Research on Risk Identification and Industrial Governance of Digital Education Products Based on Data Annotation Technology

The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.

Life Time Attributable Cancer Risk Estimated Using Scanner Reported Dose Length Product during Chest Computed Tomography Imaging in Young Children

This study aims to estimate the lifetime attributable cancer risk (LAR) for pediatric chest computed tomography (CT) examinations in five age groups using recently published age and region-specific conversion coefficients multiplying the widely available scanner registered dose length products (DLP) displayed on the CT console and hence calculating the Effective Dose (ED). The ED is then multiplied by the International Commission on Radiological Protection (ICRP) published risk factor for LAR. The obtained LAR values are compared with the international literature. Factors that may affect the LAR value are reported and discussed. The study included one hundred twenty five chest CT examinations for both males and females aged from less than one year to fifteen years. The patients reported data are from one single medical institution and using two CT scanners from June 2022 to December 2023. The results of this study may serve as benchmark for institutional radiation dose reference levels and risk estimation.

Sources of Farm Risk and Management Strategies among Cowpea(Vigna unguiculata SSP)Producers in North East Nigeria

The study identified sources of farm risks and management strategies used among cowpea producers in North East,Nigeria.Data were collected using structured questionnaires from 595 cowpea producers.Multi-stage sampling procedure was used to select cowpea producers for the study.In the first stage purposive sampling was used to select three(3)states from the six(6)states in the region and these states include Adamawa,Bauchi and Gombe States.From these selected states two(2)local governments each were selected based on apriory information on cowpea production from the state Agricultural Development Programs(ADPs)and analysed using descriptive statistics,Likert scale and multiple regression model.The result revealed that,pest and diseases emerged as the common source of production risk at 74%.Also,uncertainty from product price 66%was a major source of marketing risk.Furthermore,inadequate credit was an important financial risk at 54%and lack of cooperative 51%were major sources of both financial and institutional risks.The valid management strategies used in mitigating/coping among cowpea producers were livestock production to complement income,sales of produce,engagement in other jobs/activities,access to ADP’s extension agent among others.Therefore,cowpea production is affected by production/environmental risk,marketing risk,financial risk,institutional risk and human/personnel risk and exhibited risk aversion attitude.The study recommends strategy of developing early varieties,disease resistant crops and products that are resistant to pest both in the farm and storage to raise the productivity of cowpea.Also,cowpea producers’cooperatives should be strengthened with priority given enlightened/educating members,create strong bargaining power for farm products as well as accessing credit facilities.Similarly,inputs such as fertilizers and certified improved high-quality seeds are available and accessible to cowpea producers to increase production and reduce risks.

Problems of Training Konni Producers in the Context of Reforming the Management of Hydroagricultural Developments: Challenges, Issues and Perspectives

Following the reform of the governance of irrigation schemes in Niger, producer cooperatives are encountering real difficulties in ensuring effective and efficient management of irrigation water, infrastructure maintenance and renewal of hydromechanical equipment. The objective of this research is to analyze the issues and challenges of capacity building for Konni producers in the context of AHA management reform in Niger. The methodological approach adopted is based on documentary research and field surveys with all the actors directly concerned with the management of the Konni irrigated perimeter. A total of 448 people were interviewed in all the localities selected. Direct observation and interview are the two field data collection techniques adopted. The data collected was processed and on the basis of the established diagnosis, the training needs were identified. The results show that there are several experiences in terms of training and capacity building of actors in charge of the management of irrigation systems at the Konni AHA level. However, the sustainability of the perimeter is threatened by various crises. The main themes that founded the first training were related to the mobilization, transport and distribution of irrigation water, operation and maintenance, and setting and collection of the fee. In view of the expectations of operators, future issues and challenges, the training modules are increasingly oriented towards social management, the integration of gender in management and environmental impacts. Even if technical progress is possible, the real lever is organizational and requires the professionalization of irrigators. This process requires a new pedagogical approach aimed at irrigators.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Natural Disaster Risk Monitoring for Immovable Cultural Relics Based on Digital Twin

