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Gasifying waste represents a sustainable and highly effective approach; however, ensuring rigorous control of hydrogen leakage is paramount to guarantee both safety and long-term sustainability. Due to the distinctive features of these production facilities and the likelihood of their placement in public municipal spaces, it is imperative to prioritize a comprehensive approach to ensuring the safety of these installations. This includes a thorough evaluation of the risks linked to hydrogen and taking proactive measures to prevent accidents, a crucial aspect that has been neglected in prior research endeavors. Therefore, this article introduces an enhanced iteration of the risk management framework based on the failure mode and effects analysis (FMEA) and the evaluation based on distance from average solution (EDAS) methods, implemented in a municipal solid waste gasification system to facilitate hydrogen production. The research employs FMEA to scrutinize potential failure modes, strategically prioritizing them through advancements in the EDAS methodology. Notably, this framework is seamlessly integrated during the conceptual design phase, showcasing its efficacy in bolstering risk-informed design strategies. Through rigorous comparative and sensitivity analyses, the resilience of the framework is underscored. The refined FMEA-EDAS framework holds substantial practical implications for managing hydrogen production facilities by providing a structured approach to resource allocation and ensuring adherence to industry standards. Furthermore, it fosters interdisciplinary collaboration, potentially serving as a knowledge hub to fortify safety measures within the realm of hydrogen production. • We propose a new FMEA-EDAS MCDM for waste-to-hydrogen gasification. • We analyze a real case study with 20 failure modes, revealing root causes. • We validate our framework via comparative and sensitivity analysis. • We provide a comprehensive safety planning solution for the case study. • The proposed mode contributes to global energy transition with cleaner solutions. [ABSTRACT FROM AUTHOR]

Particularities in psychiatry care can increase the risk of medication errors (MEs). To analyze the MEs that occurred in a psychiatric hospital and to quantify relationships between the use of certain types of medication and the type of MEs. We conducted a retrospective register based cross-sectional study in a French psychiatric hospital (2014–2021). All MEs were analyzed using ALARM method to identify type, stage of occurring and interception (defenses), consequences, drug involved and root causes. The prevalence-odds ratio (POR) was calculated to estimate relationships between five selected medication situations (long-acting injectable antipsychotics (LAIA), oral liquid dosage forms in a multiple-unit-container (OLDS-MC), psychotropic drugs (PD), controlled medicines (CM) or high-alert drugs) and the type of MEs occurred. Among the 609 MEs reported, wrong dose (32.2%), wrong drug (30.3%), omission (14.2%) and wrong patient (12.9%) were frequently observed. The ME occurrence stage were prescribing (55.3%) and administration (30.2%). Medication order review intercepted 77.9% of MEs. CM or LAIA increased the risk of medication omission (POR: 3.9, 95%CI: 1.8–8.4 and 2.5, 95%CI; 1.2–5.1, respectively) while the use of high-alert medications decreased it (0.2, 95%CI: 0.1–0.8). OLDS-MC and PD were more likely to be administered to the wrong patient (6.1, 95%CI: 3.3–11.4 and 16.1, 95%CI: 7.2–35.8). LAIA were associated with an increased risk of wrong dose (3.4, 95%CI: 1.8–6.3). Actual errors risk was lower with high-alert drugs (0.5, 95%CI: 0.3–09), but higher with CM (3.5, 95%CI: 1.5–8.0), OLDS-MC (2.1, 95%CI: 1.2–3.8) and PD (2.5, 95%CI: 1.8–3.5). Patients exposed to high-alert drugs were likely to have a serious error (3.5, 95%CI: 1.2–10.4). This study sheds an innovative approach to analyze MEs by demonstrating that certain medication situations were more likely to lead to certain types of error. This enables the most appropriate prevention barriers to be put in place to intercept ME. • In psychiatry, certain medication situations were associated with certain errors. • Long-acting injectable antipsychotics are associated with a higher risk of wrong dose. • Liquid medicines in psychiatry are associated with a higher risk of wrong patient. • Restrictive regulation induced a higher risk of omission with controlled medicines. [ABSTRACT FROM AUTHOR]

To identify trigger tools applied to detect adverse drug events (ADEs) in older people and describe their utility and performance. A systematic review was conducted in the PubMed, Lilacs, and Scopus databases (January 2024). Studies that developed, applied, or validated trigger tools and evaluated their utility and/or performance for detecting ADEs in older people were considered. Direct proportion meta-analyses using the inverse-variance method were performed for prevalence of ADEs and positive predictive value (PPV). Twenty-four studies (25 publications) were included. Twelve trigger tools were identified, of which six were developed for detecting ADEs in older population, four developed for general population and modified for older people, and two developed for general population. No tools for detecting ADEs in older people receiving palliative care or hospitalized in intensive or surgical care units were found. The performance of triggers was presented through PPV (11.5–71%), negative predictive values (83.3%), and sensitivity (30–94.8%). The overall PPV was 33.3% (95%CI: 32.5–34.2%). Triggers with good performance were changes in plasma levels of digoxin, glucose, and potassium; changes in international normalized ratio; abrupt medication stop; hypotension; and constipation. The prevalence of ADEs ranged from 2.8 to 66%, with overall prevalence of ADEs of 20% (95%CI: 19.3–20.8%). Preventability ranged from 8.4 to 94.4%. Metabolic or electrolyte disturbances induced by diuretics, constipation induced by opioids, and falls and delirium induced by benzodiazepines were the most prevalent ADEs. The trigger tools are flexible and easy to apply, and they can contribute to the detection of ADEs, their associated risk factors, the level of harm, and preventability in different health settings. However, there is no consensus on good or poor values of PPV, which indicate the performance of triggers. Furthermore, there is limited evidence regarding the evaluation of performance through negative predictive value, sensitivity, and specificity. CRD42022379893. [ABSTRACT FROM AUTHOR]

The area of data science knowledge responsible for dealing with this new reality is diffuse, including mathematics, statistics, computing, engineering, psychology, and administration, among many other areas that make up a new scenario that is still changing. Different models have emerged over the years to systematize the procedures to be followed. Among them, CRISP-DM (Cross Industry Standard Process for Data Mining) has become one of the most widespread in the industry. However, the lack of detailed instructions means the framework is often incorrectly used. Therefore, this research aims to present a utilitarian and didactic model based on the latest advances in the literature and through the lens of production engineering. In order to achieve this objective, exploratory research was carried out based on a systematic review and subsequent categorization of each of the CRISP-DM steps, detailing the authors' contributions to each stage. In addition, it is proposed that guidelines from the areas of Quality Management and Risk Management be added to the subject, consolidating a useful and didactic model of relevance. [ABSTRACT FROM AUTHOR]

Critical infrastructures (CIs) play an important role in urban economic development and the maintenance of social stability. In recent years, with the increase in natural and man-made risk events affecting CI operations, CI risk management is facing severe challenges and gradually transitioning to CI resilience management. However, the connotation of "resilience - risk" for CIs is still not clearly conceptualized. To address this problem, an exploratory theoretical framework is constructed, including three stages of system resilience identification, resilience impact analysis and connotation element extraction. Subsequently, based on the constructed framework, probability, consequence, and resilience-based scenario that align with the resilience characteristics and impact analysis results are extracted as connotation elements to define a triplet spatial-temporal evolution function of "resilience - risk". This study can provide a theoretical reference for better understanding the relationship between CI resilience and CI risk. [ABSTRACT FROM AUTHOR]

