Historical heritage-MultiCriteria Decision Method (H-MCDM) to prioritize intervention strategies for the adaptive reuse of valuable architectural assets

Identifying the most suitable strategy for the adaptive reuse of historic architectural heritage is a complex challenge. This is because each rehabilitation project of an abandoned historic building must not only ensure the simultaneous pursuit of social, cultural and financial goals, but also the transmission of tangible and intangible values to future generations. In this context, the use of multi-criteria approaches helps to synthesise stakeholders' preferences based on multiple and conflicting criteria, with the aim of promoting sustainable solutions for the restoration and valorisation of valuable architectural assets. To this end, we characterise the Historical heritage - MultiCriteria Decision Method (H-MCDM), an analysis and evaluation tool aimed at identifying the best adaptive reuse of historic buildings considering the principles of architectural conservation and both economic and socio-cultural values. It is a model based on the Analytic Hierarchy Process (AHP), which employs 7 evaluation indicators, chosen after a critical and interpretative analysis of both the sustainability principles promoted by the United Nations and UNESCO, and the ICOMOS quality principles. The H-MCDM is structured on the following five logical-operational steps: (i) identification of strategies for adaptive reuse of the historic building; (ii) construction of the matrices of the pairwise comparisons of the criteria and estimation of the vector of the weights of the criteria; (iii) construction of the matrices of the pairwise comparisons of the alternatives against each evaluation criterion and estimation of the local scores of the alternatives; (iv) consistency checks of the decision matrices; (v) calculation of the total priority and ranking of the HBU strategies for historic assets. The application to a case study demonstrates that, due to its adaptability and versatility, the H-MCDM can be a valid and consistent decision support in public resource allocation processes for the rehabilitation of architectural heritage.•The H-MCDM is a flexible and practical tool to evaluate the best strategy for adaptive reuse of historical heritage.•The H-MCDM is an AHP-based model which employs 7 indicators relating to the social, cultural and economic spheres.•The evaluation indicators are chosen in accordance with 2030 SDGs and European Quality Principles.

Forecasting and advancing water carrying capacity in Henan Province in China: Application of 'four determinations with water' in AHP and SD modeling

Water resources carrying capacity (WRCC) is indispensable for sustainable development, acting as a crucial determinant for harmonizing ecological preservation with socio-economic advancement. This research delineates an advanced evaluation index system for WRCC, focusing on Henan Province, China, a region straddling the Yangtze, Huaihe, Yellow, and Haihe river basins. Leveraging the analytic hierarchy process (AHP) with a system dynamics (SD) model, our analysis dissects the nonlinear interplays among demographic expansion, economic activities, land use patterns, water resources, and water environment. We introduce a novel integration of the "Four Determinations with Water" principle with sustainable development tenets, thereby sculpting six exploratory scenarios that chart Henan's potential paths from 2022 to 2035. Through these scenarios, we forecast and scrutinize the evolution of population dynamics, GDP, water supply, and sewage discharge volumes, employing rigorous quantitative analyses for a holistic evaluation. The results show that: WRCC in Henan Province becomes larger gradually, and, in Scenario 6, the WRCC indicator is the largest (0.643 in 2035) and the prediction effect is the best, while in Scenario 1, the WRCC indicator is the smallest (0.472 in 2035) and the prediction effect is the worst. Based on the prediction results, suggestions were made to adjust the industrial structure and strengthen the awareness of water conservation to improve the regional water resources carrying capacity.

An application of AHP and fuzzy entropy-TOPSIS methods to optimize upstream petroleum investment in representative African basins

The growing demand of China for petroleum heightens the complexities and prospects in worldwide investments, necessitating refined and strategic investment approaches. Evaluating the potential of different hydrocarbon-potential areas needs more comprehensive scientific evaluation models. This study aims to establish a Comprehensive Investment Potential of Petroleum (CIPP) framework for targeted sedimentary basins by using an integrated approach that combines the Analytic Hierarchy Process (AHP) and the Entropy-Weighted Fuzzy TOPSIS models. We focus particularly on representative African basins to inform strategic decision-making for the Chinese overseas petroleum enterprises. We firstly interpret the geological condition of these petroleum basins by researching multiple databases and proprietary research data. Then, we use a combined approach of ranking-classification-correlation analysis to evaluate 17 representative basins, taking into account both overall and individual key performance indicators. Our findings suggest the Illizi Basin and the Offshore Côte d'Ivoire Basin could be the most favorable for investment and development. Those like Southwest African Basin warrant cautious consideration. The new evaluation model and computational workflow offer an effective workflow for assessing multiple petroleum basins. This work provides not just practical investment strategies for companies aiming for African petroleum basins, but also a transferable methodology for optimizing investment decisions.

Research on rockburst prevention systems based on the attenuation law of coal and rock vibration wave energy

During the coal and rock mass fracture process, elastic properties are released and vibration waves are radiated outward. The energy attenuation characteristics of these waves can describe the cumulative damage and elastic energy accumulation of the mass. To investigate coal and rock mass failure characteristics and energy attenuation rules during rockburst, numerical simulation and laboratory testing were utilized to study the energy transfer laws under various parameters. Six variables, including elastic modulus, Poisson's ratio, bulk density, cohesion, internal friction angle, and void ratio, were selected to simulate the rockburst energy release process under different parameter combinations by adding surface pressure to the model. The coal and rock mass energy attenuation coefficient was obtained by fitting the node energy straight line using the least squares method. The six variables' influence on vibration wave energy transfer was obtained using analytic hierarchy process program written in MATLAB, and a comprehensive calculation formula was proposed. Using the energy attenuation coefficient, the rock layer energy diffusion distance was calculated and compared with the roof collapse rock layer step distance, resulting in the roof rock layer cutting distance determination. By roof rock strata precutting, rockburst occurrence can be prevented, ensuring safe and efficient coal mine production.

Age-appropriate design of domestic intelligent medical products: An example of smart blood glucose detector for the elderly with AHP-QFD Joint KE

Background

In response to the rise of intelligent products and the increasing prevalence of urban "empty nesters," we have developed a product specifically tailored for elderly diabetic patients. This product fulfils functional requirements and addresses stylistic preferences, contributing to the age-friendly evolution of home intelligent medical devices, particularly in intelligent blood glucose monitoring.

Methods

Our approach commenced with a comprehensive user experience analysis to ascertain the needs of elderly users regarding home blood glucose meters. This involved constructing a hierarchy of user demands, followed by analysing and prioritising these needs. Utilizing Quality Function Deployment (QFD), we aligned user requirements with design specifications, identifying specific product functionalities and service design elements. Further, we employed Kansei Engineering (KE) to select sample designs that resonate with the concept of sensual imagery, leading to the derivation of specific modelling intentions. Combining these design elements, we proposed product design strategies and conducted practical case studies. The effectiveness of these designs was then assessed through fuzzy evaluation methods, allowing for user feedback.

Results

Employing the Analytic Hierarchy Process for goal analysis, along with Quality Function Deployment theory and Kansei Engineering, we developed a home intelligent blood glucose meter catered to the elderly. This device not only meets its users' physiological and psychological needs but also provides an operationally convenient, health-conscious, and aesthetically pleasing experience.

Conclusions

This methodology enhances the age-appropriate design of home-based smart glucose monitors for the elderly, offering innovative insights and optimization strategies for designing elderly-centric smart medical products.

InSAR and machine learning reveal new understanding of coastal subsidence risk in the Yellow River Delta, China

Coastal subsidence is a geological disaster that has devastating consequences. However, an accurate understanding of its risks involves more than simply assessing the amount or rate of land subsidence. The existing methods used to evaluate geological disaster risks depend on extensive data collection, entail substantial workloads, suffer from error estimation challenges, and lack regional adaptability. These limitations prevent us from fully understanding coastal subsidence risks in estuarine deltas. Therefore, in this study, we propose a new subsidence risk assessment method that addresses the challenges of traditional geological risk assessments in terms of spatial coverage, spatiotemporal resolution, and data collection difficulty. First, Sentinel-1 multitemporal interferometric synthetic aperture radar (MT-InSAR) and cluster analysis were used to estimate the subsidence hazards. Subsequently, Landsat-8 imagery and a random forest (RF) classifier were used to obtain land use and land cover (LULC), and the analytic hierarchy process (AHP) was used to obtain settlement vulnerability. Thereafter, subsidence susceptibility was derived from the sediment layer thickness. By combining subsidence hazard, vulnerability, and susceptibility, the first subsidence risk map with a 30 m resolution was generated. The results showed that 4.54 % of the Yellow River Delta (YRD) area was high-risk, 8.75 % was medium-risk, and 10.14 % was low-risk. Notably, the risk map shows a clear overlap between high-risk and saltwater mining areas in the YRD. The proposed method is expected to improve our understanding of the coastal subsidence risk in estuarine deltas. Considering that the risk in high-value economic areas in the YRD is increasing, whereas the risk in low-value economic areas may change owing to human activity, early preventive measures are required.

