Developing a risk assessment tool for cancer-related venous thrombosis in China: a modified Delphi-analytic hierarchy process study.

OBJECTIVE: To develop a Risk Assessment Tool for Cancer-related Venous Thrombosis in China. METHODS: A modified two-round Delphi method was employed to establish consensus within a field to reach an agreement via a questionnaire or by interviewing a multidisciplinary panel of experts by collecting their feedback to inform the next round, exchanging their knowledge, experience, and opinions anonymously, and resolving uncertainties. Furthermore, The AHP (Analytic Hierarchy Process) was used to determine the final quality indicators' relative importance. RESULTS: The expert's positive coefficient was 85.19% in the first round and 82.61% in the second round, with authoritative coefficients of 0.89 and 0.92 in the respective surveys. The P-value of Kendall's W test was all less than 0.001 for each round, and the W-value for concordance at the end of the two rounds was 0.115. The final Risk Assessment Tool for Cancer-related Venous Thrombosis consisted of three domains, ten subdomains, and 39 indicators, with patient factors weighing 0.1976, disease factors weighing 0.4905, and therapeutic factors weighing 0.3119. CONCLUSION: The tool is significantly valid and reliable with a strong authority and coordination degree, and it can be used to assess the risk of cancer-related VTE and initiate appropriate thrombophylactic interventions in China.

Adaptable leadership for arid/semi-arid wetlands conservation under climate change: Using Analytical Hierarchy Process (AHP) approach.

Adverse socio-economic and environmental impacts of climate change on wetlands have enforced the international community and many nations to develop adaptive policies for wetland management, which require effective leadership to influence relevant stakeholders. This study identifies and prioritizes leadership functions and theories for climate change adaptation (CCA) in wetlands ecosystems, particularly in arid and semi-arid regions. A mixed qualitative-quantitative research methodology was applied through focus groups and a survey with a sample of national, sub-national, and local experts on wetlands management and climate change in Iran. The Analytic Hierarchy Processing (AHP) technique identified the political-administrative (weight = 0.245), adaptive (W = 0.244), and enabling (W = 0.237) functions for CCA, respectively, as three prioritized leadership functions, followed by the dissemination function (W = 0.102), which emphasizes the necessity of applying and enhancing leaders' social capacities, knowledge, communication skills, and personal networks to facilitate social learning and actions regarding CCA in local communities and among relevant organizations. It is necessary to overcome structural and functional barriers for leaders and their followers to information access and involvement in participatory decision-making platforms. Moreover, network and communication leadership theories (W = 0.368) and sustainable leadership perspectives (W = 0.362), respectively, have the highest priority among leadership theories and are crucial for establishing participatory decision-making among relevant stakeholders and applying adaptive strategies for wetlands governance under climate change conditions. The reconceptualization of leadership as a complex adaptive notion draws attention to the social complexities and emerging characteristics of leadership in contemporary societies and organizations. The understanding of leaders' and followers' networks and identifying the core role of leaders provides a foundation for developing leadership functions and theories beyond hierarchical, individualistic, and one-way concepts of leadership.

Analyzing the effectiveness of environmental impact assessment in Paraná, Brazil and California, United States with fuzzy-set qualitative comparative analysis and the analytical hierarchy process.

Environmental impact assessment (EIA) has become one of the most widespread environmental management instruments. Despite this, EIA is routinely criticized for being ineffective at impacting decision-making. This study compared the EIA systems of Paraná, Brazil and California, United States using the effectiveness dimensions from the EIA literature. This study formats the cases into contextual conditions using the fuzzy-set qualitative comparative analysis (fsQCA) to identify the necessary or sufficient conditions that cause effective outcomes. These effectiveness outcomes are then ranked by EIA stakeholders via the analytical hierarchy process (AHP) to identify stakeholder priorities and to improve stakeholder management. The results show that in Paraná stakeholders identified normative effectiveness as the most important dimension, while stakeholders in California identified this dimension as the second-most important following substantive effectiveness. Public participation was found to be a necessary condition for both substantive and normative effectiveness to occur. Early project definition was found to be sufficient for substantive effectiveness and necessary for normative effectiveness, for which stakeholder coordination was a sufficient condition. This suggests that in order for EIA to influence decision-making and foster sustainable development, greater care needs to be taken to actively engage stakeholders in public participation, with clear roles and project design communicated early on, and a clear role for regulatory authority to promote stakeholder coordination for acceptable outcomes. These findings suggest that some effectiveness dimensions are caused by similar conditions, which could help focus stakeholder management efforts and point to new avenues for future EIA effectiveness research.

IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater.

The sustainable management of groundwater resources in developing countries is often challenging due to limited measurement and monitoring infrastructure to collect data necessary for decision support. To make a contribution towards addressing these challenges, this study investigated the use of Internet of Things (IoT) technology and low-cost sensors to collect the required groundwater-level data and develop a model to map the recharge potential with stormwater. The study focused on two stormwater ponds located in a highly urbanised area in Cape Town, South Africa. A combination of Geographic Information System and analytic hierarchy process was integrated to generate a groundwater recharge potential zone map of the study area. The IoT-based data were used to develop and calibrate a numerical groundwater model in MODFLOW. The study determined that retrofitted stormwater ponds are potential groundwater augmentation zones and can provide opportunity for stormwater recharge in urban areas. Overall, this study highlights the potential of IoT to collect hydrogeological data with low-cost sensors. Data can be collected at high temporal resolution, and the spatial scale can be increased due to availability of low-cost sensors.

Investigation of port intervention to coastal and nearshore dynamics: a GIS and AHP approach.

The goal of the study was attempted to understand the impact of selected ports on the coastal and nearshore dynamics. Dwelling activities along the coastal zone were particularly high in the last two decades. Hence, ports constructed between 2000 and 2022 such as Mundra, Hazira, Karaikal, Krishnapatnam, Gangavaram, and Gopalpur were considered for the study. The land and shore dynamics were assessed prior and after their construction. The landward impact was identified by the changes in LULC, and the dynamics of coastal sediments were assessed from numerical model before and after the ports' construction. The highly impacted land and shore features were used in analytical hierarchy process (AHP) to assess the extent of their impact due to port construction. The extent of impacts was indicated as "criteria weight (CW)" expressed as percentage. Village-wise local sensitivity analysis (LSA) of the port environs due to port activities was also assessed with six parameters such as changes in LULC, cyclone, population, road network, cultural heritage site and shore stability based on their influence on the coast on case-by-case basis using AHP. The obtained influence of the impact of these parameters was used to determine the category of local sensitivity of the adjacent villages around the ports. For effective management planning, the LSA was classified into five classes, namely, very low, low, moderate, high, and very high. Villages categorized with different sensitivities can be attempted for suitable management plans and similar studies can be attempted for all villages impacted by port interventions.

Spatial assessment of flood vulnerability and waterlogging extent in agricultural lands using RS-GIS and AHP technique-a case study of Patan district Gujarat, India.

Assessing and mapping flood risks are fundamental tools that significantly contribute to the enhancement of flood management strategies. Identifying areas that are susceptible to floods and devising strategies to reduce the risk of waterlogging is of utmost importance. In the present study, an integrated approach, combining advanced remote sensing technologies, Geographic Information Systems (GIS), and analytic hierarchy process (AHP), was adopted in the Patan district of Gujarat, India, with a coastline spanning over 1600 km, to evaluate the numerous variables that contribute to the risk of flooding and waterlogging. After evaluating the flood conditioning factors and their respective weights using the analytic hierarchy process (AHP), the results were processed in GIS to accurately delineate areas that are prone to flooding. The results highlighted exceptional precision in identifying vulnerable areas, allowing for a thorough evaluation of the impact severity. The integrated approach yields valuable insights for multi-criteria assessments. The findings indicate that a significant portion of the district's land, precisely 8.94%, was susceptible to very high- risk of flooding, while 27.76% were classified as high-risk areas. Notably, 35.17% of the region was identified as having a moderate level of risk. Additionally, 20.96% and 7.15% were categorized as low-risk and very low-risk areas, respectively. Overall, the study highlights the need for proactive measures to mitigate the impact of floods on vulnerable communities. The research findings were verified by conducting ground truth and visual assessments using microwave satellite imagery (Sentinel-1). The aim of this validation was to test the accuracy of the study in identifying waterlogged agricultural areas and their extent based on AHP analysis. The ground verification and analysis of satellite images confirmed that the model accurately identified approximately 74% of the area categorized under high and very high flood vulnerability to be waterlogged and flooded. This research can provide valuable assistance to policymakers and authorities responsible for flood management by gathering necessary information about floods, including their intensity and the regions that are most susceptible to their impact. Additionally, it is crucial to implement corrective measures to improve soil drainage in vulnerable areas during heavy rainfall events. Prioritizing the adoption of sustainable agricultural practices and improving land use are also crucial for environmental conservation.

