An Improved Spatially Aware Routing Algorithm for Mobile Ad Hoc Network in Inter-Vehicle Communication

A new algorithm called spatially aware routing algorithm with enhanced learning (SAREL) is proposed to guarantee the rationality of route selecting in inter-vehicle communication scenario. Firstly, the traffic model is discussed and set up by using Poisson distribution. Then we analyze the process of traffic evaluation with enhanced learning, and exploit movement estimation to assist state memorization. The improvement of algorithm is provided at last compared with our previous work. Simulation results show that SAREL algorithm could achieve better performance in packet delivery ratio, especially when network connection ratio is average. Key words mobile ad hoc network - spatially aware routing - enhanced learning CLC number TP 316 Foundation item: Supported by Open Laboratory Foundation by China Ministry of Education (TKLJ9903), Project CarTALK 2000 by the European Commission (IST-2000-28185) and Project FleetNet-Internet on the Road by the German Ministry of Education and Research (01AK025)Biography: HAN Lu (1974-), male, Ph. D candidate, research direction; distributed artificial intelligence.

Prevalence, Awareness and Risk Factors for Hypertension in Adults Attending a Tertiary Hospital in South-East Nigeria

Hypertension, a non-communicable disease, is considered a major public health challenge because of its widespread prevalence globally coupled with its huge morbidity and mortality burden, which is largely preventable if early detection and prompt initiation of management are done. Hypertension prevalence is increasing especially in the developing world, despite this, its awareness among the general population is low. This study aimed at determining the prevalence of hypertension among adult attendees of the General Outpatient Clinic of the Federal University Teaching Hospital (FUTH), Owerri, with an assessment of the proportion of hypertensives who were aware of their hypertensive status, and identifying risk factors of hypertension in the study participants. A cross-sectional analytical study was conducted between October and November 2022 at the General Outpatient Clinic of the FUTH, Owerri. A total of 257 consenting and eligible adult patients made up of 135 males and 122 females, aged 18 years and above, were selected by systematic random sampling method. The overall prevalence of hypertension was 34.6%. The prevalence was higher in females than in males (37.7% vs 31.9%, P = 0.325). Among the hypertensive subjects 56.2% had awareness of their hypertensive status. Following a multiple regression analysis, hypertension was independently associated with age, family history of hypertension, occupation (retirees, traders, farmers and the unemployed), and marital status (being widowed). Hypertension is prevalent in our environment;the prevalence rate from this study is higher than in most studies in our environment, suggesting possibly, a rising burden. The results from the study underscore the need for increased and sustained advocacy for implementation of policies and programs directed at increased detection and management of hypertension in the different population groups such as annual wellness check for employees in the formal sector, largescale dietary and lifestyle adjustments, and know your numbers (an approach to population driven blood pressure check for all adults). Also, health workers should use any opportunity of contact with a patient to screen for hypertension.

Depressive semantic awareness from vlog facial and vocal streams via spatio-temporal transformer

With the rapid growth of information transmission via the Internet,efforts have been made to reduce network load to promote efficiency.One such application is semantic computing,which can extract and process semantic communication.Social media has enabled users to share their current emotions,opinions,and life events through their mobile devices.Notably,people suffering from mental health problems are more willing to share their feelings on social networks.Therefore,it is necessary to extract semantic information from social media(vlog data)to identify abnormal emotional states to facilitate early identification and intervention.Most studies do not consider spatio-temporal information when fusing multimodal information to identify abnormal emotional states such as depression.To solve this problem,this paper proposes a spatio-temporal squeeze transformer method for the extraction of semantic features of depression.First,a module with spatio-temporal data is embedded into the transformer encoder,which is utilized to obtain a representation of spatio-temporal features.Second,a classifier with a voting mechanism is designed to encourage the model to classify depression and non-depression effec-tively.Experiments are conducted on the D-Vlog dataset.The results show that the method is effective,and the accuracy rate can reach 70.70%.This work provides scaffolding for future work in the detection of affect recognition in semantic communication based on social media vlog data.

