Not in Control,but Liable?Attributing Human Responsibility for Fully Automated Vehicle Accidents

Human agency has become increasingly limited in complex systems with increasingly automated decision-making capabilities.For instance,human occupants are passengers and do not have direct vehicle control in fully automated cars(i.e.,driverless cars).An interesting question is whether users are responsible for the accidents of these cars.Normative ethical and legal analyses frequently argue that individuals should not bear responsibility for harm beyond their control.Here,we consider human judgment of responsibility for accidents involving fully automated cars through three studies with seven experiments(N=2668).We compared the responsibility attributed to the occupants in three conditions:an owner in his private fully automated car,a passenger in a driverless robotaxi,and a passenger in a conventional taxi,where none of these three occupants have direct vehicle control over the involved vehicles that cause identical pedestrian injury.In contrast to normative analyses,we show that the occupants of driverless cars(private cars and robotaxis)are attributed more responsibility than conventional taxi passengers.This dilemma is robust across different contexts(e.g.,participants from China vs the Republic of Korea,participants with first-vs third-person perspectives,and occupant presence vs absence).Furthermore,we observe that this is not due to the perception that these occupants have greater control over driving but because they are more expected to foresee the potential consequences of using driverless cars.Our findings suggest that when driverless vehicles(private cars and taxis)cause harm,their users may face more social pressure,which public discourse and legal regulations should manage appropriately.

Exploring the Factors Associated with 12-Month Non-Return to Work among Motorcyclists Involved in Road Accidents

Introduction: Motorcyclists bear a disproportionate burden of morbidity and mortality from road accidents. In addition, the consequences of these accidents affect the ability of victims to return to work. This study aimed to determine the prevalence and factors associated with non-return to work among surviving motorcyclists involved in road accidents 12 months after the event. Materials and Methods: It was a cross-sectional study conducted using data from a cohort of motorcyclists involved in accidents and recruited in five hospitals in Benin from July 2019 to January 2020. The dependent variable was non-return to work 12 months after the accident (yes vs no). The independent variables were categorized into two groups: baseline and 12-month follow-up variables. Logistic regression was used to determine the factors associated with non-return to work at 12 months among the participants. Results: Among the 362 participants, 55 (15.19%, 95% CI = 11.84 - 19.29) had not returned to work 12 months after the accident. Risk factors for non-return to work identified were: smoking (aOR = 4.41, 95% CI = 1.44 - 13.56, p = 0.010), hospitalization (aOR = 2.87, 95% CI = 1.14 - 7.24, p Conclusion: The prevalence of non-return to work at 12 months was high among surviving motorcyclists involved in road accidents in Benin. Integrated support for patients based on identified risk factors should effectively improve their return to work.

Stem cell transplantation in cerebrovascular accidents:A global bibliometric analysis(2000-2023)

BACKGROUND Cerebrovascular accident(CVA)is a major global contributor to death and disability.As part of its medical management,researchers have recognized the importance of promising neuroprotective strategies,where stem cell transplantation(SCT)is thought to confer advantages via trophic and neuroprotective effects.AIM To evaluate the current state of research on SCT in patients with CVA,assess key trends and highlight literature gaps.METHODS PubMed was screened for SCT in CVA-related articles in October 2023,for each country during the period between 2000 and 2023.Using the World Bank data,total population and gross domestic product were collected for comparison.VOSviewer_1.6.19 was used to create the VOS figure using the results of the same query.Graphs and tables were obtained using Microsoft Office Excel.RESULTS A total of 6923 studies were identified on SCT in CVA,making 0.03%of all published studies worldwide.Approximately,68%were conducted in high-income countries,with a significant focus on mesenchymal stem cells.The journal“Stroke”featured the largest share of these articles,with mesenchymal SCT having the highest rate of inclusion,followed by hematopoietic SCT.Over time,there has been a noticeable shift from in vitro studies,which assess stem cell proliferation and neurogenesis,to in vivo studies aimed at evaluating efficacy and safety.Additionally,the number of reviews increased along this approach.CONCLUSION This bibliometric analysis provides a comprehensive guide for physicians and researchers in the field through an objective overview of research activity,and highlights both current trends and gaps.Having a potential therapeutic role in CVA,more research is needed in the future to focus on different aspects of SCT,aiming to reach a better treatment strategy and improve life quality in patients.