Modeling climate change adaptation for sustainable coastal zones using GIS and AHP.

The world is currently confronting one of its biggest environmental challenges: combating climate change. Coastal zones are one of the areas thought to be most sensitive to current and future climate change threats. The paper integrates Remote Sensing (RS), Geographic Information System (GIS) techniques, and Multi-Criteria Decision Analysis (MCDA) to detect vulnerable areas from climate change impacts in coastal zones in order to recommend adaptation systems in new coastal zones that can withstand various climatic changes. The proposed decision-making framework was developed in three phases: 1) climate data collection and processing; 2) Coastal Climate Impact Assessment (CCIA) model development; and 3) implementation and adaptation system selection. The climate data collection and processing phase involves determining the most significant climate change parameters and their indicators that affect coastal zone stability, extracting climatic data indicators from different climate database sources, and prioritizing the selected indicators. The indicators' weights were estimated using the Analytical Hierarchy Process (AHP) through a questionnaire survey shared with experts in climate change impacts. A CCIA model development phase involves the formulation of the proposed model using GIS technique to discover the vulnerable areas according to the most dominant impact. The implementation and adaptation system selection phase involves the application of the framework to Al-Alamein New City in Egypt. A sensitivity analysis was conducted to measure the behavior of several climate change parameters to identify the most critical parameter for climate change in Al-Alamein New City. The results showed that the geology of the region is the most crucial component influenced by climate change. It is capable of producing a very sensitive area in the coastal zone while also taking other factors into account. When creating new urban neighborhoods, the erosion of the shoreline is the least important factor to consider. This is because coastal deterioration is caused by both the influence of metrological data on the region and the impact of human activity. Shoreline deterioration will be reduced if climate conditions are maintained while limiting the impact of human activities. To adapt to the long-term effects of climate change on coastal zones, a combination of soft and hard protection systems should be considered.

[Application of Delphi method and analytic hierarchy process to construct the evaluation index system of healthy enterprises].

Objective: Explore the application of Delphi method and analytic hierarchy process to explore the construction of scientific, objective and comprehensive evaluation index system for healthy enterprise construction and promote the construction of healthy enterprises. Methods: In October 2022, through Delphi expert consultation and analytic hierarchy process, the indexes were screened and the weights of the indexes were determined, and the evaluation index system of healthy enterprises was established. Results: The positive coefficients of experts in the two rounds were all 100.00%, the authority coefficient of experts was 0.82, the coefficients of variation of the indexes in the two rounds were all less than 0.30. The coordination coefficients of experts in the first and second rounds were 0.64 and 0.77, respectively (P<0.001) . After two rounds of Delphi method expert consultation, a healthy enterprise evaluation index system including 4 first-level indexes, 14 second-level indexes, and 63 third-level indexes was constructed. Conclusion: The constructed health enterprise evaluation index system is highly scientific and reliable, covering the main factors of healthy enterprise construction, and providing a reliable and quantifiable basis and self-assessment basis for the establishment of healthy enterprises.

Integration of hydrogeological data, GIS and AHP techniques applied to delineate groundwater potential zones in sandstone, limestone and shales rocks of the Damoh district, (MP) central India.