The digital economy has brought about a rapid expansion of cross-border activities, making risk management and control in the areas of data security and cross-border business more important. In this study, we apply a bibliometric approach to systematically organize the research progress on cross-border risks both domestically and internationally. Overall, by visualizing and analyzing 296 Chinese and 315 English papers collected, we observe an increasing scholarly interest in cross-border risk issues as evidenced by the growth trends of literature publication data. We then examine the network of cooperative relationships between various countries/regions, and identify five clusters of literature in Chinese and English research respectively, through visualization technologies in bibliometrics. These clusters clearly exhibit the current status of research on cross-border risks around the world in recent years. Furthermore, we aggregate a collection of risk factors from various types of cross-border activities, thereby delivering insights for the construction of industrial ecosystems and policy makings by governments. [ABSTRACT FROM AUTHOR]

Energy sources and the overall energy system are currently experiencing significant instability. The combination of high demand and reduced supply results in the emergence of new sources of risk throughout the entire value chain. To the best of the authors' knowledge, there is a limited literature focusing on risk management in energy projects, particularly in the context of photovoltaic energy projects. Consequently, a risk management methodology tailored to the specific requirements of a photovoltaic energy project was developed and implemented. This project entails the installation of a photovoltaic plant in the North of Portugal, with the goal of utilizing solar energy to generate 547,500.45 KWh of clean energy per year. Although the company responsible for the project already adhered to certain risk management guidelines, no formalized process has been previously implemented. An action-research approach was employed. Concurrently with the project's development phase, a Risk Management Plan was created, and all the supporting documents were integrated, including a Risk Register, a guide for progress meetings, and a record of lessons learned. The findings revealed that risk monitoring and control enabled better control of the project execution processes, adherence to various project schedules, effective risk management by maximizing positive impacts and minimizing negative ones, the facilitation of agile decision-making, and the recording of lessons learned regarding the risk management process. Additionally, an unexpected outcome emerged from the research - the importance of communication among teams involved in risk management. This research has made significant contributions towards improving the management of photovoltaic energy projects by developing processes, methods, and templates specifically tailored to these unique projects. These findings can be utilized in future projects with similar characteristics, enabling more efficient and effective risk management. [ABSTRACT FROM AUTHOR]

In this paper the risks that affect highway construction projects duration are studied by qualitative and quantitative approaches. For the qualitative analysis the consistency of expert opinions was evaluated, and two methods were applied to identify critical risks that affect local projects. The quantitative analysis studied the impact of those risks over the activities of a local project and also the relationship between risks using fuzzy logic and Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

Biomarkers are essential for clinical risk management in anorexia nervosa (AN). Biomarkers can inform decisions regarding AN treatment at specific steps during the therapeutic cycle. Biomarker research will help to define subgroups of people with AN and guide decisions on individually tailored therapies, including psychotherapy. Anti-hypothalamus autoantibodies, cytokines, and metabolically relevant hormones such as insulin and leptin may be novel future drug targets for the treatment of AN. Pharmacogenetic testing and therapeutic drug monitoring are available for research and clinical application in AN, but they are usually not utilized in clinical practice. In anorexia nervosa (AN), measurable biological parameters can inform the process of treating patients. Such biomarkers include established laboratory parameters as well as a range of potential future biomarkers, including genetic, metabolomic, microbiomic, endocrine, immunological, hematological, electrophysiological, and neuroimaging parameters. In this opinion article we discuss how these biomarkers can support diagnosic and therapeutic processes at specific steps during the AN treatment cycle, that is, the diagnosis, diagnostic specification, risk management, choice of therapy, therapy monitoring, and treatment review. History-taking, physical and neuropsychological examination, clinical observation, and judgment about treatment success by the patient, their carers, and members of the multidisciplinary team are essential to interpret laboratory and imaging data appropriately and to assess the full clinical picture. [ABSTRACT FROM AUTHOR]

The Tokyo 2020 Olympic and Paralympic Games was one of the largest international mass-gathering events held after the beginning of coronavirus disease 2019 (COVID-19) pandemic. In this scoping review, we extracted papers discussing COVID-19 risk assessment or management at the Tokyo 2020 Games to determine the nature of studies that were conducted. Among the 75 papers obtained from two search engines (PubMed and ScienceDirect) and four papers collected from hand-searches, 30 papers were extracted. Only eight papers performed both COVID-19 prior risk assessment and quantitative evaluation of effectiveness measures, highlighting the importance of rapid, solution-focused risk assessment. Furthermore, this review revealed that the findings regarding the spread of COVID-19 infection to citizens in the host country were inconsistent depending on the assessment methods and that assessments of the spread of infection outside the host country were lacking. [ABSTRACT FROM AUTHOR]

The high costs of environmentally responsible and socially just approaches are some of the factors that hinder the implementation of sustainable projects in the industrial sector. However, upstream collaborative integration in the corrugated cardboard industry in southeastern Brazil is a reality. In this context, this study aimed to highlight the structure of a collaborative sustainable project in the context of the corrugated cardboard industry, to analyze ESG risk management in the corrugated cardboard industry in the Southeast Region of Brazil, the relationship between ESG risk management and social responsibility in corrugated cardboard industries, the strengths and weaknesses of risk management models in use by the consulted participants, and to propose innovations regarding risk analysis, applicable in sustainable projects with a collaborative bias. The methodology adopted was the case study, with consultation with managers in professional activity in the industrial sector, corroborated by document analysis and systematic review of the literature. We identified preliminary risk analysis (PRA) and failure mode analysis (FMEA) as key practices used by managers in the corrugated paper industry in the region. These practices are insufficient in the convergence of objectives, engagement with the community, and extension of the lifecycle of products and processes. Our findings show that the sustainability of a project may be an extension of the risk analyses carried out in the initial phase, mainly about strategic decision-making and the operationalization of investments. Without bias to the need for risk analysis, the life cycle analysis is also an effective way of highlighting the critical factors, weaknesses, and strengths of a sustainable project. The study indicates the so-called GUT matrix approach (gravity – urgency – tendency) as the most suitable for innovation in risk analyses oriented towards sustainable projects in the analyzed sector. [ABSTRACT FROM AUTHOR]

This study assesses the time-varying connectedness and portfolio implications among equity markets, commodities, and cryptocurrencies. To this end, we employ the DCC-GARCH model and time-frequency framework on daily data. The sample covers a period spanning from January 2018 to October 2023. The results confirm the existence of financial contagion evidence during the pandemic outbreak and the Russian invasion of Ukraine among the equity markets and alternative assets. Furthermore, from the perspective of portfolio management, we find that gold can be a suitable asset for diversifying specific risks, followed by soft commodities and Bitcoin during tranquil periods. We demonstrate that gold serves as a good long-term safe investment, whereas gold and Bitcoin lose their safe-haven properties in the short and mid term. Conversely, oil is the least effective diversification and safe-haven asset for equities. However, the hedging analysis indicates an increase in the hedge ratio during crisis periods across all pairs. The hedging performance of each asset is modest and varies due to critical market circumstances during the pandemic and the war. These findings suggest that investors should frequently rebalance the portfolio structure rather than adopting a static method such as buy and hold. [ABSTRACT FROM AUTHOR]

