Search

The World Health Organization (WHO) recognises air pollution as a serious public health concern in many developing countries due to the influx of energy-intensive industries with limited planning and exposure mitigation strategies. Due to industrial expansion and release of associated air pollutants in Oman, the US Environmental Protection Agency human health risk assessment (HHRA) model was used to determine the non-carcinogenic hazard associated with exposure to industrial emissions. Across the three industrial cities (Nizwa, Sur and Rusayl), the study found ambient average concentrations (μg/m3) of 1 h carbon monoxide (CO) (606–1974), nitrogen dioxide (NO2) (7.7–43.9) and sulfur dioxide (SO2) (4.8–9.0) and 24 h PM2.5 (7.3–7.8) and PM10 (38.7–51.5) to be significantly lower than both the Ministry of Environment and Climatic Affairs (MECA) and WHO limits. The HHRA analysis showed that exposure to the air pollutants produced low non-carcinogenic adverse health effects, as the hazard quotient (HQ) was found to be

Understanding the runout of slope failures is important for hazard identification, risk assessments, and disaster prevention. This study evaluates the accuracy of three runout software packages, DAN3D, Anura3D, and FLO-2D, for modeling the runout of the 2014 Oso landslide and investigates the viability of predicting the runout of other landslides and slope failures under similar conditions. The Oso landslide runout analyses using Anura3D and FLO-2D conducted for this study adopt the geotechnical conditions and failure mechanism reported by Stark and his colleagues in 2017. Together with DAN3D and Anura3D modeling reviewed from previous studies, the accuracy and applicability of these runout models are assessed using field observations. These analyses show the importance of (i) using a digital terrain model in the runout analysis, (ii) modeling field representative shear strength properties and failure mechanisms, and (iii) predicting runout distance, splash height, and duration for risk assessments and to improve public safety for this and other slopes.

Food safety management in cocoa and chocolate focuses mainly on incoming hazards and their controls at different stages of processing, as well as prevention of recontamination during further processing. Due to the nature of the products (low moisture, high fat) some specifics need to be taken into account in order to ensure efficient and successful food safety management. The risks associated with these products had been recognized by European industry organizations for chocolate, confectionery and biscuits. In the 1990s, the IOCCC published two codes of practice: one based on the HACCP, and one for specific GMPs for the cocoa, chocolate and confectionery industry [(Caobisco) Brochures available from CAOBISCO (Association of Chocolate, Biscuit and Confectionery Industry of the EU). http://www.caobisco.com/page.asp?p=220 >(accessed 02.06.11)]. The microbiological safety of chocolate products can be ensured by consequent application of the HACCP concept and adherence to prerequisite programs to ensure good manufacturing and agricultural practices, throughout the whole processing chain. This includes not only the final processing steps of making chocolate, but starts at the level – and sourcing – of raw agricultural materials used in chocolate making like cocoa and nuts. Microbial data can play an important role in the verification of implemented controls, but their validity and limitations need to be understood (Kvenberg, J.E., Schwalm, D.J., 2000. Use of microbial data for hazard analysis and critical control point verification – Food and Drug Administration perspective. J. Food Prot. 63 (6), 810 -814; Swanson, K.M.J., Anderson, J.E., 2000. Industry perspective on the use of microbial data for hazard analysis and critical control point validation and verification. J. Food Prot. 63 (6), 815–818; Kornacki, J.L., 2006. Microbiological sampling in the dry foods processing environment. Food Safety. Mag., pp.66).

Background Studies on the clinical implication of hospital selection for patients with lung cancer are few. Therefore, this study aimed to analyze 2005–2016 data from the Korean national database to assess annual trends of lung cancer surgery and clinical outcomes according to hospital selection. Methods Data of 212 554 patients with lung cancer who underwent upfront surgery were screened. Trends according to sex, age, residence, and income were examined. Descriptive statistics were performed, and p trend values were estimated. The association between survival and hospital selection was assessed using the log‐rank test. A multivariate Cox regression analysis was also performed. Results A total of 49 021 patients were included in this study. Surgery was prevalent among men, patients aged 61–75 years, capital area residents, and high‐income patients. However, with the increasing rate of surgery among women, patients aged ≥76 years, city residents, and middle‐income patients, the current distribution of lung cancer surgery could change. The rate of lobectomy among these groups increased. All patients, except those in capital areas, preferred a hospital outside their area of residence (HOR); the number of patients with this tendency also increased. However, this trend was not observed among low‐income patients and those aged ≥76 years. There were significant differences in survival according to hospital selection. Conclusions The trend of lung cancer surgery is changing. The current medical system is effective in providing lobectomy for patients including women, aged ≥76 years, city residents, and middle‐income. Increasing tendency to choose an HOR requires further study., The trend of lung cancer surgery is changing. Women, ≥76 years, city residents, and middle‐income increased. All patients, expect those in capital areas, preferred hospital outside their area of residence. The rate of lobectomy increased.

Risk analysis, as an important prerequisite of risk management, is critical to reducing occupational injuries and other related losses. However, suffering greatly from incomplete hazard identification and inaccurate probability analysis, risk analysis is considered the weakest link in risk management, which seriously affects risk evaluation and control in complex workplaces. To improve the performance of hazard identification and analysis, a data-driven risk analysis approach is established, which consists of an improved equivalent class transformation (Eclat) algorithm, a sliding window model, and a change pattern mining algorithm. Through this approach, a large number of historical hazard records are transformed into association rules composed of object keywords and deviation keywords, and information such as potential keyword combinations, conditional probabilities of potential deviations, and the change pattern of potential hazards can be extracted. The function of the approach is threefold. Firstly, the data-driven risk analysis process is designed to identify the association rules between different hazard keywords. Secondly, Eclat algorithm is optimized to calculate the frequency and probability of potential hazards, which is conducive to improving the accuracy of probability estimation. Thirdly, the change pattern is developed to analyse the hazard change trend to support the cause analysis. A practical application in a Chinese hazardous chemical manufacturer is presented. Case studies have shown that the efficiency of the improved algorithm is increased by 13.68%, and 59.66% of potential hazards can be identified in advance, and relevant information can be extracted to support risk analysis.

There are many techniques for hazard identification and are divided into shortcut, standard and advanced techniques. Among these, HAZOP and What-If techniques are mostly engaged by practitioners in the chemical process industry. Both of these have certain advantages and limitations, i.e., HAZOP is structured, and what-if covers broad range of scenarios. There is no hazard identification method, which can cover a broad range of scenarios and is structured in nature. For this purpose, a new technique namely integrated hazard identification (IHI) is proposed in this article that integrates HAZOP and What-If. The methodology is demonstrated via hazard identification study of urea synthesis section. Risk ranking is used to sort out the worst-case scenario. This worst-case scenario is further studied in detail for quantification that is performed using the ALOHA software. This quantification has assisted to detect ammonia concentrations in nearby control room and surroundings for worst-case scenario. It is revealed that if ammonia pump is not stopped within 10 minutes, concentration inside and outside the control room may reach to 384 ppm and 2630 ppm, compared to 1100 ppm (AEGL-3). Thus the proposed method would be easy, time saving and covers more details and would be handy for practicing engineers working in different chemical process industries.