Transient Analysis of a Reactor Coolant Pump Rotor Seizure Nuclear Accident

The reactor coolant pump(RCP)rotor seizure accident is defined as a short-time seizure of the RCP rotor.This event typically leads to an abrupt flow decrease in the corresponding loop and an ensuing reactor and turbine trip.The significant reduction of core coolant flow while the reactor is being operated at full load can have very negative consequences.This potentially dangerous event is typically characterized by a complex transient behavior in terms of flow conditions and energy transformation,which need to be analyzed and understood.This study constructed transient flow and rotational speed mathematical models under various degrees of rotor seizure using the test data collected from a dedicated transient rotor seizure test system.Then,bidirectional fluid-solid coupling simulations were conducted to investigate the flow evolution mechanism.It is found that the influence of the impeller structure size and transient braking acceleration on the unsteady head(Hu)is dominant in rotor seizure accident events.Moreover,the present results also show that the rotational acceleration additional head(Hu1)is much higher than the instantaneous head(Hu2).

A STAMP-Game model for accident analysis in oil and gas industry

Accidents in engineered systems are usually generated by complex socio-technical factors.It is beneficial to investigate the increasing complexity and coupling of these factors from the perspective of system safety.Based on system and control theories,System-Theoretic Accident Model and Processes(STAMP)is a widely recognized approach for accident analysis.In this paper,we propose a STAMP-Game model to analyze accidents in oil and gas storage and transportation systems.Stakeholders in accident analysis by STAMP can be regarded as players of a game.Game theory can,thus,be adopted in accident analysis to depict the competition and cooperation between stakeholders.Subsequently,we established a game model to study the strategies of both supervisory and supervised entities.The obtained results demonstrate that the proposed game model allows for identifying the effectiveness deficiency of the supervisory entity,and the safety and protection altitudes of the supervised entity.The STAMP-Game model can generate quantitative parameters for supporting the behavior and strategy selections of the supervisory and supervised entities.The quantitative data obtained can be used to guide the safety improvement,to reduce the costs of safety regulation violation and accident risk.

Uncertainty and sensitivity analysis of in-vessel phenomena under severe accident mitigation strategy based on ISAA-SAUP program

The phenomenology involved in severe accidents in nuclear reactors is highly complex.Currently,integrated analysis programs used for severe accident analysis heavily rely on custom empirical parameters,which introduce considerable uncertainty.Therefore,in recent years,the field of severe accidents has shifted its focus toward applying uncertainty analysis methods to quantify uncertainty in safety assessment programs,known as“best estimate plus uncertainty(BEPU).”This approach aids in enhancing our comprehension of these programs and their further development and improvement.This study concentrates on a third-generation pressurized water reactor equipped with advanced active and passive mitigation strategies.Through an Integrated Severe Accident Analysis Program(ISAA),numerical modeling and uncertainty analysis were conducted on severe accidents resulting from large break loss of coolant accidents.Seventeen uncertainty parameters of the ISAA program were meticulously screened.Using Wilks'formula,the developed uncertainty program code,SAUP,was employed to carry out Latin hypercube sampling,while ISAA was employed to execute batch calculations.Statistical analysis was then conducted on two figures of merit,namely hydrogen generation and the release of fission products within the pressure vessel.Uncertainty calculations revealed that hydrogen production and the fraction of fission product released exhibited a normal distribution,ranging from 182.784 to 330.664 kg and from 15.6 to 84.3%,respectively.The ratio of hydrogen production to reactor thermal power fell within the range of 0.0578–0.105.A sensitivity analysis was performed for uncertain input parameters,revealing significant correlations between the failure temperature of the cladding oxide layer,maximum melt flow rate,size of the particulate debris,and porosity of the debris with both hydrogen generation and the release of fission products.

Assessing the Variability of Extreme Weather Events and Its Influence on Marine Accidents along the Northern Coast of Tanzania