Awareness of Diabetic Retinopathy in Diabetic Individuals Based on Knowledge, Attitude, and Practice in Cameroon: A Multicentre Study

Introduction: Diabetic retinopathy accounts for 5% of all causes of blindness. We set out to assess knowledge, attitude, and practice patterns in patients with diabetes regarding diabetic retinopathy (DR) and identify barriers that may exist in this context. Material and Methods: We conducted a cross-sectional study by consecutively enrolling patients with diabetes consulting at four hospitals in Cameroon between November 2021 and March 2023. We surveyed participants about their understanding of diabetic retinopathy (DR), their approach to it, and their visits to eye specialists by means of a single-investigator-interviewer-administered questionnaire. Data was anonymously analysed using STATA/BE 17 and presented in frequencies and Spearman’s correlation coefficient. The error margin was 5% and all results with p-value Results: We enrolled 152 patients with type 2 diabetes mellitus, with a mean age of 60.30 years and a male-to-female ratio of 0.9. Out of the 152 patients enrolled, 138 (90.59%) agreed that the eyes could be damaged by diabetes. Meanwhile, only 21 (15.79%) associated diabetes with DR. Of the 41.18% who were occasionally sent for an eye exam by their consulting physicians, 91.72% made it to the consultations. Spearman’s correlation showed no significant relationship between the knowledge of eye involvement in diabetes and visits to eye specialists, regardless of blood sugar levels (p = 0.30). Conclusion: We were able to show that there is a lack of sensitization of patients with diabetes on diabetic retinopathy and referral to ophthalmologists.

Awareness of the Termination of Pregnancy Act of the Laws of Zambia among Women of Reproductive Age at Kanyama First Level Hospital in Lusaka District Zambia

Background: Termination of pregnancy (TOP) in Zambia is guided by the Termination of Pregnancy (TOP) Act of 1972 and as amended in 1994 of the laws of Zambia. However, despite provision of Comprehensive abortion care services with the liberal law, statistics at Kanyama First Level Hospital in relation to unsafe illegal abortions are alarming. This study sought to understand the Awareness on the TOP Act of the laws of Zambia among women of reproductive age 15 - 49 years at Kanyama First Level Hospital in Lusaka District. Purpose of the Study: To assess awareness on the TOP Act among women of reproductive age at Kanyama First Level Hospital in Lusaka, Zambia. Methodology: A convergent parallel mixed method design was conducted using both survey and in-depth interviews among women of reproductive age at Kanyama First Level Hospital in Lusaka District. The study surveyed 370 randomly sampled women aged 15 to 49 years old while the in-depth interviews included eight women purposively sampled from the survey population. Survey data was analyzed using descriptive and inferential statistics while qualitative data thematic analysis was used. Results: The study found that 37% of the participants were aware of the TOP Act while 63.8% viewed legalization of abortion for any reason as wrong. The study results also showed that widowed women were 8 times more likely to be aware of the TOP Act compared to single women (AOR: 8.262;95% CI: 1.105, 61.778). Women in business were significantly more likely to be aware of the TOP Act compared to those who reported having no occupation. (AOR: 2.61;95% CI: 1.246, 5.499). Limited access to information, the social stigma attached to abortion, health care providers’ attitudes, cultural norms, values and religious beliefs, restrictive legal requirements, and absence of a supportive network were some of the barriers affecting awareness and utilization of available safe abortion care services. Conclusions: The research findings concluded that a significant lack of awareness among women of reproductive age regarding the Termination of Pregnancy (TOP) Act. The majority of respondents held the view that abortion should only be legalized for medical reasons. Furthermore, there was a notable gap in knowledge concerning the penal code’s provisions on abortion.

Promoting Sickle Cell Trait Awareness and Education: A Typology of Interventions in the United States to Inform Ongoing Efforts to Patients and Providers

Research Background: Sickle cell trait has no treatment or cure and predominantly affects people who are Black, but can affect anyone of any race or ethnicity. While commonly incorrectly considered benign by providers and the public, people with a sickle cell trait experience life-threatening outcomes that are exacerbated by extreme conditions. There is a severe lack of awareness and understanding of sickle cell trait and the associated health complications among sickle cell trait carriers and healthcare providers. Purpose/Aim: Interventions that aim to improve awareness of sickle cell trait differ in approaches and are not well documented in the literature. This typology aims to highlight current efforts to inform targeted interventions that raise awareness through consistent messaging, educate people and providers on sickle cell trait and the related health complications, and support the design and implementation of comprehensive sickle cell trait awareness initiatives. Methods: We conducted a scoping review of United States-based sickle cell trait interventions and performed a content analysis to identify the categories and characteristics of these efforts. We then organized the results into a typology according to established protocols. Results: Among 164 interventions, twenty-five (15%) met the typology inclusion criteria described above and were grouped into categories: Seven of twenty-five interventions were Educational Interventions (28%), three of twenty-five interventions (12%) were Combined Screening and Educational-Based Interventions, eight of twenty-five interventions (32%) were Policy and Guideline-Based Intervention, and six of twenty-five interventions (24%) were Sickle Cell Trait Organization-Led Interventions. Conclusions: There is a lack of consistency in messaging across interventions whether delivered by credible healthcare institutions or national organizations, which can result in lack of education and awareness and confusion around sickle cell trait. Categorizing interventions through a typology allows clarity and informs consistency in messaging, which should be at the forefront of future sickle cell trait efforts.

Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving

Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles.Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle collisions.However,they suffer from over-conservatism,potentially resulting in false–positive risk events in complicated real-world applications.In this paper,we combine two reachability analysis techniques,a backward reachable set(BRS)and a stochastic forward reachable set(FRS),and propose an integrated probabilistic collision–detection framework for highway driving.Within this framework,we can first use a BRS to formally check whether a two-vehicle interaction is safe;otherwise,a prediction-based stochastic FRS is employed to estimate the collision probability at each future time step.Thus,the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety-critical events.To construct the stochastic FRS,we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction accuracy.Extensive experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving data.The efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway scenarios.The proposed risk assessment framework is promising for real-world applications.

Data Mining and Spatial Analysis of Social Media Text Based on the BERT-CNN Model to Achieve Situational Awareness: a Case Study of COVID-19

In response to the COVID-19,social media big data has played an important role in epidemic warning,tracking the source of infection,and public opinion monitoring,providing strong technical support for China’s epidemic prevention and control work.The paper used Sina Weibo posts related to COVID-19 hashtags as the data source,and built a BERT-CNN deep learning model to perform fine-grained and high-precision topic classificationon massive social media posts.Taking Shenzhen as a region of interest,we mined the“epidemic data bulletin”and“daily life impact”posts during the epidemic for spatial analysis.The results show that the confirmed communities and designated hospitals in Shenzhen as a whole present the characteristics of“sparse east and dense west”,and there is a strong positive spatial correlation between the number of confirmed cases and social media response.Specifically,Nanshan District,Futian District and Luohu District have more confirmed cases due to large population movements and dense transportation networks,and social media has responded more violently,and people’s lives have been greatly affected.However,Yantian District,Pingshan District and Dapeng New District showed opposite characteristics.The case study results further show that using deep learning methods to mine text information in social media is scientifically feasible for improving situational awareness and decision support during the COVID-19.

Awareness, Practice and Intention to Practice Testicular Self-Examination among Professional Working Males in Ghana

Background: The aetiology of Testicular Cancer (TC) is still unknown to researchers but many of the associated risk factors have been identified. These include family history, age, racial origin, cryptorchidism, urogenital malformations, testicular atrophy, and infertility. Given the lack of scientific data on the causes of the disease, it has been asserted in previous studies that the promotion of awareness and early detection are prerequisites to mitigating risks of metastasis as well as improving survival. This study is to assess the awareness, practice, and intention to practice testicular self-examination among professional working males in Accra. Methods: A quantitative cross-sectional design with a structured research instrument was used to collect data from respondants. The purposive and convenience sampling techniques were used to collect data from 300 men at Accra in Ghana. The study was conducted at two (2) Universities and a Senior High school at Accra in Ghana. The data was then analysed using descriptive statistics, logistic regression, multiple linear regression, and structural equation modeling. Results: From the study findings, 37% of male participants rated their knowledge of testicular self-examination and related symptoms as good, 28% of participants practised testicular self-examination monthly, while 65% of respondents expressed their intention to practice monthly testicular self-examination. The findings from logistic regression demonstrated that level of education, age, and marital status of participants had a significant influence on testicular self-examination. Additionally, the multiple linear regression results revealed knowledge and self-efficacy significantly predict testicular self-examination intention. The path coefficient results from the structural equation model are consistent with results from the regression models. Conclusion: This research is the first to investigate testicular self-examination among men in Ghana. The findings revealed awareness and practice of TSE are low among participants. Therefore, the research findings would improve the expertise of physicians and nurses in providing counsel, intervention, and support for patients at risk of testicular cancer.

