Global Risk Research Articles

Global Cardiovascular Risk and Associated Factors in 2792 French Military and Civilian Aircrew.

INTRODUCTION: Cardiovascular (CV) diseases are a major public health issue, the prevention of which plays a key role in promoting flight safety. However, few studies have looked at the determinants of the overall risk of CV morbidity-mortality within the various aeronautical occupations.METHODS: A monocentric, observational, cross-sectional study was based on the retrospective data collected during 6 mo at the Toulon Aeromedical Center. From October 2017 to April 2018, 2792 professional aircrew ages 18-74 were included. The overall CV risk was estimated using the European Society of Cardiology SCORE and the Framingham model, as well as a summation model.RESULTS: More than two-thirds of this mainly male population (86.2%) had no more than one CV risk factor [69.9% (68.2-71.6)]. In 82.5% of cases, this was dyslipidemia according to current European criteria [55.8% (52.4-59.1)] or smoking [26.7% (23.8-29.8)]. An overall risk level of "moderate" to "very high" concerned only one subject in five according to the SCORE model [20.1% (18.6-21.6)], one in six according to Framingham [16.3% (14.9-17.7)] and almost one in three according to the summation model [30.1% (28.4-31.9)].DISCUSSION: Multivariate analyses found no significant associations between socio-professional criteria and overall risk levels. The results have underlined the effect of dyslipidemia and smoking on early risk among applicants. Beyond the illustration of favorable cardiovascular status among aircrews related to the standards of selection and close monitoring process, areas for improvement were identified, inviting the development of prevention strategies around the "moderate" overall CV risk.Huiban N, Gehant M, Brocq F-X, Collange F, Mayet A, Monteil M. Global cardiovascular risk and associated factors in 2792 French military and civilian aircrew. Aerosp Med Hum Perform. 2024; 95(5):233-244.

Which SDM Model, CLIMEX vs. MaxEnt, Best Forecasts Aeolesthes sarta Distribution at a Global Scale under Climate Change Scenarios?

A precise evaluation of the risk of establishing insect pests is essential for national plant protection organizations. This accuracy is crucial in negotiating international trade agreements for forestry-related commodities, which have the potential to carry pests and lead to unintended introductions in the importing countries. In our study, we employed both mechanistic and correlative niche models to assess and map the global patterns of potential establishment for Aeolesthes sarta under current and future climates. This insect is a significant pest affecting tree species of the genus Populus, Salix, Acer, Malus, Juglans, and other hardwood trees. Notably, it is also categorized as a quarantine pest in countries where it is not currently present. The mechanistic model, CLIMEX, was calibrated using species-specific physiological tolerance thresholds, providing a detailed understanding of the environmental factors influencing the species. In contrast, the correlative model, maximum entropy (MaxEnt), utilized species occurrences and spatial climatic data, offering insights into the species' distribution based on observed data and environmental conditions. The projected potential distribution from CLIMEX and MaxEnt models aligns well with the currently known distribution of A. sarta. CLIMEX predicts a broader global distribution than MaxEnt, indicating that most central and southern hemispheres are suitable for its distribution, excluding the extreme northern hemisphere, central African countries, and the northern part of Australia. Both models accurately predict the known distribution of A. sarta in the Asian continent, and their projections suggest a slight overall increase in the global distribution range of A. sarta with future changes in climate temperature, majorly concentrating in the central and northern hemispheres. Furthermore, the models anticipate suitable conditions in Europe and North America, where A. sarta currently does not occur but where its preferred host species, Populus alba, is present. The main environmental variables associated with the distribution of A. sarta at a global level were the average annual temperature and precipitation rate. The predictive models developed in this study offer insights into the global risk of A. sarta establishment and can be valuable for monitoring potential pest introductions in different countries. Additionally, policymakers and trade negotiators can utilize these models to make science-based decisions regarding pest management and international trade agreements.

