Identification Of Safety Risks Research Articles

Columbia-Suicide Severity Rating Scale (C-SSRS) Reveals High Rates of Suicidality in 602 Patients With Cleft and Craniofacial Conditions.

Little is known about rates of suicidal ideation and behavior among youth with cleft lip and/or palate (CLP) and other craniofacial conditions. Records of patients ages 6 and older who were administered the Columbia-Suicide Severity Rating Scale (C-SSRS) Lifetime Version during routine multidisciplinary cleft or craniofacial team visits between 2019 and 2023 were examined. Demographics information, C-SSRS data, and diagnoses were assessed with statistics including t tests, the Fisher exact test, and odds ratios. A total of 1140 C-SSRS questionnaires across 602 (433 CLP and 169 craniofacial) patients with an average age of 11.2±3.7 years were included. Eighty-four (13.6%) patients endorsed lifetime suicidal ideation, 9 (1.5%) had at least one instance of suicidal behavior, 30 (5.0%) endorsed nonsuicidal self-injury, and 2 (0.3%) engaged in self-injurious behavior. Compared with CLP, those with other craniofacial conditions had similar odds of endorsing suicidal ideation and behavior (P≥0.05). Compared with those with isolated cleft palates, CLP had greater odds of endorsing suicidal ideation and behavior, though those differences were not significant (P≥0.05). Incidence of suicidality was unchanged before, during, and after the COVID-19 pandemic (P≥0.05). Dividing patients by sex or insurance type revealed no difference in suicidality (P≥0.05). Patients with CLP and craniofacial conditions have a high incidence of suicidal ideation and behavior, though levels are similar between these groups. Suicidality in these patients was not negatively impacted by the COVID-19 pandemic. Early identification of safety risks and psychosocial challenges through regular screening can facilitate connection with appropriate clinical interventions.

Optimizing Early Clinical Investigations in Cancer Immunotherapy: The Translational Journey of RG6292, a Novel, Selective Treg-Depleting Antibody.

The multifaceted IL-2/IL-2R biology and its modulation by promising therapeutic agents are highly relevant topics in the cancer immunotherapy field. A novel CD25-Treg-depleting antibody (Vopikitug, RG6292) has been engineered to preserve IL-2 signaling on effector T cells to enhance effector activation and antitumor immunity, and is currently being evaluated in the clinic. The Entry into Human-enabling framework described here investigated the characteristics of RG6292, from in vitro quantification of CD25 and RG6292 pharmacology using human tissues to in vivo assessment of PK/PD/safety relationships in cynomolgus monkeys as non-human primate species (NHP). Fundamental knowledge on CD25 and Treg biology in healthy and diseased tissues across NHP and human highlighted the commonalities between these species in regard to the target biology and demonstrated the conservation of RG6292 properties between NHP and human. The integration of in vitro and in vivo PK/PD/safety data from these species enabled the identification of human relevant safety risks, the selection of the most appropriate safe starting dose and the projection of the pharmacologically-relevant dose range. The first clinical data obtained for RG6292 in patients verified the appropriateness of the described approaches as well as validated the full clinical relevance of the projected safety, PK, and PD profiles from animal to man. This work shows how the integration of mechanistic non-clinical data increases the predictive value for human, allowing efficient transition of drug candidates and optimizations of early clinical investigations.

Hydroponic Nutrient Solution Temperature Impacts Tulane Virus Persistence over Time

