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Analytical treatment interruptions (ATIs) are widely used to evaluate HIV cure-related research interventions. However, sex partners of cure-related trial participants might be at risk of acquiring HIV during ATIs. Addressing this risk is key to ensuring the continued success of trials involving ATIs and offer greater acceptability across multiple trials sites. In 2022, the Advancing Clinical Therapeutics Globally (ACTG) Network convened a Partner Protections Working Group (PPWG) to update the 2020 HIV transmission risk toolkit developed by Peluso and colleagues. In our review of the original toolkit, we identified new challenges and needs at the participant, partner and study levels, as well as new evidence on measures to address these needs and more advanced ethical thinking on partner protections in HIV cure-related trials with ATIs. Based on these findings, we developed an updated toolkit that will provide trial participants and their partners with better support to address new and unfamiliar situations and protect partners from undue harm. We present this toolkit, make it available as a resource for cure-related trials with ATIs and discuss possible future directions.

High levels of lipoprotein(a) [Lp(a)] are causal for atherosclerotic cardiovascular disease (ASCVD). Lp(a) is the most prevalent inherited dyslipidemia and strongest genetic ASCVD risk factor. This risk persists in the presence of at target, guideline-recommended, LDL-C levels and adherence to lifestyle modifications. Epidemiological and genetic evidence supporting its causal role in ASCVD and calcific aortic stenosis continues to accumulate, although various facets regarding Lp(a) biology (genetics, pathophysiology, and expression across race/ethnic groups) are not yet fully understood. The evolving nature of clinical guidelines and consensus statements recommending universal measurements of Lp(a) and the scientific data supporting its role in multiple disease states reinforce the clinical merit to start population screening for Lp(a) now. There is a current gap in the implementation of recommendations for primary and secondary cardiovascular disease (CVD) prevention in those with high Lp(a), in part due to a lack of protocols for management strategies. Importantly, targeted apolipoprotein(a) [apo(a)]-lowering therapies that reduce Lp(a) levels in patients with high Lp(a) are in phase 3 clinical development. This review focuses on the identification and clinical management of patients with high Lp(a). Specifically, we highlight the clinical value of measuring Lp(a) and its use in determining Lp(a)-associated CVD risk by providing actionable guidance, based on scientific knowledge, that can be utilized now to mitigate risk caused by high Lp(a).

SYNOPSIS: This study investigates the risk mitigation and internal control processes organizations implement in their robotic process automation (RPA) deployments in accounting. The roles of internal controls and risk mitigation are examined by exploring how RPA Program Managers have adopted internal controls and risk mitigation regarding RPA in accounting. Employing interviews with 20 RPA Program Managers, this study provides rich insights into RPA Governance for accounting processes. The interviews revealed that organizations adopt various governance models to ensure proper oversight over RPA in accounting. RPA Governance models range from being fully centralized to being entirely decentralized. RPA risk and control oversight includes unique risk assessments for the RPA accounting environment and specialized monitoring to ensure that RPA in accounting performs as expected. JEL Classifications: M41; M42. [ABSTRACT FROM AUTHOR]

Risk management has always been a trend in manufacturing related literature in the era of zero-defect manufacturing (ZDM). However, a gap still exists to present a holistic viewpoint of the integration for a product and its related processes involved during decision-making in manufacturing industry. The (knowledge-driven) integrated-decision support system indicates the opportunity by integrating the product design and manufacturing processes related risks in a manufacturing industry to make better decisions at the shop floor. It further proposes a direction towards development of a decision support system framework for their respective risks' identification as well as mitigation to enhance the quality, while minimizing time and cost. Over the years, risk identification has been considered well but risk mitigation has mostly been overlooked in the published literature. This paper scanned over a thousand papers from renowned journals published between 2005 and 2024. Currently, the evolution involved in the advancement of decision support tools for risk management has been reviewed by utilizing systematic literature review methodology. The study also provides a design overview, highlighting its features, pros, and cons of the existing methods which can be used for risk identification, prioritization, and mitigation in the development of a dynamic decision support system to aim (data-driven) zero-defect manufacturing (ZDM). Lastly, the paper discusses the current challenges and opportunities to lessen the manufacturing recalls in the industry, followed by phases of the proposed model. [ABSTRACT FROM AUTHOR]

Food-borne pathogens and antimicrobial resistance (AMR) represent the significant public health challenges in the 21st century. Increased emergence of AMR in major zoonotic food-borne pathogens (Salmonella, Campylobacter) and in commensal bacteria (E. coli, enterococci), its presence in agro-food (meat) chain and environment, including control/prevention of AMR transfer from food-producing animals to humans via food consumption, is of utmost importance for public health. This review highlights the most relevant risk mitigation strategies for AMR in the meat production chain within One Health context. The monitoring and surveillance systems for AMR in meat chain are presented and briefly discussed, including sampling schemes, susceptibility testing, clinical resistance and epidemiological cut-off values. The most effective approaches to track and manage AMR in farm-abattoir-meat processing-retail continuum have been recommended, including aspects of international harmonization of critically important antimicrobials for human and veterinary use. The successful AMR monitoring and control in the meat chain can be achieved by evidence-based and integrated approach within One Health context. The application of state-of-the-art technologies and methods for detection and tracking of zoonotic food borne pathogens and AMR, such as Whole Genome Sequencing supported with data processing using Artificial Intelligence (machine learning), can contribute to achieving this goal. [ABSTRACT FROM AUTHOR]

