Accident Factors Research Articles

PERILAKU BERKENDARA SEPEDA MOTOR 150 CC MENGGUNAKAN METODE NATURALISTIC DRIVING STUDY DAN DRIVERS BEHAVIOUR QUESTIONNAIRE

Driver behavior is the most dominant factor in accidents. Almost all accidents are preceded by violations of traffic signs. Through previous accident data, important and useful information can be known. The study aims to analyze two-wheeled motorbike riding behavior using Naturalistic Driving Study (NDS) and determine the influence of age and behavior of 150cc motorbike riders. Data taken from recordings taken by respondents and questionnaires. The results of the regression test to determine differences in age on motorbike rider behavior with a constant value of a = 196.03 show that this figure is a constant number which means that, if it does not involve age (X), the value of riding behavior (Y) is -5, 3956x. The regression coefficient is -5.3945. This figure is minus (-), which means that age (X) has a negative effect on driving behavior (Y).

Ensuring the safety of citizens by rescuers/police officers in case of a chemical attack (accident at a chemical enterprise) in the conditions of marital law

The work deals with the urgent problem of ensuring the safety of life of the population in the conditions of martial law, introduced in Ukraine – providing premedical assistance to victims of a chemical attack (as a result of the action of dangerous factors of a man-made accident at a specialized chemical enterprise).
 The potential possibilities of means of defeating the units of the chemical forces of the aggressor state are analyzed, the cases of the use of chemical weapons by the occupiers in relation to both the units of the Armed Forces of Ukraine and the civilian population during the war in Ukraine, as well as the real situations of destroyed chemical plants in many regions of the country, are described and summarized.
 On the basis of the analysis of operational publications in the Internet and scientific works of a great number of scientists, the general algorithm of rescue actions during the evacuation of victims of a chemical attack/accident (workers/residents) was considered, modern approaches in the order of providing premedical aid both at chemical enterprises and at home conditions when people are injured by the most common chemical substances were clarified, recommendations concerning compliance by police officers with established rules of conduct at the scene of the incident are offered.
 The main signs that characterize the beginning of a chemical attack in the conditions of martial law and allow the population to identify it quickly are given: 1) chemical alarm signals; 2) features of air raids or enemy artillery fire; 3) simultaneous mass death of small animals, birds and insects.
 The peculiarities of the effect on the human body of such substances as chlorine, ammonia, hydrogen chloride (hydrochloric acid), nitrogen (nitrogen N), nitric acid, oxide (dioxin) of nitrogen, for each of which characteristic symptoms of damage for the victim are determined, the procedure for providing premedical aid to victims in case of damage by them, as well as under the influence of chemical weapons (sarin, phosgene) has been specified.
 Based on the analysis of special literature and the results of the conducted research, a generalization was made regarding the importance of training the population in effective (and therefore safe) actions in the event of a chemical attack by the military units of the aggressor state (a man-made accident at chemical enterprises), the need to observe the established rules of conduct and safety measures in the case of a missile/artillery attack by the occupiers, regardless of the region or territory of fighting actions in Ukraine

Assessment of aviation accident datasets in severity prediction through machine learning

The importance and seriousness of civil aviation safety have become more noticeable due to the intricate advancement of air transportation. It is crucial to apply diverse datasets to evaluate and anticipate the degree of aviation safety. Data on the different causes of accidents can be analyzed and applied to predict and prevent potential accidents. The main goal of this research is to explore how Machine Learning (ML) techniques can be used to identify correlations and connections between various contributing factors in aviation accidents. It applies ML algorithms on datasets extracted from original data sourced from the National Transportation Safety Board (NTSB) of the United States, Transportation Safety Board (TSB) of Canada, and Australian Transport Safety Bureau (ATSB) aviation accident records spanning from January 2008 to January 2023. Initially, this study uses Artificial Neural Network (ANN), Decision Tree (DT), and Support Vector Machine (SVM) models to predict the civil aviation accident rates for the United States, Canada, and Australia data separately. Sequentially, by extracting Common Features (CF) and reclassifying the Common Sub-Features (CSF) of these three countries, a comprehensive model is created. Finally, it evaluates the differences and limitations of these countries' datasets. The results show that the separate models exhibit a higher level of prediction accuracy and lower errors compared to the common models and the best results (81% accuracy) were achieved through SVM.

