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Background: Operators in the obituary and necropsy sectors are exposed to various environmental hazards during specific tasks. Despite this exposure, occupational risks have often been underestimated, resulting in a lack of substantial evidence. The primary objectives of this study were to identify sources of chemical risk, establish procedures for monitoring and quantifying exposure during necropsy activities, and recommend adjustments to regulatory guidelines to protect the health of the operators. The study was conducted at the Legal Medicine Unit of the Umberto I General Hospital in Rome, focusing on the quantitative measurement of particulate matter (PM) exposure among at-risk operators during necropsy activities. Environmental levels of total suspended particles, PM10, PM4, PM2.5, and PM1 were assessed by evaluating the average, minimum, and maximum instantaneous indoor concentrations using an airborne analyzer. Results: The monitoring activities revealed that the PM concentrations were significantly lower than the recognized reference values. However, bone sawing, body removal, and cleaning were identified as high-risk maneuvers for dust suspension. Conclusions: Our study highlighted specific risks associated with necropsy activities, particularly concerning timing and certain maneuvers. These results may lead to interventions for improving current prevention procedures, implementing good practices, and developing specific guidelines to enhance operator safety. [ABSTRACT FROM AUTHOR]

Introduction: Needlestick and sharps injuries (NSSIs) represent an existential occupational hazard risk to orthopaedic surgeons during their career due to the interaction with various devices, instruments and bone fragments. Consequently, NSSIs have the potential to transmit infections such as Hepatitis B (HBV), Hepatitis C (HCV) and Human Immunodeficiency Virus (HIV) leading to serious illness. The purpose of this cross-sectional study was to identify the clinical settings predisposing orthopaedic surgeons to NSSIs and assess their adherence to safety protocols in the Indian context. Materials and Methods: An online cross-sectional survey of 618 orthopaedic surgeons in India, stratified by experience into two groups: under five years and with 5 years or more was undertaken. The data were collected via an expert-validated online questionnaire to evaluate demographic distribution, injury characteristics, knowledge of safety protocols, and adherence to these protocols. Descriptive statistics summarized the data, Chi-square tests assessed variable associations, and odds ratios were computed for significant variables. Ethical integrity was maintained via electronic informed consent and for confidentiality assurances. Results: The study revealed that orthopaedic surgeons with less than 5 years of clinical experience had higher risks for NSSIs as compared to those with 5 or more years of clinical practice. Conversely, the latter group was more susceptible to bone spike injuries and viral positive needlestick incidents. The analysis shows that whilst the more experienced practitioners displayed greater proficiency in the application of universal precautions and NSSI prevention, they were also less likely to report injuries, often due to discomfiture. Risk profiles were consistent across different practice settings and affiliations, regardless of experience level. Conclusion: This cross-sectional study reveals less experienced orthopaedic surgeons face higher risks of NSSIs, possibly due to inadequate education or awareness. More experienced practitioners encounter distinct risks, likely owing to long-term exposure and traditional practices. There is an immediate need to raise awareness of the potential risks of NSSIs, enhanced education, appropriate training, collaboration with the hospital risk management team and developing a culture of transparent reporting to mitigate these risks. The emphasis should be on reducing the incidence and fostering open reporting of NSSIs to protect clinicians and promote health safety. [ABSTRACT FROM AUTHOR]

Data-driven business models imply the inter-organisational exchange of data or similar value objects. Data science methods enable organisations to discover patterns and eventually knowledge from data. Further, by training machine learning models, knowledge is materialised in those models. Thus, organisations might risk the exposure of competitive knowledge by sharing data-related value objects, such as data, models or predictions. Although knowledge risks have been studied in traditional business models, little research has been conducted in the direction of data-driven business models. In this explorative qualitative study, we conducted 28 expert interviews in three rounds (two exploratory and one evaluatory) and identified five types of risks along the three basic types of value objects: data, models and predictions. These risks depend on the context, i.e., when competitive knowledge could be discovered from shared value objects. We found that those risks can be mitigated by technology, contractual regulations, trusted relationships, and adjusting the business model design. In this study, we show that the risk of knowledge leakage is a relevant risk factor in data-driven business models. Overall, knowledge risks should be considered already during business model design, and their management requires an interdisciplinary approach via a balanced assessment. The level of knowledge protection from a technology perspective highly depends on computer science innovations and thus is a moving target. As an outlook, we suggest that knowledge risk will become even more relevant with the extensive usage of machine learning and artificial intelligence in data-driven business models. [ABSTRACT FROM AUTHOR]

Financial risks are among the most important risks in the construction industry projects, which significantly impact project objectives, including project cost. Besides, financial risks have many interactions with each other and project parameters, which must be taken into account to analyze risks correctly. In addition, a source of financial risks in a project is the contract, which is the most important project document. Identifying terms related to financial risks in a contract and considering their effects on the risk management process is an essential issue that has been neglected. Hence, an integrated model for evaluating financial risks and their related contractual clauses were presented. To this end, the effect of financial risks on the project cost was simulated using a system dynamics model. Moreover, terms related to financial risks in a contract text were identified and extracted using text mining, and their effect was included in the system dynamics model. The model was implemented in a hospital construction project in Tehran as a case study, and its results were analyzed. The innovation of the research is integrating text mining and the system dynamics model to investigate the effect of financial risks and related contractual clauses on the project cost. [ABSTRACT FROM AUTHOR]

Credit risk, stemming from the failure of a contractual party, is a significant variable in financial institutions. Assessing credit risk involves evaluating the creditworthiness of individuals, businesses, or entities to predict the likelihood of defaulting on financial obligations. While financial institutions categorize consumers based on creditworthiness, there is no universally defined set of attributes or indices. This research proposes Range control-based class imbalance and Optimized Granular Elastic Net regression (ROGENet) for feature selection in credit risk assessment. The dataset exhibits severe class imbalance, addressed using Range-Controlled Synthetic Minority Oversampling TEchnique (RCSMOTE). The balanced data undergo Granular Elastic Net regression with hybrid Gazelle sand cat Swarm Optimization (GENGSO) for feature selection. Elastic net, ensuring sparsity and grouping for correlated features, proves beneficial for assessing credit risk. ROGENet provides a detailed perspective on credit risk evaluation, surpassing conventional methods. The oversampling feature selection enhances the accuracy of minority class by 99.4, 99, 98.6 and 97.3%, respectively. [ABSTRACT FROM AUTHOR]