In consideration of ongoing climate changes, it has been necessary to provide new tools capable of mitigating hydrogeological risks. These effects will be more marked in small catchments, where the geological and environmental contexts do not require long warning times to implement risk mitigation measures. In this context, deep learning models can be an effective tool for local authorities to have solid forecasts of outflows and to make correct choices during the alarm phase. In this study, we investigate the use of deep learning models able to forecast hydrometric height in very fast hydrographic basins. The errors of the models are very small and about a few centimetres, with several forecasting hours. The models allow a prediction of extreme events with also 4–6 h (RMSE of about 10–30 cm, with a forecasting time of 6 h) in hydrographic basins characterized by rapid changes in the river flow rates. However, to reduce the uncertainties of the predictions with the increase in forecasting time, the system performs better when using a machine learning model able to provide a confidence interval of the prediction based on the last observed river flow rate. By testing models based on different input datasets, the results indicate that a combination of models can provide a set of predictions allowing for a more comprehensive description of the possible future evolutions of river flows. Once the deep learning models have been trained, their application is purely objective and very rapid, permitting the development of simple software that can be used even by lower skilled individuals. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive analysis of the security and compliance framework within cloudbased ERP systems, with a particular focus on Workday, a leader in the market for enterprise resource planning (ERP) solutions. As businesses increasingly transition to cloud ERP systems, ensuring robust security and regulatory compliance has become critical to safeguarding sensitive data, maintaining operational integrity, and meeting industry-specific regulations. The paper begins by introducing the essential concepts of cloud ERP security, highlighting the challenges of data breaches, data integrity, and access control. It further explores Workday's advanced security infrastructure, including its encryption protocols, secure data storage, and real-time monitoring systems, as well as its adherence to global compliance standards such as GDPR, SOC 2, and ISO 27001. The analysis also emphasizes Workday's tailored security features for specific industries like finance, healthcare, and government, demonstrating how its platform fosters customer trust and drives adoption across diverse sectors. Looking to the future, the paper discusses emerging trends, including the integration of Artificial Intelligence (AI), Machine Learning (ML), and blockchain technology, which hold potential for enhancing data security and compliance in cloud ERP environments. This deep dive into Workday's security and compliance framework underscores its role in mitigating risks, ensuring regulatory adherence, and positioning itself as a trusted solution in an evolving cloud landscape. [ABSTRACT FROM AUTHOR]

The maritime transport sector is confronted with a multitude of operational risks that demand the implementation of efficacious management strategies. It is often the case that traditional frameworks prove inadequate, particularly in the context of integrating innovative technologies such as blockchain. This research underscores the potential of blockchain technology to mitigate the aforementioned risks by addressing challenges such as inefficiencies in documentation, a lack of transparency, security vulnerabilities, and regulatory compliance issues. Blockchain offers a decentralized, immutable ledger that facilitates documentation, reduces errors, prevents fraud, and enhances transparency and traceability. This encourages more effective collaboration among stakeholders and enhances security measures, particularly in the context of cybersecurity. Furthermore, it facilitates regulatory compliance through transparent record-keeping and automated reporting via smart contracts. While blockchain technology has the potential to optimize supply chain management and enhance data analytics for proactive risk management, the successful implementation of such solutions requires the collaboration of industry stakeholders, regulatory support, and ongoing innovation. Further research should investigate the scalability of blockchain technology, its integration with other digital technologies, its long-term impact, and the establishment of standardized protocols. The complete potential of blockchain technology in the management of maritime operational risks has yet to be fully actualized. [ABSTRACT FROM AUTHOR]

Life insurance companies, as equity stakeholders in policyholders' lives, have incentives to mitigate their health risks. I introduce a framework that enables life insurers to evaluate the financial viability of developing and implementing health engagement programs. By leveraging a proprietary big database of health and mortality information from a large U.S. life insurer, I use machine learning techniques to quantify the benefits and use a rational addiction model to calculate the costs associated with these programs. The estimated net benefit available to the life insurer from the smoking cessation program is USD 87 million and the aggregate benefit from including other chronic conditions is USD 872 million. I explore the broader application of this framework in a general health policy context. [ABSTRACT FROM AUTHOR]

The Huanghe Estuary, which is characterized by dynamic hydrological and ecological processes, is highly susceptible to marine oil spills due to dense maritime traffic and extensive industrial activities. This study evaluated the vulnerability of estuarine wetlands in the Huanghe Estuary to oil spill stress using the Pressure-Situation-Sensitivity-Recovery (PSSR) framework. By employing the Geographic Information System (GIS) and the Analytic Hierarchy Process (AHP), this study categorized the vulnerability index (0-1) into five classes: Very Low (0- 0.098), Low (0.098-0.125), Medium (0.125-0.192), High (0.192-0.224), and Very High (0.224-1). The results indicate that the ships indicator has the highest weight, followed by oil rigs. In contrast, the number of chemical splash-proof suits and tugboats have the lowest weights. Wetland vulnerability under oil spill stress exhibited significant spatial variation, with higher vulnerability observed in areas closer to the coastline, such as the eastern part of Kenli County, the northern part of Wudi County, and the northern part of Hekou District. This study underscores the need for targeted measures and enhanced monitoring to mitigate the risks of large oil spills and protect the ecological integrity of the Huanghe Estuary. The findings presented herein provide critical information that will help policymakers and environmental managers implement effective conservation strategies and risk mitigation efforts in this ecologically sensitive and economically important region. [ABSTRACT FROM AUTHOR]

High-frequency drought hazards have presented persistent challenges for environmental management and sustainable development in the South Hebei Plain, China. In this paper, the assessment of meteorological droughts in the South Hebei Plain was conducted using a multifaceted approach to ensure a comprehensive analysis. Our results demonstrated that distinct timescale cycles, ranging from centennial–semicentennial to interdecadal variations, can be identified over the past few centuries. These cycles aligned with patterns observed in the middle Yangtze basin and corresponded to regional climatic conditions. The drought cycles in the South Hebei Plain showed significant correlations with variations in the monsoon climate, sunspot activity, global changes, and human disturbances. Changes in the frequency, duration, and intensity of droughts have notably impacted hydrological variations. Extreme droughts, in particular, have heightened concerns about their effects on river systems, potentially increasing the risk of channel migration. This study enhanced our understanding of meteorological hazard patterns in the South Hebei Plain and provided valuable insights into different stages of drought management. It thus can offer lessons for improving drought preparedness and resilience and for formulating adaptive measures to mitigate future droughts and promote regional sustainability. [ABSTRACT FROM AUTHOR]

