Weight Method Research Articles

Spatio-Temporal Analysis of Urban Emergency Response Resilience During Public Health Crises: A Case Study of Wuhan

In recent years, public health emergencies have severely disrupted city functions and endangered residents’ health and lives, enhancing the emergency response capacity, a crucial aspect of building resilient cities. Based on the Wuhan Statistical Yearbook and local economic and social big data, this study constructed a resilience assessment system that covers resistance, adaptability, and resilience. Evaluate the resilience level of each region and analyze its spatiotemporal characteristics using the entropy weight method, Theil index, and natural breakpoint method. The central area exhibited higher resilience levels, while peripheral areas showed lower resilience, owing to location advantage and developmental disparities. The obstacle degree model revealed that scientific and technological innovation, social rescue capabilities, and population size are the primary weak links in building urban emergency response capacity. Based on these findings, this study aims to provide policy recommendations and improvement measures for multiple stakeholders, guide the construction of resilient cities, enhance the ability to respond to public health crises and recovery speed, and ensure urban functions and residents’ well-being.

Study on the Coupling Coordination Degree and Driving Mechanism of “Production-Living-Ecological” Space in Ecologically Fragile Areas: A Case Study of the Turpan–Hami Basin

One of the key conditions for achieving superior regional growth is ensuring the harmonious development of both the layout and functions of territorial space. Territorial space, which includes production space, living space, and ecological space, serves as a critical system and venue for economic, cultural, and social activities in a region. The harmonized growth of production–living–ecological space (PLES) is essential for attaining sustainable development goals. Research on PLES offers a fresh perspective on promoting sustainable development of the spatial domain and the sustainable use of resources. However, studies on PLE functions in ecologically fragile areas are lacking. Therefore, in this study, which adopts a PLES perspective, land-use data are used to classify land according to the dominant functions of production, ecology, and living. Integration of point-of-interest (POI) data with socio-economic data was established to spatially describe indicators at the grid level and create a scoring system for PLES indicators in ecologically fragile areas. Finally, the entropy weight method, holistic assessment methods, coupling coordination degree model (CCDM), and geodetector were employed to explore the coupling coordination relationships and factors influencing PLESs in the Turpan–Hami Basin from 2010 to 2020. The results indicate that the Turpan–Hami Basin consists predominantly of potential ecological space, mainly in the central and northern regions, which are characterized by the Gobi Desert and bare rock landforms. Over the past decade, the PLES framework has seen a notable rise in the allocation of residential and ecological areas, whereas the portion dedicated to production spaces has diminished. The overall coupling coordination degree (CCD) of PLES in the Turpan–Hami Basin is at a coordinated level and gradually increasing. The most significant impact on the degree of PLES coupling coordination is exerted by population and natural factors. The research findings provide theoretical support for the sustainable utilization of resources in the Turpan–Hami Basin and other ecologically fragile areas while also offering scientific evidence to promote the coupling coordination of PLES, thereby contributing to high-quality regional development.

Intermittent Preventive Treatment of Malaria in Pregnancy and the Impact on Neonates in African Countries as Assessed by Entropy Weight and TOPSIS Methods.

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.

Driving forces and obstacles analysis of urban high-quality development in Chengdu.

High-quality development paths in important cities are blurry and lacking. In order to explore the important engine for Chengdu high-quality development, driving forces and obstacles recognition has emerged as a pivotal technological solution. Using the Chengdu in Sichuan province of China as a research area and quantitative data from 2010 to 2019, this study has used content mining to recognize urban high-quality development (UHQD) variables, and calculated variables' weights by entropy weight method, and explored driving forces and obstacles of UHQD by the technique for order preference by similarity to ideal solution (TOPSIS) method. The main findings are: (1) there are 36 UHQD variables; (2) Chengdu high-quality development overall level soars from 2017 to 2019, only with two negative growth rates in 2011, 2015; (3) There are 3 key driving force paths: (1) improving green development by volume of industrial wastewater discharged, comprehensively utilised ratio of industrial solid wastes, harmless treatment rate of domestic garbage; (2) stressing open development by total import and export/GDP, actual use of foreign capital, number of foreign tourists/total tourists; and (3) intensifying shared development by funds for urban residents under basic provision protection. (4) 3 clearing obstacles paths can also realize Chengdu high-quality development: (1) improving innovative development level by R&D internal outlay, patent authorisations, state high-level tech enterprises; (2) optimizing coordinated development level by the proportion of tertiary industry; (3) promoting shared development level by urban basic pension insurance. According to these findings, suggestions are put forward to promote Chengdu high-quality development from the perspective of policy implementation.

