Computing-in-memory(CIM)has been a promising candidate for artificial-intelligent applications thanks to the absence of data transfer between computation and storage blocks.Resistive random access memory(RRAM)based CI...Computing-in-memory(CIM)has been a promising candidate for artificial-intelligent applications thanks to the absence of data transfer between computation and storage blocks.Resistive random access memory(RRAM)based CIM has the advantage of high computing density,non-volatility as well as high energy efficiency.However,previous CIM research has predominantly focused on realizing high energy efficiency and high area efficiency for inference,while little attention has been devoted to addressing the challenges of on-chip programming speed,power consumption,and accuracy.In this paper,a fabri-cated 28 nm 576K RRAM-based CIM macro featuring optimized on-chip programming schemes is proposed to address the issues mentioned above.Different strategies of mapping weights to RRAM arrays are compared,and a novel direct-current ADC design is designed for both programming and inference stages.Utilizing the optimized hybrid programming scheme,4.67×programming speed,0.15×power saving and 4.31×compact weight distribution are realized.Besides,this macro achieves a normalized area efficiency of 2.82 TOPS/mm2 and a normalized energy efficiency of 35.6 TOPS/W.展开更多
Objective:To investigate the impact of programmed harmonious nursing combined with hierarchical management on nursing quality and satisfaction in a health management center.Methods:A total of 100 patients who received...Objective:To investigate the impact of programmed harmonious nursing combined with hierarchical management on nursing quality and satisfaction in a health management center.Methods:A total of 100 patients who received care at this health management center from January 2024 to January 2025 were selected as subjects.Using a random number table method,they were divided into an observation group(n=50)and a control group(n=50).The control group followed traditional methods,while the observation group integrated programmed harmonious nursing with hierarchical management.Comparative analysis was conducted on nursing quality scores,adverse event occurrence rates,and patient satisfaction between the two groups.Results:The observation group showed significantly improved nursing quality scores(P<0.05)and markedly reduced incidence of adverse events(P<0.05),with statistically significant differences compared to pre-treatment conditions(P<0.05).Conclusion:The combination of hierarchical management and programmed harmonious nursing demonstrates effectiveness in enhancing medical service quality,reducing adverse reactions,and improving patient satisfaction—a method worthy of promotion.展开更多
The purpose of this study is to investigate the effectiveness of the“expiration manager”mini program in managing the validity of ward items.The program was used to manage frequently and infrequently used consumables...The purpose of this study is to investigate the effectiveness of the“expiration manager”mini program in managing the validity of ward items.The program was used to manage frequently and infrequently used consumables by setting up an automatic reminder function.The item failure rate and the time required for nurses to conduct counts over 6 months before and after implementation were compared,as well as evaluated system availability using the System Usability scale(SUS).Results showed that after implementing the mini program,both the item failure rate and non-recognition rate significantly decreased(P<0.05),while the inspection pass rate significantly increased(P<0.05),and the monthly inventory time was reduced(P<0.05).The SUS evaluation yielded a total score of 74.38±11.73,with learnability at 80.21±20.27 and availability at 72.92±11.18,all indicating good user acceptance.In conclusion,the“expiration manager”mini program can effectively improve the efficiency of item expiration management,reduce the risk of expiration,and save inspection time,thereby demonstrating high user acceptance and promising potential for wider adoption.展开更多
This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a dis...This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a distributed hydrological model with an interval two-stage stochastic programing （ITSP）. The distributed hydrological model was used for establishing a rainfall-runoff forecast system, while random parameters were pro- vided by the statistical analysis of simulation outcomes water resources management planning in Kaidu-Konqi The developed STIP model was applied to a real case of watershed, where three scenarios with different water re- sources management policies were analyzed. The results indicated that water shortage mainly occurred in agri- culture, ecology and forestry sectors. In comparison, the water demand from municipality, industry and stock- breeding sectors can be satisfied due to their lower consumptions and higher economic values. Different policies for ecological water allocation can result in varied system benefits, and can help to identify desired water allocation plans with a maximum economic benefit and a minimum risk of system disruption under uncertainty.展开更多
We used a goal programming technique to determine the optimal harvest volume for the Iranian Caspian forest. We collected data including volume, growth, wood price at forest roadside, and variable harvesting costs. Th...We used a goal programming technique to determine the optimal harvest volume for the Iranian Caspian forest. We collected data including volume, growth, wood price at forest roadside, and variable harvesting costs. The allometric method was used to quantify seques- trated carbon. Regression analysis was used to derive growth models. Expected mean price was estimated using wood price and variable harvesting costs. Questionnaire was used to determine the constraints and the equation coefficients of the goal programming model. The optimal volume was determined using the goal programming method according to multipurpose forest management. LINGO software was used for analysis. Results indicated that the optimum volumes of species were 250.25 m3.ha-1 for beech, 59 m3.ha-1 for hornbeam, 73 m3.ha-1 for oak, 41 m3.ha-1 for alder, and 32 m3.ha-1 for other species. The total optimum volume is 455.25 m3.ha-1.展开更多
Planning for water quality management is important for facilitating sustainable socio-economic development;however, the planning is also complicated by a variety of uncertainties and nonlinearities. In this study, an ...Planning for water quality management is important for facilitating sustainable socio-economic development;however, the planning is also complicated by a variety of uncertainties and nonlinearities. In this study, an interval-parameter fuzzy robust nonlinear programming (IFRNP) model was developed for water quality management to deal with such difficulties. The developed model incorporated interval nonlinear programming (INP) and fuzzy robust programming (FRP) methods within a general optimization framework. The developed IFRNP model not only could explicitly deal with uncertainties represented as discrete interval numbers and fuzzy membership functions, but also was able to deal with nonlinearities in the objective function.展开更多
