Machine Learning-Based Decision-Making Mechanism for Risk Assessment of Cardiovascular Disease

Cardiovascular disease(CVD)has gradually become one of the main causes of harm to the life and health of residents.Exploring the influencing factors and risk assessment methods of CVD has become a general trend.In this paper,a machine learning-based decision-making mechanism for risk assessment of CVD is designed.In this mechanism,the logistics regression analysismethod and factor analysismodel are used to select age,obesity degree,blood pressure,blood fat,blood sugar,smoking status,drinking status,and exercise status as the main pathogenic factors of CVD,and an index systemof risk assessment for CVD is established.Then,a two-stage model combining K-means cluster analysis and random forest(RF)is proposed to evaluate and predict the risk of CVD,and the predicted results are compared with the methods of Bayesian discrimination,K-means cluster analysis and RF.The results show that thepredictioneffect of theproposedtwo-stagemodel is better than that of the comparedmethods.Moreover,several suggestions for the government,the medical industry and the public are provided based on the research results.

Lead, Zinc and Iron Pollutants Load Assessment in Selected Rivers in Southern Nigeria: Implications for Domestic Uses

The aim of the study is to comparatively assess the concentrations of lead, zinc and iron in Rivers Ase, Warri and Ethiope, in Nigeria. Monthly water samples were collected from six randomly selected sites along the rivers course. 72 water samples were collected from each river at 0 - 15 cm depths. Samples were analysed based on the standard methods recommended by the WHO for testing lead, zinc and iron. The assessment of the water quality was done using the Water Quality Index (WQI) of the Canadian Council of Ministers of the Environment (CCME-WQI). While hypotheses were tested using ANOVA. Findings indicated that CCME-WQI values were 47.3, 66.52 and 78.7. This meant that the water quality of River Ase is impaired and departed from desirable levels, while that of Warri and Ethiope were considered to occasionally be impaired and depart from desirable levels. The ANOVA model showed that there is a significant variation in heavy metal load in the selected rivers at P < 0.05. River water was put to domestic uses such as drinking (20.5%) preparing food (17.8%), bathing (19.8%), washing clothes and dishes (21.3%), brushing teeth (13.3%), and catering for domestic animals (7.5%). Poverty (49.5%) was the major reason for the use of river water for domestic purposes. The locals highlighted that they usually suffer from cholera (26.8%), diarrhoea (25.8%), dysentery (24%) and typhoid (23.5%) as a result of using the river water. The study recommended routine monitoring of anthropogenic and geologic activities, testing of the water regularly amongst others.

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.

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.

Clinical validation of the early embryo viability assessment system: Analysis for the blastocyst morphology and pregnancy outcomes

Objective:To determine the relationship between the early embryo viability assessment(EEVA)and blastocyst morphological parameters and pregnancy outcomes.Methods:This retrospective cohort study was conducted on 291 intracytoplasmic sperm injection cycles including 2522 embryos with indications of prolonging embryo culture to the blastocyst stage in the Genea embryo review incubator,and 511 single vitrified-warmed blastocyst transfer cycles from January 2020 to June 2023.The EEVA system produced an EEVA score from E1(best)to E5(worse)for the potential of blastocyst formation.Blastocyst morphology was evaluated.The association between the EEVA score and each type of blastocyst morphology,implantation rate,clinical pregnancy,and ongoing pregnancy were assessed using generalized estimating equations.Results:The inner cell mass A(ICM A),trophectoderm A(TE A),blastocoele expansion degree of 3,4,5,6,7 rates were higher with lower the EEVA score.The adjusted odd ratio(aOR)(E5 vs E1)was 0.3 for ICM A,0.174 for TE A and 0.210 for BL3,4,5,6,7(all P<0.001),suggesting a significant association between lower EEVA scores and improved embryo quality.The implantation,clinical pregnancy,and ongoing pregnancy rate were also higher with lower the EEVA score.The aOR of E5 vs E1 was 0.245 for implantation,0.185 for clinical pregnancy and 0.200 for ongoing pregnancy rate(P<0.001).Conclusions:There were associations between blastocyst morphology,pregnancy outcome and EEVA scores.The good blastocyst morphology and pregnancy outcomes are higher with lower the EEVA score.

