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The recent technological advances in Automated Driving Systems (ADS) have fueled interest in the use and impact of vehicle fleetsinvolved in driverless passenger transport services. This research identifies key safety risks associated Level 4 ADS-equipped vehicleoperation for fleets employed for Mobility as a Service (MaaS) applications. The study goes beyond assessing the functional safety ofthe ADS-equipped vehicles to explore the role of fleet operators in ensuring the operational safety of the vehicle fleets through remote driving assistance functions. This work identifies key responsibilities of the fleet operators in implementing risk reductionmeasures related to organizational management of change, training remote supervisors, ensuring suitable working conditions, enforcing vehicle connectivity and dispatching requirements, and coordinating incident mitigation procedures, training, tools, and work conditions. The study employs a hazard identification methodology that combines traditional and innovative methods to analyze risks involving human, software, and hardware systems. The study identified twenty hazard scenarios arising from system failures, human errors, and unsafe interactions during different operational phases. These are ranked based on their impact on safety and resource intensity, enabling fleet operators to make better decisions regarding resource allocation. By implementing these actions, fleet operators can prevent and mitigate safety hazards in the operation of ADS-equipped fleets though remote monitoring and driving assistance functions. The hazards and risk mitigation activities identified in this report may also improve the operational safety of passenger vehicles equipped with ADS technology as they become more widely deployed in future large-scale commercialoperations.

With the rise of artificial intelligence in safety-critical systems like surface transportation, there is a commensurate need for new hazard analysis approaches to determine if and how AI contributes to accidents, which are also increasing in number and severity. The original Swiss Cheese model widely used for hazard analyses focuses uniquely on human activities that lead to accidents, but cannot address accidents where AI is a possible causal factor. To this end, the Taxonomy for AI Hazard Analysis (TAIHA) is proposed that introduces layers focusing on the oversight, design, maintenance, and testing of AI. TAIHA is illustrated with real-world accidents. TAIHA does not replace the traditional Swiss Cheese model, which should be used in concert when a joint human-AI system exists, such as when people are driving a car with AI-based advanced driving assist features. [ABSTRACT FROM AUTHOR]

Proton exchange membrane (PEM) electrolysis is a promising technology for clean hydrogen production. To support safe deployments of PEM electrolyzers, we performed a failure modes and effects analysis (FMEA) on a lab-scale PEM electrolyzer to identify risk-significant scenarios. We identified 20 failure scenarios leading to a hydrogen release, 46 for an oxygen release, and 67 for hydrogen and oxygen mixing. Hydrogen fires or the collection of hydrogen and oxygen gas poses risk to facility personnel and surrounding equipment. The gas-water separators, pump supplying water to the electrolyzer stack, and electrolyzer stack were found to contribute to the most high-risk scenarios. Identifying these scenarios enables the mitigation of issues seen in early deployments and is a step toward a complete Quantitative Risk Assessment. The results provide a technical basis to support risk-informed safe and reliable deployment and operation of electrolyzer technologies by enabling development of safety plans, design, and operational strategies. • Conducted a FMEA on a lab-scale PEM electrolyzer • Provided 133 failure scenarios leading to H2 release, O2 release, or H2–O2 mixing • Determined the system components that contributed to the most high-risk scenarios • Provided mitigation measures for risk reduction of PEM electrolyzers [ABSTRACT FROM AUTHOR]

The selection and scaling of ground motion records is considered a primary and essential task in performing structural analysis and design. Conventional methods involve using ground motion models and a conditional spectrum to select ground motion records based on the target spectrum. This research demonstrates the influence of adopting different weighted factors for various period ranges during matching selected ground motions with the target hazard spectrum. The event data from the Next Generation Attenuation West 2 (NGA-West 2) database is used as the basis for ground motion selection, and hazard de-aggregation is conducted to estimate the event parameters of interest, which are then used to construct the target intensity measure (IM). The target IMs are then used to select ground motion records with different weighted vector-valued objective functions. The weights are altered to account for the relative importance of IM in accordance with the structural analysis application of steel moment resisting frame (SMRF) buildings. Instead of an ordinary objective function for the matching spectrum, a novel model is introduced and compared with the conventional cost function. The results indicate that when applying the new cost function for ground motion selection, it places higher demands on structures compared to the conventional cost function. Moreover, submitting more weights to the first-mode period of structures increases engineering demand parameters. Findings demonstrate that weight factors allocated to different period ranges can successfully account for period elongation and higher mode effects. [ABSTRACT FROM AUTHOR]

Tsampa, as an essential traditional food in Tibet, demands strict quality and safety assurances during its industrial production process. In order to ensure the food safety of the public, it is urgent to establish a comprehensive quality and safety control system aimed at enhancing the food quality and safety of Tsampa. This study conducts a systematic hazard analysis on the entire production process of Tsampa from raw materials to finished products, identifies critical control points, sets critical limits and corrective measures, and ultimately formulate and verify a HACCP (Hazard Analysis and Critical Control Point) plan. By applying the HACCP system to the production processes of local Tibetan Tsampa enterprises, five critical control points, including raw material acceptance, raw material storage, roasting, packaging, and finished product storage, were identified and subjected to in-depth analysis of significant hazards. Corresponding control measures and critical parameters were established for various hazards. The effective implementation of the HACCP system within the actual production processes ensures comprehensive control over the quality and safety of Tsampa, thereby promoting the sustainable development of the Tibetan Tsampa industry.

After the Minxian-Zhangxian magnitude 6.6 earthquake on July 22, 2013, debris flow occurred in Fangjiagou, Zhangxian County. To reduce the potential damage of debris flow, a three-level check dam and drainage channel were built in the gully to regulate the peak flow of debris flow and reduce the threat to the downstream accumulation fan protection objects. However, The control project currently in place in the study area has been designed based on the characteristics of previous debris flow occurrences, and its effectiveness for future incidents remains to be tested. This study used the bilinear interpolation method to fine process DEM data of high-precision remote sensing image, reconstructed the check dam and topographic model of Fangjiagou small watershed, and adopted FLO-2D software to simulate and analyze the movement characteristics and risk of Fangjiagou debris flow under different precipitation probability conditions; the effect of debris flow control project thus then was evaluated. The results show that: As the intensity of rainfall gradually increases, the desilting ability of the barrier dam for debris flow increases gradually, and the debris flow does not pass the barrier dam. The limiting efficiency of flow rate of debris flow is 80.1%, which greatly weakens the impact of failure ability of debris flow. The area with a high risk of debris flow is reduced by 45.34%, which effectively reduces the influence range of debris flow. This study presents that the debris flow blocking project has a remarkable treatment effect under the simulation condition of Fangjiagou dam construction, which can provide effective guidance for the feasibility test of debris flow blocking projects in similar small watersheds.