Stakeholders in multimodal freight transport encounter significant challenges due to the multitude of unknowns and inherent risks that can adversely affect operations. The subjective nature of the information complicates the identification and assessment of these risks, making them particularly challenging in the context of multimodal transport, where the potential consequences can be substantial. This research intends to provide a comprehensive understanding of the asymmetries in risks associated with multimodal freight transport by identifying and evaluating quantitative hazards. By integrating fuzzy set theory and failure mode and effects analysis (FMEA), the study offers a structured approach to statistically forecast risks, addressing imprecision in traditional risk assessments. Qualitative interviews conducted with multimodal freight transport operators in Thailand reveal critical insights, including the identification of high-priority risks such as delays from regulatory compliance, inadequate infrastructure, and inefficiencies in stakeholder communication. The findings of this study not only highlight these pressing issues but also provide actionable strategies to mitigate risks, thereby enhancing the operational resilience of multimodal freight transport systems. [ABSTRACT FROM AUTHOR]

Objective - Coal mining operations encounter substantial risks and uncertainties that originate from a wide array of sources, encompassing but not limited to natural calamities, supplier disruptions, market volatilities, regulatory modifications, and geopolitical instability. This study aims to conduct a comprehensive literature review on supply chain resilience in the coal mining industry and pinpoint potential avenues for further investigation. Methodology - A systematic literature review (SLR) was utilized to examine a total of 115 studies in the field of management and the coal mining supply chain. The studies were published from 2010 to 2023. The vulnerabilities and resilience strategies within the coal mining supply chain are the focal points of our research. We have integrated viewpoints from the domains of management and the coal mining supply chain to support our analysis. Findings - Challenges such as resource distribution, government policies, and maintenance are prevalent, pointing to the need for strategies that enhance performance through dynamic optimization and incentivizing integration. Practitioners must identify vulnerabilities in the coal mining supply chain to proactively anticipate and effectively manage potential disruptions, thus bolstering operational resilience. Novelty -This study fills the gap in extant literature by investigating the sequential application of supply chain resilience in the context of coal mining operations using the integrative view of supply chain nodes. [ABSTRACT FROM AUTHOR]

As the number of Small and Medium Enterprises (SMEs) rises in the world, the amount of sensitive data used also increases, making them targets for cyberattacks. SMEs face a host of issues such as a lack of resources and poor cybersecurity talent, resulting in multiple vulnerabilities that increase overall risk. Cybersecurity risk assessment frameworks have been developed by multiple organizations such as the National Institute of Science and Technology (NIST) and the International Organization for Standardization (ISO), but they are complicated to understand and challenging to implement. This research aimed to create an effective cybersecurity risk assessment framework specifically for SMEs while considering their limitations. This was achieved by first identifying common threats and vulnerabilities and categorizing them according to their importance and risk. Secondly, popular frameworks like the NIST CSF and ISO 27001/2 were analyzed for their proficiencies and deficiencies while identifying relevant areas for SMEs. Finally, novel techniques catered to SMEs were explored and incorporated to create an effective framework for SMEs. This framework was also developed in the form of a tool, providing an interactive and dynamic environment. The tool was effective, and the framework is a promising start but requires more quantitative analysis. [ABSTRACT FROM AUTHOR]

Abstract In consideration of ongoing climate changes, it has been necessary to provide new tools capable of mitigating hydrogeological risks. These effects will be more marked in small catchments, where the geological and environmental contexts do not require long warning times to implement risk mitigation measures. In this context, deep learning models can be an effective tool for local authorities to have solid forecasts of outflows and to make correct choices during the alarm phase. In this study, we investigate the use of deep learning models able to forecast hydrometric height in very fast hydrographic basins. The errors of the models are very small and about a few centimetres, with several forecasting hours. The models allow a prediction of extreme events with also 4–6 h (RMSE of about 10–30 cm, with a forecasting time of 6 h) in hydrographic basins characterized by rapid changes in the river flow rates. However, to reduce the uncertainties of the predictions with the increase in forecasting time, the system performs better when using a machine learning model able to provide a confidence interval of the prediction based on the last observed river flow rate. By testing models based on different input datasets, the results indicate that a combination of models can provide a set of predictions allowing for a more comprehensive description of the possible future evolutions of river flows. Once the deep learning models have been trained, their application is purely objective and very rapid, permitting the development of simple software that can be used even by lower skilled individuals.

Abstract Life insurance companies, as equity stakeholders in policyholders’ lives, have incentives to mitigate their health risks. I introduce a framework that enables life insurers to evaluate the financial viability of developing and implementing health engagement programs. By leveraging a proprietary big database of health and mortality information from a large U.S. life insurer, I use machine learning techniques to quantify the benefits and use a rational addiction model to calculate the costs associated with these programs. The estimated net benefit available to the life insurer from the smoking cessation program is USD 87 million and the aggregate benefit from including other chronic conditions is USD 872 million. I explore the broader application of this framework in a general health policy context.

Legislation and ethical guidelines around the globe call for effective human oversight of AI-based systems in high-risk contexts – that is oversight that reliably reduces the risks otherwise associated with the use of AI-based systems. Such risks may relate to the imperfect accuracy of systems (e.g., inaccurate classifications) or to ethical concerns (e.g., unfairness of outputs). Given the significant role that human oversight is expected to play in the operation of AI-based systems, it is crucial to better understand the conditions for effective human oversight. We argue that the reliable detection of errors (as an umbrella term for inaccuracies and unfairness) is crucial for effective human oversight. We then propose that Signal Detection Theory (SDT) offers a promising framework for better understanding what affects people's sensitivity (i.e., how well they are able to detect errors) and response bias (i.e., the tendency to report errors given a perceived evidence of an error) in detecting errors. Whereas an SDT perspective on the detection of inaccuracies is straightforward, we demonstrate its broader applicability by detailing the specifics for an SDT perspective on unfairness detection, including the need to choose a standard for (un)fairness. Additionally, we illustrate that an SDT perspective helps to better understand the conditions for effective error detection by showing examples of task-, system-, and person-related factors that may affect the sensitivity and response bias of humans tasked with detecting unfairness associated with the use of AI-based systems. Finally, we discuss future research directions for an SDT perspective on error detection. [ABSTRACT FROM AUTHOR]