Evaluating lake water quality with a GIS-based MCDA integrated approach: a case in Konya/Karapınar

Considering water quality is an essential requirement in terms of environmental planning and management. To protect and manage water resources effectively, it is necessary to develop an analytical decision-support system. In this study, a systematic approach was suggested to evaluate the lake water quality. The methodology includes the prediction of the values in different locations of the lakes from experimental data through inverse distance weighting (IDW) method, creation of maps by using Geographic Information System (GIS) integrated with analytic hierarchy process (AHP) from multi-criteria decision analysis (MCDA), reclassification into five class, combining the time-related spatial data into a single map to predict the whole lake water quality from the data of sampling points, and finally overlapping the final maps with topography/geology and land use. The proposed approach was verified and presented as case study for Meke and Acigol Lakes in Konya/Turkey which were affected by human and natural factors although they have ecological, hydromorphological, and socio-economic importance. In the proposed approach, categorizing water quality parameters as "hardness and minerals," "substrates and nutrients," "solids content," "metals," and "oil-grease" groups was helpful for AHP with the determined group weights of 0.484, 0.310, 0.029, and 0.046, respectively. Assigning weights within each group and then assigning weights between groups resulted in creating accurate final map. The proposed approach is flexible and applicable to any lake water quality data; even with a limited number of data, the whole lake water quality maps could be created for assessment.

Identifying high-vulnerable garbage accumulation areas in Coimbatore City, India: an AHP-GIS approach for effective waste management

Urbanization has resulted in a surge in municipal solid waste (MSW) generation, posing critical waste management challenges in urban areas. To tackle this issue, we introduce a novel approach for mapping garbage vulnerability zones (GVZ) in Coimbatore City, India, combining the analytic hierarchy process (AHP) and Geographic Information System (GIS). Seven criteria, including per capita waste generation, open dumping, land use land cover, road/railway networks, and population, were integrated and analyzed in GIS. AHP pairwise comparison method assigned weights to each criterion and principal component analysis (PCA) further validated the interconnectedness of the criteria and their impact on the GVZs. The results indicated that open dumping locations and population density are the most influential factors contributing to the risk of garbage accumulation, making up 23.7% and 21.2% of the total weight, respectively. The GVZ map reveals that 94.6% of Coimbatore City is at risk of MSW accumulation, with 20.2% highly and 74.4% moderately vulnerable. Eleven high GVZ clusters were identified, with Saravanampatti, located in the northeastern part of Coimbatore City, being the most vulnerable area. The H3 hexagon format of the GVZ map enhances its usability for monitoring and mitigation capabilities. In conclusion, our comprehensive AHP-GIS approach facilitates effective waste management practices, sustainable resource utilization, and better environmental and public health outcomes in urban areas. The demonstrated methodology has the potential for application in similar developing urban areas in South Asia and the Global South, serving as a valuable tool to address the challenges posed by increasing MSW generation.

[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.

Sustainable tourism development for traditional Chinese drama's intangible cultural heritage

This study establishes an expert-driven evaluation system to assess the sustainable tourism development of drama-related intangible cultural heritage in China. Utilizing the Saaty 1-9 scale and hierarchical analysis method, 52 experts determined indicator weights and current development levels. Four dimensions are evaluated: humanistic value, project quality, tourism development, and sustainability. Results reveal humanistic value as most vital at 41.70 % weight. Secondary factors are project quality (29.89 %), tourism development (20.87 %), and sustainability (7.54 %). Aesthetic value, dissemination degree, and location conditions proved to the crucial tourism indicators. The ideological value of drama is paramount, alongside visibility and climate factors. The evaluation demonstrated strong preservation of humanistic value but deficiencies in tourism development, especially regarding infrastructure. Key recommendations include balancing preservation, dissemination, and innovation; emphasizing ideological value, visibility, and climate suitability; maintaining humanistic diversity; and improving site infrastructure. Further testing of evaluation indicators across periods is warranted alongside examining green revitalization potential. This assessment, guided by experts, offers a thorough framework for the sustainable development and preservation of the precious intangible heritage embodied in Chinese drama.

[Construction of an evaluation index system for the capability of comprehensive control of mountain - type zoonotic visceral leishmaniasis based on the One Health concept]

OBJECTIVE

To construct an evaluation index system for the capability of comprehensive control of mountain-type zoonotic visceral leishmaniasis based on the One Health concept, so as to provide insights into the control and elimination of mountain-type zoonotic visceral leishmaniasis using the One Health approach.

METHODS

A preliminary evaluation index system was constructed based on literature review, panel discussions and field surveys. Thirty-three experts were selected from 7 provincial disease control and prevention centers in Beijing Municipality, Hebei Province, Shanxi Province, Henan Province, Sichuan Province, Shaanxi Province and Gansu Province where mountain-type zoonotic visceral leishmaniasis was endemic, and two rounds of expert consultations were conducted to screen the indicators. The positive coefficient, degree of concentration, degree of coordination, and authority of the experts were calculated, and the normalized weights of each index were calculated with the analytic hierarchy process.

RESULTS

The response rates of questionnaires during two rounds of expert consultation were both 100.00% (33/33), and the authority coefficients of the experts were 0.86 and 0.88, respectively. The coefficients of coordination among experts on the rationality, importance, and operability of the indicators were 0.392, 0.437, 0.258, and 0.364, 0.335, 0.263, respectively (all P values < 0.05). Following screening, the final evaluation index system included 3 primary indicators, 17 secondary indicators, and 50 tertiary indicators. The normalized weights of primary indicators "external environment", "internal support" and "comprehensive control" were 16.98%, 38.73% and 44.29%, respectively. Among the secondary indicators of the primary indicator "external environment", the highest weight was seen for natural environment (66.67%), and among the secondary indicators of the primary indicator "internal support", the lowest weight was seen for the scientific research for visceral leishmaniasis control (8.26%), while other indicators had weights of 12.42% to 13.38%. Among the secondary indicators of the primary indicator "comprehensive control", the weight was 16.67% for each indicator.

CONCLUSIONS

An evaluation index system has been constructed for the capability of comprehensive control of mountain-type zoonotic visceral leishmaniasis based on the One Health concept. In addition to assessment of the effect of conventional mountain-type zoonotic visceral leishmaniasis control measures, this index system integrates the importance of top-level design, organizational management, and implementation of control measures, and includes indicators related to multi-sectoral cooperation.

Selection of software agile practices using Analytic hierarchy process

Context

The increasing use of software and information technology in modern society requires that the deployment of IT solutions should be more efficient and controlled. In this sense, agile methodologies are essential to achieve this goal, but a relevant question arises: Which is the right methodology for reaching that goal?

Objective

The purpose of the research was to study the prioritization of agile practices and improvement objectives in the context of software development, using the Analytic Hierarchy Process (AHP) method. For this purpose, 42 agile practices, 16 improvement objectives, 4 organizations dedicated to software development in Colombia and 40 professionals in the area of information and communication technologies in the same country were considered.

Method

ology: The methodological approach used was mixed. On the one hand, we applied a quantitative approach for the treatment of data with the AHP method and, on the other hand, a qualitative analysis by consulting experts through a digital survey to validate the prioritization of the improvement objectives. Questionpro was used as a support tool for multicriteria comparison.

Results

The main results show that applying AHP allowed us to prioritize 6 improvement objectives and 5 agile practices, where it is highlighted that the prioritization does not discard the other objects of comparison but allows us to put into practice the prioritized elements to favor their progressive implementation. The non-prioritized elements could be part of future iterations of multicriteria comparison that go hand in hand with capacity development and organizational maturity models in the context of global software development.

Conclusion

It is highlighted that, although there is evidence of the application of multi-criteria comparison methods in the software development industry, this work applies such methods in the context of four different agile methodologies, which translates into a precedent for the conformation of hybrid methodological approaches.