Controlled environment agriculture (CEA), or indoor agriculture, encompasses non-traditional farming methods that occur inside climate-controlled structures (e.g., greenhouses, warehouses, high tunnels) allowing for year-round production of fresh produce such as leaf lettuce. However, recent outbreaks and recalls associated with hydroponically grown lettuce contaminated with human pathogens have raised concerns. Few studies exist on the food safety risks during hydroponic cultivation of leaf lettuce; thus, it is important to identify contributing risk factors and potential mitigation strategies to prevent foodborne transmission via hydroponically grown produce. In this study, the concentration of infectious Tulane virus (TV), a human norovirus surrogate, in hydroponic nutrient solution at 15 °C, 25 °C, 30 °C, and 37 °C was determined over a duration of 21 days to mimic the time from seedling to mature lettuce. The mean log PFU reduction for TV was 0.86, 1.80, 2.87, and ≥ 3.77 log10 at 15 °C, 25 °C, 30 °C, and 37 °C, respectively, at the end of the 21-day period. Similarly, average decimal reduction values (D-values) of TV at 15 °C, 25 °C, 30 °C, and 37 °C were 48.0, 11.3, 8.57, and 7.02 days, respectively. This study aids in the (i) identification of possible food safety risks associated with hydroponic systems specifically related to nutrient solution temperature and (ii) generation of data to perform risk assessments within CEA leaf lettuce operations to inform risk management strategies for the reduction of foodborne outbreaks, fresh produce recalls, and economic losses.

Research on Safety Risk Transfer in Subway Shield Construction Based on Text Mining and Complex Networks

Subway construction is often in a complex natural and human-machine operating environment, and that complicated setting leads to subway construction being more prone to safety accidents, which can cause substantial casualties and monetary losses. Thus, it is necessary to investigate the safety risks of subway construction. The existing literature on the identification and assessment of subway construction safety risks (SCSR) is susceptible to the influence of subjective factors. Moreover, although existing studies have explored the interrelationships between different risks, these studies usually analyze the interrelationships of single risks, lack the study of risk chain transfer relationships, and fail to find out the key path of risk transfer. Therefore, this paper innovatively combines text mining, association rules, and complex networks to deep mine subway construction safety incident reports and explore the risk transfer process. Firstly, it uses text mining technology to identify subway construction safety risks. Then, association rules are introduced to explore the causal relationships among safety risks. Finally, the key safety risks and important transfer paths of subway construction safety accidents (SCSA) are obtained based on the complex network model. Research results show that (a) improper safety management, unimplemented safety subject responsibilities, violation of operation rules, non-perfect safety responsibilities system and insufficient safety education and training are the key safety risks in SCSA; (b) two shorter key risk transfer paths in the subway construction safety network can be obtained: insufficient safety education and training→lower safety awareness→violation of operation rules→safety accidents; insufficient safety checks or hidden trouble investigations→violation of operation rules→safety accidents; (c) in the process of risk transfer, the risk can be controlled by controlling the key safety risk or cutting off the transfer paths. This paper provides new ideas and methods for SCSR identification and influence element mining, and the results of the study help safety managers propose accurate subway construction safety risk control measures.

Computer vision-based safety risk computing and visualization on construction sites

Despite advancements in computer vision technology for construction site safety, the identification and evaluation of potential safety risks stemming from on-site hazardous objects and their spatial interactions is under-researched. Moreover, the subsequent visualization of risks, essential for effective safety management, remains insufficiently explored. This paper presents a model combining computer vision and the TOPSIS method to automate safety risk quantification and visualization during the construction process. Uniquely, it enhances risk predictions by dynamically monitoring the quantity and distance changes of hazard sources and their risk-related objects in real-time, beyond pre-construction risk identification and predictions. Experimental validation shows the model's effectiveness in risk quantification and visualization, with a high consistency ratio of 95% compared to expert manual assessments. This model lays the groundwork for more precise risk calculation and evaluation, fostering improved safety management decisions.