The marine accidents are among the main components of the Zanzibar Disaster Management Policy (2011) and the Zanzibar Blue Economy Policy (2020). These policies aimed to institute legal frame works and procedures for reducing both the frequency of marine accidents and their associated fatalities. These fatalities include deaths, permanent disabilities and loss of properties which may result into increased poverty levels as per the sustainable development goal one (SDG1) which stipulates on ending the poverty in all its forms everywhere. Thus, in the way to support these Government efforts, the influence of climate and weather on marine accidents along Zanzibar and Pemba Channels was investigated. The study used the 10 years (2013-2022) records of daily rainfall and hourly wind speed acquired from Tanzania Meteorological Authority (TMA) (for the observation stations of Zanzibar, Pemba, Dares Salaam and Tanga), and the significant wave heights data, which was freely downloaded from Globally Forecasting System (GFS-World model of 13 km resolution). The marine accident records were collected from TASAC and Zanzibar Maritime Authority (ZMA), and the anecdotal information was collected from heads of quay and boat captains in different areas of Zanzibar. The Mann Kendal test, was used to determine the slopes and trends direction of used weather parameters, while the Pearson correlations analysis and t-tests were used to understand the significance of the underlying relationship between the weather and marine accidents. The paired t-test was used to evaluate the extent to which weather parameters affect the marine accidents. Results revealed that the variability of extreme weather events (rainfall, ocean waves and wind speed) was seen to be among the key factors for most of the recorded marine accidents. For instance, in Pemba high rainfall showed an increasing trend of extreme rainfall events, while Zanzibar has shown a decreasing trend of these events. As for extreme wind events, results show that Dar es Salaam and Tanga had an increasing trend, while Zanzibar and Pemba had shown a decreasing trend. As for the monthly variability of frequencies of extreme rainfall events, March to May (MAM) season was shown to have the highest frequencies over all stations with the peaks at Zanzibar and Pemba. On the other hand, high frequency of extreme wind speed was observed from May to September with peaks in June to July, and the highest strength was observed during 09:00 to 15:00 GMT. Moreover, results revealed an increasing trend of marine accidents caused by bad weather except during November. Also, results showed that bad weather conditions contributed to 48 (32%) of all 150 recorded accidents. Further results revealed significant correlation between the extreme wind and marine accidents, with the highest strong correlation of r = 0.71 (at p ≤ 0.007) and r = 0.75 (at p ≤ 0.009) at Tanga and Pemba, indicating the occurrence of more marine accidents at the Pemba channel. Indeed, strong correlation of r = 0.6 between extreme rainfall events and marine accidents was shown in Pemba, while the correlations between extremely significant wave heights and marine accidents were r = 0.41 (at p ≤ 0.006) and r = 0.34 (p ≤ 0.0006) for Pemba and Zanzibar Channel, respectively. In conclusion, the study has shown high influence between marine accidents and bad weather events with more impacts in Pemba and Zanzibar. Thus, the study calls for more work to be undertaken to raise the awareness on marine accidents as a way to alleviate the poverty and enhance the sustainable blue economy.

Conceptual Strategy for Mitigating the Risk of Hydrogen as an Internal Hazard in Case of Severe Accidents at Nuclear Power Plant Considering Existing Risks and Uncertainties Associated with the Use of Traditional Strategies

Hydrogen challenge mitigation stands as one of the main objectives in the management of severe accidents at Nuclear Power Plants (NPPs). Key strategies for hydrogen control include atmospheric inertization and hydrogen removal with Passive Autocatalytic Recombiners (PARs) being a commonly accepted approach. However, an examination of PAR operation specificity reveals potential inefficiencies and reliability issues in certain severe accident scenarios. Moreover, during the in-vessel stage of severe accident development, in some severe accident scenarios PARs can unexpectedly become a source of hydrogen detonation. The effectiveness of hydrogen removal systems depends on various factors, including the chosen strategies, severe accident scenarios, reactor building design, and other influencing factors. Consequently, a comprehensive hydrogen mitigation strategy must effectively incorporate a combination of strategies rather than be based on one strategy, taking into consideration the probabilistic risks and uncertainties associated with the implementation of PARs or other traditional methods. In response to these considerations, within the framework of this research it has been suggested a conceptual strategy to mitigate the hydrogen challenge during the in-vessel stage of severe accident development.

Accidental Ingestion of Nitric Acid in an Agricultural Company: A Case Study and Literature Review

Introduction: Though common in society, caustic accidental ingestion is rare in the agricultural industry. This study describes a case of ingestion of nitric acid used as an agricultural fertilizer by an ordinary worker at the Société de Cultures Légumières. Clinical Case: This is a 33-year-old unschooled woman who ingested a sip of nitric acid from an abandoned labelled acid canister near a farming plot of land. She showed a burn of the oral cavity with a bleeding tablecloth and an intense retrosternal pain. The duodenal oesophagus fibroscopy screening that was carried out 18 hours after the accident, revealed an esophagitis class 2b. The tests revealed no anomalies. Fifteen (15) days after the accident, the FOGD was normal. Following an 8-month-follow up, no signs of stenosis or degeneration were noted. Conclusion: The accidental ingestion of nitric acid is rare in adult. Its treatment is mainly symptomatic and aims at preserving vital functions without directly fighting the ingested substance off. The right actions must be integrated into the 15-minute Health and Safety awarenesssessions for optimum pre-hospital management. The hospital evaluation is mandatory and is carried out thanks to the digestive endoscopy, which is still relevant in this indication, but is completed by the thoraco-abdominal CT. The latter is very sensitive the transmural necrosis diagnosis.

