An Analysis of Supply Chain Environment in Great Wall Motor Based on Life-Cycle Assessment

Great Wall Motor(GWM),a leading automotive manufacturer,places a strong emphasis on environmental sustainability and social responsibility.The company focuses on comprehensively evaluating and enhancing its supply chain to align with these objectives.This evaluation spans the entire product life cycle,encompassing design,manufacturing,packaging,distribution,usage,and recycling and disposal processes.Key areas of focus include optimizing raw material selection,improving product recyclability,reducing energy consumption and waste emissions,and minimizing carbon emissions during transportation.Through these endeavors,GWM not only enhances its environmental performance by reducing carbon emissions and resource consumption but also bolsters its brand image and competitiveness in the market.GWM’s dedication to environmental innovation and technological leadership serves as a driving force behind sustainable development and social responsibility within the industry.

Comparative Life-cycle Assessment of Sheet Molding Compound Reinforced by Natural Fiber vs. Glass Fiber

We present comparative life-cycle assessments of three fiber-reinforced sheet molding compounds （SMCs） using kenaf fiber, glass fiber and soy protein resin. Sheet molding compounds for automotive applications are typically made of unsaturated polyester and glass fibers. Replacing these with kenaf fiber or soy protein offers potential environmental benefits. A soy-based resin, maleated acrylated epoxidized soy oil （MAESO）, was synthesized from refined soybean oil. Kenaf fiber and polyester resins were used to make SMC 1 composites, while SMC2 composites were made from kenaf fiber and a resin blend of 20% MASEO and 80% unsaturated polyester. Both exhibited good physical and mechanical properties, though neither was as strong as glass fiber reinforced polyester SMC. The functional unit was defined as mass to achieve equal stiffness and stability for the manufacture of interior parts for automobiles. The life-cycle assessments were done on SMCI, SMC2 and glass fiber reinforced SMC. The material and energy balances from producing one functional unit of three composites were collected from lab experiments and the literature. Key environmental measures were computed using SimaPro software. Kenaf fiber-reinforced SMC composites （SMC1 and SMC2） performed better than glass fiber-reinforced SMC in every environmental category. The global warming potentials of kenaf fiber-reinforced SMC （SMCI） and kenaf soy resin-based SMC （SMC2） were 45% and 58%, respectively, of glass fiber-reinforced SMC. Thus, we have demonstrated significant ecological benefit from replacing glass fiber reinforced SMC with soy-based resin and natural fiber.

Life-cycle Assessment of Carbon Dioxide Capture for Enhanced Oil Recovery

The development and deployment of Carbon dioxide Capture and Storage （CCS） technology is a cornerstone of the Norwegian government＇s climate strategy. A number of projects are currently evaluated/planned along the Norwegian West Coast, one at Tjeldbergodden. COe from this project will be utilized in part for enhanced oil recovery in the Halten oil field, in the Norwegian Sea. We study a potential design of such a system. A combined cycle power plant with a gross power output of 832 MW is combined with CO2 capture plant based on a post-combustion capture using amines as a solvent. The captured CO2 is used for enhanced oil recovery （EOR）. We employ a hybrid life-cycle assessment （LCA） method to assess the environmental impacts of the system. The study focuses on the modifications and operations of the platform during EOR. We allocate the impacts connected to the capture of CO2 to electricity production, and the impacts connected to the transport and storage of CO2 to the oil produced. Our study shows a substantial reduction of the greenhouse gas emissions from power production by 80% to 75 g·（kW·h）^-1. It also indicates a reduction of the emissions associated with oil production per unit oil produced, mostly due to the increased oil production. Reductions are especially significant if the additional power demand due to EOR leads to power supply from the land.

The Markovian Approach for Probabilistic Life-Cycle Assessment of Existing Structures

The reliability of structural systems, lying in aggressive environments, changes over time. Proper maintenance is usually required to achieve a suitable performance level of life-cycle. The damage process affecting the systems often suffers from uncertainty due to the randomness involved in each environmental attack. Therefore, basing on suitable damage modeling as well as on probabilistic analysis, the main features of time-variant deterioration process are modeled and then the life-cycle is assessed. On the basis of Markov renewal theory (MRT), this paper proposes a combined approach using an appropriate time dependent damage model and probabilistic analysis. Since repairing deteriorated structures requires the arrangement of maintenance strategies, possible selective maintenance scenarios have to be considered. Referring to the relationship between MRT and an appropriate condition index, some repair strategies have been proposed and compared with each other. Those strategies are applied just to seriously deteriorated members. Furthermore selective maintenance benefits are economically investigated.