Reprint of “Unveiling the dance of commodity prices and the global financial cycle”

We examine the impact of commodity price changes on the business cycles and capital flows in emerging markets and developing economies (EMDEs), distinguishing between their role as a source of shock and as a channel of transmission of global shocks. Our findings reveal that surges in export prices, triggered by commodity price shocks, boost domestic GDP, an effect further amplified by the endogenous decline of country spreads. However, the effects on capital flows appear muted. Shifts in U.S. monetary policy and global risk appetite drive the global financial cycle in EMDEs. Eased global credit conditions, attributed to looser U.S. monetary policy or lower global risk appetite, lead to a rise in export prices, higher output, a decrease in government borrowing costs, and stimulate greater capital flows. The endogenous response of export prices amplifies the output effects of a more accommodative U.S. monetary policy while country spreads magnify the impact of shifts in global risk appetite.

Utilizing Ant Forest technology to foster sustainable behaviors: A novel approach towards environmental conservation

Amidst mounting environmental threats and exacerbated global risks from climate change, the urgency for sustainable behaviors has never been more critical, demanding concerted efforts to cultivate individual actions for environmental conservation. Ant Forest technology, a groundbreaking innovation for sustainable lifestyles, stands at the forefront of this battle, harnessing technological advancements to drive positive environmental impact and must be championed. This research investigates the dynamics of environmental conservation behaviors facilitated by Ant Forest Technology. Employing a theoretical framework integrating the Technology Acceptance Model (TAM) and Self-Determination Theory (SDT), the study explores the impact of autonomous and controlled motivation on attitudes, intentions, and conservation behaviors. Furthermore, the research assesses the influence of knowledge disseminated through Ant Forest Technology on users' intentions and behavior toward conservation behaviors. The study utilized the partial least square structural equation modeling in its analysis. Findings reveal that both motivational factors and knowledge significantly shape users' engagement in conservation behaviors activities through perceived ease of use and usefulness. These insights contribute to the development of effective policies and interventions aimed at harnessing Ant Forest Technology as a powerful tool for fostering widespread environmental conservation behaviors.

HIGHER BASELINE SYSTOLIC BLOOD PRESSURE IS ASSOCIATED WITH GREATER BLOOD PRESSURE REDUCTIONS FOLLOWING RADIOFREQUENCY RENAL DENERVATION IN A POOLED COHORT OF OVER 3900 PATIENTS

Objective: Uncontrolled hypertension (HTN) is the leading global risk factor for cardiovascular disease, and higher systolic blood pressure (SBP) increases this risk. Radiofrequency renal denervation (RF RDN) has been shown to reduce BP effectively in patients with uncontrolled HTN. We investigated the relationship between increasing baseline SBP and its change after RF RDN. Design and method: Patients undergoing RF RDN (N=3974) were pooled from global clinical trials in patients on antihypertensive drugs: SPYRAL First-In-Man, SYMPLICITY HTN-3, HTN-Japan, SPYRAL HTN ON-MED, and the Global SYMPLICITY Registry DEFINE. Office and 24-h ambulatory SBP at baseline and 6 months after RF RDN were evaluated. Linear regression analysis was performed to evaluate the correlation between baseline and SBP change after 6 months (SBP change=intercept+slope∗baseline SBP). Results: The baseline SBP for office and 24-h ambulatory BP were 167±24mmHg and 154±18mmHg, respectively. Patients were prescribed 4.4±1.5 antihypertensive drugs at baseline. After 6 months, prescribed antihypertensive drugs decreased to 4.3±1.5 (p<0.0001). In both office and 24-h ambulatory SBP, baseline SBP correlation with SBP change after 6 months was statistically significant; every 1mmHg increase in baseline office SBP was associated with a 0.59mmHg (r2=0.30; p<0.001) reduction in SBP, and every 1mmHg increase in baseline 24-h ambulatory SBP was associated with a 0.45mmHg (r2=0.19; p<0.001) reduction in SBP at 6 months. According to this linear regression, a baseline office SBP of 160mmHg, 170mmHg and 180mmHg were associated with 6 months office SBP reduction by -9.2mmHg, -15.1mmHg and -21.0mmHg, respectively (Figure). Reductions in SBP of this magnitude have previously been shown to correspond with substantial reductions in the risk of cardiovascular events. Conclusions: A continuous and inverse relationship was observed between baseline SBP and 6 months SBP change in patients with uncontrolled HTN undergoing RF RDN. Higher baseline SBP led to a greater reduction in SBP and may derive greater benefit from an RDN procedure. These findings may help clinicians and patients in their shared decision making regarding their BP management. However, this is a retrospective analysis which needs further prospective validation.