Nutritional Assessment Tools for Patients with Cancer:A Narrative Review

Cancer patients are at high risk of malnutrition,which can lead to adverse health outcomes such as prolonged hospitalization,increased complications,and increased mortality.Accurate and timely nutritional assessment plays a critical role in effectively managing malnutrition in these patients.However,while many tools exist to assess malnutrition,there is no universally accepted standard.Although different tools have their own strengths and limitations,there is a lack of narrative reviews on nutritional assessment tools for cancer patients.To address this knowledge gap,we conducted a non-systematic literature search using PubMed,Embase,Web of Science,and the Cochrane Library from their inception until May 2023.A total of 90 studies met our selection criteria and were included in our narrative review.We evaluated the applications,strengths,and limitations of 4 commonly used nutritional assessment tools for cancer patients:the Subjective Global Assessment(SGA),Patient-Generated Subjective Global Assessment(PG-SGA),Mini Nutritional Assessment(MNA),and Global Leadership Initiative on Malnutrition(GLIM).Our findings revealed that malnutrition was associated with adverse health outcomes.Each of these 4 tools has its applications,strengths,and limitations.Our findings provide medical staff with a foundation for choosing the optimal tool to rapidly and accurately assess malnutrition in cancer patients.It is essential for medical staff to be familiar with these common tools to ensure effective nutritional management of cancer patients.

Comparative study of different machine learning models in landslide susceptibility assessment: A case study of Conghua District, Guangzhou, China

Machine learning is currently one of the research hotspots in the field of landslide prediction.To clarify and evaluate the differences in characteristics and prediction effects of different machine learning models,Conghua District,which is the most prone to landslide disasters in Guangzhou,was selected for landslide susceptibility evaluation.The evaluation factors were selected by using correlation analysis and variance expansion factor method.Applying four machine learning methods namely Logistic Regression(LR),Random Forest(RF),Support Vector Machines(SVM),and Extreme Gradient Boosting(XGB),landslide models were constructed.Comparative analysis and evaluation of the model were conducted through statistical indices and receiver operating characteristic(ROC)curves.The results showed that LR,RF,SVM,and XGB models have good predictive performance for landslide susceptibility,with the area under curve(AUC)values of 0.752,0.965,0.996,and 0.998,respectively.XGB model had the highest predictive ability,followed by RF model,SVM model,and LR model.The frequency ratio(FR)accuracy of LR,RF,SVM,and XGB models was 0.775,0.842,0.759,and 0.822,respectively.RF and XGB models were superior to LR and SVM models,indicating that the integrated algorithm has better predictive ability than a single classification algorithm in regional landslide classification problems.

Distribution, health and ecological risk assessments of trace elements in Nigerian oil sands

The Nigerian oil sands represent the largest oil sand deposit in Africa, yet there is little published information on the distribution and potential health and ecological risks of trace elements in the oil resource. In the present study, we investigated the distribution pattern of 18trace elements(including biophile and chalcophile elements) as well as the estimated risks associated with exposure to these elements. The results of the study indicated that Fe was the most abundant element, with a mean concentration of 22,131 mg/kg while Br had the lowest mean concentration of 48 mg/kg. The high occurrence of Fe and Ti suggested a possible occurrence of ilmenite(Fe TiO_(3)) in the oil sands. Source apportionment using positive matrix factorization showed that the possible sources of detected elements in the oil sands were geogenic, metal production, and crustal. The contamination factor, geo-accumulation index, modified degree of contamination, pollution load index, and Nemerow pollution index indicated that the oil sands are heavily polluted by the elements. Health risk assessment showed that children were relatively more susceptible to the potentially toxic elements in the oil sands principally via ingestion exposure route(HQ > 1E-04). Cancer risks from inhalation are unlikely due to CR < 1E-06 but ingestion and dermal contact pose severe risks(CR > 1E-04). The high concentrations of the elements pose serious threats due to the potential for atmospheric transport, bioaccessibility, and bioavailability.