Application of Life-Cycle Assessment for the Study of Carbon and Water Footprints of the 16.5 MWe Wind Farm in Villonaco, Loja, Ecuador

Wind technology is considered to be among the most promising types of renewable energy sources, and due to high oil prices and growing concerns about climate change and energy security, it has been the subject of extensive considerations in recent years, including questions related to the relative sustainability of electricity production when the manufacturing, assembly, transportation and dismantling processes of these facilities are taken into account. The present article evaluates the environmental impacts, carbon emissions and water consumption, derived from the production of electric energy of the Villonaco wind farm, located in Loja, Ecuador, during its entire life cycle, using the Life Cycle Analysis for this purpose. Finally, it is concluded that wind energy has greater environmental advantages since it has lower values of carbon and water footprints than other energy sources. Additionally, with the techniques Cumulative Energy Demand and Energy Return on Investment, sustainability in the production of electricity from wind power in Ecuador is demonstrated;and, that due to issues of vulnerability to climate change, the diversification of its energy mix is essential considering the inclusion of non-conventional renewable sources such as solar or wind, this being the only way to reduce both the carbon footprint and the water from the energy supply.

LIFE-CYCLE ASSESSMENT AND LIFE-CYCLE COST AS COLLABORATIVE TOOLS IN RESIDENTIAL HEATING SYSTEM SELECTION

Typically the selection of a residential heating system focuses on first costs rather than the economic or environmental life cycle consequences.The use of life cycle assessment and life cycle cost methodologies in the design phase provide additional criteria for consideration when selecting a residential heating system.A comparative case study of a gas forced air and radiant solar heating system was conducted for a 3,000 square foot house located in Fort Collins,Colorado,U.S.A.The initial results of an analysis of the life cycle assessment and the life cycle cost data indicated the gas forced air system was superior,both environmentally and economically.Further data analysis pinpointed solar radiant system components for replacement in an effort to reduce both life cycle environmental emissions and costs.This analysis resulted in a hybrid radiant system using a high-efficiency gas-fired boiler,a choice that lowered both the solar radiant system’s costs and emissions.This new system had slightly lower environmental impacts than both the gas forced air system and solar radiant system.Unfortunately the hybrid system had less impact on the life cycle cost with the hybrid system substantially more expensive then the gas-forced air alternative.

Life-cycle assessment and techno-economic analysis of the production of wood vinegar from Eucommia stem: a case study

This research undertook a case study of the life-cycle assessment and techno-economic analysis of the slow pyrolysis of Eucommia stem for the production of wood vinegar and activated carbon.The results showed that the production of one ton of wood vinegar via the slow pyrolysis of Eucommia stem show comparatively low global warming potential(2.37×10^(2) kg CO_(2) eq),primary energy demand(3.16×10^(3) MJ),acidification potential(2.19 kg SO2 eq),antimony depletion potential(3.86×10^(–4) kg antimony eq),and ozone depletion potential(7.46×10^(–6) kg CFC-11 eq)and was more environmentally friendly than the production of dilute acetic acid(12 wt%)via petrochemical routes.Meanwhile,the total capital investment,total product cost,and cash flowsheet were provided in the techno-economic analysis.Then,the net present value,internal rate of return,and dynamic payback period of the production process were evaluated.The findings indicated that while this production process is cost-effective,it might not be economically attractive or could generate investment risks.An increase in the added value of the wood vinegar and the activated carbon could remarkably improve the economic feasibility of this production process.