Although effective risk management during operations relies on risk perception and risk communication, the aviation industry has not systematically considered the contribution of these two constructs to safety events. This study analyzed a representative sample of safety investigation reports (1) to identify the degree to which risk perception and communication and their factors have been influential overall and across various flight operation stages of investigated events, and (2) to examine whether their contribution has changed with time. The analysis of 140 reports showed environmental factors affected risk communication and perception most frequently, whereas emotional and physiological factors were found in the sample with very low frequencies. Also, risk communication and perception and their factors did not appear with the same frequency across the various flight stages, and a few variations were observed over time. The aviation industry could consider the results of this study to steer its efforts toward mitigating the adverse effects of factors related to ineffective risk perception and communication. This could include the inclusion of respective factors in safety reporting schemes, investigation methods and analyses and, possibly, a tailored approach to the various flight stages and targeted risk literacy interventions.

Recent developments in water resource monitoring have increased the demand for the reliable identification of faecal pollution sources, also defined as microbial (faecal) source tracking (MST). Standardized faecal indicator bacteria (SFIB) enumeration does not directly support MST, as SFIB occur in animal and human sources. The aim of this study was to rigorously evaluate the applicability of host-associated faecal genetic MST markers detected by quantitative PCR (qPCR) at representative Austrian water resources (ground-, surface-, raw and treated wastewater, n = 196 samples) with high importance for the water management sector. Groundwater covered a gradient of non- (i.e., deep wells) to surface influenced resources (i.e., karst and shallow wells). In addition, single faecal excreta from humans as well as representative livestock and wildlife species were collected to evaluate the faecal source-specificity and -sensitivity of the MST assays. Genetic MST marker resistance against UV irradiation was evaluated in on-site ground and wastewater treatment installations. Bacteroides-based human- (HF183II, BacHum), ruminant- (BacR), and pig-associated (Pig2Bac) MST marker qPCR quantification was performed in concert with cultivation of E. coli, intestinal enterococci, and Clostridium perfringens (SFIB diagnostics). The selected MST makers revealed high faecal source identification capacity for the Austrian water compartments and quantitatively reflected the selected faecal pollution gradient. The study also demonstrated that SFIB data can efficiently be combined with MST data to solve previously unanswered questions in water safety monitoring and management (e.g., support pollution source-targeted catchment protection, hazard assessment, and health risk management). Further research and development needs are discussed to exploit the full power of MST technology. In conclusion, this study illustrates the capacity of molecular faecal pollution diagnostics to revolutionize water quality testing in the decades to come.

Background. Understanding disaster risk is the first priority for action based on the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR), and hazard assessment is the first step in the assessment of disaster risks. Therefore, assessing health-oriented hazards is the first measure in disaster risk assessment in the medical universities area in Iran. This article introduces a national experience and results obtained from designing a national tool for defining and assessment of health-oriented hazards in Iran. Methods. In the present study, a National Health-Oriented Hazard Assessment tool (NHHAT) was developed by experts and implemented by the Iranian Ministry of Health for gathering data according to frequency, probability, magnitude, and vulnerability of the hazards to identify the first ten hazards of medical universities in the two decades ago (2000–2021). Finally, the top 20 health-oriented hazards were identified among the ten hazards reported by each university. Results. According to the findings, the four most important hazards were road traffic accidents, earthquakes, drought, and seasonal floods. Nevertheless, the hazards such as desertification, tunnel events, soil liquefaction, mass population movement, and sea progression were among the rarest ones reported in the medical universities in Iran. Conclusion. Many functional aspects of disaster risk management depend on the realistic and accurate information related to the main elements of risk, especially the probable hazards in the communities. The comprehensive hazard assessment can only provide such information using context-bond tools. This is an applied study and a national implementation to fulfill the priority of the Sendai framework (i.e., understanding disasters risk) in Iran. It is suggested that other countries should also compile standard tools to explore the hazards for designing up-to-date hazard maps.

Backfill coal mining, an environmentally friendly practice, is widely used to mitigate the hazards of water and sand inrushes (WSIs) and surface subsidence. In this study, a quantitative analysis for assessing the hazard reduction of WSIs due to backfilling was established that combines a modified analytic hierarchy process (AHP) with a geographic information system (GIS) and entropy. The analytical and quantitative model consists of four criteria and eight factors for the hazard assessment target layer. The weight of each index is comprehensively determined based on the modified AHP and entropy. Then, a hazard zone map that is color-coded is overlay analyzed based on GIS to comparatively evaluate the degrees of hazard from WSI due to longwall caving and paste backfill. The Taiping coal mine was used as a case study to validate the accuracy of the evaluation model. The results indicate that paste backfilling can effectively reduce the influence of the overburden failure height on WSI hazards. The highest hazard index of backfill mining was significantly reduced, and high-hazard and very high-hazard zones of longwall caving were transformed into low-hazard or even no-hazard zones. The evaluation results are in good agreement with actual engineering practices and offer an effective reference for practical engineering projects and prevention and control measures for safe mining under loose sand aquifers.

У статті описано підхід до оцінки ступеня небезпеки ерозійно-корозійного зносу елементів трубопроводів АЕС із вуглецевих сталей. З метою апробації запропонованого підходу проведено комплекс розрахунково-аналітичних робіт, зокрема: а) проаналізовано існуючий підхід до оцінки ступеня небезпеки ерозійно-корозійного зносу на АЕС України; встановлено його недоліки; б) розроблено алгоритм оцінки ступеня небезпеки ерозійно-корозійного зносу з використанням експрес-оцінки та уточненої процедури; в) верифіковано розрахункові моделі співставленням з іншими існуючими розрахунковими моделями та експериментальними даними з метою демонстрації їх коректності; г) за розробленим підходом виконано оцінку ступеня небезпеки ерозійно-корозійного зносу систем трубопроводів енергоблоків №№ 1 та 4 Відокремленого підрозділу «Запорізька атомна електростанція», виявлених у період експлуатації з 2012 року по 2016 рік. Розроблений підхід дозволяє: 1) оцінювати ступінь небезпеки ерозійно-корозійного зносу не тільки в окружному напрямку поперечного перерізу труби внаслідок дії внутрішнього тиску (підхід, що базується на вимогах ПНАЭ Г-7-002-86, щодо визначення допустимої товщини стінки бездефектного трубопроводу), але й уздовж осі трубопроводу від одночасної дії внутрішнього тиску, осьового зусилля та моментів згину. Такий підхід особливо актуальний для трубопровідних систем, які, переважно, мають складну просторову конфігурацію, що призводить до виникнення в них осьових зусиль та моментів згину внаслідок дії масових характеристик трубопроводів та арматури, температурних, сейсмічних впливів тощо; 2) оцінювати ступінь небезпеки ерозійно-корозійного зносу не тільки за його глибиною (підхід ИН-Т.0.03.190-14), а й з урахуванням довжини та ширини ерозійно-корозійного зносу. На відміну від існуючого підходу, це дозволяє коректніше оцінювати ступінь небезпеки ерозійно-корозійного зносу.