International aggregate risk: Effects on financial stability

The increasing interconnectedness of financial and economic systems has led to the emergence of global risks that can impact financial stability. In this paper, we explore how aggregate risk on a global scale can affect the stability of financial systems. We present a simple model that considers an exogenous parameter indicating the concentration of international credit risk in both domestic and foreign banking systems. When this parameter is high, the model is vulnerable to aggregate risk. Our research shows that if multiple countries are impacted by the same shock, diversification of risk becomes impossible.In the event of a global economic downturn, international lenders may become scarce, or the real interest rate may substantially increase, perhaps leading to an economic crisis.

Multicountry Time-Varying Taylor Rule: Modeling Unconventional Monetary Policies and Bond Premiums

In the post-financial-crisis era, advanced economies have increasingly adopted unconventional monetary policies such as zero interest rate policy, negative interest rate policy, forward guidance communication, and international coordination policies. Consequently, the traditional Taylor rule has lost some of its explanatory power. This analysis extends the Taylor rule from a single-country to a multicountry analysis using cross-country panel data, incorporating nonmacro factors and stationary correlation in the diffusion matrix for a dynamic factor analysis, specifically covering the Group of Seven countries with datasets compiled by Bloomberg L.P. for the period 1999–2022. This approach comprehensively models these unconventional monetary policies, demonstrating greater statistical validity than existing models. Notably, the model extracts the impact of zero interest rate policy and negative interest rate policy as nonmacro factors and presents the high correlation of residuals as indicative of international coordination among central banks. Additionally, by interpreting the discrepancy between the Taylor rule and actual rate as unintended interest rate fluctuations by central banks, the study posits that interest rates will eventually return to the central bank’s intended fair value. The model’s estimation errors could be treated akin to bond value factors in global risk premia.

Green Assets and Global Portfolio Tail Risk? A Stress-Testing exercise under multiple asset classes under distinct market phases

Despite a burgeoning literature in the sphere of cryptocurrencies and green assets, yet, as of date, the literature fares poorly in terms of a holistic assessment of all asset classes, let alone stress testing such global portfolio risk under various market conditions. Our paper fulfills such a gap in the literature. Findings reveal that, irrespective of bearish or bullish market phases, green assets should be incorporated to mute down portfolio tail risk. Robustness tests performed either via different distribution type or CVaR analysis do not materially alter the main findings of our paper. The confluence of two forces substantially boosts tail risk, namely, passive investment strategy coupled with a crypto-augmented base model. Overall, our paper advocates the inclusion of green assets not as a choice but as an obligation to portfolio managers in view of curtailing both VaR and CVaR risk levels, all geared towards hitting two birds with one stone-simultaneously buttressing a greener world while effectively mitigating global portfolio tail risk.

Brain on Fire: How Brain Infection and Neuroinflammation Drive Worldwide Epilepsy Burden

Roughly 80% of the global burden of epilepsy resides in low- and middle-income countries (LMICs; WHO, 2022). Despite numerous new therapies for the treatment of epilepsy, the number of patients who remain resistant to available medications is unchanged. Additionally, no therapy has yet been clinically proven to prevent or attenuate the development of epilepsy in at-risk individuals. Unfortunately, access to next generation therapies in LMICs is low, the stigma associated with epilepsy remains high, and access to adequate resources is unchanged. Thus, the global epilepsy burden disproportionately falls on LMICs such that strategies to conscientiously integrate global epilepsy risk factors into preclinical research may meaningfully advance 21st century epilepsy therapies. Brain infections are one of the main risk factors for epilepsy in resource-poor settings. Further, both infection- and autoimmune-associated encephalitis contribute to worldwide epilepsy risk and remain relatively understudied. For example, clinical SARS CoV-2 infection can induce rare instances of encephalopathy and acute seizures. Among viruses known to cause acute brain infection, enteroviruses increase risk for encephalitis-induced epilepsy, but are not associated with risk for other neurodevelopmental disorders (eg, autism spectrum or attentional deficit hyperactivity disorders). Naturally occurring models of viral infection-induced epilepsy therefore provide an exquisite opportunity to uncover novel contributors to epileptogenesis. Moreover, the convergent neuroinflammatory pathways that are associated with viral infection-induced encephalitis and autoimmune encephalitis reflect an untapped therapeutic opportunity to meaningfully reduce the global burden of epilepsy. This review summarizes the latest advances in translational research integrating encephalitis-induced seizure and epilepsy models, in tandem with progress in clinical diagnosis of inflammation and virally mediated epilepsy. This improved awareness of the shared biological underpinnings of epileptogenesis following brain infection or autoimmune encephalitis is anticipated to beneficially impact the global burden of epilepsy.