The potential demand on financial risk management has being increased considerably by the reason of Basel 11 regulations and instabilities in economy. In recent years, financial institutions and companies have been st...The potential demand on financial risk management has being increased considerably by the reason of Basel 11 regulations and instabilities in economy. In recent years, financial institutions and companies have been struggled for building up intensive financial risk management tools due to Basel II guidance on establishing financial self-assessment systems. In this respect, decision support system has a significant role on effectuating intensive financial risk management roadmap. In this study, a reformative financial risk management system is presented with the combination of determining financial risks with their importance, calculating risk scores and making suggestions based on detected risk scores by applying corrective actions. First, financial risk factors and indicators of these risk variables are selected and weights of these variables are specified by using fuzzy goal programming. After that, total risk scores are calculated and amendatory financial activities are appeared by means of expertons method which also provides possibilities of the alternative decisions. To illustrate the performance of integrated and multistage decision support system, a survey is applied on the end users.展开更多
Fusarium head blight(FHB)is a worldwide devastating disease of small grain cereals and Fusarium graminearum species complex(FGSC)is the major pathogen causing the disease.The epidemics of FHB lead to the reduction of ...Fusarium head blight(FHB)is a worldwide devastating disease of small grain cereals and Fusarium graminearum species complex(FGSC)is the major pathogen causing the disease.The epidemics of FHB lead to the reduction of grain yield and economic losses.Additionally,mycotoxins produced by the FHB pathogens are hazardous to the health of human and livestock.In this review,we summarize the epidemiology of FHB,and introduce effects of this disease on economy,environment and food safety.We focus on the integrated management approaches for controlling FHB including agronomic practices,resistant cultivars,chemical control,and biocontrol.In addition,we also discuss the potential novel management strategies against FHB and mycotoxin.展开更多
Global Memory Net (GMNet) is intended to be an effective gateway to the world cultural, historical, and heritage image collections from selected academic educational and research partners in the world. Much of these u...Global Memory Net (GMNet) is intended to be an effective gateway to the world cultural, historical, and heritage image collections from selected academic educational and research partners in the world. Much of these unique collections of great value to education and research are not currently accessible due to distance, form, and technical barriers. This project is to find new ways to enable users to access and exploit these significant research collections via global network. As GMNet is ending its first 5-year phase in October 2005, it has contributed substantially to the community building in digital library development by ac- commodating numerous collaborators and technical staff from various parts of the world to spend 3 to 5 months as a full-member of the GMNet team in Boston. They have come from different parts of China—such as Sichuan, Hainan, Shanghai and Xi’an; Croatia; and Hanoi, Vietnam. In addition to contribute to the overall system development and enhancement of system function- alities, they have brought valuable sample image collections of their own institutions/countries, and actually developed prototype collections as a part of GMNet. This paper describes the exciting and productive experience of the first of this visiting research group in developing the GMNet’s Version 2.0 PHP-based system under Prof. Chen’s overall supervision. It also describes both the system’s technical level structure—user/Web-based application/data, and complex functionalities with multi-collection, multi-lingual, multi-modal searching capabilities; system management capabilities; as well as provisions for user uploads and retrieval for our own projects. This Version 2.0 system is built on the Linux/Apache/PHP/MySQL platform. What is described in this paper is an actual case which has formed a base for further new development by others in the research group. It demonstrates fully the value of the synergistic collaboration among global partners for universal digital library development. More information can be found in http://www.memorynet.org/.展开更多
Objective:The enhanced recovery after surgery(ERAS)program is less implemented in gastric cancer patients.The purpose of this survey is to investigate the implementation status of ERAS in perioperative period in gastr...Objective:The enhanced recovery after surgery(ERAS)program is less implemented in gastric cancer patients.The purpose of this survey is to investigate the implementation status of ERAS in perioperative period in gastric cancer.Methods:This clinical observational study enrolled 329 patients between January 2020 and August 2020 in a single gastric cancer center.The questionnaire consisted of 4 par ts:basic information,preoperative status,intraoperative status,and postoperative status of ERAS implementation in gastric cancer surgery.Results:In the preoperative period,patients'education and counseling(100%)were well adopted.Smoking cessation(34.6%),drinking cessation(36.9%),avoidance of preoperative mechanical bowel preparation(24.3%),respiratory function training(11.2%),and administration of carbohydrate-rich drink before surgery(0.6%)were relatively not well adopted.During the operation,maintenance of intraoperative normothermia and fluid management(100%),as well as epidural analgesia(81.5%),were well adopted.Thromboprophylaxis was performed in 133(40.4%)patients.In the postoperative period,early active mobilization was implemented about 9.5 h,and early ambulation was implemented about 39.5 h,after surgery.A total of 140(42.5%)patients received prolonged prophylactic antibiotics;268(81.5%)patients were provided diet upon gas passage;and 320(97.3%)patients received intravenous fluid administration more than 5 d after surgery.The practice rate of early removal of urinary catheter(0%)and nasogastric tube(15.5%)was relatively low.A total of 11(3.3%)patients experienced postoperative complication,and 1(0.3%)patient received unplanned reoperation.The average costs were￥59,500,and the average hospital stay was 12(5,36)d.Conclusions:Standard perioperative management of ERAS program in gastric cancer surgery in China still requires improvement.展开更多