Child Victims of Road Traffic Accidents: Epidemiological and Clinical Aspects in the Medical and Surgical Emergency Department of the Donka National Hospital

Introduction: Children involved in road accidents most often suffer head or limb injuries. The severity of these injuries varies according to the age of the child, the type of road user and whether or not protective devices are used. The aim of this study was to carry out a census of admissions and to identify the epidemiological and clinical profile of children involved in road traffic accidents at Donka National Hospital. Methods: This is a descriptive cross-sectional study of children involved in traffic accidents over a 3-month period from September 1 to November 30, 2021. All children admitted to the emergency department for a traffic accident were included in the study. Results: During the study period, 435/530 children (82.1%) were victims of road accidents. Boys accounted for 54.94% of cases, compared with 45.06% for girls. The age group most affected was 12-17 years old (48.97%). October had the highest accident rate (36.4%). Pedestrians are most affected (52.87%). Bicycles and mopeds were involved in 59.77% of accidents. Head injury was the most frequent pathology (33.33%). The study showed that 12.64% of victims were referred to intensive care, pediatric surgery, etc. We recorded 8 cases of death (1.84%). Conclusion: This study highlighted the characteristics, incidence and risk factors for accidents in children admitted to emergency departments. Accident prevention, particularly serious accidents in children, requires more precise knowledge of the factors and circumstances leading to their occurrence.

Otorhinolaryngological (ORL) and Cervicofacial Injuries Resulting from Road Accidents within the Otorhinolaryngology (ORL) Department of the Regional Hospital of Mamou

Introduction: Otorhinolaryngological (ORL) and cervicofacial traumas encompass injuries affecting the neck, face, and ORL region, resulting from external influence. The objective of this study was to conduct an epidemiological and clinical analysis of ORL and cervicofacial injuries observed in victims of road accidents treated at the Otorhinolaryngology (ORL) department of the Regional Hospital of Mamou. Materials and Methods: This prospective and descriptive study was conducted over a period of 12 months, from January 1st to December 31st, 2021, within the Otorhinolaryngology (ORL) department of the Regional Hospital of Mamou. It included patients hospitalized for ORL and/or cervicofacial traumas resulting from road accidents during the study period. Results: A total of 348 cases were included, representing 36.22% of all traumas related to road accidents (AVP) within the Regional Hospital of Mamou. The average age of the patients was 26.44 years, with a sex ratio of 3.83, favoring males. The dominant socio-professional category was students, encompassing 32.47% of cases. Road accidents were mainly associated with motorcycle use (31.32% motorcycle-to-motorcycle, 24.43% motorcycle skidding, 13.51% motorcycle-pedestrian). Facial region injuries were the most common, accounting for 69.03% of cases, followed by rhinological injuries (17.28%) and otological injuries (13.69%). Associated injuries were predominantly closed head traumas (52.55%) and lower limb fractures (20.41%). Imaging was underutilized. Regarding surgical interventions, reconstructive surgery was the most predominant, accounting for 52.51% of cases, with a management timeframe of 30 minutes to 12 hours for 99.72% of patients. Conclusion: Road traffic accidents remain a serious public health issue, primarily affecting young males. Emphasis should be placed on road safety measures to reduce the frequency of these accidents.

Analysis of Traffic Accidents in Vietnam

Understanding the causes and solutions of road traffic accidents is important for developing road and action plans in a country. In Vietnam, awareness of traffic participants is the main cause of serious traffic accidents. In recent years, the number of road traffic accidents in Tuyen Quang province with deaths has decreased, but the number of accidents has increased significantly. The article uses data on traffic accidents in Tuyen Quang over the (2016-2023) has been analytically reviewed. From there, analyze accident characteristics and causes of traffic accidents in Tuyen Quang province, and propose solutions to improve traffic safety in Tuyen Quang, Vietnam. The findings can be information for managers and researchers interested in studying the province of Tuyen Quang, Vietnam road traffic safety. Additionally, the findings have led the government to achieve national targets in reducing the number of accidents and serious injuries.