In this research, the deformation pattern of Alborz is investigated using a combination of data from the new permanent GPS networks that belong to State Organization for Registration of Deeds and Properties (SHAMIM) and Tehran Municipality (SAMT), the new temporary IASBS_NCC network and the permanent and temporary stations of the National Cartographic Organization. The addition of the 27 new GPS stations has improved the obtained velocity field, which shows that the active deformation happens across the entire width of Alborz from south to north by several faults and active fault zones. Contrary to the common belief about the strain partitioning in the Alborz Mountains between the strike-slip faults in the southern flank of the Alborz and along the compressional south-dipping Khazar fault in the northern flank of the Alborz, the new velocity field indicates a spread of strike-slip and compressional movements along different faults across the width of the Alborz. In previous works, due to the lack of GPS stations between the Khazar fault and other active faults in the northern flank of the Alborz (e.g. North Alborz fault), all the observed deformation in the northern flank of the Alborz has been associated with the Khazar fault. In the improved velocity field, the presence of a new GPS vector between the North Alborz and the Khazar fault in the eastern part of the Alborz indicates a dominant role of the North Alborz fault in the strain accommodation once compared to the Khazar fault. Like the previous works, the new velocity field shows a lower total strain for the western Alborz, which is consistent with the lower observed seismicity in the western Alborz. The new velocity field indicates an active extensional system in the western Alborz in a longitude range of 49o to 50.5o around the Tarom Valley. The extensional system might be related to the counterclock wise rotation of the South Caspian Basin relative to Eurasia. The improved velocity field shows a noticeable strike-slip motion of 2 mm/yr at the northern edge of Central Iran which could be related to the Aran-Torud fault zone and Attari fault. There is also a shortening rate of ~2 mm/yr between the northern edge of Central Iran and the Eastern Alborz which could be related to the salt tectonic within the Great Kavir fault. The improved velocity field shows a right-lateral strike-slip motion of ~1 mm/yr across the Indes and Kushk-Nosrat faults. Despite the observed large seismic activity and a geological slip rate of 2 mm/yr for the eastern part of the Mosha fault, both strike-slip and compressional slip rates along the Mosha fault are less than 1 mm/yr. Within a radius of ~50 km from the center of Tehran metropolitan area, there is no noticeable rate of strike-slip or compressional movement and the strain rate is around the error limit or less than 1 mm/yr. The low strain rate implies a very long earthquake return period for large earthquakes in Tehran metropolitan area. [ABSTRACT FROM AUTHOR]

The increasing magnitude of monetary and life losses caused by urban floods worldwide has sparked a deeper interest among researchers in comprehending these phenomena. Accurate modeling and forecasting of floods play a pivotal role in developing effective strategies for flood damage mitigation and management, thereby reducing associated hazards. A critical concern in this endeavor is optimizing the trade-off between computation time and accuracy when simulating real-time flood events. This paper aims to establish the superiority of the sub-grid approach in achieving accurate simulation results of real-time flood events within minimal computational time. By conducting simulations of one experimental test and two real-world flood events using the HEC-RAS flow simulation model, we demonstrate that the sub-grid approach significantly reduces computation time by approximately 90% while faithfully capturing the dynamics of urban flood. In contrast, the non-sub-grid approach often over-predicts flow dynamics in urban areas and fails to effectively trace building footprints, resulting in unrealistic flow patterns and under or overstating the hazard maps. In a nutshell, the sub-grid hydraulic modeling approach enables better hazard analysis and mapping. The outcomes of this research provide valuable guidance to modelers and authorities, suggesting the adoption of the sub-grid approach for accurate and reliable real-time urban flood modeling, inundation forecasting, and hazard zoning in the context of urban flood hazard analysis. [ABSTRACT FROM AUTHOR]

Background: Prevention and early intervention of alcohol use disorder (AUD) is a public health priority, yet there are gaps in our understanding of how AUD emerges, which symptoms of AUD come first, and whether there are modifiable risk factors that forecast the development of the disorder. This study investigated potential early‐warning‐sign symptoms for the development of AUD. Methods: Data were from the RADAR study, a prospective cohort study of contemporary emerging adults across Australia (n = 565, mean age = 18.9, range = 18–21 at baseline, 48% female). Participants were interviewed five times across a 2.5‐year period. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM‐5) AUD criteria and diagnoses were assessed by clinical psychologists using the Structured Clinical Interview for DSM‐IV (SCID‐IV), modified to cover DSM‐5 criteria. Hazard analyses modeled the time from first alcoholic drink to the emergence of any AUD criteria and determined which first‐emergent AUD criteria were associated with a faster transition to disorder. Results: By the final time point, 54.8% of the sample had experienced at least one DSM‐5 AUD criterion and 26.1% met criteria for DSM‐5 AUD. The median time from first AUD criterion to a diagnosis of AUD was 4 years. Social problems from drinking (hazard ratio [HR] = 3.24, CI95 = 2.14, 4.92, p < 0.001), major role (HR = 2.53, CI95 = 1.58, 4.06, p < 0.001), and drinking larger amounts/for longer than intended (HR = 2.04, CI95 = 1.20, 3.46, p = 0.008) were first‐onset criteria associated with a faster transition to AUD. Conclusion: In the context of a prospective general population cohort study of the temporal development of AUD, alcohol‐related social problems, major role problems, and using more or for longer than intended are key risk factors that may be targeted for early intervention. [ABSTRACT FROM AUTHOR]

