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Food contact materials (FCMs) can contain hazardous chemicals that may have the potential to migrate into food and pose a health hazard for humans. Previous studies have mainly focused on plastic materials, while data on packaging materials made from paper and cardboard are limited. We used a panel of cell-based bioassays to investigate the presence and impact of bioactive chemicals on human relevant endpoints like oxidative stress, genotoxicity, inflammation, xenobiotic metabolism and endocrine system effects in extracts made from paper and cardboard. In total, 23 methanol extracts of commonly used paper and cardboard available on the Swedish market were extracted as a whole product using methanol to retrieve polar substances, and tested at concentrations 0.3–10 mg/mL and 0.2–6 mg/mL. At the highest concentration bioactivities were observed in a high proportion of the samples: oxidative stress (52%), genotoxicity (100%), xenobiotic metabolism (74%), antiandrogenic- (52%) and antioestrogenic receptor (39%). Packages of potential concern included cake/pastry boxes/mats, boxes for infant formula/skimmed milk, pizza boxes, pizza slice trays and bag of cookies. It should be noted that the extraction for packages like cake/pastry boxes can be considered exaggerated, as the exposure usually is shorter. It can be hypothesised that the observed responses may be explained by inks, coatings, contaminants and/or naturally occurring compounds within the material. To summarise, an effect-based approach enables hazard identification of chemicals within FCMs, which is a valuable tool for ensuring safe use of FCMs. [ABSTRACT FROM AUTHOR]

Food contact materials (FCM) are any type of item intended to come into contact with foods and thus represent a potential source for human exposure to chemicals. Regarding FCMs made of paper and board, information pertaining to their chemical constituents and the potential impacts on human health remains scarce, which hampers safety evaluation. We describe an effect-directed strategy to identify and characterize emerging chemicals in paper and board FCMs. Twenty FCMs were tested in eight reporter gene assays, including assays for the AR, ER, AhR, PPARγ, Nrf2 and p53, as well as mutagenicity. All FCMs exhibited activities in at least one assay. As proof-of-principle, FCM samples obtained from a sandwich wrapper and a pizza box were carried through a complete step-by-step multi-tiered approach. The pizza box exhibited ER activity, likely caused by the presence of bisphenol A, dibutyl phthalate, and benzylbutyl phthalate. The sandwich wrapper exhibited AR antagonism, likely caused by abietic acid and dehydroabietic acid. Migration studies confirmed that the active chemicals can transfer from FCMs to food simulants. In conclusion, we report an effect-directed strategy that can identify hazards posed by FCMs made from paper and board, including the identification of the chemical(s) responsible for the observed activity. [ABSTRACT FROM AUTHOR]

This paper intends to give an impression of new technologies and processes that are in development for application to achieve decarbonization, and about which less or no experience on associated hazards exists in the process industry. More or less an exception is hydrogen technology because its hazards are relatively known and there is industry experience in handling it safely, but problems will arise when it is produced, stored, and distributed on a large scale. So, when its use spreads to communities and it becomes as common as natural gas now, measures to control the risks will be needed. And even with hydrogen, surprise findings have been shown lately, e.g., its BLEVE behavior when in a liquified form stored in a vessel heated externally. Substitutes for hydrogen are not without hazard concern either. The paper will further consider the hazards of energy storage in batteries and the problems to get those hazards under control. Relatively much attention will be paid to the electrification of the process industry. Many new processes are being researched, which given green energy, will be beneficial to reduce greenhouse gases and enhance sustainability, but of which hazards are rather unknown. Therefore, as last chapter the developments with respect to the concept of hazard identification and scenario definition will be considered in quite detail. Improvements in that respect are also being possible due to the digitization of the industry and the availability of data and considering the entire life cycle, all facilitated by the data model standard ISO 15926 with the scope of integration of life-cycle data for process plants including oil and gas production facilities. Conclusion is that the new technologies and processes entail new process and personal hazards, and that much effort is going into renewal but safety analyses are scarce. Right in a period of process renewal, attention should be focused on possibilities to implement inherently safer design. [ABSTRACT FROM AUTHOR]

For mining engineering and geological engineering, the deformation and fracture of coal and rock are the essential causes of dynamic disasters. In this paper, the loading experimental system was established on gas-bearing coal, to study the internal relationship between the spatial distribution of EP and the development process of damaging localization on coal mass. The results indicated the temporal response of EP signal could reflect the stress state and damage degree of gas-bearing coal, showing the precursor feather when coal mass failed. Particularly, when the stress dropped suddenly, the EP signal has a sudden mutation, and the acoustic emission (AE) signal suffered the pulsed increase, while the crack grew and expanded rapidly. Furthermore, when local severe damage occurs inside the coal mass, there was abnormal EP spatial distribution with high-value or dense contours in these zones, where simultaneously AE rupture events frequently occurred, and cracks expanded and gathered. The characteristics of EP spatial distribution can reveal the development process of coal mass damaging localization. Meanwhile, the mentioned zones with abnormal EP distribution above are hazard sources inducing coal mass’s instability and failure. The study results provide the foundational research work of fine forecasting on coal and gas outburst disaster hazard. [ABSTRACT FROM AUTHOR]

The environmental perception system is the foundation of unmanned driving systems and also the fundamental guarantee of the safety and intelligence of unmanned vehicles. The obstacle hazard identification technology is the core of the environment perception system, and it is also the basic condition for the autonomous driving of unmanned vehicles. In view of the complexity of obstacle danger identification, this research paper designs an improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Algorithm for hazard recognition of obstacles in unmanned scenes through a systematic approach. First, it highlights the significance of morphological component analysis in identifying non-smooth regions within images where obstacles are likely to be present. Second, it introduces a novel approach for core point definition by identifying an optimal MinDensity value based on the curvature of the density distribution curve. Third, it addresses variations in density sequences through smoothing and normalization. Finally, it constructs an improved DBSCAN Algorithm for hazard recognition of obstacles in unmanned scenes. It addresses limitations in the traditional DBSCAN by refining the core point definition using an adaptive density threshold. It identifies the "elbow point" in density distribution, enhancing its ability to distinguish density states. Additionally, it incorporates density curve smoothing, normalization, and a merger step for handling stationary objects. The results show that it has high accuracy (95.6%), precision (96.3%), recall (94.5%), and F-Score (95.4%), as well as increased consistency (92.5%) and dependability (93.2%). It also has fast real-time data processing, lasting only 0.12 s, making it an excellent choice for obstacle detection and unmanned hazard avoidance. [ABSTRACT FROM AUTHOR]