The Damoh district, which is located in the central India and characterized by limestone, shales, and sandstone compact rock. The district has been facing groundwater development challenges and problems for several decades. To facilitate groundwater management, it is crucial to monitoring and planning based on geology, slope, relief, land use, geomorphology, and the types of the basaltic aquifer in the drought-groundwater deficit area. Moreover, the majority of farmers in the area are heavily dependent on groundwater for their crops. Therefore, delineation of groundwater potential zones (GPZ) is essential, which is defined based on various thematic layers, including geology, geomorphology, slope, aspect, drainage density, lineament density, topographic wetness index (TWI), topographic ruggedness index (TRI), and land use/land cover (LULC). The processing and analysis of this information were carried out using Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) methods. The validity of the results was trained and tested using Receiver Operating Characteristic (ROC) curves, which showed training and testing accuracies of 0.713 and 0.701, respectively. The GPZ map was classified into five classes such as very high, high, moderate, low, and very low. The study revealed that approximately 45% of the area falls under the moderate GPZ, while only 30% of the region is classified as having a high GPZ. The area receives high rainfall but has very high surface runoff due to no proper developed soil and lack of water conservation structures. Every summer season show a declined groundwater level. In this context, results of study area are useful to maintain the groundwater under climate change and summer season. The GPZ map plays an important role in implementing artificial recharge structures (ARS), such as percolation ponds, tube wells, bore wells, cement nala bunds (CNBs), continuous contour trenching (CCTs), and others for development of ground level. This study is significant for developing sustainable groundwater management policies in semi-arid regions, that are experiencing climate change. Proper groundwater potential mapping and watershed development policies can help mitigate the effects of drought, climate change, and water scarcity, while preserving the ecosystem in the Limestone, Shales, and Sandstone compact rock region. The results of this study are essential for farmers, regional planners, policy-makers, climate change experts, and local governments, enabling them to understand the groundwater development possibilities in the study area.

A study on the quality evaluation index system of smart home care for older adults in the community --based on Delphi and AHP.

BACKGROUND: In the context of the "silver wave" and "technology wave", smart home care for older adults in the community provide new ways for China and other countries to support ageing in place. Yet, only very few studies have focused on developing a quality index system of smart care. This study attempted to draw on the SERVQUAL model to establish a quality evaluation index system for smart senior care for older adults in the community. METHODS: On the basis of the service quality model, this paper has integrated qualitative and quantitative analyses using the Delphi and Analytic Hierarchy Process (AHP) methods to construct the index system of smart home care in the community and obtain the weights. These were based on literature research and field interviews in Guangzhou and Shenzhen pilot districts. RESULTS: A quality evaluation indexes system of smart home care for older adults in the community was developed, with 5 primary indices and 33 secondary indices. The weights of the 5 stair indices from high to low were smart emergency assistance 0.332, smart meal assistance 0.272, smart medical assistance 0.229, smart cleaning assistance 0.110 and smart amusement assistance 0.057. CONCLUSION: The results from the weight allocation revealed smart emergency assistance, smart meal assistance, and smart medical care assistance were the most important and crucial aspects of community-based smart home care. The study also suggested that "timeliness", "reliability", and "ease of use" should be given more attention. It is recommended to use this index system as a regulatory benchmark to guide the government bodies, senior care enterprises and communities to take measures to enhance the quality.

Determination and prioritization of factors affecting the occurrence of needle stick injuries among healthcare workers using techniques of Delphi and fuzzy analytical hierarchy process (FAHP).

INTRODUCTION: Needlestick injuries (NSIs) are a major hazard in the workplace for healthcare workers. To prevent these injuries, it is essential to determine the important factors affecting the occurrence of them. This study aimed to identify, classify and prioritize these factors using techniques of Delphi and fuzzy analytical hierarchy process (FAHP). METHODS: This descriptive-analytical study was conducted in 2022. Firstly, the factors affecting the occurrence of needlestick injuries were identified by the literature review. Moreover, the Delphi technique was used to identify the factors. 20 experts (physicians, nurses, and occupational health experts) participated in the steps of the Delphi method. Then, these factors were grouped into six groups. In the next step, the fuzzy analytical hierarchy process (FAHP) was applied to prioritize the factors. For this purpose, the pairwise comparison questionnaire was designed and filled out by 20 experts. Finally, data were analyzed using MATLAB software (version 2018a). RESULTS: 42 factors (31 factors extracted from the literature review and 11 factors obtained from the Delphi technique) were identified in this study. These factors were categorized into six groups. Based on the results, the relative weight of non-demographic personal factors, tool and technology factors, job factors, organizational factors, demographic personal factors, and environmental factors were computed by 0.200, 0.185, 0.184, 0.157, 0.142, and 0.133, respectively. CONCLUSION: These results determined the importance of the factors affecting the occurrence of needlestick injuries. These findings can be useful for planning preventive measures.