A Workable Solution for Reducing the Large Number of Vehicle and Pedestrian Accidents Occurring on a Yellow Light

Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.

Statistical Analysis of Accident Proneness of Drivers

A mathematical model describing the risks of road accidents has been built on the basis of statistical data of drivers’ accident rate. It has been revealed that drivers can be divided by the degree of their accident proneness into four categories with sharply differing probabilities of road accidents. It has been shown that there is a possibility of classification of drivers in accordance with specified categories.

Development of Accident Prediction Model under Mixed Traffic Conditions:A Case Study

Accident prediction models are developed under mixed traffic conditions.Two models have been developed.The first model is a city based traffic accident prediction model.City population and vehicle ownership are the two parameters used to develop the model.A case study of Surat city in Gujarat is taken up.Total accident occurred in the city are regressed with population and vehicle ownership.Second model is the urban arterial based accident prediction model.Past accident record of ring road of Surat city shows that there are eight different locations on a ten kilometer stretch of ring road where the accidents took place consistently.These locations are picked up as accident spots.As there are many contributing factors and causes to road accidents.A comprehensive study of road safety found that human error was the sole cause in 57%of all accidents and was a contributing factor in over 90%.Keeping this in view a new term driver-pedestrian index is used to develop this model.Regression function of Microsoft excel is used for model development.Both the models are checked with R-statistics and t-statistics further the models are validated by using statistical goodness of fit(chi square test).Hence these models can be used to predict number of accidents in future subjected to the same geometric standards.Keeping this in mind improvement measures can be taken up by the district authorities.

Analysis of the Necessity of Stellate Ganglion Block after Anesthesia to Reduce the Risk of Cardiovascular Accidents in Coronary Heart Disease

Objective:To adjust the sympathetic nervous system through preoperative ultrasound-guided stellate ganglion block and to explore and analyze the situation and necessity of postanesthesia stellate ganglion block to reduce the risk of cardiovascular accidents in coronary heart disease.Methods:80 patients with cardiovascular risk factors in Songshan Hospital of Chifeng were selected,and the time span would cover from October 2022 to June 2024,with 80 cases of elective surgery and combined coronary heart disease.They will be randomly divided into blocked groups and conventional groups,40 cases each.Conventional block was performed after anesthesia in patients in the conventional group,and planetary ganglion block was performed after anesthesia in patients in the blocked group.The cardiovascular responses of patients in the two groups were observed,and the number of intraoperative cardiovascular active drugs and the occurrence of cardiovascular adverse events were recorded in patients in the two groups.Results:Analysis of the mean arterial pressure(MAP)and heart rate(HR)values of the two groups of patients at the time points before anesthesia(T0),the moment of tracheal intubation(T1),the moment of surgical skin cutting(T2),the end of the operation(T3),and the 6h postoperative period(T4)showed that the MAP and HR of the blocked group were lower than those of the conventional group at the time points of T1 to T4,and the differences in MAP and HR values of the two groups in different time points compared with the T0 time point were statistically significant(P<0.05)and the differences in cardiovascular response(P<0.05)were statistically significant(P<0.05).significance(P<0.05).The number of intraoperative cardiovascular active drugs used in the blocked group was shorter than that in the conventional group,and the incidence of cardiovascular adverse events was lower than that in the conventional group,with a statistically significant difference(P<0.05).Conclusion:By implementing preoperative ultrasound-guided stellate ganglion block in patients with cardiovascular risk factors,the frequency and degree of coronary heart disease symptoms will be reduced,thus reducing the risk of patients,which is worth promoting.

Characteristics of coal resources in China and statistical analysis and preventive measures for coal mine accidents