A novel network security situation assessment model based on multiple strategies whale optimization algorithm and bidirectional GRU

The rapid development of the internet has brought about a comprehensive transformation in human life. However, the challenges of cybersecurity are becoming increasingly severe, necessitating the implementation of effective security mechanisms. Cybersecurity situational awareness can effectively assess the network status, facilitating the formulation of better cybersecurity defense strategies. However, due to the low accuracy of existing situational assessment methods, situational assessment remains a challenge. In this study, a new situational assessment method, MSWOA-BiGRU, combining optimization algorithms and temporal neural networks, was proposed. Firstly, a scientific indicator system proposed in this research is used to calculate the values of each indicator. Then, the Analytic Hierarchy Process is used to derive the actual situation values, which serve as labels. Taking into account the temporal nature of network traffic, the BiGRU model is utilized for cybersecurity situational assessment. After integrating time-related features and network traffic characteristics, the situational assessment value is obtained. During the evaluation process, a whale optimization algorithm (MSWOA) improved with a mix of strategies proposed in this study was employed to optimize the model. The performance of the proposed MSWOA-BiGRU model was evaluated on publicly available real network security datasets. Experimental results indicate that compared to traditional optimization algorithms, the optimization performance of MSWOA has seen significant enhancement. Furthermore, MSWOA-BiGRU demonstrates superior performance in cybersecurity situational assessment compared to existing evaluation methods.

Lessons learned from a study based on the AHP method for the assessment of sustainability in neighborhoods

The Analytic Hierarchy Process (AHP) is a method that allows complex decisions to be made from impartiality, making it suitable for reaching a consensus among experts seeking to solve a problem. This method has been successfully applied in other investigations, and its use has been extended to several disciplines. This technical paper presents the lessons learned from a study that relied on the AHP method to determine priority aspects for sustainable neighborhoods. The research is developed in three replicable phases. In each of them, aspects that are recommended to be considered are detailed, for example, in the formulation of the hierarchical structure, selection of experts, expert survey design, and information processing for the determination of weights and levels of importance.•The utilization of software to apply the AHP method can help researchers to optimize time and resources.•Social networks proved to be more effective than conventional methods for identifying and contacting experts.•Subjective sustainability issues can be prioritized by expert consensus.

Development of care quality indicators for palliative care in China: A modified Delphi method study

Objective

While there are limited studies addressing palliative care quality in China, the availability of an effective set of care quality indicators is scarce. This study aimed to develop a comprehensive set of quality indicators for palliative care in China.

Methods

Conducting a systematic literature search across databases and guideline websites from inception to October 2020, combined with qualitative interviews, we established a preliminary pool of indicators. Subsequently, two rounds of Delphi expert consultation surveys were administered to 19 multidisciplinary experts (specializing in clinical nursing/medicine, nursing/medicine management, and health care administration, as well as those engaged in teaching and research) from 12 provinces in Mainland China (three each from North, East, and South China, and four from Central China) via email from March to June 2021. The analytic hierarchy process was employed to determine indicator weights.

Results

Both rounds of expert consultation yielded a 100% positive coefficient, with expert authority coefficient values of 0.91 and 0.93, respectively. Kendall coefficient of concordance values for the two rounds were 0.148 and 0.253 (P < 0.001), indicating consensus among experts. Consequently, 71 quality indicators deemed important in the Chinese palliative care setting were identified, comprising 22 structure indicators, 35 process indicators, and 14 outcome indicators.

Conclusions

This study established an evidence-based set of quality indicators, addressing previously unmet needs and providing a novel approach to assessing and monitoring palliative care quality. Furthermore, ongoing refinement and integration with the evolving social context are warranted.

The application of integrating comprehensive evaluation and clustering algorithms weighted by maximal information coefficient for urban flood susceptibility

Different sub-regions of Zhengzhou city have various levels of sensitivity to flood due to the impact of urbanization. Thus, an accurate flood sensitivities assessment is a key tool for flood prevention and urban planning and development. To successfully link the urban flood sensitivity assessment with the real flood situation, a method combining clustering algorithm with comprehensive evaluation is presented. The proposed method is not affected by the classification standard of sensitivities levels and has a small and undemanding demand for flood data. First, Maximal Information Coefficient between conditional factors and flood is employed to determine the weight. Then, the different results are obtained by three clustering algorithms. Finally, a four-layer evaluation structure weighted by analytic hierarchy process is established to select the best flood susceptibility map. A case study in the Zhengzhou city, China shows that the positive scale amplification strategy is relatively best and the flood sensitivity of sub-regions in Zhengzhou city should be divided into four levels obtained by K-Means clustering. Hence, it supplies the valuable insights for the urban planning and flood mitigation.

Measuring the Capability of Biological Incident Rescue Teams in China: A Fuzzy Analytic Hierarchy Process Based Model - Tianjin Municipality, China, 2022-2023

Introduction

The swift advancement of biotechnology has presented both opportunities and challenges to our society, thrusting biosafety to the forefront of concern. Consequently, the evaluation of rescue capabilities in the event of a bioterrorism incident becomes of paramount importance. Currently, there is a notable absence of specific measurement criteria and a comprehensive evaluation system. This paper aims to establish a systematic approach towards assessing emergency response capabilities in the context of bioterrorism incidents.

Methods

We employed an enhanced Delphi methodology to establish an index evaluation framework. Subsequently, the weight of the judgment matrix was ascertained via the application of the fuzzy comprehensive evaluation approach. This led to the creation of a fuzzy comprehensive evaluation model for bioterrorism rescue capability.

Results

A modified Delphi study was conducted involving 11 experts across two rounds, achieving a response rate of 100%. The Kendall coordination coefficients recorded in the first and second rounds were 0.303 and 0.632, respectively (P<0.05). Upon comprehensive analysis involving score, coefficient of variation, and full score ratio, we distinguished five primary indicators and 25 secondary indicators. Subsequently, an evaluation model was developed based on the Analytic Hierarchy Process (AHP) tailored to assess the response to a rescue from bioterrorism.

Discussion

The expert panel confirmed consensus on all aspects of the model, validating its comprehensive content. The succeeding course of action involves converting the assessment model to a measurable scale, affirming its functionality, and implementing it in practical evaluation tasks to further enhance the capabilities of the biological incident rescue team.

An investigation into the disturbance effects of coal mining on groundwater and surface ecosystems

Coal mining disturbs surface ecosystems in coal mining subsidence areas. Based on the groundwater-surface composite ecosystem analysis, we constructed an ecological disturbance evaluation index system (18 indices) in a coal mining subsidence area using the analytic hierarchy process (AHP). Taking the Nalinhe mining area in Wushen Banner, China, in 2018-2020 as an example, the weight, ecological disturbance grade and correlation of different indicators were determined by implementing fuzzy mathematics, weighting method, and correlation analysis method. The major conclusions of this review were: (i) After two years of mining, ecological disturbance was the highest in the study area (Grade III) and the lowest in the non-mining area (Grade I). (ii) Coal mining not only directly interfered with the environment, but also strengthened the connection of different ecological indicators, forming multiple ecological disturbance chains such as "mining intensity-mining thickness-buried depth/Mining thickness", "coal mining-surface subsidence-soil chemical factors", and "natural environment-soil physical factors". The disturbance chain that controls the ecological response factors in the region remains to be determined. However, the ecological response factors are the most important factor that hinders the restoration of the ecology in a coal mining subsidence area. (iii) The ecological disturbance in the coal mining subsidence area continued increasing over two years due to coal mining. The ecological disturbance by coal mining cannot be completely mitigated by relying on the self-repair capability of the environment. This study is of great significance for ecological restoration and governance of coal mining subsidence areas.