Research on coal mine safety management based on digital twin

Coal mine safety management is the foundation and decisive factor of coal mining. The manual detection model is the main way for traditional coal mine safety management, which has problems such as inefficient identification of safety risks in coal mines, poor control accuracy and slow response measures and so on. Therefore, to make up for the shortcomings in the traditional coal mine safety management model, this paper introduces digital twin technology into coal mine safety management to achieve intelligent and efficient management of coal mine safety accidents. Firstly, we introduce the digital twin technology, select the five-dimensional model as the modeling basis, based on the existing twin model architecture, analyze the types of coal mine accidents and disasters, select the most destructive gas accidents as the research object, construct a twin safety management model for coal mine gas accidents using the digital twin five-dimensional model. Secondly, analyses of the actual operation mechanism of the digital twin model, and the advantages of the twin model in achieving prior prevention, rapid response and accurate control of gas incidents are pointed out. Finally, the house of quality of the gas accident digital twin model is established through the quality functional deployment tool, and key technical requirements for the construction of the twin model are given to accelerate the application of the gas accident twin model in the field.This study innovatively introduces digital twin technology into the field of coal mine safety management, proposes the application scenarios of emerging technologies such as digital twins in the coal mine field, and provides the possibility of multi-scene application of smart mine construction and technologies such as digital twins.

The construction and application of event logic graph for pedestrian flow evacuation in typical scenarios

An event logic graph is a kind of knowledge mapping technology for knowledge inference and simulation analysis, which takes events as the core and portrays the hierarchical system and logical evolution pattern between events. In order to apply it to further improve the accuracy of related studies, such as pedestrian flow evacuation, simulation model optimization and risk prediction. In this paper, we use social network resources, media resources and journal database resources to build our corpus and adopt the explicit event relationship extraction method based on syntactic dependency and the implicit event relationship extraction method based on BERT+Bi-LSTM+Attention+Softmax for the characteristics of explicit event relationship and implicit event relationship, respectively. This paper constructs a pedestrian flow evacuation matter mapping for three typical scenarios and discusses its application path. It is found that once a sound knowledge base of logical reasoning and event logic graph is established, both research on optimization of pedestrian flow evacuation simulation models and research on identification and assessment of pedestrian flow evacuation safety risks will receive excellent support.

Assessment of Occupational Health and Safety Risk in the Road Construction Project in the Sigi Regency

The possibility occurrence of occupational health and safety risk in construction work is large because each work environment has many sources of danger but can be done prevention and handling to reduce the risk of occurrence of a work accident that’s why we need the process of identification and assessment of occupational health and safety risks. This type of research is descriptive analysis, the research approach is observational to use a sheet of JHA (Job Hazard Analysis) for hazard identification and risk assessment with a semi-quantitative analysis using the standard risk assessment AS/NZS 4360:2004. The results of the hazard identification beyond the occupational health and safety are carried out in the road construction in the Sigi Regency produce 147 of the danger that comes from the unsafe action and unsafe conditions and the results of assessing the risks over 147 hazards identified there are 5 different levels of risk ranging from the risk level the most, namely level priority 3 as much as 46%, very high as much as 22%, for priority 1 as much as 14%, substantial as much as 11%, and acceptable as much as 7%.

Safety Risk Identification Method for Railway Construction in Complex and Dangerous Areas

Safety risk identification is the premise and foundation of safety risk management for railway construction. However, due to some characteristics of railway projects, which include large volumes of work, complex construction environments, and long construction cycles, etc., the risk factors of railway projects are often hidden in all stages of engineering construction. It results in the comprehensive identification of safety risks of railway projects being usually difficult, and this problem is more serious when the railway is constructed in complex and dangerous areas. Therefore, to identify the safety risks comprehensively, this paper constructs a safety risk identification method applicable to railway construction in complex and dangerous areas. This method studies the spatial and temporal distribution of risks and their relationship with subprojects by using a work breakdown structure (WBS), a risk breakdown structure (RBS), grid-based management, and forming a safety risk identification matrix, which can help researchers analyze the characteristics of risks. In order to verify the effectiveness of the method, the A Railway, which is located in the western of China, was selected as a case study, and risk identification for its civil engineering was carried out. The research results show that in the construction process of the A Railway, the main types of safety risks suffered by various branch projects were different. In addition, some risk factors only appeared at specific times in space, and there is a strong interaction between these risk factors. Based on this method, safety risk identification can intuitively discover the spatial and temporal distribution of risk factors and analyze the interaction between risk factors, which can provide help for the formulation of targeted risk control measures.