In the process of green and smart mine construction under the context of carbon neutrality,China's coal safety situation has been continuously improved in recent years.In order to recognize the development of coal production in China and prepare for future monitoring and prevention of safety incidents,this study mainly elaborated on the basic situation of coal resources and national mining accidents over the past five years(2017-2021),from four dimensions(accident level,type,region,and time),and then proposed the preventive measures based on accident statistical laws.The results show that the storage of coal resources has obvious geographic characteristics,mainly concentrated in the Midwest,with coal resources in Shanxi and Shaanxi accounting for about 49.4%.The proportion of coal consumption has dropped from 70.2%to 56%between 2011 and 2021,but still accounts for more than half of the all.Meanwhile,the accident-prone areas are positively correlated with the amount of coal production.Among different levels of coal mine accidents,general accidents had the highest number of accidents and deaths,with 692 accidents and 783 deaths,accounting for 87.6%and 54.64%respectively.The frequency of roof,gas,and transportation accidents is relatively high,and the number of single fatalities caused by gas accidents is the largest,about 4.18.In terms of geographical distribution of accidents,the safety situation in Shanxi Province is the most severe.From the time distribution of coal mine accidents,the accidents mainly occurred in July and August,and rarely occurred in February and December.Finally,the"4+4"safety management model is proposed,combining the statistical results with coal production in China.Based on the existing health and safety management systems,the manage-ments are divided into four sub-categories,and more specific measures are suggested.

Profile of Declared Work Accidents at the Parakou Agency of the National Social Security Fund, 2015-2021, Benin

Introduction: Work accidents (WA) have consequences for both the individual and the company. The objective of this study is to study the profile of work accidents declared to the Parakou agency of the National Social Security Fund (CNSS) from 2015 to 2021. Method: This was a descriptive cross-sectional study with retrospective data collection. It concerned workers affiliated with the CNSS in Parakou, victims of declared WA whose file was available and exploitable. The sampling was exhaustive. Data was collected from registers and worker records. The variables studied were socio-demographic and related to the accident. They were analyzed using R version 4.1 software. Results: The annual incidence rate of WA varied from 5.8% in 2015 to 1.7% in 2021. The victims were 90.6% male. There were more subjects aged 28 to 37 years (37.1%). Workers and laborers were the most concerned. Fractures (22.9%) were the major lesions. At 38.5% they sat in the thoracic limbs and at 22.5% in the pelvic limbs. The majority (63.6%) of these accidents occurred in the workplace. The processing industry sector was mainly (52.1%) the place of accidents. Conclusion: The prevalence of WA declared to the agency of the National Social Security Fund of Parakou from 2015 to 2021 is decreasing. The most affected were young people. It is important to assess their socio-economic impacts.

A Deep Learning Based Sentiment Analytic Model for the Prediction of Traffic Accidents

The severity of traffic accidents is a serious global concern,particularly in developing nations.Knowing the main causes and contributing circumstances may reduce the severity of traffic accidents.There exist many machine learning models and decision support systems to predict road accidents by using datasets from different social media forums such as Twitter,blogs and Facebook.Although such approaches are popular,there exists an issue of data management and low prediction accuracy.This article presented a deep learning-based sentiment analytic model known as Extra-large Network Bi-directional long short term memory(XLNet-Bi-LSTM)to predict traffic collisions based on data collected from social media.Initially,a Tweet dataset has been formed by using an exhaustive keyword-based searching strategy.In the next phase,two different types of features named as individual tokens and pair tokens have been obtained by using POS tagging and association rule mining.The output of this phase has been forwarded to a three-layer deep learning model for final prediction.Numerous experiment has been performed to test the efficiency of the proposed XLNet-Bi-LSTM model.It has been shown that the proposed model achieved 94.2%prediction accuracy.

Epidemioclinical Aspects of Childhood Domestic Accidents in the Emergency Department of Boffa Hospital

Introduction: Domestic accidents are defined as accidents that occur in the home or its immediate surroundings. Objective: To describe the epidemioclinical and therapeutic aspects. Patients and Methods: Prospective, descriptive study from July 1, 2019 to June 30, 2020 in the emergency department of Boffa prefectural hospital included all children aged 0 to 15 years admitted for domestic accidents. Results: Of 120 cases of accidental trauma, 56 were domestic accidents. The mean age was 7.08 years. The 0 - 5 and 11 - 15 age groups were the most represented (35.71%). The sex ratio was 1.55 in favor of boys. Domestic accidents were represented by falls (26.78%), thermal burns (21.43%), snakebite wounds (17.86%) and dog bites (10.71%), drowning (5.36%), and electrification by lightning (3.60%), one case or 1.78% of each of the following: esophageal foreign body by palm nut, firearm, wall collapse, stretching of upper limb. Paracetamol was the molecule most frequently used (89.28%). The outcome was favorable in 92.86% of cases. However, four (4) deaths were recorded. Conclusion: Domestic accidents remain a significant pathology at Boffa prefectural hospital.