Wetland health assessment using DPSI framework: a case study in Kolkata Metropolitan Area

Wetlands are among the most valuable components of the ecosystem, playing an important role in preventing floods, maintaining the hydrological cycle, protecting against natural hazards, and controlling local weather conditions and ecological restoration. The Kolkata Metropolitan Area (KMA) is considered one of the most ecologically valuable regions in terms of wetland ecosystem, but due to haphazard development and human activities, the wetlands of the city are under constant threat of degradation. Therefore, this study aims to assess the factors responsible for wetland health and their dynamics using Driving Force-Pressure-State-Impact (DPSI) framework. To assess wetland health during 2011-2020, seventeen indicators and four sub-indicators were selected to calculate weights using the analytic hierarchy process (AHP). The results showed that most of the municipalities in the healthy category were in the pressure (P) section in 2011, while fluctuations were observed in the impact (I) section in several wards during 2011-20. The condition section (S) showed the overall change in the water, vegetation, and built-up categories from 2011 to 2020, so the most dominant category was "healthy," followed by "unhealthy" and "poor." The highly significant factors worsening wetland health were population density (B1), road density (B3), per capita wastewater generation (B5), per capita solid waste generation (B7), biological oxygen demand (D1a), dissolved oxygen (D1b), pH (D1c), and total coliform (D1d). The results of the study can help develop sustainable conservation and management of the wetland ecosystem in the KMA urban area and at the global level with similar geographical conditions.

Study on the spatial distribution of urban carbon emissions at the micro level based on multisource data

Global warming is currently an area of concern. Human activities are the leading cause of urban greenhouse gas intensification. Inversing the spatial distribution of carbon emissions at microscopic scales such as communities or controlling detailed planning plots can capture the critical emission areas of carbon emissions, thus providing scientific guidance for intracity low-carbon development planning. Using the Sino-Singapore Tianjin Eco-city as an example, this paper uses night-light images and statistical yearbooks to perform linear fitting within the Beijing-Tianjin-Hebei city-county region and then uses fine-scale data such as points of interest, road networks, and mobile signaling data to construct spatial characteristic indicators of carbon emissions distribution and assign weights to each indicator through the analytic hierarchy process. As a result, the spatial distribution of carbon emissions based on detailed control planning plots is calculated. The results show that among the selected indicators, the population distribution significantly influences carbon emissions, with a weight of 0.384. The spatial distribution of carbon emissions is relatively distinctive. The primary carbon emissions are from the Sino-Singapore Cooperation Zone due to its rapid urban construction and development. In contrast, carbon emissions from other areas are sparse, as there is mostly unused land under construction.

[Construction of a schistosomiasis transmission risk assessment system in Wuhan City based on analytic hierarchy process]

OBJECTIVE

To construct a schistosomiasis transmission risk assessment system in Wuhan City and preliminary evaluate its application effect, so as to promote the rational allocation of schistosomiasis control resources and accelerate the progress towards schistosomiasis elimination.

METHODS

The schistosomiasis risk assessment indicators were collected through referring schistosomiasis surveillance data of Wuhan City from 2014 to 2020, literature review and expert interviews. Indicators within each criterion and sub-criterion were screened using the Delphi method, and a hierarchical structure model was created based on analytic hierarchy process. Quantitative assignment of each indicator was conducted according to relative importance, and the weight and combination weight of each criterion were calculated in each analytic hierarchy framework to create a schistosomiasis transmission risk assessment system, which was used for the schistosomiasis transmission risk assessment in 12 national schistosomiasis surveillance sites in Wuhan City.

RESULTS

A three-level schistosomiasis transmission risk assessment system was preliminarily constructed, which included a target layer, 5 criterion layers and 21 sub-criterion layers. Of all indicators in the criterion layer, transmission route had the highest weight (0.433), followed by source of Schistosoma japonicum infection (0.294); and among all indicators in the sub-criterion layer, S. japonicum infection in Oncomelania hupensis and sentinel mice had the highest combination weight (0.125), followed by prevalence of S. japonicum infection in humans (0.091) and bovines (0.053), snail control by chemical treatment (0.049), positive rate of inquiry examinations (0.048), allocation of schistosomiasis control professionals (0.045), and areas of submerged snail-infested settings (0.041). Of the 12 national schistosomiasis surveillance sites in Wuhan City, there were 5 sites with weights of > 0.8, 4 sites with weights of 0.6 to 0.8, and 3 sites with weights of < 0.6 in 2020.

CONCLUSIONS

A schistosomiasis transmission risk assessment system has been constructed based on analytic hierarchy process in Wuhan City, which may provide a evidence-based basis for health resource allocation and decision-making for schistosomiasis control.

Identification of priority areas for water conservation in the Alto Iguaçu basin, Brazil

Geoprocessing tools are great allies in the management of water resources, permitting the evaluation of several factors integrated into a multicriteria analysis. This improves the interpretation of the behavior of water and soil in hydrographic basins, allowing the delimitation of priority areas for actions. The objective of this study was to prepare a map of priority areas for water conservation in the Alto Iguaçu basin through a multicriteria analysis, aiming to assist in the management of water resources in the region. The priority map for water conservation was prepared using the weighted linear combination (WLC) method, considering the weight added to the factors that were obtained by the analytic hierarchy process (AHP) method. The method successfully identified priority areas for water conservation, where 40.7% of the Alto Iguaçu watershed was considered High priority and Very High priority, a number consistent with regional characteristics. The multicriteria analysis proved to be a flexible and easy to implement methodology, which can help managers when considering the trade-offs among several factors. The implementation of water conservation actions in areas that have been classified as being of High and Very High priority can benefit the regional ecosystem by controlling erosion, regulating the flow of water, and thus conserving the quantity and quality of water in the basin and its downstream region, benefiting the population and regional economics. Integr Environ Assess Manag 2023;00:1-12. © 2023 SETAC.

Using the deterministic approach model for project portfolio selection problem (PPSP) solutions

Selection of projects using a robust technique is rare as most of the techniques are not considered useful due to the limitation on the number of projects that can be selected as well as cost saving projects not being selected. This study investigated the validity of a hybrid model - integrated analytical hierarchy process-goal programming (AHP-GP) - to avoid project portfolio selection problems delaying community development. The proposed model includes two steps: AHP to determine the project criteria, the relative importance of weights, and priority preferences, while the GP model was formulated to select the optimal projects. An empirical study on government agencies was carried out to validate the proposed model, and the results compared against GP as a standalone to solve the same problem. The results proved that the hybrid model (AHP-GP) was better than the GP model. AHP-GP has proved to be a robust mechanism most suitable for managerial use due to its ability to handle multi-criteria decision-making (MCDM) situations. This study showed that the hybrid model can select more projects and will create more jobs in the communities concerned compared to the single model (GP). The novelty of this study is the introduction of an integrated model formed from two distinct models as a deterministic approach to solving project portfolio selection problems.

A critical application of different methods for the vulnerability assessment of shallow aquifers in Zhengzhou City

Groundwater vulnerability can partially reflect the possibility of groundwater contamination, which is crucial for ensuring human health and a good ecological environment. The current study seeks to assess the groundwater vulnerability of Zhengzhou City by adopting an amended version of the traditional DRASTIC model, i.e., the DRASTICL model, which incorporates land use type indicators. More specifically, the AHP-DRASTICL, entropy-DRASTICL, and AE-DRASTICL models were established by optimizing weights using the analytic hierarchy process (AHP) and entropy weight method. The evaluation results for these five models were divided into five levels: very low, low, medium, high, and very high. Using Spearman's rank correlation coefficient, the nitrate concentration was used to verify the groundwater vulnerability assessment results. The AE-DRASTICL model was found to perform the best, with a Spearman correlation coefficient of 0.78. However, the AHP and entropy weight method effectively improved the accuracy of vulnerability assessment results, making it more suitable for the study area. This study provides important insights to inform the design of strategies to protect groundwater in Zhengzhou.

Construction and results of a comprehensive index for gastrointestinal health monitoring in China: a nationwide study

Background

The disease burden of gastrointestinal disease (GD) in China is high, with significant variation across provinces. A comprehensive agreed set of indicators could guide rational resource allocation to support better GD outcomes.

Methods

This study collected data from multiple sources, including national surveillance, surveys, registration systems, and scientific research. Literature reviews and Delphi methods were used to obtain monitoring indicators; the analytic hierarchy process was used to determine indicator weights.

Findings

The China Gastrointestinal Health Index (GHI) system consisted of four dimensions and 46 indicators. The weight of the four dimensions from high to low included the prevalence of gastrointestinal non-neoplastic diseases and gastrointestinal neoplasms (GN) (0.3246), clinical treatment of GD (0.2884), prevention and control of risk factors (0.2606), and exposure to risk factors (0.1264). The highest indicator weight of GHI rank was the successful smoking cessation rate (0.1253), followed by the 5-year survival rate of GN (0.0905), and the examination rate of diagnostic oesophagogastroduodenoscopy (0.0661). The overall GHI for China in 2019 was 49.89, varying from 39.19 to 76.13 across all sub-regions. The top five sub-regions in the total GHI score were in the eastern region.