Assessment of Breast Cancer Prevention Practices among Women Attending Primary Health Care in Abha City, Aseer Region, Saudi Arabia

Cancer is a leading cause of death worldwide, with breast cancer being the most common (2.26 million new cases and 685,000 deaths). In Saudi Arabia, breast cancer ranked the first among females in 2014, accounting for 15.9% of all cancers reported among Saudi nationals and 28.7% of all cancers reported among females of all ages. Early detection of breast cancer could decrease the risks, have a better prognosis, and have better outcomes/more successful treatments. Prevalence of breast cancer reached more than 25% of all diagnosed cancer in the kingdom among women. Aim: This study aims to assess the knowledge and performance of women attending primary care centers about breast self-examination and mammogram screening for prevention and early detection of breast cancer in Abha city primary healthcare centers, Kingdom of Saudi Arabia. Research Method: cross sectional design was conducted by using questionnaire, which was distributed to primary care center nurses. The collected data was statistically analyzed using the Statistical Package for Social Sciences, version 25. Results: The study found that participants had poor awareness and knowledge about breast self-examination, risk factors for breast cancer, and trends and practices in early diagnosis of breast cancer. Conclusion and Recommendations: It recommends increasing awareness campaigns and providing educational programs to improve knowledge and practices.

Research on the Reform of the Process-Tracking Ideological and Political Assessment System in Applied Universities:Taking the Personal Finance Course as an Example

Using the Xi’an Mingde Institute of Technology students as the teaching object and the Personal Finance course as an example,we explore the reform of the ideological and political assessment system of process-tracking courses in applied universities.The article analyzes the feasibility of applying the curriculum ideological and political assessment system in college courses and compares the traditional assessment system.It also proposes that applying curriculum ideological and political assessment to the college curriculum assessment system will help improve students’understanding of the“value guidance”in curriculum ideological and political education and enhance the teaching effect.

Exploration of instantaneous frequency for local control assessment in real-time hybrid simulation

Local control parameters such as instantaneous delay and instantaneous amplitude play an essential role in evaluating the performance and maintaining the stability of real-time hybrid simulation(RTHS).However,existing methods have limitations in obtaining this local assessment in either the time domain or frequency domain.In this study,the instantaneous frequency is introduced to determine local control parameters for actuator tracking assessment in a real-time hybrid simulation.Instantaneous properties,including amplitude,delay,frequency and phase,are then calculated based on analytic signals translated from actuator tracking signals through the Hilbert transform.Potential issues are discussed and solutions are proposed for calculation of local control parameters.Numerical simulations are first conducted for sinusoidal and chirp signals with time varying amplitude error and delay to demonstrate the potential of the proposed method.Laboratory tests also are conducted for a predefined random signal as well as the RTHS of a single degree of freedom structure with a self-centering viscous damper to experimentally verify the effectiveness of the proposed use of the instantaneous frequency.Results from the ensuing analysis clearly demonstrate that the instantaneous frequency provides great potential for local control assessment,and the proposed method enables local tracking parameters with good accuracy.

Comprehensive analysis of advanced glycation end-products in commonly consumed foods:presenting a database for dietary AGEs and associated exposure assessment

Advanced glycation end-products(AGEs)are a group of heterogeneous compounds formed in heatprocessed foods and are proven to be detrimental to human health.Currently,there is no comprehensive database for AGEs in foods that covers the entire range of food categories,which limits the accurate risk assessment of dietary AGEs in human diseases.In this study,we first established an isotope dilution UHPLCQq Q-MS/MS-based method for simultaneous quantification of 10 major AGEs in foods.The contents of these AGEs were detected in 334 foods covering all main groups consumed in Western and Chinese populations.Nε-Carboxymethyllysine,methylglyoxal-derived hydroimidazolone isomers,and glyoxal-derived hydroimidazolone-1 are predominant AGEs found in most foodstuffs.Total amounts of AGEs were high in processed nuts,bakery products,and certain types of cereals and meats(>150 mg/kg),while low in dairy products,vegetables,fruits,and beverages(<40 mg/kg).Assessment of estimated daily intake implied that the contribution of food groups to daily AGE intake varied a lot under different eating patterns,and selection of high-AGE foods leads to up to a 2.7-fold higher intake of AGEs through daily meals.The presented AGE database allows accurate assessment of dietary exposure to these glycotoxins to explore their physiological impacts on human health.

