Application of hybrid multi-criteria decision-making approach to analyze wastewater microalgae culture systems for bioenergy production.

Bioenergy generation from microalgae can significantly contribute to climate mitigation and renewable energy production. In this regard, several multi-criteria decision-making method were employed to prioritize appropriate microalgae culture system for bioenergy production. Entropy weight, Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were the employed MCDA method. Fourteen microalgae culture systems were selected as a case study, which contain teen monoculture and four dual-culture. Initially, through ans in-depth review of the literature and expert views, four categories total eight indicators were selected as the evaluation indices of the study, namely 1) Proliferation: Half growth cycle and Max growth rate,2) Biomass output: Bio-crude yield and Lipid yield, 3) Nutrient utilization: residual concentration of total Nitrogen and total Phosphorus, and, 4) Stability: coefficient of variation of Bio-crude yield and Lipid yield. The result indicated that "Pediastrum sp. & Micractinium sp." was identified as the most bioenergy potential microalgae culture system, and the evaluation results of entropy weight method and CRITIC method are similar. It is pertinent to note that 1)the entropy weight method exhibits lower sample size requirements, 2) the critic method excels when dealing with larger sample sizes, and 3) the TOPSIS method necessitates the incorporation of appropriate weighting methods to ensure credible results. In the application stage, the key indicators related to cost can be further included in the evaluation indices.

Comprehensive evaluation of the implementation of close-type county medical alliance in Shandong Province using entropy weight TOPSIS method and non-integer rank sum ratio method.

BACKGROUND: To improve the capacity of county medical and health services, China encourages all localities to pilot the close-type county medical alliance. In Shandong Province, medical alliances have been piloted in 47 counties, ranking first in the country. The objective of this study is to comprehensively evaluate the implementation of close-type county medical alliance in Shandong Province, identify the differences between different county regions, and analyze the reasons, so as to provide a reference for the construction of a new county medical and health service system with clear goals, powers and responsibilities, and division of labor. METHODS: The implementation of the close-type county medical alliance was comprehensively evaluated in 47 national pilot counties in Shandong Province using entropy weight TOPSIS method and non-integer rank sum ratio method. Variance analysis was used for comparison of the comprehensive evaluation results. RESULTS: The weight coefficient of evaluation indicators was highest for information interconnection, at 18.06%, and lowest for orderly referral of patients, at 3.64%. There was no difference in results of the comprehensive evaluation of entropy weight TOPSIS method and non-integer rank sum ratio method. Comprehensively order the implementation status of each pilot county according to the relative paste progress, 13 counties Y5, Y11, Y14, Y16, Y20, Y25, Y26, Y27, Y28, Y32, Y33, Y40 and Y42 were ranked highest, whereas county Y37 was ranked lowest. Non-integer rank sum ratio method graded counties into three grades: excellent, good and average. Kruskal-Wallis nonparametric test showed that the difference between the grades was statistically significant (H[Formula: see text]37.099, p[Formula: see text]0.001). Variance analysis based on comprehensive evaluation results showed that implementation status was not correlated with the county economic development level, the level of health resources input and the medical service ability of the lead hospital. CONCLUSIONS: Our findings indicated that the implementation of the close-type county medical alliance is significantly different between pilot counties, with a marked differentiation within the same urban area. Therefore, effective measures are recommended to reduce this gap, including promoting informatization empowerment of the county medical community, strengthening government responsibility and improving policy effectiveness.

Evaluation of the water quality monitoring network layout based on driving-pressure-state-response framework and entropy weight TOPSIS model: A case study of Liao River, China.

The establishment of river water quality monitoring network is crucial for watershed protection. However, the evaluation process of monitoring network layout involves significant subjectivity and has not yet to form a complete indicator system. This study constructed an indicator system based on the DPSR (Driving-Pressure-State-Response) framework in the Liao River Basin, China. SWAT model and ArcGIS were used to quantify the indicators. And the entropy weight-TOPSIS method was employed to rank monitoring points. The results showed that pressure and state indicators had a greater impact on the network layout, with the indicator for proportion of land use in residential areas carrying the largest weight of 0.136. It suggested that the risk of river pollution remained high, and the governance strategies needed to be improved. Priority monitoring points were mainly located in the east and middle of the basin, consistent with the distribution of human activities such as urban areas and farmland. In addition, the redundancy of points should be avoided, and evaluation results should be adjusted based on the actual situation. The study provided an evaluation method for the layout of monitoring points.