Abstract In South Asia, Pakistan has a long and deadly history of floods that cause losses to various infrastructures, lives, and industries. This study aims to identify the most appropriate flood risk mitigation strategies that the government of Pakistan should adopt. The assessment of flood risk mitigation strategies in this study is based on certain criteria, which are analyzed using the fuzzy full consistency method. Moreover, flood risk mitigation strategies are evaluated by using the fuzzy weighted aggregated sum product assessment (WASPAS) method, considering previously prioritized criteria. According to the results, lack of governance, lack of funding and resources, and lack of flood control infrastructure are the most significant flood intensifying factors and act as major criteria for assessing flood risk mitigation strategies in Pakistan. Adopting hard engineering strategies (e.g., dams, reservoirs, river straightening and dredging, embankments, and flood relief channels), maintaining existing infrastructure, and adopting soft engineering strategies (flood plain zoning, comprehensive flood risk assessment, and sophisticated flood modeling) are identified as the top three flood risk mitigation strategies by the fuzzy WASPAS method. The highest weight (0.98) was assigned to the adoption of hard engineering strategies to mitigate flood risks. The study introduces a novel dimension by analyzing the real-time impact of the unprecedented 2022 floods, during which approximately one-third of the nation was submerged. This focus on a recent and highly significant event enhances the study’s relevance and contributes a unique perspective to the existing literature on flood risk management. The study recommends that the government of Pakistan should prioritize hard engineering strategies for effective flood risk mitigation. It also recommends that the government should incorporate these strategies in the national policy framework to reduce flood losses in the future.

This study examines the lifecycle of the Dubai Water Canal construction, focusing on risk mitigation strategies implemented across its four distinct phases. By incrementally addressing potential risks, the project minimized exposure to uncertainties and ensured the quality and safety of the end product. Key findings highlight the minimal impact on urban growth and emphasize the importance of comprehensive feasibility studies, geological assessments, and environmental impact assessments in identifying and managing risks. The study uniquely contributes to the discourse on urban development by highlighting the effectiveness of a phased approach in large-scale projects. The research methodology involved detailed environmental and technical assessments, stakeholder engagement, and continuous monitoring throughout the project. Our conclusions underscore the need for proactive risk management, thorough planning, and sustainability to ensure the resilience and success of similar infrastructure initiatives globally. [ABSTRACT FROM AUTHOR]

In recent years, green credit has significantly supported the development of the sustainable economy. However, the existing literature presents differing views on the impact of green credit on bank performance, which is crucial for the sustainability of green credit business. Meanwhile, FinTech is comprehensively empowering green credit business. This paper investigates whether FinTech influences the effect of green credit on bank performance. Based on an analysis of data from 127 Chinese commercial banks from 2007 to 2022, we find that green credit significantly enhances bank performance, and FinTech further amplifies this positive effect. This finding partially explains the conflicting views in the existing literature, as the impact of green credit on bank performance varies under different levels of FinTech. We believe that FinTech exerts its influence through three mechanisms: cost reduction, reputation enhancement, and risk mitigation. Heterogeneity analysis reveals that the impact of FinTech is more pronounced in city commercial banks, in samples with better green credit development, and during banking industry downturns. Finally, we recommend that banks actively develop FinTech and apply it to green credit businesses to maximize the positive effects of green credit. Simultaneously, regulators and governments should provide necessary support for banks. [ABSTRACT FROM AUTHOR]

We study the impact of renewable energy on forward markets for electricity. Previous literature shows that forward prices are determined by time-varying demand and volatile spot prices. We introduce supply risk from renewable generation and find that stochastic renewable output mitigates income risk for generating firms, in particular when negative shocks to renewable output have large positive price impact. This risk off-setting effect leads to reduced hedging needs for generating companies and increases the forward premium. Using five years of high-frequency spot and futures market data, we confirm our model empirically. In sum, our findings suggest that intermittent renewable generation changes firm's hedging incentives and has significant impact on forward prices for electricity. JEL Classification: G11, G13, Q42 [ABSTRACT FROM AUTHOR]

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), as the cause of Coronavirus Disease 2019 (COVID-19), may survive in sewage or wastewater treatment plant (WWTP). This condition increases the risks of reusing treated wastewater (TW), particularly in developing countries. We introduced a new index, Viral Risk Index (VRI), for risk classification based on available knowledge about SARS-CoV-2. It was calculated by six effective parameters on the decay rate of SARS-CoV-2 in wastewater. These parameters are easily quantifiable in WWTPs in developing countries and not limited to specific operational conditions. The concentrations of Fecal coliform (FC) and total suspended solids (TSS) in TW in addition to the temperature, WWTPs’ capacity, retention time (RT), and chemical oxidation demand (COD) removal are the six subindices. VRI classifies TW in 5 categories (low-high risks). This classification prioritizes WWTPs for monthly viral surveillance and risk mitigation. Here, 23 WWTPs were examined and prioritized in Iran (April-August 2020). The results indicated that the TW in 14 WWTPs could be safely reused, whereas 9 WWTPs required more surveillance and supplementary viral controls for TW reuse. Here, waste stabilization ponds had slightly safer TW than activated sludge units. Moreover, monitoring could improve the average VRI from 2019 to 2020. [ABSTRACT FROM AUTHOR]