Life-cycle assessment of two sewage sludge-to-energy systems based on different sewage sludge characteristics:Energy balance and greenhouse gas-emission footprint analysis

Anaerobic digestion and incineration are widely used sewage sludge(SS)treatment and disposal approaches to recovering energy from SS,but it is difficult to select a suitable technical process from the various technologies.In this study,life-cycle assessments were adopted to compare the energy-and greenhouse gas-(GHG)emission footprints of two sludge-to-energy systems.One system uses a combination of AD with incineration(the AI system),whereas the other was simplified by direct incineration(the DI system).Comparison between three SS feedstocks(VS/TS:57.61-73.1 ds.%)revealed that the AI system consistently outperformed the DI system.The results of sensitivity analyses showed that the energy and GHG emission performances were mainly affected by VS content of the SS,AD conversion efficiency,and the energy consumption of sludge drying.Furthermore,the energy and GHG emission credit of the two systems increased remarkably with the increase in the VS content of the SS.For the high-organic-content sludge(VS/TS:55%–80%),the energy and GHG emission credit of the AI system increase with the increase of AD conversion efficiency.However,for the low organic content sludge(VS/TS:30%–55%),it has the opposite effect.In terms of energy efficiency and GHG performance,the AI system is a good choice for the treatment of high-organic-content sludge(VS/TS>55%),but DI shows superiority over AI when dealing with low organic content sludge(VS/TS<55%).

Degradation process assessment of prestressed concrete continuous bridges in life-cycle

To accurately evaluate the degradation process of prestressed concrete continuous bridges exposed to aggressive environments in life-cycle,a finite element-based approach with respect to the lifetime performance assessment of concrete bridges was proposed.The existing assessment methods were firstly introduced and compared.Some essential mechanics problems involved in the degradation process,such as the deterioration of materials properties,the reduction of sectional areas and the variation of overall structural performance caused by the first two problems,were investigated and solved.A computer program named CBDAS(Concrete Bridge Durability Analysis System) was written to perform the above-metioned approach.Finally,the degradation process of a prestressed concrete continuous bridge under chloride penetration was discussed.The results show that the concrete normal stress for serviceability limit state exceeds the threshold value after 60 a,but the various performance indicators at ultimate limit state are consistently in the allowable level during service life.Therefore,in the case of prestressed concrete bridges,the serviceability limit state is more possible to have durability problems in life-cycle;however,the performance indicators at ultimate limit state can satisfy the requirements.

Environmental life-cycle assessment of waste-coal pellets production

Industrial decarbonization is crucial to keeping the global mean temperature<1.5°C above pre-industrial levels.Although unabated coal use needs to be phased out,coal is still expected to remain an important source of energy in power and energy-intensive industries until the 2030s.Decades of coal exploration,mining and processing have resulted in~30 billion tonnes of waste-coal tailings being stored in coal impoundments,posing environmental risks.This study presents an environmental life-cycle assessment of a coal-processing technology to produce coal pellets from the waste coal stored in impoundments.It has been shown that the waste-coal pellets would result in the cradle-to-gate global warming of 1.68-3.50 kgCO_(2,eq)/G_(Jch),depending on the source of electricity used to drive the process.In contrast,the corresponding figure for the supply of conventional coal in the US was estimated to be 12.76 kgCO_(2,eq)/G_(Jch).Such a reduction in the global-warming impact confirms that waste-coal pellets can be a viable source of energy that will reduce the environmental impact of the power and energy-intensive industries in the short term.A considered case study showed that complete substitution of conventional coal with the waste-coal pellets in a steelmaking plant would reduce the greenhouse-gas emissions from 2649.80 to 2439.50 kgCO_(2,eq)/t_(steel).This,in turn,would reduce the life-cycle greenhouse-gas emissions of wind-turbine manufacturing by≤8.6%.Overall,this study reveals that the use of waste-coal pellets can bring a meaningful reduction in industrial greenhouse-gas emissions,even before these processes are fully decarbonized.

Preventing the Immense Increase in the Life-Cycle Energy and Carbon Footprints of LLM-Powered Intelligent Chatbots

Intelligent chatbots powered by large language models(LLMs)have recently been sweeping the world,with potential for a wide variety of industrial applications.Global frontier technology companies are feverishly participating in LLM-powered chatbot design and development,providing several alternatives beyond the famous ChatGPT.However,training,fine-tuning,and updating such intelligent chatbots consume substantial amounts of electricity,resulting in significant carbon emissions.The research and development of all intelligent LLMs and software,hardware manufacturing(e.g.,graphics processing units and supercomputers),related data/operations management,and material recycling supporting chatbot services are associated with carbon emissions to varying extents.Attention should therefore be paid to the entire life-cycle energy and carbon footprints of LLM-powered intelligent chatbots in both the present and future in order to mitigate their climate change impact.In this work,we clarify and highlight the energy consumption and carbon emission implications of eight main phases throughout the life cycle of the development of such intelligent chatbots.Based on a life-cycle and interaction analysis of these phases,we propose a system-level solution with three strategic pathways to optimize the management of this industry and mitigate the related footprints.While anticipating the enormous potential of this advanced technology and its products,we make an appeal for a rethinking of the mitigation pathways and strategies of the life-cycle energy usage and carbon emissions of the LLM-powered intelligent chatbot industry and a reshaping of their energy and environmental implications at this early stage of development.

