City Sustainable Development Evaluation Based on Hesitant Multiplicative Fuzzy Information

Sustainable development evaluation is the basis of city sustainable development research, and effective evaluation is the foundation for guiding the formulation and implementation of sustainable development strategy. In this paper, we provided a new city sustainable development evaluation method called hesitant multiplicative fuzzy TODIM (HMF-TODIM). The main advantage of this method is that it can deal with the subjective preference information of the decision-makers. The comparison study of existing methods and HMF-TODIM is also carried out. Additionally, real case analysis is presented to show the validity and superiority of the proposed method. Research results in this paper can provide useful information for the construction of sustainable cities

Effectiveness and cost-effectiveness of six GLP-1RAs for treatment of Chinese type 2 diabetes mellitus patients that inadequately controlled on metformin: a micro-simulation model

ObjectiveTo systematically estimate and compare the effectiveness and cost-effectiveness of the glucagon-like peptide-1 receptor agonists (GLP-1RAs) approved in China and to quantify the relationship between the burden of diabetic comorbidities and glycosylated hemoglobin (HbA1c) or body mass index (BMI).MethodsTo estimate the costs (US dollars, USD) and quality-adjusted life years (QALY) for six GLP-1RAs (exenatide, loxenatide, lixisenatide, dulaglutide, semaglutide, and liraglutide) combined with metformin in the treatment of patients with type 2 diabetes mellitus (T2DM) which is inadequately controlled on metformin from the Chinese healthcare system perspective, a discrete event microsimulation cost-effectiveness model based on the Chinese Hong Kong Integrated Modeling and Evaluation (CHIME) simulation model was developed. A cohort of 30,000 Chinese patients was established, and one-way sensitivity analysis and probabilistic sensitivity analysis (PSA) with 50,000 iterations were conducted considering parameter uncertainty. Scenario analysis was conducted considering the impacts of research time limits. A network meta-analysis was conducted to compare the effects of six GLP-1RAs on HbA1c, BMI, systolic blood pressure, and diastolic blood pressure. The incremental net monetary benefit (INMB) between therapies was used to evaluate the cost-effectiveness. China’s per capita GDP in 2021 was used as the willingness-to-pay threshold. A generalized linear model was used to quantify the relationship between the burden of diabetic comorbidities and HbA1c or BMI.ResultsDuring a lifetime, the cost for a patient ranged from USD 42,092 with loxenatide to USD 47,026 with liraglutide, while the QALY gained ranged from 12.50 with dulaglutide to 12.65 with loxenatide. Compared to exenatide, the INMB of each drug from highest to lowest were: loxenatide (USD 1,124), dulaglutide (USD −1,418), lixisenatide (USD −1,713), semaglutide (USD −4,298), and liraglutide (USD −4,672). Loxenatide was better than the other GLP-1RAs in the base-case analysis. Sensitivity and scenario analysis results were consistent with the base-case analysis. Overall, the price of GLP-1RAs most affected the results. Medications with effective control of HbA1c or BMI were associated with a significantly smaller disease burden (p < 0.05).ConclusionLoxenatide combined with metformin was identified as the most economical choice, while the long-term health benefits of patients taking the six GLP-1RAs are approximate

Two Heads are Better than One: Towards Better Adversarial Robustness by Combining Transduction and Rejection

Both transduction and rejection have emerged as important techniques for defending against adversarial perturbations. A recent work by Tram\`er showed that, in the rejection-only case (no transduction), a strong rejection-solution can be turned into a strong (but computationally inefficient) non-rejection solution. This detector-to-classifier reduction has been mostly applied to give evidence that certain claims of strong selective-model solutions are susceptible, leaving the benefits of rejection unclear. On the other hand, a recent work by Goldwasser et al. showed that rejection combined with transduction can give provable guarantees (for certain problems) that cannot be achieved otherwise. Nevertheless, under recent strong adversarial attacks (GMSA, which has been shown to be much more effective than AutoAttack against transduction), Goldwasser et al.'s work was shown to have low performance in a practical deep-learning setting. In this paper, we take a step towards realizing the promise of transduction+rejection in more realistic scenarios. Theoretically, we show that a novel application of Tram\`er's classifier-to-detector technique in the transductive setting can give significantly improved sample-complexity for robust generalization. While our theoretical construction is computationally inefficient, it guides us to identify an efficient transductive algorithm to learn a selective model. Extensive experiments using state of the art attacks (AutoAttack, GMSA) show that our solutions provide significantly better robust accuracy

Stratified Adversarial Robustness with Rejection

Recently, there is an emerging interest in adversarially training a classifier with a rejection option (also known as a selective classifier) for boosting adversarial robustness. While rejection can incur a cost in many applications, existing studies typically associate zero cost with rejecting perturbed inputs, which can result in the rejection of numerous slightly-perturbed inputs that could be correctly classified. In this work, we study adversarially-robust classification with rejection in the stratified rejection setting, where the rejection cost is modeled by rejection loss functions monotonically non-increasing in the perturbation magnitude. We theoretically analyze the stratified rejection setting and propose a novel defense method -- Adversarial Training with Consistent Prediction-based Rejection (CPR) -- for building a robust selective classifier. Experiments on image datasets demonstrate that the proposed method significantly outperforms existing methods under strong adaptive attacks. For instance, on CIFAR-10, CPR reduces the total robust loss (for different rejection losses) by at least 7.3% under both seen and unseen attacks.Comment: Paper published at International Conference on Machine Learning (ICML'23

Impact of the National Reimbursement Drug List Negotiation Policy on Accessibility of Anticancer Drugs in China: An Interrupted Time Series Study

Objective: Since 2016, the Chinese government has been regularly implementing the National Reimbursement Drug List Negotiation (NRDLN) to improve the accessibility of drugs. In the second round of NRDLN in July 2017, 18 anticancer drugs were included. This study analyzed the impact of the NRDLN on the accessibility of these 18 anticancer drugs in China. Methods: National hospital procurement data were collected from 2015 to 2019. As measurements of drug accessibility, monthly average of drug availability or defined daily dose cost (DDDc) was calculated. Interrupted time series (ITS) analysis was employed to evaluate the impact of NRDLN on drug accessibility. Multilevel growth curve models were estimated for different drug categories, regions or levels of hospitals. Results: The overall availability of 18 anticancer drugs increased from about 10.5% in 2015 to slightly over 30% in 2019. The average DDDc dropped from 527.93 CNY in 2015 to 401.87 CNY in 2019, with a reduction of 23.88%. The implementation of NRDLN was associated with higher availability and lower costs for all 18 anticancer drugs. We found an increasing level in monthly drug availability (β2 = 2.1126), which ascended more sharply after the implementation of NRDLN (β3 = 0.3656). There was a decreasing level in DDDc before July 2017 (β2 = −108.7213), together with a significant decline in the slope associated with the implementation of NRDLN (β3 = −4.8332). Compared to Traditional Chinese Medicines, the availability of Western Medicines was higher and increased at a higher rate (β3 = 0.4165 vs. 0.1108). Drug availability experienced a larger instant and slope increase in western China compared to other regions, and in secondary hospitals than tertiary hospitals. Nevertheless, regional and hospital-level difference in the effect of NRDLN on DDDc were less evident. Conclusion: The implementation of NRDLN improves the availability and reduces the cost of some anticancer drugs in China. It contributes to promoting accessibility of anticancer drugs, as well as relieving regional or hospital-level disparities. However, there are still challenges to benefit more patients sufficiently and equally. It requires more policy efforts and collaborative policy combination