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Azodicarbonamide (ADC) based airbag gas generants with various potential oxidizers, including (1) C2H4O2N4/KNO3 (2) C2H4O2N4/NaNO3 (3) C2H4O2N4/Sr(NO3)2 (4) C2H4O2N4/Ba(NO3)2 (5) C2H4O2N4/KIO4 and (6) C2H4O2N4/NaIO4 were thoroughly tested to identify the best mixture for a real-time ballistic application. The evaluation of the gas generant mixtures is carried out based on the performance properties such as quantity of oxidizer decomposed (in g) to give 1 g of O2, residual mass % of the mixture, density of the oxidizer, oxygen balance percentage for the oxidizer, adiabatic flame temperature, onset temperature, activation energy, pre-exponential factor, critical ignition temperature, change in enthalpy, change in entropy, impact sensitivity and friction sensitivity of the gas generant mixtures. Using the TOPSIS methodology, a systematic approach was developed for the first time to determine the best suitable airbag gas generant for real-time ballistic application by taking into account all of these properties. TOPSIS findings revealed that the preferred order of the airbag gas generant mixture is C2H4O2N4/KIO4 > C2H4O2N4/NaIO4 > C2H4O2N4/KNO3 > C2H4O2N4/NaNO3 > C2H4O2N4/Sr(NO3)2 > C2H4O2N4/Ba(NO3)2. A similar methodology can also be used to discover the best fuel/oxidizer mixture for any other composition. [ABSTRACT FROM AUTHOR]

Understanding the characteristics of extreme rainfall is vital for planning effective adaptation and mitigation measures. Thus, this study aims to evaluate the performances of 16 general circulation models (GCMs) of the coupled model intercomparison project (8 CMIP5 and 8 CMIP6) in reproducing observed extreme rainfall indices (ERFIs) and monthly rainfall in the Upper Blue Nile (UBN) basin of Ethiopia (1981–2005). The observed ERFIs were computed based on rainfall estimates of the random forest merging (RF-MERGE) algorithm, which combines ground-based rainfall with three gridded rainfall products (GRFPs). The GCMs were evaluated using statistical performance measures such as the Pearson correlation coefficient (R), root mean square error (RMSE), and percent bias (PBIAS). Using the Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS), the GCMs were ranked from least skilled to most skilled. Accordingly, MIROC5 of the CMIP5 and MPI-ESM1-2-LR of the CMIP6 models were found to be the most suitable models. Furthermore, the top-ranked models were selected and bias corrected using quantile mapping (QM), and their ensembles (CMIP5-ensemble and CMIP6-ensemble) were used for projecting future extremes under representative concentration pathways (RCP4.5 and RCP8.5) and shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5), respectively, for the periods 2031–2055 and 2056–2080. Most of the ERFIs exhibited high variability and inconsistent trends for both the observations and future periods. The findings of this study provide valuable insights the the impacts of climate change on ERFIs, and the developed framework can serves as a useful reference for future research. [ABSTRACT FROM AUTHOR]

Crushing behavior analysis and energy absorption optimization are crucial for lightweight structures in automotive applications. The present paper aims to investigate the crushing behavior of thin-walled aluminum/CFRP hybrid tubes under axial loading using an explicit finite element (FE) simulation. The damage constitutive models of aluminum and CFRP are implemented by coding the user-defined subroutine VUMAT in ABAQUS/Explicit, which includes the damage initiation and evolution laws and element deletion scheme. Parametric studies are conducted to assess the effects of radius and aluminum layer thickness on the crushing performance of hybrid tubes. Additionally, a multi-objective optimization is performed on the Isight platform using a non-dominant sorting genetic algorithm (NSGA-II) and technique for order preference by similarity to ideal solution (TOPSIS) with entropy weight method. The optimization aims to maximize crashworthiness and increase energy absorption capacity, enabling designers to select an optimum size ratio. [ABSTRACT FROM AUTHOR]

The lithography process in semiconductor dynamic random-access memory (DRAM) fabrication plants (fabs) is usually a major bottleneck, and reticle scheduling is complicated by process-specific constraints such as diversity of the product mix and rapidly changing deadlines. This study proposes a three-phase scheduling framework to solve the multi-objective reticle scheduling problem, reducing capacity loss, maintaining line balance and meeting customer demand. The genetic algorithm (GA) and the technique for order preference by similarity to ideal solution (TOPSIS) are used to optimize the scheduling with a trade-off among the multiple objectives. This study tests the proposed framework based on a real semiconductor DRAM (fab) in Taiwan, which has two unrelated parallel machines in its lithography process. The study finds that the proposed framework results in better scheduling reports, reduced computation times and improvements in the overall performance of lithography equipment. [ABSTRACT FROM AUTHOR]

Aluminum parts are used in the aviation industry because of the need for light. However, in addition to lightness, critical parts that must have high strength properties have also been developed. The corrosion resistance, resistance to high temperatures, and workability were investigated in this case. It becomes difficult to choose among many aluminum materials that can be alternatives to each other when these features are included. The developed approach, which considers many of the features listed above and ultimately recommends to the user the most suitable aluminum material for the relevant critical part, will be used in overcoming the difficulties in this process. A material selection model is proposed in this paper for this purpose, and the decision-making model is demonstrated with examples from the aviation industry. Therefore, the developed model, which will enable the selection of the most suitable materials among alternative materials, especially for critical parts in the aviation industry, will guide professionals working in this field. For this purpose, the fuzzy TOPSIS method is used in the study, and suitable alternatives are determined. Finally, a robustness analysis is proposed to determine the most suitable aluminum material for highly uncertain situations. We apply a stability evaluation study based on process control theory in the robustness analysis. [ABSTRACT FROM AUTHOR]

In the complex field of evaluating leadership styles, the integration and aggregation of data has become crucial. This article delves into the use of OWA-TOPSIS, a hybrid methodology that combines the Ordered Weighted Averages (OWA) Operator and the Method for Ordering Preferences by Similarity with the Ideal Solution (TOPSIS), to achieve an accurate and holistic assessment of leadership executive. By unifying diverse data and aggregating information from multiple sources, you achieve a more complete and nuanced view of management capabilities and styles. This approach not only improves the objectivity of the analysis, but also provides a powerful tool for decision-making in complex corporate environments, where leadership skills are critical to organizational success. The OWA-TOPSIS methodology stands out for its ability to handle ambiguous and subjective information, transforming it into a quantifiable and easily interpretable result. By applying this method, you can discern more clearly which leadership styles are most effective in different contexts and specific situations. Furthermore, the flexibility of this technique allows it to be adapted to various industries and sectors, making OWA-TOPSIS a versatile solution for leadership analysis. The research detailed in this article offers an innovative and insightful perspective on how to optimize management evaluation, thereby providing essential guidance for improving organizational effectiveness through informed leadership strategically aligned with corporate objectives. [ABSTRACT FROM AUTHOR]

In response to the problem of insufficient attention to the risk degree of potential inundation areas in the siting of shelters for dam failure floods, a new model for evaluating the sites of shelters was proposed. On the basis of establishing the risk evaluation index system, the improved catastrophe theory evaluation method was used to evaluate the risk degree and classify the risk level of the potential inundation areas. The distance between shelters and high-risk level areas was taken as the site selection evaluation index, and the disaster risk, location scale, emergency support of shelters were considered. The weights were determined by AHP method, and the TOPSIS method was applied to evaluate the sites of shelters. Finally, 13 potential inundation areas and 10 alternative shelters downstream of Luhun Reservoir in China were used as examples for validation. The results showed that among the areas with high risk levels, Baiyuan Township was a Class I hazardous area, and Pengpo Township, Minggao Township, Chengguan Street, and Longmen Township were Class II hazardous areas. The better evaluated shelters could meet the requirements of paying attention to areas with high risk degree. [ABSTRACT FROM AUTHOR]