En France, en moyenne 40 % des personnes condamnées sont en état de récidive ou de réitération. Afin d'éviter les ruptures de soins susceptibles de conduire à la commission d'une nouvelle infraction, le service médicopsychologique régional de la maison d'arrêt a d'abord développé, en 2021, l'accompagnement post-carcéral de courte durée (six mois). L'équipe pluridisciplinaire ambitionne désormais de favoriser l'entrée dans un processus de désistance des hommes suivis en prison, et accompagnés à la sortie. La stratégie arrêtée pour tenter de répondre à cette nouvelle mission comprend trois volets : formation, organisation, et développement de l'offre de soin. L'équipe a commencé à se former à trois outils : HCR20 V3, SAPROF et CAPP. Le premier intéresse l'évaluation et la gestion du risque de récidive violente interpersonnelle, le second le repérage des facteurs de protection liés à la violence, et le dernier concerne le trouble de personnalité psychopathique, facteur prépondérant de risque de violence. Sur le plan de l'organisation, les soins au SMPR ont été repensés pour intégrer l'évaluation du niveau de risque de récidive en détention, et sa réévaluation en cours d'APC. Le but est maintenant d'agir stratégiquement sur d'éventuels facteurs de risque dynamiques repérés, en tenant compte des facteurs de protection. Le développement de l'offre de soin, entrepris en 2022, a abouti en octobre 2023 à l'ouverture d'une unité de colocation thérapeutique et d'insertion (UCTI), dispositif « passerelle » pouvant accueillir cinq hommes sortants, accompagnés en post-carcéral par le SMPR, pour six mois également. L'objectif principal de cette étude observationnelle, prospective et monocentrique, est de mesurer l'efficacité du suivi intra-carcéral et de l'accompagnement post-carcéral – restructurés autour d'outils d'évaluation et de gestion du risque de récidive – des personnes sortantes de MA d'Amiens, sur la désistance à l'issue de l'APC et à cinq ans. Cette efficacité pourrait se traduire, pour les personnes accompagnées en post-carcéral, par une diminution de l'expression des traits psychopathiques et du niveau de risque de récidive entre le moment de l'incarcération et la fin de la prise en soin. Les professionnels souhaitent également documenter la mise en place des trois outils dans leur service, et en étudier la validité prédictive sur leur échantillon. L'étude sert aussi à évaluer l'efficacité du dispositif expérimental UCTI. Le repérage précoce des facteurs de risque devrait permettre d'améliorer la spécificité et la priorisation des actions de prévention du risque entrant dans le cadre des soins courants. Démonstration faite de l'efficacité de ces soins, enrichis par l'emploi d'outils adaptés à la problématique de la population carcérale sortante, il serait envisageable de répliquer cette stratégie de spécialisation psychiatrique pénitentiaire dans les équipes psychiatriques exerçant dans d'autres établissements pénitentiaires. Le projet s'inscrit dans une volonté de décloisonnement des différents secteurs concernés par la prise en charge des personnes sortantes. Le travail collaboratif en équipe pluridisciplinaire, au sein du service mais aussi avec les dispositifs de droit commun, est au cœur des retombées de cette recherche. Serait-il possible de revitaliser l'engagement individuel et collectif de ceux qui agissent auprès de patients qui peuvent présenter un risque de violence ? In France, an average of 40% of convicted prisoners are repeat offenders. To prevent disruptions in care that may lead to new offenses, the regional medico-psychological department (SMPR) of the Amiens prison first introduced short-term post-incarceration support (6 months) in 2021. The multidisciplinary team now intends to facilitate the transition to a desistance process for incarcerated men who are undergoing treatment in prison and to, provide support when they are released. The strategy consists of three main components: training, organization, and expanding the range of care. The team has already started training for three tools: HCR20 V3, SAPROF, and CAPP-IRS. The first pertains to the assessment and management of the risk of interpersonal violent relapse, the second focuses on identifying protective factors related to violence, and the third addresses psychopathy, a significant risk factor for violence. In terms of organization, care at the SMPR has been restructured to incorporate the assessment of the level of risk of relapse during detention and its reassessment during post-carceral follow-up. The aim now is to strategically address any identified dynamic risk factors, taking protective factors into account. The expansion of the care provided, begun in 2022, led to the opening of a therapeutic and integration cohabitation unit (TICU) in October 2023, serving as a "gateway" facility accommodating 5 men who have been released from custody supported by the SMPR in post-carceral care, also for a duration of 6 months. The primary objective of this observational, prospective, and single-center study is to measure the effectiveness of intra-carceral and post-carceral support – restructured around risk assessment and management tools – for individuals exiting the Amiens prison after achieving desistance at the end of the follow-up and for a period of 5 years. This effectiveness could be reflected in a reduction in psychopathic traits and in the level of risk of recidivism for those supported in post-carceral care, from the time of incarceration to the end of care. These mental health care professionals also wish to document the implementation of the three tools in their service and assess their predictive validity within their sample. The study also serves to evaluate the effectiveness of the experimental TICU program. The early identification of risk factors should improve the specificity and prioritization of risk prevention actions as part of routine care. Demonstrating the effectiveness of this extended treatment program, tailored to the needs of the outgoing incarcerated population, could lead to the replication of this specialized psychiatric approach in other penal facilities. The project is part of a common effort to break down barriers between the various sectors involved in the care of individuals who are released from prison. Collaborative multidisciplinary teamwork, both within the department and with mainstream psychiatric care facilities, lies at the core of the results of this research. Could it be possible to revitalize the individual and collective commitment of those working with patients who may present a risk of violence? [ABSTRACT FROM AUTHOR]

An understanding of clinical governance and risk management is essential for a career in obstetrics and gynaecology. In a stressed and struggling system, knowing where and how to improve our maternity services is crucial in order to keep our patients safe. This article outlines the principles of clinical governance with a focus on risk management; it provides insight as to how this is managed and implemented within NHS trusts. We will look at how just culture and systems-based learning determine the effectiveness of both, and we will demonstrate how this is used by external governing bodies to judge the safety of maternity units. Only through robust clinical governance structures is the NHS able to ensure that it learns from mistakes and evolves to safeguard future patients and its workforce. Knowledge of the inner workings of these structures is important for examination preparation, any job interview, and for providing responsible and safe care to patients as a clinician. [ABSTRACT FROM AUTHOR]

Supply Chain Integration (SCI) has attracted increasing attention in Supply Chain Risk Management (SCRM) literature as it could be a very useful tool for risk mitigation. At the same time, companies in several sectors are experiencing a transition towards more circular and sustainable business models, which poses new challenges and risks for firms. Despite the relevance of integrative practices in supply chains to deal with risks and uncertainties, evidence about the role of SCI for dealing with risks of Circular Economy (CE) is still lacking. The focus of this paper is on the causal link between SCI and SCRM in a circular economy context, with the main aim of investigating the effects of SCI and SCRM practices combined with CE on company performance. For this research, a multiple case-study approach was adopted involving several companies at different levels in the furniture industry. The results are expected to guide companies in their transition towards CE business models, being able to better deal with CE risks through integrative practices and obtaining an overall increase of efficiency, particularly in costs, due to the optimization and green use of waste materials. [ABSTRACT FROM AUTHOR]