The country of Iran is part of the Alpine-Himalayan orogeny belt and is divided into different tectonic seismic states. Based on the classification of tectonic seismic states, Kerman province is located in the central Iran zone. The city of Hojedk is also located in the seismic state of central Iran, which is in a relatively high-risk zone in terms of seismicity and has experienced large earthquake events. In this research, for the first time, the city of Hojedk has been comprehensively investigated in terms of seismic conditions to facilitate the decision-making process for preventive measures, especially the improvement and strengthening of buildings against earthquakes. In this research, data from the catalog of earthquakes of the University of Tehran's Geophysics Institute were used to analyze the earthquake hazard, and geological maps of the Geological Organization were used in the geological surveys and faults in the area. Earthquake hazard analysis in Hojedk City has been done in a probabilistic way. In this method, seismic springs have been identified and determined for the area. The information on the faults in the region and the earthquake catalog have been used for this research stage. At this stage, seismic springs are considered regionally. After determining the seismic springs, the seismic parameters were calculated and then the strong ground motion was estimated and finally, the earthquake hazard analysis was done by combining the uncertainties in the earthquake position and the magnitude of the strong ground motion parameters in the specific time period. The city of Hojedk is placed in a very high seismic risk zone. Major earthquakes have occurred in the area of this city. Due to geology, this city is located on the Shemshak, Badamo, Hojedk and Shotori formations. There are many faults in the city of Hojedk, the closest fault to this city is the Deh Zana fault. The length of this fault is 18 km and its mechanism is thrust. The area of Hojedk City is an active area in terms of the occurrence of earthquakes. In this area, 6 historical earthquakes have occurred, the largest of which occurred with a magnitude of 6.1 in 1897. Historical earthquakes are in the large range and the smallest of them has a magnitude of 5.5. 4141 earthquakes occurred in the range from 1900 to 2023, of which 4 earthquakes occurred in this time range with a magnitude of 6 or more. 8 seismic springs of regional type were identified based on the trend of faulting and accumulation of earthquakes in Hojedk city. Research on aftershocks has shown that the number of events with a magnitude of about 3.4 to 5 is the highest, and the depth of most earthquake events is between 10 and 20 kilometers. The seismic coefficients a, and b calculated in this range are 0.86 and 3.88, respectively. The seismicity rate in the studied area for magnitude 4 and greater is 1.47. The hazard analysis of the area for the return period of 475 years shows that the maximum acceleration of the bedrock in the area is 0.45, which is in the area of Hojedk city is 0.25-0.35. The acceleration map shows that the highest accelerations are in the northwest-southeast trend, which is in good agreement with the trend of the faults. Therefore, in terms of construction laws, the studied area is of special importance, so by having soil boreholes in the area, seismic micro zoning can be done and its results can be used to improve construction and select and use materials. [ABSTRACT FROM AUTHOR]

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This study aims to utilize the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique and Google Earth optical remote sensing images to analyze the area within 20 km around the epicenter of a M 3.9, earthquake that occurred in Tanchang County, Gansu Province, on December 28, 2020. The objective is to identify potential earthquake-induced landslides, assess their scale, and determine their impact range. The study results reveal the successful identification of two potential landslides in the 20 km radius around the epicenter. Through time-series deformation analysis, it was observed that these potential landslides were significantly influenced by both the earthquake and rainfall. Further estimation of these potential landslides indicates maximum depths of 7.4 m and 14.1 m for the failure surfaces, with volumes of 9.02 x 104 m³ and 25.5 x 104 m³, respectively. Finally, based on the simulation analysis of Massflow software, the maximum thickness of soil accumulation in the final accumulation area after sliding of the potential landslide in Shangyaai is 12 m, the area of the final accumulation area is 1.75 x 104 m², and the farthest movement distance is 1124 m. The maximum thickness of soil accumulation in the final accumulation area after sliding of the potential landslide in Wangshancun is 8 m, the area of the final accumulation area is 7.89 x 104 m², and the farthest movement distance is 742 m. [ABSTRACT FROM AUTHOR]

Agrometeorological hazards significantly impact agricultural production and rural economic development. The interdisciplinary nature of studying these hazards poses challenges such as poor data interoperability in research. This paper proposes a method for analyzing agrometeorological hazards using knowledge graphs to understand occurrence patterns and devise response strategies. The study involves classifying agricultural and meteorological knowledge and designing a hazard entity model based on the characteristics and influencing factors of agrometeorological hazards. Data mining and extraction techniques are used to extract relevant information from multiple sources, and a knowledge graph for knowledge fusion and storage is built. The retrieval and inference capabilities of the knowledge graphs are used to intelligently analyze agrometeorological hazards. Results indicate that analyzing agrometeorological hazards using knowledge graphs is an innovative method that offers new perspectives and ideas for agricultural meteorological hazard research, thereby promoting the sustainable development of agricultural production and the stable growth of the rural economy. [ABSTRACT FROM AUTHOR]

This study investigates the effect of extreme storms on the safety of flood protection dams within complex schemes. A modeling methodology is developed using HEC-RAS 2D and presented on an illustrative case, where nine scenarios are simulated. The impact of climatic shifts on extreme storms and dams’ safety is highlighted. The results showed that, despite multi-reservoir systems can be efficient in flood protection against their design storms, they can cause catastrophic damage when subjected to extreme events that have become evident nowadays due to climatic shifts. This is attributed to the successive failure of the water storage structures in a progressive (“domino-like”) manner. The consequences of such breaches can significantly multiply the hazards. These findings can be linked to storm Daniel that occurred at Wadi Derna in Libya and caused two successive dam breaches, leaving a tragedy. The proposed modeling methodology can be useful for designers in evaluating complex scenarios.