This study presents an innovative approach to evaluate the implementation effects of the Rural Revitalization Strategy R2S, utilising the robust capabilities of the wavelet analysis algorithm. The proposed methodology integrates the strength of wavelet transform, an advanced mathematical tool for signal processing, with the entropy weighting method and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) model. This integration creates a comprehensive framework for assessing the multifaceted impacts of rural revitalisation initiatives. The wavelet analysis algorithm is the cornerstone of this approach, enabling the decomposition of complex rural development data into different frequency components, thus facilitating a more nuanced analysis. The entropy weighting method contributes by objectively determining the weights of various evaluation indicators, ensuring that the most relevant factors in rural revitalisation are emphasised in the assessment process. The TOPSIS model complements this by clearly ranking the analysed strategies based on their proximity to an ideal solution, thereby enabling decision-makers to identify the most effective strategies for rural development. Together, these techniques form a powerful tool for evaluating the effectiveness of rural revitalisation strategies, offering critical insights for policy formulation and implementation in rural areas. This study's methodology not only enhances the accuracy of evaluation but also provides a replicable model for similar assessments in other contexts, contributing significantly to rural development and policy analysis. [ABSTRACT FROM AUTHOR]

It is important to understand the relationship between urbanization and geological disaster systems to develop sustainable management strategies for many cities in the world that are located in geologically active zones. This study explored the coupling coordination degree of urbanization and geological disasters in 11 cities in Zhejiang province, China, during 2010–2020. Based on the annual demographics and socioeconomic and geological disasters data from 2010 to 2020, we analyzed the spatiotemporal changes of the coupling coordination degree between urbanization and geological disaster systems for the 11 cities in Zhejiang province during the period 2010–2020 using the analytic hierarchy process (AHP) combined entropy-weight method to determine the weights of indexes, which were used as input into the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method and coupling coordination degree model. The results indicated that the coupling coordination degree of most cities in Zhejiang province was positively correlated with time, reaching a peak in 2017, and the gap in coupling coordination was narrowing. From 2010 to 2020, the development stage of coupling coordination in Zhejiang province was mainly barely coordinated development. Moreover, the coupling coordination degree of North Zhejiang was the best, that of Central Zhejiang was second, and that of Southwest Zhejiang was the worst in terms of spatial pattern. [ABSTRACT FROM AUTHOR]

In the current study, the high-volume replacement of river sand (20%, 30%, 40%, 50%, 60%, 80%, and 100%) by pond ash in cement mortar was considered using a 1∶3 volumetric mix proportion to evaluate the engineering properties, sustainability aspects, and cost of mortar mixes. The compressive strength, tensile bond strength, and adhesive strength increased by 30%, 21%, and 24%, respectively, at 30% replacement and were in line up to 60% replacement as compared with the reference mix. However, the drying shrinkage was observed to increase with volume replacement of river sand. The life-cycle assessment of mixes containing pond ash showed reductions in the environmental impacts. Four different scenarios were considered on the basis of the preference advantage of the indicators. Considering the engineering properties, sustainability aspects, and cost as the primary indicators, the gray clustering analysis showed that the mix with 60% volume replacement exhibited the best performance among the mixes under Scenario S-1, while TOPSIS and VIKOR showed that the mix with 50% volume replacement exhibited best performance under Scenario S-1. Overall, the comparison of all scenarios showed that the mix of 60% pond ash had the best performance followed by the mix with 50% pond ash, irrespective of the multicriteria decision-making techniques and preference advantages. [ABSTRACT FROM AUTHOR]

The advent of the Internet has led to the emergence of multi-source heterogeneous knowledge graphs, which have become a crucial means of storing and disseminating knowledge. Node importance estimation is a technique that is employed extensively in a number of fields, including recommender systems, intelligent search and resource allocation. This study introduces a Multi-perspective attention mechanism Fusion Algorithm for the mapping of multi-perspective features of knowledge graphs to Node Importance Estimation (MFA-NIE). First, structural embedding features, relational predicate features, and attribute features (both textual and quantitative) are established for the nodes. Subsequently, an enhanced attention mechanism is employed to extract, compress, and fuse these features. The fused hidden layer vector is employed in the design of a key-based attention mechanism, which enables the propagation of messages from neighboring nodes to the source node. This process results in the iterative updating of the source node’s hidden features. Finally, TOPSIS centrality, based on the topology of the source node, is employed to dynamically adjust the mapping between the fused features and node importance. Experiments were conducted on real-world, large-scale, multi-source, heterogeneous knowledge graphs, comparing the MFA-NIE algorithm with traditional and advanced baseline algorithms, including PR, PPR, GENI, RGTN, CLINE, MCRL, and others. The results demonstrate that the MFA-NIE algorithm significantly improves effectiveness and accuracy, showcasing its superiority, versatility, and practical application value. [ABSTRACT FROM AUTHOR]

The concept of the Dual-hesitant fermatean fuzzy set (DHFFS) represents a significant advancement in practical implementation, combining Fermatean fuzzy sets and Dual-hesitant sets. This new structure uses membership and non-membership hesitancy and is more adaptable for arriving at values in a domain. Since it has the capability to treat multiple fuzzy sets over the degrees of membership and non-membership, the DHFFS greatly improves the flexibility of approaches to tackle multiple-criteria decision-making (MCDM) problems. By applying generalized T‐norm (T) and T‐conorm (T*) operation, improved union and intersection formulas are derived. The proposed work adopts Hamacher operations such as Hamacher T-conorm (HT*) and Hamacher T-norm (HT) that are more efficient than conventional techniques. New aggregation operators such as Hamacher weighted arithmetic, geometric, power arithmetic, and power geometric are developed for DHFFS. These operators are most beneficial when dealing with a MCDM issue. A case study is used to demonstrate the approachs' accuracy and effectiveness in real-world decision-making. The comparative and sensitivity analysis results show that these operators are more effective than traditional methods. These results show that the proposed methods are efficient and can be applied in large-scale decision-making processes, strengthening the solutions' practical implications. [ABSTRACT FROM AUTHOR]

Object: Promoting the accessibility and equity of healthcare services, as well as enhancing service capacity, are crucial for building a sound healthcare system. Particularly in the past two years of the normalized COVID-19 situation, this issue has garnered widespread attention in the academic community. This study aims to investigate and analyze the characteristics and trends of the spatial-temporal evolution of healthcare service supply levels in China. It also seeks to explore the influencing factors and pathways for development, with the goal of optimizing the allocation of healthcare resources. Methods: This article uses the entropy weight TOPSIS method combined with Dagum Gini coefficient and Kernel density to evaluate the supply level of healthcare services in 31 provinces and cities in China from 2012 to 2020, and explores its development and spatial pattern characteristics. Then, through Moran index, panel regression model and spatial econometric testing, the spatial correlation problem and its influencing factors are further analyzed, and targeted policy recommendations are proposed based on it, laying the foundation for further promoting the balanced development of healthcare service supply capacity. Results: (1) Healthcare services supply levels in various provinces and cities in China have significantly increased, with a shift in spatial distribution from 'higher in the east and lower in the west' to 'convergence between east and west, with lower levels in the central regions.' (2) Relative differences among regions are narrowing annually, primarily due to interactions between the four regions rather than within each region, with expanding impact of overlapping regions. (3) Absolute differences among regions are also decreasing, moving towards uniformity with a contraction of extension and a restraint on the trend towards multipolarization. (4) Spatial correlation between adjacent regions is weakening, eventually becoming non-significant, with fading spatial effects. (5) The correlation between local economic development, population factors, institutional arrangements, and the current state of supply is significant, and the research design and conclusions remain robust even after thorough consideration of spatial effects. The study explores the development pathways based on the objective existence of regional development and the controllable government actions. Conclusion: The overall level of healthcare service supply in China has improved, but regional differences still exist. The objective level of regional development and the subjective behavior of local governments have a significant impact on the supply of healthcare services. Therefore, it is recommended that each region adapt to local conditions, identify its own strengths and weaknesses, coordinate resource supply and demand, consider the impact of key factors, and optimize the allocation of healthcare development resources. [ABSTRACT FROM AUTHOR]