Relationships between heart failure, depression, and anxiety: A Mendelian randomization study.

Growing evidence suggests that heart failure (HF) is associated with an increased risk of depressive disorders and anxiety. However, the existing studies were observational and may have confounded and not reflected true causal relationships. This study collected genetic instruments about HF, depression, and anxiety from publicly available genetic summary data. Two-sample Mendelian randomization (MR) analysis was performed, with inverse-variance weighted designated as the primary approach for determining causal effects. Secondary analyses included MR-Egger regression and the weighted media method. Additionally, we conducted MR pleiotropy residual sum and outlier to address horizontal pleiotropy. Cochran Q test, MR-Egger intercept test, and leave-one-out analysis were used to assess the robustness of the findings. The significance is determined by a P-value below .05. Gene prediction result revealed that HF did not exhibit a significant association with elevated incidence of depression by inverse-variance weighted method no matter HF from the Heart Failure Molecular Epidemiology for Therapeutic Targets Consortium (odds ratio [OR] = 1.05, 95% confidence interval [CI] = 0.93-1.18, P = .424 for major depressive disorder, MDD; OR = 1.01, 95% CI = 0.94-1.09, P = .782 for major depression) or the FinnGen Consortium (OR = 1.03, 95% CI = 0.92-1.15, P = .644 for MDD; OR = 1.00, 95% CI = 0.94-1.07, P = .962 for major depression). In contrast, the results of HF on anxiety exhibited inconsistency (OR = 1.60, 95% CI = 1.10-2.31, P = .013 for Heart Failure Molecular Epidemiology for Therapeutic Targets Consortium; OR = 1.42, 95% CI = 0.91-2.21, P = .123 for FinnGen Consortium); however, a combined effect analysis indicated support causal relationship between HF and the risk of anxiety (OR = 1.52, 95% CI = 1.07-2.00, P < .001). Our findings did not reveal evidence to confirm a causal association between HF and depression. However, our results provide support for a causal effect of HF on the risk of anxiety.

Evaluation of water richness in coal seam roof aquifer based on factor optimization and random forest method.

Water richness evaluation of coal seam roofs is a crucial prerequisite for preventing and controlling water hazards in coal seam roofs. For this purpose, Spearman correlation and GeoDetector were employed for factor optimization to investigate the significance of lithological and structural factors and the impact of interactions among different factors on the water richness of coal seam roofs. Water richness evaluation models of coal seam roofs were separately established via the entropy weight method (EWM), coefficient of variation method (CVM), and random forest method (RFM), and the predictive accuracies of these models were compared. Eleven lithological and structural factors were collected. Through Spearman correlation analysis, 6 factors were identified to have significant influences on water richness. By utilizing the interaction detection of GeoDetector, the effects of interfactor interactions on water richness were explored, and 3 combination factors were selected. AICc was used to determine the model's superiority. The evaluation results of the study area based on factor optimization and three methods were further compared and validated via pumping tests, workface water inflow tests, and three-dimensional high-density electrical method. The results indicated that the RFM exhibited higher prediction accuracy than did the entropy weight and coefficient of variation methods. Additionally, within each method, factor optimization led to improved model accuracy.