Due to their inherent properties, biocidal products might pose a risk to human and animal health and the environment. In risk management, there exists uncertainty about private users' comprehension of and willingness-to-adhere to use instructions that mitigate these risks (e.g., limit frequency of use or application area). This study aimed at providing insights into the users' perspective by focusing on their attention, comprehension, and the attitudinal predictors of protection motivation. In the online study (N = 957 participants from Germany) were introduced to a hypothetical purchase scenario featuring an insect spray and a realistic set of use instructions. Next, the participants' attention for the use instruction was measured in self-report and by tracking the time spent on the page with the use instruction, while Likert scale-type questions measured the comprehensibility, protection motivation, and predictors. Participants reported higher protection motivation if they spent more time with the use instruction, perceived it as comprehensible, rated the threat to humans, animals, and the environment as more severe, perceived themselves as responsible (i.e., internal locus of control) and capable (i.e., self-efficacy) of adhering to the use instructions, perceived adherence to the use instructions as effective (i.e., response efficacy) and did not perceive biocidal products as inherently safe (i.e., neutral locus of control). These results offer valuable information for an improved regulation of biocidal products and better management of potential risks associated with their use. They also provide concepts for interventions to ensure users of biocidal products follow the instructions for a safe use and better protection of the environment. [ABSTRACT FROM AUTHOR]

Claims analysis and risk management is key to avoiding fraud and managing risk in the life insurance industry. Though visualization plays a fundamental role in supporting analysis tasks in the business domain, exploring user behaviour remains a challenging task. The prevalence of natural language interactions enhanced with data visualization has become quite the norm. With the increasing demand for visualization tools and varying levels of user expertise, the use of a natural language interface (NLI) is common. However, the design of visual analytics tools enhanced by NLIs for risk management and claim analysis requires thorough task analysis and domain expertise. In this work, we investigate an alternative approach through a natural language interaction-based interactive visualization such as a chart, pie chart, or histogram, which can be used for insurance claim analysis and risk management. We design a new visual analytics solution named InsCRMVis which is enhanced by NLIs. We present an expert evaluation of InsCRMVis based on the Task Load Index questionnaire which is currently the standard metrics measure to investigate its usability (effectiveness, efficiency, satisfaction) to support human task performance. To evaluate its performance, we performed a user study of ten experts which suggests that InsCRMVis can provide better insights and assistance to insurance managers in reducing loss and guiding changes to insurance premium policies. Furthermore, we provide a concise set of guidelines that can be used when visualizing risk to avoid dangers in the insurance domain. We discuss the challenges associated with the use of a visualization system in the insurance industry, focusing on aspects related to visualization research. [ABSTRACT FROM AUTHOR]

Seaweed is seen as a promising future source of biomass, and significant efforts are taken to upscale seaweed aquaculture production in Europe. Despite regulatory frameworks for food safety, environmental safety, and occupational health and safety applicable to seaweed production, a major barrier to upscaling production is the lack of commonly accepted, uniform frameworks for safety assessment. As a consequence, efforts to deal with food safety, environmental safety, and occupational health and safety are fragmented. Based on a literature review and consultations with stakeholders, this paper introduces a generic protocol on how to approach safety of the production of seaweed. A prototype version of the generic protocol was evaluated in a practical setting in Norway. Results show that a consistent, structured approach to safety makes it possible to identify hazards and prioritize and collect data on key hazards. The protocol facilitated a sector discussion on safety, providing a shared discourse to talk about safety. It must be acknowledged that the farming and processing practices and the location of cultivation strongly influence which hazards are most relevant. The protocol succeeded in bringing focus to data collection, putting effort into the analysis of hazards considered most relevant in a practical setting. [ABSTRACT FROM AUTHOR]

Building safety has become a serious and important topic for the development of the construction industry, as well as for the preservation of contractors' and workers' lives and property. With the development and expansion of a sensitive and complex monitoring system for the safety of buildings, allowing accidents to occur is no longer acceptable. Therefore, risk management identifies potential hazards before any operations take place, and the safety system operates based on a planned, organized, and systematic process known as "pre-incident." This plan is based on the analysis-control method. Failure to utilize risk management methods and the acceleration of the construction industry can lead to a decrease in the safety of residents and introduce unpredictable risks. While nowadays risk management is less utilized for project control, contractors face numerous problems after construction. Lack of resources and facilities in this regard can be problematic, but emerging building technologies, which are slowly being identified, can solve and separate most of the industry's safety issues. Therefore, utilizing innovative building technologies not only enhances quality, speed, and cost reduction in construction but also contributes significantly to industrialization and the reduction of risks resulting from deteriorated structures towards building safety. In this study, the extraordinary effects of innovative technologies on building safety have been examined, and the relationship between risk management and innovative technologies has been investigated using a questionnaire. The impacts of all risk management and safety aspects are examined in this research, which ultimately resulted in clarifying the direct and meaningful connection between risk management and safety with modern technologies and determining the necessary corrective measures to improve building safety performance through the use of innovative building technologies. [ABSTRACT FROM AUTHOR]

We test whether organizational risk management matters to bondholders of U.S. bank holding companies (BHCs), and find that debt financing costs increase when the BHC has lower-quality risk management. Consistent with bailouts giving rise to moral hazard among bank creditors, we find that bondholders put less emphasis on risk management in large institutions for which bailouts are expected ex-ante. BHCs that maintained strong risk management before the financial crisis had lower debt costs during and after the crisis, compared to other banks. Overall, quality risk management can curtail risk exposures at BHCs and result in lower debt costs. [ABSTRACT FROM AUTHOR]

While previous studies primarily use economy-wide indicators for political risk, Hassan et al. (Quart J Econ 134(4):2135–2202, 2019) propose that a significant portion of political risk manifests itself at the individual firm level. We use their measure of political risk to examine whether and how acquirers' firm-level idiosyncratic political risks affect their mergers and acquisitions (M&A) decisions based on a sample of U.S. firms. We find that firms exposed to a high level of perceived political risk are less likely to conduct M&As. Furthermore, the negative association between firm-level political risk and M&As is more pronounced when acquiring firms lack either financial capacities or non-financial political/social capacities. More importantly, while firms with high political risk generally delay M&As, we find evidence suggesting that acquiring firms may hedge against their firm-level political risk by strategically choosing low-risk M&A targets and conducting vertical integration. Finally, we show that effectively hedged deals exhibit superior post-M&A performance in terms of higher announcement return, lower likelihood of subsequent divestiture and higher post-acquisition change in financial performance. [ABSTRACT FROM AUTHOR]

Domestic violence (DV) impacts the safety and well-being of adult victims and their children who are exposed to the violence. Police play a critical role in providing intervention strategies to protect the welfare of victims of DV. Police training, policy and procedures on intervention strategies are often adult-centric leaving little direct police interaction with children. Objective: The objective of the current study is to identify the challenges police officers perceive in providing effective safety planning and risk management strategies for domestic violence victims and their children. Participants, Setting & Methods: Interviews with domestic violence police specialists (n = 12) in Ontario, Canada were used to gather information on police officers' perspective on the challenges they face in executing safety planning and risk management strategies. A dual deductive/inductive approach to a thematic analysis at the sematic level was used (Braun and Clarke, Qualitative Research in Psychology 3:77–101, 2006) to explore themes. Results: The major themes that emerged from the interviews were: (a) challenges with the broader economic/social and judicial system; (b) challenges created by organizational factors; and (c) individual challenges affiliated with police officers' perception of barriers they encountered. These challenges all impact the police response to providing intervention strategies to DV victims and their child(ren). Conclusions: This study highlights the need for police organizations to formalize training, policies, and directives specific to safety planning and risk management for adult victims of DV and their children. [ABSTRACT FROM AUTHOR]