Rapid urbanization has caused severe deterioration of air quality globally, leading to increased hospitalization and premature deaths. Therefore, accurate prediction of air quality is crucial for mitigation planning to support urban sustainability and resilience. Although some studies have predicted air pollutants such as particulate matter (PM) using machine learning algorithms (MLAs), there is a paucity of studies on spatial hazard assessment with respect to the air quality index (AQI). Incorporating PM in AQI studies is crucial because of its easily inhalable micro-size which has adverse impacts on ecology, environment, and human health. Accurate and timely prediction of the air quality index can ensure adequate intervention to aid air quality management. Therefore, this study undertakes a spatial hazard assessment of the air quality index using particulate matter with a diameter of 10 μm or lesser (PM10) in Selangor, Malaysia, by developing four machine learning models: eXtreme Gradient Boosting (XGBoost), random forest (RF), K-nearest neighbour (KNN), and Naive Bayes (NB). Spatially processed data such as NDVI, SAVI, BU, LST, Ws, slope, elevation, and road density was used for the modelling. The model was trained with 70% of the dataset, while 30% was used for cross-validation. Results showed that XGBoost has the highest overall accuracy and precision of 0.989 and 0.995, followed by random forest (0.989, 0.993), K-nearest neighbour (0.987, 0.984), and Naive Bayes (0.917, 0.922), respectively. The spatial air quality maps were generated by integrating the geographical information system (GIS) with the four MLAs, which correlated with Malaysia's air pollution index. The maps indicate that air quality in Selangor is satisfactory and posed no threats to health. Nevertheless, the two algorithms with the best performance (XGBoost and RF) indicate that a high percentage of the air quality is moderate. The study concludes that successful air pollution management policies such as green infrastructure practice, improvement of energy efficiency, and restrictions on heavy-duty vehicles can be adopted in Selangor and other Southeast Asian cities to prevent deterioration of air quality in the future.

This study was conducted to evaluate the current implementation level of Hazard Analysis and Critical Control Point (HACCP) prerequisites adopted in poultry meat production and processing in Khartoum State, Sudan. To achieve the goal, a cross sectional study was conducted. Data and samples were collected from January to September 2018 from 12 close system broiler slaughterhouses according to Non-Probability Multistage Cluster Sampling Method in Khartoum, Khartoum North (Bahri), and Omdurman localities (4 farms from each). A standardized questionnaire was conducted for slaughterhouses (12 for each) to investigate the current status of implemented HACCP prerequisites. One hundred and eighty swab samples were taken from different sites in the slaughterhouses’ halls (surfaces, workers’ hands, boots, water, and chillers) followed by 240 swab samples collected from broiler carcasses after 4 process steps (defeathering, evisceration, washing and chilling). After bacterial culturing, isolation, and identification, all collected Data were subjected to descriptive and analytical statistic such as Chi square and ANOVA using SPSS. Low level of good practices in slaughterhouses was shown regarding programmed documented personal hygiene staff training and qualification for responsibilities 50.0% (n=6), preventative maintenance 41.7% (n=5), and appropriate use of personal facilities 58.3% (n=7). In addition to that, 66.7% (n=8) of examined premises showed difficulty in cleaning, inadequate ventilation and 33.3% (n=4) showed lack of sanitary facilities (dispensers, personnel changing rooms, toilets, washing basins). Unhealthy practices and habits were observed in majority of workers during work such as not washing hands before entering production areas, smoking, and eating and drinking in processing areas, beside low level of medical check in two thirds of them 66.7% (n=8). Bacterial growth was shown in 60.0% (n=108) and 58.80% (n=141) of slaughterhouses’ halls samples and meat samples respectively. There was significant difference between state of growth of slaughterhouses’ halls sample and farm location (χ2=7.22 and P-value = 0. 027) while a high significant difference in association between state of growth of meat samples and slaughterhouses’ location (χ2=43.02 and P-value=0. 000) was revealed. The Gram positive and Gram negative isolates were mostly detected in workers’ hands 19.60% (n=56) and 4.36% (n=12) respectively. The difference between growth state of bacteria in slaughterhouses’ halls samples and sample sites was highly significant (χ2=30.92 and P-value=0.000) and the highest growth was shown in workers’ hands. On the other hand, most of Gram positive and Gram negative bacteria in processing steps were detected after defeathering 14.40% (n=41) and evisceration 2.49% (n=7) steps. However, there was no significant difference resulting from association of state of bacterial growth of poultry meat samples and different process steps (χ2=5.14 and P-value=0.162). Slaughterhouses’ halls samples and meat samples were found contaminated with harmful pathogenic bacteria such as Salmonella spp. 1.41% (n=4), Escherichia coli 9.51% )n=27(, Staphylococcus aureus 7.75% (n=22), Citrobacter frundi 1.41% (n=4), and Micrococcus kristanae 8.75% (n=24). In conclusion, effective adoption of HACCP PRPs and biosecurity measures in Khartoum State has not been given serious attention beside lack of knowledge, resources, and absence of official authority’s role. Absence of proper “Farm to Table” hygiene policy in broiler production negatively affects poultry meat hygiene and consequently threatens public health. Therefore, formulation of suitable procedures and regulations by official authorities for implementing HACCP PRPs and biosecurity measures are needed to ensure poultry meat hygiene from primary stages of production till the end product.

In this paper, we present an open-source end-to-end Python tool for ground motion record selection and scaling for non-linear dynamic analysis of structures. The tool, named haselREC (HAzard-based SELection of RECords), has been formulated to be executed after performing a probabilistic seismic hazard and disaggregation analysis with OpenQuake, an open-source hazard and risk calculation engine developed by the Global Earthquake Model (GEM) Foundation. In addition to common intensity measures, such as peak ground acceleration and spectral acceleration, haselREC can perform ground motion record selection using average spectral acceleration, which can be advantageous when assessing multiple structures and to account for uncertainty on the conditioning response period. Moreover, haselREC can be directly linked to the web services of the European Strong Motion database for automatic download and scaling of records. The Python tool was designed to be modular, which facilitates its integration in third party scripts for automated record selection and scaling in hazard analysis studies. Here, we describe the main features of the software package in detail and provide an application example for the regional assessment of existing bridge structures.