[Quality evaluation and multi-spectral identification of origin herbs of Lonicerae Japonicae Flos based on grey correlation-TOPSIS method].

The grey correlation-TOPSIS method was used to evaluate the quality of the origin herbs of Lonicerae Japonicae Flos, and the Fourier transform near-infrared(NIR) and mid-infrared(MIR) spectroscopy was applied to establish the identification model of origin herbs of Lonicerae Japonicae Flos by combining chemometrics and spectral fusion strategies. The content of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, secoxyloganin, isoquercitrin, isochlorogenic acid B, isochlorogenic acid A, and isochlorogenic acid C in six origin herbs of Lonicerae Japonicae Flos was determined by high-performance liquid chromatography(HPLC), and their quality was evaluated by the grey correlation-TOPSIS method. The Fourier transform NIR and MIR spectra of six origin herbs of Lonicerae Japonicae Flos(Lonicera japonica, L. macranthoides, L. hypoglauca, L. fulvotomentosa, L. confuse, and L. similis) were collected. At the same time, principal component analysis(PCA), support vector machine(SVM), and spectral data fusion technology were combined to determine the optimal identification method for the origin herbs of Lonicerae Japonicae Flos. There were differences in the quality of the origin herbs of Lonicerae Japonicae Flos. Specifically, there were significant differences between L. japonica and the other five origin herbs(P<0.01). The quality of L. similis was significantly different from that of L. fulvotomentosa, L. macranthoides, and L. hypoglauca(P=0.008, 0.027, 0.01), and there were also significant differences in the quality of L. hypoglauca and L. confuse(P=0.001). The PCA and SVM 2D models based on a single spectrum could not be used for the effective identification of the origin herbs of Lonicerae Japonicae Flos. The data fusion combined with the SVM model further improved the identification accuracy, and the identification accuracy of the mid-level data fusion reached 100%. Therefore, the grey correlation-TOPSIS method can be used to evaluate the quality of the origin herbs of Lonicerae Japonicae Flos. Based on the infrared spectral data fusion strategy and SVM chemometric model, it can accurately identify the origin herbs of Lonicerae Japonicae Flos, which can provide a new method for the origin identification of medicinal materials of Lonicerae Japonicae Flos.

Controlling COVID-19 transmission with isolation of influential nodes.

To understand the transmission dynamics of any infectious disease outbreak, identification of influential nodes plays a crucial role in a complex network. In most infectious disease outbreaks, activities of some key nodes can trigger rapid disease transmission in the population. Identification and immediate isolation of those influential nodes can impede the disease transmission effectively. In this paper, the technique for order of preference by similarity to ideal solution (TOPSIS) method with a novel formula has been proposed to detect the influential and top ranked nodes in a complex social network, which involves analyzing and studying of structural organization of a network. In the proposed TOPSIS method, several centrality measures have been used as multi-attributes of a complex social network. A new formula has been designed for calculating the transmission probability of an epidemic disease to identify the impact of isolating influential nodes. To verify the robustness of the proposed method, we present a comprehensive comparison with five node-ranking methods, which are being used currently for assessing the importance of nodes. The key nodes can be considered as a person, community, cluster or a particular area. The Susceptible-infected-recovered (SIR) epidemic model is exploited in two real networks to examine the spreading ability of the nodes, and the results illustrate the effectiveness of the proposed method. Our findings have unearthed that quarantine or isolation of influential nodes following proper health protocols can play a pivotal role in curbing the transmission rate of COVID-19.

In Vitro Strategy for the Enhancement of the Production of Bioactive Polyphenols in Transformed Roots of Salvia bulleyana.