The growing integration of nondispatchable renewable energy sources(PV,wind)and the need to cut CO_(2) emissions make energy management crucial.Microgrids provide a framework for RES integration but face challenges fr...The growing integration of nondispatchable renewable energy sources(PV,wind)and the need to cut CO_(2) emissions make energy management crucial.Microgrids provide a framework for RES integration but face challenges from intermittency,fluctuating loads,cost optimization,and uncertainty in real-time balancing.Accurate short-term forecasting of solar generation and demand is vital for reliable and sustainable operation.While stochastic and machine learning methods are used,they struggle with limited data,complex temporal patterns,and scalability.Key challenges include capturing seasonal to weekly variations and modeling sudden fluctuations in generation and consumption.To address these issues,this paper presents a novel three-stage centralized EMS for interconnected microgrids.The first stage involves comprehensive data analysis to extract meaningful patterns.The second stage introduces a hybrid forecasting framework that integrates stochastic(Prophet)with machine learning(BiLSTM)techniques to improve prediction accuracy under uncertainty.In the third stage,a modified linear programming approach leverages the improved short-term forecasts to optimize energy sharing between microgrids,with the aim of reducing operational costs,minimizing carbon emissions,and improving system stability under climate variability.The proposed EMS is designed to accommodate diverse microgrid configurations while maintaining computational efficiency.Four scenarios are considered to evaluate the proposed energy management strategy.The obtained results demonstrate that the proposed EMS significantly improves both forecasting accuracy and operational performance.The combined methods achieve the best performance among all tested models,with an RMSE of 0.0070,MAE of 0.0043,and R^(2) of 0.9988,corresponding to improvements of ΔRMSE=−0.2122 and ΔR^(2)=+0.7126 relative to Prophet.These substantial gains in predictive accuracy translate into more precise battery scheduling,reduced grid dependency,and optimized power dispatching,thereby significantly enhancing system efficiency,reliability,and sustainability.Overall,the results highlight the effectiveness of integrating hybrid forecasting with optimization-based EMS,providing a viable pathway toward high penetration of renewable energy sources in future power systems.展开更多
AIM: To assess the effectiveness of the Chronic Disease Self-Management Program(CDSMP) on glycated hemoglobin A1c(HbA1c) and selected self-reported measures.METHODS: We compared patients who received a diabetes self-c...AIM: To assess the effectiveness of the Chronic Disease Self-Management Program(CDSMP) on glycated hemoglobin A1c(HbA1c) and selected self-reported measures.METHODS: We compared patients who received a diabetes self-care behavioral intervention, the CDSMP developed at the Stanford University, with controls whoreceived usual care on their HbA1c and selected self-reported measures, including diabetes self-care activities, health-related quality of life(HRQOL), pain and fatigue. The subjects were a subset of participants enrolled in a randomized controlled trial that took place at seven regional clinics of a university-affiliated integrated healthcare system of a multi-specialty group practice between January 2009 and June 2011. The primary outcome was change in HbA1c from randomization to 12 mo. Data were analyzed using multilevel statistical models and linear mixed models to provide unbiased estimates of intervention effects.RESULTS: Demographic and baseline clinical characteristics were generally comparable between the two groups. The average baseline HbA1c values in the CDSMP and control groups were 9.4% and 9.2%, respectively. Significant reductions in HbA1c were seen at 12 mo for the two groups, with adjusted changes around 0.6%(P < 0.0001), but the reductions did not differ significantly between the two groups(P = 0.885). Few significant differences were observed in participants' diabetes self-care activities. No significant differences were observed in the participants' HRQOL, pain, or fatigue measures.CONCLUSION: The CDSMP intervention may not lower HbA1c any better than good routine care in an integrated healthcare system. More research is needed to understand the benefits of self-management programs in primary care in different settings and populations.展开更多
Learning-based methods have become mainstream for solving residential energy scheduling problems. In order to improve the learning efficiency of existing methods and increase the utilization of renewable energy, we pr...Learning-based methods have become mainstream for solving residential energy scheduling problems. In order to improve the learning efficiency of existing methods and increase the utilization of renewable energy, we propose the Dyna actiondependent heuristic dynamic programming(Dyna-ADHDP)method, which incorporates the ideas of learning and planning from the Dyna framework in action-dependent heuristic dynamic programming. This method defines a continuous action space for precise control of an energy storage system and allows online optimization of algorithm performance during the real-time operation of the residential energy model. Meanwhile, the target network is introduced during the training process to make the training smoother and more efficient. We conducted experimental comparisons with the benchmark method using simulated and real data to verify its applicability and performance. The results confirm the method's excellent performance and generalization capabilities, as well as its excellence in increasing renewable energy utilization and extending equipment life.展开更多
We examined the local community incentive programs to improve traditional forest management in three forested villages in Baneh city, Kurdistan province in the northern Zagros forests of western Iran. Zagros forests c...We examined the local community incentive programs to improve traditional forest management in three forested villages in Baneh city, Kurdistan province in the northern Zagros forests of western Iran. Zagros forests cover 6.07 million ha and support rich plant and animal diversity. Changes in local community social and economic sys-tems and the inefficiency of traditional forest management led to a criti-cal situation in the stability of forest regeneration in recent decades. Due to a shortage of productive and arable lands and resulting unemployment and poverty, people overexploited the Zagros forests. Outside interven-tion in traditional forest management creates conflicts between local peoples and forest management organizations. To achieve sustainable forest management, including forest resources conservation and im-provement of natural resource based livelihoods of communities, it is desirable to implement Forestry Incentive Programs （FIP） based on the important functions of forests. Detailed information on the so-cio-economics of communities, the effect of forests on local livelihoods, and lists of products extracted from the forest were obtained from a sur-vey of local communities though questionnaire, interview and observa-tion. We studied 276 households in three villages and completed 76 ques-tionnaires by householders in the quantitative analysis. Sampling was performed by simple random sampling （SRS）. The needs of rural com-munities, such as livestock husbandry, mainly arise from the characteris-tics and environmental features of villages. We identified the driving forces, pressures, status, impacts and responses （DPSIR） to design incen-tive programs, by DPSIR analysis and interaction analysis. Evaluation of local community benefits from forests showed that in order to improve forest management, 319 dollars per year would be needed by each family as an incentive in 2010 to prevent lopping and firewood collecting, the main causes of forest degradation.展开更多