Use of a serious game simulation to build early childhood staff capacity for reducing unintentional childhood injuries

Introduction: Unintentional home injuries are common and costly, with over 1.6 million occurring among U.S. children ages 0–4 in 2018. Home visitors and other early childhood professionals can provide valuable prevention education and intervention to reduce unintentional injury risk for children. This proof-of-concept study aimed to test the feasibility of the first phase of Home Safety Hero, a software-based serious game simulation that trains users in identification of home safety risks, as a capacity building tool for early childhood professionals. Methods: The game simulation’s potential for knowledge promotion and engagement in a sample of home visitors was explored based on play of the first phase. Repeated measures ANOVAs were used to assess learning via reaction time, and engagement was measured via the User Engagement Scale (UES). Results: Reaction time (i.e., average time to identify hazards) improved from the first to last levels in both single and mixed category levels in this trial. Participant indicated agreement with four subscales of engagement measured by the UES, and neutral to agree on a fifth subscale, focused attention. Conclusions: We propose that this game simulation can meet the unique training needs of early childhood professionals while promoting home safety knowledge that can improve prevention work with families. Participant feedback was largely positive, and results suggest that the game simulation is engaging and contributes to knowledge. Practical Applications: The Home Safety Hero serious game simulation is a flexible training option that appeared to be feasible for reducing time to hazard identification among home visitors in this proof-of-concept study. The design of the game simulation has utility in meeting the specialized training needs of early childhood professionals and potential to build their capacity to provide direct intervention around home safety, reducing risk for unintentional injury among children.

BIM-Based Dynamic Construction Safety Rule Checking Using Ontology and Natural Language Processing

Real-time identification and prevention of safety risks in dynamic construction activities are demanded by construction safety managers to cope with the growing complexity of the construction site. Most of the studies on BIM-based construction safety inspection and prevention use data from the planning and design stage. Meanwhile, safety managers still need to spend a lot of time gathering reports about construction safety risks in certain periods or areas from inferred results in BIM. Therefore, this paper proposed an automatic safety risk identification and prevention mechanism for the construction process by integrating a safety rule library based on ontology technology and Natural Language Processing. An automatic inspection mechanism integrating BIM and safety rules is constructed, and a presentation mechanism of intelligent detection results based on Natural Language Processing is designed. The construction process safety rule checking system was developed, and the effectiveness of the system was verified by a case study. The outcome of this paper contributes to the development and application of ontology in construction safety research, and the NLP-based safety rule checking result presentation will benefit safety inspectors and construction managers in practice.

Possibilities of predictive toxicology in assessing the potential hepatotoxicity of medicinal substances

Currently, one of the "gold" standards for determining the potential toxicity of drugs is highly informative preventive screening (HCS). This method has become a powerful tool for the evaluation of molecular, cellular and tissue toxicity, especially in the field of predictive toxicology, aimed at predicting unwanted drug-related substances. It is critical for the pharmaceutical industry to identify and subsequently mitigate potential safety risks early in the R&D process and thus reduce toxicity and the safety-related shrinkage of drug development programs. In this article, we review some of the most common used HCS assays for predictive toxicology in the pharmaceutical industry. PubMed, Elsevier Science (Scopus), and Clarivate Analytics (Web of Science) research databases were searched for original research to identify the hallmarks of the HCS methodology. Hepatotoxicity is one of the most common causes of safety and toxicity related downsizing of potential drugs in the pharmaceutical industry, as well as drug withdrawals. Hepatotoxic substances are associated with xenobiotics, drugs, substances of natural origin and chemical agents that constitute an important cause of hepatic action. A single classification based on the mechanisms of toxicity makes it possible to distinguish between intrinsic hepatotoxicity (preliminary and dose-dependent) and idiosyncratic hepatotoxicity (invisible, non-mediated immune and metabolic reactions). HCS analyzes are not intended to replace animal testing because they cannot capture the full complexity of an organism. However, they can reduce the amount of animal testing by early detection of hazards and complement animal testing. Through early identification of safety risks and optimization of chemistry series across relevant safety endpoints, HCS assays for predictive toxicology hold the promise of enhancing the successful selection of new drug candidates with satisfactory toxicological properties.