Continuity of health care: measurement and application in two rural counties of Guangxi Province, China.

BACKGROUND: Continuity of care (COC) is highly regarded in health promotion and health system strengthening. However, there is a lack of multidimensional quantitative assessment of continuity, making it challenging to evaluate and compare. Our objective was to create a novel measurement for COC and apply it in two rural counties in China to assess its validity and feasibility in evaluating health system reform. METHOD: This study conducted a scoping literature review on COC, examining existing frameworks and indicators. Following an online expert poll, a composite indicator was developed using the analytical hierarchy process (AHP). The measurement tool was then applied to assess the current state of COC in two rural counties in China. In addition to descriptive analysis, demographic and economic characteristics were analyzed for their association with COC scores using t-tests and multiple linear regression models. RESULTS: The final COC measurement encompasses three dimensions, six sub-dimensions, and ten individual indicators, which integrated and improved the current frameworks and indicators. Relational continuity, informational continuity, and management continuity were identified as the primary dimensions of COC measurement. The COC score is 0.49 in County A and 0.41 in County B, with information continuity being the highest-scoring dimension. Notably, the disparity in continuity scores is most pronounced among individuals with varying attitudes towards health, demonstrating a positive correlation. CONCLUSION: The construction of the composite indicator in this study offers a scientific and effective metric for comprehensively measuring continuity of care. The empirical data analysis conducted in Western China serves as an illustrative application of the indicator, demonstrating its efficiency. The results obtained from this analysis provide a solid foundation and valuable reference for strengthening the health system.

Developing online medical service quality indicators in China from the perspective of online and offline integration: a modified Delphi-analytic hierarchy process study.

Online medical services (OMSs) are developing rapidly worldwide, and policies encourage the integrated development of online and offline services in China. However, there is a lack of comprehensive and systematic quality indicators for OMSs to ensure patients' safety. This study aimed to construct a set of quality indicators from the perspective of online and offline integration to provide a basis for the evaluation and management of OMS quality. Based on the literature review, we included 53 potential indicators. In two rounds of consultations, we invited 21 and 19 experts, respectively, to rate the importance and feasibility of each indicator via email. We used the modified Delphi method and analytic hierarchy process to determine the final indicators and their weights. We used experts' positive coefficient, authority coefficient, and opinion coordination degree to test the reliability and validity of experts. After two rounds of Delphi consultation, the experts' positive coefficients were 90.48% and 89.47%, respectively, and the authoritative coefficients were both >0.7. An OMS quality index system for public hospitals in China was developed with 4 primary indicators, 13 secondary indicators, and 34 tertiary indicators. Among the primary indicators, the weights of structure, process, outcome, and integration quality were 0.22, 0.26, 0.34, and 0.18, respectively. We constructed the first set of OMS quality indicators for public hospitals in China from the perspective of online and offline integration. It could be applied as a standardized and meaningful guide for OMS evaluation and quality development.

Assessing the Role of AI-Based Smart Sensors in Smart Cities Using AHP and MOORA.

We know that in today's advanced world, artificial intelligence (AI) and machine learning (ML)-grounded methodologies are playing a very optimistic role in performing difficult and time-consuming activities very conveniently and quickly. However, for the training and testing of these procedures, the main factor is the availability of a huge amount of data, called big data. With the emerging techniques of the Internet of Everything (IoE) and the Internet of Things (IoT), it is very feasible to collect a large volume of data with the help of smart and intelligent sensors. Based on these smart sensing devices, very innovative and intelligent hardware components can be made for prediction and recognition purposes. A detailed discussion was carried out on the development and employment of various detectors for providing people with effective services, especially in the case of smart cities. With these devices, a very healthy and intelligent environment can be created for people to live in safely and happily. With the use of modern technologies in integration with smart sensors, it is possible to use energy resources very productively. Smart vehicles can be developed to sense any emergency, to avoid injuries and fatal accidents. These sensors can be very helpful in management and monitoring activities for the enhancement of productivity. Several significant aspects are obtained from the available literature, and significant articles are selected from the literature to properly examine the uses of sensor technology for the development of smart infrastructure. The analytical hierarchy process (AHP) is used to give these attributes weights. Finally, the weights are used with the multi-objective optimization on the basis of ratio analysis (MOORA) technique to provide the different options in their order of importance.