BACKGROUND Gestational diabetes mellitus(GDM)has emerged as a global public health cha-llenge,fueled by increasing maternal age,rising obesity rates,and lifestyle shifts.It is linked to substantial short-and long-term...BACKGROUND Gestational diabetes mellitus(GDM)has emerged as a global public health cha-llenge,fueled by increasing maternal age,rising obesity rates,and lifestyle shifts.It is linked to substantial short-and long-term health risks for both mothers and their offspring,offering a critical opportunity for intergenerational prevention of metabolic disorders.AIM To synthesize current evidence on the pathophysiology,diagnosis,management,complications,and individualized treatment strategies of GDM.METHODS We conducted a narrative review in accordance with PRISMA guidelines.Pub-Med,Scopus,Web of Science,and EMBASE were searched for English-language articles(2017-2025)using terms such as“GDM”,“pregnancy”,“insulin resis-tance”,and“maternal outcomes”.After removing duplicates,512 records were screened;102 full texts were assessed for eligibility,and 55 studies were included based on methodological quality,clinical relevance,and alignment with the review objectives.RESULTS GDM results from a complex interplay among progressive insulin resistance,β-cell dysfunction,immune dysregulation,and placental inflammation.Emerging evidence indicates that hyperglycemia before formal diagnosis can impair fetal programming via epigenetic mechanisms.GDM increases a mother’s risk of developing type 2 diabetes mellitus seven-to tenfold and raises the incidence of cardiovascular disease,preeclampsia,and cesarean delivery.Offspring are at higher risk of macrosomia,neonatal hypoglycemia,and future metabolic and cardiovascular disorders.Lifestyle modification remains the cornerstone of therapy and,when necessary,can be supplemented with pharmacologic agents such as metformin or insulin.Postpartum follow-up,breastfeeding support,and preconception counseling are vital to long-term metabolic health.CONCLUSION GDM requires precision-based,life-course care.Future priorities include early risk detection,biomarker validation,unified diagnosis,and culturally sensitive interventions to improve maternal-child outcomes.展开更多
Due to the recent trend of software intelligence in the Fourth Industrial Revolution,deep learning has become a mainstream workload for modern computer systems.Since the data size of deep learning increasingly grows,m...Due to the recent trend of software intelligence in the Fourth Industrial Revolution,deep learning has become a mainstream workload for modern computer systems.Since the data size of deep learning increasingly grows,managing the limited memory capacity efficiently for deep learning workloads becomes important.In this paper,we analyze memory accesses in deep learning workloads and find out some unique characteristics differentiated from traditional workloads.First,when comparing instruction and data accesses,data access accounts for 96%–99%of total memory accesses in deep learning workloads,which is quite different from traditional workloads.Second,when comparing read and write accesses,write access dominates,accounting for 64%–80%of total memory accesses.Third,although write access makes up the majority of memory accesses,it shows a low access bias of 0.3 in the Zipf parameter.Fourth,in predicting re-access,recency is important in read access,but frequency provides more accurate information in write access.Based on these observations,we introduce a Non-Volatile Random Access Memory(NVRAM)-accelerated memory architecture for deep learning workloads,and present a new memory management policy for this architecture.By considering the memory access characteristics of deep learning workloads,the proposed policy improves memory performance by 64.3%on average compared to the CLOCK policy.展开更多
Background: EPI is one of the most cost-effective public health interventions that have already been identified. Mass vaccination is one of the most effective public health strategies that lead to a dramatic reduction...Background: EPI is one of the most cost-effective public health interventions that have already been identified. Mass vaccination is one of the most effective public health strategies that lead to a dramatic reduction in the incidence of many infectious diseases. This is a descriptive study (eco-logical exploratory) where data about the status of routine immunization of children under 6 years in 6 selected countries in terms of the routine immunization programs in each country, the coverage and reported cases of vaccine-preventable diseases from 2006 to 2008 were collected assuming that each country is a representative of a Continent;data about the status of Iran were also collected and a comparative study was performed in the next step. It is worth mentioning that selecting these countries was according to health experts to consolidate the data. Collection tools are data of international (WHO and UNICEF) and national organizations of the above countries. In all countries surveyed, triple vaccine, vaccines of polio, hepatitis B, measles, rubella and mumps are part of the routine immunization program for children under the age of 6 years, with the explanation that in South Africa only measles vaccine is injected instead of measles, rubella and mumps vaccines. The coverage rate of the vaccine and other vaccines in Iran was the best compared to other countries. This represents the widespread activity of health care systems of the country in the field of vaccination and tireless efforts of healthcare workers and health centers.展开更多
In order to train nurses to perform disease management and telenursing, we developed an e-learning education program, and assessed the efficacy. A single-group pre-test and post-test design was used. Nurses who worked...In order to train nurses to perform disease management and telenursing, we developed an e-learning education program, and assessed the efficacy. A single-group pre-test and post-test design was used. Nurses who worked at a medical institution or a disease management company were included, and the duration of the program was set 2 months. We developed the program so that it could grow attitude and improve knowledge and skills in disease management and patient education. Of 55 subjects, 48 who completed the program were analyzed. After the program, subjects increased knowledge and interests in disease management and patient education. Almost of the subjects answered that e-learning was a good learning method. Our program was effective at enhancing subject’s interests in disease management and patient education, and considered to improve their skills in the future.展开更多
基金supported in part by the National Natural Science Foundation of China (62422405, 62025111,62495100, 92464302)the STI 2030-Major Projects(2021ZD0201200)+1 种基金the Shanghai Municipal Science and Technology Major Projectthe Beijing Advanced Innovation Center for Integrated Circuits
文摘Computing-in-memory(CIM)has been a promising candidate for artificial-intelligent applications thanks to the absence of data transfer between computation and storage blocks.Resistive random access memory(RRAM)based CIM has the advantage of high computing density,non-volatility as well as high energy efficiency.However,previous CIM research has predominantly focused on realizing high energy efficiency and high area efficiency for inference,while little attention has been devoted to addressing the challenges of on-chip programming speed,power consumption,and accuracy.In this paper,a fabri-cated 28 nm 576K RRAM-based CIM macro featuring optimized on-chip programming schemes is proposed to address the issues mentioned above.Different strategies of mapping weights to RRAM arrays are compared,and a novel direct-current ADC design is designed for both programming and inference stages.Utilizing the optimized hybrid programming scheme,4.67×programming speed,0.15×power saving and 4.31×compact weight distribution are realized.Besides,this macro achieves a normalized area efficiency of 2.82 TOPS/mm2 and a normalized energy efficiency of 35.6 TOPS/W.