Risk Management Strategies in Facing Global Financial Market Volatility

Global financial market volatility refers to the unpredictable fluctuations in the prices of financial assets such as stocks, bonds, currencies, and commodities. This volatility can stem from various factors such as economic indicators, geopolitical events, policy changes, technological advancements, and investor sentiment. This research aims to analyze effective risk management strategies in facing global financial market volatility. Market volatility often triggers anxiety, uncertainty, and irrational investment decisions. In this situation, it is important for investors to adopt the right strategies to minimize risks and maximize long-term investment outcomes. In this study, data is collected from various sources related to global financial market volatility and risk management strategies adopted by investors during periods of uncertainty. Qualitative and quantitative analyses of this data are conducted to identify patterns of investor behavior and the effectiveness of applied risk management strategies. The research findings indicate that maintaining a long-term perspective, retaining portfolio diversification, and taking an active approach to risk management are effective strategies in dealing with market volatility. Open communication with financial professionals is also proven to be essential in helping investors stay calm and make rational decisions.

Assessment of synthetic series to design the capacity of flow regulation reservoirs

Freshwater scarcity is perceived as a global systemic risk. Intending to reach water secutiry, flow regulation reservoirs are alternatives to improve streamflow and water storage, especially in places where demand exceeds water availability during periods of drought. However, the unavailability of historical series of flows in watersheds makes the adequate design of reservoirs difficult. To overcome such difficulties, synthetic series of flows are currently being generated for the specific sections of the watercourses where these structures are to be designed. The present study aimed to evaluate two methods of generating synthetic series of flows applied to design the capacity of flow regulation reservoirs in conditions of limited data. A monitored hydrological region (Itapemirim River Basin, Espírito Santo, Brazil) and synthetic flow series generated according to the methodologies of Rodrigues (2017) and Cesconetto (2021) were used. The methodologies were tested by cross-validation, and the results were compared using graphs and statistical indicators to the results obtained with observed data, measured in fluviometric reference stations. After analyzing the statistical indicators, such as the coefficient of determination (R2), the Nash-Sutcliffe efficiency index (NSE), and the reservoir design quality index (IQD), it was concluded that the method proposed by Cesconetto (2021) showed a tendency to under-design the capacities of the reservoirs, mainly for lower flows to be regularized (β < 0.75). The method proposed by Rodrigues (2017) performed better than the method proposed by Cesconetto (2021) for the design of the capacity of flow regulation reservoirs under conditions of limited data in the Itapemirim River Basin.