ABSTRACT This study aims to evaluate homogenization techniques and conditions for producing stable, small droplet‐size water‐in‐oil (W/O) emulsions intended for incorporation into casein hydrolysate–loaded double emulsions. Three commonly used homogenization methods; rotor–stator, ultrasonic, and high‐pressure homogenization were individually optimized utilizing response surface methodology. Instances of over‐processing were observed, particularly with the rotor–stator and ultrasonic homogenizers under specific conditions. Nevertheless, optimal conditions were identified for each technique: 530 s at 17,800 rpm agitation speed for the rotor–stator homogenizer, 139 s at 39% amplitude for the ultrasonic homogenizer, and 520 s at 1475 bar for the high‐pressure homogenizer. Subsequently, the W/O emulsions produced under optimal conditions and their respective W1/O/W2 double emulsions were compared. The rotor–stator and high‐pressure homogenized W/O emulsions exhibited comparable narrow droplet‐size distributions, as indicated by similar Span values. However, high‐pressure homogenization failed to sufficiently minimize droplet size. Ultrasonic homogenization resulted in droplets at the 1‐μm scale but yielded more polydisperse droplet‐size distribution. According to TOPSIS analysis, an emulsion with a viscosity of 93.1 cP (centiPoise), a stability index of 93.8%, a D(90) of 0.67 μm (0th day), and a D(90) of 0.75 μm (30th day) produced using a rotor–stator was selected. Additionally, double emulsions containing primary emulsions prepared with the rotor–stator method demonstrated higher viscosity, narrower droplet‐size distribution, and lower creaming compared to other samples. This investigation sheds light on the influence of homogenization techniques on emulsion properties, providing valuable insights for optimizing double emulsion formulations. [ABSTRACT FROM AUTHOR]

Urban energy systems planning presents significant challenges, requiring the integration of multiple objectives such as economic feasibility, technical reliability, and environmental sustainability. Although previous studies have focused on optimizing renewable energy systems, many lack comprehensive decision frameworks that address the complex trade-offs between these objectives in urban settings. Addressing these challenges, this study introduces a novel Multi-Criteria Decision Analysis (MCDA) framework tailored for the evaluation and prioritization of energy scenarios in urban contexts, with a specific application to the city of Bozen-Bolzano. The proposed framework integrates various performance indicators to provide a comprehensive assessment tool, enabling urban planners to make informed decisions that balance different strategic priorities. At the core of this framework is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is employed to systematically rank energy scenarios based on their proximity to an ideal solution. This method allows for a clear, quantifiable comparison of diverse energy strategies, facilitating the identification of scenarios that best align with the city's overall objectives. The flexibility of the MCDA framework, particularly through the adjustable criteria weights in TOPSIS, allows it to accommodate the shifting priorities of urban planners, whether they emphasize economic, environmental, or technical outcomes. The study's findings underscore the importance of a holistic approach to energy planning, where trade-offs are inevitable but can be managed effectively through a structured decision-making process. Finally, the study addresses key gaps in the literature by providing a flexible and adaptable tool that can be replicated in different urban contexts to support the transition toward 100% renewable energy systems. [ABSTRACT FROM AUTHOR]

Urban green infrastructure plays a significant role in sustainable development and requires proper land management during planning. This study develops a valuation model for urban green infrastructure in land management, focusing on Zagreb's 17 city districts. The fuzzy AHP method was used to calculate the weighting coefficients for a suitable set of criteria, and the TOPSIS method was used to select the priority city districts for implementing green infrastructure. The research results are relevant to decision makers, who can utilize them to prioritize areas for the development and implementation of green infrastructure. The green infrastructure index calculated in this study can be compared with other spatial and land data for effective spatial planning. [ABSTRACT FROM AUTHOR]

Background/Objectives: In regions of Africa with a high prevalence of malaria, pregnant women in their first or second trimester should be administered intermittent preventive treatment in pregnancy (IPTp). However, infants may contract malaria despite the IPTp therapy that their mothers have received. The objective of the present investigation was to assess the symptoms and various treatments for neonatal malaria. Methods: Entropy weight and TOPSIS were used to achieve the study goal. The TOPSIS multi-attribute decision-making system was used to assess newborn malaria symptoms and select the optimal treatment, even for mothers receiving IPTp medication during pregnancy. The entropy weight approach calculated TOPSIS attribute weights. The present research used UNICEF data for 14 African nations in 2023. Results: The results indicated that neonates whose mothers received IPTp therapy ultimately contracted malaria, with diarrhea being the primary symptom. It is important to note that health providers administer a combination of zinc and oral rehydration solution (ORS) to infants as the most effective treatment for malaria symptoms, thereby abandoning the first-line treatment for malaria, artemisinin-based combination therapy (ACT). Conclusions: The most effective treatment for neonatal malaria is a combination of zinc and ORS, although less than half of children in Africa have access to ORS. Therefore, the findings of this study may encourage African countries to prioritize co-pack therapy in their procurement and supply, healthcare provider training, and expenditures. This therapy will also help alleviate the symptoms of malaria in neonates. [ABSTRACT FROM AUTHOR]

To ensure the successful implementation of the old community renewal project (OCRP), it is essential for the participants to allocate the project risks reasonably. Firstly, this study comprehensively identifies the 20 key risk factors of the OCRP. Secondly, an index system is established from three dimensions to evaluate the risk allocation ability of participants, including a total of nine evaluation indexes. Furthermore, a risk-sharing model based on TOPSIS method and bargaining game model is proposed to determine the optimal risk bearer and risk-taking ratio between the government and the private sector in OCRP. Finally, an OCRP in Chongqing is taken as a case study to verify the applicability of the developed model. The results indicate that in OCRP under PPP mode, the government need to independently bear 7 risks related to politics, law, policy, while the private sector needs to independently bear 8 risks mainly from project financing, design, construction, operation, and maintenance stages. In addition, the risk-taking ratios of 5 risks that require both parties to share are divided. The research findings provide references for ensuring the smooth implementation of urban renewal and sustainable development. [ABSTRACT FROM AUTHOR]

The performance evaluation of local self-government entities is very difficult, as their primary goal is not to make a profit, but to provide services to their residents that will contribute to an increase in their quality of life. In this context, it is necessary to evaluate their activity from the point of view of several available criteria, for which it is possible to find relevant and recognized sources. The presented research works with five criteria, identified by the Institute for Economic and Social Reforms, and aims to quantify the agreement of the results of the assessment of the financial health of territorial self-government entities in 2020 using the TOPSIS technique with a gradually decreasing number of criteria. For this purpose, a total of 26 combinations of criteria are created, with the number of 5, 4, 3 and 2 used criteria, the importance of which is determined based on their absolute variability using the standard deviation method. The results obtained in this way are interpreted using a wide range of mathematical and statistical methods including the Kolmogorov-Smirnov test, Levene test, Jaccard index and others. As a result, the multi-criteria evaluation of territorial self-government subjects (in our case, district cities) proved to be highly applicable. However, the result itself is largely determined by the structure and number of entry criteria. Based on the performed analyses, we can see that significant differences result from their reduction. Each such reduction has an impact on the overall results, but it is possible to find combinations that defy this conclusion. [ABSTRACT FROM AUTHOR]