文摘Objective:To investigate the impact of programmed harmonious nursing combined with hierarchical management on nursing quality and satisfaction in a health management center.Methods:A total of 100 patients who received care at this health management center from January 2024 to January 2025 were selected as subjects.Using a random number table method,they were divided into an observation group(n=50)and a control group(n=50).The control group followed traditional methods,while the observation group integrated programmed harmonious nursing with hierarchical management.Comparative analysis was conducted on nursing quality scores,adverse event occurrence rates,and patient satisfaction between the two groups.Results:The observation group showed significantly improved nursing quality scores(P<0.05)and markedly reduced incidence of adverse events(P<0.05),with statistically significant differences compared to pre-treatment conditions(P<0.05).Conclusion:The combination of hierarchical management and programmed harmonious nursing demonstrates effectiveness in enhancing medical service quality,reducing adverse reactions,and improving patient satisfaction—a method worthy of promotion.
基金The First Affiliated Hospital of Shaoyang University,China(Project No.:23FY1015)。
文摘The purpose of this study is to investigate the effectiveness of the“expiration manager”mini program in managing the validity of ward items.The program was used to manage frequently and infrequently used consumables by setting up an automatic reminder function.The item failure rate and the time required for nurses to conduct counts over 6 months before and after implementation were compared,as well as evaluated system availability using the System Usability scale(SUS).Results showed that after implementing the mini program,both the item failure rate and non-recognition rate significantly decreased(P<0.05),while the inspection pass rate significantly increased(P<0.05),and the monthly inventory time was reduced(P<0.05).The SUS evaluation yielded a total score of 74.38±11.73,with learnability at 80.21±20.27 and availability at 72.92±11.18,all indicating good user acceptance.In conclusion,the“expiration manager”mini program can effectively improve the efficiency of item expiration management,reduce the risk of expiration,and save inspection time,thereby demonstrating high user acceptance and promising potential for wider adoption.
基金supported by the National Basic Research Program of China(2010CB951002)the Dr.Western-funded Project of Chinese Academy of Science(XBBS201010 and XBBS201005)+1 种基金the National Natural Sciences Foundation of China (51190095)the Open Research Fund Program of State Key Laboratory of Hydro-science and Engineering(sklhse-2012-A03)
文摘This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a distributed hydrological model with an interval two-stage stochastic programing （ITSP）. The distributed hydrological model was used for establishing a rainfall-runoff forecast system, while random parameters were pro- vided by the statistical analysis of simulation outcomes water resources management planning in Kaidu-Konqi The developed STIP model was applied to a real case of watershed, where three scenarios with different water re- sources management policies were analyzed. The results indicated that water shortage mainly occurred in agri- culture, ecology and forestry sectors. In comparison, the water demand from municipality, industry and stock- breeding sectors can be satisfied due to their lower consumptions and higher economic values. Different policies for ecological water allocation can result in varied system benefits, and can help to identify desired water allocation plans with a maximum economic benefit and a minimum risk of system disruption under uncertainty.
文摘We used a goal programming technique to determine the optimal harvest volume for the Iranian Caspian forest. We collected data including volume, growth, wood price at forest roadside, and variable harvesting costs. The allometric method was used to quantify seques- trated carbon. Regression analysis was used to derive growth models. Expected mean price was estimated using wood price and variable harvesting costs. Questionnaire was used to determine the constraints and the equation coefficients of the goal programming model. The optimal volume was determined using the goal programming method according to multipurpose forest management. LINGO software was used for analysis. Results indicated that the optimum volumes of species were 250.25 m3.ha-1 for beech, 59 m3.ha-1 for hornbeam, 73 m3.ha-1 for oak, 41 m3.ha-1 for alder, and 32 m3.ha-1 for other species. The total optimum volume is 455.25 m3.ha-1.