Introduction: Cosmetics Europe develops two defined approaches (DAs) for eye hazard identification, that is, addressing serious eye damage (Cat. 1), eye irritation (Cat. 2), and the absence thereof...

Background The surface mining industry has one of the highest fatality rates among private industries in the United States. Despite recent decreases in the fatality rates of comparable industries, the fatality rate in the surface mining industry has increased. Meanwhile, a lack of safety research in surface mining has hindered efforts to improve safety strategies in the surface mining workplace. Method This study examined quarry workers' hazard identification skills by conducting a case study of a surface mining facility in the Mid-Atlantic region of the United States. Semistructured interviews were conducted with eight quarry workers who were employed at the mine facility. In addition to the interviews, data were collected through field notes, notes from an expert meeting with safety managers, and site photographs to explore quarry workers' safety behaviors in the workplace. Results The results showed that quarry workers identified hazards and improved their safety performance by translating safety knowledge learned from training into practice, acquiring hands-on work experience, learning from coworkers, and sharing responsibilities among team members. Conclusion This study contributes to understanding quarry workers' safe performance beyond what they have learned in safety training to include their interaction with other workers and hand-on experience in the workplace. This study informs practitioners in the surface mining industry to build a safe work environment as they design effective safety programs for employees.

In the last 10 yr, the International Atomic Energy Agency (IAEA) revised its safety standards for site evaluations of nuclear installations in response to emerging fault displacement hazard evaluation practices developed in Member States. New amendments in the revised safety guidance (DS507) explicitly recommend fault displacement hazard assessment, including separate approaches for candidate new sites versus existing sites. If there is insufficient basis to conclusively determine that a fault is not capable of surface displacement at an existing site, then a probabilistic fault displacement hazard analysis (PFDHA) is recommended to better characterize the hazard. This new recommendation has generated the need for the IAEA to provide its Member States with guidance on performing PFDHA, including its formulation and implementation. This article provides an overview of current PFDHA state-of-practice for nuclear installations that is consistent with the new IAEA safety standards. We also summarize progress in an ongoing international PFDHA benchmark project that will ultimately provide technical guidance to Member States for conducting site-specific fault displacement hazard assessments.

Based on the extensive material, approaches to assessing the risk of accumulation of heavy metals in vegetable crops grown in open and protected ground, including hydroponics, are considered. A scheme for performing risk assessment is proposed, including such stages as hazard identification, exposure assessment, the dose-effect estimates, risk characterization, and risk management. For each stage, model approaches to quantifying the risk are presented, and examples of the characteristics of non-carcinogenic and carcinogenic risk in different regions are given when consuming vegetable crops contaminated with HM. It is shown that the risk of accumulation of HM in vegetable crops can be managed with the help of various strains of microorganisms that promote both the immobilization of these metals in the soil and prevent their entry into the marketable part of vegetable products.

Trees are generally harmed by multitude factors consisting of ecological condition and anthropogenic pressures in the cities. This study compares the multilayer perceptron (MLP) neural network, radial basis function neural network (RBFNN) and support vector machine (SVM) models for Platanus orientalis trees failure prediction in urban forest ecosystems by a detailed field survey of P. orientalis trees issues. Therefore, we recorded 12 variables in 500 target trees which are categorized into in to two groups: (1) tree variables, and (2) tree defects and disorders. We developed the tree failure prediction model (TFPM) to predict the year of trees failure by artificial intelligence techniques. Compared to MLP and RBFNN, the SVM model represents the highest entity of R2 in training (0.99), test (0.986) and all (0.989) data sets. In sensitivity analysis, the classes of tree hazard are sensitive to three variables which are: soil depth, cracks and cavities, and wind protected, respectively. The results of SVM modeling, with 97.5% classification accuracy, in comparison with MLP (94%) and RBFNN (87.9%), in test samples, introduced TFPMSVM as an ecological failure hazard assessment model for P. orientalis. Such as other prediction model in urban trees management, TFPMSVM was developed for urban forest and green spaces managers to assess the hazard of old P. orientalis trees failure for precaution actions planning timely. TFPMSVM as an environmental decision support system is applicable where the old and hazardous trees could be rehabilitated or removed before any unexpected failure occurs.

There is growing interest in the use of systems-based risk assessment methods in Human Factors and Ergonomics (HFE). The purpose of this study was to test the intra-rater reliability and criterion-referenced concurrent validity of three systems-based risk assessment approaches: (i) the Systems-Theoretic Process Analysis (STPA) method; (ii) the Event Analysis of Systemic Teamwork Broken Links (EAST-BL) method; and, (iii) the Network Hazard Analysis and Risk Management System (Net-HARMS) method. Reliability and validity measures were obtained using the Signal Detection Theory (SDT) paradigm. Whilst STPA identified the highest number of risks, the findings indicate a weak to moderate level of reliability and validity for STPA, EAST-BL and Net-HARMS. There were no statistically significant differences between the methods across analyses. The results suggest that there is merit to the continued use of systems-based risk assessment methods following a series of methodological extensions that aim to enhance the reliability and validity of future applications. Practitioner summary The three risk assessment methods produced weak to moderate levels of stability and accuracy regarding their capability to predict risks. There is a pressing need to further test the reliability and validity of safety methods in Human Factors and Ergonomics.

Aiming at the problem of large error and long time of early warning response in the traditional system, this paper designs a hazard identification early warning system based on random forest algorithm in underground coal mine. By random classification decision forest created dangerous content in different areas of the downhole information input into the decision tree as a test sample, according to the result of the output of the leaf node determine the risk level of decision trees, and USES the high precision of decision forest classification ability the threat level assessment test sample, radically reducing hazards identification error. Then, based on the evaluation results, combined with the threshold value of warning criteria to identify the gas exceeding limit area, and determine the fire source warning level, so as to realize the hazard source identification and warning. The simulation results show that the average hazard location identification error of the system is only 4.1%, and the warning response time can be controlled within 9 s.

Wastewater treatment plant (WWTP) is considered one of the most dangerous sectors in the industrial field. Many workers still die each year due to poor awareness of workers about occupational health. Safety performance became important for different projects in the industrial field. Safety performance is concerned about the general behaviour of the workers in the worksite, usually, the performance can be evaluated by managing systems and identifying health hazards that can happen in the field. Many researchers tried to summary different methods to rate the safety performance. This paper describes the significant topics in risk assessment and hazard identification that have been done in the field of wastewater treatment plant (WWTP). The collected investigations have been arranged and sorted in this paper to set up strong basic information for the works in the field. Unlike the other studies, this paper is focused mainly on the safety performance, health hazard and risk assessment in the wastewater treatment plant (WWTP). This study has found the specific factors that can affect the performance of workers since the workers in general workplaces are facing difficulties in determining the hazards that can be resulted in serious problems such as injuries and death.