In the traditional decision-making process for product form design, designers and experts often prioritize schemes based on their own knowledge and experience. This approach can lead to an oversight of user preferences, ultimately affecting decision outcomes. In contrast, crowd-intelligence-driven, multi-attribute decision-making for product form design in the cloud environment builds upon traditional approaches by leveraging the vast and diverse expertise of individuals on cloud platforms, engaging participants from various fields and roles in the decision-making process to enhance comprehensiveness and accuracy. To address the issue of a single decision-maker and limited user participation in the decision-making process for product form design schemes in the cloud environment, a multi-attribute decision-making method integrating expert knowledge and user preferences is proposed. This method aims to select a product form design scheme that optimally balances expert and user satisfaction. Initially, the Pythagorean Hesitant Fuzzy Set (PHFS) is used to quantify qualitative product attributes and to establish a comprehensive multi-attribute evaluation system. In the aspect of expert decision-making, a gray correlation coefficient decision matrix based on expert knowledge is established and the overall score of the base alternative is calculated by the ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method and the Improved Osculating Value method. In terms of user decision-making, weights are determined by calculating the similarity between user evaluation matrices, and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to calculate scores for product form designs based on user preferences. Ultimately, optimal selection is achieved by aggregating the aforementioned expert evaluation values and user preference values. The method's effectiveness and feasibility are confirmed through a case study of coffee machine product form design schemes. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusion Computer‐assisted planning methods have increasingly contributed to preoperative ablation planning; however, these methods cannot automatically obtain the final optimal solution within a short time and are rarely validated in practice, greatly limiting their clinical applicability.We aimed to propose a full‐automatic multi‐stage ablation and needle trajectory planning method for CT‐guided percutaneous liver ablation to attain the final optimal plans under multiple clinical constraints rapidly.Our proposed method integrates the ablation zone planning fulfilling complete tumor coverage and critical structure avoidance while reaching a trade‐off between ablation number and healthy tissue damage, and needle trajectory planning under multiple clinical constraints. Our needle trajectory planning determines feasible skin entry regions based on hard constraints, where the multi‐objective optimization (MOO) considering soft constraints is performed using the Pareto Optimality and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods for the final optimal solution. The performance of our proposed method was evaluated on 30 tumors of various characteristics from 23 patients and clinically validated in five clinical cases.Our proposed method achieved 99.8% treatment zone coverage and 40.5% ablation efficiency without involving critical structures, and completely satisfied multiple clinical constraints in all needle trajectory planning results. The average planning time was 23.6 s for tumors of different sizes. All the plans were considered clinically acceptable by the doctors’ evaluation. Our method achieved complete tumor coverage without complications in clinical case validation.Our proposed planning method can generate a final optimal plan satisfying multiple clinical constraints within a short time, potentially facilitating preoperative planning for hepatic tumor ablation. [ABSTRACT FROM AUTHOR]

The security of agricultural water resources is crucial for food security, ecological environment and the economic development of rural areas. In order to promote efficient utilization and sustainable development of regional agricultural water resources, taking into account the impact of uncertainties and complexities, this paper adopted methods such as ordinal relation analysis, entropy weight method, and TOP- SIS (Technique for Order Preference by Similarity to Ideal Solution) to select 11 typical indicators across three subsystems of water resources, ecology and agricultural water use to build an evaluation index system. This system was used to assess the agricultural water resources security status in 14 prefecture-level cities within the Yellow River water diversion area of Henan Province in 2022. The results show that among the 14 prefecture-level cities, except Kaifeng is the "unsafe" level and Xinxiang, Hebi, and Puyang are the "generally safe" level, the other 10 cities are the "relatively safe" level, which still has some distance away from the "safe" level. It recommends to implement measures such as improving water quality, increasing available water resources, adjusting crop planting structures, enhancing water resources utilization efficiency, and enforcing the strictest water resources management system to ensure the agricultural water resources security in the Yellow River water diversion area of Henan Province. [ABSTRACT FROM AUTHOR]

Practical Application To address the challenges associated with prolonged traditional hot air drying (HAD) times and significant nutrient loss in cherries, this study employs ultrasound‐assisted hot air drying (USA‐HAD) technology. The study investigates the impacts of various ultrasound (US) frequencies, US powers, and hot air temperatures on the drying kinetics, physicochemical properties, texture attributes, and microstructure of cherries during drying. Cherry physicochemical quality serves as the evaluation criterion, with the entropy‐weighted TOPSIS method used to identify the optimal drying parameters. The findings indicate that USA‐HAD accelerates the drying process, reduces drying time, and enhances drying efficiency. In comparison to natural drying, USA‐HAD significantly preserves polysaccharides, total phenolic content, total flavonoid content, and organic acids in cherries, while boosting antioxidant activity. Concurrently, it reduces color intensity, as well as the hardness, chewiness, and gumminess of dried cherry products. Microstructural observations under different drying methods reveal an increase in surface micropores and relatively intact tissue structure. Under conditions of 55°C, 48 W, and 28 kHz, cherries exhibit superior overall quality based on the TOPSIS relative closeness degree. This study offers practical insights for optimizing post‐harvest processing of cherries.In this rapidly evolving era, the application of combination drying technology is clearly on the rise. The USA‐HAD treated cherries had better nutritional and bioactive than HAD. The conclusions obtained indicate that the USA‐HAD technology has more potential for development. [ABSTRACT FROM AUTHOR]

The present study explores the comprehensive composite material selection methodology of a tennis racket involving coupled Multi-Criteria Decision-Making (MCDM) and numerical analysis. Initially all the possible material alternatives from the composite family were shortlisted using CES Selector 2016. A design space was developed incorporating MCDM technique naming VICKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje), PROMETHEE (Preference Ranking Organisation Method for Enrichment Evaluation) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to rank the most suitable composite material based on critical mechanical properties to identify the most suitable composite materials for applications requiring optimal combinations of rigidity, strength, and structural performance. Using finite element analysis, the structural integrity of each of the materials was evaluated on static and dynamic stress analysis modules of ANSYS. Out of all material alternatives, T300 carbon fiber epoxy was considered as the most suitable for tennis rackets. Further, a comparison between the selected material was also made with conventional materials and were found in good agreement with selected material. [ABSTRACT FROM AUTHOR]

Lean Six Sigma (LSS) implementation still shows a high failure rate. Lack of readiness is one of the causes. Readiness assessment requires special exploration of each sector, including the hotel sector, where there is still no development of an LSS readiness assessment model. This study aims to develop a readiness assessment model for LSS implementation in the hotel sector. Data processing in the readiness assessment model uses the fuzzy logic method, is translated again into linguistic terms using Euclidean distance, and is ranked using the TOPSIS approach. The literature review produced 34 Readiness Factors (RF) that were validated by eight credible hotel practitioners and used as guidelines in conducting LSS readiness assessments in the hotel sector. Case studies were conducted on Hotel A and Hotel B, which showed that Hotel A was “Very Ready” and Hotel B was “Ready” to implement LSS. This research is perhaps the first of its kind in the hotel sector. This research also uses the Delphi method to collect data on the importance level, which may not have been done in collecting data on LSS readiness in any sector. [ABSTRACT FROM AUTHOR]