First national standard for river ecological safety assessment comes out

China has always been upholding the harmonious coexistence between man and nature, and protecting eco-environment at home and abroad. Therefore, the first national standard for river ecological safety assessment, GB/T 43474-2023, Technical guidelines for river ecological security assessment, was recently released, which will come into effect on April 1, 2024.

Opportunities to Improve the Quality of Environmental Reports and the Effectiveness of Environmental Impact Assessment: A Case of Electric Power Transmission Systems in Brazil

A good quality Environmental Impact Statement (EIS) is key for the effectiveness of Environmental Impact Assessment (EIA) processes and consequently to the acceptability of projects subject to EIA. The international literature has contributed to the understanding of the essential aspects to be verified regarding the quality of EIS, offering a wide spectrum of good practice examples related to the content of the studies. Even so, there is a need for empirical studies that allow the identification of specific aspects related to the context of application of the EIS, which could lead to the identification of opportunities to improve both the quality of the reports and also the effectiveness of EIA. Therefore, the present paper is focused on the quality review of a number of EIS submitted to the Brazilian Federal Environmental Agency (Ibama) to instruct the assessment of electric power transmission systems. Based on the application of the EIS quality review package as proposed by Lee and Colley (1992), the outcomes reveal opportunities for improving the scope of EIA, analysis of alternatives, prediction of magnitude and the assessment of impact significance. Finally, the development and/or adaptation of a similar tool for the systematic review of the quality of EIA reports is recommended.

MSADCN:Multi-Scale Attentional Densely Connected Network for Automated Bone Age Assessment

Bone age assessment(BAA)helps doctors determine how a child’s bones grow and develop in clinical medicine.Traditional BAA methods rely on clinician expertise,leading to time-consuming predictions and inaccurate results.Most deep learning-based BAA methods feed the extracted critical points of images into the network by providing additional annotations.This operation is costly and subjective.To address these problems,we propose a multi-scale attentional densely connected network(MSADCN)in this paper.MSADCN constructs a multi-scale dense connectivity mechanism,which can avoid overfitting,obtain the local features effectively and prevent gradient vanishing even in limited training data.First,MSADCN designs multi-scale structures in the densely connected network to extract fine-grained features at different scales.Then,coordinate attention is embedded to focus on critical features and automatically locate the regions of interest(ROI)without additional annotation.In addition,to improve the model’s generalization,transfer learning is applied to train the proposed MSADCN on the public dataset IMDB-WIKI,and the obtained pre-trained weights are loaded onto the Radiological Society of North America(RSNA)dataset.Finally,label distribution learning(LDL)and expectation regression techniques are introduced into our model to exploit the correlation between hand bone images of different ages,which can obtain stable age estimates.Extensive experiments confirm that our model can converge more efficiently and obtain a mean absolute error(MAE)of 4.64 months,outperforming some state-of-the-art BAA methods.

Assessment of Dose and Lifetime Risk of Exposure Induced Cancer in Adult Common Computed Tomography Scans in Douala-Cameroon