Consumer preferences, safety, and sustainability aspects of conventional cosmetic ingredients have contributed to an increase in the demand for natural cosmetic ingredients and products. Naturally derived active cosmetic agents and excipients may come into contact with various naturally occurring and synthetic contaminants throughout the supply chain, and substantiating their safety is essential. This review examines the safety and legislative requirements applicable to natural cosmetic ingredients in the European Union (EU). Cosmetic safety requirements include technical data based on the ingredient profile, presence of hazards and the risks associated with the intended conditions of use. The hazard analysis includes screening for microbial contaminants such as aerobic mesophilic bacteria, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida albicans; chemical contaminants such as lead, cadmium, arsenic, and mercury; and naturally occurring toxins, such as allergens. The toxicological assessment considers both local effects (such as skin sensitisation, eye/skin irritation, and photo-induced effects) and systemic effects (including acute dermal toxicity, sub-acute and sub-chronic toxicity, mutagenicity and carcinogenicity, reproductive toxicity, and toxicokinetics). The EU legislative requirements prohibit the use of animal-based tests for the toxicological evaluation of cosmetic ingredients, paving the way for alternatives termed as New Approach Methodologies (NAMs). The validation of NAMs is critical for their wider usage, and despite advancements, few have been validated, particularly for systemic toxicity testing. The use of NAMs in evaluating the safety of complex natural cosmetic ingredients is further examined. [ABSTRACT FROM AUTHOR]

Rapid urbanization in developing countries poses challenges such as rising crime rates and resource scarcity. Unmanned Aircraft Systems (UAS) offer a promising solution to enhance public safety, but their integration requires addressing specific challenges. This study employs the Systems-Theoretic Accident Model and Processes (STAMP) and System-Theoretic Process Analysis (STPA) methodologies to identify potential hazards and requirements for integrating UAS into public safety systems in urban environments. The research objectives include identifying hazards and challenges, developing safety requirements and guidelines, and proposing strategies for efficient infrastructure investment. The proposed framework, based on STAMP/STPA, includes additional steps to consider early-stage systems and maintain stakeholder traceability. A risk matrix approach is utilized to prioritize risk mitigation measures for cost-effectiveness. The findings of this study provide valuable insights for policymakers and urban planners in developing countries seeking to harness the potential of UAS technology for enhancing public safety while addressing the unique challenges posed by rapid urbanization. [ABSTRACT FROM AUTHOR]

In the last ten years, the development of automated agricultural machinery has seen noteworthy advancements. Nevertheless, the successful commercialization of these technologies depends critically on their ability to operate safely. This study evaluated the advantages and limitations of current risk assessment and hazard analysis methods currently used to ensure the safety of autonomous agricultural machines. An online survey containing 18 questions was distributed to 711 participants identified as potential individuals who are currently working or have worked on autonomous agricultural machines to determine the type and frequency of risk assessment and hazard analysis methods applied on autonomous agricultural machines, examine the advantages and limitations of each method, and investigate the perceived effectiveness of each method. Frequency analysis was used to determine the most and least utilized risk assessment and hazard analysis methods. The advantages and limitations of each risk assessment and hazard analysis approach were compared. Descriptive statistics (counts, means, medians, percent) and frequency analysis of the variables were used. The three main types of risk assessment and hazard analysis techniques applied to autonomous agricultural machines. The methods are (a) Informal Group Analysis (e.g., Brainstorming), (b) Hazard Analysis and Risk Assessment (HARA), and (c) Failure Mode and Effects Analysis (FMEA). Replicability is perceived as the main advantage of FMEA and HARA, while cost-effectiveness is the main advantage of Informal Group Analysis. The need to have pre-existing data of the autonomous agricultural machine at hand to be able to perform risk assessment and subjectivity are the main limitations of FMEA, HARA, and Informal Group Analysis dealing with novel and revolutionary autonomous agricultural machines. Industry experts do not believe that the risk assessment and hazard analysis procedures now used are reliable and efficient enough to guarantee the safety of autonomous agricultural tractors. This study reveals important information about the current state of risk assessment and hazard analysis methods in the context of autonomous agricultural machinery. This knowledge can inform future research, policy development, and industry practices to ensure the safety of autonomous agricultural machines. [ABSTRACT FROM AUTHOR]

Experience-based methods like reinforcement learning (RL) are often deemed less suitable for the safety field due to concerns about potential safety issues. To bridge this gap, we introduce STPA-RL, a methodology that integrates RL with System-Theoretic Process Analysis (STPA). STPA is a safety analysis technique that identifies causative factors leading to unsafe control actions and system hazards through loss scenarios. In the context of STPA-RL, we formalize the Markov Decision Process based on STPA analysis results to incorporate control algorithms into the system environment. The agent learns safe actions through reward-based learning, tracking potential hazard paths to validate system safety. Specifically, by analyzing various loss scenarios related to the Platform Screen Door, we assess the applicability of the proposed approach by evaluating hazard trajectory graphs and hazard frequencies in the system. This paper streamlines the RL process for loss scenario identification through STPA, contributing to self-guided loss scenarios and diverse system modeling. Additionally, it offers effective simulations for proactive development to enhance system safety and provide practical assistance in the safety field. [ABSTRACT FROM AUTHOR]

While urban underground space is being built and developed at a high speed, urban flooding is also occurring gradually and frequently. Urban water, in many disasters, has intruded into underground spaces, such as subway stations, often leading to serious casualties, in which it is crucial for people to be able to escape from the staircases. In order to enable and guide the escape of people in underground floods, a staircase model with multiple rest platforms, applicable to common entrance and exit staircase forms, was constructed. The realizable k-ε turbulence model, coupled with a volume of fluid (VOF) method, was used to simulate and analyze the flow patterns when floods of various heights intrude into the structure. The effects of rest platform settings on the ejection phenomena and flow velocity changes in flood flows were summarized. The change rule of flood flow velocity on the stairs under different flood heights and stair heights was summarized, and a linear relationship between the peak flood flow velocity and the location of the peak flow velocity point on each flight of stairs was derived. Combined with the formula of the critical conditions for people to escape upwards in the flood, the proposed escape conditions for staircases with multiple rest platforms were proposed, which provide a basis for guiding the evacuation of people in times of disaster. [ABSTRACT FROM AUTHOR]

In the process of deep cooling and liquefaction of low-concentration (concentration

Abstract Introduction The preparedness of Emergency Medical Services (EMS) plays a crucial role in managing health disaster risks. This study was conducted to assess the disaster preparedness of EMS facilities in Iran, using a nationally reliable tool. Methods A cross-sectional study was conducted in May 2021 to evaluate the disaster preparedness of EMS facilities in Iran using a national standard tool. The census sampling approach was utilized to select the samples, and descriptive statistics, as well as analytical statistics like the independent t-test and Pearson’s correlation test, were used to analyze the data using SPSS-18 software. Results The findings of this study revealed that the majority of EMS facilities in Iran possess a moderate level of preparedness in dealing with disasters. Also, the results indicate that EMS facilities have an average level of preparedness against disasters in all dimensions except for “coordination and cooperation” and “surge capacity”. Conclusion According to this study, the majority of EMS facilities in Iran are exposed to different disasters. Furthermore, the findings indicate that while EMS facilities are generally prepared to respond to disasters at an average level, there are some important preparedness gaps in dimensions like response capacities, coordination, and cooperation. Thus, specific strategies, standards, and procedures must be developed and disseminated by the National Medical Emergency Organization.