Work accidents are things that must be avoided, so that's not inflicted loss on the company and the workers. However, several workers still not pay attention to occupational health and safety regulations and in the work area still found several potential hazards. The research is conducted at PT Pindo Deli Pulp and Paper Mills Indonesia in Karawang Regency and focuses on preventive and corrective maintenance activities that prevent paper machine breakdown. The purpose of this study is to measure how big the potential hazard and impact by using Hazard and Operability Study (HAZOP) method. This method is a systematic study, which aims to find the factors that causing work accidents and find out how big the potential accidents and their impacts. The data is collected by distributing questionnaires to the employee. The results show that hazards caused by the work area and the workers themselves are 18% and 82%, respectively. Based on the severity, the number of extreme, high, medium and low risk hazards are 1, 8, 1 and 1, respectively.

To ensure the safety of ‘Fura da nono‘, a popular beverage widely consumed in the university campuses within Northern Nigeria, the HACCP system need to be applied. The study was carried out to assess the biological hazards associated with consumption of ‘Fura da nono‘ using the Hazard Analysis and Critical Control Point system. Flowchart of the production processes was drawn and samples were collected and analyzed at different stages of production for total aerobic and coliform plate counts and fungi isolation. The results showed that grinded millet have a total aerobic plate counts (TAPC) ranged from 6.72 log10 to 6.98 log10 cfu/mg, while the total coliform counts (TCC) ranged from 5.32 log10 to 5.45 log10 cfu/mg. After sieving, the (TAPC) ranged from 6.45 log10 to 6.99 log10 cfu/mg, while the (TCC) ranged from 5.23 log10 to 5.59 log10 cfu/mg. All samples were positive for fungi growth after grinding and sieving. The result of (TAPC) after addition of hot water but before molding into shape ranged from 2.99 log10 to 3.23 log10 cfu/mg, while the (TCC) ranged from 0.53 log10 to 0.86 log10 cfu/mg. After molding the millet dough into shape the (TAPC) ranged from 2.98 log10 to 3.43 log10 cfu/mg, while the (TCC) ranged from 0.78 log10 to 2.60 log10 cfu/mg. All the samples collected after adding boil water and molding the millet dough into shapes turn out to be negative for fungi growth. The risk analysis, showed high risk at the level of millet grinding, molding of dough, blending with yoghurt and packing into containers. the study revealed that the stages post boiling of the ingredients with water and molding of the dough into round shapes are the most prone to contamination as such considered as critical control points in ‘fura’ production. It was concluded that there were high bacteria counts in ‘fura’ production with dangers of food borne illnesses when consumed. There is a need to improve hygienic practices especially at the critical points observed in the study.

In India, the Firework industries are mostly located in and around Sivakasi, Tamil Nadu. Right from the initial phase of manufacturing till the transportation and storage of fireworks in the stores, risk to life and property is high so these industries are known to be highly hazardous industry. Fire is one of the major hazards which occur due to natural or man-made causes. The hazards in firework industry has been identified by walk around audit and the risk is quantified by Hazard Identification and Risk Assessment (HIRA) method for every task. After quantifying the risk suitable control measures are suggested to reduce the high-level risk into as low as possible. The risk zones as identified through the task-based quantification, helps the safety engineers to make necessary measures for the health and safety of the workers.

The article intended to provide a concise and affluent proposal for the development of HACCP plan in the production of ready-to-drink Fura-da-Nono using information from reputable literature and guidelines recommend by food regulatory bodies. Poor personal hygiene, low quality raw materials and the rudimentary operations involved in the traditional processing of ready-to-drink Fura-da-Nono accounts for inconsistent quality, shorter shelf-life, poor hygiene and unacceptable qualities. During processing, materials are exposed to filthy processing environment, contaminated water, unclean processing equipment and contaminated packaging and storage containers. Application of HACCP guidelines in the production of ready-to-drink Fura-da-Nono will significantly improve its safety by assuring acceptance of only good quality raw materials and ensuring adequate processing along the production chain. These will not only guarantee the safety of the finished product, but will also ensure better nutritional qualities and acceptable organoleptic properties. Keywords: HACCP; Traditional food; Fura; Fura-da-Nono

Ultraviolet (UV) filters used in sunscreens are among the anthropogenic substances that may enter the marine environment by both indirect (via wastewater) and direct pathways (leisure activities). Owing to the recent global decline in coral population, the impact of those UV filters on the coral health is currently under increased investigation. First results from scientists suggest that some of the filters may be toxic to various coral life stages, but an initial cross comparison with existing data from other freshwater organisms does not indicate that corals are specifically more susceptible to UV filters than other standard species. In fact, the available data leading to this conclusion is still vague and based on toxicity and bioaccumulation tests with corals, which are both still at the research stage. To facilitate a proper hazard assessment, robust experimental procedures for coral ecotoxicological studies are considered mandatory. In other words, additional steps should be taken to standardize and validate such new test systems to generate reliable results, which then can be used in regulatory decision making. Furthermore, to facilitate a more detailed and site-specific environmental risk assessment in the marine area, an application-based exposure scenario must be developed. Until these data and tools become available, environmental hazard and risk assessments may be carried out using existing data from freshwater organisms and existing tonnage-based exposure scenarios as a potential surrogate. Integr Environ Assess Manag 2021;17:926-939. © 2021 SETAC.

The international and national directives and legislation requires to perfom validated in vitro alternative methods to animal testing of chemicals and mixtures for predictible and precise evoluation of toxicity in human. The regulatory agencies require the hazard assessment on skin and ocular as reported by the United Nations, Globally Harmonized System (UN GHS) of Classification and Labeling of Chemicals. To address this need and investigate the usage of alternative methods, the five representative chemical mixtures were prepared in different compositions and their toxicity was evaluated using in vitro validated EpiDerm™ SCT for skin corrosion, EpiDerm™ SIT for skin irritation, and EpiOcular™ OCL for eye irritation. The tested chemical mixtures 1 and 3 were found corrosive for skin and irritant for both skin and eye. They were identified in the category 1 according to UN GHS. The tested chemical mixtures 2, 4, and 5 were found to be neither corrosive nor irritant to the skin and eye. They were identified in the UN GHS No Category. The potential usage of in vitro Reconstructed Human Epidermis and Cornea-like Epithelial as a replacement to animal testing contributed significantly to classify the ocular and skin irritation/corrosion of liquid and solid chemical mixtures and to comply with the regulatory testing requirements. This study confirm that the use of alternative assays instead of conventional in vivo animal test methods could be very reliable and accurate tool to evaluate the skin and eye irritation/corrosion for hazard identification of chemical mixtures.