Household Solid Waste Awareness and Practices among Residents of Windhoek, Namibia

This study explores household solid waste management (HSWM) practices and awareness among residents of Windhoek West, a rapidly urbanizing constituency in the Khomas Region of Namibia. Employing a descriptive methodology, the research investigates the interplay between public awareness, regulatory frameworks, and the availability of waste management facilities to assess their impact on waste management behaviors. Our findings indicate significant gaps in both knowledge and infrastructure that hinder effective waste management. The study reveals that while there is a high willingness among residents to engage in recycling and waste reduction, actual practices are limited due to inadequate facilities and lack of stringent enforcement of waste policies. This research identifies key factors that influence waste management practices, including demographic characteristics and access to waste management facilities. It also proposes actionable strategies such as expanding recycling and sorting facilities, enhancing educational campaigns tailored to local needs, and implementing regular enforcement mechanisms. These strategies are aimed at improving compliance with waste management protocols and fostering a culture of environmental responsibility. The results of this investigation show the critical role of ongoing education and infrastructural improvement in bridging existing knowledge gaps and facilitating effective waste management practices. This research lays a foundational step toward enhancing sustainable urban development and effective waste management in Windhoek, providing valuable insights for policymakers, community leaders, and stakeholders engaged in urban environmental management.

Impact of educational interventions on mothers’ awareness and communication with their attention-deficit hyperactivity disorder children

Objective:The objectives of this study are to evaluate the effects of the educational intervention on mothers’knowledge,awareness,and communication difficulties experienced with their children and mothers’capacity to successfully interact with their affected child before and after the intervention.Materials and Methods:A quasi-experimental research design was used.A total of 30 mothers and their children complaining of attention-deficit hyperactivity disorder from four Dawadmi primary schools were included.Data were collected through a self-developed questionnaire from September 2023 to January 2024 after study acceptance by Shaqra University’s scientific deanship.Intervention prepared according to subjects’needs and current scientific base and demonstrated in 10 sessions in schools.Results:Regarding mothers’age,more than one-fourth of them(26.7%)ranged from 31 to 35 year old,and about a third(36.7%)had secondary education.Regarding mother’s job,about 76.7%do not work,and the majority of affected children(66.6%)were male,there were significant improvements in mothers’knowledge pre-and postintervention also a significant improvement in mothers’awareness about symptoms of poor attention,hyperactivity,and impulsivity pre-and postintervention was found.Significant differences were found before and after the intervention regarding the impact of the intervention in decreasing mothers’challenges.Conclusion:The study hypothesis was accepted,and the intervention improved mothers;knowledge,awareness,and communication challenges.The intervention should be conducted and followed up for a long period of time to manage all mother’s and children’s daily challenges,improve children’s daily activities,and stabilize effective communication patterns between children and their family members.

Hypertension Prevalence,Awareness,Treatment,and Control and Their Associated Socioeconomic Factors in China:A Spatial Analysis of A National Representative Survey

Objective We aimed to investigate and interpret the associations between socioeconomic factors and the prevalence, awareness, treatment, and control of hypertension at the provincial level in China.Methods A nationally and provincially representative sample of 179,059 adults from the China Chronic Disease and Nutrition Surveillance study in 2015–2016 was used to estimate hypertension burden. The spatial Durbin error model was fitted to investigate socioeconomic factors associated with hypertension indicators.Results Overall, it was estimated that 29.20% of the participants were hypertensive nationwide,among whom, 34.32% were aware of their condition, 27.69% had received antihypertensive treatment,and 7.81% had controlled their condition. Per capita gross domestic product(GDP) was associated with hypertension prevalence(coefficient:-2.95, 95% CI:-5.46,-0.45) and control(coefficient: 6.35, 95% CI:1.36, 11.34) among adjacent provinces and was also associated with awareness(coefficient: 2.93, 95%CI: 1.12, 4.74) and treatment(coefficient: 2.67, 95% CI: 1.21, 4.14) in local province. Beds of internal medicine(coefficient: 2.66, 95% CI: 1.08, 4.23) was associated with control in local province. Old dependency ratio(coefficient:-3.58, 95% CI:-5.35,-1.81) was associated with treatment among adjacent provinces and with control(coefficient:-1.69, 95% CI:-2.42,-0.96) in local province.Conclusion Hypertension indicators were not only directly influenced by socioeconomic factors of local area but also indirectly affected by characteristics of geographical neighbors. Population-level strategies should involve optimizing supportive socioeconomic environment by integrating clinical care and public health services to decrease hypertension burden.