In this paper we build a methodology for pricing of insurance-linked securities which are tied to multiple natural catastrophe perils. As a representative example, we construct a multi-peril catastrophe (CAT) bond which can be linked to the industry loss indices or actual losses incurred by an insurer. We provide pricing formulas for such CAT bonds. We illustrate the introduced methodology on the US natural catastrophe data obtained from Property Claim Services (PCS). Within this dataset, we specifically examine two types of risks: losses associated with wind and thunderstorm events, and those linked to winter storm events. Then, we fit and validate the underlying compound non-homogeneous Poisson processes taking into account the fact that the data are left-truncated. The best fitted loss distributions appear to be Burr and Generalised Extreme Value and for the first peril and log-normal for the second. Finally, we visualise the zero-coupon CAT bond prices for the selected best-fitted models. [ABSTRACT FROM AUTHOR]

Overhead road obstacles present a significant logistical hazard to the heavy vehicle industry. Traditional overheight vehicle warning systems such as passive warning systems (PWS) and active warning systems (AWS) have not adequately reduced the frequency and impact of overheight incidents, encouraging transportation agencies to employ intelligent transport system (ITS) strategies using state-of-the-art advanced technologies. This research takes an innovative approach in developing an immersive user-focused experience, harnessing multi-disciplinary methods and tools to engineer a spatial digital twin prototype for a novel Internet-of-Things (IoT)-based active warning alert and re-routing system (AWARS). LiDAR and 3D GIS were used to model the complex road environment, tailored to the strict fiscal objectives sought by economically mindful organisations. Tree crowns were extracted from near-Infrared aerial imagery and digital elevation models, supplying the dimensions necessary for 3D tree modelling. IoT connectivity was configured using a real-time analytics approach to deliver alerts and re-routing options. The World Traffic Service with live and predictive traffic data was used for the routing application programming interface (API). A standard-configuration common rigid truck (CRT) was inserted into the 3D road environment model to simulate overheight collisions and to ascertain the effect of re-routing on estimated time of arrival (ETA). Longer ETA durations were observed for routes computed by the digital twin. Theoretically, enhanced situational awareness and subsequent reduction of risk likelihood suggests an optimised response to industry demands, despite extended travel times, cultivating a favorable impact on the supply chain through enhanced safety management. [ABSTRACT FROM AUTHOR]

In this paper we introduce the Intensive Mobile Treatment (IMT) model, which arose from a 2016 New York City initiative to engage individuals who were "falling through the cracks" of the mental health, housing, and criminal justice systems. People who are referred to IMT often have extensive histories of trauma. They experience structural racism and discrimination within systems and thus can present as distrustful of treatment teams. We detail the structure of the program as we practice it at our non-profit agency and outline the psychodynamic concepts that inform our work with challenging populations. We acknowledge IMT's role in engaging in advocacy and addressing social justice in our work. We also discuss how through this model we are able to both mitigate and tolerate risk in participants with difficult-to-manage behaviors. This is typically a long-term, non-linear process. We address how this impacts the team dynamic as a whole and explain how with long-term, trusting therapeutic relationships, participants can change and grow over time. We also explain the ways in which our non-billing model plays an integral role in the treatment we are able to provide and identify several challenges and areas for program growth. In outlining our model and its methodology, we hope to empower other practitioners to adapt IMT to other settings beyond the New York City area. [ABSTRACT FROM AUTHOR]

Project risk management which has been rarely considered, especially in software projects, is a crucial process to complete projects successfully. This paper aims to propose a novel project risk management framework both to evaluate the project risks and to predict the success or failure of software projects based on their risk. This new framework uses Machine Learning (ML) and Multi-Attribute Decision-Making under a cloud model to effectively manage uncertainty. Based on the proposed framework, in the first stage, the important risks of the software projects are identified by an organized approach. Then, the risks are evaluated based on their probability and impacts on time, cost, and quality. In the second stage, the obtained results of the previous stage are entered into a new COPRAS method under the cloud model to rank the risks. Then, the risks are classified into various groups according to their rank. It helps project managers to gain a profound awareness of their high-priority project risks. In this paper, data on risks for fifty software projects has been collected. All the steps of the second stage are implemented on these projects in order to assess their risks. As a result, a data set whose features are nine types of software project risks and the label of success or failure of the projects is created. To recognize the pattern between risks' values and the success or failure of the projects, various efficient ML algorithms such as Naive Bayes, Logistic regression, Decision Tree, Bagging, Random Forest, and AdaBoost are applied. This framework can predict the success or failure of software projects based on their risks with good accuracy. The results depict that the Naive Bayes algorithm has the best results compared to others. [ABSTRACT FROM AUTHOR]

The article considers approaches to improving the risk assessment system based on action priority setting, which is used in the AIAG & VDA FMEA methodology. Two variants of action priority matrices are proposed, both symmetrical in terms of the number of qualitative categories for the severity, occurrence, and detection (SOD) scores. The new matrices are compared with the original matrix and with each other. The changes and their significance for risk analysis results are considered and discussed for each of the new matrices. [ABSTRACT FROM AUTHOR]

The article considers the risk assessment system based on selecting risk response actions in accordance with the calculated risk priority number. Problems of the application of the RPN method and ideas for overcoming these problems are considered. An approach consistent with the AIAG & VDA FMEA methodology that is capable of eliminating some disadvantages of using the priority risk number method is proposed. [ABSTRACT FROM AUTHOR]

As the problems with managing traffic in cities get worse, this paper looks at a way to make it easier to judge safety and handle risks in the flow of traffic on major roads in cities. By combining artificial driving and smart network connection, the study aims to find better ways to predict, lower, and respond to possible risks on city roads. Getting a lot of data from various sources, such as traffic cameras, sensors, and systems that link vehicles, is part of the research method. Artificial driving models are used to simulate and guess how traffic will move. Cars and buildings can share data in real time through an intelligent network connection. This paper carefully looks at safety by measuring things like collision rates and response times, and then it compares the findings to what happened when traditional traffic management methods were used. Adaptive traffic control and predictive analytics are two types of risk management that are talked about as ways to stop safety problems before they happen. Case studies show examples of how artificial driving and smart network connections have been used successfully to improve road safety in cities. At the end of the paper, issues that came up are discussed, and ideas are given for future research that will help improve how safety is assessed and risks are managed in metro areas where arterial traffic flow is changing. [ABSTRACT FROM AUTHOR]