基金supported in part by National Natural Science Foundation of China(61533017,61273140,61304079,61374105,61379099,61233001)Fundamental Research Funds for the Central Universities(FRF-TP-15-056A3)the Open Research Project from SKLMCCS(20150104)
文摘Planning for water quality management is important for facilitating sustainable socio-economic development;however, the planning is also complicated by a variety of uncertainties and nonlinearities. In this study, an interval-parameter fuzzy robust nonlinear programming (IFRNP) model was developed for water quality management to deal with such difficulties. The developed model incorporated interval nonlinear programming (INP) and fuzzy robust programming (FRP) methods within a general optimization framework. The developed IFRNP model not only could explicitly deal with uncertainties represented as discrete interval numbers and fuzzy membership functions, but also was able to deal with nonlinearities in the objective function.
文摘The potential demand on financial risk management has being increased considerably by the reason of Basel 11 regulations and instabilities in economy. In recent years, financial institutions and companies have been struggled for building up intensive financial risk management tools due to Basel II guidance on establishing financial self-assessment systems. In this respect, decision support system has a significant role on effectuating intensive financial risk management roadmap. In this study, a reformative financial risk management system is presented with the combination of determining financial risks with their importance, calculating risk scores and making suggestions based on detected risk scores by applying corrective actions. First, financial risk factors and indicators of these risk variables are selected and weights of these variables are specified by using fuzzy goal programming. After that, total risk scores are calculated and amendatory financial activities are appeared by means of expertons method which also provides possibilities of the alternative decisions. To illustrate the performance of integrated and multistage decision support system, a survey is applied on the end users.
基金the Science and Technology Project of Zhejiang Province,China(2018C02G2011110)the National Natural Science Foundation of China(31930088 and 32001855)the earmarked fund for China Agriculture Research System(CARS-3-1-29).
文摘Fusarium head blight(FHB)is a worldwide devastating disease of small grain cereals and Fusarium graminearum species complex(FGSC)is the major pathogen causing the disease.The epidemics of FHB lead to the reduction of grain yield and economic losses.Additionally,mycotoxins produced by the FHB pathogens are hazardous to the health of human and livestock.In this review,we summarize the epidemiology of FHB,and introduce effects of this disease on economy,environment and food safety.We focus on the integrated management approaches for controlling FHB including agronomic practices,resistant cultivars,chemical control,and biocontrol.In addition,we also discuss the potential novel management strategies against FHB and mycotoxin.
基金supported by the US National Science Foundation/International Digital Library Program(Grant No.NSF/CISE/IIS-9905833).
文摘Global Memory Net (GMNet) is intended to be an effective gateway to the world cultural, historical, and heritage image collections from selected academic educational and research partners in the world. Much of these unique collections of great value to education and research are not currently accessible due to distance, form, and technical barriers. This project is to find new ways to enable users to access and exploit these significant research collections via global network. As GMNet is ending its first 5-year phase in October 2005, it has contributed substantially to the community building in digital library development by ac- commodating numerous collaborators and technical staff from various parts of the world to spend 3 to 5 months as a full-member of the GMNet team in Boston. They have come from different parts of China—such as Sichuan, Hainan, Shanghai and Xi’an; Croatia; and Hanoi, Vietnam. In addition to contribute to the overall system development and enhancement of system function- alities, they have brought valuable sample image collections of their own institutions/countries, and actually developed prototype collections as a part of GMNet. This paper describes the exciting and productive experience of the first of this visiting research group in developing the GMNet’s Version 2.0 PHP-based system under Prof. Chen’s overall supervision. It also describes both the system’s technical level structure—user/Web-based application/data, and complex functionalities with multi-collection, multi-lingual, multi-modal searching capabilities; system management capabilities; as well as provisions for user uploads and retrieval for our own projects. This Version 2.0 system is built on the Linux/Apache/PHP/MySQL platform. What is described in this paper is an actual case which has formed a base for further new development by others in the research group. It demonstrates fully the value of the synergistic collaboration among global partners for universal digital library development. More information can be found in http://www.memorynet.org/.
基金supported by Program of Shanghai Shenkang Hospital Development Center (SHDC22020204)Nursing Science Support Program of Zhongshan Hospital,Fudan University (XK-082-007)Management Fund of Zhongshan Hospital,Fudan University (2022ZSGL01)。
文摘Objective:The enhanced recovery after surgery(ERAS)program is less implemented in gastric cancer patients.The purpose of this survey is to investigate the implementation status of ERAS in perioperative period in gastric cancer.Methods:This clinical observational study enrolled 329 patients between January 2020 and August 2020 in a single gastric cancer center.The questionnaire consisted of 4 par ts:basic information,preoperative status,intraoperative status,and postoperative status of ERAS implementation in gastric cancer surgery.Results:In the preoperative period,patients'education and counseling(100%)were well adopted.Smoking cessation(34.6%),drinking cessation(36.9%),avoidance of preoperative mechanical bowel preparation(24.3%),respiratory function training(11.2%),and administration of carbohydrate-rich drink before surgery(0.6%)were relatively not well adopted.During the operation,maintenance of intraoperative normothermia and fluid management(100%),as well as epidural analgesia(81.5%),were well adopted.Thromboprophylaxis was performed in 133(40.4%)patients.In the postoperative period,early active mobilization was implemented about 9.5 h,and early ambulation was implemented about 39.5 h,after surgery.A total of 140(42.5%)patients received prolonged prophylactic antibiotics;268(81.5%)patients were provided diet upon gas passage;and 320(97.3%)patients received intravenous fluid administration more than 5 d after surgery.The practice rate of early removal of urinary catheter(0%)and nasogastric tube(15.5%)was relatively low.A total of 11(3.3%)patients experienced postoperative complication,and 1(0.3%)patient received unplanned reoperation.The average costs were￥59,500,and the average hospital stay was 12(5,36)d.Conclusions:Standard perioperative management of ERAS program in gastric cancer surgery in China still requires improvement.