Advancement of Dengue Virus Vaccine: Progress and Challenges

The dengue virus (DENV), which causes dengue, infects 100 to 300 million people globally each year [1]. Aedes aegypti mosquitoes carry the Dengue virus, which causes dengue fever, which is still a serious global health risk, particularly in tropical and subtropical areas [2]. Since there are now no targeted antiviral therapies and due to difficulties with traditional vector control techniques, the focus has shifted to developing vaccines as the main preventive measure. In order to create a variety of vaccination forms, including live attenuated, recombinant subunit, inactivated virus, viral vectored, DNA, and mRNA vaccines, scientists have targeted E protein and NS1. An important advancement in the fight against Dengue fever has been the development of vaccinations that are able to neutralize all four serotypes. But there are obstacles such as lack of vaccine effectiveness against specific serotypes, side effects produced by vaccine in progeny and vaccine-induced immunological enhancement (ADE).Immunization can lessen the burden on healthcare systems, lower the number of hospitalizations caused by dengue, and help stop outbreaks. The development and implementation of dengue vaccine research are significantly accelerated by international cooperation, public-private partnerships, and regulatory cooperation. Effective programs show how crucial it is to work together to combat dengue fever on a worldwide scale. The difficulties involved in developing a dengue vaccine, ongoing funding, campaigning, and research are crucial. There are several viable approaches to increase the efficacy and accessibility of the Dengue vaccine, including cross-disciplinary cooperation, novel vaccination platforms, and emerging technology. In conclusion, overcoming obstacles unique to each serotype, embracing creative approaches to vaccine design, and negotiating scientific intricacies are all necessary steps on the path to developing successful Dengue virus vaccines. The convergence of state-of-the-art technologies, computational modeling, and cooperative research endeavors can potentially realize the objective of vaccination-based comprehensive dengue prevention.

The Importance of Risk Preference Parameters in Prospect Theory: Evidence from Mutual Fund Flows

In this paper, we use the well-documented mutual fund flow-performance relationship to infer information about investors’ preferences. We show that applying preference parameter values from experimental settings to market data can significantly understate the role of prospect theory in explaining investor behavior. We find evidence that mutual fund investors exhibit loss aversion and differential attitudes toward risk over losses (risk-seeking) and gains (risk-averse) but no significant probability weighting when evaluating fund performance. Our results apply more strongly to retail funds compared to institutional funds, consistent with the view that prospect theory is more relevant for retail investors. Finally, we show that, for parameter values that best explain fund flows, prospect theory outperforms the global risk aversion framework and widely-used asset pricing models in explaining investors’ responses to fund performance.

Informed Ignorance as a Form of Epistemic Injustice

Ignorance, or the lack of knowledge, appears to be steadily spreading, despite the increasing availability of information. The notion of informed ignorance herein proposed to describe the widespread position of being exposed to an abundance of information yet lacking relevant knowledge, which is tied to the exponential growth in misinformation driven by technological developments and social media. Linked to many of societies’ most looming catastrophes, from political polarization to the climate crisis, practices related to knowledge and information are deemed some of the most imminent and daunting modern threats, evidenced by the latest report of the World Economic Forum, which has named misinformation the most severe short-term global risk. This paper’s epistemic perspective links the properties of today’s information culture and the ways in which it interacts with individual capacities and limitations in current technological and socio-political contexts. Such a position is analyzed through the lens of epistemic principles as a contemporary epistemic phenotype that emerges from an environment of ill-adapted and excessive information inputs and leads to a distinctive type of social injustice that is primarily epistemic in nature. While equity and accessibility are widely discussed as important contributing factors to epistemic discrepancies, other overlooked but fundamental issues underlying epistemic injustices are considered, such as information manipulation, cognitive limitations, and epistemic degradation. To effectively face this elusive threat, we propose an inclusive viewpoint that harnesses knowledge from cognitive science, science and technology studies, and social epistemology to inform a unifying theory of its main impacts and driving forces. By adjusting a modern epistemic framework to the described phenomena, we intend to contextually outline its trajectory and possible means of containment based on a shared responsibility to maintain ethical epistemic standards. In a time of international unrest and mounting civil acts of violence, it is pertinent to emphasize the ethical principles of knowledge systems and authorities and suggest policy adaptations to maintain a social contract based on the shared values of truth and freedom.

Bangladesh's Climate Vulnerability and Overseas Migration: Navigating Challenges and Paving the Way Forward

Bangladesh ranks seventh on the Global Climate Risk Index 2021, which identifies the nations most susceptible to natural catastrophes, demonstrating how sensitive the country is to both climate change and natural disasters. Millions of people are forced to migrate to neighboring cities and urban areas in search of work and a living each year as a result of climate change and natural disasters such as river bank erosion, salinity intrusion, floods, cyclones, and landslides in Bhola, Khulna, Bagerhat, Patuakhali, and Gaibandha. Urban life is strained by this influx, especially in terms of housing, water supply, and sanitation. Many of these individuals also seek overseas employment as a means of survival. While numerous organizations, including government institutions, are working to promote safe and regular international migration and overseas employment, a portion of these individuals fall prey to labor trafficking due to a lack of information, monitoring, and services from the administration. Additionally, communities in climate-risk areas are ultimately forced to choose between internal and international migration due to the sluggish adoption of climate-resilient agricultural methods and technologies, as well as the dearth of technical and vocational education options. For these regions of significant natural disasters and climate change, the government has to provide more secure migration policies and encourage productive remittance investment.