Purpose: To propose a five-point scale for radiology report importance called Report Importance Category (RIC) and to compare the performance of natural language processing (NLP) algorithms in assessing RIC using head computed tomography (CT) reports written in Japanese. Materials and methods: 3728 Japanese head CT reports performed at Osaka University Hospital in 2020 were included. RIC (category 0: no findings, category 1: minor findings, category 2: routine follow-up, category 3: careful follow-up, and category 4: examination or therapy) was established based not only on patient severity but also on the novelty of the information. The manual assessment of RIC for the reports was performed under the consensus of two out of four neuroradiologists. The performance of four NLP models for classifying RIC was compared using fivefold cross-validation: logistic regression, bidirectional long–short-term memory (BiLSTM), general bidirectional encoder representations of transformers (general BERT), and domain-specific BERT (BERT for medical domain). Results: The proportion of each RIC in the whole data set was 15.0%, 26.7%, 44.2%, 7.7%, and 6.4%, respectively. Domain-specific BERT showed the highest accuracy (0.8434 ± 0.0063) in assessing RIC and significantly higher AUC in categories 1 (0.9813 ± 0.0011), 2 (0.9492 ± 0.0045), 3 (0.9637 ± 0.0050), and 4 (0.9548 ± 0.0074) than the other models (p <.05). Analysis using layer-integrated gradients showed that the domain-specific BERT model could detect important words, such as disease names in reports. Conclusions: Domain-specific BERT has superiority over the other models in assessing our newly proposed criteria called RIC of head CT radiology reports. The accumulation of similar and further studies of has a potential to contribute to medical safety by preventing missed important findings by clinicians. [ABSTRACT FROM AUTHOR]

With the social economy's rapid progress and the popularization of environmental awareness, ecological enterprises have gradually become a crucial trend in the development of modern enterprises. This work intends to promote the development of ecological enterprises to a higher level. This work first analyzes the management mode of ecological enterprises in the context of big data in China. Then, it establishes various indicators to analyze the role of sustainable technological innovation in enterprise development and the impact of digital empowerment on enterprise development. Finally, this work takes China's manufacturing industry and ecological enterprises in Hubei Province as examples to summarize the digital empowerment of sustainable technological innovation management of ecological enterprises under the background of big data. The final result indicates that sustainable technological innovation significantly reduces ecological enterprises' resource consumption and waste emissions. Additionally, it has a significant positive effect on improving enterprise output value and economic benefits. The digital empowerment of enterprises has a significant driving effect on sustainable technological innovation, with a digital driving coefficient of 26. This work provides a feasible scheme for the specific application of big data analysis in the technology innovation management of ecological enterprises, including market demand analysis, environmental monitoring and governance, technology assessment and risk management. This work expounds the role of big data analysis technology in improving decision-making efficiency, optimizing resource allocation and enhancing the competitiveness of enterprises in the digital empowerment of ecological enterprises. [ABSTRACT FROM AUTHOR]

Rural areas are disproportionately affected by climate change due to their relative social and economic vulnerability. Particularly in a coastal region like Shanghai where sea level rise and natural hazards are worsened by climate change, it is crucial to address these problems. Despite this, there exists a knowledge gap on climate change vulnerability in Shanghai rural areas. This study assesses the climate change vulnerability of rural areas in Shanghai by constructing a climate change vulnerability index based on the IPCC framework for vulnerability. Statistical, geospatial, and biophysical data was collected on all rural areas in Shanghai, and factor analysis was performed on the dataset to extract 6 factors from a total of 21 indicators, with these factors making up 67.39% of total variance in data. These factors included: socio-ecological-built characteristics (21.8%), demographic pressure (13.32%), weather variability and climate hazards (11.41%), sponge city characteristics (8.42%), demographic sensitivity (6.86%), and landscape characteristics (6.09%). It was found that 542,377 (7%) of the total rural population in Shanghai was living in subdistricts with high CVI, including 62,891 children (8%) and 58,441 elders (8%). Based on the results of this study it is suggested that planners prioritize robust transportation networks during times of emergency, robust weather and storm monitoring systems, policies that aim to preserve agricultural land and promote ecological agriculture practices and provide additional resources for more vulnerable populations such as the elderly, children, and women to mitigate climate change vulnerability. This research study provides a scientific basis for local planners and policy makers to formulate risk management policies to mitigate the negative impacts of climate change and provides crucial implications for rural planning. [ABSTRACT FROM AUTHOR]

Over the past decade, healthcare systems have started to establish control centres to manage patient flow, with a view to removing delays and increasing the quality of care. Such centres—here dubbed Healthcare Capacity Command/Coordination Centres (HCCCs)—are a challenge to design and operate. Broad-ranging surveys of HCCCs have been lacking, and design for their human users is only starting to be addressed. In this review we identified 73 papers describing different kinds of HCCCs, classifying them according to whether they describe virtual or physical control centres, the kinds of situations they handle, and the different levels of Rasmussen's [1] risk management framework that they integrate. Most of the papers (71%) describe physical HCCCs established as control centres, whereas 29% of the papers describe virtual HCCCs staffed by stakeholders in separate locations. Principal functions of the HCCCs described are categorised as business as usual (BAU) (48%), surge management (15%), emergency response (18%), and mass casualty management (19%). The organisation layers that the HCCCs incorporate are classified according to the risk management framework; HCCCs managing BAU involve lower levels of the framework, whereas HCCCs handling the more emergent functions involve all levels. Major challenges confronting HCCCs include the dissemination of information about healthcare system status, and the management of perspectives and goals from different parts of the healthcare system. HCCCs that take the form of physical control centres are just starting to be analysed using human factors principles that will make staff more effective and productive at managing patient flow. [ABSTRACT FROM AUTHOR]

Purpose: Obesity's prevalence is rising in women of reproductive age worldwide and has become the most common medical condition at this age group. Besides, its occurrence is also rising during pregnancy. This condition not only increases the risk of noncommunicable diseases on the mother, such as cardiovascular disease and diabetes, but also transfers this risk to the offspring. Methods: This is a narrative review based on scientific and review articles on the matter. Results: Obesity is associated with an increased risk of gestational diabetes mellitus, gestational hypertension and preeclampsia, venous thromboembolism, infection, and mental health problems. Furthermore, it has an impact on the progress of labor and induction matters. Regarding offspring outcomes, it is related to higher incidence of congenital anomalies, perinatal mortality, and the occurrence of large for gestational age newborns. Still, it has implications on cardiometabolic risk and neurodevelopment in offspring. Conclusion: It is, therefore, imperative to encourage the adoption of healthy lifestyles, especially in the peri-conception and interpregnancy periods. Likewise, there must be support in the multidisciplinary monitoring of these pregnant women to minimize associated complication rates. [ABSTRACT FROM AUTHOR]