The associations between modifiable risk factors and constipation: a comprehensive mendelian randomization study

ObjectiveEarly identification of modifiable risk factors is crucial for the prevention of constipation. This study systematically investigated the relationship between genetically predicted modifiable risk factors and constipation.MethodsThe inverse variance weighting (IVW) method was employed as the primary analytical approach. For similar exposure indicators, the multivariate Mendelian randomization (MVMR) method was used to adjust for potential biases in univariate MR analysis. The robustness of the results was further evaluated using the MR-Egger intercept test, Cochran’s Q test, and leave-one-out analysis. Bonferroni correction was applied to reduce the false positive rate in the results.ResultsThe IVW analysis indicated a significant causal association between genetically predicted gastroesophageal reflux disease [OR (95% CI) = 1.192 (1.079–1.315), P = 0.0005], atorvastatin use [OR (95% CI) = 16.995 (3.327–86.816), P = 0.0007], and constipation. Additionally, there was a potential causal association between education level [OR (95% CI) = 0.859 (0.767–0.964), P = 0.009], major depressive disorder [OR (95% CI) = 1.206 (1.041–1.399), P = 0.013], hypothyroidism [OR (95% CI) = 2.299 (1.327–3.985), P = 0.003], and aspirin use [OR (95% CI) = 4.872 (1.174–20.221), P = 0.029] with constipation. No causal associations were found for the other included indicators. Sensitivity analysis demonstrated the absence of evidence for heterogeneity and pleiotropy in any positive results.ConclusionThis study identified several risk factors that could be targeted for the prevention of constipation, offering valuable insights for public health policies.

Association Between Glaucoma and Brain Structural Connectivity Based on Diffusion Tensor Tractography: A Bidirectional Mendelian Randomization Study.

Glaucoma is a neurodegenerative ocular disease that is accompanied by cerebral damage extending beyond the visual system. Recent studies based on diffusion tensor tractography have suggested an association between glaucoma and brain structural connectivity but have not clarified causality. To explore the causal associations between glaucoma and brain structural connectivity, a bidirectional Mendelian randomization (MR) study was conducted involving glaucoma and 206 diffusion tensor tractography traits. Highly associated genetic variations were applied as instrumental variables and statistical data were sourced from the database of FinnGen and UK Biobank. The inverse-variance weighted method was applied to assess causal relationships. Additional sensitivity analyses were also performed. Glaucoma was potentially causally associated with alterations in three brain structural connectivities (from the SN to the thalamus, from the DAN to the putamen, and within the LN network) in the forward MR analysis, whereas the inverse MR results identified thirteen brain structural connectivity traits with a potential causal relationship to the risk of glaucoma. Both forward and reverse MR analyses satisfied the sensitivity test with no significant horizontal pleiotropy or heterogeneity. This study offered suggestive evidence for the potential causality between the risk of glaucoma and brain structural connectivity. Our findings also provided novel insights into the neurodegenerative mechanism of glaucoma.

Trait Association Studies to Determine Selection Indices in F5 Segregating Populations of Rice (Oryza sativa L.)

The experiment consisted of 38 promising F5 breeding lines developed and evaluated for correlation coefficient, path coefficient and selection indices studies with four check varieties viz., NVSR-2435, Sardar, Lalkada Gold and GR-18 in RBD with three replications during kharif-2023 at RRRS, Vyara, Gujarat. Genotypic correlation analysis revealed that grain yield per plant appeared to be positively and significantly correlated with productive tillers per plant, plant height, panicle length, straw yield per plant and 100 grain weight, which suggested that these characters can be improved simultaneously towards higher grain yield per plant by direct selection. Genotypic path analysis revealed that positive and direct effects on grain yield per plant were exhibited by days to maturity, productive tillers per plant, panicle length, 100 grain weight and straw yield per plant. Among these traits, panicle length, productive tillers per plant, 100 grain weight and straw yield per plant exhibited direct effect along with highly significant and positive association with grain yield per plant. Therefore, selection for such traits may be considered as most important yield attributing characters. The negligible residual effect of 0.037 was observed in path analysis, indicates that the model explained large proportion of variance. Thirty-one selection indices were constructed in all possible combinations of grain yield per plant (X1) along with four components viz., productive tiller per plant (X2), panicle length (X3), 100 grain weight (X4) and straw yield per plant (X5) through equal weight method. Among all the selection indices, the relative efficiency (%) and expected genetic advance (GA) was noted maximum with four characters selection index (I1245) compared to grain yield per plant (I1).