Sources of Evidence Triggering and Supporting Safety-Related Labeling Changes: A 10-Year Longitudinal Assessment of 22 New Molecular Entities Approved in 2008 by the US Food and Drug Administration.

New safety issues concerning US FDA-approved drugs are commonly communicated through safety-related labeling changes. Therefore, to optimize and refine postmarket safety surveillance strategies, it is important to comprehensively characterize the sources of data giving rise to safety-related labeling changes. Our objective was to characterize the sources of data triggering and supporting the identification of new safety risks of FDA-approved drugs communicated through safety-related labeling changes. We conducted a retrospective study with a 10-year observation period using FDA's internal electronic data repositories for all prescription new molecular entities (NME) approved in 2008. We collected and analyzed information on new safety issues, the section of the full prescribing information updated, initiators (FDA, drug manufacturer), and triggering and supporting sources of evidence. Among 22 NMEs approved in 2008, 189 new safety issues for 18 NMEs were identified.Compared to drug manufacturer, FDA initiated safety-related labeling changes in nine of the ten changes to theBoxed Warnings, 28 of the 52 changes to the Warnings and Precautions, and 43 of the 134 changes to the Adverse Reactions sections of the full prescribing information. The most frequent triggering sources of evidence included the drug manufacturer safety database (32.3%) and FDA Adverse Event Reporting System (FAERS) safety reports (15.3%) for all relevant sections of the full prescribing information, and class-labeling changes (17.5%) for Boxed Warnings and the Warnings and Precautions sections. The most frequent triggering source of evidence was FAERS safety reports (69%) in the first year after drug approval and the drug manufacturer safety database in subsequent years. Our findings emphasize the continued importance of safety reports from FAERS and drug manufacturer safety databases and a comprehensive drug safety surveillance program throughout a drug's lifecycle.

A Conceptual Framework for the Identification of Food Safety Risks in Global Commodity Flows Exemplified by Agricultural Bulk Commodities

A Conceptual Framework for the Identification of Food Safety Risks in Global Commodity Flows Exemplified by Agricultural Bulk Commodities

Identification and assessment of occupational safety risks in case of failure to capture an orphan source of ionizing radiation

Occupational safety and health belong to fundamental human rights. This fully applies to the protection of employees and other persons, which operate or are located in facilities for the collection of scrap metal. The founder of the landfill or the employer has an irreplaceable place in the field of protection of persons against the effects of ionizing radiation. Based on the identification and assessment of occupational safety risks in the event of failure to ensure timely detection of an orphan source of ionizing radiation, the operator must assess all risk factors with emphasis on radiation. At the same time, it must take specific regime measures, which would minimize the impact on people and the environment. The article deals with the causes of failure the system of protection against the effects of ionizing radiation. The assessment of these causes is performed using the fault tree analysis method with the application of Boolean equations. The result of solving the problem is the calculation of the failure of the regime protection system in the devices, intended for the collection of scrap metal, caused by human error as a result of intentional or negligent actions of the operator and insufficient training in the areas of control of measuring devices, principles of correct use of detection devices, insufficient visual identification of potentially dangerous objects. The contribution of this paper is in the design of appropriate regime measures eliminating the consequences of non-capturing a source of ionizing radiation.