Simple Summary: The Danish pig industry, in collaboration with the authorities, has implemented several risk-reducing measures to prevent the introduction of African Swine Fever into Danish pig production. Ongoing risk assessments are conducted to adjust or establish new measures. The first outbreaks in a new area in Northern Europe often occur in wild boar, likely due to discarded food waste at rest areas and in forested areas. A fence has been established on the Danish–German border to limit the migration of wild boar from Germany to Denmark, and the limited population of wild boar in Denmark has been culled. All trucks that transport pigs or cattle are cleaned and disinfected at the border if they have been abroad, according to the DANISH Transportstandard. Through continuous contact with the feed industry, changes in the importation of feedstuffs and other auxiliaries are analyzed, and risk assessments for each feed item are conducted. Based on this, according to the Danish Product Standard, it is not permitted to store or use feed items such as hay, straw, silage, or bedding imported from areas with outbreaks of African Swine Fever on Danish properties with pigs. These types of feed items can contain parts of dead animals in which the virus can survive for a long time. Oil cakes, fats, and oils imported from countries with African Swine Fever may only be used after heat treatment. African Swine Fever poses a significant threat to pig production. An outbreak in Denmark would have severe economic consequences, potentially resulting in a loss between 335 million and 670 million euros. To mitigate the major risk factors, the Danish authorities and the Danish pig industry have implemented several risk-reducing measures. The small wild boar population in Danish nature has been culled, and a fence between Denmark and Germany has been constructed to stop or reduce the risk of migrating wild boar from Germany. All trucks arriving from abroad, intended for the transport of Danish pigs, are inspected, washed, and disinfected at facilities near the border before being allowed to transport pigs between herds or from herds out of Denmark. Cross-border trade of feedstuffs and potentially risky materials is continuously monitored. Based on risk assessments, feed types or bedding materials from countries with African Swine Fever that could contain parts of wild boar are banned from Danish pig herds. Certain types of fats and oils from countries with African Swine Fever can only be used after heat treatment. The import of whole kernels of corn, wheat, or barley is not considered a risk. [ABSTRACT FROM AUTHOR]

Introduction: This article aims to characterise hospital admissions involving opioid toxicity across South Australia to guide future implementation and evaluation of risk mitigation strategies. Methods: International Classification of Diseases, 10th Edition codes (T40.0–T40.4) were used to identify admissions involving pre‐hospital opioid toxicity in public hospitals across South Australia from 1 June 2017 to 30 August 2020. Demographic and episode of care data were extracted and summarised using descriptive statistics. Admission cost estimates were calculated using Independent Hospital Pricing Authority data. Results: A total of 2046 cases met the criteria for inclusion; over half (56%) were female and median age on admission was 44 years (interquartile range 27 years). Where opioid toxicity was the primary diagnosis, 70% of admissions did not specify the responsible opioid and 23% were related to heroin use. One‐fifth of admissions occurred outside of metropolitan Adelaide. Individuals living in an area of relative socio‐economic disadvantage were over‐represented. Over half of admissions required a stay >24 h; 19% were admitted for ≥5 days, 22% required intensive care and ~10% required mechanical ventilation. The total estimated cost of admissions involving opioid toxicity in South Australia over the 3‐year period was $18,230,546.50, equating to $5.6 million per annum. Discussions and Conclusions: These findings highlight the significant personal, fiscal, and systemic impacts of opioid toxicity‐related hospital admissions in South Australia and provide a baseline to evaluate the effectiveness of initiatives to reduce opioid‐related harm, including real‐time prescription monitoring and take‐home naloxone supply. [ABSTRACT FROM AUTHOR]

This article analyzes the recently renewed, permanent exhibition of the Royal Museum for Central Africa (AfricaMuseum) in Tervuren, Belgium. The museum is seen as a translational space, considering the parallels between, on the one hand, curatorial strategies to represent cultural otherness and, on the other, processes of cultural and interlingual translation (Sturge 2007). We draw on an interdisciplinary mindset of translation as change and choice, as a multimodal and multimedial activity, and as an inevitably meaning-transforming process. Pressured to keep pace with the rapidly evolving public debate on decolonization, the curators-translators of the AfricaMuseum are aware that they are dealing with "sensitive texts" (Simms 1997) and have, accordingly, adopted a set of strategies to reduce perceived "translation risks" (Pym and Matsushita 2018). The article explores these strategies at three levels of translation operating in the museum: cultural, intersemiotic, and interlingual. In particular, we reveal the inherent tensions in the current display by discussing scenographic interventions that undermine the decolonization efforts in a number of galleries. These tensions are conceptualized as incomplete or incoherent forms of translation and illustrate the "work in progress" in the AfricaMuseum. [ABSTRACT FROM AUTHOR]

Agriculture is vulnerable to extreme weather shocks. Climate change increases both the frequency and the intensity of such shocks. To safeguard farmers' income and food production, climate adaptation measures are required. This article aims to examine the effectiveness of crop diversification as an adaptation measure, using Italy as a case study. We apply a control function approach to a panel dataset of 20,790 Italian farms, which considers (i) the crop diversification decision and (ii) the influence of crop diversification on farmers' levels of crop income and income risk. We find that, while specialisation can increase income, crop diversification reduces income risk most effectively when growing four different crops. At this level of diversification, income risk is approximately 29% lower as opposed to monoculture farming. Although the Common Agricultural Policy's greening payments for crop diversification make sense from an ecological and risk‐reducing point of view, we find that they are potentially insufficient to cover the loss of expected crop income from diversification. While crop diversification reduces income risk in general, we find no specific benefit in terms of weather shock‐induced risks. This may be because a price increase following a weather shock buffers its adverse effect. However, identifying the reasons requires further research. [ABSTRACT FROM AUTHOR]

Interventional radiology (IR) procedures require specific patient positioning and sometimes long durations on the procedure table. Research literature has shown that there is not enough emphasis on safe patient positioning in IR. This paper discusses potential positioning injuries, techniques to prevent injury, and how to identify at-risk patients. The recommendations from the Association of Perioperative Registered Nurses highlight the importance of proper positioning for IR procedures to enhance patient safety and reduce the risk of injury. By implementing these best practices, IR staff can ensure that their patients receive the best possible care while minimizing the risk of harm. [ABSTRACT FROM AUTHOR]

This research investigates the strategic adoption of Bitcoin as a corporate asset in Indonesia, focusing on its potential as an inflation hedge and its impact on enhancing shareholder value. Employing a mixed-method approach combining qualitative interviews and the Analytical Hierarchy Process (AHP), the study explores the challenges, risks, and opportunities associated with integrating Bitcoin into corporate financial strategies. The findings reveal that risk mitigation emerges as the primary priority for companies considering Bitcoin adoption, underscoring the need for robust strategies such as investment diversification, hedging, and scenario analysis. Stakeholder acceptance, encompassing investors, regulators, and market sentiment, is identified as the second most crucial factor, highlighting the importance of a supportive regulatory environment and investor confidence. The research also highlights the significance of analyzing price trends and optimizing asset allocation strategies. The AHP analysis identifies the Strategic Diversification approach as the most preferred alternative, aligning with Modern Portfolio Theory principles. Additionally, the study addresses accounting and financial reporting challenges associated with Bitcoin adoption, emphasizing the need for clear guidance and standards. The implementation plan outlines key aspects such as infrastructure development, education initiatives, risk management frameworks, and regulatory collaboration to facilitate the responsible integration of Bitcoin into Indonesian corporate finance strategies. [ABSTRACT FROM AUTHOR]