Incidental finding (IF) follow-up is of critical importance for patient safety and is a source of malpractice risk. Laboratory, imaging, or other types of IFs are often uncovered incidentally and are missed, not addressed, or only result after hospital discharge. Despite a growing IF notification literature, a need remains to study cost-effective non–electronic health record (EHR)–specific solutions that can be used across different types of IFs and EHRs. The objective of this study was to evaluate the utility and cost-effectiveness of an EHR-independent emergency medicine–based quality assurance (QA) follow-up program in which an experienced nurse reviewed laboratory and imaging studies and ensured appropriate follow-up of results. A QA nurse reviewed preceding-day abnormal studies from a tertiary care hospital, a community hospital, and an urgent care center. Laboratory values outside preset parameters or radiology over-reads resulting in clinically actionable changes triggered contact with an on-call emergency physician to determine an appropriate intervention and its implementation. Of 104,125 visits with 1,351,212 laboratory studies and 95,000 imaging studies, 6530 visits had IFs, including 2659 laboratory and 4004 imaging results. The most common intervention was contacting a primary care physician (5783 cases [88.6%]). Twenty-one cases resulted in a patient returning to the ED, at an average cost of $28,000 per potential life-/limb-saving intervention. Although abnormalities in laboratory results and imaging are often incidental to patient care, a dedicated emergency department QA follow-up program resulted in the identification and communication of numerous laboratory and imaging abnormalities and may result in changes to patients' subsequent clinical course, potentially increasing patient safety. [ABSTRACT FROM AUTHOR]

[Display omitted] • An integrated machine-learning co-seismic landslide detection method has been developed. • The new method combines multi-source data and pixel- and object-based treatments. • The influence of training data size on detection performance is systematically investigated. • The proposed method exhibits outstanding performance in two earthquake case studies. Numerous co-seismic landslides can be triggered by a strong earthquake. Fast and accurate detection and mapping of these landslides are crucial for rapid risk assessment and humanitarian assistance. Traditional visual interpretation is time-consuming and heavily influenced by human judgement. This paper presents an integrated machine learning (ML) powered method for co-seismic landslide detection, which combines multi-source data, pixel-based and object-based treatments, and ML techniques. The proposed method first fuses multi-source data, including optical images, synthetic aperture radar images and digital elevation models, to produce data layers and reference landslide inventories for learning. After that, ML algorithms are coupled with pixel-based and object-based treatments to produce a series of co-seismic landslide detection models. Powerful models are subsequently recommended after comprehensive evaluation. Two case studies of earthquakes in China are presented. The first is in the epicenter area of the 2008 Wenchuan earthquake. Even trained with only 5% of local data, the proposed method still achieves an accuracy of area (AOA) of 97.77% in the trained area and an AOA of 93.17% in a new area. If trained with the entire local data, an AOA of 99.99% in the trained area and 94.56% in a new area can be obtained. The second case detects the co-seismic landslides induced by the 2017 Jiuzhaigou earthquake. An AOA of 96.55% is achieved with 5% of local data. The case studies confirm the outstanding performance and generic nature of the proposed machine learning method, greatly advancing the state of the art of high-resolution co-seismic landslide detection and the landslide science. [ABSTRACT FROM AUTHOR]

Patients' Own Medications (POMs) are useful to inform clinical decision-making, best possible medication history documentation, and ensure timely medication administration. A procedure was developed for managing POMs specifically in the emergency department (ED) and short stay unit. This study evaluated the impact of this procedure on process and patient safety outcomes. An interrupted time-series was undertaken in a metropolitan ED/short stay unit between November 2017 and September 2021. Pre-implementation and during each of four post-implementation time-periods, data were collected at unannounced times on approximately 100 patients taking medications prior to presentation. Endpoints included proportion of patients with POMs stored in green POMs bags, in standardised locations, and proportion who self-medicated without nurses knowing. Following procedure implementation, POMs were stored in standardised locations for 45.9 % of patients. Proportion of patients with POMs stored in green bags increased from 6.9 % to 48.2 % (difference 41.3 %, p < 0.001). Patient self-administration without nurses' knowledge declined from 10.3 % to 2.3 % (difference 8.0 %, p = 0.015). POMs were infrequently left in ED/short stay unit after discharge. The procedure has standardised POMs storage, but room for further improvement remains. Although POMs were not locked away and were readily available to clinicians, patient self-medication without nurses' knowledge declined. [ABSTRACT FROM AUTHOR]

Humans form and maintain friendships across long distances, which can provide access to non-local resources and support against large shocks that affect the entire local community. However, there may be a greater risk of defection in long-distance friendships, as monitoring for defection is more difficult at greater distances; accordingly, help between long-distance friends may be more explicitly contingent than between close-distance friends. We interviewed 918 participants from 21 fishing villages in Tanzania about whether they had received help in the form of a gift or loan from a friend living in their village and a friend living in a neighboring village. As there are local expectations that loans will be repaid but gifts will not, we predicted that close-distance friends would be more likely to help with gifts, whereas long-distance friends would be more likely to help with loans. Contrary to our predictions, gifts and loans between close- and long-distance friends were similar in kind and amount, though close-distance friends provided help more frequently, possibly because close-distance friends are more likely to meet frequently and belong to the same religious congregation. These results indicate that long-distance friendships are an important, and likely robust, strategy for managing risk and accessing more resources. [ABSTRACT FROM AUTHOR]

We reviewed environmental public health practice at a local level (roles, responsibilities, interaction with partner agencies) to establish what and how an integrated approach to the service, as found in Cheshire and Merseyside, North West England, should be delivered, if at all, and at what footprint. Mixed methods approach. We triangulated: qualitative interviews with relevant professionals to gain an in-depth understanding of their interest and vision for any health protection input to health risks and outcomes from environmental issues; an electronic questionnaire assessing experience, interest, vision and comfort zones of a wider range of professionals involved in environmental health issues; a half-day workshop to review study findings and agree ways forward. Stakeholders value their local health protection team's input, but environmental public-health knowledge and skills also exist in local authority teams. Regional health protection teams can provide environmental public-health expertise to local partners and agencies. They harness national input and evidence with local frontline professionals practice, enabling locally grounded approaches, integrating science into local contexts, to answer difficult, often incorrigible, problems. Specialist leadership by experienced Consultants in Health Protection is of value to local authority public health and environmental teams and should be based on a footprint that is appropriate to enhance local relationships without compromising available expert knowledge and skills. [ABSTRACT FROM AUTHOR]

Hydrogen energy has become a pivotal actor in achieving carbon neutrality by 2050 in the era of the climate crisis. Regardless of its importance, three consecutive hydrogen safety accidents and their aftermath in South Korea have aggravated the public's acceptance of hydrogen. Hydrogen-induced risks have always existed in our society regardless of technical improvement. Here, the task of the government is to manage the hydrogen risk to prevent hydrogen disasters. This study included three steps in its research design; 1) selecting experts through snowball sampling, 2) conducting a qualitative email survey, and 3) analyzing the qualitative answer sheet by applying semantic network analysis. We found that experts' evaluations of the Korean hydrogen PR policy were positive regarding responsiveness but negative regarding openness, guidelines, and control tower. Therefore, we suggest practical policy recommendations; the central government should play an important role in cultivating professional crisis management PR personnel and others. [Display omitted] • Experts positively evaluate the responsiveness of hydrogen PR policies in Korea. • Yet, experts negatively evaluate policy openness, guidelines, and control tower. • The government should improve communication about hydrogen technology. • The government needs to cultivate professional crisis management PR personnel. [ABSTRACT FROM AUTHOR]