Interpretation

GHI is the first system designed to monitor gastrointestinal health systematically. In the future, data from sub-regions of China should be used to test and improve the GHI system for its impact.

Funding

This research was supported by the National Health Commission of China, the First Affiliated Hospital of Naval Medical University (2019YXK006), and the Science and Technology Commission of Shanghai Municipality (21Y31900100).

AHP algorithm used to select suitable abandoned underground mines for energy storage infrastructure - iCAES technology. A specific case study for León (Spain)

In the energy transition, the promotion of renewable sources entails the development of storage technologies to manage the mismatch between energy production and demand. In this scenario, the use of CAES (Compressed Air Energy Storage) technology enables the efficient and cost-effective storage of large amounts of energy. However, this technology is developed in salt domes who have an inherent risk associated of underground exploration phase. To address this, we propose to develop an infrastructure (iCAES) in abandoned underground mines, where the exploration phase is completed and well known. For its implementation, this paper defines a structure hierarchization method gathers the technical and socio-economic criteria. It involves a multi-criteria problem, and the correct selection of the location must be based on specific mathematical algorithms. For this case the Analytic Hierarchy Process (AHP) from multi-criteria decision making (MCDM) methods allows quantified by means of a scientific and mathematical scale and the assignment of weights, so that it is possible to evaluate different alternatives. This is possible thanks to the application of the AHP model in absolute terms. The information gathering has been based on the specific case study of coal basins in the north of Spain, in the region of León. Considering the proposed methodology, the most suitable alternative locations to implement iCAES in the region of León were identified.

Mapping analytical hierarchy process research to sustainable development goals: Bibliometric and social network analysis

The drive to achieve the Sustainable Development Goals (SDGs) becomes more urgent as the 2030 deadline draws near, increasing research in various sectors. Nevertheless, studies that systematically map Analytical Hierarchy Process (AHP) publications with the SDGs need to be more conspicuously lacking. Our study adds a new perspective to the field by creatively bridging this knowledge gap using the Elsevier SDG Mapping Initiative. To find research clusters, trends, and themes linked to SDGs and their connection to environmental sustainability, we thoroughly analyzed 29,897 publications from 2012 to 2022. The analysis showed that SDG 15, SDG 7, SDG 12, SDG 13, and SDG 11 were the top five SDGs, with an environmental focus among the 17 SDGs. These top SDGs had many clusters connected to them, illustrating various sustainability-related problems. The study also looked at connections between SDGs, the nations with the highest rates of productivity, the top contributors, and the journals with the highest citation counts. We discovered three separate SDG clusters using co-occurrence network analysis, each representing a different SDG. We discovered relevant SDGs using Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis and centrality indicators like eigenvector and betweenness. This novel method for publishing analysis combines an AHP focus that aligns with the SDGs with social network analysis and centrality metrics. Our research advances knowledge of how the AHP technique can assess initiatives supporting the SDGs. We offer essential insights into prioritizing sustainable development measures by identifying research clusters, trends, and issues related to environmental sustainability. This study highlights the subject's most important SDGs, productive nations, helpful organizations, and significant journals.

A feasibility assessment of utilizing concentrated solar power (CSP) in the Zimbabwean regions of Hwange and Lupane

The current study assesses the feasibility of Zimbabwe's Hwange and Lupane regions to host a large-scale Concentrated Solar Power (CSP) facility. The study's overarching goal is to aid in identifying, classifying, and validating suitable sites for hosting a CSP facility. In this paper, suitable sites are identified and classified by coupling the multi-criteria decision-making (MCDM) technique (specifically the analytical hierarchy process, abbreviated AHP) and geographic information system (GIS) software. Following the identification of suitable regions, the validation is carried out by technical and economic measures. As a specific criterion for decision-making, a geographic database was developed utilizing layers provided by various data sets on irradiance, orography, location, and water resources. The final maps using special tools in ArcGIS Pro revealed that the land available for concentrating solar power in Hwange and Lupane is 1792 km² (5.6% of the study area) and 3771 km² (11.9% of the study area), respectively. A Monte Carlo Simulation (MCS) of the theoretical power potential revealed that suitable sites in Hwange and Lupane could technically generate power ranging from 380.0 TWh/year to 477.5 TWh/year and 878.8 TWh/year to 1125.0 TWh/year, respectively. The CSP facility without a thermal energy storage (TES) facility has a $ cost per kWh of 0.1879, while the CSP-TES hybrid costs 0.1468. The LCOE for CSP without TES and CSP with TES is $ 0.0679 and $ 0.0268 higher than Zimbabwe's electricity cost, respectively. Overall, results suggest that Lupane is an excellent location for CSP facilities and supports policymakers in establishing renewable energy tariffs, resulting in economic and sustainable development.

Flood prediction and vulnerability assessment at the south-western region of Bangladesh

Flood is a frequent experience for the people living in Bangladesh, especially in the south-western region. But due to its complexity and multidisciplinary nature, flood management remains a very difficult task. This research focused on finding the most vulnerable areas to flooding for each polder within the Khulna and Satkhira districts since those areas can be identified as one of the most vulnerable areas to flooding. Water level data from fourteen stations of seven rivers (Sibsa, Rupsa-Pasur, Kobadak, Bhadra, Kobadak, Ichamati (Western Border), Betna-Kholpetua, and Satkhira Khal) were analyzed to calculate water levels for 2, 5, 10, 25, and 100-year return period applying normal distribution, extreme value type-I (EV-I), and log person type-III (LP-III) distribution methods. The EV-I distribution method was showing the best fit. The study revealed that station SW243 (Rupsa-Pasur River) in the Dacope region has the most extreme water level, station SW259 (Sibsa River) has the second-highest water level, and station SW254.5 (Satkhira Khal) in Satkhira Sadar has the third-highest water level for the return period of 100 years. A flood inundation map was prepared using the EV-I method's 10-year return period value. The Analytic Hierarchy Process (AHP) was used to demonstrate the polders' vulnerability depending on several factors. Overall, polder15 (Ghubra, Satkhira) is the most vulnerable polder, while polder 33 and polder 32 respectively are the second and third most vulnerable polders for flooding, both located in the Dacope region.

Assessing the impact of COVID-19 pandemic on the performance indicators of safety management using the analytic hierarchy process (AHP) in an electricity industry

Introduction

The importance of evaluating the performance of different management systems in industries necessitates examining the performance of the Health, Safety, and Environment (HSE) management system along with other management systems. Particularly during the COVID-19 pandemic, there is a greater need than ever to assess the impact of the COVID-19 spread on the performance of the HSE management system compared to before this pandemic. This research aims to investigate safety performance indicators (SPIs) on the performance of the HSE management system and the impact of the COVID-19 spread on these indicators.

Methods

This cross-sectional, descriptive-analytical study was conducted to evaluate the influence of the COVID-19 outbreak on the safety performance to revise the industry safety index in an electricity distribution company using the multi-criteria decision-making method before and after the disease epidemic in three stages. In the first part, the safety indicators were identified according to the comprehensive safety indicators available in the industries and experts' opinions. In the second part, safety indicators were ranked, weighted, and prioritized using the Analytic Hierarchy Process (AHP). In the third part, these indicators were calculated and compared in the periods before and after the outbreak of COVID-19.

Results

Two main criteria, namely the "effectiveness criterion" and the "applicability/calculation criterion", were identified for the evaluation and pairwise comparisons of performance indicators. Among these two criteria, the applicability/calculation criterion had higher priority and importance for the evaluation of indicators. Pairwise comparisons of the indicators indicated that the "accident frequency rate" and "safe T-factor" indicators (with weights of 0.238 and 0.023 respectively) had the highest and lowest priorities, respectively, for the assessment of organizational safety performance among the SPIs.

Conclusion

Based on the calculations of the indicators and their analyses before and after the outbreak of COVID-19, the current status of the safety performance of the HSE unit was not significantly affected by this pandemic. However, the investigations carried out while collecting the data needed to calculate the indicators and evaluate the performance of this unit demonstrated that some indicators were not considered sufficiently in the studied electricity industry. Since conducting regular performance evaluations greatly impacts the achievement of continuous improvement, more attention should be paid to compiled indicators, which should be periodically assessed in the organization to achieve continuous improvement.