Natural disaster risk monitoring is an important task for disaster prevention and reduction.In the case of immovable cultural relics,however,the feedback mechanism,risk factors,monitoring logic,and monitoring indicators of natural disaster risk monitoring are complex.How to achieve intelligent perception and monitoring of natural disaster risk for immovable cultural relics has always been a focus and a challenge for researchers.Based on the analysis of the concepts and issues related to the natural disaster risk of immovable cultural relics,this paper proposes a framework for natural disaster risk monitoring for immovable cultural relics based on the digital twin.This framework focuses on risk monitoring,including the physical entities of natural disaster risk for immovable cultural relics,monitoring indicators,and virtual entity construction.A platform for monitoring the natural disaster risk of immovable cultural relics is proposed.Using the Puzhou Ancient City Site as a test bed,the proposed concept can be used for monitoring the natural disaster risk of immovable cultural relics at different scales.

Automatic detection of small bowel lesions with different bleeding risks based on deep learning models

BACKGROUND Deep learning provides an efficient automatic image recognition method for small bowel(SB)capsule endoscopy(CE)that can assist physicians in diagnosis.However,the existing deep learning models present some unresolved challenges.AIM To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks,and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding groups.METHODS The proposed model represents a two-stage method that combined image classification with object detection.First,we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images,normal SB mucosa images,and invalid images.Then,the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding,and the location of the lesion was marked.We constructed training and testing sets and compared model-assisted reading with physician reading.RESULTS The accuracy of the model constructed in this study reached 98.96%,which was higher than the accuracy of other systems using only a single module.The sensitivity,specificity,and accuracy of the model-assisted reading detection of all images were 99.17%,99.92%,and 99.86%,which were significantly higher than those of the endoscopists’diagnoses.The image processing time of the model was 48 ms/image,and the image processing time of the physicians was 0.40±0.24 s/image(P<0.001).CONCLUSION The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images,which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.

Risk preferences and the low-carbon agricultural technology adoption:Evidence from rice production in China

Climate change which is mainly caused by carbon emissions is a global problem affecting the economic development and well-being of human society.Low-carbon agriculture is of particular significance in slowing down global warming and reaching the goal of“carbon peak and carbon neutrality”.Therefore,taking straw incorporation as an example,this paper aims to investigate the impact of risk preferences on farmers’low-carbon agricultural technology(LCAT)adoption.Based on a two-phase micro-survey data of 1038 rice farmers in Jiangsu,Jiangxi,and Hunan provinces,this paper uses experimental economics methods to measure farmers’risk aversion and loss aversion to obtain the real risk preferences information of the farmers.We also explore the data to examine the actual LCAT adoption behavior of farmers.The results revealed that both risk aversion and loss aversion significantly inhibit farmers’LCAT adoption:more risk-averse or more loss-averse farmers are less likely to adopt LCAT.It is further found that crop insurance,farm scale and governmental regulations can alleviate the negative impact of risk aversion and loss aversion on farmers’LCAT adoption.Therefore,we propose that local governments need to promote low-carbon agricultural development by propagating the benefits of LCAT,extending crop insurance,promoting appropriate scale operations,and strengthening governmental regulations to promote farmers’LCAT adoption.

Purification of Produced Water from a Sour Oilfield in South Kuwait. 1. Oil-Water Separation and Industrial Salt Production

Produced water from an oil extraction site in South Kuwait was sampled after primary oil – water separation had been carried out. The produced water was filtered through a mixture of activated charcoal and esterified cellulosic material gained from spent coffee grounds as a tertiary adsorption treatment. The earth-alkaline metal ions and heavy metals were separated from the de-oiled produced water by addition of either sodium or potassium hydroxide in the presence of carbon dioxide or by direct addition of solid sodium carbonate. The resulting filtrate gave salt of industrial purity upon selective crystallization on evaporation.