In exploring alternative and more sustainable sources, hydrogen has played a dominant role as an energy vector and is suitable for reducing carbon emissions. However, given the properties of hydrogen and existing transportation challenges for this substance, studies that involve assessing risk when transporting hydrogen still need attention. Therefore, this paper presents a multi-criteria decision model to support organizations responsible for transporting hydrogen in a pipeline in risk management under a multidimensional perspective. In particular, we developed a search algorithm to select sections within the set that makes up the pipeline network (a portfolio-based approach), with a view to identifying the most critical areas in terms of risks and to optimizing the allocation of resources for mitigation while respecting current requirements. In addition, these risks are evaluated under three dimensions of loss: environmental, financial, and human. Hence, a numerical application is presented to illustrate the benefits of the model proposed. The results demonstrate that the model can help managers make more informed and strategic decisions about where to direct their risk management efforts to maximize pipeline safety and minimize incident risks. [ABSTRACT FROM AUTHOR]

A risk screening program has been developed to identify facilities that have the potential impact to public and environmental receptors. This allows the company to assess and effectively manage the risks associated with these facilities through their internal "Specialized Field Risk Management" (SFRM) program. Conducting risk screening and keeping it current in an operating environment is very challenging because of the large number of ongoing development projects, the frequent changes of operating conditions, and public encroachment on these facilities. This paper presents a systematic approach to implement and keep this risk screening program evergreen under these changing conditions. In this approach, existing project management systems such as Management of Change and Well Execution Planner were leveraged to develop and convey the risk screening workflow. In areas of concern such as public encroachment, where monitoring processes were not in place, a risk screening workflow was created to address the gap. This risk screening workflow was also integrated into asset acquisition due diligence activities to support these important business decisions. These workflows were consolidated into a single robust risk screening program managed by a centralized functional group. This program has been proven effective in identifying and avoiding potential high offsite risks in the planning stage of a project, as well as to help manage these risks through the asset's life cycle. [ABSTRACT FROM AUTHOR]

• There was good treatment fidelity based on case management, as well as good adhesion to recommendations. • The satisfaction of both groups was positive, although the Intervention Group had a better score. • There was a significant influence of monthly income and general health on treatment fidelity (Intervention Group). • Age, years of schooling, general health and physical mobility influenced satisfaction with case management. • The understanding of how clinical and sociodemographic factors influence health interventions can be useful to adapt and replan the care provided. To verify the treatment fidelity and satisfaction with a multifactorial intervention based on case management in community-dwelling older people with falls history and related sociodemographic and clinical factors. This is a single-center, randomized, parallel-group controlled clinical trial. 62 community-dwelling older people with falls history were distributed into two groups. The Intervention Group (IG) underwent a case management involving multidimensional evaluation, explanation of the risk factors for falls identified, implementation of an intervention proposal based on the identified risks, elaboration of an individualized falls intervention plan, implementation, monitoring and review of the intervention plan. The Control Group (CG) was accompanied by a monthly phone call. After 16 weeks, the volunteers answered two closed questionnaires about treatment fidelity or non-fidelity to intervention (IG) and satisfaction with intervention (both groups). In addition, the frequency of intervention, adherence to each recommendation of the case management and satisfaction with general care were evaluated. There was good treatment fidelity based on case management, as well as good adherence to recommendations. In addition, the satisfaction of both groups was positive, although the IG had a better score (p<0.05). There was a significant influence of monthly income and general health on treatment fidelity (IG). Also, age, years of schooling, general health and physical mobility significantly influenced satisfaction with the IG. There was a significant influence of number of falls on satisfaction with monitoring conducted in the CG. Clinical and sociodemographic factors can influence treatment fidelity and satisfaction of older people with falls history to a falls prevention program. [ABSTRACT FROM AUTHOR]

With the increasing deployment of hydrogen fuel cell forklifts, it is essential to understand the risks of incidents involving these systems. A quantitative risk assessment (QRA) study was conducted to determine the potential hydrogen release scenarios, probabilities, and consequences in fuel cell forklift operations. QRA modeling tools, such as fault tree analysis (FTA) and event sequence diagrams (ESD), were used together with hydrogen systems data. This work provides insights into the fatality risk from a hydrogen fuel cell forklift and the reliability of its design and components. The analysis shows that the expected fatal accident rate of a hydrogen forklift is considerably higher than current fatal injury rates observed by the Bureau of Labor Statistics for industrial truck operators and material handling occupations. Nevertheless, the average individual risk posed to forklift drivers was found to be likely tolerable based on current risks accepted by industrial truck operators. Jet fires are found to dominate the system's risk, however, the risk of explosions is also considerable. An importance measures analysis shows that these risks could be mitigated by improving the design and reliability of pressure relief devices, as well as other components prone to leak such as filters and check valves. We also identify sources of uncertainty and conservatisms in the QRA process that can guide future research in hydrogen systems. These results provide powerful insight into improvements in the design of fuel cell forklifts to reduce risk and enable the safe deployment of this key technology for a decarbonized future. [Display omitted] • Employed FMEA and fault trees to model failure events in H2 forklifts. • Utilized Event Sequence Diagrams and physics simulations to assess loss of life. • Determined risk tolerability of H2 forklift compared to current industry statistics. • Determined most important risk-influencing factors for a H2 forklift design. • Provided H2 forklift design recommendations for risk reduction and safer deployment. [ABSTRACT FROM AUTHOR]

In this paper, an improved approach for space mission risk classification based on text mining is proposed. The method consists of the text mining of extracted bibliographic data with an improved accuracy compared to previous works. Based on these data, a weight is attributed to each of the identified risk parameters and a total mission class score is calculated. A quantification of the interrelation of these parameters, with the use of the t-score metric, together with the appropriate visualization is also provided for further analysis. The proposed method serves as an assistant tool to the appointed panel of experts that is traditionally tasked with the assignment of weights to the parameters. It allows for the consideration of parameters of widely different importance, even by almost an order of magnitude. Eight classification parameters are assessed including: (a) Criticality to the Agency, (b) Objective importance, (c) Cost, (d) Lifetime, (e) Complexity, (f) Manned mission, (g) Destination, and (h) Omega Factor. The most important parameter is shown to be the Complexity of the mission contributing around one fourth of the total weight. Finally, the NASA Mars Perseverance mission is used to demonstrate the application of the classification algorithm. • Improved approach for space mission risk classification based on text mining. • Weight calculation for risk parameters and space mission risk classification. • Visualization of risk parameter interrelation based on t-score metric. • Automated assistant tool to experts for space mission risk assessment. • Risk classification of NASA Mars Perseverance mission. [ABSTRACT FROM AUTHOR]

Renewable energy attracts increasing attention from both industry and academia under the context of carbon neutrality. For wind and solar energy, the strong dependence on natural processes results in the imbalance between energy production and real demands. Energy storage technologies, e.g., Compressed Air Energy Storage (CAES), are promising solutions to increase the renewable energy penetration. However, the CAES system is a multi-component structure with multiple energy forms involved in the process subject to high temperature and high-pressure working conditions. The CAES system is a complex process flowsheet consisting of charging and discharging process. The process should be optimized to achieve the best thermodynamic and economic performance. Under the optimal design conditions, it might lead to severe consequences once a failure occurs, e.g., harm to humans, the environment, and assets. Limited attention and scarce available information have been paid to the CAES system risk management yet. Hence, this paper applies the System-Theoretic Process Analysis (STPA), which is a top-down method based on system theory, to identify the CAES system safety hazards. The results are expected to provide a preliminary guideline for practitioners regarding the safety and reliability of the CAES system. As a result, a more reliable CAES system can contribute to a more flexible energy system with more efficient and economic utilization of fluctuating renewable energy. [ABSTRACT FROM AUTHOR]