The underground parts of Salvia bulleyana, a rare Chinese plant species, have long been used in traditional Chinese medicine. The Rhizobium rhizogenes-transformed root culture obtained from this plant might be a promising novel source of valuable phenolics, including rosmarinic acid. The present study identifies for the first time, the optimal growth conditions of S. bulleyana hairy roots regarding production efficiency. The comprehensive optimization comprised cultivation in different basal media (B5, SH, MS, and WP) with full- and half-strength macro- and microelements, different vitamin contents (full, half, one-quarter part, and without) and sucrose concentrations (2, 3, 4, 5%), and under different light conditions: in dark, under blue LED (λ = 430 nm), red LED (λ = 670 nm), mixed blue and red LED (30%:70%), and white LED (390-670 nm). Hairy root growth and bioactive compound accumulation were also detailed every five days over the 50-day culture cycle. The optimal conditions were determined using a technique for order preference by similarity to the ideal solution (TOPSIS). The most efficient combination for root growth and polyphenol content was found to be ½SH liquid medium with half vitamin concentration and 3% sucrose when grown in the dark. The biomass yield during the growth cycle was 6.1 g (fresh weight-FW) and 0.92 g (dry weight-DW) on one Erlenmeyer flask: a 14.3-fold increase in FW and 16.1-fold increase in DW in relation to the inoculum. The highest mean total phenolic content was 93.6 mg/g DW including about 70 mg/g DW rosmarinic acid, reached on day 40 of culture; compared to roots of two-year-old plants grown under field conditions, the total phenolic acid content was four times higher and rosmarinic acid eight times higher. The obtained results place the investigated culture among the best hair root cultures for rosmarinic acid production.

Spatial-Temporal Sensitivity Analysis of Flood Control Capability in China Based on MADM-GIS Model.

To facilitate better implementation of flood control and risk mitigation strategies, a model for evaluating the flood defense capability of China is proposed in this study. First, nine indicators such as slope and precipitation intensity are extracted from four aspects: objective inclusiveness, subjective prevention, etc. Secondly, the entropy weight method in the multi-attribute decision making (MADM) model and the improved three-dimensional technique for order preference by similarity to ideal solution (3D-TOPSIS) method were combined to construct a flood defense capacity index evaluation system. Finally, the receiver operating characteristic (ROC) curve and the Taylor plot method were innovatively used to test the model and indicators. The results show that nationwide, there is fine flood defense performance in Shandong, Jiangsu and room for improvement in Guangxi, Chongqing, Tibet and Qinghai. The good representativity of nine indicators selected by the model was verified by the Taylor plot. Simultaneously, the ROC calculated area under the curve (AUC) was 70%, which proved the good problem-solving ability of the MADM-GIS model. An accurate assessment of the sensitivity of flood control capacity in China was achieved, and it is suitable for situations where data is scarce or discontinuous. It provided scientific reference value for the planning and implementation of China's flood defense and disaster reduction projects and emergency safety strategies.

[Analysis and evaluation of dynamic accumulation of multiple active constituents in Taxilli Herba in Guangxi].

A method based on ultra-high performance liquid chromatography with triple quadrupole/linear ion trap mass spectrometry(UHPLC-QTRAP-MS/MS) was developed for the simultaneous determination of 33 active constituents, including flavonoids, organic acids, nucleosides, and amino acids in Taxilli Herba to analyze and evaluate the dynamic accumulation of their multiple active constituents. The separation was performed at 30 ℃ on an XBridge~® C_(18) column(4.6 mm×100 mm, 3.5 µm) with gradient elution using 0.1% formic acid aqueous solution-methanol as the mobile phase at a flow rate of 0.5 mL·min~(-1), and the injection volume was 2 µL. The constituents were ionized in the electrospray ionization source(ESI) and quantitated by the multiple reaction monitoring(MRM) mode. The entropy weight TOPSIS method was used to objectively assign weights to the target constituents and rank them according to their relative closeness coefficient(C_i) to construct a multi-index comprehensive evaluation model of Taxilli Herba. The results showed that the concentrations and peak areas of 33 target constituents had good linearity in their respective linear ranges, and the correlation coefficients(r) were not less than 0.999 0. The RSD of precision, reproducibility, and stability were not higher than 4.7%. The average recoveries were 98.03%-101.3% with RSD less than 4.0%. There were differences in the content of 33 active constituents in Taxilli Herba at different harvest periods. The overall quality of Taxilli Herba harvested from mid-February to early March was better, which was consistent with the traditional harvest period. This study provides basic information for revealing the rule of dynamic accumulation of multiple active constituents in Taxilli Herba and determining the suitable harvesting period. Meanwhile, it also provides a new methodological reference for the comprehensive evaluation of the intrinsic quality of Taxilli Herba.

Evaluation of the quality of COVID-19 prevention and control by a novel comprehensive evaluation model in a tertiary general hospital: a prospective observational study.