Overnight radiology (ONR) is necessary for providing timely patient care but poses unique professional and personal challenges to the radiologists. Maintaining a sustainable, long-term overnight radiology program hinges on the retention of radiologists who grasp the institutional workflow and can adeptly navigate inherent disruptions while consistently delivering high-quality patient care. Design of radiology shifts can significantly impact the performance and well-being of radiologists, with downstream implications for patient care and risk management. We provide a narrative review of literature to make recommendations for optimally designing ONR shifts, with a focus on professional and personal challenges pertinent to overnight radiologists and system-based risk mitigation strategies. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive and integrated framework of global supply network risk structures based on agency theory, which contributes to the literature on global supply chain risk management. The research was conducted using a combination of in-depth interviews with eight management executives from four apparel businesses and a large-scale survey involving 253 companies operating within the Vietnamese apparel supply chain, especially those that execute partial free-on-board (partial FOB) orders. The empirical evidence obtained from the research demonstrated that corporate performance is highly vulnerable to various types of supply chain risks, such as logistics, information, operational, supply, demand, and external risks. To enhance supply chain resilience during disruptive events such as the COVID-19 pandemic, the US-China trade war, and Ukraine-Russia conflicts, the study recommends the adoption of such strategies as diversified sourcing, supply chain collaboration and integration, and Industry 4.0 technology adoption. For global apparel firms that relocate their offshore manufacturing from China to Vietnam, it is important to identify these global supply chain risks and employ risk management strategies to ensure the efficient and effective functioning of the supply chain during disruptions. [ABSTRACT FROM AUTHOR]

Globalization may cause companies to broaden their customer bases, operate internationally, and serve more customers. However, it also entails dangers, including shifting circumstances, disruptions, and elevated prices. To address these issues, outsourcing has evolved, lowering outputs and service costs. To mitigate these risks, businesses employ strategies such as interventionism, protectionism, and regionalization. By investigating and simulating the interplay of outsourcing approaches to equip businesses with supply chain resilience (SCRES), this study aims to close the knowledge gap between the existing knowledge and global supply chain (GSC) risk management practices. To choose the best alternative for our case study company, we analyzed four distinct outsourcing techniques, namely offshoring, reshoring, nearshoring, and farshoring; furthermore, we investigated the outsourcing elements typically taken into account to achieve resilience. The results indicated that the reshoring method would be the most promising one for this company, under specific circumstances, in terms of attaining resilience in the manufacturing industry. [ABSTRACT FROM AUTHOR]

Vulnerability evaluation plays a key role in risk assessment and reduction and is essential for defining strategies for climate change adaptation and mitigation. In dealing with the safeguarding of cultural heritage at risk, we are still far from adopting and applying an agreed methodology for vulnerability assessment. With the aim to support practitioners, heritage managers, and policy and decision makers to undertake actions that address the protection of cultural heritage at risk, the methodology set up in the framework of the Interreg Central Europe STRENCH is illustrated and discussed here. Based on three major requirements (susceptibility, exposure, and resilience) and a continuous consultation with local stakeholders, the proposed methodology is applicable for evaluating the vulnerability of built heritage and cultural landscape exposed to hydrometeorological hazards, such as heavy rains, floods, and droughts. The results obtained through its validation on 15 case studies from seven Central European regions are shown to underline the strengths and limitations of the methodological approach. Iterative consultation with local stakeholders was fundamental for the definition of the criteria/subcriteria and related values for the assessment of the requirements. Application to further sites in other contexts would surely contribute to strengthening the reliability of the methodological approach. [ABSTRACT FROM AUTHOR]

Maritime authorities have the administrative responsibility for the safety and security of shipping and the prevention of marine and atmospheric pollution caused by ships. This responsibility involves various tasks that can be supported through effective risk management, but currently, there are no models available to evaluate its level of maturity in maritime administrations. To fill this gap and respond to the needs identified by maritime authorities, this article introduces a new risk maturity model called the R-Mare matrix. This model is built on recent scientific knowledge in the field of risk management, and it has been designed in close cooperation with end-users and maritime risk management experts using the Delphi methodology. As a result of this process, the article provides a qualitative risk maturity matrix specifically tailored to support the self-evaluation of maritime authorities. The matrix consists of 17 state-of-the-art risk management attributes, a five-step risk maturity scale, and associated risk maturity grid descriptions. These elements can be used to evaluate the current risk management performance of maritime authorities, identify areas for improvement, and develop a plan to achieve a higher level of maturity. Overall, the R-Mare matrix model represents an important step forward in this field while laying the foundation for further development. [ABSTRACT FROM AUTHOR]

The present paper aims to unveil the experience of rural women in a disaster cycle. The paper contains the ethnographic accounts of the women affected by cyclone 'Fani', which hit the coasts of Odisha on 3rd May 2019. The study concentrated on the village 'Kaliakera' of Puri, Odisha and spanned three months just after the cyclone. Adopting an exploratory design with an intersectionality approach, the study covered 60 women respondents drawn through stratified sampling from diverse caste groups. With an emic perspective and ethnographic tools, the accounts of these women have been captured. The study concluded that risk perception is low among women, reducing their disaster preparedness ability. Family members' concerns and decisions played a crucial role in the disaster preparedness of women. Low disaster preparedness makes risk management difficult for them during and after a disaster. Livelihood, health and food insecurities were the most common risk encountered by rural women. Past experience with disaster, caste dynamics, and socio-economic conditions affect women's effective handling of the disaster. Understanding rural women's experiences can help devise targeted interventions at the community level for a sustainable and resilient recovery in the post-disaster period. [ABSTRACT FROM AUTHOR]

Water security in arid and semi-arid Middle Eastern climates has been severely impacted by effects of climate change such as reduced precipitation, diminished storage, increased evapotranspiration, and prolonged heat waves. These climate effects are compounded in Iraq, where populations, agriculture, industry, and energy rely heavily on varying transboundary water flows to meet water demands. Iraq's most profitable sector, energy, is especially threatened by insufficient water supply, which complicates government decision making in energy infrastructure development. The goal of this paper is to develop a scenario-based multi-criteria analysis framework to prioritize infrastructure investments in the context of climate change and scarcity of natural resources. Infrastructure facilities are evaluated against social, economic, climate, and hydrologic criteria across a set of disruptive climatological, economic, and social scenarios to identify robust initiatives and the most and least disruptive scenarios to the system. A particular innovation of this paper is the evaluation of hydrology data derived from satellites in determining water scarcity impact on individual energy facilities. The methods are demonstrated for a critical sector of Iraq's economy: oil and natural gas. The demonstration includes 13 system-order criteria, 44 oil and gas initiatives within Iraq, and seven risk scenarios. The results include an accounting of the most and least disruptive scenarios to energy sector priorities and scenario-based system orderings to guide stakeholders in investment prioritization. [ABSTRACT FROM AUTHOR]