Endocrine disrupting chemicals or carcinogens have been known for decades for their endocrine signal disruption. Endocrine disrupting chemicals are a serious concern and they have been included in the top priority toxicants and persistent organic pollutants. Therefore, researchers have been working for a long time to understand their mechanisms of interaction in different human organs. Several reports are available about the carcinogen potential of these chemicals. The presented review is an endeavor to understand the hazard identification associated with endocrine disrupting carcinogens in relation to the human body. The paper discusses the major endocrine disrupting carcinogens and their potency for carcinogenesis. It discusses human exposure, route of entry, carcinogenicity and mechanisms. In addition, the paper discusses the research gaps and bottlenecks associated with the research. Moreover, it discusses the limitations associated with the analytical techniques for detection of endocrine disrupting carcinogens. [Display omitted] • Types of endocrine disrupting chemicals (EDCs) related to cancer were analyzed. • EDCs associated cancers and their mechanisms were discussed. • Human exposure to EDCs was explored. • Assessment of EDCs carcinogenicity was performed. • Research gaps and future studies were suggested. [ABSTRACT FROM AUTHOR]

The setting of concentrations for testing substances in ecotoxicological studies is often based on fractions of the concentrations that cause 50% mortality (LC50 or LD50) rather than environmentally relevant levels. This practice can result in exposures to animals at test concentrations that are magnitudes of order greater than those experienced in the environment. Often, such unrealistically high concentrations may cause non-specific biochemical or morphologic changes that primarily reflect the near-lethal health condition of the animal subjects, as opposed to effects characteristic of the particular test compound. Meanwhile, it is recognized that for many chemicals, the toxicologic mode of action (MOA) responsible for lethality may differ entirely from the MOAs that cause various sublethal effects. One argument for employing excessively high exposure concentrations in sublethal studies is to ensure the generation of positive toxicological effects, which can then be used to establish safety thresholds; however, it is possible that the pressure to produce exposure-related effects may also contribute to false positive outcomes. The purpose of this paper is to explore issues involving some current usages of acute LC50 data in ecotoxicology testing, and to propose an alternative strategy for performing this type of research moving forward. Toward those ends, a brief literature survey was conducted to gain an appreciation of methods that are currently being used to set test concentrations for sublethal definitive studies. [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]

Sucralose, a sugar substitute first approved for use in 1991, is a non-caloric sweetener regulated globally as a food additive. Based on numerous experimental animal studies (dating to the 1980s) and human epidemiology studies, international health agencies have determined that sucralose is safe when consumed as intended. A single lifetime rodent carcinogenicity bioassay conducted by the Ramazzini Institute (RI) reported that mice fed diets containing sucralose develop hematopoietic neoplasia, but controversy continues regarding the validity and relevance of these data for predicting health effects in humans. The present paper addresses the controversy by providing the perspective of experienced pathologists on sucralose-related animal toxicity and carcinogenicity data generally, and the RI carcinogenicity bioassay findings specifically, using results from publicly available papers and international regulatory authority decisions. In the authors' view, flaws in the design, methodology, data evaluation, and reporting of the RI carcinogenicity bioassay for sucralose diminish the value of the data as evidence that this agent represents a carcinogenic hazard to humans. This limitation will remain until the RI bioassay is repeated under Good Laboratory Practices and the design, data, and accuracy of the pathology diagnoses and interpretations are reviewed by qualified pathologists with experience in evaluating potential chemically-induced carcinogenic hazards. [ABSTRACT FROM AUTHOR]

The manufacture and production of industrial chemicals continues to increase, with hundreds of thousands of chemicals and chemical mixtures used worldwide, leading to widespread population exposures and resultant health impacts. Low-wealth communities and communities of color often bear disproportionate burdens of exposure and impact; all compounded by regulatory delays to the detriment of public health. Multiple authoritative bodies and scientific consensus groups have called for actions to prevent harmful exposures via improved policy approaches. We worked across multiple disciplines to develop consensus recommendations for health-protective, scientific approaches to reduce harmful chemical exposures, which can be applied to current US policies governing industrial chemicals and environmental pollutants. This consensus identifies five principles and scientific recommendations for improving how agencies like the US Environmental Protection Agency (EPA) approach and conduct hazard and risk assessment and risk management analyses: (1) the financial burden of data generation for any given chemical on (or to be introduced to) the market should be on the chemical producers that benefit from their production and use; (2) lack of data does not equate to lack of hazard, exposure, or risk; (3) populations at greater risk, including those that are more susceptible or more highly exposed, must be better identified and protected to account for their real-world risks; (4) hazard and risk assessments should not assume existence of a "safe" or "no-risk" level of chemical exposure in the diverse general population; and (5) hazard and risk assessments must evaluate and account for financial conflicts of interest in the body of evidence. While many of these recommendations focus specifically on the EPA, they are general principles for environmental health that could be adopted by any agency or entity engaged in exposure, hazard, and risk assessment. We also detail recommendations for four priority areas in companion papers (exposure assessment methods, human variability assessment, methods for quantifying non-cancer health outcomes, and a framework for defining chemical classes). These recommendations constitute key steps for improved evidence-based environmental health decision-making and public health protection. [ABSTRACT FROM AUTHOR]

The use of robotics and automation (RA) within construction operations to combat stagnant productivity, high rates of injuries and fatalities, and a declining workforce is increasing. However, utilizing RA for construction operations creates human-robot interactions (HRIs) that can lead to the emergence of novel hazards or exacerbate existing safety risk levels. These hazards, if ignored, could worsen worker safety performance. This paper presents a study intended to identify critical HRI safety risks and develop a pre-task planning protocol for the assessment of safety risks associated with the use of RA. To achieve this goal, the authors utilized a sequential multi-phase approach relying on information obtained from a literature review, a 3-round Delphi process consisting of a panel of experts from industry and academia, and interviews with safety experts. Forty hazards associated with RA and 20 potential strategies for the mitigation of HRI safety risks were identified and evaluated. This information was used to develop a safety risk assessment tool that yields an overall risk rating of using RA. This study contributes to knowledge and practice by identifying and quantifying critical safety risks associated with HRI and developing a tool to assess and mitigate unique HRI safety risks. Utilizing insights developed in this study could improve construction worker safety and health and aid the industry's increasing push towards a smart and safe workforce. [ABSTRACT FROM AUTHOR]

Large-scale irrigation area reconstruction and expansion projects involve the repair, reconstruction and new construction of sluices, channels, inverted siphons, aqueducts and other structures. In order to ensure the quality of the project and avoid the occurrence of safety accidents, it is necessary to explore, prevent and control the hazards that may lead to building quality defects and safety accidents during the construction period. Using the work breakdown structure method and the analytic hierarchy process, the paper took the sluice engineering construction as an example and established the hazard identification and risk assessment model during the sluice engineering construction period. It had been successfully used in the identification and risk assessment of hazard sources during the construction period of the sluice project of the second phase of Zhaokou Yellow River diversion irrigation area. The research results show that the construction operation risks and building material risks have the greatest impact on the overall safety of the project and the two types of hazard sources that need to be focused on prevention and control during the project construction period. [ABSTRACT FROM AUTHOR]