BACKGROUND: Prevention and control (P&C) of Corona Virus Disease 2019 (COVID-19) is still a critical task in most countries and regions. However, there are many single evaluation indexes to assess the quality of COVID-19 P&C. It is necessary to synthesize the single evaluation indexes reasonably to obtain the overall evaluation results. METHODS: This study was divided into three steps. Step 1: In February 2020, the improved Delphi method was used to establish the quality evaluation indexes system for COVID-19 P&C. Step 2: in March 2020, the CRITIC method was used to adjust the Order Relation Analysis (G1) method to obtain the subjective and objective (S&O) combination weights. The comprehensive evaluation value was obtained using the weighted Efficacy Coefficient (EC) method, weighted TOPSIS method, weighted rank-sum ratio (RSR) method, and weighted Grey Relationship Analysis (GRA) method. Finally, the linear normalization method was used to synthesize the evaluation values of different evaluation methods. Step 3: From April 2020 to May 2021, this evaluation method was used to monitor and assess COVID-19 P&C quality in critical departments prospectively. The results were reported to the departments monthly. RESULT: A quality evaluation indexes system for COVID-19 P&C was established. Kendall's consistency test shows that the four evaluation method had good consistency (χ2 = 43.429, P<0.001, Kendall's consistency coefficient = 0.835). The Spearman correlation test showed that the correlation between the combined evaluation results and the original method was statistically significant(P < 0.001). According to the Mann-Kendall test, from March 2020 to May 2021, the mean value of COVID-19 P&C quality in all critical departments showed an upward trend (P < 0.01). CONCLUSIONS: The combined comprehensive evaluation method based on the S&O combined weight was more scientific and comprehensive than the single weighting and evaluation methods. In addition, monitoring and feedback of COVID-19 P&C quality were helpful for the improvement of P&C quality.

Sustainable Performance Evaluation: Evidence from Listed Chinese Mining Corporations.

Rapid industrial development has caused a series of environmental problems, which is not conducive to sustainable development of society as a whole. It is necessary to build a sustainable development evaluation system. Most of the existing literature has evaluated corporate sustainable performance from the economy, environment and society on the basis of triple bottom lines. Considering the research gap and the practice need, an evaluation system is established from four dimensions, referred to as economy, society, environment and responsibility management, and 29 indicators are designed to measure these four dimensions. Twenty seven listed Chinese mining corporations are selected as research samples, and the entropy-weight-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is applied to calculate indicators' weights. Results show that the four dimensions of sustainable performance weights from high to low are society, environment, economy, and management process.

A Group Decision Making Framework Based on Neutrosophic TOPSIS Approach for Smart Medical Device Selection.

Advances in the medical industry has become a major trend because of the new developments in information technologies. This research offers a novel approach for estimating the smart medical devices (SMDs) selection process in a group decision making (GDM) in a vague decision environment. The complexity of the selected decision criteria for the smart medical devices is a significant feature of this analysis. To simulate these processes, a methodology that combines neutrosophics using bipolar numbers with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) under GDM is suggested. Neutrosophics with TOPSIS approach is applied in the decision making process to deal with the vagueness, incomplete data and the uncertainty, considering the decisions criteria in the data collected by the decision makers (DMs). In this research, the stress is placed upon the choosing of sugar analyzing smart medical devices for diabetics' patients. The main objective is to present the complications of the problem, raising interest among specialists in the healthcare industry and assessing smart medical devices under different evaluation criteria. The problem is formulated as a multi criteria decision type with seven alternatives and seven criteria, and then edited as a multi criteria decision model with seven alternatives and seven criteria. The results of the neutrosophics with TOPSIS model are analyzed, showing that the competence of the acquired results and the rankings are sufficiently stable. The results of the suggested method are also compared with the neutrosophic extensions AHP and MOORA models in order to validate and prove the acquired results. In addition, we used the SPSS program to check the stability of the variations in the rankings by the Spearman coefficient of correlation. The selection methodology is applied on a numerical case, to prove the validity of the suggested approach.

Is smart city low-carbon? Evidence from China.

Smart cities were originally conceived to address a myriad of urban challenges arising from rapid urbanization, including energy scarcity, congestion, and environmental degradation. The Chinese government has made substantial efforts to advance smart city initiatives. However, the extent to which the integration of smart technologies contributes to urban sustainability, especially within a high-carbon urbanization paradigm, poses a critical question in light of escalating extreme weather events and worsening global challenges. Urgency is underscored in prioritizing low-carbon strategies within smart city frameworks. This paper presents a Multicriteria Decision Making Network (MCDN) approach to assess and rank the low-carbon levels (LCL) of 36 pilot smart cities in China. Findings reveal that overall LCL among these cities remains relatively modest, with significant disparities attributed to varying economic, social, institutional, cultural, and environmental contexts. The study also delves into the nexus between urban intelligence and LCL, highlighting a discernible positive correlation between a city's smartness and its low-carbon profile. Moreover, empirical evidence suggests that advancements in smart technologies are conducive, albeit to varying degrees, to enhancing urban LCL. In light of these findings, recommendations are made to fortify economic and social advancement, bolster management practices, and foster multi-stakeholder collaboration to propel the coordinated development of smart and low-carbon initiatives in China.