Coupling and Coordination Analysis of High-Quality Agricultural Development and Rural Revitalization: Spatio-Temporal Evolution, Spatial Disparities, and Convergence

The coupling and coordination of high-quality agricultural development (HQAD) and rural revitalization is an inevitable choice to accelerate the realization of Chinese-style agricultural and rural modernization. Based on system theory, this study reconstructs the indicator systems of both and conducts measurements by applying the improved AHP–entropy weight method. This study has extended the analytical methods of kernel density estimation, Dagum Gini coefficient, σ convergence, and spatial β convergence to further investigate the spatio-temporal evolution, regional disparities, and convergence effect of the coupling coordination degree (CCD) of HQAD and rural revitalization in China from 2010 to 2020. The results show that the CCD has a tendency to increase year by year, presenting the characteristics of ‘high coupling degree–low comprehensive development level–low coupling coordination degree’, and also has the spatial distribution pattern of ‘high in the east and low in the west’. In addition, most of the provinces have a tendency to jump to a higher stage of coupling coordination; the overall trend of the kernel density curves is favorable; the results of Dagum’s Gini coefficient show that inter-regional disparities contribute the most to regional spatial disparities; and there is a significant tendency towards σ convergence and spatial β convergence of the CCD in China and the four regions. This study stimulates a broader discussion of rural revitalization, with potential implications for decision making in practice.

Optimisation and Application of Entropy Weight Method-TOPSIS Model for Ranking the Importance of Urban Express Sites

With the rapid development of e-commerce, the importance of express delivery network in the modern logistics system is becoming more and more prominent. In order to scientifically assess the importance of urban express sites, this paper proposes a multi-objective decision-making method based on entropy weight method and TOPSIS model. The entropy weight method is objectively assigned by analysing the data dispersion of indicators, and the TOPSIS model is used to rank urban sites by calculating their distance from ideal and negative ideal solutions. In this paper, we firstly processed the data with multiple interpolation to ensure its accuracy, and selected four key indicators, namely, shipping volume, receiving volume, correlation and growth trend of express delivery volume. The results show that the entropy weight method-TOPSIS model can effectively assess the importance of each city site, provide a scientific basis for optimising the express delivery network, and have a wide range of application potential.

Genetic association of gut microbiota with osteoarthritis: a multivariable Mendelian randomization study considering medication use.

Background. The interplay among human gut microbiota (GM) composition, osteoarthritis (OA) and OA-related medication use has been extensively discussed. However, to date, there has been no exploration of the genetic correlation among these three factors.Hypothesis/Gap. The potential causal link between GM and OA), and whether medications influence this relationship, remains unclear.Methods. We utilized bidirectional Mendelian randomization (MR) to explore the genetic associations between GM and OA. We leveraged genome-wide association study (GWAS) summary statistics from the MiBioGen and GO consortia, which provided data on GM taxa and OA cases, respectively. We identified outlier single-nucleotide polymorphisms using radial-MR and assessed causal associations using inverse variance weighting (IVW), weighted median and MR-Egger methods. Robust outcomes, consistent across these methods, were reported. We addressed potential biases through tests for horizontal pleiotropy and heterogeneity, supplemented by the Mendelian randomization pleiotropy residual sum and outlier method. Multivariable MR techniques were applied to adjust for OA medication use using UK Biobank data.Results. IVW estimates revealed a significant increase in hip OA risk for Gordonibacter and Eubacterium (brachy group) [odds ratio (OR): 1.09, 95% confidence interval (CI): 1.04-1.15, P=7.82E-04; OR: 1.09, 95% CI: 1.03-1.16, P=4.67E-03, respectively]. Conversely, Senegalimassilia, Slackia and Streptococcus exhibited protective effects (OR: 0.88, P=2.14E-02; OR: 0.88, P=3.33E-02; 0.91, P=4.29E-02). Sutterella increased the risk of knee OA (OR=1.15, 95% CI: 1.07-1.25, P=4.06E-04), while Haemophilus decreased it (OR=0.94, 95% CI: 0.88-1.00, P=4.26E-02). No significant heterogeneity or horizontal pleiotropy was observed in the results. Even after accounting for the potential confounding effect of medication, the results remained consistent. No reverse causation was detected.Conclusions. Our MR study reveals gut microbiome links to OA risk. Associations hold after adjusting for medication, indicating a potential causal connection between GM and OA.