Development of Localized Assessment of Municipal Wastewater Disposal Risks

A means to develop a comparative assessment of the risks of available wastewater effluent disposal options on a local scale needs to be developed to help local decision-makers make decisions on options such as direct or indirect potable reuse options. These options have garnered more interest as a result of water supply limitations in many urban areas. This risk assessment was developed from a risk assessment developed at the University of Miami in 2001 and Florida Atlantic University (FAU) in 2023. Direct potable reuse and injection wells were deemed to have the lowest risk in the most recent study by FAU. However, the injection well option may not be available everywhere. As a result, a more local means to assess exposure risk is needed. This paper outlines the process to evaluate the public health risks associated with available disposal alternatives which may be very limited in some areas. The development of exposure pathways can help local decision-makers define the challenges, and support later expert level analysis upon which public health decisions are based.

Survey and Prospect for Applying Knowledge Graph in Enterprise Risk Management

Enterprise risk management holds significant importance in fostering sustainable growth of businesses and in serving as a critical element for regulatory bodies to uphold market order.Amidst the challenges posed by intricate and unpredictable risk factors,knowledge graph technology is effectively driving risk management,leveraging its ability to associate and infer knowledge from diverse sources.This review aims to comprehensively summarize the construction techniques of enterprise risk knowledge graphs and their prominent applications across various business scenarios.Firstly,employing bibliometric methods,the aim is to uncover the developmental trends and current research hotspots within the domain of enterprise risk knowledge graphs.In the succeeding section,systematically delineate the technical methods for knowledge extraction and fusion in the standardized construction process of enterprise risk knowledge graphs.Objectively comparing and summarizing the strengths and weaknesses of each method,we provide recommendations for addressing the existing challenges in the construction process.Subsequently,categorizing the applied research of enterprise risk knowledge graphs based on research hotspots and risk category standards,and furnishing a detailed exposition on the applicability of technical routes and methods.Finally,the future research directions that still need to be explored in enterprise risk knowledge graphs were discussed,and relevant improvement suggestions were proposed.Practitioners and researchers can gain insights into the construction of technical theories and practical guidance of enterprise risk knowledge graphs based on this foundation.

A risk assessment method considering risk attributes and work safety informational needs and its application

The technological revolution has spawned a new generation of industrial systems,but it has also put forward higher requirements for safety management accuracy,timeliness,and systematicness.Risk assessment needs to evolve to address the existing and future challenges by considering the new demands and advancements in safety management.The study aims to propose a systematic and comprehensive risk assessment method to meet the needs of process system safety management.The methodology first incorporates possibility,severity,and dynamicity(PSD)to structure the“51X”evaluation indicator system,including the inherent,management,and disturbance risk factors.Subsequently,the four-tier(risk point-unit-enterprise-region)risk assessment(RA)mathematical model has been established to consider supervision needs.And in conclusion,the application of the PSD-RA method in ammonia refrigeration workshop cases and safety risk monitoring systems is presented to illustrate the feasibility and effectiveness of the proposed PSD-RA method in safety management.The findings show that the PSD-RA method can be well integrated with the needs of safety work informatization,which is also helpful for implementing the enterprise's safety work responsibility and the government's safety supervision responsibility.

Purification of Produced Water from a Sour Oilfield in South Kuwait. 2. Oil-Water Separation and Crystallization of Calcium Carbonate

Oil-water separation for produced water (PW) originating from an oil extraction site in South Kuwait was carried out using bleached, esterified cellulosic material from used coffee grounds. Thereafter, earth-alkaline metal ions, specifically calcium ions, of the de-oiled PW were removed by precipitation with sodium carbonate to give access to pure sodium chloride as industrial salt from the remaining PW. While the purity of the precipitated calcium carbonate (CaCO3) depends on the precipitation conditions, CaCO3 of up to 95.48% purity can be obtained, which makes it a salable product. The precipitation of CaCO3 decreases the amount of calcium ions in PW from 11,300 ppm to 84 ppm.

Climate change drives flooding risk increases in the Yellow River Basin

The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.

