases to the completion of remedial works in 2022. This paper discusses the approach to management of geotechnical risk for the scheme, from desk study through implementation of an on-slope ground investigation and interim risk mitigation, to design and implementation of the remedial measures. The paper describes the nature and trigger of the landslide case study, adaptations in the design phase to provide resilience to geohazards and future climatic conditions, the constraints that were overcome during the site works and measures taken to manage residual risk and ensure ease of maintenance. Thematic collection: This article is part of the Geo-resilience and infrastructure collection available at: https://www.lyellcollection.org/topic/collections/geo-resilience-and-infrastructure

Developing a risk framework for assembly construction based on stakeholder theory and structural equation modelling.

Occupational injuries in the construction industry have plagued many countries, and many cases have shown that accidents often occur because of a combination of project participants. Assembled construction (AC) projects have received extensive attention from Chinese scholars as a future trend, but few studies have explored the interrelationships and potential risks of various stakeholders in depth. This study fills this research gap by proposing a multi-stakeholder AC risk framework. The study surveyed 396 stakeholders, then analyzed the collected data and created a risk framework based on Structural Equation Modelling (SEM) and the CRITIC weighting method. The results revealed that factors like "regular supervision is a formality," "blindly approving the wrong safety measures," and "failure to organize effective safety education and training." are vital risks in AC of China. Finally, the study validates the risk factors and the framework with 180 real-life cases, which shows that the proposed framework is theoretically grounded and realistic. The study also suggests multi-level strategies such as introducing AI-based automated risk monitoring, improving the adaptability of normative provisions to technological advances, and advancing the culture of project communities of interest to ensure AC's safe practices.

Variation in farming damselfish behaviour creates a competitive landscape of risk on coral reefs.

Interspecific interactions are fundamental drivers of animal space use. Yet while non-consumptive effects of predation risk on prey space use are well-known, the risk of aggressive interactions on space use of competitors is largely unknown. We apply the landscape of risk framework to competition-driven space use for the first time, with the hypothesis that less aggressive competitors may alter their behaviour to avoid areas of high competitor density. Specifically, we test how aggressive risk from territorial algal-farming damselfishes can shape the spatial distribution of herbivore fish competitors. We found that only the most aggressive damselfish had fewer competitors in their surrounding area, demonstrating that individual-level behavioural variation can shape spatial distributions. In contradiction to the landscape of risk framework, abundances of farming damselfish and other fishes were positively associated. Our results suggest that reef fishes do not simply avoid areas of high damselfish abundance, but that spatial variation in aggressive behaviour, rather than of individuals, created a competitive landscape of risk. We emphasize the importance of individual-level behaviour in identifying patterns of space use and propose expanding the landscape of risk framework to non-predatory interactions to explore cascading behavioural responses to aggressive risk.

Management and Business Model Risk Profile in Security Systems Development

The business model applied in the development of security systems by scientific organizations, independently or in terms of key partnerships with higher education institutions and business organizations structured through competence centres, are part of their strategic assets. But in managing this business model, both planned and unforeseeable risks may arise, which determines the need to develop a business model risk framework. The author's experience in structuring a business model risk framework for the development of security systems by scientific organizations is the basis of the present publication.

"KVANT TAHDIDI: KVANT HISOBLASHNING XALQARO KIBERXAVFSIZLIKKA TAʼSIRINI VA YANGI HUQUQIY BAZALARGA SHOSHILINCH EHTIYOJNI OʻRGANISH""KVANT TAHDIDI: KVANT HISOBLASHNING XALQARO KIBERXAVFSIZLIKKA TAʼSIRINI VA YANGI HUQUQIY BAZALARGA SHOSHILINCH EHTIYOJNI OʻRGANISH"

"The rapid advancement of quantum computing poses a significant threat to the cybersecurity of our increasingly digitized world. As quantum computers become more powerful and accessible, they have the potential to break many of the cryptographic algorithms that currently secure our sensitive data, financial transactions, and critical infrastructure. This looming “quantum threat” has far-reaching implications for individuals, organizations, and nation-states, as it could lead to widespread data breaches, economic disruption, and compromised national security. Despite the growing recognition of this risk, existing legal and regulatory frameworks are largely unprepared to address the unique challenges of quantum-enabled cyber threats. Moreover, the geopolitical implications of the quantum revolution are complex and multifaceted, with the potential to reshape the global balance of power and exacerbate technological inequalities. To mitigate these risks and promote quantum readiness, there is an urgent need for the international community to develop new legal frameworks and cooperative mechanisms that span technical, economic, legal, and political domains. This article provides an interdisciplinary analysis of the quantum threat to cybersecurity, examines its potential impacts across various sectors and international relations, and offers policy recommendations for developing a comprehensive global governance framework. By proactively addressing this challenge through multi-stakeholder collaboration and quantum-resistant solutions, we can work towards a more secure and resilient digital future in the face of this transformative technology. "