La bactériologie de l'environnement, ou bactériologie d'environnement, est une sous-spécialité de la microbiologie d'environnement et un outil de gestion de la fraction bactériologique des risques biologiques. Dans un établissement de soins, son objectif est, entre autres, d'identifier les réservoirs et/ou les sources potentielles des bactéries d'intérêt, d'étudier les activités biologiques, la dissémination et la persistance des bactéries ou de leurs éléments génétiques mobiles dans un environnement, la formation des biofilms et la réactivité avec des composés inorganiques, d'estimer le risque/opportunité associé à ces bactéries ainsi qu'à leurs éléments génétiques mobiles, de sélectionner les procédures et les méthodes de surveillance des bactéries du microbiote ou flore microbienne environnementale afin de permettre la mise en place de solutions techniques et/ou technologiques appropriées en vue de prévenir les transferts de contamination entre humains, animaux et environnement. En dehors de l'évaluation du risque de biocontamination, la bactériologie d'environnement, comme la microbiologie d'environnement toute entière, est un outil d'évaluation des opportunités associées à la biotechnologie et au développement durable. La mise en œuvre de la bactériologie d'environnement exige des compétences humaines, une organisation pragmatique dans un écrin de démarche qualité aboutie et un financement ad hoc. Environmental bacteriology is a part of and subspecialty of environmental Microbiology and the bacteriologic risk management tool. In health-care facilities, its objectives are to identify bacteriological biocontamination risk associated with health-care settings' environment. It contributes to identifying reservoirs and sources of potentially harmful or useful environmental bacteria and their mobile elements such as genes or metabolites. It's used to evaluate the risk/opportunity associated with environmental bacteria, to study their environmental dissemination and/or persistence, the formation of their biofilms. It's also the best tool to choose and tailor bio-decontamination interventions' efficacy. As a such, environmental bacteriology contributes to the development of biotechnologies and sustainable development and not only in environmental fields. Practicing environmental bacteriology necessitate an environmental microbiologic laboratory well equipped, well financed, run under a risk and quality management policy purposely built using competent, continuously trained and up-to-date knowledge personal. [ABSTRACT FROM AUTHOR]

Considering the potential magnitude and impact of cyber-attacks, organizations must be able to understand their capabilities to prevent, respond and re-cover from these attacks as well to implement and refine adequate resilience plans. Due to the importance of cyber resilience, this survey aimed to review relevant case studies published in the scientific literature. The identified case studies followed different approaches since some of them were focused on risk assessment and risk management processes and the complexity of their implementation, while others were focused on the use of well-known frameworks to assess cyber resilience or on proposing new cyber resilience frameworks and tools. [ABSTRACT FROM AUTHOR]

This review article examines recent advances in the use of machine learning for process industries. The article presents common process industry tasks that researchers are solving with machine learning techniques. It then identifies a lack of consensus among past studies when selecting an appropriate model given a prescribed application. Furthermore, the article identifies that relatively few past studies have considered model interpretability – a "black-box" challenge holding back machine learning's implementation in more high-risk industrial applications. This interdisciplinary field of engineering and computer science is still reasonably young. Additional research is recommended to standardize methods and establish a strategic framework to manage risk during adoption of machine learning models. [ABSTRACT FROM AUTHOR]

Providing solutions in the form of Product-Service Systems (PSS) becomes an established strategy of manufacturing companies for gaining competitive advantages. Especially in times of global crisis, the innovative business models of PSS can provide a secure and continuous source of revenue. The provision of these business models, however, is often accompanied with more risks than in traditional business models since the provider assumes the responsibilities for e. g. the availability of the technical asset. To cope with these risks, suitable methods and tools are needed. This paper introduces multimethod simulation modeling as a new tool for the risk management of PSS. [ABSTRACT FROM AUTHOR]

Healthcare providers are obliged to reduce the risk of harm to patients using their services. Robust risk management embraces a blame-free reporting culture and learning from clinical errors whilst adopting a proactive approach to the measurement of patient safety indicators. A good safety culture within an organisation provides assurance to service users, staff, and the public, that there is commitment to provision of high quality safe and effective care. Risk management is everybody's responsibility. Therefore, all clinicians must possess an understanding of risk management processes. This review outlines the key elements of risk management within gynaecology and explains how risks are identified, assessed, quantified and managed. Examples from within the gynaecological setting and the challenges and the emergent risks posed by the COVID19 pandemic, are also discussed. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes a respiratory illness called the novel coronavirus 2019 (COVID-19). COVID-19 was declared a pandemic on March 11, 2020. Bow tie analysis (BTA) was applied to analyze the hazard of SARS-CoV-2 for three receptor groups: patient or family member at the IWK Health Centre in acute care, staff member at a British Columbia Forest Safety Council (BCFSC) wood pellet facility, and staff member at the Suncor refinery in Sarnia, Ontario. An inherently safer design (ISD) protocol for BTA was used as a guide for evaluating COVID-19 barriers, and additional COVID-19 controls were recommended. Two communication tools were developed from the IWK bow tie diagram to disseminate the research findings. This research provides lessons learned about the barriers implemented to protect people from contracting COVID-19, and about the use of bow tie diagrams as communication tools. This research has also developed additional example-based guidance that can be used for the COVID-19 pandemic or future respiratory illness pandemics. Recommended future work is the application of BTA to additional industries, the consideration of ISD principles in other control types in the hierarchy of controls (HOC), and further consideration of human and organizational factors (HOF) in BTA. [ABSTRACT FROM AUTHOR]

• Prediction accuracy of loss reserving by incorporation of heterogeneity among policies. • Use expectation-maximization algorithm to obtain the maximum likelihood estimations • Show the deviation of loss reserving weakly converges to a normal distribution. • Simulation study to evaluate the performance of EM algorithm and the Newton-Raphson method. • Analyse real-life health insurance data to illustrate the use of the method. In stochastic reserving, the incurred outstanding liabilities of general insurance companies result in incomplete claims because of truncation and censoring. It is necessary for insurance companies to predict liabilities in risk management. We propose a model that allows the incorporation of heterogeneity among policies, which is important for loss reserving. The incompleteness of observation data leads us to use expectation-maximization (EM) algorithm to obtain the maximum likelihood estimations of the parameters of the model. We also show that the deviation of loss reserving from the loss reserve weakly converges to a normal distribution at the rate m , where m is the size of the risk portfolio. A simulation study is conducted to compare the proposed method with the ones without policyholder's information as well as obtained by chain ladder method and compare the convergence rates of EM algorithm and the direct maximization by Newton-Raphson method. We also analyse real-life health insurance data to illustrate the use of the method in practice. [ABSTRACT FROM AUTHOR]

This paper discusses the asymmetric volatility spillovers between these two markets of BRICS' countries during different financial and economic circumstances from 2010 until 2021, using the ARFIMA-FIAPARCH to model the dynamics of the marginal distribution. We study the feasibility of hedging stocks with oil, risk measurement functions allow financial practitioners to calculate the optimal hedge ratios and the corresponding to hedge portfolio returns. A dual long memory model is adopted to estimate the conditional mean and the conditional variance. Thereafter, a V a R , C V a R and Δ C V a R are applied to assess oil price exposure. Furthermore, to evaluate the optimal portfolio, we adopted the optimal portfolio weight, the optimal hedge ratio and the hedge effectiveness oil. Our results show that there are distinct economic benefits from hedging stocks with oil, although the effectiveness of hedging is both time-varying and market-state-dependent. We determine that the volatility transmission was time-varying and that influence from the Asian crisis, the bursting of the dot com bubble, the 2008 global financial crisis, the recent oil-price crash, and COVID 19 alternated between negative and positive values, over the entire studied period. During times of global financial uncertainty, investors reduce stock positions more than commodity positions, thus crude oil prices shock negatively affect the portfolio returns of stock-oil hedges. all stock market–oil pairs display the highest hedging effectiveness during the COVID-19 pandemic, which proved that the oil market can assist as a hedge for stock market in a portfolio. [ABSTRACT FROM AUTHOR]