Evaluation of water inrush risk is becoming increasingly important as coal mining activities reach greater depths. Hazard identification, as well as hazard analysis, is the first step in accident prevention. However, there have not been any studies that focus on the hazard analysis system for mine water inrush. In this paper, hazard identification and its definitions are briefly summarized and a comprehensive review of methods for hazard identification and classification are conducted. To illustrate the hazard of coal mine water inrush, data on coal mine accidents (since 2001) are collected and hundreds water inrush accidents were analyzed in depth. Empirical, statistical analysis and case study method were used to conduct the research. By collecting a large number of mine water inrush cases, hazard identification and risk control measures for coal mine water inrush accidents were conducted. Hazard identification method based on fault tree analysis, as well as a method based on management oversight and risk tree (MORT) and energy release theory were put forward. The analysis results show that the historical information and experiences are critically important in hazard identification of mine water inrush. Hazard of mine water inrush is divided into dynamic root hazard and static root hazard which can be further categorized into static innate hazard and dynamic-triggered hazard. Strategies for risk control of mine water inrush are combined into three aspects: engineering controls, operation system controls, and human behavior controls. Finally, a case study of the Taoyuan coal mine was conducted to illustrate the proposed system, with limitations and future studies are discussed. The hazard identification and classification system can be broadly applied to coal mines and will improve risk control and prevention of mine water inrush accidents. [ABSTRACT FROM AUTHOR]

Crane-related accidents often occur due to failure in timely and accurate hazard identification. Virtual Reality (VR) technology facilitates immersive environments for improving hazard identification without real-world consequences. However, the impact of simulation fidelity on hazard identification performance, particularly for novice crane operators, remains underexplored. This paper examines how simulation fidelity and task complexity affect hazard identification performance among novice operators through a VR experiment with two fidelity and two complexity levels. Findings demonstrate high-fidelity (HF) scenarios significantly improve hazard identification success rate and speed for swing-over hazards but extend task completion times. Task complexity modulates simulation fidelity's impact on task completion, with significant differences between fidelity levels observed only under low complexity. These insights inform the design and calibration of simulation fidelity in VR platforms, potentially improving training efficacy and crane lifting safety for novice operators. • Explores the impact of simulation fidelity on novice crane operators' hazard identification. • Finds that high-fidelity boosts success rate but reduces speed in hazard identification. • Highlights accuracy-speed trade-off due to simulation fidelity changes. • Emphasises interaction fidelity for immersive, real-world-like experiences. • Guides on balancing simulation fidelity and cost-effectiveness in VR safety training. [ABSTRACT FROM AUTHOR]

Nanoplastics are associated with several risks to the ecology and toxicity to humans. Nanoplastics are synthetic polymers with dimensions ranging from 1 nm to 1 μm. They are directly released to the environment or secondarily derived from plastic disintegration in the environment. Nanoplastics are widely detected in environmental samples and the food chain; therefore, their potentially toxic effects have been widely explored. In the present review, an overview of another two potential sources of nanoplastics, exposure routes to illustrate hazard identification of nanoplastics, cell internalization, and effects on intracellular target organelles are presented. In addition, challenges on the study of nanoplastics and future research areas are summarized. This paper also summarizes some approaches to eliminate or minimize the levels of nanoplastics to ensure environmental safety and improve human health. [ABSTRACT FROM AUTHOR]

Hazard identification in the construction industry is subject to a larger number of variables and unknowns than in other manufacturing industries making the hazard identification process more difficult and resulting in many injuries and fatalities. Moreover, previous research identified a research gap with regards to a universal hazard identification method. The results presented in this paper are a prerequisite for the development of such a method. Specifically, this paper proposes a novel classification of hazards in order to enable a more accurate hazard identification process which can take all possible hazards into consideration. Based on the theoretical framework, three hazard types are proposed in the research: self-induced hazards, peer-induced hazards, and global hazards. This classification is based on who is the source (who causes) the hazards in relation to who is affected by the hazards. Such classification was not identified in previous literature. This research also has practical implications. Such classification of hazards may influence safety experts to more actively focus on peer-induced hazards which are the hardest to identify. Finally, the outputs of the entire research should enable a more accurate and comprehensive hazard identification resulting in reduced injury and fatality rates in the construction industry. [ABSTRACT FROM AUTHOR]

Power systems and their primary components, mostly the transmission and distribution of overhead lines, substations, and other power facilities, are distributed in space and are exposed to various atmospheric and meteorological conditions. These conditions carry a certain level of risk for reliable electrical power delivery. Various atmospheric hazards endanger the operation of power systems, where the most significant are thunderstorms, wildfire events, and floods which can cause various ranges of disturbances, faults, and damages to the power grid, or even negatively affect the quality of life. By utilizing a weather monitoring and early warning system, it is possible to ensure a faster reaction against different weather-caused fault detections and elimination, to ensure a faster and more adequate preparation for fighting extreme weather events, while maintaining overhead line protection and fault elimination. Moreso, it is possible to bypass overhead lines that have the highest risk of unfavorable meteorological events and hazards, and reroute the energy, thus providing electricity to endangered areas in times of need while minimizing blackouts, and consequently, improving the quality of human life. This paper will present an analysis of the various risks of atmospheric phenomena, in the meteorological and climate context, and discuss various power system components, the power system control, operations, planning, and power quality. A concept with the main functionalities and data sources needed for the establishment of an early warning weather hazard system will be proposed. The proposed solution can be used as a utility function in power system control to mitigate risks to the power system due to atmospheric influences and ongoing climate change. [ABSTRACT FROM AUTHOR]

Highlights • A network theoretic metric for comparing HAZID methods was presented. • The metric counts socio-technical interactions in accident scenarios. • The metric is called the P3 Interaction Contribution (PIC). • The PIC results showed clear differences in HAZID results. • Future experiments to validate the PIC were presented. Abstract Comparing the results of hazard identification (HAZID) methods is a complex task, but the question that drives this activity is vitally important: which HAZID method should be used to best identify an accident scenario? Despite many efforts to address this, effective metrics do not yet readily exist for clearly comparing HAZID results for a particular scenario. The complexity of socio-technical systems is often cited as a key factor that limits effective scenario identification, calling into question traditional HAZID efforts. Motivated by the observation that interactions between multiple component types, such as People, Plant and Procedures (P3), often significantly contribute to major process system accidents, being an expression of the complexity of the system, a novel, precise, network topology-based metric for calculating the contribution of P3 Interactions to accident scenarios is presented. This metric, called the P3 Interaction Contribution (PIC), is intended to be used for comparing the HAZID results. An illustrative example of using the PIC for HAZID comparison is included, whereby Failure Mode and Effects Analysis (FMEA), Blended Hazard Identification methodology (BLHAZID) and Systems Theoretic Process Analysis (STPA) were each applied to a heat exchanger start-up operation. The results show initial promise that the PIC can be effective as a HAZID comparison tool. The main outputs of this paper are the presentation of the PIC calculation process and the method for applying the PIC to HAZID results. The paper concludes with recommendations for further experimental work to explore the validation and assess the true value of the PIC. [ABSTRACT FROM AUTHOR]