基金Prince Sattambin AbdulazizUniversity for funding their research work through the project number PSAU/2024/01/31821.
文摘The growing integration of nondispatchable renewable energy sources(PV,wind)and the need to cut CO_(2) emissions make energy management crucial.Microgrids provide a framework for RES integration but face challenges from intermittency,fluctuating loads,cost optimization,and uncertainty in real-time balancing.Accurate short-term forecasting of solar generation and demand is vital for reliable and sustainable operation.While stochastic and machine learning methods are used,they struggle with limited data,complex temporal patterns,and scalability.Key challenges include capturing seasonal to weekly variations and modeling sudden fluctuations in generation and consumption.To address these issues,this paper presents a novel three-stage centralized EMS for interconnected microgrids.The first stage involves comprehensive data analysis to extract meaningful patterns.The second stage introduces a hybrid forecasting framework that integrates stochastic(Prophet)with machine learning(BiLSTM)techniques to improve prediction accuracy under uncertainty.In the third stage,a modified linear programming approach leverages the improved short-term forecasts to optimize energy sharing between microgrids,with the aim of reducing operational costs,minimizing carbon emissions,and improving system stability under climate variability.The proposed EMS is designed to accommodate diverse microgrid configurations while maintaining computational efficiency.Four scenarios are considered to evaluate the proposed energy management strategy.The obtained results demonstrate that the proposed EMS significantly improves both forecasting accuracy and operational performance.The combined methods achieve the best performance among all tested models,with an RMSE of 0.0070,MAE of 0.0043,and R^(2) of 0.9988,corresponding to improvements of ΔRMSE=−0.2122 and ΔR^(2)=+0.7126 relative to Prophet.These substantial gains in predictive accuracy translate into more precise battery scheduling,reduced grid dependency,and optimized power dispatching,thereby significantly enhancing system efficiency,reliability,and sustainability.Overall,the results highlight the effectiveness of integrating hybrid forecasting with optimization-based EMS,providing a viable pathway toward high penetration of renewable energy sources in future power systems.
基金Supported by The National Institutes of Health’s National Institute on Minority Health and Health Disparities,No.#1P20MD002295
文摘AIM: To assess the effectiveness of the Chronic Disease Self-Management Program(CDSMP) on glycated hemoglobin A1c(HbA1c) and selected self-reported measures.METHODS: We compared patients who received a diabetes self-care behavioral intervention, the CDSMP developed at the Stanford University, with controls whoreceived usual care on their HbA1c and selected self-reported measures, including diabetes self-care activities, health-related quality of life(HRQOL), pain and fatigue. The subjects were a subset of participants enrolled in a randomized controlled trial that took place at seven regional clinics of a university-affiliated integrated healthcare system of a multi-specialty group practice between January 2009 and June 2011. The primary outcome was change in HbA1c from randomization to 12 mo. Data were analyzed using multilevel statistical models and linear mixed models to provide unbiased estimates of intervention effects.RESULTS: Demographic and baseline clinical characteristics were generally comparable between the two groups. The average baseline HbA1c values in the CDSMP and control groups were 9.4% and 9.2%, respectively. Significant reductions in HbA1c were seen at 12 mo for the two groups, with adjusted changes around 0.6%(P < 0.0001), but the reductions did not differ significantly between the two groups(P = 0.885). Few significant differences were observed in participants' diabetes self-care activities. No significant differences were observed in the participants' HRQOL, pain, or fatigue measures.CONCLUSION: The CDSMP intervention may not lower HbA1c any better than good routine care in an integrated healthcare system. More research is needed to understand the benefits of self-management programs in primary care in different settings and populations.
基金supported in part by the National Key Research and Development Program of China(2024YFB4709100,2021YFE0206100)the National Natural Science Foundation of China(62073321)+1 种基金the National Defense Basic Scientific Research Program(JCKY2019203C029)the Science and Technology Development Fund,Macao SAR,China(0015/2020/AMJ)
文摘Learning-based methods have become mainstream for solving residential energy scheduling problems. In order to improve the learning efficiency of existing methods and increase the utilization of renewable energy, we propose the Dyna actiondependent heuristic dynamic programming(Dyna-ADHDP)method, which incorporates the ideas of learning and planning from the Dyna framework in action-dependent heuristic dynamic programming. This method defines a continuous action space for precise control of an energy storage system and allows online optimization of algorithm performance during the real-time operation of the residential energy model. Meanwhile, the target network is introduced during the training process to make the training smoother and more efficient. We conducted experimental comparisons with the benchmark method using simulated and real data to verify its applicability and performance. The results confirm the method's excellent performance and generalization capabilities, as well as its excellence in increasing renewable energy utilization and extending equipment life.
文摘We examined the local community incentive programs to improve traditional forest management in three forested villages in Baneh city, Kurdistan province in the northern Zagros forests of western Iran. Zagros forests cover 6.07 million ha and support rich plant and animal diversity. Changes in local community social and economic sys-tems and the inefficiency of traditional forest management led to a criti-cal situation in the stability of forest regeneration in recent decades. Due to a shortage of productive and arable lands and resulting unemployment and poverty, people overexploited the Zagros forests. Outside interven-tion in traditional forest management creates conflicts between local peoples and forest management organizations. To achieve sustainable forest management, including forest resources conservation and im-provement of natural resource based livelihoods of communities, it is desirable to implement Forestry Incentive Programs （FIP） based on the important functions of forests. Detailed information on the so-cio-economics of communities, the effect of forests on local livelihoods, and lists of products extracted from the forest were obtained from a sur-vey of local communities though questionnaire, interview and observa-tion. We studied 276 households in three villages and completed 76 ques-tionnaires by householders in the quantitative analysis. Sampling was performed by simple random sampling （SRS）. The needs of rural com-munities, such as livestock husbandry, mainly arise from the characteris-tics and environmental features of villages. We identified the driving forces, pressures, status, impacts and responses （DPSIR） to design incen-tive programs, by DPSIR analysis and interaction analysis. Evaluation of local community benefits from forests showed that in order to improve forest management, 319 dollars per year would be needed by each family as an incentive in 2010 to prevent lopping and firewood collecting, the main causes of forest degradation.