Psychophysiological components of the activities of operators of nuclear power plants as a factor of accidents in the conditions of the threat of social catastrophe

The purpose of the study is to establish the peculiarities of operator’s work and the leading factors of the formation of its psychophysiological tension at nuclear power plants in the conditions of the threat of social catastrophe in connection with military operations. The study was conducted at the Zaporizhzhya and Khmelnytsky nuclear power plants for the period of 2020-2021. To study the dynamics of the psychophysiological state of operators of nuclear power plants, a verbal-communicative diagnostic method was used to collect information about the operators investigated using Google Form and traditional physiological, psychological and psychophysiological methods. The socio-demographic features of the investigated operators of the block control panel were analyzed. It was established that men only (100%) aged 24-49 and with work experience from 4 to 20 years were among the examined. All surveyed operators (41 people) are residents of the city, with completed higher education and are family members. The methods of psychological (reactive anxiety, mood, activity, mood, attention), physiological (cardiography, blood pressure) and psychophysiological (simple sensorimotor and psychophysical) research methods were used to empirically assess the intensity of activity of the operators of the block control panel of nuclear power plants. There were examined operators, while on duty when control errors and pre-accident situations were recorded. It was established that the psychological, physiological and psychophysiological characteristics of these operators are followed by increased reactive anxiety, decreased indicators of well-being, activity, mood, reduction in functional reserves of the cardiorespiratory system, mental and physical capacity. These indicators are considered as criteria for the development of regulatory measures. It is proposed to take into account not only technological factors, but also the psychophysiological features of operators in the dynamics of their manifestation when developing measures for the optimal selection and personnel placement. The complex of methods for researching the functional state of operators can be used to optimize their professional selection and retraining, which can lead to reducing accidents and costs for professional training. The expected effect is an increase in the efficiency and quality of operator’s activity, the productivity and reliability of the performance of production tasks, an increase in professional longevity, a decrease in rate and occupationally-related morbidity of these specialists.

Aetiology of bioethanol related burn accidents: A qualitative study

BackgroundSince insight into the motivation of behaviour in bioethanol related burn accidents is lacking, this study aimed to qualitatively examine influencing factors in bioethanol related burn accidents. In order to identify target points for effective burn prevention. MethodsPatients previously admitted with bioethanol related acute non-intentional burn injury to the three Dutch burn centres were eligible. One interviewer conducted fourteen semi-structured interviews. Interviews were transcribed and coded by two independent researchers. Conclusions were drawn based on generalised statements on the concerned topics. ResultsFour overall themes in influencing factors were found, namely 1) motivation; including non-designated use and impaired judgement, 2) knowledge and education; including unknown product and properties and information overload, 3) risk perception; including poor recognisability of risks and preferred trial and error and 4) thresholds; including easy availability and unclear liability. ConclusionTrust in consumers may be over-estimated, as proper use cannot be expected. To prevent future bioethanol related burn incidents, thresholds for obtaining and using bioethanol should be increased, safe alternatives to ignite open fires and wood stoves should be provided and knowledge and warnings should be improved.

Landing trajectory and control optimization for helicopter encountering different tail rotor pitch lockups