Since the identification of fire hazards in landfills has not been sufficiently investigated and studied, the goal of this research is to present a methodological approach to the issue. This paper defines fire occurrence indicators, which are considered as one of the risk factors of underground and/or surface fires in non-sanitary landfills. In this study, fire hazards are identified in terms of present landfill gas concentrations and gas well temperatures monitored by a thermal imaging camera at the nonsanitary landfill "Bubanj" in Niš, Serbia, which has been in service for 49 years. Landfill gas concentrations at the landfill were measured from May to October 2015. The paper also presents ambient air temperatures, which influence landfill gas and gas well temperatures, a necessary factor of landfill fires. Significant fire predictors for the landfill body have been determined based on all the temperatures and concentrations of landfill gas components measured using the statistical method of logistic regression. [ABSTRACT FROM AUTHOR]

Much has been written about the value of risk assessment, in particular the quantified version, QRA, here considered in the context of industrial processing oil, gas, and chemicals. It is plagued by mistrust due in part because estimated uncertainties are generally not included. QRA is done for predictive purpose, to design risk reducing measures, and to base safety decisions on, but many major accidents occur according to scenarios not foreseen in the analysis. Yet, QRA forces us to think. Predicting what can happen under specified conditions is the most elementary step in better safety. So, we must improve the methods and in particular to model sensitive uncertainties and establish confidence limits about our predictions. The present paper will review in short the state of affairs, and it will summarize recent contributions shedding light of what is currently wrong with QRA. The paper will further present for the various aspects and steps to be done in a QRA directions, in which progress is being made and where promising possibilities may appear. The latter are according to the opinion and the scope of the authors, so hopefully there is much more! Anyhow, due to complexities of socio-technical systems a QRA will require more effort, so to keep it practical large scale application of computerization will be a must. And, to improve trust in QRA we must acknowledge variability and quantify the uncertainties as we see them; in addition, there will be hidden uncertainties, which gives reason to think in resilience terms too. [ABSTRACT FROM AUTHOR]

• Testing of chemicals does not always inform their subsequent risk management. • Optimised testing strategies can improve efficiency of classification and labelling. • Hazard pictograms were used to reflect the protection level for a given chemical. • Two strategies led to the same protection level and required fewer tests. • Another strategy led to the same protection level and reduced animal testing. This paper outlines a new concept to optimise testing strategies for improving the efficiency of chemical testing for hazard-based risk management. While chemical classification based on standard checklists of information triggers risk management measures, the link is not one-to-one. Toxicity testing may be performed with no impact on the safe use of chemicals. Each hazard class and category is not assigned a unique pictogram and for the purpose of this proof-of-concept study, the level of concern for a chemical for the population and the environment is simplistically considered to be reflected by the hazard pictograms. Using active substances in biocides and plant protection products as a dataset, three testing strategies were built with the boundary condition that an optimal approach must indicate a given level of concern while requiring less testing (strategy B), prioritising new approach methodologies (strategy C) or combining the two considerations (strategy D). The implementation of the strategies B and D reduced the number of tests performed by 6.0% and 8.8%, respectively, while strategy C relied the least on in vivo methods. The intentionally simplistic approach to optimised testing strategies presented here could be used beyond the assessment of biocides and plant protection products to gain efficiencies in the safety assessment of other chemical groups, saving animals and making regulatory testing more time- and cost-efficient. [ABSTRACT FROM AUTHOR]

The traditional hazard analysis approaches applied to the socio-technical system cannot cover the complex organization structures, the interactions between systems and human behaviors, the interrelated factors among sub-systems and the safety culture of specific societies. This paper presents an integrated hazard identification approach named System-Theoretic Process Analysis Based on Formalization Model (BFM-STPA), which can solve the above issues. Firstly, the hierarchical control structure models of the socio-technical system are established through Colored Petri Nets (CPN) due to its strong description ability and executable ability, which may also be regarded as the graphical system specification. Secondly, the hazards can be identified according to the CPN models following a series of guide conditions. Thirdly, the comprehensive contributing factors to the hazards will be found out by tracing the former states within the reachability graph generated from CPN model. Finally, an integrated hazard log can be derived for further hazard analysis and safety-guided design. In this paper, the above method was applied in the Chinese Train Control System level 3 (CTCS-3). And the process of hazard identification for the scenario of Temporary Speed Restriction issued was elaborated in detail. Compared with the hazard log generated by Hazard and Operability (HAZOP), the hazard log generated by BFM-STPA covered not only the subsystem failures, but also the deviation of interactions among subsystems from design intent, human errors and socio-technical drawbacks related to the TSR Issued scenario of CTCS-3. [ABSTRACT FROM AUTHOR]

Despite major efforts, food safety and food fraud issues continue to appear, showing the need for an improved risk anticipation to enhance consumer protection. To this end, we need a holistic view on the food production beyond the classical farm to fork principle and consider developments in- and outside the food chain. Commodity flows and prices are considered as relevant drivers for the emergence of food safety and fraud issues. To conveniently obtain information on these drivers and to monitor their changes, we developed a tool to analyze the volume, origin and price of foods imported to Germany, based on data of the German Foreign Trade Statistic. The ISAR-Tool ( I mport S creening for the A nticipation of Food R isks) facilitates a descriptive analysis of the import data of about 2400 different food items imported from 220 countries and an automated analysis of the data for a systematic detection of unexpected changes in import volumes and prices. For the automated approach, time series analyses using SARIMA and ETS models are applied and data points outside the model-based 99% prediction intervals are considered as potentially relevant changes. Monthly, more than 2000 of such changes are detected, leaving us with the challenging task of their evaluation for food safety and food fraud. To deal with the vast amount of results, of which the great majority cannot be linked to food safety or fraud issues, we implemented prioritization routines, and the 200 most critical results are considered for further expert evaluation. Despite remaining challenges in the performed evaluation process of the automated analysis, the described approach facilitates already at this stage an improved identification of food safety and food fraud hazards and the implementation of more targeted food safety controls, as shown in this paper. Our most prominent example of an identified food fraud and food safety risk was the detection of massive adulterations of hazelnut products with almonds and cashews, which were associated to the observed all-time high in hazelnut prices. Based on our findings, we conclude that the ISAR-Tool and the described analyses of commodity flows and prices can be important elements in the anticipation of risks and enable an enhanced consumer protection. [ABSTRACT FROM AUTHOR]

• An extended STPA approach is proposed for safety analysis for human-system collaboration. • The human-related cognitive hazards are identified by incorporating a human cognitive model into STPA. • The operational contexts of unsafe control actions (UCAs) are systematically derived by using process model hierarchies. • Results reflect differences in humans' and technical hazards between the remote control mode and remote supervision mode of autonomous ships. • The result is beneficial for the development of future human-oriented and safe design of autonomous ships and their Shore Control Center (SCC). Shore control center (SCC) operators of maritime autonomous surface ships (MASS) may be allocated with complex responsibilities within different degrees of autonomy (DoA), from remote control to remote supervision, and the role of human in-the-loop is significant. In the current research on MASS, however, the safety of interactions between humans and systems are not sufficiently considered. Hence, this paper proposes a system-theoretic approach to safety analysis for human-system collaboration. The novelty of the approach is the definition of operational contexts of MASS and the integration of a human cognitive model into the system theoretic process analysis (STPA), called STPA-Cog. The method is demonstrated in two case studies of MASS: (i) remote control mode (RCM) and (ii) remote supervision mode (RSM), focusing on two types of navigational accidents (i.e., collision and grounding). The analysis results are derived by comparing the human-related and technical-related causal scenarios in RCM and in RSM. The findings can assist in human-oriented design and operational planning for SCC of MASS. Further, the proposed approach also has the potential to be used and extended to systemic safety analysis in other intelligent transportation systems. [ABSTRACT FROM AUTHOR]