Large-scale algae production has garnered interest due to its potential as a biofuel feedstock. Previous research assessing the profitability of algae products has been mostly based on values averaged over time, but algae production and resulting financial returns exhibit significant variability due to weather and fluctuations in selling prices for algae-based products. In other sectors, producers often reduce weather- and market price-related financial risk with financial instruments such as insurance, but little research has been performed on the design of insurance products to protect algae producers. This study develops a novel index-based insurance instrument that pays-out during unfavorable weather and market conditions, then explores the instrument's effectiveness, combined with a cash reserve, in reducing revenue stream variability for an algae producer. Results indicate that a biophysically based index-insurance product tailored to the specific financial risks in algae production can reduce variability in net revenues and can do so at a lower cost than relying solely on cash reserves, the most common financial risk management tool. Assessing the performance of index-insurance in algae production is particularly timely given the passage of the 2018 Farm Bill, which newly opens opportunities for the USDA to provide crop insurance to algae producers. [Display omitted] [ABSTRACT FROM AUTHOR]

Since the beginning of the 21st century, China's new media industry has attracted more and more investors' attention with its rapid development. However, its stock market has consistently shown unstable performances in recent years. In this study, we explore the interconnections between new-media stocks by conducting liquidity risk and liquidity spillover analysis between individual stocks and markets. We find that the instability of China's new media stocks stems from the volatility of idiosyncratic risks and high systemic correlation across markets, which collectively contribute to higher liquidity risk spillover effects. [ABSTRACT FROM AUTHOR]

Afin d'étudier la perception du rôle et l'implication effective des manipulateurs en électroradiologie médicale dans la gestion des risques en radiothérapie, un questionnaire a été élaboré et diffusé dans cinq pays (France, Suisse, Belgique, Irlande, Pays-Bas). L'article présente les résultats de cette enquête et la comparaison entre les différents pays. Globalement les résultats de l'enquête montrent une bonne implication et perception des manipulateurs autour de la démarche de gestion des risques bien que la formation sur ce domaine reste à systématiser. Bien qu'avec des différences dans les résultats entre les pays participants, l'enquête semble mettre en évidence le déploiement d'actions de prévention évaluées comme peu efficaces par les répondants et aussi par la littérature scientifique internationale. In order to study the role perception and the effective involvement of Radiation TherapisTs (RTTs) in risk management in radiotherapy, a survey was developed and distributed in five countries (France, Switzerland, Belgium, Ireland, the Netherlands). The article presents the results of this survey and the comparison between the different countries. Overall, the results of the survey show a good involvement and perception of the RTTs around the risk management approach, although training in this area has yet to be systematized. Although with differences in the results between the participating countries, the survey seems to highlight the deployment of preventive actions that are evaluated as not very effective by the respondents and by the international scientific literature. [ABSTRACT FROM AUTHOR]

• International Collaboration between 15 countries to derive a Biomonitoring guidance. • Step-by-step approach for health professionals deriving biomonitoring values. • Occupational Biomonitoring Levels (OBLs) values are valuables in risk assessment. • Effective communication of biomonitoring results are necessary to ensure ethical use. Biomonitoring has been widely used in assessing exposures in both occupational and public health complementing chemical risk assessments because it measures the concentrations of chemical substances in human body fluids (e.g., urine and blood). Biomonitoring considers all routes and sources of exposure. An occupational biomonitoring guidance document has been elaborated (OECD Occupational Biomonitoring Guidance) within the OECD framework and specifically, the Working Parties on Exposure and Hazard Assessment by scientific experts from 40 institutes and organizations representing 15 countries. The guidance provides practical information for assessing chemical exposures in occupational settings including the three common routes of exposure: inhalation, skin absorption and ingestion due to hand to mouth contact. The elaborated stepwise approach for conducting biomonitoring is tailored for occupational health professionals, scientists, risk assessors, and regulators. It includes methods for selecting appropriate biomarkers, devising sampling strategies, and assessing laboratories for validated analytical methods for the biomarker of interest, and ensuring timely feedback of results. Furthermore, it describes procedures for setting up efficient biomonitoring programs based on the Similar Exposure Group (SEG) approaches. Derived health-based human exposure biomarker assessment values called Occupational Biomonitoring Levels (OBLs) are proposed for use in occupational exposure and risk assessment. It also helps with the interpretation of biomonitoring results routinely collected and procedures for communicating biomonitoring results at individual, collective, and workplace levels. Ethical considerations associated with biomonitoring are also discussed. The ultimate goal of this biomonitoring approach is to promote harmonized application and interpretation of biomarkers as well as evidence-based occupational risk management measures. [ABSTRACT FROM AUTHOR]

• Positive and negative ecological linkages are modelled. • The concept of ecological risk networks was pioneered. • Proposing a research framework for ecological and risk networks. • Ecological networks and risk networks were identified. • Building a comprehensive ecological security pattern. This paper proposes a network structure that simulates regions' dual positive and negative ecological linkages based on ecological protection and risk management perspectives. This network structure model simulates positive and negative ecological flows between regions by establishing ecologically discrete, isolated, structurally and functionally interconnected regions. We first define the concepts related to ecological networks and risk networks. Taking Shaanxi Province as a case study, we construct a comprehensive ecological security pattern based on identifying ecological and risk networks. (1) Our results show 30 ecological and 34 risk source patches in our study area. These patches are connected through 103 ecological and 77 risk corridors, respectively. (2) Most of the ecological nodes, ecological corridors, risk nodes, risk corridors, and integrated ecological and risk nodes in the ecological security pattern of our study area are distributed along the watershed. Additionally, some risk nodes and risk corridors are distributed along the transportation network. Our study area shows a comprehensive ecological security pattern of protection and control with emphasis on protection in the south, protection in the center, and control in the north. (3) Further analysis showed that the intersection of ecological corridors and risk corridors with different degrees of importance would form four types of integrated ecological and risk nodes. The first type of integrated node has a strong isolation effect on both ecological and risk sources; the second type of integrated node has a weak isolation effect on ecological source sites but a strong isolation effect on risk source sites; the third type of integrated node has a strong isolation effect on ecological source sites but a weak isolation effect on risk source sites; and the fourth type of integrated node has a weak isolation effect on both ecological and risk sources. Our research contributes to the existing scholarship by providing a scientific basis for the comprehensive management of ecological security. Furthermore, it also provides support for enriching and developing the connotation and extension of ecological network research. [ABSTRACT FROM AUTHOR]