Targeting of rainwater harvesting structures using geospatial tools and analytical hierarchy process (AHP) in the semi-arid region of Rajasthan (India)

Burgeoning population growth and subsequent demand for freshwater, besides competition among irrigation, domestic, and industrial sectors, coupled with a changing climate, have necessitated prudent and effective management of water resources. Rainwater harvesting (RWH) is considered one of the most effective strategies for water management. However, the location and design of RWH structures are essential for proper implementation, operation, and maintenance. An attempt has been made in this study to locate the most suitable site for RWH structure and design using one of the robust multi-criteria decision analysis techniques, viz. analytic hierarchy process, using geospatial tools in the Gambhir watershed, Rajasthan, India. High-resolution Sentinel-2A data and a digital elevation model of the Advanced Land Observation Satellite were used in this study. Five biophysical parameters, viz. land use and land cover, slope, soil texture, surface runoff, and drainage density, were considered to identify suitable locations for RWH structures. It was observed that runoff is the prime factor in determining the location of RWH structures compared to other parameters. It was revealed that 75.54 km² (13% of the total area) was very highly suited for the construction of RWH structures, while 114.56 km² (19%) was highly suitable. A total of 43.77 km² (7%) of land was determined to be unsuitable for the construction of any type of RWH structure. Farm ponds, check dams, and percolation ponds were suggested for the study area. Furthermore, Boolean logic was used to target a particular type of RWH structure. The study indicated that a total of 25 farm ponds, 14 check dams, and 16 percolation ponds can be constructed at identified locations in the watershed. Water resource development maps of the watershed generated using an analytical approach would be useful for policymakers and hydrologists for targeting and implementing RWH structures in the study watershed.

A safety assessment model of filling mining based on comprehensive weighting-set pair analysis

Filling mining is the main mining method in coal mine, and its safety is the pillar of the overall safety of the mine. Filling mining can effectively protect the surface environment, better solve the problem of ground pressure, and maximize the recovery of underground resources. Therefore, this method has an irreplaceable role in deep mining of coal mines and is highly valued by the mining industry all around the world. In order to evaluate the implementation effect of filling mining, a comprehensive weighting-set pair analysis safety evaluation model is established. This model optimizes the subjectivity of analytic hierarchy process (AHP) and the objectivity of Entropy Weight Method (EWM) in traditional methods. Besides, we add experts' weight to Entropy Weight Method. The combination of the two methods makes the index weight more reasonable and effective, and can more fully reflect the difference and correlation of index. Firstly, the accident causation analysis and taxonomy (ACAT) is used to find out the accident causation factors of filling mining, and then, the AHP and EWM are used to determine the weight of each evaluation index from different perspectives. Then, the evaluation group is established to score the importance of each expert, so as to reduce the subjectivity of expert scoring. Finally, according to the principle of set pair analysis, the safety evaluation model of filling mining is applied to Yuxing Coal Mine in Inner Mongolia. The evaluation result shows that the safety grade of this mine is grade 1 "safety." This paper provides a new way and direction for the comprehensive evaluation of similar mining methods, the establishment of index system, the acquisition of index weights, and the evaluation of safety level, which has promotion and application value.

Wildlife resource conservation and utilization for achieving sustainable development in China: main barriers and problem identification

The rapid growth of the industrial economy has affected the survival of wildlife, and the decline in wildlife resources will in turn have some negative impact on the industrial economy. For the sustainable development of the industrial economy, human beings began to reflect on traditional development thinking and strive to find a development strategy that harmonizes industrial economic development and resource protection, and wildlife protection gradually attracted people's attention. "Protecting wild animals, maintaining ecological balance, and promoting economic development" has become a hot topic in the new century. Wildlife resources are valuable natural resources and play an important role in the ecosystem, which is related to the well-being and future of human beings. In recent years, China has made great progress in wildlife protection, while protecting and expanding wildlife habitats, introducing relevant laws and regulations, and other measures which have been implemented recently. However, there are still shortcomings in the protection of wildlife in China. Over-utilization, habitat loss and degradation, environmental pollution, climate change, weak legal awareness, and indiscriminate hunting all pose serious threats to wildlife in China. In this regard, this paper summarizes the main problems and barriers to wildlife resource conservation and utilization in China. Based on the analytic hierarchy process (AHP), the main technology factors influencing wildlife resource conservation and utilization in China are identified. Finally, the future research development direction of wildlife conservation is discussed based on the critical factors. This can provide some guidance for developing wildlife resource conservation and utilization for a sustainable ecosystem in China.

Identifying the roles of energy and economic factors on environmental degradation in MINT economies: a hesitant fuzzy analytic hierarchy process

Globally, research communities have been studying the different determinants of environmental degradation or pollution using different contexts and methods. In this study, we identify several energy and economic factors, such as energy consumption (EC), gross domestic product (GDP), energy production (EP), urbanization (URB), and foreign direct investment (FDI) as the most effective factors of environmental degradation by obtaining several environmental researchers' opinions and using the hesitant fuzzy analytic hierarchy process. In the later stage of the analysis, we use these variables as regressors of the ecological footprint (EF) as a proxy for environmental degradation. Since we find evidence of cross-sectional dependence among the members of the variables, we use second-generational panel tests. First, we test the stationarity of the variables using the cross-sectionally augmented IPS (CIPS) panel unit test. The results show that the regressors have different orders of integration. So, we employ the Durbin-Hausman panel cointegration test to test the existence of a long-run relationship between the variables. Having found a long-run relationship, we estimate the long-run coefficients using the common correlated effects mean group estimator, which reveals that energy consumption has an increasing effect on the EF in Indonesia and Turkey, while energy production has a negative impact in Mexico and Turkey. While GDP has an increasing effect in all countries, FDI has a similar effect in only Indonesia. Moreover, URB decreases the ecological footprint in Nigeria, while it increases in Turkey. Our approach to the evaluation of environmental degradation can be generalized to other regions as well as where there is a significant need to understand the roles of different drivers on environmental degradation or pollution.

Assessment of the incubating environment for investment in biogas technology in Syria by using AHP and SWOT

In light of the massive energy supply shortage due to the Syrian war since 2011, renewable energy adoption has a high potential to cover the actual energy demand. Hence, this study aims to shed light on the factors that affect investment in biogas technology. With the scarcity of research on alternative energies in Syria, this paper focused on the characteristics of the Syrian environment toward biogas technology adoption. The results show that Syrian society accepts and desires to adopt new technologies, representing an optimal strategy to stimulate biogas technology use and the need to spread awareness about its benefits. The SWOT model was applied to identify strengths, weaknesses, opportunities, and threats facing biogas technology adoption. The analytical hierarchy process model was applied to set priorities and make better decisions related to the knowledge of biogas, acceptance of biogas technology, desire for and common approach for its use, the resulting organic fertilizer, and administrative and financial aspects. The work concludes that the southern region was at the forefront in the areas studied in terms of weights of biogas technology investment criteria, subsequently, the central and later the coastal regions. By presenting a systematic and comprehensive approach, this study represents a roadmap to assist decision-makers in inking decisions related to adopting and deploying biogas technology on a larger scale and contributes to developing a criterion for selecting biogas sites in Syria.

A study on social media and higher education during the COVID-19 pandemic

Nowadays social media usage has increased drastically among the stakeholders of higher educational institutions. The COVID-19 pandemic has suddenly increased the surge of social media users due to the forced implementation of online pedagogy and travel restrictions. The research study presented in this paper attempted to analyze social media usage in higher education. The data were collected from primary and secondary sources with the help of leading research databases, survey questionnaires, the Delphi method, and brainstorming sessions. Statistical tools and analytic techniques incorporated in the study included bibliometric analysis, word cloud, co-occurrence network, thematic map, thematic evolution, co-word analysis, country-wise analysis along with collaboration network, statistical survey, mind mapping, and analytic hierarchy process. The study justified the aspects of social media usage in the higher educational environment. It was found that the research fraternity around the globe focused more on understanding the aspects of social media and higher education during the trying times of the Coronavirus crisis. The maximum impact of social media usage on higher education was found to be from teaching-learning and discussions, and public relations and networking. It was also found that social networking platforms like WhatsApp, YouTube, Facebook (Meta), LinkedIn, Instagram, and Twitter were very common among the stakeholders of higher education. This study is of huge importance because it can help in paving the way to strategize remedial measures for increasing positivity and minimizing the negativity of social media usage in institutions of higher education across the world.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10209-023-00988-x.