• Wearable EEG-based hotspot approach supports ubiquitous construction hazard identification. • Similarities and discrepancies between VR and physical set-ups are revealed. • EEG classifiers developed in VR can be applied to a real-world setting. • Hotspot analysis allows for a spatial association between hazards and EEG signals. • Dual-layer approach enables the reduction of significant motion artifacts in EEG signals. Hazard identification on construction jobsites is one of the most critical components of construction safety management. To overcome the limitations in the current manual practice, researchers explored the correlation between hazard perception and changes in workers' electroencephalogram (EEG) signals collected from wearable sensors to identify and differentiate different types of hazards. However, most of such studies are based on experiments in a virtual reality (VR) environment. The unproven applicability of the VR-led results to the real jobsites and the potential discrepancies in results between the physical and virtual environments are the main barriers toward EEG-based ubiquitous hazard identification on the jobsites. To bridge the research gaps, this paper tests the feasibility of identifying construction hazards in physical and VR environments, and compares their results to identify discrepancies. Two experimental environments (physical and VR, respectively), each containing three hazards, were designed with the same configuration. Hazard identification task was performed in both experiments, data (e.g., EEG signals) was collected and preprocessed, and corresponding features were extracted. Hotspot analysis was conducted to infer the existence of hazards by assessing spatial associations. The results showed that both physical and VR settings were effective for hazard detection, while a better performance was observed in the VR setting. In addition, the potential of developing hazard zones as well as particular hazard locations and a gradual increase in subjects' perceived hazard level were revealed. The results highlight the opportunities of revealing potential construction hazards on the construction jobsite using wearable EEG. [ABSTRACT FROM AUTHOR]

Purpose – This paper aims to propose a method of hazards identification of uncontained engine rotor failure (UERF) based on collision detection between geometric models. UERF is a typical particular risk that imposes threat on flight safety of an aircraft. Aircraft systems are made up of many parts and components; therefore, it is difficult to identify hazards caused by UERF early in the design cycle. Design/methodology/approach – The methodology involves the following steps: the mapping relationship of input information is established; the parametric models are used to simulate the uncontained fragments of different categories; the parts and components that the uncontained fragment may collide with are determined by uniform space decomposition and precise collision detection; and the catastrophic hazards are identified with the comparison of the collision detection result sets and the minimum cut sets. Findings – An application case, which takes the hydraulic system of a certain type of civil aircraft in design as a study object, shows that the method proposed in this paper is suitable and efficient for hazards identification of UERF. Practical implications – The method proposed herein is useful for acquiring the minimum cut sets that will be triggered by the uncontained fragment in the design phase. Originality/value – A novel and effective method of hazards identification of UERF for an aircraft with large and complex systems is presented, which is helpful to the optimization of the layout design of parts and components of the aircraft. [ABSTRACT FROM AUTHOR]

A requirement arose during decommissioning work at a UK Magnox Nuclear Power Station to identify the hazards involved in removing High Dose Rate Items from a Cartridge Cooling Pond. Removing objects from the cooling pond under normal situations is a routine event with well understood risks but the situation described in this paper is not a routine event. The power station has shifted from an operational phase in its life-cycle to a decommissioning phase, and as such the risks, and procedures to deal with them, have become more novel and uncertain. This raises an important question. Are the hazard identification methods that have proven useful in one phase of the system lifecycle just as useful in another, and if not, what methods should be used? An opportunity arose at this site to put the issue to a direct test. Two methods were used, one practitioner focussed and in widespread use during the plant's operational phase (the Structured What-If method), the other was an analyst method (Cognitive Work Analysis). The former is proven on this site but might not be best suited to the novelty and uncertainty brought about by a shift in context from operations to decommissioning. The latter is not proven on this site but it is designed for novelty and uncertainty. The paper presents the outcomes of applying both methods to a real-world hazard identification task. [ABSTRACT FROM AUTHOR]

High-level radioactive liquid waste tanks have the possibility of releasing radioactivity, and thus it is of great importance to identify hazards in such storage tanks and take measures to improve their safety. In this paper, a hazard and operability (HAZOP) methodology is used to identify the hazards in a double-shell stainless-steel tank for high-level radioactive liquid waste storage for which a risk matrix was implemented to assess the risks posed by the hazard. First, during the HAZOP process, appropriate process parameters and guidewords were selected to describe the deviation of the storage tank, and the causes and possible consequences of deviations as well as existing protection measures were analyzed. The risk matrix then was used to evaluate the risk level of the deviation identified, combined with the consequences of the deviation as well as the associated likelihood of its occurrence. Results showed that primary tank leaks and hydrogen combustion or explosion in tanks are undesirable risks, and thus corresponding countermeasures were put forward. The analysis results could be used to provide guidance for safe operation of, and rectification of hidden dangers in, high-level radioactive liquid waste storage tanks. [ABSTRACT FROM AUTHOR]

Source location is crucial to manage contaminant emissions in atmosphere, In order to determine the source location without dependence on the absolute measurement data, a method based on optimal correlated matching of concentration distribution (OCMCD) was proposed. First, the estimation efficiency, accuracy and dependence on source strength of OCMCD were compared with the common method which estimates multiple parameters of the source term simultaneously. The results show that the method of OCMCD performs better than the common multiple parameters estimation method based on the mean errors between prediction and measurement in both estimation accuracy and efficiency. The test results with different sets of source strength manifest that OCMCD relies minimally on the source strength Then, a wind direction correction parameter and a weighted term of normalization concentration error were introduced into the model to compensate some missed information and improve the location results. The influence of data noises on the estimation accuracy of OCMCD method was also verified by adding extra manual noises on the measurement data. Then, the dependence of estimation performance with OCMCD method on atmosphere conditions were investigated statistically with experiment release cases. The results showed that source location was identified well in most of cases. Finally, OCMCD method was extended to determine the source location during the source trace process with a mobile sensor. The test results with a simulation scenario based on Zigzag search strategy demonstrate that the source location determined by OCMCD source criterion is much closer to the real source position than that determined by the criterion of the maximum concentration. Therefore, the results have proven the feasibility and superiority of OCMCD proposed in this paper to estimate source location in cases of both static sensor distribution and mobile sensors. OCMCD will be a potentially useful method to identify emission source location in atmosphere. [ABSTRACT FROM AUTHOR]