In recent years, tail rotor failure has been a significant factor in helicopter accidents, contributing to around 30 % of all incidents. Among these failures, tail rotor pitch lockup accounts for nearly 2/3. However, there is currently a lack of research on the landing trajectory and control optimization for piloted helicopters facing tail rotor pitch lockup. Therefore, this paper aims to study the landing trajectory and pilot control strategy optimization during helicopter tail rotor pitch lockup. The findings of this research are expected to provide valuable insights and serve as a reference for subsequent real-time pilot-in-the-loop simulations and final flight tests. In this paper, we utilize the UH-60A helicopter as a prototype to establish a flight dynamics model and a pilot model. The aerodynamic forces and induced velocity of the main rotor are calculated using the blade element method and Pitt-Peters model. The rotor flap motion is simplified to a first-order harmonic quantity. We then formulate the problem of safe landing and control optimization as a nonlinear optimal control problem, with the cost function designed to reflect safety and feasibility during the flight and touchdown process. To solve the optimal control problem numerically, we use direct multiple shooting and sequential quadratic programming algorithms. Flight test data for the UH-60A, encompassing steady-state flight, dynamic response, and autorotation landing, are utilized to validate the accuracy of the flight dynamics model and the effectiveness of the optimal control algorithm. Finally, the paper investigates the safe landing trajectories and control strategies for the sample helicopter when encountering high tail rotor pitch lockup and low tail rotor pitch lockup, respectively. Simulation results demonstrate that when the tail rotor is stuck at a high pitch, it is advisable for pilots to execute a high-power state landing by maintaining the engine at high power while reducing forward speed and descent rate. Conversely, when the tail rotor is stuck at a low pitch, flying at an economical speed (in a low-power state) is advantageous, but it does not facilitate a safe landing thereafter. If the pilot attempts a conventional landing, the yaw rate at touchdown would be very high and potentially dangerous. In contrast, if an autorotation landing is executed, the landing will be safer with a much lower yaw rate at touchdown. The optimal landing trajectory and control process align with the recommendations from actual helicopter flight tests. The proposed method provides feasible pilot control strategies for safe landing when helicopters encounter various tail rotor pitch lockup situations. This research can serve as a reference for pilots before conducting actual flight tests.

Analyzing the Risk Factors of Hazardous Chemical Road Transportation Accidents Based on Grounded Theory and a Bayesian Network

With the increase in the production and use of hazardous chemicals in China, road transportation safety issues are becoming increasingly prominent. To study the causes of road transportation accidents involving hazardous chemicals, prevent accident occurrence, and realize the safety and sustainable development of the transportation of hazardous chemicals, we combined grounded theory (GT) and a Bayesian network (BN) model to quantify the causal relationship of the interactions among the influencing factors leading to hazardous chemical road transportation accidents that occurred in China in the period of 2017–2020. The influencing factors of these accidents were classified into 5 core categories, 12 main categories, and 28 categories through the GT method, and then a BN-based model was established for these collected accidents. The conditional probability and posterior probability of each influencing factor leading to an accident were determined through BN learning, and then the causal relationship of the interactions between the influencing factors was quantified. The results indicated that the probability of road transportation accidents involving hazardous chemicals considered in this study reaches 72.5% under the combined influence of various factors, and the most likely causal chain of an accident is that equipment failure during the hazardous chemical transportation process contributes to an Unsafe Tanker State, which in turn leads to an accident. The sensitivity analysis confirmed that the key impact factor of hazardous chemical road transportation accidents is equipment failure, followed by improper operation. Overall, this study presents a reference and a foundation for avoiding or reducing risks as much as possible during daily hazardous chemical road transportation operations and risk supervision, realizing safe, sustainable development.

Red Cell Distribution Width-to-Albumin Ratio Is a Simple but Robust Prognostic Biomarker in Peripheral T-Cell Lymphoma