Decoupling analysis of economic development and human well-being: A case study of the Qinghai-Xizang Plateau, China.

Clarifying the relationship between economic development and human well-being is conducive to promoting high-quality economic development. This study focused on 16 prefecture-level cities in the Qinghai-Xizang Plateau region. The critic weighting method assessed the 2007-2018 human well-being index (HWI). The Tapio decoupling model allowed the study of the human well-being decoupling state. Finally, the drivers of decoupling between economic development and human well-being were analyzed using the Logarithmic Mean Divisia Index method. The results indicated that (1) almost all cities in the study region had an upward 2007-2018 HWI trend, but there were significant differences in growth magnitude and change trend. (2) Economic development and human well-being in the study region in 2007-2018 had expansion negative decoupling, thus, human well-being increased with economic growth, but not as fast as gross domestic product. 9 cities in 2007 showed weak decoupling, expansion connection, and expansion negative decoupling, increasing to 13 cities by 2018, indicating that human well-being development gradually improved from 2007 to 2018. (3) For most cities, the economic scale effect was the most influential factor in the decoupling of economic development and human well-being. Therefore, this study provided policy recommendations for decoupling economic development and human well-being.

Associations between Sjogren syndrome and psychiatric disorders in European populations: a 2-sample bidirectional Mendelian randomization study.

Psychiatric disorders, such as major depressive disorder (MDD), anxiety disorder (AD), bipolar disorder (BD), and schizophrenia (SCZ), are disturbances in brain activity that lead to disorders of cognition, behavior, and emotion regulation. Among Sjogren syndrome (SS) patients, psychiatric disorders are more prevalent than in the general population. Identifying associated risk factors can provide new evidence for clinical diagnosis and treatment. We selected genetic instruments based on published genome-wide association studies (GWASs) to determine predisposition. Then, we conducted a 2-sample bidirectional Mendelian randomization (MR) analysis to explore the potential causal associations between SS and four major psychiatric disorders. The primary analysis was performed using MR with the inverse-variance weighted method. Confirmation was achieved through Steiger filtering and testing to determine the causal direction. Sensitivity analyses were conducted using MR-Egger, MR-PRESSO, and "leave-one-out" method methods. Our study showed that SS was linked to BD and SCZ, indicating that individuals with SS may have a reduced risk of developing BD (IVW: OR = 0.940, P=0.014) and SCZ (IVW: OR = 0.854, P=1.47*10-4), while there was no causal relationship between SS and MDD or AD. MR-Egger regression shows no evidence of pleiotropy (BD: intercept = 0.007, p = 0.774; SCZ: intercept = 0.051, p = 0.209). The same as the MR-PRESSO analysis (BD: global test p = 1.000; SCZ: global test p = 0.160). However, the results from the leave-one-out analysis demonstrated instability. Specifically, after excluding SNP rs3117581, the effects on BD and SCZ were found to be non-significant, suggesting the potential influence of unrecognized confounding factors. The results of the reverse MR show that four major psychiatric disorders had no causal effects on SS. Our research findings demonstrate a causal relationship between SS and SCZ, as well as between SS and BD. There are no causal effects between the four major psychiatric disorders and SS. These findings suggest that SS may have the potential to reduce the risk of both psychiatric disorders. This study provides new insight for their prevention and treatment.