• OCMCD model based on distribution matching to locate the emission source is proposed. • The method improves the efficiency compared with multiple parameters estimation. • OCMCD model with modified terms improves the estimation property. • OCMCD method depends less on absolute data noises. • The method can be used to determine source location in the case of mobile sensor. Source location is crucial to manage contaminant emissions in atmosphere, In order to determine the source location without dependence on the absolute measurement data, a method based on optimal correlated matching of concentration distribution (OCMCD) was proposed. First, the estimation efficiency, accuracy and dependence on source strength of OCMCD were compared with the common method which estimates multiple parameters of the source term simultaneously. The results show that the method of OCMCD performs better than the common multiple parameters estimation method based on the mean errors between prediction and measurement in both estimation accuracy and efficiency. The test results with different sets of source strength manifest that OCMCD relies minimally on the source strength Then, a wind direction correction parameter and a weighted term of normalization concentration error were introduced into the model to compensate some missed information and improve the location results. The influence of data noises on the estimation accuracy of OCMCD method was also verified by adding extra manual noises on the measurement data. Then, the dependence of estimation performance with OCMCD method on atmosphere conditions were investigated statistically with experiment release cases. The results showed that source location was identified well in most of cases. Finally, OCMCD method was extended to determine the source location during the source trace process with a mobile sensor. The test results with a simulation scenario based on Zigzag search strategy demonstrate that the source location determined by OCMCD source criterion is much closer to the real source position than that determined by the criterion of the maximum concentration. Therefore, the results have proven the feasibility and superiority of OCMCD proposed in this paper to estimate source location in cases of both static sensor distribution and mobile sensors. OCMCD will be a potentially useful method to identify emission source location in atmosphere. [ABSTRACT FROM AUTHOR]

The analysis of remote sensing data to assess geohazards is being improved by web-based platforms and collaborative projects, such as the Geohazard Exploitation Platform (GEP) of the European Space Agency (ESA). This paper presents the evaluation of a surface velocity map that is generated by this platform. The map was produced through an unsupervised Multi-temporal InSAR (MTI) analysis applying the Parallel-SBAS (P-SBAS) algorithm to 25 ENVISAT satellite images from the South of Spain that were acquired between 2003 and 2008. This analysis was carried out using a service implemented in the GEP called "SBAS InSAR". Thanks to the map that was generated by the SBAS InSAR service, we identified processes not documented so far; provided new monitoring data in places affected by known ground instabilities; defined the area affected by these instabilities; and, studied a case where GEP could have been able to help in the forecast of a slope movement reactivation. This amply demonstrates the reliability and usefulness of the GEP, and shows how web-based platforms may enhance the capacity to identify, monitor, and assess hazards that are associated to geological processes. [ABSTRACT FROM AUTHOR]

The objective of this paper is to develop online risk models that can be updated as conditions change, using risk as one metric to control an autonomous ship in operation. This paper extends and integrates the System Theoretic Process Analysis (STPA) and Bayesian Belief Networks (BBN) with control systems for autonomous ships to enable supervisory risk control. The risk metric is used in a Supervisory Risk Controller (SRC) that considers both risk and operational costs when making decisions. This enables the control system to make better and more informed decisions than existing ship control systems. The novel control system is tested in a case study where the SRC can change: (i) which machinery system is active; (ii) which control mode to run the ship in; and (iii) which speed reference to follow. The SRC is able to choose the optimum machinery, control mode, and speed reference to maintain safe control of the ship over a route in changing conditions. • Method for developing a supervisory risk controller for autonomous surface ships. • Show how risk models can be used in ship control systems. • Supervisory controller for high-level control of autonomous surface ships. • Case study with supervisory risk control of autonomous surface ships. [ABSTRACT FROM AUTHOR]

• A semi-automatic model is developed for hazard and accident cause identification. • We explore and analyze the semantic relationship between the hazards of marine accidents. • The importance of both hazards and accident causes is calculated and ranked. • We gain accident causes distribution in 40 different accident scenarios by using topic model. In the past decades, marine accidents brought the serious loss of life and property and environmental contamination. With the accumulation of marine accident data, especially accident investigation reports, compared with subjective reasoning based on expert experience, data-driven methods for analysis and accident prevention are more comprehensive and objective. This paper aims to develop a content-aware corpus-based model for the analysis of marine accidents to mine the accident semantic features. The general research framework is established to combine accident data, expert prior knowledge, and semi-automated natural language processing (NLP) technology. The NLP models are optimized, fused, and applied to the case study of ship collision accidents. The results show that the proposed model can accurately and quickly extract hazards, accident causes, and scenarios from the accident reports, and perform semantic analysis for the latent relationships between them to extend the accident causation theory. This study can provide a powerful and innovative analysis tool for marine accidents for maritime traffic safety management departments and relevant research institutions. [ABSTRACT FROM AUTHOR]

Current onsite safety management always relies on time-consuming predefinitions of hazardous zones based on the managers' personal capabilities. However, in a typical labor-intensive industry such as construction, the workers themselves can provide a wealth of information for hazard identification. Historical accident-free working locations on site provide a valuable means of recognizing safe workplaces. This paper presents an approach to the automated classification of construction site zones derived from the location tracks of workers collected from a real-time location system (RTLS). Through data mining, filtering and analysis, the location tracks are transformed into grid density maps and continuous density maps. These illustrate the characteristics of spatial-temporal activities onsite as well as providing a visual representation of the distribution of safe and hazardous individual workplaces. A personnel hazard map is generated automatically based on historical accident-free location tracks from a field project using the proposed approach. Compared with the actual workplaces in terms of accuracy, precision, sensitivity and specificity, the evaluation result reveals that the hazardous areas on a construction site can be automatically classified to improve the workplace management of individual workers. The contributions of this research include an automated zone classification algorithm and an evaluation framework consisting of four indicators for hazard awareness onsite. [ABSTRACT FROM AUTHOR]

Manufacturing machine designers must take into account different aspects of products such as technology, legislation and occupational safety. European directive 2006/42/CE promulgates machine safety design principles to prevent occupational risks. Aimed at machine designers, its objective is to set out the need to obtain the lowest possible risk level according to the state of the art. Although the designers of catalog machines have access to specific standards to perform a priori risk analyses, this is not the case for special machine designers. An original approach called EZID is presented in this paper to help all machine designers in the task of hazard identification. Based on the fact that hazards are linked to the presence of energies, EZID identifies hazards through the detection of design parameters linked to energy sources and flows. It then feeds back organized information to designers on every potential exchange of energy between the machine and its operators, bringing to light the need to add risk prevention solutions. The first part provides a detailed classification of energy parameters considered to be the primary indicators of hazards. This is followed by an explanation of the logical rules describing how damage is generated by the combination of the other design parameters, increasing the level of detail in hazard identification. The next part focuses on the characterization of significant hazards. Finally, the results obtained from using this approach during the industrial design of a supply line are presented to confirm that EZID is functional from the earliest stage of design. [ABSTRACT FROM AUTHOR]