Background: Among medical technologies that use ionizing radiation, CT is currently the radio diagnostic technic that can deliver the highest radiation to the Patient compared with other conventional procedures. In developing countries, the uses and risks of CT have not been well characterized. Objective: To estimate the lifetime attributable risk (LAR) incidence and mortality for cancer for each procedure for adult’s patients who had Computed Tomography examinations in 10 imaging centers in the city of Douala-Cameroon so as to provide a reference data. Materials and Methods: We conducted a cross-sectional study describing radiation dose associated with the 8 most common types of diagnostic CT studies performed on 1287 consecutive adult patients at 10 Douala radiology department. We estimated lifetime attributable risks of cancer by study type from these measured doses. Estimation of LAR for cancer incidence and mortality was based on the effective dose, patient’s sex and age at exposure using the BIER VII preferred models. Results: Mean effective dose from CT scans examinations varied from: 0.30 and 8.81 mSv. The highest doses were observed for lumbar spine CT (8.81 mSv), followed by abdomen-pelvis procedure (6.46 mSv), chest-abdomen-pelvic CT (6.61 mSv), chest CT (3.90 mSv), cervical Spine CT (3.05 mSv), head CT (1.7 mSv) and lower for sinus CT (0.30 mSv). The LAR values of all cancer from patients’ CT scans obtained vary from 67.13 excess per 100,000 (about 1 in 1489) and 0.45 excess per 100,000 (about 1 in 222,222). All cancer risk was high for lumbar spine CT in women 20 years old (67.13 excess deaths in 100,000 scans) followed by chest-abdomen-pelvic CT (50.36 excess deaths in 100,000 scans) and abdomen-pelvic CT (49.22 excess deaths in 100,000 scans) for the same age group. The LAR of incidence and mortality values were higher from female’s patients than males and higher for younger than older patients. Conclusion: This study was set out to estimate the LAR values associated with adult common CT scans procedures. The data indicates, LAR risks related to induced cancer from CT exposures were estimated to be low. This risk can be relatively significant for younger age group compared to older age group. The LAR values obtained will help to better evaluate radiation exposure risk, before ordering a CT scans examinations.

Postoperative accurate pain assessment of children and artificial intelligence: A medical hypothesis and planned study

Although the pediatric perioperative pain management has been improved in recent years,the valid and reliable pain assessment tool in perioperative period of children remains a challenging task.Pediatric perioperative pain management is intractable not only because children cannot express their emotions accurately and objectively due to their inability to describe physiological characteristics of feeling which are different from those of adults,but also because there is a lack of effective and specific assessment tool for children.In addition,exposure to repeated painful stimuli early in life is known to have short and long-term adverse sequelae.The short-term sequelae can induce a series of neurological,endocrine,cardiovascular system stress related to psychological trauma,while long-term sequelae may alter brain maturation process,which can lead to impair neurodevelopmental,behavioral,and cognitive function.Children’s facial expressions largely reflect the degree of pain,which has led to the developing of a number of pain scoring tools that will help improve the quality of pain mana-gement in children if they are continually studied in depth.The artificial inte-lligence(AI)technology represented by machine learning has reached an unprecedented level in image processing of deep facial models through deep convolutional neural networks,which can effectively identify and systematically analyze various subtle features of children’s facial expressions.Based on the construction of a large database of images of facial expressions in children with perioperative pain,this study proposes to develop and apply automatic facial pain expression recognition software using AI technology.The study aims to improve the postoperative pain management for pediatric population and the short-term and long-term quality of life for pediatric patients after operational event.

Fortifying Smart Grids: A Holistic Assessment Strategy against Cyber Attacks and Physical Threats for Intelligent Electronic Devices

Intelligent electronic devices(IEDs)are interconnected via communication networks and play pivotal roles in transmitting grid-related operational data and executing control instructions.In the context of the heightened security challenges within smart grids,IEDs pose significant risks due to inherent hardware and software vulner-abilities,as well as the openness and vulnerability of communication protocols.Smart grid security,distinct from traditional internet security,mainly relies on monitoring network security events at the platform layer,lacking an effective assessment mechanism for IEDs.Hence,we incorporate considerations for both cyber-attacks and physical faults,presenting security assessment indicators and methods specifically tailored for IEDs.Initially,we outline the security monitoring technology for IEDs,considering the necessary data sources for their security assessment.Subsequently,we classify IEDs and establish a comprehensive security monitoring index system,incorporating factors such as running states,network traffic,and abnormal behaviors.This index system contains 18 indicators in 3 categories.Additionally,we elucidate quantitative methods for various indicators and propose a hybrid security assessment method known as GRCW-hybrid,combining grey relational analysis(GRA),analytic hierarchy process(AHP),and entropy weight method(EWM).According to the proposed assessment method,the security risk level of IEDs can be graded into 6 levels,namely 0,1,2,3,4,and 5.The higher the level,the greater the security risk.Finally,we assess and simulate 15 scenarios in 3 categories,which are based on monitoring indicators and real-world situations encountered by IEDs.The results show that calculated security risk level based on the proposed assessment method are consistent with actual simulation.Thus,the reasonableness and effectiveness of the proposed index system and assessment method are validated.