Exploring the interaction and coupling effects within the population‒land‒water‒industry (PLWI) system is conducive to promoting high-quality regional sustainable development. Taking the lower Yellow River during the period from 2000 to 2020 as a research sample, this study used the entropy weight TOPSIS method, the coupling coordination degree (CCD) model and kernel density estimation to synthetically evaluate the CCD of the PLWI system. The GeoDetector model was applied to explore the factors influencing the CCD of the PLWI system considering the nonlinear relationship. The major results can be summarized as follows: (1) From 2000 to 2020, the comprehensive development index (CDI) of the population, land, water and industry subsystems followed a gradual upward trend in the lower Yellow River, increasing by 0.293, 0.033, 0.111 and 0.369, respectively. However, the CDI of the land subsystem varied greatly between regions. Some cities, such as Jinan, Jining and Binzhou, experienced large declines in the CDI of the land subsystem, from 0.433, 0.534 and 0.572 to 0.358, 0.481 and 0.522, respectively. (2) The CCD of the PLWI system in the lower Yellow River showed an upward trend, increasing from 0.481 to 0.678, and became more concentrated during 2000–2020. Most of the region transitioned from near disorder to primary coordination. (3) Factors such as number of health technicians per 10,000 people, average salary, number of college students per 10,000 people, per capita GDP and per capita education expenditure were critical to the coordinated development of the PLWI system, the explanatory powers were 0.644, 0.639, 0.610, 0.498 and 0.455, respectively. Finally, this study proposed three policy recommendations to improve coupling coordination in the lower Yellow River Basin: Improving population quality, promoting green technology and rational land planning. [ABSTRACT FROM AUTHOR]

In this study, computational fluid dynamic (CFD) simulation of a vertical axis wind turbine (VAWT) geometry based on the Unsteady Reynolds–Averaged Navier–Stokes equations was investigated. In addition, the relationship between the geometric parameters of the VAWT and the two response variables, that is, moment and lift force, was determined using response surface methodology (RSM). Then, the Non‐Dominated Sorting Genetic Algorithm (NSGA‐II) was used to solve the multi‐objective optimization problem. The results obtained from the RSM showed that the lift force of the turbine is more sensitive to the change in the blade chord length, and the output moment of the turbine is more sensitive to the change in the rotor radius. Using the NSGA‐II multi‐objective optimization algorithm and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, it was determined that among the optimal values of the independent variable, the most optimal response occurs in blade chord length = 0.18 m, rotor radius = 0.4 m, blade pitch angle = −3.27° and number of blades = 4. In these optimal values of the independent variables, the values of the dependent variables, which included the turbine's moment and the blades' lift force, were obtained as 9.58 N m and 57.89 N, respectively. [ABSTRACT FROM AUTHOR]

Crawling robots are the focus of intelligent inspection research, and the main feature of this type of robot is the flexibility of in-plane attitude adjustment. The crawling robot HIT_Spibot is a new type of steam generator heat transfer tube inspection robot with a unique mobility capability different from traditional quadrupedal robots. This paper introduces a hierarchical motion planning approach for HIT_Spibot, aiming to achieve efficient and agile maneuverability. The proposed method integrates three distinct planners to handle complex motion tasks: a nonlinear optimization-based base motion planner, a TOPSIS-based base orientation planner, and a Mask-D3QN (MD3QN) algorithm-based gait motion planner. Initially, the robot's base and foot workspace were delineated through envelope analysis, followed by trajectory computation using Larangian methods. Subsequently, the TOPSIS algorithm was employed to establish an evaluation framework conducive to foundational turning planning. Finally, the MD3QN algorithm trained foot-points to facilitate robot movement along predefined paths. Experimental results demonstrated the method's adaptability across diverse tube structures, showcasing robust performance even in environments with random obstacles. Compared to the D3QN algorithm, MD3QN achieved a 100% success rate, enhanced average overall scores by 6.27%, reduced average stride lengths by 39.04%, and attained a stability rate of 58.02%. These results not only validate the effectiveness and practicality of the method but also showcase the significant potential of HIT_Spibot in the field of industrial inspection. [ABSTRACT FROM AUTHOR]

To address the prevailing problems of high water and fertilizer input and low productivity in Isatis tinctoria L. production in the Hexi Corridor in China, the effects of different irrigation amounts and nitrogen application rates on growth characteristics, photosynthetic physiology, root yield, and quality of I. tinctoria plants were studied with the aim of obtaining the optimal irrigation level and nitrogen application rate. From 2021 to 2023, we established a two-factor split-plot experiment in the oasis irrigation area with three irrigation amounts (sufficient water, medium water, and low water are 100%, 85%, and 70% of the typical local irrigation quota) for the main zone; three nitrogen application rates (low nitrogen, 150 kg ha−1, medium nitrogen, 200 kg ha−1, and high nitrogen, 250 kg ha−1) for the secondary zone; and three irrigation amounts without nitrogen as the control to explore the response of these different water and nitrogen management patterns for I. tinctoria in terms of growth characteristics, photosynthetic physiology, root yield, and quality. The results showed the following: (1) When the irrigation amount was increased from 75% to 100% of the local typical irrigation quota and the nitrogen application rate was increased from 150 to 250 kg ha−1, while the plant's height, leaf area index, dry matter accumulation in the stem, leaf, and root, as well as the net photosynthetic rate (Pn), the stomatal conductance (Gs), and the transpiration rate (Tr) of I. tinctoria increased gradually, and the root–shoot ratio decreased. (2) When the irrigation amount increased from 75% to 100% of the local typical irrigation quota, the yield and net proceeds of I. tinctoria increased from 43.12% to 53.43% and 55.07% to 71.61%, respectively. However, when the irrigation quota was 100% of the local typical irrigation quota, and the nitrogen application rate increased from 150 to 200 kg ha−1, the yield of I. tinctoria increased from 21.58% to 23.69%, whereas the increase in nitrogen application rate from 200 to 250 kg ha−1 resulted in a decrease in the yield of I. tinctoria from 10.66% to 18.92%. During the 3-year experiment, the maximum yield of I. tinctoria appeared when treated with sufficient water and medium nitrogen, reaching 9054.68, 8066.79, and 8806.15 kg ha−1, respectively. (3) The effect of different water and nitrogen combination treatments on the root quality of I. tinctoria was significant. Under the same irrigation level, increasing the nitrogen application rate from 150 to 250 kg ha−1 could increase the contents of indigo, indirubin, (R,S)–goitrin, total nucleoside, uridine, and adenosine in the root of I. tinctoria from 3.94% to 9.59%, 1.74% to 12.58%, 5.45% to 18.35%, 5.61% to 11.59%, 7.34% to 11.32%, and 14.98% to 54.40%, respectively, while the root quality of I. tinctoria showed a trend of first increasing and then decreasing under the same nitrogen application level. (4) AHP, the entropy weight method, and the TOPSIS method were used for a comprehensive evaluation of multiple indexes of water–nitrogen coupling planting patterns for I. tinctoria, which resulted in the optimal evaluation of the W3N2 combination. Therefore, the irrigation level was 100% of the local typical irrigation quota, the nitrogen application rate should be appropriately reduced, and controlling the nitrogen application rate at the level of 190.30–218.27 kg ha−1 can improve water–nitrogen productivity yields for I. tinctoria and root quality. The results of this study can provide a theoretical basis and technical support for a more reasonable water and fertilizer management model for the I. tinctoria production industry in the Hexi Corridor in China. [ABSTRACT FROM AUTHOR]

High energy consumption and poor processing quality are common problems in wood sawing. To address these issues, in this article, specific cutting energy and surface roughness were investigated with saw blade speed as control variables. Analysing the effect of parameters on specific cutting energy and surface roughness. The sawing parameters were optimised with the objectives of minimum specific cutting energy and minimum surface roughness. The findings indicate that specific cutting energy and surface roughness reduction with increasing rake angle; specific cutting energy and surface roughness decrease with increasing spindle speed; specific cutting energy decreases and surface roughness increases with increasing feed rate. ANOVA analysis reveals that sawing speed (n) has the most significant impact on specific cutting energy during oak cutting. The optimal solution derived from TOPSIS suggests a specific cutting energy of 2E7 J/m3 and a surface roughness of 1.758 μm. The innovation of this paper is the study of the specific cutting energy and the optimisation of parameters. These findings provide valuable theoretical and practical guidance for enhancing the efficiency and quality of oak processing while minimizing energy consumption. [ABSTRACT FROM AUTHOR]