PurposeClimate change and global warming pose a serious threat to the community as deglaciating environments trigger glacial lake outburst floods (GLOFs). The Sendai framework underpins the role of disaster risk reduction (DRR) for sustainable development, thereby calling for the development of GLOF hazard and risk assessment procedures. This study aims to delineate the enablers of GLOF risk and establish a contextual relationship between them.Design/methodology/approachThe risk enablers are identified from the extant GLOF literature, and the experts from disaster management area are consulted to explore the underlying contextual relationship among them. An interpretive structural model is developed from the responses to analyze the contextual relationships among the risk enablers.FindingsThe interpretive structural modeling results manifest that seismic activity, temperature and precipitation events, and proximity are key drivers that trigger flash floods from the lakes and an effective assessment of these triggers may contribute significantly to GLOF risk mitigation.Originality/valueThe study models the complex relationship among the risk enablers for a glacial flood hazard that find commonality across all geographic contexts. The findings provide the practitioners of DRR useful insights into these factors and their subsequent impact on others, while conducting hazard assessment of glacial lakes that may contribute to the sustainable development of settlements lying downstream to glacial lakes.

How societies organize themselves to respond to cascading impacts exacerbated by climate change will help define the future of disaster planning, mitigation, response, and recovery. Current emergency management risk analyses focus on identifying a broad array of threats and hazards that may affect an area. However, there is limited attention and understanding of the totality of hazard impacts, the relationship of consequences across disasters, and the dangers of not addressing critical capabilities necessary to rapidly managing consequences—including the potential to create new incidents within incidents. Through a focused review of the related literature and guiding policy documents, this study aims to provide a cascading consequence-based framework that can support emergency managers in the analysis of their jurisdictional risks, development of emergency operations plans, and decision-making. Results include the identification of an alternative framework to identify cascading networks, the creation of a supplementary model for downstream risk assessment, and refined Threat and Hazard Identification and Risk Analysis (THIRA) outputs for improved grant allocation. The proposed framework has the potential to help organizations factor both conspicuous and downstream consequences into their Emergency Operations Plans in the planning and mitigations phases. This proposed refinement, which looks deeper into the progression of a disaster, has both national and international implications.

Purpose Conditional survival (CS) and failure hazard estimations can provide important dynamic prognostic information for clinical decision‐making and surveillance counseling. The current study aimed to investigate the CS and dynamic failure hazard in non‐metastatic nasopharyngeal carcinoma (NPC) treated with intensity‐modulated radiotherapy (IMRT). Methods Conditional overall survival (COS) and progression‐free survival (CPFS) estimates adjusted for age and gender against each AJCC 8th stage were calculated. Multivariable Cox regression (MCR) models were fitted in the entire population at baseline and subsequently separate MCR models were fitted in patients who have maintained event‐free time of 1 to 10 years to generate respective hazard ratio (HR). Annual hazard rates of death and progression over 10 years for each stage were also estimated. Results A total of 1993 patients were eligible for analysis. The estimated 5‐year OS and PFS for entire cohort were 79.0% and 70.7% at initial diagnosis. After 5 years of event‐free follow‐up, additional 5‐year COS and CPFS increased to 85.9% and 85.5%, respectively. Stage I/II maintained dramatically favorable CS and low hazard (< 5%) of death and progression over time. Relative to stage I/II, stage III manifested non‐significantly higher failure hazard for the first 3 years of survivorship and approached to similar level of stage I/II afterwards. Stage IVA presented most impressive improvement in terms of both COS (∆=9.8%) and CPFS (∆ = 16.8%) whereas still drastically inferior to that of stage I‐III across all conditional time points. After 4 years of follow‐up, progression hazard of stage IVA became relatively steady of approximate 6%. Conclusions Survival prospect of non‐metastatic NPC improves over years with distinct dynamic patterns across stages, providing important implications for personalized decision‐making in terms of both clinical management and surveillance counseling. Stage‐dependent and hazard‐adapted clinical management and surveillance are warranted., This study aimed to investigate the conditional survival (CS) and dynamic failure hazard in non‐metastatic nasopharyngeal carcinoma (NPC) treated with intensity‐modulated radiotherapy (IMRT). Survival prospect of non‐metastatic NPC improved over years with distinct dynamic patterns across stage, providing important implications for personalized decision‐making in terms of both clinical management and surveillance counseling. Stage‐dependent and hazard‐adapted clinical management and surveillance are warranted.

The safety assessment process tailored to Remotely Piloted Aircraft Systems (RPAS) applications has been discussed briefly. The modified Hazard Reference System for STANAG 4703 Category UAV including Non Safety Effect (NSE) severity category has been proposed. The Functional Hazard Analysis (FHA) for small Unmanned Aerial Vehicle (UAV) Structural Health Monitoring (SHM) system has been conducted.

Occupational Health & Safety (OHS) is not only important for improving the social security and welfare of its workers but far from that, K3 has a positive impact on the sustainability of employee work productivity. In term of safety, the production department of PG Kremboong still bring some risks that may cause work accidents, such as the leaks in the evaporator and juice heater body that frequently happened in the processing department. The hazard identification assessment uses the RPN (Risk Priority Number) method where each risk-causing factor is assessed by its value of severity, frequency or probability (occurrence), and detection, then illustrated with a Pareto Diagram to determine the most dominant problem. and using the five why's analysis method to analyze the root causes of the problem in order to obtain a solution. The most dominant risk in PG. KREMBOONG is a leak in the evaporator body that hits the worker and a leak in the juice heater body, based on RPN values which reached 36 and 27.

Today, the use of risk assessment methods in various industries is expanding so that there are currently more than 70 types of different risk assessment methods in the world. These methods are usually used to identify, control and reduce the consequences of risks. The main methods of risk assessment are appropriate methods for risk assessment and their results can be used for management and decision-making to control and reduce its consequences. The purpose of this study is to identify and evaluate the risks to safety, health and the environment and to provide proposed and corrective solutions to reduce or eliminate HSE risks using the HAZID method. This descriptive cross-sectional study was performed for 4 months to identify the risks. For this purpose, a list of possible safety, health and environmental risks was prepared and the risk was evaluated by HAZID technique. In total, 5.15% of the identified risks are unacceptable, 20.62% are undesirable, 50.51% are acceptable, but 23.72% of the need for revision is minor. The results of this research include the implementation of measures such as safety training - professional training - inspection monitoring system - personnel safety management - preventive maintenance system management and forming a safety audit team - establishing regular House Keeping programs, etc. in identifying and Controls identified risks.