Systematic review on the identification of safety risks in off-site manufacturing (OSM)

PurposeOff-site manufacturing (OSM) has emerged as a method of modern construction that provides several benefits including achieving lower costs, a quicker schedule and environmentally friendly solutions. Although numerous researches are available that advocate the adoption of OSM, the devotion towards OSM safety is somewhat limited. However, OSM invariably generates safety risks, including dynamics and uncertainty in safety management. There is a unique call to have an investigation on the identification of OSM safety risks.Design/methodology/approachTo provide a full picture on the OSM safety, a systematic literature review was adopted based on interpretivist philosophical stance. The literature search was conducted in key electronic databases to identify OSM safety-focused publications. Bibliometric analysis was adopted to identify co-occurrences of keywords and collaboration among authors in OSM safety-related research publications. Content analysis was conducted to provide a taxonomy of OSM safety risks. The identified studies were critically analysed to determine the focus of OSM safety research and provide future research directions.FindingsThe results demonstrated frequently appeared OSM safety aspects while highlighting the limitedness of collaborative research outputs in common authorships. Content analysis subsequently unveiled safety risks in OSM under human, organisational and work environmental factors. A critical analysis of extant literature revealed seven research classifications of OSM safety. Directions were offered to enhance OSM safety by applying principles of targeted safety management concepts, technology-driven safety measures and bespoke training programs.Originality/valueThis study provides a comprehensive review on the identification of safety risks throughout OSM while presenting the avenues useful for the development of OSM safety management strategies.

A web-based tool for the early identification and real time assessment of drug-induced proarrhythmic and torsade de pointes safety risk

Abstract Introduction It is well recognized that early identification of drug-induced proarrhythmic safety risks is crucial to drug development for ethical, animal sparing and costs reduction considerations. The availability, however, of easily accessible, user-friendly tools for real time assessments of the proarrhythmic potential of chemical compounds has been lacking. The novel Tx index, implemented in the presented web-based tool, was applied to a dataset of 84 compounds. Materials and methods The tool is based on 206,766 cellular simulations of compound-induced effects on Action Potential Duration (APD) in isolated endocardial, midmyocardial, and epicardial cells and on 7,072 tissue simulations on QT prolongation in a virtual tissue. Simulations were performed by blocking the slow and the fast components of the delayed rectifier current (IKs and IKr, respectively) and the L-type calcium current (ICaL) at different levels. Based on these simulations, four Tx indices were defined as the ratio of drug concentration leading to a 10% prolongation of the APDendo, APDmid, APDepi or QT over the maximum Effective Free Therapeutic Plasma Concentration (EFTPC), respectively. A dataset of 44 non-torsadogenic and 40 torsadogenic drug compounds was used to validate the performance of the tool. The workflow of the web-based tool was built on the cloud environment, in compliance with the highest standards of security and privacy. hERG test (positive response: hERG pIC50 >6) was applied to the 84 compounds to compare performances. Results Receiver operating characteristic (ROC) curves were constructed on the four estimated Tx indices for each compound in the dataset to enable the identification of torsadogenic potential cut-off values2. These were identified as 8, 8, and 6.4 for Tx-APDendo, Tx-APDmid, Tx-APDepi and as 9.2 for Tx-QT, respectively. The classification of the 84 compounds resulted in an accuracy ranging between 87% and 88% for the four Tx indices Tx-APDendo, Tx-APDmid, Tx-APDepi and Tx-QT. Discussion and conclusion hERG block exhibits poor performance. When applying the hERG test to the 84 compounds, it exhibited a TPR of 55%, a TNR of 89%, and an A of 73%, in close agreement with previous studies. In comparison, the in silico Tx tests described in this study yield TPRs of 85%, TNRs of 86–89% and As of 86–87%. This method does not include drug effects on Na+ channels, which is related to the misclassification of 3 compounds (quetiapine, ranolazine, and lamotrigine – significant Na+ channels blockers at EFTPC). Future work will include this channel. The presented web-based tool is a highly innovative method for an accurate torsadogenic risk assessment. Each assessment required only a few seconds of computational time. Illustration workflow of the web tool Funding Acknowledgement Type of funding source: None

Understanding fish production and marketing systems in North-western Nigeria and identification of potential food safety risks using value chain framework