GDP is a common and essential indicator for evaluating a country's overall economy. However, environmental issues may be overlooked in the pursuit of GDP growth for some countries. It may be beneficial to adopt more sustainable criteria for assessing economic health. In this study, green GDP (GGDP) is discussed using mathematical approaches. Multiple dataset indicators were selected for the evaluation of GGDP and its impact on climate mitigation. The k-means clustering algorithm was utilized to classify 16 countries into three distinct categories for specific analysis. The potential impact of transitioning to GGDP was investigated through changes in a quantitative parameter, the climate impact factor. Ridge regression was applied to predict the impact of switching to GGDP for the three country categories. The consequences of transitioning to GGDP on the quantified improvement of climate indicators were graphically demonstrated over time on a global scale. The entropy weight method (EWM) and TOPSIS were used to obtain the value. Countries in category 2, as divided by k-means clustering, were predicted to show a greater improvement in scores as one of the world's largest carbon emitters, China, which belongs to category 2 countries, plays a significant role in global climate governance. A specific analysis of China was performed after obtaining the EWM-TOPSIS results. Gray relational analysis and Pearson correlation were carried out to analyze the relationships between specific indicators, followed by a prediction of CO2 emissions based on the analyzed critical indicators. [ABSTRACT FROM AUTHOR]

This study investigates the factors influencing C O 2 emissions in Romania from 1990 to 2023 using the Autoregressive Distributed Lag (ARDL) model. Before the ARDL model, we identified a set of six policies that were ranked using Fuzzy Electre, Topsis, DEMATEL, and Vikor. The multi-criteria decision-making (MCDM) methods have highlighted the importance of a circular policy on C O 2 emission reduction, which should be a central focus for policymakers. The results of the ARDL model indicate that, in the long term, renewable energy production reduces C O 2 emissions, showing a negative relationship. Conversely, an increase in patent applications and urbanization contributes to higher C O 2 emissions, reflecting a positive impact. In total, five key factors were analyzed: C O 2 emissions per capita, patent applications, gross domestic product, share of energy production from renewables, and urbanization. Notably, GDP does not significantly explain C O 2 emissions in the long run, suggesting that economic growth alone is not a direct driver of C O 2 emission levels in Romania. This decoupling might result from improvements in energy efficiency, shifts towards less carbon-intensive industries, and the increased adoption of renewable energy sources. Romania has implemented effective environmental regulations and policies that mitigate the impact of economic growth on C O 2 emissions. [ABSTRACT FROM AUTHOR]

Piracy has long plagued the maritime industry, and has led to significant losses of life and goods. The risk of maritime piracy is largely predicted at present based on static analysis. This does not suitably address practical needs because the behavior and activities of maritime pirates are dynamic. Selecting an appropriate strategy for reducing the risk of piracy under a dynamic environment featuring uncertainty thus remains a key challenge. In this study, we propose a two-stage technique for order of preference by similarity to an ideal solution (TOPSIS) model based on the Bayesian network (BN). A data-driven BN is constructed in the first stage of the proposed method to identify the causal relationships influencing the behaviors of pirates. The second stage involves calculating a decision matrix of the strategies by using TOPSIS, where this enhances the strength of risk prediction and dynamic diagnosis by the BN. The main novelty of the proposed model is that it can provide quantitative measurements of strategies for reducing the probability of piracy in a dynamic environment. It provides a decision-making tool for researchers, shipping companies, and national navies to assess the risk of piracy and select effective measures to reduce its likelihood. [ABSTRACT FROM AUTHOR]

This study integrated multiple objective decision-making approaches including data envelopment analysis (DEA), rough set theory and TOPSIS method for exploring the competitiveness of pharmaceutical multinational enterprises. Firstly, this study applied an advanced two-stage network DEA to measure the R&D efficiency and business performance of pharmaceutical multinational enterprises (PMNEs) listed in the Forbes Global 2000 and ranked these PMNEs by using rough set theory, DEA and TOPSIS method. In addition, differences in environmental, social, and governance (ESG) performance across three continents were investigated. Findings show that North America is significantly the best (worst) region in terms of business performance (R&D efficiency) while Europe is significantly the best (worst) region in terms of R&D efficiency (business performance). Alfresa Holdings Corporation, a PMNE from Japan, is the only PMNE that is efficient from both an R&D and business performance perspective. European PMNEs have significantly better environmental and social performance than other regions, however, they have the worst governance performance. Overall, this study provides insights to managers and investors into the application of various methods for accurately measuring performance and ranking multinational enterprises. [ABSTRACT FROM AUTHOR]

Bamboo, recognized as a versatile and eco-friendly construction material, has garnered substantial interest in recent times. This study undertakes a comprehensive assessment of five bamboo species—Bullet, Deluxe, Choti Khunti, Premium, and Kanaat. The primary objective is to evaluate their suitability for construction practices. The investigation initiates with an analysis of the bamboo species density and moisture content, shedding light on their physical properties and durability. The results reveal notable variations, with Choti Khunti bamboo boasting the highest density and the lowest moisture content, signifying its potential resilience. Additionally, the study scrutinizes the shrinkage behavior of these bamboo species concerning changes in thickness, diameter, and length under varying temperatures. Deluxe bamboo shows compressive and tensile strengths of 82.64 N/mm2 and 151.95 N/mm2, respectively. In the term of bending strength, Kanaat bamboo exhibits the highest bending strength of 319.26 N/mm2. To facilitate decision-making, three multi-criteria decision-making (MCDM) methods—TOPSIS, AHP, and VIKOR—are employed to rank these bamboo species based on their overall laboratory performance. The consensus among these methods places deluxe bamboo in the top position, followed by bullet, thus positioning deluxe as the most promising bamboo species for construction applications. [ABSTRACT FROM AUTHOR]

Concept selection is one of the most important activities in new product development processes in that it greatly influences the direction of subsequent design activities. As a complex multiple-criteria decision-making problem, it often requires iterations before reaching the final decision where each selection is based on previous selection results. Reusing key decision elements ensures decision consistency between iterations and improves decision efficiency. To support this reuse, this article proposes a fuzzy ontology-based decision tool for concept selection. It models the key decision elements and their relations in an ontological way and scores the concepts using weighted fuzzy TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). By applying the tool to an example, this article demonstrates how the concepts, criteria, weights, and results generated for one decision can be reused in the next iteration. [ABSTRACT FROM AUTHOR]

• Heterogeneity in pedestrians' perceived importance of crossing facilities was studied. • TOPSIS was used to derive the relative importance and ranking of attributes. • Heterogeneity in perceived importance was investigated using non-parametric tests. • Mann-Whitney U and Kruskal-Wallis H tests were employed as non-parametric tests. • Heterogeneity was found to be significant w.r.t walking preference and age group. • There was no effect of gender on heterogeneity in perceived importance. Although several studies in the past discussed the effects of socio-demographic and trip characteristics on users' preferences towards crossing facilities in urban areas, they were mostly confined to metro cities or million-plus cities. Adequate investigation has not been performed for the same in the small-sized cities where pedestrian activities are expected to be more frequent because of the higher share of shorter and walkable trip lengths. Accordingly, the present study aimed to investigate the heterogeneity in the perceived importance of crossing facility attributes among different pedestrian groups based on gender, age group, and walking preference. The study was conducted in a small-sized city, Roorkee, in the state of Uttarakhand, India. A face-to-face questionnaire survey of 554 pedestrians was conducted to collect their perceived importance towards 12 crossing facility attributes under study using a 5-point Likert-type ordinal scale. Collected data was analyzed using the non-parametric tests to measure the heterogeneity in the perceived importance of crossing facility attributes among aforementioned pedestrian groups. Subsequently, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method was used to derive relative importance scores of attributes found statistically significant in heterogeneity tests for different pedestrian groups. The findings of the present study reveal that perceived importance towards crossing facility attributes is heterogeneous based on the pedestrians' age group and walking preferences; however, it remains unaffected by gender. These findings would help policymakers, planners, and government authorities frame improvement strategies for the existing crossing facilities in the city. [ABSTRACT FROM AUTHOR]