The Optimal Stopping Problem under a Random Horizon

This paper considers a pair (F,τ), where F is a filtration representing the “public” flow of information that is available to all agents over time, and τ is a random time that might not be an F-stopping time. This setting covers the case of a credit risk framework, where τ models the default time of a firm or client, and the setting of life insurance, where τ is the death time of an agent. It is clear that random times cannot be observed before their occurrence. Thus, the larger filtration, G, which incorporates F and makes τ observable, results from the progressive enlargement of F with τ. For this informational setting, governed by G, we analyze the optimal stopping problem in three main directions. The first direction consists of characterizing the existence of the solution to this problem in terms of F-observable processes. The second direction lies in deriving the mathematical structures of the value process of this control problem, while the third direction singles out the associated optimal stopping problem under F. These three aspects allow us to deeply quantify how τ impacts the optimal stopping problem and are also vital for studying reflected backward stochastic differential equations that arise naturally from pricing and hedging of vulnerable claims.

Autism in ICU.

Autism is a lifelong neurodevelopmental condition. Autistic people face challenges as patients in the intensive care unit (ICU) and as providers of healthcare in the ICU. This article describes the experience of autistic people using a neurodiversity-affirming approach. Using the 'Autistic SPACE' framework, the needs of autistic people are described in terms of sensory needs, need for predictability, need for autistic acceptance, communication differences and how to approach them, and the benefits of a person-centred empathy-based approach to autistic people. The approach to autistic patients is described in terms of reasonable adjustments within a framework of positive risk taking. For supervisors and managers of autistic healthcare professionals, autism-friendly adjustments to training and working practice, with rationales, are suggested.

Spatio-temporal assessment of heat health risk in Chinese metropolitan cities based on the modified multi-indicators coupled risk framework

Extreme heat events are the leading cause of climate-related disease and death globally. Heat health risk assessment is an effective tool to understand and reduce heat-related morbidity and mortality. However, the indicators of previous studies made it difficult to characterize risk accurately, especially the most important hazard. Besides, studies prefer to focus on spatial variation and ignore the temporal variation. Based on these challenges, this study constructed a modified framework from three components including heat hazard, human exposure, and social vulnerability to propose an assessment of heat health risk in Chinese metropolitan cities from 2000 to 2020. The results indicated that (1) Compared to the traditional framework using a single indicator, the R² has been improved 0.16. (2) Spatially, in the large city, the city with a larger size has a higher risk index except supercity. And more open space has the ability to reduce the damage caused by heat. (3) Temporally, the average heat health risk index of cities increased gradually about 24.72 % from 2020 to 2000. This framework can help to improve the accuracy and flexibility of heat health risk assessment and provide support for sustainable urban development.

Effect of smartphone addiction on compulsive app downloading tendency: protective factors for generation Z consumers

Purpose This study aims to focus on how smartphone addiction impacts young consumer behavior related to mobile technology (i.e. the compulsive app downloading tendency). After a thorough literature review and following the risk and protective factors framework, this study explores factors that could mitigate its effects (resilience, family harmony, perceived social support and social capital). Design/methodology/approach The study used the covariance-based structural equation modeling approach to analyze data collected from 275 Generation Z (Gen Z) smartphone users in Spain. Findings Results suggest that resilience is a critical factor in preventing smartphone addiction, and smartphone addiction boosts the compulsive app downloading tendency, a relevant downside for younger Gen Z consumers. Originality/value Through the lens of the risk and protective factors framework, this study focuses on protective factors to prevent smartphone addiction and its negative side effects on app consumption. It also offers evidence of younger consumers’ vulnerability to smartphone addiction, not because of the device itself but because of app-consumption-related behaviors.

Architecting the metabolic reprogramming survival risk framework in LUAD through single-cell landscape analysis: three-stage ensemble learning with genetic algorithm optimization

Recent studies have increasingly revealed the connection between metabolic reprogramming and tumor progression. However, the specific impact of metabolic reprogramming on inter-patient heterogeneity and prognosis in lung adenocarcinoma (LUAD) still requires further exploration. Here, we introduced a cellular hierarchy framework according to a malignant and metabolic gene set, named malignant & metabolism reprogramming (MMR), to reanalyze 178,739 single-cell reference profiles. Furthermore, we proposed a three-stage ensemble learning pipeline, aided by genetic algorithm (GA), for survival prediction across 9 LUAD cohorts (n = 2066). Throughout the pipeline of developing the three stage-MMR (3 S-MMR) score, double training sets were implemented to avoid over-fitting; the gene-pairing method was utilized to remove batch effect; GA was harnessed to pinpoint the optimal basic learner combination. The novel 3 S-MMR score reflects various aspects of LUAD biology, provides new insights into precision medicine for patients, and may serve as a generalizable predictor of prognosis and immunotherapy response. To facilitate the clinical adoption of the 3 S-MMR score, we developed an easy-to-use web tool for risk scoring as well as therapy stratification in LUAD patients. In summary, we have proposed and validated an ensemble learning model pipeline within the framework of metabolic reprogramming, offering potential insights for LUAD treatment and an effective approach for developing prognostic models for other diseases.