India, one of the most dynamic ancient civilizations, possesses a multitude of historical artifacts, with 37 of its notable architectural structures recognized as UNESCO World Heritage Sites. Yet, the ever-changing climate, especially air pollution, expedites the natural deterioration of historic sites and diminishes their aesthetic appeal, causing socio-economic damage. With this in mind, the current study aims to offer a logical scientific foundation for the implications of air pollution, seasonal shifts, and COVID-19 on 14 significant historical places in India during the year 2019-20. Delhi, among the cities most severely affected by atmospheric pollution, recorded an alarming air quality index (AQI) of 102–141, which can intensify the risk of cultural sites to corrode and deteriorate. Analysis reveals that the winter season had elevated levels of NO2 and particle pollution (PM2.5, PM10), whereas summer had the higher levels of O3. Throughout the 5-month lockdown period, ozone levels exhibited an elevation, contrasting with the reduction observed in other air parameters. Notably, there was a substantial 70% decrease in particulate matter concentration, which had previously remained stable over the course of the year. Variations in geographic locales and anthropogenic influences contribute significantly to the dose-response statistics, revealing an unprecedented elevation in corrosion risks to historical limestone and sandstone structures across target sites. Moreover, the research addresses available Governmental initiatives, and effective strategies designed to safeguard heritage sites against the corrosion and material degradation, offering a comprehensive exploration of protective measures. Thereby, the current research is centred on establishing a foundational understanding of the impact of air pollution on cultural heritage, utilizing a comparison to the year with the lowest air pollution levels, which can aid policymakers in enhancing risk management and implementing a robust national mandate for the preservation of cultural heritage sites against corrosion. [ABSTRACT FROM AUTHOR]

Tailings storage facilities (TSFs) impound mining waste behind dams to ensure public safety, but failure incidents have prompted calls for more robust monitoring programs. Satellite-based interferometric synthetic aperture radar (InSAR) has grown in popularity due to its ability to remotely detect millimeter-scale displacements in most urban and some natural terrains. However, there remains a limited understanding of whether InSAR can be as accurate or representative as on-the-ground instruments, whether failures can be predicted in advance using InSAR, and what variables govern the quality and reliability of InSAR results. To address these gaps, we analyze open-source, medium-resolution Sentinel-1 data to undertake a ground-truth assessment at a test site and a forensic analysis of five failure cases. We use a commercial software with an automated Persistent Scatterer (PS) workflow (SARScape Analytics) for all case study sites except one and a proprietary algorithm (SqueeSAR) with a dual PS and Distributed Scatterer (DS) algorithm for the ground-truth site and one forensic case. The main goal is to deliver practical insights regarding the influence of algorithm/satellite selection, environmental conditions, site activity, coherence thresholds, satellite-dam geometry, and failure modes. We conclude that Sentinel-1 InSAR can serve as a hazard-screening tool to help guide where to undertake targeted investigations; however, most potential failure modes may not exhibit InSAR-detectable accelerations that could assist with time-of-failure prediction in real time. As such, long-term monitoring programs should ideally be integrated with a combination of remote sensing and field instrumentation to best support engineering practice and judgment. [ABSTRACT FROM AUTHOR]

Drier conditions have been observed in Northern Patagonia, Argentina, in the last decades, affecting the pastoralism production system. In this context, two laws were promoted to foster goat and sheep production. This research investigated the hydro-climatic changes and the governmental initiatives, within these two laws, that follow them with special emphasis on climate hazard responses and their relationship with coping or adaptation strategies. A climatic shift was found as a tipping point in the climatic regime to drier conditions in 2006/7. This is observed in the annual mean streamflow of the Neuquén river which presented a 40% drop. Governmental funds were mostly oriented to tackle water-bonded problems given the lack of water and the remaining budget was mainly destined to infrastructure. This was done under the belief of drought events rather than a climatic shift. Distinguishing between them is a key factor for risk management stakeholders, since a drought must be mitigated with coping strategies, whereas a climate shift implies a long-lasting adaptation to a new reality. Even though they were not initially designed with consideration for climate change, some of these measures favor the adaptation process to this new drier scenario. Thus, many of the measures aimed to mitigate the structural vulnerabilities of the pastoral system in the region. This new scenario has triggered the need for a compulsory broad change in the socio-productive pastoral system, which might take more time than the assimilation of the negative impacts. [ABSTRACT FROM AUTHOR]

This study aims to test for detecting a change point in the conditional quantile of general location-scale time series models. This issue is quite important in risk management because the conditional quantile is utilized to measure the value-at-risk or expected shortfall of financial assets. In this paper, we design two types of cumulative sum tests based on the conditional quantiles. Their limiting null distributions are derived under regularity conditions, together with consistency of the proposed tests under the alternative. Monte Carlo simulations demonstrate the good performance of the proposed tests in terms of both stability and power for various time series settings. A real data analysis using the daily returns of the Brent Oil futures also confirms the validity of the tests in real-world applications. [ABSTRACT FROM AUTHOR]

This paper studies a framework of Reliable Capacitated Facility Location Problem with Single source constraint, which allows us to capture the mental account management problem for a bank under uncertain environment. In the problem, each facility, corresponding to a financial product, has limited capacity and may fail randomly, which represents that the product fails to reach the threshold level of return. Each customer, corresponding to a mental account, is served by a single primary facility or product, and its demands, or the setting goals, can be split on several backup facilities or alternative investments with redundant capacity. With the operation, a portion of the satisfaction can still be met by the backup facilities when the primary service of a customer fails. We formulate a mixed integer programming model for the problem and design a Lagrangian relaxation based solution algorithm, which sophisticatedly exploits the structure of the model and transfers the complicated relaxation problems into 0–1 knapsack problems to reduce the complexity. A local search procedure is also incorporated into the algorithm to enhance the accuracy of small- and large-scale computation. Finally, a real-life case of mental accounting is investigated to illustrate the application of the decision model. [ABSTRACT FROM AUTHOR]

Background: Interprofessional training wards (ITW) are increasingly being integrated into teaching and training concepts in visceral surgery clinics. Objective: How safe is patient care on an ITW in visceral surgery? Material and methods: Data collection took place from November 2021 to December 2022. In this nonrandomized prospective evaluation study the frequency and severity of adverse events (AE) in 3 groups of 100 patients each in a tertiary referral center hospital for visceral surgery were investigated. The groups consisted of patients on the ITW and on the conventional ward before and after implementation of the ITW. The Global Trigger Tool (GTT) was used to search for AE. Simultaneously, a survey of the treatment was conducted according to the Picker method to measure patient reported outcome. Results: Baseline characteristics and clinical outcome parameters of the patients in the three groups were comparable. The GTT analysis found 74 nonpreventable and 5 preventable AE in 63 (21%) of the patients and 12 AE occurred before the hospital stay. During the hospital stay 50 AE occurred in the operating theater and 17 on the conventional ward. None of the five preventable AE (in 1.7% of the patients) was caused by the treatment on the ITW. Patients rated the safety on the ITW better than in 90% of the hospitals included in the Picker benchmark cohort and as good as on the normal ward. Conclusion: The GTT-based data as well as from the patients' point of view show that patient care on a carefully implemented ITW in visceral surgery is safe. [ABSTRACT FROM AUTHOR]