Life cycle assessment as a prospective tool for sustainable agriculture and food planning at a local level

Owing to the far-reaching environmental consequences of agriculture and food systems,such as their contribution to climate change,there is an urgent need to reduce their impact.International and national governments set sustainability targets and implement corresponding measures.Nevertheless,critics of the globalized system claim that a territorial administrative scale is better suited to address sustainability issues.Yet,at the subnational level,local authorities rarely apply a systemic environmental assessment to enhance their action plans.This paper employs a territorial life cycle assessment methodology to improve local environmental agri-food planning.The objective is to identify significant direct and indirect environmental hotspots,their origins,and formulate effective mitigation strategies.The methodology is applied to the administrative department of Finistere,a strategic agricultural region in North-Western France.Multiple environmental criteria including climate change,fossil resource scarcity,toxicity,and land use are modeled.The findings reveal that the primary environmental hotspots of the studied local food system arise from indirect sources,such as livestock feed or diesel consumption.Livestock reduction and organic farming conversion emerge as the most environmentally efficient strategies,resulting in a 25%decrease in the climate change indicator.However,the overall modeled impact reduction is insufficient following national objectives and remains limited for the land use indicator.These results highlight the innovative application of life cycle assessment led at a local level,offering insights for the further advancement of systematic and prospective local agri-food assessment.Additionally,they provide guidance for local authorities to enhance the sustainability of planning strategies.

Evaluating reservoir suitability for large-scale hydrogen storage:A preliminary assessment considering reservoir properties

With rising demand for clean energy,global focus turns to finding ideal sites for large-scale underground hydrogen storage(UHS)in depleted petroleum reservoirs.A thorough preliminary reservoir evaluation before hydrogen(H_(2))injection is crucial for UHS success and safety.Recent criteria for UHS often emphasize economics and chemistry,neglecting key reservoir attributes.This study introduces a comprehensive framework for the reservoir-scale preliminary assessment,specifically tailored for long-term H_(2) storage within depleted gas reservoirs.The evaluation criteria encompass critical components,including reservoir geometry,petrophysical properties,tectonics,and formation fluids.To illustrate the practical application of this approach,we assess the Barnett shale play reservoir parameters.The assessment unfolds through three key stages:(1)A systematic evaluation of the reservoir's properties against our comprehensive screening criteria determines its suitability for H_(2) storage.(2)Using both homogeneous and multilayered gas reservoir models,we explore the feasibility and efficiency of H_(2) storage.This phase involves an in-depth examination of reservoir behavior during the injection stage.(3)To enhance understanding of UHS performance,sensitivity analyses investigate the impact of varying reservoir dimensions and injection/production pressures.The findings reveal the following:(a)Despite potential challenges associated with reservoir compaction and aquifer support,the reservoir exhibits substantial promise as an H_(2) storage site.(b)Notably,a pronounced increase in reservoir pressure manifests during the injection stage,particularly in homogeneous reservoirs.(c)Furthermore,optimizing injection-extraction cycle efficiency can be achieved by augmenting reservoir dimensions while maintaining a consistent thickness.To ensure a smooth transition to implementation,further comprehensive investigations are advised,including experimental and numerical studies to address injectivity concerns and explore storage site development.This evaluation framework is a valuable tool for assessing the potential of depleted gas reservoirs for large-scale hydrogen storage,advancing global eco-friendly energy systems.