As the service age of bridges increases, the degeneration of the bridge components leads to changes in the importance of corresponding state assessment indices. Employing fixed weights in bridge service condition assessments may result in inconsistent outcomes with the actual conditions. Therefore, this paper proposes an index weight updating method that aims to achieve index weight updating based on the operational status of bridges, thereby enhancing the accuracy of bridge service condition assessment results. This method utilizes the bidirectional projection of fuzzy numbers representing index state intervals and ideal targets as the technique for order preference by similarity to an ideal solution (TOPSIS) evaluation criteria for index importance. This paper conducts case analyses of a suspension bridge across multiple service periods which comprise three primary conditions: periods of intact bridge status, suboptimal conditions resembling expected degradation, and damaged status due to external effects. The case study results demonstrate that the updated weight using the proposed method effectively reflects the influence of actual changes in bridge status on the importance of indices. In the cases of good condition or matching the expected degradative state, the updated weights obtained could better reflect the actual service condition of the bridge compared to fixed weights provided by standards. When considering the effect of accidents or other incidental factors, the updated weights obtained through the proposed method could reflect the influence of actual component conditions on the importance of indices while the initial weights and age-dependent updated weights cannot. Thereby, the assessment results derived from this approach are more consistent with expected states and maintenance levels, validating its effectiveness and comparative advantages over alternative methodologies. The results indicate that the proposed method can significantly enhance the rationality of assessment index weights, serving as a more effective and rational approach for evaluating bridge service conditions. [ABSTRACT FROM AUTHOR]

According to survey data released by the National Bureau of Statistics, from 2011 to 2022, the total output value of China's construction industry showed an increasing trend year by year. From 2018 to 2021, infrastructure investment has always maintained a positive growth, indicating that the current construction industry is in a rapid development stage. In order to improve the development quality of the construction industry as much as possible, it is of great significance to develop the whole Process engineering consulting service model. The quality evaluation of whole process engineering consulting service modes is MAGDM. The single-valued neutrosophic sets (SVNSs) is useful tool to cope with uncertain information during the quality evaluation of whole process engineering consulting service modes. In this paper, the single-valued neutrosophic number combined TOPSIS (SVNN-CTOPSIS) model based on single-valued neutrosophic number Hamming distances (SVNNHD) and single-valued neutrosophic number Euclidean distance (SVNNED) is formed to cope with the MAGDM. The CRITIC model is utilized to obtain the weight numbers in light with the SVNNHD and SVNNED under SVNSs. Finally, numerical example and comparative analysis for quality evaluation of whole process engineering consulting service modes is utilized to verify SVNN-CTOPSIS model. The main contributions of this study are formed: (1) the CRITIC model is formed to obtain the weight numbers in light with SVNNHD and SVNNED; (2) the SVNN-CTOPSIS model is formed in light with SVNNHD and SVNNED under SVNNs; (3) Finally, numerical example and comparative analysis for quality evaluation of whole process engineering consulting service modes is employed to verify SVNN-CTOPSIS model. [ABSTRACT FROM AUTHOR]

The study monitors chronological changes (1922–36 to 2023) in channel morphological status of the Mayurakshi River in Eastern India using the index of Geomorphic Status (GS). It encompasses Changes in Sedimentary Units (SU), Changes in Sediment Availability (SA), Changes in Bar Stability (BS) and Changes in Channel Flow (CF). The Index of Geomorphic Status (GS) reveals a sharp morphological degradation of the Mayurakshi River in the recent past. Therefore, a detailed checklist of channel width, bed-level, configuration dynamics and channel connectivity was prepared to identify medium- and short-term Channel Adjustment (CA). The study reveals that instream sand mining and structural interventions coupled with low discharge are the key factors hindering channel morphological recovery. Finally, a new Channel Recovery Potential Index (CRP) has been proposed by considering short-term channel adjustment, sediment connectivity, geomorphological setup and anthropogenic stresses. Preferred alternatives and optional groups assessed from the AHP-TOPSIS and AHP-VIKOR models were used to quantify the channel Recovery Potential. Outcome of the study reveals that reach 1 has more chance of channel recovery (TOPSIS: 0.77 and VIKOR: 0.00) compared to other sectors. [ABSTRACT FROM AUTHOR]

Pavement maintenance and rehabilitation decision-making needs to weigh multiple strategic goals to achieve sustainable development through the pavement maintenance management system. Making decisions regarding pavement preventive maintenance is both intricate and costly. This study introduces a multi-criteria decision-making framework aimed at enhancing the scientific basis of such decisions. The framework first establishes an evaluation system for preventive maintenance strategies by considering three primary evaluation criteria—service functionality, pavement performance, and economic benefits, and then identifies nine specific evaluation indicators to influence these criteria, with a comparison matrix constructed to determine the weight of each indicator in relation to the maintenance decision hierarchy. Following this, the technique for order preference by similarity to ideal solution (TOPSIS) is employed to prioritize four commonly utilized preventive maintenance strategies. The results reveal that pavement condition and maintenance costs are the most influential factors in determining the appropriate preventive maintenance strategies for national highways. The priority rankings for the four strategies—slurry seal, micro-surfacing, chip seal, and ultra-thin overlays—are found to be 56.12%, 63.86%, 12.12%, and 83.52%, respectively, with ultra-thin overlays identified as the optimal choice for second-class highways. The decision-making model utilized in this study enables a multi-dimensional analysis, reducing the subjectivity inherent in expert evaluations and facilitating the prompt identification of the most suitable maintenance strategy. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Financial institutions should prioritize the adoption of comprehensive Environmental, Social, and Corporate Governance (ESG) disclosure policies to improve their market reputation and decrease capital expenditures. The current study's research objective is to investigate the impact of both inside and outside executives on the successive adoption of ESG strategies, based on the sustainable leadership theoretical framework and the bottom-up corporate governance theory. Data for the current study were obtained from the Refinitiv Eikon database and analyzed through using the entropy weight and TOPSIS techniques. The research suggests that including fully autonomous board members has the potential to improve the transparency of firms' ESG criteria. This result was derived from an analysis of data pertaining to the behavior of CEOs and non-executives at the company level in Fiscal Year (FY) 2023. The verification of the soundness and dependability of this finding has been carried out by scrutinizing the problem of endogeneity and diverse techniques of data representation. Furthermore, our study has disproven the idea that having CEOs on the board of directors may significantly improve the ESG performance of financial institutions. Consequently, the research proposes that adopting a strict policy of board independence has the capacity to alleviate the environmental, social, and governance repercussions that arise from the control of internal executives, namely CEOs. [ABSTRACT FROM AUTHOR]