文摘BACKGROUND Gestational diabetes mellitus(GDM)has emerged as a global public health cha-llenge,fueled by increasing maternal age,rising obesity rates,and lifestyle shifts.It is linked to substantial short-and long-term health risks for both mothers and their offspring,offering a critical opportunity for intergenerational prevention of metabolic disorders.AIM To synthesize current evidence on the pathophysiology,diagnosis,management,complications,and individualized treatment strategies of GDM.METHODS We conducted a narrative review in accordance with PRISMA guidelines.Pub-Med,Scopus,Web of Science,and EMBASE were searched for English-language articles(2017-2025)using terms such as“GDM”,“pregnancy”,“insulin resis-tance”,and“maternal outcomes”.After removing duplicates,512 records were screened;102 full texts were assessed for eligibility,and 55 studies were included based on methodological quality,clinical relevance,and alignment with the review objectives.RESULTS GDM results from a complex interplay among progressive insulin resistance,β-cell dysfunction,immune dysregulation,and placental inflammation.Emerging evidence indicates that hyperglycemia before formal diagnosis can impair fetal programming via epigenetic mechanisms.GDM increases a mother’s risk of developing type 2 diabetes mellitus seven-to tenfold and raises the incidence of cardiovascular disease,preeclampsia,and cesarean delivery.Offspring are at higher risk of macrosomia,neonatal hypoglycemia,and future metabolic and cardiovascular disorders.Lifestyle modification remains the cornerstone of therapy and,when necessary,can be supplemented with pharmacologic agents such as metformin or insulin.Postpartum follow-up,breastfeeding support,and preconception counseling are vital to long-term metabolic health.CONCLUSION GDM requires precision-based,life-course care.Future priorities include early risk detection,biomarker validation,unified diagnosis,and culturally sensitive interventions to improve maternal-child outcomes.
基金supported in part by the NRF(National Research Foundation of Korea)Grant(No.2019R1A2C1009275)by the Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by theKorean government(MSIT)(No.2021-0-02068,Artificial Intelligence Innovation Hub).
文摘Due to the recent trend of software intelligence in the Fourth Industrial Revolution,deep learning has become a mainstream workload for modern computer systems.Since the data size of deep learning increasingly grows,managing the limited memory capacity efficiently for deep learning workloads becomes important.In this paper,we analyze memory accesses in deep learning workloads and find out some unique characteristics differentiated from traditional workloads.First,when comparing instruction and data accesses,data access accounts for 96%–99%of total memory accesses in deep learning workloads,which is quite different from traditional workloads.Second,when comparing read and write accesses,write access dominates,accounting for 64%–80%of total memory accesses.Third,although write access makes up the majority of memory accesses,it shows a low access bias of 0.3 in the Zipf parameter.Fourth,in predicting re-access,recency is important in read access,but frequency provides more accurate information in write access.Based on these observations,we introduce a Non-Volatile Random Access Memory(NVRAM)-accelerated memory architecture for deep learning workloads,and present a new memory management policy for this architecture.By considering the memory access characteristics of deep learning workloads,the proposed policy improves memory performance by 64.3%on average compared to the CLOCK policy.
文摘Background: EPI is one of the most cost-effective public health interventions that have already been identified. Mass vaccination is one of the most effective public health strategies that lead to a dramatic reduction in the incidence of many infectious diseases. This is a descriptive study (eco-logical exploratory) where data about the status of routine immunization of children under 6 years in 6 selected countries in terms of the routine immunization programs in each country, the coverage and reported cases of vaccine-preventable diseases from 2006 to 2008 were collected assuming that each country is a representative of a Continent;data about the status of Iran were also collected and a comparative study was performed in the next step. It is worth mentioning that selecting these countries was according to health experts to consolidate the data. Collection tools are data of international (WHO and UNICEF) and national organizations of the above countries. In all countries surveyed, triple vaccine, vaccines of polio, hepatitis B, measles, rubella and mumps are part of the routine immunization program for children under the age of 6 years, with the explanation that in South Africa only measles vaccine is injected instead of measles, rubella and mumps vaccines. The coverage rate of the vaccine and other vaccines in Iran was the best compared to other countries. This represents the widespread activity of health care systems of the country in the field of vaccination and tireless efforts of healthcare workers and health centers.
文摘In order to train nurses to perform disease management and telenursing, we developed an e-learning education program, and assessed the efficacy. A single-group pre-test and post-test design was used. Nurses who worked at a medical institution or a disease management company were included, and the duration of the program was set 2 months. We developed the program so that it could grow attitude and improve knowledge and skills in disease management and patient education. Of 55 subjects, 48 who completed the program were analyzed. After the program, subjects increased knowledge and interests in disease management and patient education. Almost of the subjects answered that e-learning was a good learning method. Our program was effective at enhancing subject’s interests in disease management and patient education, and considered to improve their skills in the future.