Workforce shortages during the COVID-19 pandemic and the recent threat of railroad strike in the United States have generated greater public awareness of how freight flow disruptions can harm society. Unlike highways, trains often do not have the ability to take alternative routes that directly connect major metropolitan areas; hence railroad networks are vulnerable to disruptions like accidents. This study developed a data mining workflow to rank commodity movements that are at the highest risk of disruption from railroad accidents and other types of regional disasters that can affect railroad operations. A key finding is that five U.S. metropolitan areas are at least five times more likely than others to experience a railroad accident. Those five areas account for more than 40% of the monetary value in alcoholic beverages, raw meats, gasoline, plastic-based products, and rubber-based products moved by rail. Hence, any disruption in those five areas can lead to widespread shortages of those commodities. The implication is that decision makers should focus risk mitigation and resiliency strategies in those five metropolitan areas and on the top commodity categories at risk. [ABSTRACT FROM AUTHOR]

A risk analyst assesses potential financial losses based on multiple sources of information. Often, the assessment does not only depend on the specification of the loss random variable, but also on various economic scenarios. Motivated by this observation, we design a unified axiomatic framework for risk evaluation principles which quantify jointly a loss random variable and a set of plausible probabilities. We call such an evaluation principle a generalised risk measure. We present a series of relevant theoretical results. The worst-case, coherent and robust generalised risk measures are characterised via different sets of intuitive axioms. We establish the equivalence between a few natural forms of law-invariance in our framework, and the technical subtlety therein reveals a sharp contrast between our framework and the traditional one. Moreover, coherence and strong law-invariance are derived from a combination of other conditions, which provides additional support for coherent risk measures such as expected shortfall over value-at-risk, a relevant issue for risk management practice. [ABSTRACT FROM AUTHOR]

Our article offers insights on the role of operational research (OR) in understanding financial and economic systems' risks and dynamics. It presents the latest methods in OR to address risks and uncertainties in these systems, covering topics such as options pricing, portfolio optimization, banking resilience, and the analysis of financial and economic co-movements. The included studies utilize advanced analytical tools, like stochastic programming, decision analysis, and machine learning, to create robust models for complex systems. These contributions aim to be valuable for academics, practitioners, policymakers, and regulators in the field. [ABSTRACT FROM AUTHOR]

The inopportune organization of spice supply chains (SSCs) results in aided risks, resource wastages, and sustainability issues. Nevertheless, practitioners and academicians alike must investigate spice supply chain management (SSCM) in terms of long-term sustainability. This study draws on the available literature to compile a collection of characteristics and maintain sustainable spice supply chain management techniques which come up with associated risks and relevant obstacles. Existing studies claim that due to a lack of resources, the associated risks are the root of poor SSCM performance. As a result, the goal of this study is to identify the primary risk variables using qualitative data; nevertheless, the attributes must be converted into a scale that is comparable. The fuzzy Delphi method (FDM) was used to obtain valid and reliable attributes from qualitative data, while the fuzzy decision-making trial and evaluation laboratory (FDEMATEL) was used to address uncertainty and interrelationships simultaneously. FDM results suggest that there are eighteen critical risk variables and seven risks threatening effective SSCM. FDEMATEL results reveal qualitative data translated into crisp, comparable values in order to investigate causal linkages between variables and confirm the compatibility of the theoretical structure with industry realities. The findings show fluctuation in the Price (C8), diseases and pests (C20), human contamination (C23), spice adulteration (C24), and loss of food quality, and quantity (C36) are all important risks and sub-risks in these causative interrelationships. The primary risks involved in enhancing SCM include Financial Risk (A5), Ergonomic Risk (A8), and Operation and Management Risk (A10). The study recommends that industry professionals use future marketing tools to protect themselves from price changes which allow them to assess supply and demand circumstances and manage price risks over distance and time. Spices are the key contributors to earning a sizable amount of foreign currency through export in a developing country. It suggests to policymakers, regulatory organizations, and practitioners to develop regulations, raise farmer understanding about pest control, impose stiff penalties on vendors and businesses proven to be involved in spice adulteration, and develop a sustainable fertilizer distribution system. These corresponding action plans for improving the SSC sector and comparing it with agro-food and short-supply chains are investigated. This study contributes to theory by utilizing FDM and FDEMATEL methods for addressing the uncertainty and interrelationship among associated risks that hinder SCM from attaining sustainability. [ABSTRACT FROM AUTHOR]

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Risk managers as corporate stewards are important gatekeepers in enterprises and they are essential to managing risks. Relatedly, a more accurate evaluation of the risk factors allows a well-founded decision-making process and reduces the number of surprising situations that could occur especially in volatile markets. Forward-looking risk management increases entrepreneurial resilience because risk factors are already estimated at an earlier stage in the corresponding risk analysis. Furthermore, the range of potential solutions can be estimated in a successive way. These aspects are relevant especially for products with follow-up effects. Such new product bundles are typical in current businesses. They require a more precise risk analysis, which allows an effective view of the life-cycles of the whole products and the customer relationships. Within well-founded risk decomposition, the existing risk can be managed appropriately. The following study presents a special life-cycle approach for evaluating products and customers in risky situations. Especially for important management decisions, such an approach is necessary, given that only a few products or customers can have a major influence on the success of the enterprise. Therefore, a systematic risk-oriented approach is essential that adequately identifies, assesses and controls the risk factors and enables agile adaptability for fast changes. Considering the risk management perspective, simulation techniques are a useful approach to solve sophisticated decision situations. The applicability of this concept is demonstrated using a computation example reflecting real-world circumstances. The presented approach is broadly defined. That is the reason why the approach can also be transferred to other sectors. [ABSTRACT FROM AUTHOR]

The integration of risk into management control has recently received increased attention in the management accounting and control literature. Much of this research has focused on the organizational and individual actor level. However, some studies suggest that the integration of risk into the organizational control package may equally be influenced by forces operating at other levels of analysis– including the economic and political level and the organizational field level. In this guest editorial for the special issue on "Courageous Risk Governance: Enabling Resilience, Autonomy, and New Thinking," I therefore discuss how our collective understanding of the integration of risk into management control could be enhanced by research at multiple levels of analysis. The papers included in this special issue show that when this integration is successfully managed, organizations can achieve valuable outcomes, such as increased resilience. For both practitioners and academics, future research on such integration therefore seems fruitful and necessary. This article provides ideas for particularly relevant questions about this integration and for theories that can guide such research. [ABSTRACT FROM AUTHOR]