Smart logistics (SL) reflects the digital transformation of the logistics industry, which is key for economic development. Most evaluations are based on the application of technology in SL, and few studies have evaluated SL from a comprehensive perspective. The paper builds the SL development index (SLDI) model from five dimensions based on the driving force, pressure, state, impact, and response (DPSIR) model and identifies the indicator weight by the entropy weight technique. The paper employs the ETDK method, a combined quantitative approach that incorporates entropy weight (E), the technique for order preference by similarity to an ideal solution (TOPSIS) (T), the Dagum Gini coefficient (D), and Kernel density estimation (K), to calculate the closeness degree, analyze spatial-temporal differentiation, and explain the distribution characteristics using data from China spanning 2013 to 2021. The findings show that (1) The SL evaluation is multidimensional and cannot be evaluated only based on technical indicators. A comprehensive evaluation indicator system is necessary. (2) A combined quantitative approach can measure SL development from multiple perspectives and get a clearer picture of the characteristics and regional differences of SL. (3) Influenced by economic development, infrastructure, regional clusters, location, talent, etc., the overall SL development is improving yearly, but SL development in different regions is unbalanced and has different distribution characteristics. The SLDI model developed in this paper will provide a more scientific and reasonable tool for comprehensively evaluating SL. The findings are helpful in proposing suggestions and optimization approaches for subsequent research on SL evaluation and development. [ABSTRACT FROM AUTHOR]

The objective of this study is to enhance the resilience of the coal-to-liquids (CTL) industrial chain and supply chain to withstand increasing shock pressures. There is an urgent need to improve the resilience of the industrial chain and supply chain. This paper identifies 21 resilience-influencing factors from 4 perspectives: absorption capacity, adaptability, recovery capacity, and self-learning capacity; it then constructs an evaluation indicator system. The Interval Type 2 Fuzzy-Decision-Making Trial and Evaluation Laboratory-Analytic Network Process (IT2F-DEMATEL-ANP) method is adopted to determine the weights of the indicator system, and a resilience evaluation is performed based on the Interval Type 2 Fuzzy-Prospect Theory-Technique for Order Preference by Similarity to an Ideal Solution (IT2F-PT-TOPSIS) method. Furthermore, in the case of the CTL industrial chain and supply chain of China Shenhua Energy Group Ningxia Coal Industry Co., Ltd. (CENC) (Ningxia, China), this study ranks the resilience level from 2018 to 2022 to identify the factors that have contributed to a reduction in resilience and to implement measures to enhance the resilience of the CTL industrial chain and supply chain. The results show that the level of the CTL industrial chain and supply chain resilience was lowest in 2020, while it was highest in 2021. Factors such as the degree of domestication of key technologies, the rationality of the CTL industry layout, and the stability of supply and demand chains are identified as significant determinants of resilience levels. This points the way to enhancing the resilience of the CTL industry and supply chain. [ABSTRACT FROM AUTHOR]

The study introduces an innovative three-stage nested power generation system that enables the cascading utilization of LNG cold energy. It makes the most of wasted energy by using ship jacket cooling water (JCW) and exhaust gas (EG) as heat sources, a trans-critical carbon dioxide cycle as internal circulation, and utilizing the pressure exergy of LNG. We choose two azeotrope mixing fluids that match the requirements and create four cases for the outer and middle cycle working fluids in the three-stage nested system. To discover the ideal system performance from the perspectives of exergy (E), economy (E), and environment (E), four cases were subjected to multi-objective optimization using the multi-objective particle swarm optimization technique (MOPSO). Finally, the optimal solution was found by applying the TOPSIS decision-making method. Through comparative analysis, the optimal system is selected among the four optimization results. R170 (22.66%) and R1150 (77.34%) are used as the outer circulating working medium, while R170 (90.86%) and R1270 (9.14%) are utilized as the inter-cycle working fluid. The net output work is 575.75 kW, the optimal exergy efficiency is 46.09%, the optimal electricity production cost is $0.04009 per kWh, the carbon dioxide emissions can be reduced by 36,910 tons, and the payback period is 2.548 years. After optimization, a more energy-efficient and environmentally friendly power generation system is obtained. [ABSTRACT FROM AUTHOR]

In the context of rapid urbanization, public spaces in traditional villages face challenges such as material ageing, loss of characteristics, and functional decline. The scientific and objective assessment of the quality of these public spaces is crucial for the sustainable development of traditional villages. Panoramic images, as an important source of spatial data, combined with deep learning technology, can objectively quantify the characteristics of public spaces in traditional villages. However, existing research has paid insufficient attention to the evaluation of the quality of public spaces in traditional villages at the micro-scale, often relying on questionnaires and interviews, which makes it difficult to meet the needs of planning and construction. This study constructs an evaluation system for the quality of public spaces in traditional villages, taking national-level traditional villages in the Fangshan District of Beijing as an example, based on traditional field research, using deep learning and panoramic images to automatically extract the features of public spaces in traditional villages, using a combination of the Analytic Hierarchy Process (AHP) and Criteria Importance Through Intercriteria Correlation (CRITIC) methods to determine the weights of the indicators and applying the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method to evaluate the quality of public spaces in traditional villages. The study found that the quality of public spaces in Nanjiao Village is Grade I; Shuiyu Village and Liulinshui Village, Grade III; and Heilongguan Village, Grade IV and that there is still much room for improvement in general. The evaluation results match well with the public's subjective perceptions, with an R2 value of 0.832, proving that the constructed evaluation system has a high degree of accuracy. This study provides a scientific basis and an effective tool for the planning, design, and management of public spaces in traditional villages, which helps decision-makers better protect and utilize them. [ABSTRACT FROM AUTHOR]

This study examines the dry milling process of a rare-earth-based magnesium alloy, emphasizing the optimization of the milling parameters and their impact on the surface quality, cutting forces, and the rate of material removal. The objective is to improve our comprehension of the milling behavior of the Mg-Gd-Y-Er alloy. The Taguchi technique is adopted to formulate the experimental design. This study methodically investigates the influence of heat treatment (T4 and T6) on milling performance, and the effects of speed, feed rate, and depth of cut. The output variables considered for this investigation are the surface roughness (Ra, Rz, Sa, and Sz), material removal rate (MRR), and cutting force. To optimize the milling parameters and achieve superior outcomes, the multi-objective optimization technique TOPSIS is used. At a feed rate of 150 mm/min, a spindle speed of 1500 rpm, and a depth of cut of 1 mm, the T4-treated sample exhibits a minimum surface roughness value of 0.0305 µm. The highest resultant force values of 96.4416 N and 176.1070 N for 200 °C and 225 °C T6-treated alloys are obtained by combining process parameters such as a spindle speed of 1500 rpm, a feed rate of 50 mm/min, and a depth of cut of 1.5 mm. Furthermore, the maximum closeness coefficient value is achieved by combining a spindle speed of 1000 to 1500 rpm, a feed rate of 150 mm/min, and a depth of cut of 0.5 mm to 1 mm. The closeness coefficient value is significantly influenced by the most significant process parameters, as indicated by the ANOVA results. [ABSTRACT FROM AUTHOR]

The aim of the current paper is to identify the effective factors in forming the cyberloafing phenomenon and rank these factors. In the present study, a multiple attribute decision-making method has been used. The statistical population of this study consists of managers and employees of the Yazd Provincial Tax Administration, and 27 of them were selected based on accessibility. This research is applied and descriptive-analytical in terms of purpose and type. Based on the literature review, eighteen effective factors in the formation of cyberloafing were identified. Different MADM techniques, such as SAW, TOPSIS, ELECTRE, and TOXONOMY, were used to rank each factor. Finally, the Copeland fusion technique was used to reach a consensus on the execution of the mentioned techniques. Our investigations have shown that organizational policy factors, organizational commitment, and having a lot of leisure time had the most significant impact on the formation of the cyberloafing phenomenon. Also, interpersonal conflict, role overload, and belief in disorder had the least impact on the formation of the cyberloafing phenomenon. The current research is the first one conducted with this approach, especially in Iran, and its results can be considered by managers in other organizations as well. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)