Evaluation of the coordination between marine ecological environment protection and marine economic development in China

Over the years, the development of marine economy has been an important component of coastal cities' total economic growth in China. Whether the coastal cities had paid enough attention to the coordination of marine economic development and ecological environment protection in the process of marine development activities needed to be evaluated accordingly. An index evaluation system for the coordination between marine ecological environment protection and marine economic development in coastal cities of China was established in this work by using the analytic hierarchy process. The statistical analysis results from 2006 to 2018 showed that much more attention had been paid on marine ecological environment protection since the year 2012 in China. The evaluated results showed that among all coastal provinces and cities, Shanghai and Shandong Provinces had the best coordination between marine economic development and marine ecological environment protection in the year 2016. Years of data showed that marine economic development and marine ecological environmental protection complement each other and promote each other. At the same time, the analysis results of this indicator evaluation system showed that marine ecological environment protection in China should further strengthen the protection by preventing and controlling marine pollution and carrying out ecological restoration.

A humanistic-care factors application hierarchical design-model for intelligent elderly products

At present, many countries and regions around the world have entered an aging society, so the demand intelligent elderly product has begun to double. However, in the design process of intelligent elderly products, there is a lack of a set of perfect method model and evaluation criteria for the application of humanistic care factors in intelligent elderly products. To standardize the use of humanistic care factors in the design of intelligent elderly products. Firstly, this study uses grounded theory to code and analyze the humanistic care factors. Secondly, the analytic hierarchy process (AHP) and analytic network process (ANP) are used for comparative study to obtain the sensitivity priority of the application of humanistic care factors, and a new design method model is proposed. Finally, the fuzzy evaluation method is used to verify the rationality of the design method model. The study shows that the use of humanistic care factors has the greatest impact on emotion, especially in the consideration of Interactivity, followed by Color mildness and Companionship. The results are divided in the form of a hierarchical demand tower, to establish a new Humanistic-care Factors Application Hierarchical Design-model (HFAHD) for intelligent elderly products. The HFAHD can not only help designers to improve the design efficiency in the design of intelligent elderly products, but also further standardize the use of humanistic care factors in the design of intelligent elderly products. Through the combination of quantitative research and qualitative research, it is proposed to divide the use of humanistic care factors into hierarchical models to help designers better use the HFAHD. This study not only improves the design standards of intelligent elderly products, but also extends to other design fields in further research, and promotes the more rational use of humanistic care factors in design.

A multi-objective optimization approach for integrated risk-based internal audit planning

Annual audit planning is a multi-criteria decision-making problem faced by internal audit departments of all organizations. Due to the constrained audit resources, the planning process primarily involves the analysis and evaluation of complex factors for selecting auditable units that maximize the full potential of internal audit. Previous research on internal audit planning only focused on the goal of risk minimization and applied ranking methods to prioritize alternatives. In order to enable internal audit activities to add more value to the organization, the integrated risk-based internal audit planning is proposed to assist audit department in achieving multiple objectives in addition to risk management. Meanwhile, a multi-stage framework is proposed to support the development of such value-added internal audit plan. The new framework integrates the risk assessment of auditable units with the selection of audit activities and resource allocation through a combined analytic hierarchy process (AHP), fuzzy comprehensive evaluation (FCE) and weighted multi-choice goal programming (WMCGP) approach. The model considers both qualitative and quantitative decision criteria. A real-life case study of the development of an integrated risk-based annual audit plan is presented, and sensitivity analysis is performed to illustrate the validity of the proposed approach. The results indicate that the proposed framework is a useful tool for internal audit planning and the implications of the study can be extended to various selection and allocation problems.

Appraisal of groundwater pollution risk by combining the fuzzy AHP and DRASTIC method in the Burdur Saline Lake Basin, SW Turkey

To ensure sustainable groundwater management, water resources must be protected in terms of quantity and quality. In this context, it is important to reveal the potential of existing groundwater resources to be affected by environmental and/or geogenic pollutants. In the present study, groundwater vulnerability assessment was performed using DRASTIC model by fuzzy AHP and GIS integration for Burdur Saline Lake basin, SW Turkey. In addition, validation and sensitivity analyses were performed in the study. Weight and rating values assigned for DRASTIC parameters and sub-parameters were determined by fuzzy AHP method, and these values were used in GIS analyses. In the validation analysis of the obtained groundwater vulnerability map, NO₃ ion was considered since the agricultural activities are intense in the study area. In addition, sensitivity analyses were performed to determine the most effective parameter. According to the obtained results, 26.43% of the study area was determined as the highly vulnerable areas, while 11.44 and 62.13% were moderate vulnerable and low vulnerable, respectively. Impact of the vadose zone, depth to water table, and net recharge parameters were determined as more effective than other parameters. The nitrate concentrations of the groundwater in the region confirm the vulnerability map obtained by the study. Therefore, it is recommended to take realistic and urgent protection measures aimed at sustainable use of groundwater in highly vulnerable areas.

A new method for subsea tunnel site selection based on environmental bearing capacity

Engineering site selection is an essential and systematic work in the early engineering construction stage. At present, the subsea tunnel site selection mainly depends on manual experience. There is still a lack of subsea tunnel site selection systems based on environmental impact. This study develops a comprehensive site selection evaluation system based on the analytic hierarchy process (AHP) and fuzzy evaluation method for the subsea tunnel site selection. It is a multi-indicator mathematical model evaluation system. On this basis, the ecological site selection method of the subsea tunnel is further studied, an indicator system for evaluating the environmental carrying capacity of the island is established, and the site selection results of the subsea tunnel based on the environmental indicators are obtained. We compared the site selection results of the two methods. The results show that the conventional method and the ecological site selection method based on environmental indicators can well carry out the site selection of subsea tunnels. The two methods take into account both the overall and local optimum of the subsea tunnel route and organically combine the overall and local objectives. This way provides a reference for the design and construction of the subsea tunnel in the future and points out the direction for the site selection of other large-scale projects with significant environmental impact.

Identification of suitable zones and sites for rainwater harvesting using GIS and multicriteria decision analysis

Identifying suitable zones for surface water storage and groundwater recharge is needed to enhance irrigation water availability. This study was undertaken to map rainwater harvesting (RWH) potential zones using geospatial tools and analytic hierarchy process (AHP). The suitable locations for RWH were also mapped using the Boolean logic concept. The surface runoff is a vital factor to demarcate the appropriate zones for RWH. The curve number approach was used to estimate the surface runoff potential. The runoff coefficient (RC) map was generated based on rainfall and surface runoff depth. Weights have been allocated to selected themes of RC, drainage density, and slope. The themes were integrated using geographic information system (GIS) and AHP to demarcate the suitable zones for RWH. The derived RWH potential map was categorized into zones like "very good," "good," "moderate," "poor," and "very poor" with an aerial extent of 14.3%, 24.7%, 28.3%, 20.2%, and 12.6%, respectively. The area suitable for farm ponds was found to be about 9% (408 km²), 13% (329 km²), and 4% (244 km²) in Mirzapur, Chandauli, and Sonbhadra districts, respectively. Furthermore, 22, 15, and 21 locations were found suitable for check dams in Mirzapur, Chandauli, and Sonbhadra districts, respectively. At a large scale, effective planning of water management strategies based on multicriteria decision analysis and GIS offers increased availability of surface and groundwater resources and may help for enhancing the agricultural land use options. The higher resolution maps may be further utilized to plan RWH strategies at village level.

Agricultural water allocation with climate change based on gray wolf optimization in a semi-arid region of China

Background

We quantified and evaluated the allocation of soil and water resources in the Aksu River Basin to measure the consequences of climate change on an agricultural irrigation system.

Methods

We first simulated future climate scenarios in the Aksu River Basin by using a statistical downscaling model (SDSM). We then formulated the optimal allocation scheme of agricultural water as a multiobjective optimization problem and obtained the Pareto optimal solution using the multi-objective grey wolf optimizer (MOGWO). Finally, optimal allocations of water and land resources in the basin at different times were obtained using an analytic hierarchy process (AHP).