It has been 15 years since the catastrophic 2005 Kashmir Mw 7.6 earthquake induced thousands of landslides in northern Pakistan and Kashmir. There have been many studies on various aspects of the landslides triggered by the earthquake, such as the mechanisms of individual large landslides, regional seismic landslide inventory mapping, spatial distribution pattern, susceptibility and hazard assessment, and landslide evolution, which provide beneficial scientific results. However, there is currently no summary and generalization of these studies for ready use of the researchers to fully understand the information of the landslide caused by the earthquake. This study comprehensively reviews and summarizes the important results obtained from published data on the landslides. The seismogenic and regional active faults, fragile lithological condition, heavy rainfall, anthropogenic activities, and steep terrain were considered as main controlling factors for the landslide occurrence. Studies on landslide evolution reveal that vegetation on most of the landslides was partially recovered after the earthquake, while slope failures along roads and drainages increased. In the affected area, landslides are still a great threat to communication networks and communities. Despite many past studies, there is still a need or in-depth research using more precise methods to understand the mechanism, hazard, and risk assessment, numerical simulation, landslide risk management and mitigation, and continuous or temporal monitoring of landslides in the affected area. Combined with high-quality data on landslides triggered by other earthquake events in recent years, the study points out the prospects of Kashmir earthquake-induced landslides and summarizes the future challenges of earthquake-triggered landslides research, including accuracy of inventories, the precision of landslide, susceptibility methods, prevention and control of landslide, and landslide hazards and risk assessment. This review can provide a reasonable scientific research and disaster prevention and mitigation strategy and scheme for landslides triggered by a large earthquake in the future.

Compiling an inventory is a fundamental step for carrying out assessments of landslide hazards. However, data in sufficient quantity and quality are not always available. Thus, this study puts forward an approach for drawing up a landslide inventory using textual data from telephone records, and for mapping hazards of landslides in an urban area. Forty thousand seven hundred ninety-two textual records and the naive Bayes algorithm were used to classify them, and these form the landslide inventory. After creating the inventory, the random forest algorithm with 12 conditioning variables was used to map landslide hazards. The text classification model obtained an accuracy of 0.8671 and a Kappa index of 0.8038. The hazard mapping model obtained accuracy of 0.9503 and an AUC (area under the curve)-ROC (receiver operating characteristics) of 0.9870. The results produced by the model were also compared with real landslides reported in news reports and were shown to be close to what had happened, thus demonstrating the ability of the proposed approach to predict landslides. Finally, the proposed approach can be used in simulation environments, thereby supporting strategic decision-making associated with hazard analysis.

Occupational health analyses the job and health relationships, in particular the chronic health influence of chemicals to workers. In most of the previous works for inherent hazards assessment, the focus was put on safety aspect; with very minor elements of health are taken into account. Most of the earlier design stage assessment methods focus only on the hazard identification and assessment part; but not the risk mitigation element. This study aims to create an assessment method that integrate the existing inherent hazards assessment index which is the Inherent Occupational Health Index (IOHI) with suitable Layers of Protection (LOP) strategies for each of the enlisted hazard parameters. The IOHI considers the health hazards existed during research and development stage. Risk prevention and minimization strategies are proposed according to each hazard parameters and levels. Scores are also assigned to each LOP strategies. Integration of occupational health hazard assessment index with the prevention strategy is achieved through a designed formula. The proposed method provides users with list of suitable counter measures for each hazard parameter, and each option offers varied level of effectiveness. The proposed index is applied to two process routes of methyl methacrylate production which are ethylene via propionaldehyde based route (C2/PA) and propylene based route (C3). The results revealed that the process routes are in the category of “safe” when the proposed control strategies are evaluated in the assessment.

Seismic inversion is a fundamental tool in geophysical analysis, providing a window into Earth. In particular, it enables the reconstruction of large-scale subsurface Earth models for hydrocarbon exploration, mining, earthquake analysis, shallow hazard assessment, and other geophysical tasks.

The fracture-induced electromagnetic radiation (FEMR) method is a promising geophysical method for the monitoring and early warning of coal-rock burst disasters. At present, the time-series characteristics of FEMR data are primarily used for rock burst monitoring and early warning. However, these rock burst precursor signal identification and hazard warning methods need further development. The progress made in the field of deep learning provides a new method for the identification of rock burst warning signals and the realization of intelligent early warning. In this paper, based on a deep learning algorithm, a method for identifying rock burst precursor FEMR signals is proposed. Based on bidirectional long short-term memory recurrent neural networks, this method trains and validates the model by analyzing a large number of normal FEMR signals and rock burst FEMR precursor signals. The input of the model is the FEMR data sequence, and the corresponding output is the hazard identification result. Upon the completion of training and validation, the model can perform automatic/intelligent shock hazard precursor signal recognition and quickly and accurately provide rock burst hazard early warning without requiring parameter adjustment and manual intervention. The results obtained showed that the rock burst precursor signal recognition method based on the recurrent neural network responds well to the rock burst hazard and can capture information regarding impact hazards in advance. Therefore, it is of great significance with regard to accurate rock burst monitoring and early warning.

Near-fault (NF) earthquakes cause severe bridge damage, particularly urban bridges subjected to light rail transit (LRT), which could affect the safety of the light rail transit vehicle (“light rail vehicle” or “LRV” for short). Now when a variety of studies on the fault fracture effect on the working protection of LRVs are available for the study of cars subjected to far-reaching soil motion (FFGMs), further examination is appropriate. For the first time, this paper introduced the LRV derailment mechanism caused by pulse-type near-fault ground motions (NFGMs), suggesting the concept of pulse derailment. The effects of near-fault ground motions (NFGMs) are included in an available numerical process developed for the LRV analysis of the VBI system. A simplified iterative algorithm is proposed to assess the stability and nonlinear seismic response of an LRV-reinforced concrete (RC) viaduct (LRVBRCV) system to a long-period NFGMs using the dynamic substructure method (DSM). Furthermore, a computer simulation software was developed to compute the nonlinear seismic responses of the VBI system to pulse-type NFGMs, non-pulse-type NFGMs, and FFGMs named Dynamic Interaction Analysis for Light-Rail-Vehicle Bridge System (DIALRVBS). The nonlinear bridge seismic reaction determines the impact of pulses on lateral peak earth acceleration (Ap) and lateral peak land (Vp) ratios. The analysis results quantify the effects of pulse-type NFGMs seismic responses on the LRV operations' safety. In contrast with the pulse-type non-pulse NFGMs and FFGMs, this article's research shows that pulse-type NFGM derail trains primarily via the transverse velocity pulse effect. Hence, this study's results and the proposed method can improve the LRT bridges' seismic designs.