Fish production systems in North-western Nigeria have a significant role in food, nutrition and income generations to families, yet an important setup for zoonotic disease transmission. The aim of this study was to provide a broad knowledge of the structure, activities and food safety risks of the fish value chains operating in North-western Nigeria using the value chain framework. A total of 16 focus groups and 8 key informant interviews were conducted to gather data from fish producers, fish sellers and fish processors in selected peri-urban and rural settlements in Kaduna State. In addition, 129 semi-structured questionnaires and observation checklists were used in this study to gather evidence-based data, such as demography of value chain actors, product characterization, and food safety risks.The fish value-chain in North-western Nigeria is characterised by four main stakeholders, namely, fish producers, transporters, as well as raw- and processed-fish-sellers (wholesalers, retailers). Two major sources were identified supplying farmed fish to North-western Nigeria: the distributors from the central and southern part of the country and the fish farmers within the North-western and North-eastern regions of Nigeria. Raw-fish-wholesalers within the two major markets sold most of their high-value products to raw-fish-retailers, while low-value products were routed to raw-fish-retailers in the rural communities, processed-fish-retailers and household consumers in rural settlements. There were no large companies operating and no differentiation of chains between aquaculture and wild fishery. Raw fishes not sold and began to rot were sold to street vendors at a cheaper price and household consumers.Fish production and supply chains were characterised by poor structural and sanitary support for food safety and hygiene measures. Food safety risks identified were related to lack of biosecurity measures in fish farms, lack of cold chain and access to running water, poor hygiene practices by all handlers, lack of fish inspection at all levels, lack of use of protective clothing and limited health inspection of handlers.In overall, government control of activities in fish value chains was relatively poor leading to the absence of food safety regulatory enforcement characterised by lack of institutional goals on improving food safety measures in a chain-wide distribution. Hence, this study points the significant structural, sanitary and hygiene limitations along the fish value chain components. It provides a baseline for microbial food safety risk assessments, and information required for policy-making regarding implementation of disease control programmes, as the sector is fast-evolving in Sub-Saharan Africa.

Identification and Solution of Safety and Operational-Economic Risks in Railway Transport

Abstract The paper is concerned with the issue of safety and risks in transport with a detailed focus on rail transport. Nowadays, when it is required to prefer safe and environmentally friendly modes of transport, the knowledge of this issue is important. Part of the paper is an analysis of individual risk factors in railway transport. These include risks in the field of railway safety, natural disasters, economic risks, risks in management systems and technical equipment, and risks related to legislative changes. Attention is paid to comparison and evaluation of individual risk factors in terms of severity and probability of occurrence - frequency. Following the analysis and evaluation of the risk level, are suggest possible or optimal ways to resolve them. The outcome of it is to eliminate or minimize them in the railway transport undertaking. The final part briefly describes the current situation in rail transport, recent developments and the main conditions and assumptions for its further development.

Road Traffic Safety Risk Estimation Method Based on Vehicle Onboard Diagnostic Data

Currently, research on road traffic safety is mostly focused on traffic safety evaluations based on statistical indices for accidents. There is still a need for in-depth investigation on preaccident identification of safety risks. In this study, the correlations between high-incidence locations for aberrant driving behaviors and locations of road traffic accidents are analyzed based on vehicle OBD data. A road traffic safety risk estimation index system with road traffic safety entropy (RTSE) as the primary index and rapid acceleration frequency, rapid deceleration frequency, rapid turning frequency, speeding frequency, and high-speed neutral coasting frequency as secondary indices is established. A calculation method of RTSE is proposed based on an improved entropy weight method. This method involves three aspects, namely, optimization of the base of the logarithm, processing of zero-value secondary indices, and piecewise calculation of the weight of each index. Additionally, a safety risk level determination method based on two-step clustering (density and k-means clustering) is also proposed, which prevents isolated data points from affecting safety risk classification. A risk classification threshold calculation method is formulated based on k-mean clustering. The results show that high-incidence locations for aberrant driving behaviors are consistent with the locations of traffic accidents. The proposed methods are validated through a case study on four roads in Chongqing with a total length of approximately 38 km. The results show that the road traffic safety trends characterized by road safety entropy and traffic accidents are consistent.