Optimizing microbial strain selection for pyrethroid biodegradation in contaminated environments through a TOPSIS-based decision-making system.

Improved and contemporary agriculture relies heavily on pesticides, yet some can be quite persistent and have a stable chemical composition, posing a significant threat to the ecology. Removing harmful effects is upon their degradability. Biodegradation must be emphasized to lower pesticide degradation costs, especially in the soil. Here, a decision-making system was used to determine the best microbial strain for the biodegradation of the pyrethroid-contaminated soil. In this system, the criteria chosen as: pH (C1), Temp (C2), RPM (C3), Conc. (C4), Degradation (%) (C5) and Time required for degradation(hrs) (C6); and five alternatives were Bacillus (A1), Acinetobacter (A2), Escherichia (A3), Pseudomonas (A4), and Fusarium (A5). The best alternative was selected by applying the TOPSIS (technique for order performance by similarity to ideal solution) method, which evaluates based on their closeness to the ideal solution and how well they meet specific requirements. Among all the specified criteria, Acinetobacter (A2) was the best and optimal based on the relative closeness value (( R i ∗ ) = 0.740 (A2) > 0.544 (A5) > 0.480 (A1) > 0.403 (A4) > 0.296 (A3)). However, the ranking of the other alternatives is also obtained in the order Fusarium (A5), Bacillus (A1), Pseudomonas (A4), Escherichia (A3). Hence this study suggests Acinetobacter is the best microbial strain for biodegradation of pyrethroids; while least preference should be given to Escherichia. Acinetobacter, versatile metabolic nature with various xenobiotic compounds' degradation ability, is gram-negative, aerobic, coccobacilli, nonmotile, and nonspore forming bacteria. Due to less study about Acinetobacter it is not in that much frame as the other microorganisms. Hence, considering the Acinetobacter strain for the biodegradation study will give more optimal results than the other microbial strains. Novelty of this study, the TOPSIS method is applied first time in selecting the best microbial strain for the biodegradation of pyrethroid-contaminated soil, considering this selection process as multi-criteria decision-making (MCDM) problem.

Characteristics of Medical Quality in Tertiary Traditional Chinese Medicine Hospitals by TOPSIS and RSR Methods.

Performance evaluation is important for improving medical quality and services. But, there is a lack of research for medical quality in traditional Chinese medicine (TCM) hospitals. This study examines the medical quality and various indicators of tertiary public traditional Chinese medicine hospitals in Gansu Province, to establish a foundation for improving the medical and management standards of these hospitals. This study collected performance assessment data from 10 tertiary TCM hospitals in Gansu Province from 2019 to 2022. Thirteen indicators with TCM characteristics were selected and categorized into 3 aspects: control of medical costs, internal operational dimensions, and comprehensive management. The level of medical quality in different hospitals and in different years were determined using the TOPSIS method for ranking and the RSR method for grading. Firstly, in terms of TCM characteristic indicators, hospital H had the highest control of medical costs and comprehensive management among different hospitals, with 45.87% and 24.20% respectively. The highest values for control of medical costs and comprehensive management were observed in 2020, with 40.65% and 18.69% respectively among different years. When evaluating the medical quality of different hospitals using the TOPSIS method, it was found that hospital H had the highest ranking from 2020 to 2022, with Ci values of 0.725, 0.778, and 0.667 respectively. Additionally, the RSR method indicated that hospital H had a high level of grading from 2020 to 2022, with Pi values of 0.687, 0.690, and 0.723 respectively. These findings suggest that the medical quality of hospital H is at a high and stable level of development. Based on the TOPSIS method to evaluate the performance appraisal results and ranking of different hospitals from 2019 to 2022. The results showed that the highest ranking was hospital B(Ci = 0.913) in 2019. The highest ranking was hospital C(Ci = 0.809)in 2020. The highest ranking was hospital D(Ci = 0.689) in 2021. The highest ranking was hospital J(Ci = 0.865) in 2022. The RSR method indicated that high grading level were hospitals B(Pi = 0.899),F(Pi = 0.795) in 2019. The highest grading level was hospital C(Pi = 0.809) in 2020. The highest grading level were hospitals A(Pi = 0.868), D(Pi = 0.813), E(Pi = 0.689), G(Pi = 0.873), J(Pi = 0.813), K(Pi = 0.842) in 2022. Based on the above results indicate that there is a large variation in the medical quality profile of different hospitals from 2019 to 2022. By comparing the results of TOPSIS and RSR method from 2019 to 2022, we found that the hospitals with identical ranking were D and J, and the hospitals with ≤2 difference in ranking was A,B,C,E in 2019, the hospitals with >2 ranking was A, F in 2020, the hospitals with >2 ranking were C, G in 2021, and the hospitals with identical ranking results were B,D,E,G,J in 2022. Comparing the ranking results of TOPSIS and RSR methods, showed that the hospitals with identical rankings were B, F from 2019 to 2022. The difference in ranking results ≤2 were A, C, D, E, G, H, J, K, indicating that high consistency between TOPSIS and RSR methods and credible results. The findings reveal significant fluctuations in medical quality across different years, while the overall level of medical quality remains relatively stable among the various hospitals. It is recommended that TCM hospitals focus on improving management efficiency, optimizing hospital operations, enhancing the utilization of medical resources, and fostering the efficient development of hospitals.