The hazard identification is one of the most significant issues of the safety management process. Conventional approaches to hazard identification in a job safety analysis (JSA) tend to failure of identifying all the potential hazards involved in a work and can lead to accidents. How to identify the hazards thoroughly has becoming a challenge. The energy source based job safety analysis (ESBJSA) method proposed in this paper, aimed to identify and assess all the potential hazards effectively by applying an analysis basis on energy sources. Through clarifying the energy sources in each sub step and identifying the corresponding potential hazards of each energy source respectively, the measures and solutions to eliminate or reduce the risks can be determined. The ESBJSA method was applied in an offshore construction and installation project, and the total recordable incident rate (TRIR) result was reduced 50% when compared with another similar project using conventional JSA method. Additionally, ESBJSA is a technique that can be fully applicable to many high risk construction and installation projects in shipyard. [ABSTRACT FROM AUTHOR]

• A new occupational health and safety training method is proposed, especially for long-term health risks. • The training method is developed based on the integration of diminished quality of life (DQL) and virtual reality (VR). • The DQL-VR training improves the training quality in both hazard identification and risk perception. Safety training using Virtual Reality (VR) can be widely found in many industries. They are majorly focused on educating sequential operations, standard working procedures, and short-term safety risk assessment. Occupational health and safety (OHS) issues at the workplace contain both short-term safety incidents and long-term health issues. Comparing to short-term safety training, long-term health training is little discussed in the existing literature. One of the reasons is that the health issues are more complex than safety, as the biological outcomes may take time to develop, affected by multiple resources, and the injuries may be cumulative. The key contribution of the current paper is the development of a solid training method based on the integration of diminished quality of life (DQL) risk assessment and VR, namely DQL-VR. The use of DQL-VR would assist in delivering OHS knowledge to trainees with a special focus on chronic health components. The use of DQL increases the ability of trainees to determine long-term health hazards and perceive long-term health risks. The use of VR improves the learning efficacy and users' acceptance of the safety training. A pilot test is investigated to examine the efficacy of DQL-VR comparing with traditional safety training. The result shows that DQL-VR has great positive efforts in teaching hazard identification and risk perception, especially for long-term health aspects. The findings also indicate that the use of DQL-VR would benefit trainees' recall of knowledge. The development of DQL-VR also offers opportunities for trainees to foresee the hazards and experience the harmful consequences in a safe environment. [ABSTRACT FROM AUTHOR]

[Display omitted] • Approaches and models in Human Health Risk Assessment are comprehensively reviewed. • Method on the mechanisms of contaminant actions on human health hazards is needed. • Integration and update of existing toxicity databases are necessary. • Lack of health-based screening values is a barrier to biomonitoring. • The integration of fate and transport models and risk assessment systems is essential. Soil contamination is a serious global hazard as contaminants can migrate to the human body through the soil, water, air, and food, threatening human health. Human Health Risk Assessment (HHRA) is a commonly used method for estimating the magnitude and probability of adverse health effects in humans that may be exposed to contaminants in contaminated environmental media in the present or future. Such estimations have improved for decades with various risk assessment frameworks and well-established models. However, the existing literature does not provide a comprehensive overview of the methods and models of HHRA that are needed to grasp the current status of HHRA and future research directions. Thus, this paper aims to systematically review the HHRA approaches and models, particularly those related to contaminated sites from peer-reviewed literature and guidelines. The approaches and models focus on methods used in hazard identification, toxicity databases in dose–response assessment, approaches and fate and transport models in exposure assessment, risk characterization, and uncertainty characterization. The features and applicability of the most commonly used HHRA tools are also described. The future research trend for HHRA for contaminated sites is also forecasted. The transition from animal experiments to new methods in risk identification, the integration and update and sharing of existing toxicity databases, the integration of human biomonitoring into the risk assessment process, and the integration of migration and transformation models and risk assessment are the way forward for risk assessment in the future. This review provides readers with an overall understanding of HHRA and a grasp of its developmental direction. [ABSTRACT FROM AUTHOR]

The paper presents problems of hazard identification in transportation systems, where not only field of action is large but also cause-consequences relations between failure causes and losses are distant in time and space. It is observed in transportation systems of goods and passengers, systems of water, gas, oil distribution and electro-energetic nets. Proposed systemic approach based on system elements classification on active (casual) and passive ones (affected). There are described concepts of vulnerability (damageability), resilience (ability of recovering and risk controlling by introducing safety measures to undesired event chain. [ABSTRACT FROM AUTHOR]

Awkward identification, superficial knowledge and misperception of occupational risks related to underground working environment in Romanian mining industry, basically linked to their probability of occurrence and severity, but also to the lack of scenario development generated in the last decades a series of undesired events with great losses, both in terms of human lives and property damage. Managing hazards in underground mining operations necessarily involves a systematic and structured process based on proactive behaviour of all stakeholders. The process should be initiated and, then, developed and spotted from exploration to closure of mining activities, namely throughout the entire life cycle of any mine unit. Nowadays, despite a strong regression of the Romanian mining industry, or quite for this reason, the commitment for quality, consistency and effectiveness of performed occupational risk analysis and management across the remaining mine units should become more accurate and holistic, considering the particular risks related to industry restriction. More and more complex evaluation tools should be applied, bringing their related benefits and consequently providing the opportunity to practically achieve higher effectiveness of decision-making processes. This paper is aimed to highlight the structure and spot the light on the main problems to be addressed by occupational health and safety engineers and managers from any mine, when setting the strategic, organizational and risk management goals, context and framework needed to perform a usable and rational risk assessment. Another goal of our systematization effort is to emphasize and offer guidance on how an adequate and targeted risk analysis method applicable in every life cycle stage of a mine, ranging from design until closure and rehabilitation should be selected. [ABSTRACT FROM AUTHOR]

New safety critical systems are about to appear in our everyday life: advanced robots able to interact with humans and perform tasks at home, in hospitals, or at work. A hazardous behavior of those systems, induced by failures or extreme environment conditions, may lead to catastrophic consequences. Well-known risk analysis methods used in other critical domains (e.g., avionics, nuclear, medical, transportation), have to be extended or adapted due to the non-deterministic behavior of those systems, evolving in unstructured environments. One major challenge is thus to develop methods that can be applied at the very beginning of the development process, to identify hazards induced by robot tasks and their interactions with humans. In this paper we present a method which is based on an adaptation of a hazard identification technique, HAZOP (Hazard Operability), coupled with a system description notation, UML (Unified Modeling Language). This systematic approach has been applied successfully in research projects, and is now applied by robot manufacturers. Some results of those studies are presented and discussed to explain the benefits and limits of our method. [ABSTRACT FROM AUTHOR]

The paper presents the attempts at determining the reasons for the hazardous incidents which threaten the safety of people working on scaffolds, as well as in their vicinity. The article is divided into two parts, the former referring to the information on the accident rate involving scaffoldings as well as the research on the likelihood of the occurrence of perilous situations, the inspection of their technical state and the breaches of the OSH Regulations included. The latter part is devoted to the thorough analysis on the particular stages of the scaffold operation life, the special attention being paid to the practices, errors and failures while designing scaffolding. Moreover, it concerns the selection of the scaffold elements, the assembly and disassembly of scaffolding as well as their usage which can result in an accident or a building collapse. The range of activities that contribute to the decrease in or even the avoidance of risky situations involving scaffolds is hereby presented in conclusions. [ABSTRACT FROM AUTHOR]