This paper provides a bibliometric analysis and literature review to explore the current application landscape of the Systems Theoretic Accident Model and Processes (STAMP) principles and techniques in the railway transportation domain. Following PRISMA guidelines, we systematically reviewed 118 research documents retrieved from prominent bibliographic databases, covering the period from 2008 to September 2023. The investigated research works, involving STAMP, mainly focus on two topics: 1) applications of STAMP to railway accident modeling/analysis and 2) applications of Systems Theoretic Process Analysis (STPA) to railway hazard analysis and risk assessment. In this paper, while the STAMP related studies are discussed with respect to the considered railway accidents, the studies related to STPA analysis are discussed with respect to three subjects, STPA applications, STPA comparative studies, and STPA extensions and improvements. Ultimately, this review aims to provide academic researchers and railway practitioners with a comprehensive exploration and analysis of the current state of knowledge on STAMP within the railway sector.

Shared kitchens, where users share kitchen space, are becoming popular worldwide due to the economic cost savings of startup businesses. This study conducted monitoring of microbial and chemical hazards from prepared foods and the environment of shared kitchen facilities, surveyed shared kitchen operators, and compared shared kitchen regulations between Korea and other countries. The monitoring results indicate that the hygiene status of the facilities and the microbial and chemical hazards in the prepared foods were all within the standard specifications, showing significantly lower levels compared to regular restaurants (p < 0.05). In particular, concurrent-use and time-division types of open shared kitchens showed significantly lower levels of both hazards than separated-individual kitchens. Survey results of hygiene inspection also confirmed better hygiene management in concurrent-use and time-division types of open shared kitchens in Korea. However, more frequent cleaning and disinfection, hygiene inspections, and training are high economic burdens in the operation of shared kitchens compared to regular restaurants. Moreover, mandatory insurance subscriptions, the operator’s responsibility in hygiene-related incidents, and high operational costs collectively challenge shared kitchens’ competitiveness in the food service market. Critical reassessments of regulations utilizing the benefits of shared kitchens are needed to promote a safe dining culture and the growth of shared kitchen startup businesses. [ABSTRACT FROM AUTHOR]

Background: Weather and climate disasters are responsible for over 13 000 US deaths, worsened morbidity, and $1.7 trillion in additional costs over the last 40 years with profound racial disparities. Objectives: This project empirically generated items for a novel survey instrument of household hazard vulnerability with initial construct validation while addressing racial bias in the data collection process. Methods: Cognitive interviews facilitated understanding regarding the performance of drafted survey questions with transdisciplinary expert panelists from diverse US regions on unique hazard/disaster/event items. To prevent representation bias in data collection, those with Black and/or African American racial, biracial, or multiracial identities were over-sampled. Interview video recordings were qualitatively analyzed using thematic and pattern coding. Results: A cognitive process mapped to themes of disaster characteristics, resources, individual life facets, and felt effects was revealed. We identified 379 unique instances of linked terms as synonyms, co-occurring, compounding, or cascading events. Potential for racial bias in data collection was elucidated. Analysis of radiation exposure, trauma, and criminal acts of intent items revealed participants may not interpret survey items with these terms as intended. Conclusion: Potential for racial bias exists relative to water dam failure, evacuation, external flood, suspicious packages/substances, and transportation failure. Hazard terms that were not interpreted as intended require further revision in the validation process of individual or household disaster vulnerability assessments. Several commonalities in the cognitive process and mapping of disaster terms may be utilized in disaster and climate change research aimed at the individual and household unit of analysis. [ABSTRACT FROM AUTHOR]

The correct estimation of seismic hazards is a touchstone of seismic risk assessments. However, there is no quantitative or standard methodology to include the impacts of geological (i.e., seismo-tectonic) features of active faults or fault zones, and current classification schemes are not useful in hazard evaluations. Therefore, an attempt has been made to develop a methodology that integrates seismo-tectonic parameters of active faults to better inform urban and regional planning decisions. Fault rating system (FRS) provides a comparative review of faults/fault zones using a rating-based approach. In this approach, seven seismo-tectonic parameters are used to classify the fault/fault zone. Each of the seven parameters is assigned a value corresponding to the seismo-tectonic characteristics. The sum of the seven seismo-tectonic parameters is the fault index (FI) value, which lies in the range 0–100. A total of 64 important faults/fault zones were statistically analyzed to determine the best correlations with FI and moment magnitude (Mw) and peak ground acceleration (PGA). It was found that the FI values provide strong correlations with maximum Mw and PGA. It is proposed urban and regional planners use FRS to ensure a consistent approach in characterizing key aspects of active faults in earthquake-prone regions and in estimating ground motion parameters. [ABSTRACT FROM AUTHOR]

Safety-critical systems, such as the railway signal system, are subject to potentially high costs from failures, including loss of life and property damage. The use of new technology, including communication-based train control (CBTC) systems with software and computers, has changed the types of accidents that occur. Software-related issues and dysfunctional interactions between system components controlled by the software are increasingly the cause of incidents. Developing a “safe” safety-critical system requires accurate and complete safety requirements, which are the foundation of system development. Traditional hazard analysis techniques are insufficient for identifying the causes of accidents in modern railway signaling systems. Systems-Theoretic Process Analysis (STPA) is a powerful new hazard analysis method designed to address these limitations. Building upon this foundation, a hierarchical approach to safety requirement development has been further developed. This approach combines STPA analysis with a hierarchical modeling approach to establish traceability links from safety requirements to specific architectures, refine and allocate system-level safety requirements to relevant subsystems, and abstract safety requirements at higher hierarchical levels to enable easy changes to lower-level implementations. This paper employs the aforementioned methodology within the context of the CBTC system, thereby enhancing risk management and hazard analysis, enabling early insights, and facilitating the generation of safety requirements of CBTC System.