Cardiovascular health awareness,risk perception,behavioural intention and INTERHEART risk stratification among middle-aged adults in Malaysia

Objective:To investigate the interrelationship between cardiovascular health awareness,risk perception,behavioural intention,and INTERHEART risk stratification in a middle-aged adult population in Malaysia.Methods:A cross-sectional survey with convenience sampling was conducted during November 2022 and January 2023.Participants completed validated questionnaires assessing cardiovascular health awareness,risk perception of cardiovascular diseases,behavioural intention towards adopting healthy habits,and INTERHEART risk stratification score(IHRS)based on established risk factors.A total of 602 respondents were included in the final analysis.Data were analysed with independent t-test/one-way ANOVA or Mann-Whitney/Kruskal-Wallis to test the differences,Pearson correlation or linear regression test to analyze the association of independent and dependent variables.Results:There was a significant positive correlation between medical knowledge related to cardiovascular disease(CVD)and knowledge related to CVD risk prevention,risk perception,behavioural intention and IHRS(P<0.05,Pearson correlation).Notably,individuals with higher IHRS tended to have lower knowledge related to CVD and CVD risk prevention,risk perception,and behavioural intention.Males,laborers,active/former smokers,individuals with lower household income and educational levels,those involved in occupations not related to the healthcare sector,and those who did not receive the CVD health brochure or are unaware of health self-assessment tools are likely to have lower levels of knowledge,risk perception,and poorer behavioural intention regarding cardiovascular health(P<0.05,one-way ANOVA).While educational level,smoking status,awareness about CVD poster,self-assessment tools were repeatedly significantly associated with knowledge related to CVD and CVD risk prevention,risk perception,behavioral intention and/or IHRS(P<0.05,linear regression).Conclusions:These findings underscore the importance of promoting cardiovascular health awareness and risk perception among middle-aged adults to foster positive BI and reduce CVD risk.Tailored interventions targeting specific risk factors identified by INTERHEART may enhance risk stratification accuracy and facilitate targeted preventive strategies.

Construction and validation of a risk-prediction model for anastomotic leakage after radical gastrectomy: A cohort study in China

Objectives:Anastomotic leakage(AL)stands out as a prevalent and severe complication following gastric cancer surgery.It frequently precipitates additional serious complications,significantly influencing the overall survival time of patients.This study aims to enhance the risk-assessment strategy for AL following gastrectomy for gastric cancer.Methods:This study included a derivation cohort and validation cohort.The derivation cohort included patients who underwent radical gastrectomy at Sir Run Run Shaw Hospital,Zhejiang University School of Medicine,from January 1,2015 to December 31,2020.An evidence-based predictor questionnaire was crafted through extensive literature review and panel discussions.Based on the questionnaire,inpatient data were collected to form a model-derivation cohort.This cohort underwent both univariate and multivariate analyses to identify factors associated with AL events,and a logistic regression model with stepwise regression was developed.A 5-fold cross-validation ensured model reliability.The validation cohort included patients from August 1,2021 to December 31,2021 at the same hospital.Using the same imputation method,we organized the validation-queue data.We then employed the risk-prediction model constructed in the earlier phase of the study to predict the risk of AL in the subjects included in the validation queue.We compared the predictions with the actual occurrence,and evaluated the external validation performance of the model using model-evaluation indicators such as the area under the receiver operating characteristic curve(AUROC),Brier score,and calibration curve.Results:The derivation cohort included 1377 patients,and the validation cohort included 131 patients.The independent predictors of AL after radical gastrectomy included age65 y,preoperative albumin<35 g/L,resection extent,operative time240 min,and intraoperative blood loss90 mL.The predictive model exhibited a solid AUROC of 0.750(95%CI:0.694e0.806;p<0.001)with a Brier score of 0.049.The 5-fold cross-validation confirmed these findings with a calibrated C-index of 0.749 and an average Brier score of 0.052.External validation showed an AUROC of 0.723(95%CI:0.564e0.882;p?0.006)and a Brier score of 0.055,confirming reliability in different clinical settings.Conclusions:We successfully developed a risk-prediction model for AL following radical gastrectomy.This tool will aid healthcare professionals in anticipating AL,potentially reducing unnecessary interventions.