Landslides pose significant threats to communities and infrastructure worldwide, necessitating the development of effective hazard and exposure reduction strategies to mitigate the potential risks. In particular, debris flows can be highly destructive landslides. The paper deals with an integrated monitoring system designed both to further validate an existing debris flow inception and propagation methodology developed by the authors and to fine-tune the landslide inception and warning model to be used in an early warning system. The design of the integrated monitoring system, the definition of the acquisition time of instruments, and the processing of the measured data were based on studies performed in the study area of Favazzina (Italy), which is affected by debris flows that are very difficult to monitor. The proposed approach used to design the integrated monitoring system may serve as a useful methodological tool to be adopted in similar geological and geotechnical contexts within the framework of risk mitigation strategies. [ABSTRACT FROM AUTHOR]

This research examines the correlation between corporate green innovation and its positive impacts by analyzing firm-level data from the S&P 500 spanning the years 2001 to 2022. Drawing on previous studies, this research employs rigorous methodologies and measures to assess the influence of green innovation. The study investigates the drivers of green innovation and assesses its potential effects on firm performance and risk reduction. Firstly, it explores the factors that contribute to the adoption of green innovation. Secondly, it examines how green innovation affects firm performance and mitigates risks. The findings of the study demonstrate that implementing green innovation leads to a reduction in firm volatility and credit risk, while also enhancing firm value and emission performance. The robustness tests conducted further reinforce these conclusions, thereby contributing to the existing body of literature that highlights the crucial role of corporate characteristics in promoting sustainable business practices through green innovation. These insights hold significant value for investors, policymakers, and regulators, providing them with valuable information for making informed decisions regarding green investments and the formulation of policies that foster sustainability through green innovation. [ABSTRACT FROM AUTHOR]

During the rainy season in Brazil, landslides can have catastrophic consequences, including loss of life, damage to urban infrastructure and significant economic impacts. Now, more than eight million people in Brazil live in disaster-prone areas. The objective of this article is to present a chronological review of the principal policies and programmes at the national, state, and municipal levels, with an emphasis on their key actions aimed at mitigating the impact of disasters related to natural hazards, particularly landslides. Our analysis was based on official records of public policies from the national, state, and municipal governments. The results show that several initiatives were initially developed at the local and regional level. However, it was not until the late 1980s that a comprehensive organisation of civil protection at the national level emerged as a response measure. It is possible to highlight three phases (understanding, coexistence, and prevention) of institutional action focused on risk management in the face of disasters. Despite the growing knowledge of risk scenarios, disasters continue to occur in Brazil on an annual basis, revealing several obstacles to reducing their impact, particularly given the social and economic disparities between Brazilian regions and the applicability of public policies that must overcome the limitations of each municipality. [ABSTRACT FROM AUTHOR]

Life insurance companies are subject to various risks related to universal life products. One such risk-paid-up-arises when policyholders, at some point before maturity, exercise their option to stop paying the periodic premiums initially agreed to for the life of the policy. Here, several predictive models are applied, aimed at anticipating the future state of in-force premium payment policies. This is undertaken in conjunction with balancing techniques, designed to avoid misclassification errors caused by the scarcity of paid-up events in our data. Using the findings from our predictive modeling, we initially identify certain policyholder profiles that seem less likely to paid-up premiums and consequently may be considered as potential targets for underwriting. Additionally, we delve into an essential aspect of policy design: surrender fees. Our analysis highlights a pattern where surrender fees, intended to mitigate surrender risk, may actually exacerbate the risk of policies becoming paid-up under certain circumstances. [ABSTRACT FROM AUTHOR]

In South Asia, Pakistan has a long and deadly history of floods that cause losses to various infrastructures, lives, and industries. This study aims to identify the most appropriate flood risk mitigation strategies that the government of Pakistan should adopt. The assessment of flood risk mitigation strategies in this study is based on certain criteria, which are analyzed using the fuzzy full consistency method. Moreover, flood risk mitigation strategies are evaluated by using the fuzzy weighted aggregated sum product assessment (WASPAS) method, considering previously prioritized criteria. According to the results, lack of governance, lack of funding and resources, and lack of flood control infrastructure are the most significant flood intensifying factors and act as major criteria for assessing flood risk mitigation strategies in Pakistan. Adopting hard engineering strategies (e.g., dams, reservoirs, river straightening and dredging, embankments, and flood relief channels), maintaining existing infrastructure, and adopting soft engineering strategies (flood plain zoning, comprehensive flood risk assessment, and sophisticated flood modeling) are identified as the top three flood risk mitigation strategies by the fuzzy WASPAS method. The highest weight (0.98) was assigned to the adoption of hard engineering strategies to mitigate flood risks. The study introduces a novel dimension by analyzing the real-time impact of the unprecedented 2022 floods, during which approximately one-third of the nation was submerged. This focus on a recent and highly significant event enhances the study's relevance and contributes a unique perspective to the existing literature on flood risk management. The study recommends that the government of Pakistan should prioritize hard engineering strategies for effective flood risk mitigation. It also recommends that the government should incorporate these strategies in the national policy framework to reduce flood losses in the future. [ABSTRACT FROM AUTHOR]