Abstract A comprehensive evaluation method is proposed to analyze dust pollution generated in the production process of mines. The method employs an optimized image-processing and deep learning framework to characterize the gray and fractal features in dust images. The research reveals both linear and logarithmic correlations between the gray features, fractal dimension, and dust mass, while employing Chauvenel criteria and arithmetic averaging to minimize data discreteness. An integrated hazardous index is developed, including a logarithmic correlation between the index and dust mass, and a four-category dataset is subsequently prepared for the deep learning framework. Based on the range of the hazardous index, the dust images are divided into four categories. Subsequently, a dust risk classification system is established using the deep learning model, which exhibits a high degree of performance after the training process. Notably, the model achieves a testing accuracy of 95.3%, indicating its effectiveness in classifying different levels of dust pollution, and the precision, recall, and F1-score of the system confirm its reliability in analyzing dust pollution. Overall, the proposed method provides a reliable and efficient way to monitor and analyze dust pollution in mines.

System Theoretic Process Analysis (STPA) is a method for analyzing hazards caused by interactions between components of an industrial product. STPA is applied in the upper stream stages of industrial product development, STPA detects hazards while referring to the whole configuration of the industrial product. Therefore, STPA generally does not deal with detailed information about the industrial product. Since the information on the industrial product is insufficient, it is difficult to clarify the factors of hazards, the occurrence order of factors, and the conditions that occur the hazard by STPA. Therefore, the following methods were added to the conventional STPA; the method of describing the components of industrial products in hierarchical detail, the method of clearly defining the behaviour of each component, and the method of tracking the structured CSD to clarify the causes of the hazard. By adding those methods, it became possible to conduct a hazard analysis of the industrial product in detail. As a result of applying the proposed method to the existing railroad crossing control system, it was confirmed that the proposed method could detect more factors of hazards and create adequate scenarios from the occurrence of hazard causes to the occurrence of the hazard.

Agrometeorological hazards significantly impact agricultural production and rural economic development. The interdisciplinary nature of studying these hazards poses challenges such as poor data interoperability in research. This paper proposes a method for analyzing agrometeorological hazards using knowledge graphs to understand occurrence patterns and devise response strategies. The study involves classifying agricultural and meteorological knowledge and designing a hazard entity model based on the characteristics and influencing factors of agrometeorological hazards. Data mining and extraction techniques are used to extract relevant information from multiple sources, and a knowledge graph for knowledge fusion and storage is built. The retrieval and inference capabilities of the knowledge graphs are used to intelligently analyze agrometeorological hazards. Results indicate that analyzing agrometeorological hazards using knowledge graphs is an innovative method that offers new perspectives and ideas for agricultural meteorological hazard research, thereby promoting the sustainable development of agricultural production and the stable growth of the rural economy.

This paper presents the results of a simulation model regarding the productivity and safety working space for construction workers through the floors of a building using swarm intelligence (SI), a field of artificial intelligence (AI), and specifically using artificial bee colony (ABC) optimization. After designing the algorithm used to build the simulation model, the simulation was used in an actual building project by comparing the travel times of workers conventionally transporting material with another group working on routes optimized by the algorithm. Thus, the proposed algorithm provides routes combining shorter travel times and correct distances between workers when transporting materials in a construction site, handling the interference between crews. After validating the algorithm on-site, no statistically significant differences were found between the travel times of workers and the times delivered by the algorithm. Additionally, the travel times using the routes obtained through the algorithm were significantly lower than those made by workers who moved freely without a predefined route. In summary, the algorithm proposed may help construction practitioners maintain safe movements that respond to hazard contexts imposed by any restriction that demands a safety distance.

Abstract Landslides are an example of severe natural disasters that occur worldwide and generate many harmful effects that can affect the stability and development of society. A better-quality susceptibility mapping technique for the landslide risk is crucial for mitigating landslides. However, the use of assemblages of multivariate statistical methods is still uncommon in Indonesia, particularly in the Kepahiang Regency of Bengkulu Province. Therefore, the objective of this study was to provide an improved framework for creating landslide susceptibility map (LSM) using multivariate statistical methods, i.e., the analytical hierarchy process (AHP) method, the simple additive weighting (SAW) method and the frequency ratio (FR) method. In this study, we established a landslide inventory considering 15 causative factors using the area under the curve (AUC) validation method and another evaluation technique. The performance of each causative factor was evaluated using multicollinearity and Pearson correlation analysis with regression-based ranking. The LSM results showed that the most susceptible areas were located in the districts of Kabawetan, Kepahiang, and Tebat Karai. The high landslide risk in these areas could be attributed to the slope conditions in mountainous regions, which are characterized by high annual rainfall and seismic activity. The AUC training values of the AHP, SAW, and FR methods were 0.866, 0.838, and 0.812, respectively. Then, on the validation dataset, the AHP method yielded the highest AUC value (0.863), followed by the SAW (0.833) and FR (0.807) methods. Moreover, the AHP method provided a higher accuracy value, which suggests that the AHP method is more suitable than the other methods. Therefore, our research indicated that all algorithm methods generate a positive impact and greatly improve landslide susceptibility evaluation, especially for the preparation of landslide damage assessments in this study area. Finally, the method proposed in this study could improve the feasibility of LSM and provide support for Indonesian government decision-makers in arranging hazard mitigation measures in the Kepahiang Regency, Indonesia.