Background: Red cell distribution width (RDW) is the difference in the volume and size of erythrocytes. High RDW has been identified as a worse prognostic factor in various diseases, including sepsis, cerebrovascular accidents, and diverse cancers. More recently, RDW-to-albumin ratio (RAR) is a comprehensive biomarker combining inflammation and nutrition status that better reflects a patient's frailty. However, little is known about its prognostic relevance in peripheral T-cell lymphoma (PTCL), with only one publication focusing on RDW (Castro et al.). Methods: This retrospective analysis included consecutive patients with newly diagnosed PTCL between 2007 and 2023 at Kameda Medical Center. Extranodal NK/T-cell lymphoma, adult T-cell leukemia/lymphoma, and ALK-positive anaplastic large cell lymphoma were excluded due to distinct prognosis and treatment strategies. The RDW coefficient of variation (RDW-CV) was assessed prior to treatment and calculated using the following formula: 1 standard deviation of mean corpuscular volume (MCV) divided by MCV, multiplied by 100. Receiver operating curve (ROC) analysis was used to determine the optimal cutoff value of RDW-CV and RAR for 2-year outcomes. Survival analyses were conducted using Kaplan-Meier curves with log-rank tests, and Cox proportional hazard models were used for univariate and multivariate analyses. Results: In total, 115 patients were included in this analysis. The median age was 74 years (range 45-93), with male predominance (60.8%). Sixty-five patients (56.5%) were initially treated with the CHOP regimen, while 29 patients (25.2%) received more intensive chemotherapy. The most common disease subtype was PTCL-not otherwise specified (49.5%), followed by angioimmunoblastic lymphoma (40.0%). The median RDW-CV and RAR were 14.8 (range 12.2-21.5) and 4.61 (range 2.6-9.8), respectively. The RDW-CV was significantly correlated with levels of hemoglobin (R = -0.4), albumin (R = - 0.59), and lactate dehydrogenase (R = 0.27) (all P < 0.05). ROC curve analysis for 2-year survival revealed a higher area under the curve (AUC) for RAR (0.79) compared to RDW (0.74), with cutoff values of 4.4 and 14.1, respectively (Figure 1). Using this cutoff value, patients with high RAR had significantly worse overall survival (OS) and progression free survival (PFS) than those without (2-year OS rate: 82.5% vs. 35.1%, Figure 2; 2-year PFS rate: 54.8% vs. 27.9%, P <0.001). On multivariate analysis, high RAR was associated with a significantly worse PFS (hazard ratio [HR] =1.89 [95% confidence interval 1.15-3.11], P =0.01) and OS (HR=3.02 [1.66-5.50], P <0.001) independent of the international prognostic index (IPI), dose reduction of chemotherapy and lymphoma subtype. Conclusion: We demonstrated that RAR improved the prognostic stratification compared to RDW-CV alone. Additionally, baseline high RAR was identified as a simple but robust prognostic factor independently associated with IPI category and treatment intensity in PTCL patients.

Relationship Between Work-Related Stress and Accidents: Moderating Role of Safety Factors

Work-related stress has been identified as a risk factor for accidents according to the inadaptability theory of accident causation. The same theory says that increasing adaptability can reduce accidents. So, safety culture can be expected to be a moderator in the relationship between work-related stress and errors or accidents (as a composite construct). A survey was conducted among 431 employees from various industries using the job stress index, safety culture scale, and workplace error-accident history scale with the aim of testing if safety culture mitigates the relationship between workplace stress and errors/accidents. Work-related stress and errors/accidents correlated significantly, r=.18, p<.01. However, safety culture was not found to moderate their relationship. The conclusion is that a safety culture may not reduce the accidents caused because of work-related stress, and alternatives need to be sought. However, other studies with more methodological rigor or more objective data are needed to verify this conclusion.

The Using of Media Games to Improve SMCP (Standard Marine Communication Phrases) Vocabulary in Maritime English

Abstract. Shipping is the world's largest trade and also one of the most dangerous. Safety of life at sea, the environment at sea, and 80% of world trade depend on professional and competent seafarers. Ziarati (2006) identified that poor communication as one of the most significant factors in accidents at sea and ports. SMCP is a collection of words or phrases in English which is supported by the international community means of communication at sea then developed and adapted to IMO (International Maritime Organization) standards. SMCP aims to explain external communication phrases such as communication between ships, between ships and land parties such as ports. The main goal is to reduce language problems in communicating at sea and also to avoid misunderstandings that can lead to accidents. So, it is possible to learn vocabulary in SMCP to achieve maximum results if it is done in a pleasant atmosphere. This study uses a quantitative approach using a quasi-experimental method. The population in this study was the cadets of the diploma program majoring in Nautica in the second semester of The Surabaya Shipping Polytechnic (2015-2016) academic year, amounting to 110 people. The sample of this study was 20 cadets in class C. In this study, the result in question was the use of games to support the learning of maritime English SMCP vocabulary.
 Keywords: Games, Vocabulary; SMCP; Maritime English