Results

(1) The SDSM is able to simulate future climate change scenarios in the Aksu River Basin. Evapotranspiration (ET₀) will increase significantly with variation as will the amount of available water albeit slightly. (2) To alleviate water pressure, the area of cropland should be reduced by 127.5 km² under RCP4.5 and 377.2 km² under RCP8.5 scenarios. (3) To be sustainable, the allocation ratio of forest land and water body should increase to 39% of the total water resource in the Aksu River Basin by 2050.

Criminal law regulation of cyber fraud crimes-from the perspective of citizens' personal information protection in the era of edge computing

Currently, cloud computing provides users all over the globe with Information and Communication Technology facilities that are utility-oriented. This technology is trying to drive the development of data center design by designing and building them as networks of cloud machines, enabling users to access and run the application from any part of the globe. Cloud computing provides considerable benefits to organizations by providing rapid and adaptable ICT software and hardware systems, allowing them to concentrate on creating innovative business values for the facilities they provide. The right to privacy of big data has acquired new definitions with the continued advancement of cloud computing, and the techniques available to protect citizens' personal information under administrative law have managed to grow in a multitude. Because of the foregoing, internet fraud is a new type of crime that has emerged over time and is based on network technology. This paper analyzed and studied China's internet fraud governance capabilities, and made a comprehensive evaluation of them using cloud computing technology and the Analytic Hierarchy Process (AHP). This paper discussed personal information security and the improvement of criminal responsibility from the perspective of citizens' information security and designed and analyzed cases. In addition, this paper also analyzed and studied the ability of network fraud governance in the era of cloud computing. It also carried out a comprehensive evaluation and used the fuzzy comprehensive evaluation method to carry out the evaluation. A questionnaire survey was used to survey 100 residents in district X of city Z and district Y of the suburban area. Among the 100 people, almost all of them received scam calls or text messages, accounting for 99%, of which 8 were scammed. Among the people, more than 59.00% of the people expressed dissatisfaction with the government's Internet fraud satisfaction survey. Therefore, in the process of combating Internet fraud, the government still needs to step up its efforts.

Priority setting in cardiovascular research in Iran using standard indigenous methods

Background

Determining cardiovascular disease (CVD) research priorities is essential given the high burden of these diseases, limited financial resources, and competing priorities. This study aimed to determine the research priorities in CVD field in Iran using standard indigenous methods.

Materials and Methods

An extensive search was done in relevant international and national studies. Then, an indigenous standard multistage approach based on multicriteria decision analysis steps was adapted to local situation and implemented. This process included forming a working group of experts in priority setting methodology, identifying the context and prioritization framework, discussing the methodology with the National Network of CVD Research (NCVDR) members who ultimately determined the priority research topics, weighted topics criteria, ranked topics, and reviewed all determined research priorities for final report.

Results

Thirteen cardiovascular research priorities were determined by the NCVDR members. The first five priorities based on their scores include studies in hypertension, prevention and control of ischemic heart disease (IHD) and its risk factors, burden of IHD, Registration of CVDs, and COVID-19 and CVDs.

Conclusion

Cardiovascular research priorities were determined using a standard indigenous approach by national experts who are the NCVDR members. These priorities can be used by researchers and health decision makers.

Investigation of the pharmaceutical warehouse locations under COVID-19-A case study for Duzce, Turkey

Pharmaceutical warehouses are among the centers that play a critical role in the delivery of medicines from the producers to the consumers. Especially with the new drugs and vaccines added during the pandemic period to the supply chain, the importance of the regions they are located in has increased critically. Since the selection of pharmaceutical warehouse location is a strategic decision, it should be handled in detail and a comprehensive analysis should be made for the location selection process. Considering all these, in this study, a real-case application by taking the problem of selecting the best location for a pharmaceutical warehouse is carried out for a city that can be seen as critical in drug distribution in Turkey. For this aim, two effective multi-criteria decision-making (MCDM) methodologies, namely Analytic Hierarchy Process (AHP) and Evaluation based on Distance from Average Solution (EDAS), are integrated under spherical fuzzy environment to reflect fuzziness and indeterminacy better in the decision-making process and the pharmaceutical warehouse location selection problem is discussed by the proposed fuzzy integrated methodology for the first time. Finally, the best region is found for the pharmaceutical warehouse and the results are discussed under the determined criteria. A detailed robustness analysis is also conducted to measure the validity, sensibility and effectiveness of the proposed methodology. With this study, it can be claimed that literature has initiated to be revealed for the pharmaceutical warehouse location problem and a guide has been put forward for those who are willing to study this area.

Applying the AHP to Conflict Resolution: A Russia-NATO Case Study

In this paper, we apply the Analytic Hierarchy Process approach to conflict resolution in the context of the Russia-Ukraine conflict. We build models that illustrate the evaluation criteria, strategic and sub-criteria, and concessions for each party in this negotiation. Ratings are used to evaluate the degree to which concessions contribute or take away from successful resolution of the conflict. Afterwards, gain ratios are built to determine the benefit-cost scores so that concessions may be traded that result in equitable solutions. The approach presented here demonstrates for the first time why all concessions that parties to a conflict may offer might not trade all at once. A Max-Min optimization approach is used to maximize the gain to both parties of the conflict while minimizing the disparity in gain between the two.

Sustainable development index of shale gas exploitation in China, the UK, and the US

While shale gas could complement the world's natural gas supply, its environmental tradeoffs and sustainability potential should be cautiously assessed before using it to satisfy future energy needs. Shale gas development in China is still in its infancy but has been progressing by the Central Government at a fast pace nowadays. Advanced experience from North America would greatly benefit sustainable design and decision-making for energy development in China. However, the lack of consistency concerning internal and external parameters among previous investigations does not allow an integrated impact comparison among shale gas-rich countries. Herein, we applied a meta-analysis to harmonize environmental tradeoff data through a comprehensive literature review. Greenhouse gas emission, water consumption, and energy demand were selected as environmental tradeoff indicators during shale gas production. Data harmonization suggested that environmental tradeoffs ranged from 5.6 to 37.4 g CO₂-eq, 11.0-119.7 mL water, and 0.027-0.127 MJ energy to produce 1 MJ shale gas worldwide. Furthermore, sustainable development indexes (SDIs) for shale gas exploitation in China were analyzed and compared to the United States and the United Kingdom by considering environment, economy, and social demand through an analytic hierarchy process. The United States and China elicit higher SDIs than the United Kingdom, indicating higher feasibility for shale gas exploitation. Although China has relatively low scores in the environmental aspect, large reservoirs and high future market demand make Chinese shale gas favorable in the social demand aspect. Region-specific SDI characteristics identified among representative countries could improve the sustainability potential of regional development and global energy supply.

Integrating the impact of large-scale hydraulic engineering with a sustainable groundwater development strategy: A case study of Zhengzhou City, China

With the rapid growth of China's economy, the increase in water demand has threatened the sustainable development of groundwater. Construction of the South-to-North Water Diversion Project alleviated this problem. Zhengzhou, with a large population and high-intensity energy consumption, is a water-receiving city of the South-to-North Water Diversion Central Line Project (CLP). A series of ecological risks caused by the excessive exploitation of groundwater have been exposed. It is urgent to strengthen the assessment and management of groundwater to ensure sustainable development. In this study, the multi-criteria decision analysis (MCDA) underpinned the assessment of the sustainable groundwater development (ASGD) framework. Eight assessment factors were established based on the resource supply function (RSF) and eco-environment stability function (ESF). The novelty of this study lies in the integration of ASGD results with the impact of the CLP on the evolution of groundwater levels in Zhengzhou. Thus, more comprehensive and scientific management suggestions for groundwater development in Zhengzhou were obtained. GIS technology was integrated with the ASGD framework to identify five visualized areas: centralized groundwater supply area (8.61%), decentralized groundwater supply area (27.91%), vulnerable eco-environment area (14.34%), recharge protection area (45.67%), and unsuitable exploitation area (3.47%). The CLP changed the groundwater evolution pattern in Zhengzhou. The results showed that the operation of the CLP effectively slowed the decline in groundwater levels, thus confirming that the CLP has a positive impact on the rational utilization of groundwater. The disuse of two groundwater sources (G1 and G9) were able to enhance sustainable groundwater development. Meanwhile, five groundwater sources in the plain area proved unsuitable. Overall, this study provides a scientific basis for groundwater management in Zhengzhou City, while generating new ideas for sustainable groundwater development in cities affected by large-scale hydraulic projects worldwide.