• EPE model from perspective of energy works well in UUTs' hazard identification. • UUTs probably have more serious consequences in the worst-case accident scenario. • UUTs do have significant advantages for active safety to minimize probabilities. • UUTs need to be clearly classified and coordinately developed with other facilities. With the rapid urbanization and development of China, urban utility tunnels (UUTs) that combine various city lifelines are developing quickly. However, along with the convenience brought by UUTs, these concentrated lifelines also create more potential hazards. To overcome the shortage of traditional hazard identifications and match the characteristics of UUTs, the EPE model (Energy transfer theory - Preliminary hazard analysis - Evolution tree) is proposed in this paper. Based on the EPE model, a series of well-organized hazard lists of UUTs are presented, including 189 hazards in 28 categories, covering common hazards, specific hazards and risks of multi-hazards of UUTs. Following the identification of worst-case accident scenarios, a comparison analysis of UUTs and traditional pipelines is performed. Moreover, several practical suggestions regarding long-term planning, durability, classification and regulation of UUTs are proposed. This research may be helpful to establish safer, more coordinated and efficient UUTs to facilitate city life. [ABSTRACT FROM AUTHOR]

Autonomous marine systems may switch between various operational modes with different levels of autonomy (LoA), due to a rapidly changing environment and the complex nature of tasks. The dynamic autonomy brings an additional layer of complexity to ensuring safe marine operations, but this functionality is not sufficiently considered in current risk analysis methods. Hence, this paper proposes an approach to hazard identification based on the system theoretic process analysis (STPA) that includes unsafe transitions between different LoA in systems. A case study of a remotely operated vehicle (ROV) with four operational modes with different LoAs is used to illustrate the approach. The results show that the proposed approach contributes to: 1) communicating a shift of responsibilities among human operator and system controller in different operational modes by specifying how the allocation of the responsibility between human operators and the controller changes, and what updated process model of the operator and the controller are to ensure a successful transition; 2) refining safety constraints to be more concrete to improve system design, and operational procedures and 3) identifying triggering events for marine system modes' transitions to handle environmental interaction systematically and sufficiently. • The autonomy as functionality has not been well considered in hazard analysis process. • A STPA-based framework is proposed to identify unsafe transition control actions. • The dynamic autonomy is a key factor to safe operation in a co-agency context. [ABSTRACT FROM AUTHOR]

• STPA may contribute significantly to assuring the safety of autonomous ships. • Situation awareness systems for autonomous vessels are vital for safe operation. • With increasing autonomy, the number of violated safety constraints is reduced. • With increasing autonomy, mitigative control actions become less feasible. • Assessing the safety of autonomous ships must include the role of the human element. During the last decade, a series of autonomous vessels projects have been conducted strengthening the vision of the positive impacts on human safety, cost savings and environmental protection using advanced Artificial Intelligence (AI) based on data fused algorithms from various sensors. Although these projects have demonstrated the technological feasibility of this idea, the hypothesis that autonomous ships will be safer needs to be tested and safety constraints must be established. The main objective of this paper is to determine the hazards for the system as a function of the vessel's autonomy level. This is accomplished by implementing the System Theoretic Process Analysis (STPA) on specific levels of increasing autonomy, as described by the International Maritime Organization (IMO), where the human element is limited to remote monitoring and the on-board control system makes most of the decisions and takes most of the actions. STPA assumes that accidents are caused by unsafe interactions among system components, none of which may have failed. STPA presents an advantage over other hazard analysis tools, by being more flexible in terms of required information and by having a top-down functional model approach. The STPA's results are used to determine how hazard occurrence changes, considering the interactions among system components and hard to identify failure points. These results will be used to evaluate the hypothesis that autonomous shipping will be safer and potentially contribute to the ongoing discussion for the regulatory framework that must be implemented for autonomous shipping to become a large-scale reality. [ABSTRACT FROM AUTHOR]

The pre-marketing testing of drugs and chemicals is now a paradigm of contribution to the safeguard of public health. As pointed out by the ICH concept paper E14/S7B, there is a need for science-based frameworks that allow a better design, conduction, and interpretation of nonclinical and toxicity tests, particularly, in order for those assays to influence nonclinical and clinical evaluations and decisions better. Critical issues related to the performance and predictive values of nonclinical testing were highlighted and discussed in this article, specifically, to help pharmacologists, toxicologists, and regulators in the evaluation of the reliability of such tests, and basing the prospective decisions on the true predictivity of selected screening tests. This review addressed two common mistakes in drug and chemical testing, namely, (a) the assumption of either sensitivity or specificity as automatically "predictive," and (b) the reporting of the predictive values disregarding a truly representative prevalence. This review also discussed a statistical basis to apply for (industry standpoint) or grant (regulatory standpoint) authorization for the waiving of selected nonclinical tests. Furthermore, this review can be guiding for those who are entering into the field of drug and chemical testing. Through application, investigation, and enhancement of the conceptual framework discussed in this review, nonclinical testing is expected to provide a higher contribution to drug and chemical development, regulatory science, and public health. [ABSTRACT FROM AUTHOR]

Many civilian applications of commercial unmanned aircraft are being planned to operate in the years ahead. Several countries have developed their own framework to design the operation of unmanned aircraft and the different services that demand safe operation. This paper focuses on the European framework denoted as U-space which concludes with the joint integration of manned and unmanned aircraft in the airspace. U-space is a set of novel services and specific procedures designed to provide safe and efficient access into the airspace to the airspace users. U-space constitutes a management system to organise unmanned operations and provides relevant information to drone operators as well as manned aircraft, air navigation service providers and authorities. The understanding of associated hazards and risks to unmanned aircraft is a critical issue for their operation in complex and non-segregated airspaces. The safety assessment developed herein is crucial to identify safety indicators for U-space. In addition, the identification of safety indicators was used to identify gaps in U-spaces services that are not correctly covered by the U-space framework. Particularly, several safety indicators are identified that currently U-space services do not consider and can imply an increase in the operational risk of unmanned operations. [ABSTRACT FROM AUTHOR]

Investigation reports of fatal confined space accidents nearly always point to a problem of identifying or underestimating risks. This paper compares 4 different risk analysis tools developed for confined spaces by applying them to 3 hazardous scenarios. The tools were namely 1. a checklist without risk estimation (Tool A), 2. a checklist with a risk scale (Tool B), 3. a risk calculation without a formal hazard identification stage (Tool C), and 4. a questionnaire followed by a risk matrix (Tool D). Each tool's structure and practical application were studied. Tools A and B gave crude results comparable to those of more analytic tools in less time. Their main limitations were lack of contextual information for the identified hazards and greater dependency on the user's expertise and ability to tackle hazards of different nature. Tools C and D utilized more systematic approaches than tools A and B by supporting risk reduction based on the description of the risk factors. Tool D is distinctive because of 1. its comprehensive structure with respect to the steps suggested in risk management, 2. its dynamic approach to hazard identification, and 3. its use of data resulting from the risk analysis. [ABSTRACT FROM PUBLISHER]