A bipolar fuzzy decision-making system for assessing high-risk coexisting tuberculosis disease in pregnant women.

Tuberculosis (TB) diagnosis poses a formidable challenge in global healthcare, particularly impacting older individuals and pregnant women. Diagnosing TB disease during pregnancy and in comorbid patients is more challenging due to overlapping symptoms with normal pregnancy conditions and existing treatments for other diseases, necessitating careful assessment to differentiate TB symptoms from those of other underlying conditions. To address this issue, this study designs a novel bipolar fuzzy decision-support system by integrating the concept of complex proportional assessment (COPRAS) and a technique for order preference by similarity to the ideal solution (TOPSIS) approaches using bipolar heptagonal fuzzy numbers. The approach is utilized to assess the high-risk of TB coinfection disease in pregnant women. The bipolar fuzzy set provides positive and negative membership degrees of an element, which divulge a balanced perspective by both the presence and absence of the disease. Additionally, a defuzzification algorithm is proposed for bipolar heptagonal fuzzy numbers, converting bipolar heptagonal fuzzy into a bipolar crisp score (CBHpFBCS). The bipolar fuzzy entropy measure is utilized to weight the criteria. The findings highlight that TB+HIV (G3) coinfection is more severe in pregnant women compared to other TB comorbidities. Finally, sensitivity and comparative analyses are executed across diverse criteria weight scenarios and with existing fuzzy multi-criteria decision-making (MCDM) methods to validate the robustness of the proposed method and its outcomes.

Measurement and spatial correlation analysis of high-quality development Level: A case study of the Yangtze River Delta urban agglomeration in China.

Against the backdrop of slowing economic growth and increasing environmental pressure, the Yangtze River Delta city cluster, as one of the largest city clusters in the world, has become more driven in its pursuit of high-quality development. We constructed a system of 24 evaluation indexes and used entropy-weighted TOPSIS to calculate and study the high-quality development index of urban agglomerations in the region. First, the level of high quality development (HQD) of the Yangtze River Delta city cluster generally improved from 2010 to 2021, with 2017 was the best year, while 2010 was the worst year. Second, in the multidimensional evaluation of HQD, Jiangsu excels in innovation and people's livelihood with 0.524 and 0.534, respectively; Shanghai (0.531) excels in coordinated development; Zhejiang excels in green and economic development with 0.557 and 0.484, respectively; and Anhui lags behind in all aspects. Third, the development process of HQD in the Yangtze River Delta region is uneven, and the level of HQD development varies greatly among the city clusters in the province. The measurement results show that Shanghai (0.511) has the highest score, followed by Zhejiang (0.484), Jiangsu (0.440) and Anhui (0.435). Fourth, spatial correlation analysis shows that Shanghai and Jiangsu are mainly distributed in the double-high region, Zhejiang is distributed in the high-low region, while Anhui is concentrated in the low-low region. The results of this study help us understand more deeply the characteristics and challenges of high-quality development in the Yangtze River Delta urban agglomerations and provide a scientific basis for more precise urban development policies.