Life-Cycle Impact Assessment of Air Emissions from a Cement Production Plant in Cambodia

Cement industrial emissions account for 32% of air pollution in Cambodia. With that in mind, we examined the environmental impact of Cambodia’s cement industry and identified ways that it could reduce air pollution. The study focused on raw material extraction and preparation, calcination, and cement preparation. Data for the life-cycle inventory were provided by the Kampot Cement Plant. Air emissions were assessed using EMEP/EEA and IPCC criteria, and the impact assessment used ReCiPe (2016). The baseline analysis revealed that calcination contributed the most air pollutants, so mitigation scenarios focused on alternative fuels only during the calcination stage of cement production: 1) 100% coal (S1);2) 93% coal and 7% biomass (S2);3) 85% coal and 15% biomass (S3);4) 70% coal and 30% biomass (S4);and 5) 50% coal and 50% biomass (S5). The results demonstrated that certain mitigation measures reduced major emissions and environmental damage. S5 had the best results, reducing CO2 by 49.97, NOx by 2.233, and SO2 by 49.333%;however, it increased PM2.5 by 19.60% and total heavy metal (Pb, Cd, Hg, As, Cr, Cu, Ni, Se, Zn) output by 28.113%. The results of the study showed reductions in serious health and environmental effects associated with climate change of 48.83%, ozone generation of 9.62%, and particulate matter formation of 28.80%. However, carcinogenic and non-carcinogenic human toxicity increased by 35.66%. Therefore, such mitigation effect would be benefit to carbon reduction target in Cambodia.

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.

Risk assessment of oil and gas investment environment in countries along the Belt and Road Initiative

With the implementation of the Belt and Road Initiative, China is deepening its cooperation in oil and gas resources with countries along the Initiative. In order to better mitigate risks and enhance the safety of investments, it is of significant importance to research the oil and gas investment environment in these countries for China's overseas investment macro-layout. This paper proposes an indicator system including 27 indicators from 6 dimensions. On this basis, game theory models combined with global entropy method and analytic hierarchy process are applied to determine the combined weights, and the TOPSIS-GRA model is utilized to assess the risks of oil and gas investment in 76 countries along the Initiative from 2014 to 2021. Finally, the GM(1,1) model is employed to predict risk values for 2022-2025. In conclusion, oil and gas resources and political factors have the greatest impact on investment environment risk, and 12 countries with greater investment potential are selected through cluster analysis in conjunction with the predicted results. The research findings may provide scientific decisionmaking recommendations for the Chinese government and oil enterprises to strengthen oil and gas investment cooperation with countries along the Belt and Road Initiative.

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.

Effect of a comprehensive geriatric assessment nursing intervention model on older patients with diabetes and hypertension

BACKGROUND The Comprehensive Geriatric Assessment(CGA)was introduced late in China and is primarily used for investigating and evaluating health problems in older adults in outpatient and community settings.However,there are few reports on its application in hospitalized patients,especially older patients with diabetes and hypertension.AIM To explore the nursing effect of CGA in hospitalized older patients with diabetes and hypertension.METHODS We performed a retrospective single-center analysis of patients with comorbid diabetes mellitus and hypertension who were hospitalized and treated in the Jiangyin Hospital of Traditional Chinese Medicine between September 2020 and June 2022.Among the 80 patients included,40 received CGA nursing interventions(study group),while the remaining 40 received routine nursing care(control group).The study group's comprehensive approach included creating personalized CGA profiles,multidisciplinary assessments,and targeted inter-ventions in areas,such as nutrition,medication adherence,exercise,and mental health.However,the control group received standard nursing care,including general and medical history collection,fall prevention measures,and regular patient monitoring.After 6 months of nursing care implementation,we evaluated the effectiveness of the interventions,including assessments of blood glucose levels fasting blood glucose,2-h postprandial blood glucose,and glycated hemoglobin,type A1c(HbA1c);blood pressure indicators such as diastolic blood pressure(DBP)and systolic blood pressure(SBP);quality of life as measured by the 36-item Short Form Survey(SF-36)questionnaire;and treatment adherence.RESULTS After 6 months,the nursing outcomes indicated that patients who underwent CGA nursing interventions experienced a significant decrease in blood glucose indicators,such as fasting blood glucose,2-h postprandial blood glucose,and HbA1c,as well as blood pressure indicators,including DBP and SBP,compared with the control group(P<0.05).Quality of life assessments,including physical health,emotion,physical function,overall health,and mental health,showed marked improvements compared to the control group(P<0.05).In the study group,38 patients adhered to the clinical treatment requirements,whereas only 32 in the control group adhered to the clinical treatment requirements.The probability of treatment adherence among patients receiving CGA nursing interventions was higher than that among patients receiving standard care(95%vs 80%,P<0.05).CONCLUSION The CGA nursing intervention significantly improved glycemic control,blood pressure management,and quality of life in hospitalized older patients with diabetes and hypertension,compared to routine care.