Real-Time Robotic Presentation Skill Scoring Using Multi-Model Analysis and Fuzzy Delphi-Analytic Hierarchy Process.

Existing methods for scoring student presentations predominantly rely on computer-based implementations and do not incorporate a robotic multi-classification model. This limitation can result in potential misclassification issues as these approaches lack active feature learning capabilities due to fixed camera positions. Moreover, these scoring methods often solely focus on facial expressions and neglect other crucial factors, such as eye contact, hand gestures and body movements, thereby leading to potential biases or inaccuracies in scoring. To address these limitations, this study introduces Robotics-based Presentation Skill Scoring (RPSS), which employs a multi-model analysis. RPSS captures and analyses four key presentation parameters in real time, namely facial expressions, eye contact, hand gestures and body movements, and applies the fuzzy Delphi method for criteria selection and the analytic hierarchy process for weighting, thereby enabling decision makers or managers to assign varying weights to each criterion based on its relative importance. RPSS identifies five academic facial expressions and evaluates eye contact to achieve a comprehensive assessment and enhance its scoring accuracy. Specific sub-models are employed for each presentation parameter, namely EfficientNet for facial emotions, DeepEC for eye contact and an integrated Kalman and heuristic approach for hand and body movements. The scores are determined based on predefined rules. RPSS is implemented on a robot, and the results highlight its practical applicability. Each sub-model is rigorously evaluated offline and compared against benchmarks for selection. Real-world evaluations are also conducted by incorporating a novel active learning approach to improve performance by leveraging the robot's mobility. In a comparative evaluation with human tutors, RPSS achieves a remarkable average agreement of 99%, showcasing its effectiveness in assessing students' presentation skills.

Socio-economic or environmental benefits from pondscapes? Deriving stakeholder preferences using analytic hierarchy process and compositional data analysis.

Ponds occupy a large share of standing water worldwide and play an important role in providing various ecosystem services. There are concerted efforts of the European Union either to create new ponds, or to restore and preserve existing ponds as nature-based solutions to provide benefits to ecosystem and human well-being. As part of the EU PONDERFUL project, selected pondscapes (i.e. landscapes of ponds) in eight different countries - hereafter "demo-sites", are studied to comprehensively understand their characteristics and their efficiency to provide ecosystem services. In addition, the needs and knowledge of stakeholders who own, work, research, or benefit from the pondscapes are also important, because of their capabilities to create, manage and develop the pondscapes. Therefore, we established connection with stakeholders to study their preferences and visions on the pondscapes. Using the analytic hierarchy process, this study shows that in general stakeholders in the European and Turkish demo-sites prefer environmental benefits to economic benefits, while stakeholders in the Uruguayan demo-sites rank the economic benefits higher. More specifically, in the European and Turkish demo-sites, the biodiversity benefits, i.e. life-cycle maintenance, habitat and gene pool protection, receive the highest ranking among all groups. On the other hand, stakeholders at the Uruguayan demo-sites rank provisioning benefits as the most important, because many ponds in Uruguayan demo-sites are being used for agricultural purposes. Understanding those preferences helps policy makers to address the needs of stakeholders more correctly, when considering any action or policy for the pondscapes.

Optimization of Ethanol Extraction Technology for Yujin Powder Using Response Surface Methodology with a Box-Behnken Design Based on Analytic Hierarchy Process-Criteria Importance through Intercriteria Correlation Weight Analysis and Its Safety Evaluation.