Estimation of liver standardized uptake value in F18-FDG PET/CT scanning: impact of different malignancies, blood glucose level, body weight normalization, and imaging systems.

The aim of this work was to investigate homogeneity and stability of liver SUV in terms of different malignancies considering different body normalization schemes and blood glucose concentrations as well as PET/CT imaging systems. The study included 207 patients with four different types of cancers namely breast, lymphoma, lung, and bone-metastasis. Data acquisition was performed with GE Discovery IQ, Biograph mCT, uMI 550, and Ingenuity TF64 after a single intravenous injection of 194 ± 67.5 MBq of 18F-FDG. In body weight normalization, SUVmax and SUVmean in bone-mets as well as SUVmean in lung patients were not statistically different among scanners especially for data corrected for glucose levels (p = 0.062, 0.121, and 0.150, respectively). In SUVlbm derived from lung patients, there was no significant differences in Philips in comparison to GE and Siemens (both, p > 0.05) for data corrected and not corrected for glucose levels. In SUVbsa, the only non-significant difference revealed among scanners was in the measurements of SUVmean obtained from lung and bone-mets (p = 0.107 and 0.114) both corrected for glucose levels. In SUVbmi, SUVmean of lung and bone-mets as well as SUVmax of bone-mets showed a non-significant differences among the four different scanning systems (p = 0.303, 0.091, and 0.222, respectively) for data corrected for glucose levels. Liver glucose correction needs further investigations in individual tumors but could be potentially affected by whether measurements are made on SUVmean versus SUVmax, body weight normalization, as well as the imaging system. As such, selection of normalization to body weight method should be carefully selected before clinical adoption and clinically adopted and body surface area would provide the highest correlation. As such, normalization of body weight should be carefully made before clinical adoption. SUVmean proves to be useful and stable metric when liver is corrected for blood glucose levels.

Development and Application of an Employee Moral Quotient (MQ) Evaluation Index System for Chinese Petroleum Enterprises

Recognizing the critical role of oil and gas resources as strategic assets and acknowledging the increasing emphasis on green development and social responsibility driven by international energy agreements and the “dual carbon” strategy, this study addresses the urgent need for a robust employee evaluation framework within China’s petroleum sector. While existing systems often prioritize competence-based indicators, they frequently overlook the crucial aspect of employee Moral Quotient (MQ). This research focuses on developing and validating a holistic, scientifically grounded, multi-dimensional, and dynamic MQ evaluation index system tailored specifically for Chinese petroleum enterprises. The study employed a mixed-methods approach, integrating a comprehensive literature review, semi-structured interviews with industry experts, and robust quantitative techniques, including the Analytic Hierarchy Process (AHP) and the entropy weight method. A two-round Delphi study, involving 18 experts from six provinces across China, ensured broad representation and facilitated the construction of the evaluation index system and the determination of indicator weights. The Delphi process achieved a high degree of expert consensus, evidenced by a 100% questionnaire response rate in both rounds, expert authority coefficients of 0.851 and 0.879, respectively, and Kendall’s coefficient of concordance of 0.243 and 0.247 (p &lt; 0.01), respectively, demonstrating strong reliability and scientific validity. The resulting MQ evaluation index system comprises eight first-level indicators and thirty-three s-level indicators, encompassing key dimensions of employee morality relevant to the petroleum industry. This comprehensive system provides a robust and objective tool for employee selection, training, performance evaluation, and career development within Chinese petroleum enterprises, supporting informed decision-making in human resource management and fostering a culture of ethical conduct and sustainable development. Furthermore, the developed framework offers valuable insights and serves as a potential model for petroleum enterprises and other resource-intensive industries globally seeking to integrate MQ assessment into their human capital management strategies.