Significant risks in project completion delay could be buried in the development of project schedules because of theoretical flaws in project schedule risk analysis. Major project delays hamper infrastructure development endeavors and cause negative consequences to project finance, the public interest, and socioeconomic growth. This research critically reviews the theoretical foundation of the Program Evaluation and Review Technique (PERT) and identifies two major flaws: (1) failing to account for variances of activities on subcritical paths; and (2) lacking the functionality of characterizing variance-criticality for activities in a project network. Further, the path variance-criticality index and the activity variance-criticality index are formalized for defining the subcritical path(s) and identifying the variance-critical activities. Reducing time duration variances in the identified variance-critical activities exerts a significant impact on mitigating project schedule delay risks. A case study is given to illustrate the analytical steps for identifying variance-critical activities in a project. Monte Carlo simulations were conducted to validate the effectiveness of the proposed analytical approach. The enhanced PERT for project schedule risk analysis is instrumental in (1) identifying critical and subcritical paths in the project network model; (2) clarifying the notion of variance-criticality for prioritization of activities based on the impact of activity time variance on project time variance; and (3) reining in project schedule risks by reducing time duration variances on those variance-critical activities in project planning. [ABSTRACT FROM AUTHOR]

Purpose of Review: The purpose of this review is to summarize and evaluate most recent evidence on the epidemiology of infections and associated risk factors in patients with primary systemic vasculitides (PSV), as well as discuss mitigation strategies including the risk of antibiotic prophylaxis. Recent Findings: Infections remain one of the leading causes of mortality in patients with PSV, with rates of severe infection ranging from 16 to 40% in different cohorts. Older age, frailty, renal and pulmonary involvement, and higher burden of comorbidities have been recognized as important patient-associated risk factors. Treatments including higher cumulative doses of glucocorticoids are associated with an increased risk of infections, and recent studies show the potential benefit of interventions such as reduced-dose glucocorticoid regimens. Existing mitigation strategies include screening, vaccination, and infection prophylaxis. The latter remains particularly important for Pneumocystis jirovecii pneumonia; however, the benefit-risk ratio seems to be less clear outside of induction phase (i.e., high dose of glucocorticoids) and optimal treatment duration remains less clear. Summary: Patients with PSV are at increased risk of infections, due to disease itself, comorbidities, and treatment side effects. Awareness of the timing and types of infection, as well as mitigation strategies are imperative to ensure treatment success and survival for patients. [ABSTRACT FROM AUTHOR]

The application of antimicrobials in aquaculture primarily aims to prevent and treat bacterial infections in fish, but their inappropriate use may result in the emergence of zoonotic antibiotic-resistant bacteria and the subsequent transmission of resistant strains to humans via food consumption. The aquatic environment serves as a potential reservoir for resistant bacteria, providing an ideal breeding ground for development of antimicrobial resistance (AMR). The mutual inter-connection of intensive fish-farming systems with terrestrial environments, the food processing industry and human population creates pathways for the transmission of resistant bacteria, exacerbating the problem further. The aim of this study was to provide an overview of the most effective and available risk mitigation strategies to tackle AMR in aquaculture, based on the One Health (OH) concept. The stringent antimicrobial use guidelines, promoting disease control methods like enhanced farm biosecurity measures and vaccinations, alternatives to antibiotics (ABs) (prebiotics, probiotics, immunostimulants, essential oils (EOs), peptides and phage therapy), feeding practices, genetics, monitoring water quality, and improving wastewater treatment, rather than applying excessive use of antimicrobials, can effectively prevent the development of AMR and release of resistant bacteria into the environment and food. The contribution of the environment to AMR development traditionally receives less attention, and, therefore, environmental aspects should be included more prominently in OH efforts to predict, detect and prevent the risks to health. This is of particular importance for low and middle-income countries with a lack of integration of the national AMR action plans (NAPs) with the aquaculture-producing environment. Integrated control of AMR in fisheries based on the OH approach can contribute to substantial decrease in resistance, and such is the case in Asia, where in aquaculture, the percentage of antimicrobial compounds with resistance exceeding 50% (P50) decreased from 52% to 22% within the period of the previous two decades. [ABSTRACT FROM AUTHOR]

Supply chains play a critical role in the operational success of organizations, impacting both costs and product quality. However, they are often exposed to various risks that can disrupt business processes. This research aims to identify supply chain risks and propose mitigation strategies using the House of Risk (HOR) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) methods. Through interviews, key issues were identified in a fiberglass company's supply chain, including raw material supply fluctuations, procurement cost variability, defective materials, inappropriate specifications, outdated technology, insufficient worker skills, and ambitious company targets. The novelty of this study lies in the application of MOORA, which introduces a correlation matrix for risk mitigation by considering both cost minimization and benefit maximization. The analysis identified 12 risk agents and 26 risk events, which were prioritized using HOR stage 2 with the MOORA method. The top preventive actions were ranked, providing actionable recommendations for companies to address supply chain risks more effectively. The findings of this research offer practical insights for companies in the fiberglass industry to enhance supply chain resilience by integrating cost and benefit considerations into their risk management strategies. [ABSTRACT FROM AUTHOR]

Earthquake-induced damage to gas pipelines can have severe economic, social, and environmental consequences. To mitigate these risks, one effective way is to carefully design the route of gas pipelines, considering the seismic hazard of the region. This paper proposes a methodology that incorporates seismic risk assessment into the process of designing gas pipeline routes. Conventional gas pipeline design methods consider only minimum distances from faults and fail to account for seismic potential. The methodology is applied to three gas pipeline routing problems in the high seismic region of southern Iran. Seismic risk is evaluated using the HAZUS method, and routing is performed through a GIS-based approach. Results are compared with conventional approaches in terms of length, seismic risks, and damage costs, showing the proposed method's effectiveness in reducing immediate consequences like leaks and breaks in gas transportation. The proposed method reduces seismic damage by 3 to 68% for routing problems. [ABSTRACT FROM AUTHOR]