A comprehensive evaluation method is proposed to analyze dust pollution generated in the production process of mines. The method employs an optimized image-processing and deep learning framework to characterize the gray and fractal features in dust images. The research reveals both linear and logarithmic correlations between the gray features, fractal dimension, and dust mass, while employing Chauvenel criteria and arithmetic averaging to minimize data discreteness. An integrated hazardous index is developed, including a logarithmic correlation between the index and dust mass, and a four-category dataset is subsequently prepared for the deep learning framework. Based on the range of the hazardous index, the dust images are divided into four categories. Subsequently, a dust risk classification system is established using the deep learning model, which exhibits a high degree of performance after the training process. Notably, the model achieves a testing accuracy of 95.3%, indicating its effectiveness in classifying different levels of dust pollution, and the precision, recall, and F1-score of the system confirm its reliability in analyzing dust pollution. Overall, the proposed method provides a reliable and efficient way to monitor and analyze dust pollution in mines. [ABSTRACT FROM AUTHOR]

Transportation corridors constructed using through- and side-cuts are susceptible to hazardous slope failures, potentially causing infrastructure damage, operational suspensions and loss of life. To monitor the stability of known geohazards at the local scale, geotechnical investigation of each slope is typically performed to calculate a factor of safety. In many corridors, however, this method is labour-intensive due to the quantity of geohazards and statistical methods are instead used to identify hazardous sections. This paper introduces a new slope failure hazard assessment technique, utilising susceptibility mapping of geospatial information and computer vision-based analysis of right-of-way videos recorded by railroad track inspection vehicles, applied to a section of railroad track near Harrisburg, Pennsylvania. Combining these results, an enhanced relative hazard assessment algorithm was formulated. Using the developed framework, geohazards of primary concern were determined which should be prioritised for future geotechnical investigation and remediation efforts. [ABSTRACT FROM AUTHOR]

Climate change is causing glaciers in the Himalayas to recede and shrink. The changing climate is the primary trigger of the expansion of glacial lakes that increases the possibilities of outburst floods (GLOFs) and leads to quantifiable losses such as mortality and damage to populations and infrastructure downstream. Therefore, determining the hazard related to the glacier lakes of the Himalayan region is essential. We have developed an approach named SHIVEK, consisting of the SWIR band thresholding technique and hazard analysis to estimate the possible downstream risk along the GLOF flow path. We examined the spatiotemporal expansion of Imja Lake from 1997 to 2020 using Landsat 5, 7, and 8 data. We employed an automated form of the previously described method based on SWIR band thresholding. The study creates yearly composites from June to September using pre-processed Landsat imageries using a cloud-based platform Google Earth Engine. Our results show a continuous expansion in the geographical area of Imja Lake from 0.81 to 1.56 km2 in 23 years between 1997 and 2020, averaging nearly 0.032 km2 per year. Also, the lake's area between 2012 and 2020 expanded by 0.26 km2. The overall accuracy of 88.96 ± 6.93% has been achieved for spatiotemporal maps of Imja Lake and intensified confidence in the approach. This study estimates a total of 645 buildings and four bridges that can be impacted due to the outburst of Imja Lake. [ABSTRACT FROM AUTHOR]

Intermediate-frequency debris flows has the characteristics of high danger and long outbreak period. Human activities can trigger its occurrence and aggravate its disaster severity. When the channel cannot meet the capacity for drainage and water transport, it will cause blockage and endanger the safety of both sides of the strait and even the main river channel. Due to the lack of analysis on the danger of intermediate-frequency debris flows, this paper takes the intermediate-frequency debris flow in Hada Gully, Yunnan Province as an example to explore its characteristics and the danger of its recurrence and channel blockage caused by debris flows and proposes prevention and control suggestions. The results show that the debris flow has a density of 1.62 t/m3, a flow velocity of 4.794 m/s at the outlet of the channel, a peak flow rate of 54.43 m3/s at the channel outlet and a total discharge of 11072.03 m3 for a single occurrence based on the 10% burst frequency. A culvert was constructed in the downstream channel, with a flow capacity of 16.5 m3/s, which is less than the flow rate of a debris flow once in 20 years. Once a large debris flow occurs, there is a risk of blockage. The study found that the hazard level of intermediate-frequency debris flows in Hada gully is highly dangerous, and the history of blockage indicates the possibility of its recurrence and the risk of debris flow blocking the Lapu River.

Consumer preferences, safety, and sustainability aspects of conventional cosmetic ingredients have contributed to an increase in the demand for natural cosmetic ingredients and products. Naturally derived active cosmetic agents and excipients may come into contact with various naturally occurring and synthetic contaminants throughout the supply chain, and substantiating their safety is essential. This review examines the safety and legislative requirements applicable to natural cosmetic ingredients in the European Union (EU). Cosmetic safety requirements include technical data based on the ingredient profile, presence of hazards and the risks associated with the intended conditions of use. The hazard analysis includes screening for microbial contaminants such as aerobic mesophilic bacteria, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida albicans; chemical contaminants such as lead, cadmium, arsenic, and mercury; and naturally occurring toxins, such as allergens. The toxicological assessment considers both local effects (such as skin sensitisation, eye/skin irritation, and photo-induced effects) and systemic effects (including acute dermal toxicity, sub-acute and sub-chronic toxicity, mutagenicity and carcinogenicity, reproductive toxicity, and toxicokinetics). The EU legislative requirements prohibit the use of animal-based tests for the toxicological evaluation of cosmetic ingredients, paving the way for alternatives termed as New Approach Methodologies (NAMs). The validation of NAMs is critical for their wider usage, and despite advancements, few have been validated, particularly for systemic toxicity testing. The use of NAMs in evaluating the safety of complex natural cosmetic ingredients is further examined.

Rapid urbanization in developing countries poses challenges such as rising crime rates and resource scarcity. Unmanned Aircraft Systems (UAS) offer a promising solution to enhance public safety, but their integration requires addressing specific challenges. This study employs the Systems-Theoretic Accident Model and Processes (STAMP) and System-Theoretic Process Analysis (STPA) methodologies to identify potential hazards and requirements for integrating UAS into public safety systems in urban environments. The research objectives include identifying hazards and challenges, developing safety requirements and guidelines, and proposing strategies for efficient infrastructure investment. The proposed framework, based on STAMP/STPA, includes additional steps to consider early-stage systems and maintain stakeholder traceability. A risk matrix approach is utilized to prioritize risk mitigation measures for cost-effectiveness. The findings of this study provide valuable insights for policymakers and urban planners in developing countries seeking to harness the potential of UAS technology for enhancing public safety while addressing the unique challenges posed by rapid urbanization.