The Formative Factors of a Rock Burst Based on Energy Calculations and the Experimental Verification of Butterfly-Shaped Plastic Zones

The research on the formation factors of rock burst is one of the main research directions of rock mechanics in recent years, which is helpful to solve the problem of rock burst accidents. So, in this study, the calculation method of energy released during rock burst is first obtained by using different medium models, and then, the formation factors of rock bursts are obtained by comparing the calculation energy with the actual accident energy. The method of energy calculation utilizes the difference between elastoplastic and pure elastic models to innovatively quantify the specific values of energy released before and after the occurrence of the rock burst. It is considered that the stress and plastic zone state before the occurrence of rock burst have an important influence on the occurrence of the accident and are one of the formation factors, while the deviatoric stress field and butterfly-shaped plastic zone create conditions for greater energy release. In addition, the trigger stress constitutes another formation factor. The plastic zone state before rock failure is verified by the experimental test; the location distribution shape of acoustic emission (AE) events during the later stage of compression failure is approximately the same as theoretical result. The results also preliminarily indicated the fractal characteristics of acoustic emission events distribution before sample failure. The study obtained the formative factors of rock burst accident, which provides a new ideas and references for the research on the formation of rock bursts.

Key Factors in Crane-Related Occupational Accidents in the Spanish Construction Industry (2012-2021).

The construction industry is one of the riskiest sectors worldwide, with crane operations being one of the most dangerous activities. The aim of this study was to gain insight into the key factors involved in crane-related occupational accidents in the construction industry in Spain. To this end, 1314 accidents involving cranes were analyzed from a total of 241,937 accidents that occurred in the construction of buildings. The data were collected from the Spanish government's occupational accident statistics corresponding to the years 2012-2021. The results evidenced a statistically significant relationship between cranes as the material agent and the size of the company, with 95% of cases corresponding to small- or medium-sized companies (less than 250 employees). Additionally, it shows how the crane operator is identified as a material contributor to crane accidents in the construction industry, and may be considered a key component to these accidents. In conclusion, improving the knowledge gained about the key factors in crane-related accidents at work in the construction industry provides essential information that helps to design and implement appropriate preventive measures to avoid the recurrence of unwanted events with these machines.

A Bayesian network-based model for risk modeling and scenario deduction of collision accidents of inland intelligent ships

Safety is an important premise and foundation for the operation of intelligent ships. This paper introduces a novel scenario analysis framework that employs disaster system theory to produce more comprehensive results for identifying scenario elements and calculating collision risks for inland intelligent ships. The framework is utilized to investigate the collision accident risk evolution mechanism. This process is incorporated into Bayesian Network (BN) modeling for ship collisions on inland rivers. By comparing the change in occurrence probability and consequence severity of risk factors for inland ship collision accidents with and without selected intelligent technologies, the collision risk of intelligent ships is quantified. The results indicate that the application of intelligent technologies, such as ship speed optimization and situational awareness, can reduce the occurrence probability of collision accidents and mitigate the severity of their consequences. Moreover, it has been discovered that such intelligent technologies have a greater impact on accidents with severe consequences than those with minor consequences. This research provides a framework for the preliminary safety evaluation of inland intelligent ships. It is of great significance to accelerate the improvement of navigational risk prevention and response-ability of inland intelligent ships in the future.

A hybrid STAMP-fuzzy DEMATEL-ISM approach for analyzing the factors influencing building collapse accidents in China.

To explore the factors influencing recent construction collapse accidents, this study utilizes a sample of 355 reports on building collapse accidents from 2012 to 2022. The investigation employs the systems-theoretic accident modeling and processes (STAMP) model to retrieve 22 key causal factors of accidents from the physical, operational, managerial, and supervisory layers. Subsequently, an improved decision-making trial and evaluation laboratory (DEMATEL)-interpretive structural modeling (ISM) method is used to analyze the relationships and strengths of these influencing factors, providing a comprehensive understanding of the logical connections between the causes of building collapse accidents. The results indicate that the deep-rooted causes of building collapse accidents are primarily lax safety management at the enterprise level and the exchange of interests at the government regulatory level, which in turn affect workers at the operational level and the physical aspects of accidents on-site. Furthermore, integrating the STAMP model and the triangular fuzzy DEMATEL-ISM model overcomes the limitations of the traditional STAMP model, allowing for a more focused identification of key factors.