Here, we aimed to optimize the ethanol extraction technology for Yujin powder (YJP) and evaluate its safety. The ultrasonic-assisted ethanol reflux extraction method refluxing was used to extract YJP. The parameters were optimized through a combination of single-factor and response surface methodology (RSM). The comprehensive Y value score calculated using the content of 13 active ingredients in YJP ethanolic extracts (YEEs) and the yield of the dry extract were used as measuring criteria. RSM with a Box-Behnken design using three factors and three levels was adopted to optimize the ethanol extraction technology for YJP. Finally, acute and subchronic toxicity tests were performed to evaluate its safety. The results revealed the best technological parameters: a liquid-material ratio of 24:1, an ethanol concentration of 69%, assistance of ultrasound (40 °C, 50 kHZ, 30 min), reflux time of 53 min, and reflux temperature of 50 °C. In acute toxicity tests, the maximum administration dosage in mice was 28.21 g/kg, which is higher than 10 times the clinical dosage. Adverse effects in the acute and subchronic toxicity tests were not observed. All clinical indexes were normal. In conclusion, the RSM based on AHP-CRITIC weight analysis could be used to optimize the ethanol extraction technology for YJP and YEEs prepared under the above conditions and ensure high safety.

Ranking the Critical Success Factors for Hospital Information Systems Using a Fuzzy Analytical Hierarchy Process.

The design, development, and maintenance of hospital information systems face major challenges, which ultimately cause failures of these information systems. This study aimed to identify and rank critical success factors for hospital information systems by applying a fuzzy analytical hierarchy process. Potential critical success factors that could contribute to the success of hospital information systems were identified and extracted through a systematic review of the relevant studies. A questionnaire containing the critical success factors was designed and distributed to 250 hospital information system professionals. The hierarchical structure of the critical success factors was defined by using an exploratory factor analysis, and pairwise comparison matrices of the fuzzy analytical hierarchy process model were designed based on the identified factor structure. As a result, 50 potential critical success factors were extracted from 21 articles, and their content validity and face validity were assessed by the experts. Based on the exploratory factor analysis results, 36 critical success factors were classified into seven dimensions: organizational fitness, user-friendliness, maintainability, portability, productivity, reliability, and organizational and external support. The fuzzy analytical hierarchy process results indicated that reliability, user-friendliness, and organizational fitness (with 20.3, 19.9, and 18 points, respectively) had the greatest impact on the success of hospital information systems. The findings revealed that managers and policymakers should consider these critical success factors in designing and developing hospital information systems.

Performance evaluation of rural water environment governance based on AHP: a case study of the Beitang River Basin.

Rural water environment governance in China still lacks a systematic and comprehensive assessment protocol to help analyze and improve such governance performance. The Analytic Hierarchy Process (AHP) method was employed in this study to build a governance assessment system that integrates ecological conditions, water pollution control, and public satisfaction. To cover these topics, the assessment system is composed of an indicator layer that is customized to rural water environment governance in China. The Beitang River, located in the rural region of Hangzhou, Zhejiang, China, was presented as a case study. Field investigation provided raw data for this assessment. A questionnaire survey was conducted to interview local residents on the governance performance. An additional survey with executives who played major roles in the governance was performed to reconstruct a water environment assessment on the Beitang River prior to the governance, in order to highlight the effects of the governance through contrast. The results showed consistency in the questionnaire survey and the assessment system. The AHP assessment system was able to reflect the improvement in the water quality, river ecology, and residential welfare after the governance, and suggested limits and future directions in the following upgrade programs for the river basin.

An integrated AHP-PROMETHEE II ranking method to evaluate the resilience of sewer networks considering urban flood and ground collapse risks.

The aim of this study is to present criteria to evaluate the resilience of sewer networks related to ground collapse and urban flooding likely to occur in a specific region and then to determine the ranks of the sewer networks resilience of the selected regions to show the applicability of the analytic hierarchy process (AHP) and the Preference Ranking Organization Method for Enriching Evaluations (PROMETHEE II) method. Fourteen evaluation criteria representing resistance, reliability, redundancy, and response and recovery are presented and their weights are estimated by the AHP by asking questionnaires to 10 sewer experts, leading to the result that the sub-criteria of reliability showed the highest importance, followed by the length ratio of good pipelines (under resistance) and adequacy of the flow capacity of the bypass pipelines (under redundancy). Four separate small blocks of drainage areas (total area of 3.57 km2; sewer length of 50.6 km) in Seoul are chosen for the case study. Using appropriate preference functions and thresholds for each evaluation criterion for PROMETHEE II application yields the resilience rankings of four blocks as Block III > Block IV > Block I > Block II. A sensitivity analysis was also carried out by changing the weights.