Background Over 800 pesticides are registered for use in the United States. Human studies indicate concern that some pesticides currently in use in large quantities may also pose a carcinogenic hazard. Our objective is to identify candidates for future hazard evaluations among pesticides used in high volumes in the United States and also classified as potential carcinogens by U.S. Environmental Protection Agency (USEPA). We also identify data gaps where further research is needed. Methods We used a systematic, two-tiered review approach to prioritize pesticides. First, we identified currently registered pesticides classified by USEPA as “possible”, “suggestive”, or “likely” human carcinogens. Among these, we selected pesticides USEPA has listed as commonly used by volume in at least one sector (agriculture, home and garden, or industry, commercial, and/or government), and those without a published hazard evaluation in the past 5 years. Second, we searched primary literature databases for peer-reviewed human cancer studies reporting pesticide-specific data published since the last USEPA carcinogenicity evaluation for each pesticide, and created evidence maps of the number of studies meeting our criteria for each identified pesticide. No evaluation of study results or risk-of-bias assessments were conducted. Results We identified 18 pesticides meeting our selection criteria, 16 pesticides had information from human cancer studies published after their initial carcinogenicity review. Of these, eight pesticides had at least three studies for one or more cancer sites: carbaryl, dichloropropene, dimethoate, mancozeb, metolachlor, pendimethalin, permethrin, and trifluralin. A major limitation in the literature revealed a shortage of studies reporting risk estimates for individual pesticides, rather pesticides were grouped by chemical class. Conclusions Our scoping report provides a map of the existing literature on real-world exposures and human cancer that has accumulated on pesticides classified as potential carcinogens by USEPA and used in high volumes. We also illustrate that several pesticides which are “data-rich” may warrant updated authoritative hazard evaluations. Our two-tiered approach and utilization of evidence mapping can be used to inform future decision-making to update cancer hazard evaluations.

In the framework of the multi-disciplinary LIQUEFACT project, funded under the European Commission’s Horizon 2020 program, the LIQUEFACT Reference Guide software has been developed, incorporating both data and methodologies collected and elaborated in the project’s various work packages. Specifically, this refers to liquefaction hazard maps, methodologies and results of liquefaction vulnerability analysis for both building typologies and critical infrastructures, liquefaction mitigation measures as well as cost-benefit considerations. The software is targeting a wider range of user groups with different levels of technical background as well as requirements (urban planners, facility managers, structural and geotechnical engineers, or risk modelers). In doing so, the LIQUEFACT software shall allow the user assessing the liquefaction-related risk as well as assisting them in liquefaction mitigation planning. Dependent on the user’s requirements, the LIQUEFACT software can be used to separately conduct the liquefaction hazard analysis, the risk analysis, and the mitigation analysis. At the stage of liquefaction hazard, the users can geo-locate their assets (buildings or infrastructures) against the pre-defined macrozonation and microzonation maps in the software and identify those assets/sites that are potentially susceptible to an earthquake-induced liquefaction damage hazard. For potentially susceptible sites the user is able to commission a detailed ground investigation (e.g. CPT, SPT or VS30 profile) and this data can be used by the software to customise the level of susceptibility to specific site conditions. The users can either use inbuilt earthquake scenarios or enter their own earthquake scenario data. In the Risk Analysis, the user can estimate the level of impact of the potential liquefaction threat on the asset and evaluate the performance. For the Mitigation Analysis, the user can develop a customized mitigation framework based on the outcome of the risk and cost-benefit analysis.

The dc in a power network might be caused by geomagnetic disturbances that result from either a geomagnetic storm or a high-altitude nuclear detonation. The augmenting trend of inverter-based resources is also acting as a source of small dc injection into the power systems. As the resultant, dc could lead toward a possible power system failure, a myriad of neutral blocking devices (NBDs) have been proposed, where, these devices are installed between the neutral and ground of wye-grounded transformers. However, the electrical safety assessment of these devices is critical prior to adding them to the grid as they might raise serious concerns both for the power equipment and the power system maintenance staff. This work is the first effort toward hazard identification and quantitative risk assessment associated with NBDs. It proposes a risk management framework for augmented electrical safety pertinent to these devices. Later, it analyzes the proposed neutral blocking strategies and highlights the associated risks to the operational safety of these installations, particularly concerning electromagnetic pulse (EMP) attacks, cyber threats, and equipment malfunction. Finally, an ideal NBD operational design is proposed incorporating a variety of risk reduction measure to avoid any hazardous situation arising from such installations. This work could provide a guideline for the electric utilities and academic researchers to consider these safety implications prior to proposing or installing these devices.

The article aims to review the various Ergonomics studies carried out in various domains mainly focusing on preventing the incidents and accidents that will lead to the human factors and ergonomics problems faced by the industrial workers. The various researchers have identified various tools to improve the ergonomic interventions methods to overcome and decrease the incident frequency. Although safety is a very relevant contribution to their ergonomics and human parts, this article is discussed based on the various industrial zones. After that, a clear way of mitigation and prevention methods can be implemented in the workplace. A workplace that deals with the machinery part interacts with the environment with the comfort level zones. Especially in the manufacturing industry, ergonomics is prominent human factors. This article reviewed various methodology proposed in various industries based on the postures and awkward frequencies of each work activity. Each research tool defines different comfort level zones that interact with the workers. Based on that, only future work carried out, and problems were extensively identified by the previous literature.

Background Risk stratification is essential to assess mortality risk and guide treatment in patients with precapillary pulmonary hypertension (PH). We herein compared the accuracy of different currently used PH risk stratification tools and evaluated the significance of particular risk parameters. Methods We conducted a retrospective longitudinal observational cohort study evaluating seven different risk assessment approaches according to the current PH guidelines. A comprehensive assessment including multi-parametric risk stratification was performed at baseline and 4 yearly follow-up time-points. Multi-step Cox hazard analysis was used to analyse and refine risk prediction. Results Various available risk models effectively predicted mortality in patients with precapillary pulmonary hypertension. Right-heart catheter parameters were not essential for risk prediction. Contrary, non-invasive follow-up re-evaluations significantly improved the accuracy of risk estimations. A lack of accuracy of various risk models was found in the intermediate- and high-risk classes. For these patients, an additional evaluation step including assessment of age and right atrium area improved risk prediction significantly. Discussion Currently used abbreviated versions of the ESC/ERS risk assessment tool, as well as the REVEAL 2.0 and REVEAL Lite 2 based risk stratification, lack accuracy to predict mortality in intermediate- and high-risk precapillary pulmonary hypertension patients. An expanded non-invasive evaluation improves mortality risk prediction in these individuals.

From the annual reports of bench marked companies from 2016 to 2018, also from the case studies available approximate 100 disaster cases were analyzed in knowing the possible hazard during drilling. The outcome indicates the change in control measures that is suggested in-order to have safe and healthy work environment at work place which in turn helps in preparing the risk register. In oil industry Risk Assessment needs to be performed on steady and systematic or regular basis. The goal of risk assessment is to identify the hazards, to determine the rating of various risks with controls, to revise the risk controls implementation from the previous sessions of risk assessment. Risk assessment process provides a method for assessing the likelihood of health, safety and environmental impacts. This paper highlights in order to know the details of hazard identification, its assessment and with controls includes: hazard Identification- finding potential hazards, defining the risks and rating which is linked to the hazard based on severity, frequency and probability. Hazard Control -controlling of hazards and associated risks with the hazard. Control Measures- providing information on training, supervision on the hazard, education, analyzing the risks, controls measure for the employees affected by the hazards with evaluation of hazard. Furthermore, an example is shown how to do or calculate the quantitative risk assessment for the various hazards that comes across various operations in hydrocarbon industry.