Amphibious Airplane Accidents: An Exploratory Analysis

Causes and contributing factors of amphibious airplane accidents are examined by comparing the proportion of fatal accidents for different causes of accidents, with a focus on landings on water and low-level flying maneuvers. A set of 183 accidents involving amphibious planes from 2005 to 2020 was extracted from the National Transportation Safety Board’s online database. Amphibious airplane accidents are reported to be fatal in 34% of cases, which is higher than the average of 20% for general aviation. Logistic regression analysis shows that the maneuvering flight phase and decision-making factors are significantly more often associated with fatal accidents than other flight phases and causes. In addition, the number of accidents associated with decision-making factors significantly increased during the studied time period. Amphibious airplanes benefit from accident analysis despite the absence of denominator data and the limitations of most general aviation accident reports. Intentional low-level flying is shown to be a central area of concern that may be addressed at the operational as well as the training level. Landing accidents could be avoided by introducing additional warning systems and training regarding (retractable) landing gear as well as general awareness training of decision-making during landings on water.

Establishment of a Dynamic Factor Prediction Module for Risk Assessment in Coastal Activity Sites

Recent persistent coastal developments have expanded recreational areas and enhanced accessibility. However, this growth has also led to a rise in safety incidents. These accident factors can be divided into human-made and natural types. The latter is comprised of dynamic factors like waves, tides, sea fogs, and winds. While institutions like the Korea Meteorological Administration and the Korea Hydrographic and Oceanographic Agency already offer data on these dynamic factors, the resolution is often insufficient for a precise assessment of localized risks. In this study, to overcome these limitations, we utilized the dynamic information from existing open systems to construct a high-resolution numerical simulation. Through this, we developed an automated module to predict dynamic factors in localized coastal activity areas. Particularly during the module's construction, we compared and reviewed the numerical prediction results for waves with observed wave heights.

Causal Analysis of Fall Accidents in Hydraulic Engineering Based on Text Mining and Decision-Making Trial and Evaluation Laboratory and Interpretative Structural Modeling

Hydraulic engineering construction safety has become a major concern in engineering sustainability. Fall accidents, as a common type of accident during the hydraulic engineering construction process, have caused physical and fatal injuries and property losses on an individual and societal scale. With a sizable workforce, complex operational structures and demanding construction conditions, hydraulic engineering projects present more pronounced safety management challenges than other infrastructure initiatives. As a result, the risk of accidents, particularly fall accidents, is heightened in this domain. To prevent fall accidents and minimize losses, this study used the investigation reports of 389 cases of fall accidents as the analyzed corpus, and 16 contributing factors of fall accidents were extracted with the utilization of text mining. Accident feature terms were visualized through word clouds and ring bar graphs. The logical relationship among the influencing factors was quantified based on Decision-Making Trial and Evaluation Laboratory and Interpretative Structural Modeling (DEMATEL-ISM). The contributing factors and occurrence mechanism of fall accidents in hydraulic engineering were analyzed by establishing a multilevel hierarchical hybrid model. The results showed that the multilevel hierarchical hybrid model was divided into five levels. Thirteen causal chains were obtained. Chaotic security management, weak safety awareness and an inadequate safety system were the most critical factors, while the remaining eleven transitional factors and four surface factors also contributed significantly to the occurrence of accidents. Human and management factors dominated the overall factor transfer pathway. This study proposes countermeasures to the above-mentioned factors and provides a theoretical basis for the sustainable and safe construction of hydraulic engineering.