Keep your enemies safer: technical cooperation and transferring nuclear safety and security technologies

Even during the Cold War, the United States and the Soviet Union cooperated on nuclear safety and security. Since accidental or unauthorized nuclear detonations anywhere threaten peace everywhere, it seems straightforward that states more experienced in developing nuclear safety and security technologies would transfer such methods to other states. Yet, the historical record is mixed. Why? While existing explanations focus on the political costs and proliferation risks faced by the transferring state, this article argues that specific technological features condition the feasibility of assistance. For more complex nuclear safety and security technologies, robust technical cooperation is crucial to build the necessary trust for scientists to transfer tacit knowledge without divulging sensitive information. Leveraging elite interviews and archival evidence, my theory is supported by four case studies: US sharing of basic nuclear safety and security technologies with the Soviet Union (1961–1963); US withholding of complex nuclear safety and security technologies from China (1990–1999) and Pakistan (1998–2003); and US sharing of complex nuclear safety and security technologies with Russia (1994–2007). My findings suggest the need to examine not only the motivations behind nuclear assistance but also the process by which it occurs and the features of the technologies involved, with implications for how states cooperate to manage the global risks of emerging technologies.

Wrist Circumference Cutoff Points for Determining Excess Weight Levels and Predicting Cardiometabolic Risk in Adults.

(1) Background: An elevated wrist circumference may indicate excess weight and cardiometabolic risk. The present study aims to identify wrist circumference cutoff points (WrC) to determine excess weight levels and predict cardiometabolic risk in adults. (2) Methods: A cross-sectional study was conducted with adults aged 20 to 59 years old, attending the outpatient clinic at University Hospital/Federal University of Sergipe HU/UFS-EBSERH. Demographic, anthropometric, biochemical, and blood pressure (BP) data were collected. Cardiometabolic risk was assessed, according to the global risk score (ERG) and Framingham score criteria. The descriptive analysis included calculating medians and frequencies of anthropometric, demographic, biochemical, and blood pressure variables. The gender and age of adult groups were compared using the Mann-Whitney test. Spearman's correlation coefficient and multiple regression analysis were used to assess the association between wrist circumference (WrC) and the variables mentioned above. The predictive validity of WrC in identifying excess weight levels and cardiometabolic risk was analyzed using the ROC curve. The sample consisted of 1487 adults aged 20 to 59 years, 55.7% of whom were female; (3) Results: WrC correlated positively with other adiposity indicators such as waist circumference and Body Mass Index. WrC was the anthropometric indicator most significantly associated with cardiometabolic risk factors. WrC cutoff points identified by the study for determining excess weight were categorized by gender and age group. For males aged 20 to 40 years and >40 years, respectively, the cutoff points for overweight were 17.1 cm and 17.3 cm, and for obesity, 17.9 cm and 17.5 cm. For females aged 20 to 40 years and >40 years, respectively, the cutoff points for overweight were 15.6 cm and 15.4 cm, and for obesity, 16.1 cm and 16 cm (4). Conclusions: Wrist circumference showed a significant correlation with other adiposity indicators and can be used to identify adults with excess weight and predict cardiometabolic risk.

Residual Cardiovascular Risk: Role of Remnants Cholesterol, Monocyte/HDL Ratio and Lipoprotein Ratios on Personalized Cardiovascular Prevention.