Business failure prediction has become crucially important for today's firms, enabling them to reduce financial risks and make informed decisions. This study uses a dataset of 6819 companies and 96 financial and macroeconomic variables to present a comparative analysis of machine learning (ML) models for predicting corporate bankruptcies. Behind this research is to improve the accuracy of bankruptcy prediction, which can help companies make more informed decisions and reduce financial risks. This study aims to evaluate the effectiveness of 16 ML algorithms in terms of accuracy, sensitivity, and other relevant metrics. The work uses methodologies that include data collection and cleaning, exploratory data analysis, model preprocessing and training, and model performance evaluation. Data preprocessing and hyperparameter optimization techniques were used to improve model performance. The evaluated algorithms include Classifiers such as Stacking Classifier (SCC), Randomized Search Classifier (RCV), Historical Gradient Boosting Classifier (HGBC), MLP Classifier (MLPC), K-Neighbors Classifier (KNC), Decision Tree Classifier (DTC), XGBRF Classifier (XGBRFC), Support Vector Classifier (SVC), Logistic Regression Classifier (LR), Linear SVC Classifier (LSVC). With an accuracy of 97.63 %, recall of 97.63 %, and F1-score of 97.63 %, the results show that the SCC algorithm was the best. Other models, such as RCV and DTC, also showed good results, with accuracies above 97 %. However, models such as PAC and BNB had lower performance and accuracy below 90 %. Finally, this study compares the results of ML models in predicting business failures and highlights their effectiveness. The SCC algorithm is considered the most suitable model for this task, as it suggests that it can help economic actors make more informed decisions and reduce financial risks in the context of firms. [ABSTRACT FROM AUTHOR]

This study investigates the factors influencing the comfort level of the general public when disclosing personal information for the coronavirus disease 2019 contact tracing. This is a secondary analysis of the American Trends Panel, a national probability-based online panel of American adults, with data collected by the Pew Research Center between July 13 and 19, 2020. Grounded in privacy management theories, ordered logistic regression analyses examined three types of information disclosure: places visited, names of contacts, and location data from cell phones. Key independent variables measured trust in the stakeholders' ability to protect data and perceived risks to health and finances. The findings suggest that higher levels of trust in entities' data security capabilities can predict individuals' comfort levels when disclosing personal data. Additionally, the participants were more comfortable with noncommercial data use, especially when it was used by researchers and state and local officials. However, financial threats showed variations in sharing certain types of data. Individuals were less likely to feel at ease sharing contact tracing data as concerns about personal finances increased. Similarly, when individuals perceived threats to the U.S. economy, they were less likely to feel comfortable sharing their location data from cell phones, which might have been perceived as intrusive. Public health outreach efforts should account for individual differences and the nature of the information requested in commercial and noncommercial contexts. Future studies can enhance the explanatory capacity of data disclosure models by incorporating additional relevant contextual and environmental variables. • Public cooperation with contact tracing is important to curb disease spread during health crises. • Privacy management theories shape public engagement with contact tracing. • The level of trust is key for disclosing personal data. • Comfort levels in disclosing personal data vary between commercial and noncommercial contexts. • Perceived financial and health threats influence comfort levels in disclosing personal data. [ABSTRACT FROM AUTHOR]

• Safety risk management practices in the Ghanaian oil & gas industry were assessed. • A disparity between work as planned and work as done was observed. • Qualitative risk management tools were preferred over quantitative risk management tools. • Bowtie analysis was narrowly used and identified as an opportunity to improve risk management. Risk management has been regarded as one way to improve workplace health and safety conditions. However, very little research has been published on the perspectives of practitioners on safety risk management in general and the Ghanaian oil and gas industry in particular. This study bridges this literary gap by presenting findings from an online survey that investigated the perspectives of practitioners on safety risk management processes of the Ghanaian oil and gas industry. The results of 219 respondents indicated that a disparity existed between the risk methods the practitioners were required to use by their companies and the risk management methods the practitioners preferred to use, and this was verified through statistical testing. Whereas the practitioners were required by their organisations to use quantitative methods, they preferred to use qualitative methods, indicating a difference between work as planned/imagined and work as done. It was further observed that risk management tools/techniques were mostly used proactively, with a limited reactive application during accident investigations. This suggests the limited/lack of integration of risk management into accident investigation processes. Furthermore, feedback from the respondents indicated the narrow use of bowtie analysis in the Ghanaian mining industry as over 60 % of the practitioners had received no training and could not use bowtie analysis. The practitioners' responses generally showed that whereas current risk management processes in the Ghanaian oil and gas industry had some strengths, some weaknesses exist which offer improvement opportunities. These have been discussed throughout the paper. [ABSTRACT FROM AUTHOR]

This paper proposes an intelligent risk management system in stock markets based on indications of social media platforms. Based on a brief survey, we found that the literature focuses on identifying, assessing and optimizing risks in stock markets using classical data sources as well as utilizing mathematical, statistical and machine learning techniques. So, we suggest a trendy data source that is social media and employing natural language processing as an advanced technique to identify and estimate risks in stock markets. This NLP model can help the investors of stock markets to be aware of the potential risks, its types and magnitudes which can help them to take the best decisions. In addition , we describe this model and some important expressions for risk analysis, risk recognition and risk estimation are driven. Besides, a practical experiment is provided to identify and evaluate the potential risks in NASDAQ stock market. Moreover, several performance measures are used to validate the efficiency of the proposed model such as the mean accuracy for the processes of risk analysis, risk identification and risk assessment is 73.33 %. [ABSTRACT FROM AUTHOR]

In the financial market, different assets typically exhibit time-varying asymmetric dependence in scenarios of rise and fall. To accommodate this feature, this article proposes a novel model, the Skew t stochastic factor Copula model, designed to accurately capture the skewness characteristic of each variable. We employ an expectation-maximization algorithm for variable clustering and demonstrate its finite sample properties. In addition, we integrate this proposed model into a mean-ES model and explore its feasibility and applicability in financial risk measurement and portfolio optimization, supported by empirical studies. • A Skew t stochastic factor Copula model is constructed and practically applied. • The EM algorithm based on this model has been verified to possess finite sample properties. • The mean-ES portfolio solution is obtained for this Copula model. • The portfolio model demonstrates excellent performance in empirical studies. [ABSTRACT FROM AUTHOR]

With the intensification of technological innovation competition and the surge in the number of patents in modern society, companies' technology activities such as technology R&D, technology licensing and technology transfer now regularly involve large patent portfolios, as well as a rising risk of patent infringement. However, the existing patent infringement risk assessment methods are only designed for individual patents, which is not enough to meet the companies' practical need for assessing and managing the infringement risk of large patent portfolios. Therefore, this study proposes a combined approach using network analysis and intuitionistic fuzzy technique for order preference by similarity to ideal solution (IF-TOPSIS), which can assess and rank the infringement risk of a company's patent portfolio relative to each of its competitors' patent portfolios, thereby providing a scientific base for the company's management decisions on patent portfolios. In this approach, one-mode weighted patent proximity networks are constructed to extract topology information of patent portfolios, and the IF-TOPSIS method is combined to obtain and rank the risk results under a proper fuzzy framework. The case study uses patent portfolios containing a total of 6736 standard-essential patents (SEPs) in the information and communications technology (ICT) industry as test data, and verifies the practicality and validity of this intelligent approach. Managerial implications for technology managers and patent attorneys are elaborated. • A combined approach is proposed for assessing infringement risk of patent portfolios. • A hierarchical indicator system is established at patent portfolio level. • Patent proximity networks are analyzed to extract information of patent portfolios. • IF-TOPSIS is used for risk assessment and ranking under a fuzzy framework. • A case of standard-essential patent portfolios in the ICT industry is studied. [ABSTRACT FROM AUTHOR]