Evaluating Sustainability Practices in Viticulture Through a Comprehensive Study of Environmental, Social, and Economic Factors: A Case from Batman Province, Türkiye

This study aims to assess the sustainability level of viticulture farms in Batman province and identify the factors that hinder their sustainability. The data used for the study were collected in the 2021 production year through surveys of 94 farms. A composite sustainability index was developed to measure the sustainability level of viticultural activities. Positive or endogenous weighting methods, such as Principal Component Analysis (PCA), were used to reduce the number of sustainability indicators and determine their weights. The index values for economic, environmental, and social sustainability were found to be 0.40, 0.44, and 0.53, respectively. The overall sustainability index value for the farms was calculated as 0.43. The study also highlighted that 46.81% of the farms are at risk in terms of sustainability, with larger farms showing better sustainability performance compared to smaller ones.

Evaluation system of vocational education construction in China based on linked TOPSIS analysis

In response to the task of vocational education reform in the new era, in order to cultivate innovative skilled talents, it is necessary to improve traditional evaluation methods to enhance their efficiency. This study proposes an evaluation model for vocational education construction that combines grey relational analysis and approximate ideal point method (TOPSIS). By selecting indicators and combining subjective analytic hierarchy process and objective entropy weight method for weight allocation, the weights of the indicators are determined using subjective analytic hierarchy process and objective entropy weight method. Through experimental analysis, the results showed that among the 11 analysis indicators, the weight of policy environment indicators was the highest at 0.124, while the weight of employment rate and contract signing rate indicators was the lowest at 0.050. The above results indicate that the TOPSIS comprehensive evaluation system based on grey correlation analysis has better application effects in practical scenarios and is more suitable for the development requirements of vocational education.

Application of the Simple Additive Weighting (SAW) Method in the Decision Support System for the Selection of Study Programs at the University of Papua

To help prospective students choose a study program that suits their abilities and interests, it is necessary to design a decision support system. This system aims to facilitate the selection process of study programs for prospective students. This research aims to develop a decision support system that can help prospective students in choosing a study program at the Faculty of Engineering, University of Papua in an objective and structured manner. This study applies the Simple Additive Weighting method to facilitate the decision-making process by considering a number of relevant criteria. The evaluation is based on the following criteria: tuition fees, accreditation status, number of teaching staff and staff, and job prospects. The findings of the study revealed that the Informatics Engineering and Civil Engineering Study Programs, both at the S1 level, obtained the highest identical preference value, namely 1, outperforming other study programs. However, the best alternative is the S1 Informatics Engineering Study Program.

The Association between Non-Alcohol Liver Fatty Disease and Coronary Artery Calcification: A Two-Sample Mendelian Randomization Study.

Although prior observational studies have suggested that patients with non-alcohol fatty liver disease (NAFLD) may have a higher risk of coronary artery calcification (CAC), these findings remain controversial. This study aimed to explore the causal association between NAFLD and CAC at genetic level by two-sample Mendelian randomization (MR) analysis. Utilizing summary-level data from multiple large-scale genome-wide association studies (GWAS) in European populations, a two-sample MR analysis was initially conducted to explore the potential causal association between NAFLD and CAC. The results of the MR analysis were pooled through random-effect meta-analysis. The inverse variance weighting (IVW) method served as the primary approach for MR analysis. Additionally, the weighted median, MR-Egger and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods was applied for sensitivity analysis. Summary-level data on liver fatty content was utilized for validation analysis, while summary-level data on cirrhosis served as positive control, further ensuring the validity and robustness of our findings. Reverse MR analysis was performed to assess the association between CAC and NAFLD, employing instrument variables derived from CAC. The MR analysis indicated that genetically predicted NAFLD had no effects on the risk of CAC (Beta: 0.01, 95% CI: -0.02 to 0.03, P = 0.74). Likewise, the reverse MR analysis found no significant genetic association between CAC and NAFLD (OR: 1.00, 95% CI: 0.96 to 1.06, P = 0.88). Validation analysis yielded consistent results, showing no significant association between fatty liver content and CAC. Our two-sample MR analysis did not support that there is a causal association between NAFLD and CAC at genetic level. The association between NAFLD and CAC reported in some previous observational studies may rely on NAFLD complicated with metabolic disorders, rather than being directly linked to the hepatic steatosis.