Introduction: Lipoprotein(a) [Lp(a)] is linked to higher risks of atherosclerotic cardiovascular disease (ASCVD). Current guideline recommendations are quite liberal on measuring Lp(a) (Class IIa, Level C), and may lead to underuse among (interventional) cardiologists. Areas covered: This case-based narrative review outlines four clinical cases of patients with elevated Lp(a) to illustrate its pathophysiological impact on coronary artery disease (CAD). The expert consensus statements from the American Heart Association (AHA) and European Atherosclerosis Society (EAS) served as the basis of this review. More recent publications, from 2023 to 2024, were accessed through the MEDLINE online library. Expert opinion: We highlighted the importance of routine Lp(a) measurement in identifying patients at high risk for atherosclerosis, necessitating potent risk mitigation. Measuring Lp(a) helps clinicians identify which patients are at highest residual risk, who require potent pharmacological treatment and special attention during catheter interventions. As noninvasive and advanced intravascular imaging modalities evolve, future catheterization laboratories will integrate advanced imaging, diagnostics, and treatment, facilitating tailored patient care. Knowing Lp(a) levels is crucial in this context. While Lp(a)-lowering drugs are currently investigated in clinical trials, it is of paramount importance to know Lp(a) levels and strive toward aggressive management of other modifiable risk factors in patients with elevated Lp(a) and established symptomatic CAD being diagnosed or treated in catheterization laboratories. [ABSTRACT FROM AUTHOR]

This research takes a look at how the imperatives of digital transformation impose an impact on the landscape of risk management strategies across four dimensions: the adoption of technology, cybersecurity and data privacy, regulatory compliance, and finally, risk mitigation strategies. 100 participants from different walks of industry from jordan responded to structured questionnaires in the assessment of how such organizations operate to manage emerging risks ushered in by digital technologies. Results indicate that while digital transformation significantly enhances operational efficiency and agility, it introduces new causes for concern in cybersecurity and compliance. Respondents showed a high level of investment in technology with a mean of 4.3 and efficiency improvement at a mean of 4.5, although some shortcomings persist regarding employee cybersecurity awareness, with a mean of 3.6, and complexity of regulatory compliance, with a mean of 3.7. Although risk mitigation strategies have become common, only 32% of organizations have integrated their risk management teams into digital initiatives. This paper concludes by remarking on the basis of an update an organization needs to make to its risk management framework, improve cybersecurity training, and undertake proactive compliance mappings in order to achieve successful meeting of the complexities posed by the digital era. [ABSTRACT FROM AUTHOR]

The Digital Services Act (DSA) creates a system of general risk management that is composed of two main obligations: risk assessment (Article 34), and risk mitigation (Article 35). The obligations are mandatory for very large online platforms and search engines (VLOPs/VLOSEs). The adoption of the risk-based approach to digital services make the law more future-proof. But inevitably it also makes the law very vague. This vagueness of the statutory language causes some to suggest that the European Commission will inevitably become the proverbial Ministry of Truth when tackling disinformation. This article argues that upon closer reading of the DSA, and its constitutional context, the worries that the Commission inevitably becomes a Ministry of Truth are misplaced. Suppressing incorrect or misleading lawful information is not the goal of the DSA. That is not to say that the DSA cannot be abused. But the law is not pre-programmed to do so. [ABSTRACT FROM AUTHOR]

Patients with chronic pain face significant barriers in finding clinicians to manage long-term opioid therapy (LTOT). For patients on LTOT, it is increasingly common to have them sign opioid treatment agreements (OTAs). OTAs enumerate the risks of opioids, as informed consent documents would, but also the requirements that patients must meet to receive LTOT. While there has been an ongoing scholarly discussion about the practical and ethical implications of OTA use in the abstract, little is known about how clinicians use them and if OTAs themselves modify clinician prescribing practices. To determine how clinicians use OTAs and the potential impacts of OTAs on opioid prescribing. We conducted qualitative analysis of four focus groups of clinicians from a large Midwestern academic medical center. Groups were organized according to self-identified prescribing patterns: two groups for clinicians who identified as prescribers of LTOT, and two who did not. 17 clinicians from General Internal Medicine, Family Medicine, and Palliative Care were recruited using purposive, convenience sampling. Discussions were recorded, transcribed, and analyzed for themes using reflexive thematic analysis by a multidisciplinary team. Our analysis identified three main themes: (1) OTAs did not influence clinicians' decisions whether to use LTOT generally but did shape clinical decision-making for individual patients; (2) clinicians feel OTAs intensify the power they have over patients, though this was not uniformly judged as harmful; (3) there is a potential misalignment between the intended purposes of OTAs and their implementation. This study reveals a complicated relationship between OTAs and access to pain management. While OTAs seem not to impact the clinicians' decisions about whether to use LTOT generally, they do sometimes influence prescribing decisions for individual patients. Clinicians shared complex views about OTAs' purposes, which shows the need for more clarity about how OTAs could be used to promote shared decision-making, joint accountability, informed consent, and patient education. [ABSTRACT FROM AUTHOR]

The emergence of connected vehicles has transformed the automotive sector by enhancing the vehicle's functionality, efficiency, and safety. The performance and security of these vehicles significantly rely on the deployment of the over-the-air software update. However, the execution of OTA comes with many challenges, especially with regard to security vulnerabilities and risks. The current paper delves into the complexities of the secure OTA software update for connected vehicles addressing the most critical issues; authentication; encryption and integrity verification, and risk management. Through advanced cryptographic methodologies, stringent authentication processes, and secure communication channels, automotive manufacturers and other service providers can guarantee the integrity and confidentiality of the updates, and consumers' data from malicious attack. Moreover, the paper explores the regulatory and other standards-related matters that control the use of OTA in the automotive sector. An understanding of the secure OTA update mechanisms aids the stakeholders in establishing a resilient connection in connected vehicles boosting consumer trust and the future of the automobiles industry. [ABSTRACT FROM AUTHOR]

Rubella, or German measles, is a vaccine-preventable disease. Rubella infection is usually mild; however, infection in pregnancy is associated with severe outcomes for the baby, including pregnancy loss or a combination of developmental defects called congenital rubella syndrome. Within the last ten-year period, two cases of congenital rubella syndrome in Saskatchewan were reported to the provincial ministry and the Public Health Agency of Canada of the newborns of mothers who had recently arrived from Sub-Saharan Africa. Both infants had multiple health complications at birth consistent with congenital rubella and tested positive for the rubella virus. The article discusses the challenges encountered by the healthcare system in diagnosing, investigating, monitoring and managing cases of congenital rubella syndrome to prevent further sporadic transmission. The article emphasizes the need to provide additional support for cases and their households, especially new Canadians with less support to comply with public health advice and the importance of routine immunization to eliminate rubella globally. [ABSTRACT FROM AUTHOR]