Cardiovascular diseases represent the leading cause of death in the world and are subject to limitations in prevention strategies despite the use of very effective drugs. The concept of residual risk (RR) is intrinsically related to that of global risk of which it represents a very significant percentage. In the cardiovascular field, the term RR refers to the probability of incurring a major cardiovascular event, despite adequate control of the risk factors present in the individual patient. A significant portion of the RR in the cardiovascular field results from the underestimation of additional risk factors not subjected to adequate intervention such as, for example, triglyceride levels in patients treated for the presence of hypertension and/or hypercholesterolemia. The control of the RR therefore appears as an essential condition for the effective reduction of the global risk profile and is based on an integrated intervention that combines all the different prevention strategies derived from the available evidence and capable of interacting on the basis of a strengthening reciprocal between lifestyle and pharmacological and nutraceutical intervention methods.

Dynamic linkage between environmental segments of stock markets: the role of global risk factors

ABSTRACT This study evaluates the links between representative indices of companies with high environmental performance and the propensity of such indices to economic and financial shocks. Five indices, representing environmental segments and four global macroeconomic and financial variables, were analyzed over a thirteen-year period, which included various crisis moments, such as the sovereign debt crisis, the COVID-19 pandemic and the onset of the Russia/Ukraine conflict. Using dynamic and nonlinear models, our research reveals statistically significant and consistent relationships between the variables under investigation, particularly during periods of global financial and pandemic crises. The analysis revealed that the VIXCLS is the most influential global risk factor, with certain risk factors being influenced by environmental segments, particularly Alternative Energy. This influence can create conditions conducive to contagion risk and diminish the benefits of portfolio diversification. This study contributes to a deeper understanding of the connection between environmental investments and their vulnerability to significant global events and risks.

Promoting Artificial Intelligence for Global Breast Cancer Risk Prediction and Screening in Adult Women: A Scoping Review.

Background: Artificial intelligence (AI) algorithms can be applied in breast cancer risk prediction and prevention by using patient history, scans, imaging information, and analysis of specific genes for cancer classification to reduce overdiagnosis and overtreatment. This scoping review aimed to identify the barriers encountered in applying innovative AI techniques and models in developing breast cancer risk prediction scores and promoting screening behaviors among adult females. Findings may inform and guide future global recommendations for AI application in breast cancer prevention and care for female populations. Methods: The PRISMA-SCR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) was used as a reference checklist throughout this study. The Arksey and O'Malley methodology was used as a framework to guide this review. The framework methodology consisted of five steps: (1) Identify research questions; (2) Search for relevant studies; (3) Selection of studies relevant to the research questions; (4) Chart the data; (5) Collate, summarize, and report the results. Results: In the field of breast cancer risk detection and prevention, the following AI techniques and models have been applied: Machine and Deep Learning Model (ML-DL model) (n = 1), Academic Algorithms (n = 2), Breast Cancer Surveillance Consortium (BCSC), Clinical 5-Year Risk Prediction Model (n = 2), deep-learning computer vision AI algorithms (n = 2), AI-based thermal imaging solution (Thermalytix) (n = 1), RealRisks (n = 2), Breast Cancer Risk NAVIgation (n = 1), MammoRisk (ML-Based Tool) (n = 1), Various MLModels (n = 1), and various machine/deep learning, decision aids, and commercial algorithms (n = 7). In the 11 included studies, a total of 39 barriers to AI applications in breast cancer risk prediction and screening efforts were identified. The most common barriers in the application of innovative AI tools for breast cancer prediction and improved screening rates included lack of external validity and limited generalizability (n = 6), as AI was used in studies with either a small sample size or datasets with missing data. Many studies (n = 5) also encountered selection bias due to exclusion of certain populations based on characteristics such as race/ethnicity, family history, or past medical history. Several recommendations for future research should be considered. AI models need to include a broader spectrum and more complete predictive variables for risk assessment. Investigating long-term outcomes with improved follow-up periods is critical to assess the impacts of AI on clinical decisions beyond just the immediate outcomes. Utilizing AI to improve communication strategies at both a local and organizational level can assist in informed decision-making and compliance, especially in populations with limited literacy levels. Conclusions: The use of AI in patient education and as an adjunctive tool for providers is still early in its incorporation, and future research should explore the implementation of AI-driven resources to enhance understanding and decision-making regarding breast cancer screening, especially in vulnerable populations with limited literacy.