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.

Health risk assessment of trace metal(loid)s in agricultural soils based on Monte Carlo simulation coupled with positive matrix factorization model in Chongqing, southwest China

This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.

Study on the impact of comprehensive geriatric assessment on anxiety and depression in chronic obstructive pulmonary disease patients

BACKGROUND Psychological factors such as anxiety and depression will not only aggravate the symptoms of chronic obstructive pulmonary disease(COPD)patients and reduce the quality of life of patients,but also affect the treatment effect and long-term prognosis.Therefore,it is of great significance to explore the clinical application of senile comprehensive assessment in the treatment of COPD and its influence on psychological factors such as anxiety and depression.AIM To explore the clinical application of comprehensive geriatric assessment in COPD care and its impact on anxiety and depression in elderly patents.METHODS In this retrospective study,60 patients with COPD who were hospitalized in our hospital from 2019 to 2020 were randomly divided into two groups with 30 patients in each group.The control group was given routine nursing,and the observation group was given comprehensive assessment.Clinical symptoms,quality of life[COPD assessment test(CAT)score],anxiety and depression Hamilton Anxiety Rating Scale(HAMA)and Hamilton Depression Rating Scale(HAMD)were compared between the two groups.RESULTS CAT scores in the observation group decreased from an average of 24.5 points at admission to an average of 18.3 points at discharge,and in the control group from an average of 24.7 points at admission to an average of 18.3 points at discharge.The average score was 22.1(P<0.05).In the observation group,HAMA scores decreased from 14.2 points at admission to 8.6 points at discharge,and HAMD scores decreased from 13.8 points at admission to 7.4 points at discharge.The mean HAMD scores in the control group decreased from an average of 14.5 at admission to an average of 12.3 at discharge,and from an average of 14.1 at admission to an average of 11.8 at discharge.CONCLUSION The application of comprehensive geriatric assessment in COPD care has a significant effect on improving patients'clinical symptoms and quality of life,and can effectively reduce patients'anxiety and depression.

Importance of risk assessment,endoscopic hemostasis,and recent advancements in the management of acute non-variceal upper gastrointestinal bleeding

Acute non-variceal upper gastrointestinal bleeding(ANVUGIB)is a common medical emergency in clinical practice.While the incidence has significantly reduced,the mortality rates have not undergone a similar reduction in the last few decades,thus presenting a significant challenge.This editorial outlines the key causes and risk factors of ANVUGIB and explores the current standards and recent updates in risk assessment scoring systems for predicting mortality and endoscopic treatments for achieving hemostasis.Since ANUVGIB predominantly affects the elderly population,the impact of comorbidities may be responsible for the poor outcomes.A thorough drug history is important due to the increasing use of antiplatelet agents and anticoagulants in the elderly.Early risk stratification plays a crucial role in deciding the line of management and predicting mortality.Emerging scoring systems such as the ABC(age,blood tests,co-morbidities)score show promise in predicting mortality and guiding clinical decisions.While conventional endoscopic therapies remain cornerstone approaches,novel techniques like hemostatic powders and over-the-scope clips offer promising alternatives,particularly in cases refractory to traditional modalities.By integrating validated scoring systems and leveraging novel therapeutic modalities,clinicians can enhance patient care and mitigate the substantial morbidity and mortality associated with ANVUGIB.