An FDS Simulation to Predict the Kerosene Pool Fire Results at Rocket Launchpad Basement Facilities in the Republic of Korea

In the Republic of Korea, a new rocket launchpad was constructed to launch the KSLV-II on an island, and all the launchpad facilities are located in basement. Because of the complex and diverse facilities, fire accidents have increased. Using the FDS (Fire Dynamics Simulator) to predict the damage from kerosene storage and drain tank pool fires is garnering more attention as a tool of choice. The FDS supports a sprinkler model, which is needed to analyze fire extinguishing by water sprinkling. To predict and estimate the resistance of the building and thermal damage, the main analysis factors for a kerosene tank pool fire accident are temperature and HRR (heat release rate per unit volume). In 3 m3 release cases, the maximum temperature decreased by 33% from 900 K to 600 K by sprinkled water, and the maximum HRR decreased by 70% from 20,000 kW/m3 to 6000 kW/m3. In 10 m3 release cases, the temperature and HRR decreased by 44%, from 800 K to 450 K and 68% from 25,000 kW/m3 to 8000 kW/m3, respectively.

Preanalytical factors influencing the results ofethanol analysis inpostmortem specimens.

Excessive drinking and drunkenness are underlying factors in many fatal accidents, which make the quantitative determination of ethanol in postmortem (PM) specimens an essential part of all unnatural death investigations. The same analytical methods are used to determine ethanol in blood taken from living and deceased persons although the interpretation of the results is more complicated in medical examiner cases owing to various preanalytical factors. The biggest problem is that under anaerobic conditions ethanol can be produced naturally in decomposed bodies by microbial activity and fermentation of blood glucose. Ways are needed to differentiate antemortem ingestion of ethanol from PM synthesis. One approach involves the determination of ethanol in alternative specimens, such as bile, cerebrospinal fluid, vitreous humor and/or urine, and comparison of results with blood alcohol concentration (BAC). Another approach involves the analysis of various alcohol biomarkers, such as ethyl glucuronide, ethyl sulfate and/or phosphatidylethanol or the urinary metabolites of serotonin 5-hydroxytryptophol/5-hydroxyindoleacetic acid (5-HTOL/5-HIAA). If ethanol had been produced in the body by microbial activity, the blood samples should also contain other low-molecular volatiles, such as acetaldehyde, n-propanol and/or n-butanol. The inclusion of 1-2% w/v sodium or potassium fluoride, as an enzyme inhibitor, in all PM specimens is essential to diminish the risk of ethanol being generated after sampling, such as during shipment and storage prior to analysis. Furthermore, much might be gained if the analytical cut-off for reporting positive BAC was raised from 0.01 to 0.02 g% when PM blood is analyzed. During putrefaction low BACs are more often produced after death than high BACs. Therefore, when the cadaver is obviously decomposed, a pragmatic approach would be to subtract 0.05 g% from the mean analytical result. Any remaining BAC is expected to give a more reliable indication of whether alcohol had been consumed before death.

Causes and Strategies for Reducing Road Traffic Accidents in the Bongo District of Ghana

Aim: This study intends to assess drivers’ state of knowledge on the main causes and the best strategies capable of reducing road traffic accidents in the Bongo District of Ghana.
 Study Design: The study was a descriptive design.
 Place and Duration of Study: The study was conducted in the Bongo District of the Upper East Region of Ghana between July 2023 and August 2023.
 Methodology: The researcher conducted a survey involving 100 drivers who were randomly selected from a driver population of 120 in the Bongo District. The data were analyzed using Microsoft Excel [Version 19]. The results of the data analysis were presented as tables and charts.
 Results: The study found that the main causes of road traffic accidents emanate from human error such as low driving skills, excessive speeding, and poor vision of driver. Also, road conditions like bad road networks, no lane markings, and no speed limit signs were found as causal factors of road traffic accidents. Faulty vehicles with causative factors such as defective tyres, brakes, and lights were noted to be also responsible for road accidents. Nevertheless, the least factor was environmental conditions such as bad weather conditions and stray animals being enumerable as environmental conditions which cause road accidents. The study further found that the best strategies for curbing road traffic accidents were enforcement of traffic laws, education and training of drivers, obeying traffic rules by drivers, and maintaining vehicles well.
 Conclusion: The study, therefore, concluded that human factors play a central role in contributing to road accidents and curbing road traffic accidents. The research findings can be used to guide stakeholders in formulating and prioritizing interventions that are more human-centred for the curbing of road traffic accidents in the Bongo District of Ghana.