A Deep Learning‑Based Approach for Terminal Area Flight Flow Operational Safety Situation Awareness

Safety is the cornerstone of the civil aviation industry and the enduring focus of civil aviation.This paper uses air traffic complexity and potential aircraft conflict relationships as entry points to study the operational safety level of terminal area flight flows and proposes a deep learning-based method for safety situation awareness in terminal area aircraft operations.Firstly,a more comprehensive and precise safety situation assessment features are constructed.Secondly,a deep clustering situation recognition model with added safety situation information capture layer is proposed.Finally,a spatiotemporal graph convolutional neural network based on attention mechanism is constructed for predicting safety situations.Experimental results from a real dataset show that:(1)The proposed model surpasses traditional models across all evaluated dimensions;(2)the recognition model ensures that the encoded features capture distinctive safety situation information,thereby enhancing model interpretability and task alignment;(3)the prediction model demonstrates superior integrated modeling capabilities in both spatial and temporal dimensions.Ultimately,this paper elucidates the spatiotemporal evolution characteristics of air traffic safety situation levels,offering valuable insights for air traffic safety management.

A Situational Awareness Method for Initial Insulation Fault of Distribution Network Based on Multi-Feature Index Comprehensive Evaluation

Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.

Current status and prospects of research on safety situation awareness of high speed railway operation environment

Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters,perimeter intrusion and external environmental hazards.The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.Design/methodology/approach–In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments,the research status is elaborated,and the latest research progress and achievements of the team are introduced.This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological,perimeter and external environmental situation perception methods for high-speed rail operation.Findings–Based on the technical route of“situational awareness evaluation warning active control,”a technical system for monitoring the safety of high-speed train operation environments has been formed.Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters,perimeter intrusion and the external environment on high-speed rail safety.These works strongly support the improvement of China’s railway environmental safety guarantee technology.Originality/value–With the operation of CR450 high-speed trains with a speed of 400 kmper hour and the application of high-speed train autonomous driving technology in the future,new and higher requirements have been put forward for the safety of high-speed rail operation environments.The following five aspects of work are urgently needed:(1)Research the single factor disaster mechanism of wind,rain,snow,lightning,etc.for high-speed railways with a speed of 400 kms per hour,and based on this,study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment,revealing the coupling disastermechanism ofmultiple influencing factors;(2)Research covers multi-source data fusion methods and associated features such as disaster monitoring data,meteorological information,route characteristics and terrain and landforms,studying the spatio-temporal evolution laws of meteorological disasters,perimeter intrusions and external environmental hazards;(3)In terms of meteorological disaster situation awareness,research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines;(4)In terms of perimeter intrusion,research amulti-modal fusion perception method for typical scenarios of high-speed rail operation in all time,all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and(5)In terms of external environment,based on the existing general network framework for change detection,we will carry out research on change detection and algorithms in the surrounding environment of highspeed rail.

DAUNet: Detail-Aware U-Shaped Network for 2D Human Pose Estimation

Human pose estimation is a critical research area in the field of computer vision,playing a significant role in applications such as human-computer interaction,behavior analysis,and action recognition.In this paper,we propose a U-shaped keypoint detection network(DAUNet)based on an improved ResNet subsampling structure and spatial grouping mechanism.This network addresses key challenges in traditional methods,such as information loss,large network redundancy,and insufficient sensitivity to low-resolution features.DAUNet is composed of three main components.First,we introduce an improved BottleNeck block that employs partial convolution and strip pooling to reduce computational load and mitigate feature loss.Second,after upsampling,the network eliminates redundant features,improving the overall efficiency.Finally,a lightweight spatial grouping attention mechanism is applied to enhance low-resolution semantic features within the feature map,allowing for better restoration of the original image size and higher accuracy.Experimental results demonstrate that DAUNet achieves superior accuracy compared to most existing keypoint detection models,with a mean PCKh@0.5 score of 91.6%on the MPII dataset and an AP of 76.1%on the COCO dataset.Moreover,real-world experiments further validate the robustness and generalizability of DAUNet for detecting human bodies in unknown environments,highlighting its potential for broader applications.

Artificial intelligence awareness and perceptions among pediatric orthopedic surgeons:A cross-sectional observational study