Global economic crises can have a significant impact on businesses across different sectors, often leading to difficulties or even insolvency. In such a situation, organizational resilience is often considered a means to ensure the competitive advantage. Although the concept has gained popularity in recent years, empirical research on the determinants and effects of organizational resilience remains scarce. Therefore, we first examine the potential management accounting determinants of organizational resilience. Second, we investigate the effect of organizational resilience on competitive advantage. A cross-sectional survey conducted in January and February 2021 resulted in 127 observations of medium- and large-sized German companies. We find that a risk management orientation and the importance of the planning function of budgeting are positively associated with both the adaptive capability factor and the planning factor of organizational resilience. Furthermore, we find that adaptive capability increases a company's competitive advantage in both business-as-usual situations and in times of crisis. Our findings inform practitioners about how key management accounting concepts, such as risk management and corporate planning, can increase organizational resilience and, consequently, the positive outcomes of organizational resilience. [ABSTRACT FROM AUTHOR]

Performance management and risk management in the public sector have undergone significant improvements; however, few empirical studies have conceptualised the integration of performance management and risk management. This study aimed to understand why it fails in practice and turns into disintegration. To do this, we analyse the role of different actors involved in the integration between performance management and risk management. We have conducted our analysis at the organisational level in a regional context, adopting two different research methods, documentary analysis and collections of interviews. This paper contributes to the theoretical debate with interesting new insights about organisational practices in the public sector. In this research, we adopted the disintegration framework, broadly used as a research methodology in the ontological and social paradigm as reported (Täubig in Totale Institution Asyl, Juventa Verlag, Munich, 2009) for analysing the integration and disintegration between performance management and risk management. This approach presumes the collective engagement of researchers and practitioners, which can help bring to the surface the knowledge embedded in practice and transform it into actionable knowledge to produce practice changes. This study contributes to the public accounting literature by providing empirical evidence about organisational practices in the public sector. It offers a practical and general understanding of performance management and risk management practices functioning in public government. It shows the fundamental role played by key actors when performance management and risk management practices are implemented. This empirical research also has practical implications, creating the basis for the implementation of an integrated system of performance management and risk management in regional governments. [ABSTRACT FROM AUTHOR]

In this study, liquid chromatography with tandem mass spectroscopy was applied to detect Tetrodotoxin and analogues (TTXs) on pufferfish (Sphoeroides marmoratus) tissues, accidentally found in the stomach of a cuttlefish (Sepia officinalis). The cuttlefish tissues were also analysed. Pufferfish (digestive tract, skin, gonads, liver/spleen, muscle) and cuttlefish (mantle, head/visceral mass) tissues were tested positive for TTXs. In pufferfish, the highest concentration of TTX was found in the digestive tract (4.94 mg/ kg), while in cuttlefish in the mantle (0.21 mg/kg). The presence of TTXs in S. marmoratus was linked to its geographical area of origin while a TTXs cross-contamination of the cuttlefish was hypothesized. Despite the European ban on pufferfish commercialization, campaigns addressed to their morphological identification by consumers and operators might improve its risk management. The risk related to TTXs cross-contamination of edible seafood such as cuttlefish might require specific control measures. Moreover, the collaboration between competent authorities and medical personnel are essential for the monitoring of human poisoning. [ABSTRACT FROM AUTHOR]

Although adverse events related to extracorporeal membrane oxygenation have been reported, epidemiological data on life-threatening events are insufficient to study the causes of such adverse events. Data from the Japan Council for Quality Health Care database were retrospectively analyzed. The adverse events extracted from this national database included events associated with extracorporeal membrane oxygenation reported between January 2010 and December 2021. We identified 178 adverse events related to extracorporeal membrane oxygenation. At least 41 (23%) and 47 (26%) accidents resulted in death and residual disability, respectively. The most common adverse events were cannula malposition (28%), decannulation (19%), and bleeding (15%). Among patients with cannula malposition, 38% did not undergo fluoroscopy-guided or ultrasound-guided cannulation, 54% required surgical treatment, and 18% required trans-arterial embolization. In this epidemiological study in Japan, 23% of the adverse events related to extracorporeal membrane oxygenation had fatal outcomes. Our findings suggest that a training system for cannulation techniques may be needed, and hospitals offering extracorporeal membrane oxygenation should perform emergency surgeries. [ABSTRACT FROM AUTHOR]

Addressing recent calls by European regulatory and supervisory authorities, we develop a new bottom-up climate risk assessment method to examine the resilience of the European banking industry regarding transitory climate risks. We illustrate our approach by estimating the impact of a 50–100 EUR carbon tax per tCO 2 equivalent on the valuation and default risk of STOXX Europe 600 firms. For about 5% of the sample firms, we find asset devaluation shocks larger than 30% and for about 16% of the firms probabilities of default (PDs) dropping below investment-grade level of 3%. At the sector level, our results yield asset devaluations shocks of 15–36% and new PDs of 5–34% for the six most affected sectors. Running a stress test on credit risk based on these results, we find a decrease in capital ratios between - 1.2 and - 1.6 percentage points for key regulatory capital ratios in the most adverse scenario while only addressing 36% of the bank's total risk-weighted assets. Our analysis sheds light on the substantial transitory climate risk for asset portfolios of banks and contributes to the pressing question how to integrate climate risk into risk management and regulation of financial institutions. [ABSTRACT FROM AUTHOR]

The Information Security Management Systems (ISMS) are global and risk-driven processes that allow companies to develop their cybersecurity strategy by defining security policies, valuable assets, controls, and technologies for protecting their systems and information from threats and vulnerabilities. Despite the implementation of such management infrastructures, incidents or security breaches happen. Each incident has associated a level of severity and a set of mitigation controls, so in order to restore the ISMS, the appropriate set of controls to mitigate their damage must be selected. The time in which the ISMS is restored is a critical aspect. In this sense, classic solutions are efficient in resolving scenarios with a moderate number of incidents in a reasonable time, but the response time increases exponentially as the number of incidents increases. This makes classical solutions unsuitable for real scenarios in which a large number of incidents are handled and even less appropriate for scenarios in which security management is offered as a service to several companies. This paper proposes a solution to the incident response problem that acts in a minimal amount of time for real scenarios in which a large number of incidents are handled. It applies quantum computing, as a novel approach that is being successfully applied to real problems, which allows us to obtain solutions in a constant time regardless of the number of incidents handled. To validate the applicability and efficiency of our proposal, it has been applied to real cases using our framework (MARISMA). [ABSTRACT FROM AUTHOR]