Survey on Knowledge of Cardiovascular Disease Risk Factors in the Dakar Region

Introduction: Non-communicable diseases constitute a major public health problem, due to their morbi-mortality. The aim was to study knowledge of cardiovascular risk factors among residents of Dakar. Patients and Methods: This was a descriptive cross-sectional study. Our investigations were recruited over a six-month period (October 17, 2021 to March 21, 2022). Results: Two hundred and twenty-six (226) patients were enrolled. The mean age was 45.9 years. The under-40 age group was the most represented with 37.2%. There were 129 men (57.1%), giving a male/female sex ratio of 1.33. The highest level was represented by 159 people (70.4%). Those who responded (heart disease) were in the majority (38.1%). Hypertension was the most common CVD for 101 people (44.7%). One hundred and ninety (190) people (84%) knew the risk factors for CVD. Good knowledge of risk factors concerned 103 people (54.2%). Obesity was the best-known risk factor in 156 cases (69%). The media was the most important source of information for 121 people (53.5%). Hypertensives were the most represented with 8.4%. One hundred and thirty (130) people (57.5%) had previously paid attention to these FDRCVs. Awareness campaigns were the most effective means of communication for 170 cases (75.2%). Sixteen (16) people (35.6%) were taking antihypertensive medication. Walking was the most popular physical activity for 102 people (45%). People with a balanced diet were in the majority, with 174 respondents (77.0%). Conclusion: NCDs are a major cause of morbidity and mortality. It is essential to develop and implement a prevention and management program.

Prevalence of Mastitis and Associated Risk Factors in Lactating Camels (Camelus Dromedarius) on Dairy Farms in Benadir Region, Somalia

The study took a comprehensive approach to understanding mastitis in lactating camels, a disease that significantly impacts milk quantity and quality. This complex and multifactorial disease poses a significant challenge to dairy camel farming, particularly in Somalia. The studys objective was to determine the prevalence of mastitis and the risk factors associated with it among lactating camels on dairy farms in Benadir, Somalia. To achieve this, a cross-sectional study was conducted from May to September 2022 in the Benadir region of Somalia. A total of 96 lactating camels underwent examination using the California Mastitis Test (CMT) to identify clinical and subclinical mastitis cases. Additionally, a questionnaire survey was conducted among 20 farm employees/owners to gather information on hygiene practices, parity, lactation stage, tick infestation, and the presence of udder/teat lesions. Data regarding parity and lactation stage were obtained through owner interviews. The data collected on specifically designed forms were recorded and entered into a Microsoft Excel spreadsheet for analysis using SPSS version 20 statistical software, ensuring a comprehensive and reliable analysis of the data. The studys findings revealed a significant prevalence of camel mastitis, with 34.4% (33/96) of lactating camels affected and clinical and subclinical cases constituting 5.2% and 29.2%, respectively. Quarter-level prevalence was 46.3%, with clinical and subclinical mastitis at 4.7% and 41.6%, respectively. The study also identified significant associations (P < 0.05) among risk factors such as stage of lactation, parity, and age, indicating a higher susceptibility to mastitis in older camels during early lactation compared to those in late lactation and younger camels. These findings underscore the crucial role of inadequate hygienic conditions on camel farms and udder tick infestations in driving the elevated prevalence of mastitis, highlighting the need for improved management practices in dairy farming in Benadir, Somalia. Effective interventions, including improved management practices and extension services, are essential to reduce the burden of mastitis in dairy camels.

Understanding Osteoporosis: Pathophysiology, Risk Factors, Diagnosis, and Management

Osteoporosis is a systemic skeletal disease characterized by low bone mineral density (BMD) and deterioration of bone architecture, resulting in reduced bone strength and, consequently, increased susceptibility to fractures which poses a significant public health concern worldwide, particularly in aging populations [1]. The health-economic impact of vertebral and hip fractures has been extensively explored and it is well known that these fractures are associated with morbidity/disability and increased mortality;they also account for a substantial portion of the direct fracture costs. This review aims to provide a comprehensive overview of osteoporosis, including its pathophysiology, risk factors, diagnostic approaches, and management strategies. By elucidating the multifaceted nature of this condition, healthcare providers can better identify individuals at risk, implement preventive measures, and optimize treatment to reduce the burden of osteoporotic fractures.