BACKGROUND Artificial intelligence(AI)is a branch of computer science that allows machines to analyze large datasets,learn from patterns,and perform tasks that would otherwise require human intelligence and supervision.It is an emerging tool in pediatric orthopedic surgery,with various promising applications.An evaluation of the current awareness and perceptions among pediatric orthopedic surgeons is necessary to facilitate AI utilization and highlight possible areas of concern.AIM To assess the awareness and perceptions of AI among pediatric orthopedic surgeons.METHODS This cross-sectional observational study was conducted using a structured questionnaire designed using QuestionPro online survey software to collect quantitative and qualitative data.One hundred and twenty-eight pediatric orthopedic surgeons affiliated with two groups:Pediatric Orthopedic Chapter of Saudi Orthopedics Association and Middle East Pediatric Orthopedic Society in Gulf Cooperation Council Countries were surveyed.RESULTS The pediatric orthopedic surgeons surveyed had a low level of familiarity with AI,with more than 60%of respondents rating themselves as being slightly familiar or not at all familiar.The most positively rated aspect of AI applications for pediatric orthopedic surgery was their ability to save time and enhance productivity,with 61.97%agreeing or strongly agreeing,and only 4.23%disagreeing or strongly disagreeing.Our participants also placed a high priority on patient privacy and data security,with over 90%rating them as quite important or highly important.Additional bivariate analyses suggested that physicians with a higher awareness of AI also have a more positive perception.CONCLUSION Our study highlights a lack of familiarity among pediatric orthopedic surgeons towards AI,and suggests a need for enhanced education and regulatory frameworks to ensure the safe adoption of AI.

Women Awareness on the Importance of Agriculture Technologies Using ICT-Based Training Programs

Awareness policy intended to contribute to changing rural women realities to urgent needs of information and gain knowledge was to be demonstrated through in-depth information and communication technology-based(ICTs-based)training program that focused on the importance of advanced agricultural technologies in the production chain in developing countries like Egypt through access and use of the ICTs.Women are becoming well trained on the detailed steps of improved technologies applied in supply chain.Their increased awareness of the necessity of quality management to be followed during their work in the postharvest handling system helped them to produce high-quality products to meet the export requirements of foreign markets and add value to the export quality.Women have been able to reduce the extremely high losses that occurred due to improper handling in particular.The outcomes of proper and healthy procedures,precautions and personal protection were gained by rural women and technicians working in the supply chain.Moreover,women themselves became more confident in their know-how and more comfortable in transgressing cultural norms that inhibited their progress.

Farmers’ Knowledge and Awareness towards the Use of Agrochemicals in Vegetable Cultivation, Fako Cameroon

Agrochemicals are contemporary, omnipresent tool used in vegetable cultivation. Farmers’ knowledge and awareness of the proper usage of agrochemicals are critical for mitigating the negative effects on human health. This cross-sectional study was aimed at assessing the usage knowledge, risk awareness of toxicological and chemical classes, proper handling and use practices for agrochemicals homologated for use in vegetable farming, and the occurrence of health-related symptoms as a result of exposure among these farmers. The study included 93 vegetable growers from agricultural hotspot towns in Fako, southwest Cameroon. The field study, ran from November 2021 to December 2023, using a questionnaire to collect information on farmers demographic, and their knowledge of pesticide classes, and the related risk of associated with the handling of agrochemicals. Results show that all vegetable farmers, particularly those engaged in agribusiness, employ pesticide inputs to maximize production. Six pesticides, two fertilizer types, and one unknown substance were identified. While 23 active compounds were found, the most utilized were abamectin, emamectin (10.46%), dimethoate (9.30%,) and ethoprophos (8.13%). Two active chemicals, dimethoate and methalaxyl, are illegal yet remain in circulation. Toxicological classes I and II, with the greatest harmful effect on human health, were the most commonly utilized (64.27%). Thirty-nine percent of farmers never use personal protection equipment when working with agrochemicals, demonstrating a significant gap in knowledge and awareness of agrochemicals and their various applications and handling procedures in the field. The government should implement an intensive specialized educational program for on-field farmers with incentives in order to promote sustainable agriculture methods that ensure environmental and human safety.

Effect of Health Management in Raising Awareness Rate of Disease Prevention and Treatment in Patients with Prehypertension

Objective: To analyze the effect of health management on improving the awareness rate of disease prevention and treatment in patients with prehypertension, so as to provide guidance for clinical management of patients with prehypertension. Methods: 108 patients diagnosed with prehypertension in our hospital were divided into a control group and an experimental group. The control group was not given management measures, while the experimental group was given health management. The incidence of hypertension and cognition level of hypertension knowledge were compared between the two groups after management. Results: The incidence of hypertension in the experimental group was 7.41% lower than that in the control group 29.63%. The cognitive level of hypertension in the patients (66.54 ± 1.25) was significantly higher than that in the patients without health management (41.45 ± 2.45), and P < 0.05;Conclusion: For patients with prehypertension, the implementation of health management is helpful to improve their cognition of hypertension, master related prevention knowledge, and reduce the incidence of hypertension.