Background: In the field of digital circuit design, assuring the safety and reliability of logic circuits is critical. Unexpected behaviors or performance abnormalities represent possible hazards to these circuits. Objective: The aim of hazard analysis in logic circuits is to anticipate potential circuitry difficulties and correct them during the design and testing phases. This proactive strategy aims to eliminate any hazards that might jeopardize the circuit's dependability or safety. Methods: The method is used to examine the design and functioning of a logic circuit, concentrating on its inputs, outputs, inherent logic, and time. This extensive study assists in anticipating any possible problems that the circuit may offer. Results: Following the hazard analysis, the insights gained are used to enhance the circuit design, implement safety measures, or conduct more testing. This guarantees that the circuit satisfies the appropriate levels of safety and reliability. Conclusion: Conducting a comprehensive hazard analysis is an essential step in creating safe and dependable logic circuits. Potential dangers may be discovered and minimized by meticulously evaluating a circuit's design and functioning, assuring smooth operation.

For decades, the Buriganga River in Dhaka, Bangladesh, has suffered from persistent pollution, leading to heavy metal contamination in fish samples that poses significant risks to human health. This study conducted an analysis of the whole bodies of various fish species, including Heteropnuestes fossilis, Channa punctatus, Notopterus notopterus Channa striata and Colisa fasciata to examine the concentrations of Chromium, Manganese, Nickel, Copper, Zinc, Arsenic, Cadmium, Barium, and Lead. The analysis was performed using inductively coupled plasma mass spectrometry, revealing notable concentrations of Pb, Ni, Cd, and Zn, with average levels of 6.85, 156.77, 0.41, and 3.37 mg/kg, respectively.Assessment of target hazard quotients for Pb, against recommended benchmark doses of observable effects, indicated levels 2 to 6 times higher than the recommended safety thresholds. The cumulative totals of target hazard quotients across multiple specimens exceeded 2 and, in some cases, reached up to 7, surpassing the safety cutoff of 1. The risk of cancer from Ni and Pb was calculated to be 1 in 10,000 on average for each, classifying it as a moderate risk. Quantitative analysis revealed that heavy metal concentrations of Pb, Ni, Cd, and Zn in most fish samples exceeded reference safety values.Simultaneously, hazard analysis identified critical concerns regarding Pb content in one sample, and cumulative toxin loads in almost every sample were deemed unsafe for regular consumption. In addition to quantitative assessments, a qualitative survey employed observation techniques, focus group discussions, and key informant interviews to investigate consumption behaviors and viewpoints on fish contamination. The results revealed that consumers generally held an enthusiastic attitude towards consuming these fish and were largely unaware of the associated health hazards.

Landslides are an example of severe natural disasters that occur worldwide and generate many harmful effects that can affect the stability and development of society. A better-quality susceptibility mapping technique for the landslide risk is crucial for mitigating landslides. However, the use of assemblages of multivariate statistical methods is still uncommon in Indonesia, particularly in the Kepahiang Regency of Bengkulu Province. Therefore, the objective of this study was to provide an improved framework for creating landslide susceptibility map (LSM) using multivariate statistical methods, i.e., the analytical hierarchy process (AHP) method, the simple additive weighting (SAW) method and the frequency ratio (FR) method. In this study, we established a landslide inventory considering 15 causative factors using the area under the curve (AUC) validation method and another evaluation technique. The performance of each causative factor was evaluated using multicollinearity and Pearson correlation analysis with regression-based ranking. The LSM results showed that the most susceptible areas were located in the districts of Kabawetan, Kepahiang, and Tebat Karai. The high landslide risk in these areas could be attributed to the slope conditions in mountainous regions, which are characterized by high annual rainfall and seismic activity. The AUC training values of the AHP, SAW, and FR methods were 0.866, 0.838, and 0.812, respectively. Then, on the validation dataset, the AHP method yielded the highest AUC value (0.863), followed by the SAW (0.833) and FR (0.807) methods. Moreover, the AHP method provided a higher accuracy value, which suggests that the AHP method is more suitable than the other methods. Therefore, our research indicated that all algorithm methods generate a positive impact and greatly improve landslide susceptibility evaluation, especially for the preparation of landslide damage assessments in this study area. Finally, the method proposed in this study could improve the feasibility of LSM and provide support for Indonesian government decision-makers in arranging hazard mitigation measures in the Kepahiang Regency, Indonesia. Key points: In this paper, we present a framework for assembling multivariate statistical methods and developing landslide susceptibility mapping of Kepahiang, Bengkulu Province, Indonesia. The analytical hierarchy process provides the highest landslide susceptibility mapping accuracy and the lowest uncertainties in the study region. Slope, rainfall, and peak ground acceleration are the most essential spatial determinants of the changes in Kepahiang, Bengkulu Province, Indonesia. [ABSTRACT FROM AUTHOR]

This research aimed to investigate the levels of heavy metals (lead, cadmium, inorganic arsenic, and aluminium) and nitrate contaminants in pickle beverages sold in the Turkey market produced from various fruits and vegetables. In addition, carcinogenic and noncarcinogenic risk assessments of exposure resulting from oral consumption of these beverages have also been made. The heavy metal concentrations in 22 pickle beverages were found to be in the range of 0.369 to 119.181 for Al, 0.136 to 6.561 for iAs, 0.020 to 1.326 for Cd, and 0.118 to 3.632 µg/L for Pb, while the nitrate concentrations were < limits of detection (LOD) 117.320 mg/L. Hazard quotient values for heavy metals and nitrate are calculated as <1 in both genders and are safe regarding noncarcinogenic risks. Lifetime carcinogenic risk assessment indicated that some pickle beverages might pose a carcinogenic risk at grade A (>10−4) for iAs and grade B (10−6–10−4) for Pb in both genders. [ABSTRACT FROM AUTHOR]