Lifecycle Assessment and Multi-Parameter Optimization of Lightweight Cement Mortar with Nano Additives.

With the growing global concerns regarding sustainable development in the building and construction industries, concentration only on the engineering properties of building materials can no longer meet the requirements. Although some studies have been implemented based on the lifecycle assessment of lightweight cement-based materials, very few attempts have been made pertaining to multi-criteria optimization, especially when fly ash cenospheres are used as lightweight aggregates and nano additives are incorporated as modifying admixtures. This investigation utilized cenospheres as fine aggregates to produce green, sustainable, lightweight cement mortar. Multi-walled carbon nanotubes at 0.05, 0.15, and 0.45% were binarily added, together with 0.2, 0.6, and 1.0% of nano silica to improve the mechanical performance. Strength tests were conducted to measure the flexural and compressive behaviors, combined with a cradle-to-gate lifecycle assessment and direct cost analysis to assess the environmental and economic viability. Integrated indexes and the TOPSIS method were adopted to systematically evaluate the mortar mixes and determine the optimal mix. The outcomes show that nano additives worked synergically to enhance the mechanical properties of the mortars. The utilization of cenospheres effectively reduced environmental impacts and improved economic feasibility. Nano additives significantly affected the sustainability and economic viability; in particular, the utilization of multi-walled carbon nanotubes increased the material costs. To minimize the impact of the price of multi-walled carbon nanotubes, it is proposed to binarily use less expensive nano silica. In the multi-parameter optimization, the mix with 0.05% multi-walled carbon nanotubes and 0.02% nano silica was recommended to be the optimal mix.

Assessing indoor positioning system: A q-spherical fuzzy rough TOPSIS analysis.

This study investigates advanced data collection methodologies and their implications for understanding employee and customer behavior within specific locations. Employing a comprehensive multi-criteria decision-making framework, we evaluate various technologies based on four distinct criteria and four technological alternatives. To identify the most effective technological solution, we employ the q-spherical fuzzy rough TOPSIS method, integrating three key parameters: lower set approximation, upper set approximation, and parameter q (where q ≥ 1). Our novel approach combines the TOPSIS method with q-spherical fuzzy rough set theory, providing deeper insights into data-driven decision-making processes in corporate environments. By comparing our proposed framework with existing multi-criteria decision-making methodologies, we demonstrate its strength and competitiveness. This research contributes to enhancing decision-making capabilities in corporate settings and beyond.

Comprehensive evaluation of the international competitiveness of solar photovoltaic products in China, Japan, and Korea under RCEP background.

Under the background of global energy transformation and structural upgrading, the development of solar photovoltaic industry in various countries has been paid attention to, and solar photovoltaic products occupy an important position in the international trade of renewable energy. The signing of the RCEP agreement can create favorable external conditions for the trade and industrial cooperation of solar photovoltaic products, which has attracted global attention. Therefore, based on the background of RCEP, it is of practical significance to analyze the development and export competitiveness of solar energy products in the agreement countries. This paper uses TOPSIS to establish a comprehensive evaluation index system for the international competitiveness of solar photovoltaic products to study the international competitiveness of solar photovoltaic products in China, Japan, and Korea under the context of RCEP. The study shows that (1) China's international competitiveness in solar photovoltaic products is strong and continues to improve, while Japan is declining and Korea is growing slowly. (2) There are significant differences in the components that lead to international competitiveness among different countries. Based on the above findings, this paper proposes corresponding policy recommendations for the three countries.

Coordination evaluation of urban tourism and urban development based on TOPSIS method-a case of Xiamen city.

Facing the current situation of tourism and urban prosperity and development, whether there is a contradiction between urban tourism and urban development, and whether they can always coordinate with each other will affect the sustainable development of both. In this context, the coordination of urban tourism and urban development has become an urgent research object. Based on the statistics of twenty indicators of urban tourism and urban development in Xiamen from 2014 to 2018, the article uses the TOPSIS analysis method to develop the number of tourists. Research results show that (1) the selected indicators all showed significant growth characteristics, and over time the coordination coefficient increases year by year and gradually approaches the ideal optimal value. (2) Among them, 2018 has the highest coordination coefficient, 0.9534. (3) The occurrence of "big events" has a double-sided effect on urban tourism and development coordination.