A Multi-Attribute Decision Method under Uncertainty Environment Conditions—The Green Supplier Evaluation Perspective

Due to the continuous changes of political environment, consumption habits, technological progress and other factors, the external environment of enterprises is full of uncertainty. The turbulence of external environment is not conducive to the long-term operation and development of enterprises, but also brings great challenges to the selection of suppliers. This makes the competition of enterprises focus on how to choose long-term cooperation suppliers in the uncertain external environment. In addition, due to the deterioration of the global environment, governments pay more and more attention to environmental pollution, and consumers are more and more inclined to green consumption, which makes many companies pay more and more attention to environmental indicators when selecting suppliers. In the case of external environment turbulence and serious environmental pollution, the evaluation and selection of green suppliers in uncertain environment is particularly important for the long-term development of enterprises. What’s more, when the supplier’s capability gap is small, the decision-maker often hesitates among several suppliers. In this paper, the hesitant fuzzy is used to describe the hesitant psychology of decision-makers in selecting suppliers, the variance fluctuation is used to describe the characteristics of hesitant fuzzy numbers, and the probability is used to measure the uncertainty of the environment. A green supplier evaluation model under the uncertainty environment is proposed, which comprehensively evaluates the green suppliers under the uncertain environment. Furthermore, it is compared with other methods that do not consider the uncertainty and the adaptability of evaluation method and right confirmation method, so as to reflect the influence of uncertainty to green supplier evaluation and the importance of adaptability of evaluation method and right confirmation method

Coupling Coordinated Evolution and Forecast of Tourism-Urbanization-Ecological Environment: The Case Study of Chongqing, China

As an important pioneering city in western China, Chongqing’s urbanization and tourism development have brought increasing pressure on the eco-environmental system. This paper presents a comprehensive index system for assessment of the level of tourism based on four aspects: market size, tourism economy, tourism resources, and tourism services. In this paper, we use five indices—economic urbanization, demographic urbanization, social urbanization, spatial urbanization, and cultural urbanization—to establishe a comprehensive index system for urbanization. The developed index system also characterizes the eco-environment based on three factors: eco-environmental pressure, eco-environmental response, and eco-environmental state. A coupling coordination degree model (CCDM) focusing on the degree of coupling coordination between tourism, urbanization, and the eco-environment was established using panel data collected from 2000 to 2017 for Chongqing, China. In addition, we used the gray prediction model to predict the degree of coupling coordination of the three systems in Chongqing from 2018 to 2023. The results showed that (1) overall, despite the twists and turns in the middle of the time period, the degree of coupling coordination of the three systems has become increasingly coordinated over time; (2) the three parameters (α-tourism, ß-urbanization, and d-eco-environmental) that have been widely used in previous studies had little effect on the coupling coordinated system; and (3) according to the prediction results, the degree of coupling coordination of the three systems will continue to rise slowly, and the cooperation between the three systems will be close to perfect by 2023, which means that the development of one system will greatly drive the other two systems

Preparation and properties of MWCNTs-ODA/Ag/polyimide composite films

Silver modified aminated carbon nanotubes(MWCNTs-ODA/Ag) were prepared by functionalizing carbon nanotubes with silver nitrate(AgNO3) and 4, 4'-diaminodiphenyl ether (ODA). After in-situ polymerization, coating and thermal amination, MWCNTs-ODA/Ag/PI composite films were obtained by using ODA and pyromellitic dianhydride (PMDA) as polyimide (PI) monomers and MWCNTs-ODA/Ag as nano fillers. The effects of different nano filler contents on properties of the composite films were analyzed. The results show that when the addition amount of MWCNTs-ODA/Ag is 3% (mass fraction, the same below), the tensile strength of Ag/PI-3% film is 123.0 MPa, which is 17.9% higher than Ag/PI-0% film. The thermal conductivity reaches 0.55 W·m-1·K-1, which is 5 times that of Ag/PI-0% film. The thermal conductivity of the composite film is greatly improved with excellent mechanical properties and heat resistance

Research on the Planning Method and Strategy of Urban Wind and Heat Environment Optimization—Taking Shenzhen, a Sub-Tropical Megacity in Southern China, as an Example

The planning techniques and strategies for optimizing the urban wind and heat environment are important means for cities to adapt to climate change at the source. This study used Shenzhen, a sub-tropical megacity in southern China, as an example for evaluating the climate environment, heat island intensity, and urban form, and then for analyzing the relationships between them. The results revealed a high-quality climate area located southeast of Shenzhen that can provide a high wind speed and low temperature. Low-quality climate areas were located in the central and western regions and were less comfortable. The relationship between surface ventilation potential and urban form was analyzed using linear regression and the Pearson correlation coefficient, showing that there was a significant correlation between a surface urban heat island (SUHI) and building density (BD) as well as the sky view factor (SVF), and that there was also a correlation between the ventilation potential coefficient (VPC) and other factors, such as the surface’s roughness length (RL) and building height (BH). The results showed that ventilation capacity deteriorated as BH and RL increased. An environmentally sensitive thermal area was identified from the surface urban heat island intensity, which was always in a strong heat island (SHI) or sub-strong heat island (SSHI) year-round. It was recommended that seven level one corridors and nine level two corridors be formed. Additionally, thermal and wind environment optimization strategies and protective suggestions were proposed for the city’s overall development

Hierarchical Porous Carbon Anode Materials Derived from Rice Husks with High Capacity and Long Cycling Stability for Sodium-Ion Batteries

Compared with the cathode materials, the research on the anode materials of the sodium-ion batteries has lagged behind. Therefore, development of the anode materials with high capacity, long life, and excellent rate properties is the key to unlocking the practical application for sodium-ion batteries. This study presents the preparation of hierarchical porous hard carbon as an active anode material from rice husks. The as-synthesized materials are characterized by X-ray diffraction, N-2 adsorption, Raman spectra, scanning electron microscopy and transmission electron microscopy. These porous hard carbon materials exhibit a high specific surface area and are promising for reversible sodium storage. Galvanostatic studies show that the specific initial capacities of all samples were in the range of 130-300 mA h g(-1) at a current density of 100 mA g(-1) between 0.01 V and 2.3 V. Compared to the other samples, the hard carbon materials prepared at 800 degrees C from rice husk (RHPC-800) can deliver a high reversible capacity of 274 mA h g(-1) at a current density of 25 mA g(-1), maintain a capacity of approximately 260 mA h g(-1), and retain 92.7 % of its capacity after 500 cycles. This excellent electrochemical performance of the as-prepared RHPC-800 material is attributed to the high specific surface area and low charge transfer resistance

Combining convolutional neural network and distance distribution matrix for identification of congestive heart failure

Congestive heart failure (CHF) is a serious pathophysiological condition with high morbidity and mortality, which is hard to predict and diagnose in early age. Artificial intelligence and deep learning combining with cardiac rhythms and physiological time series provide a potential to help in solving it. In this paper, we proposed a novel method that combines a convolutional neural network (CNN) and a distance distribution matrix (DDM) in entropy calculation to classify CHF patients from normal subjects, and demonstrated the effectiveness of this combination. Specifically, three entropy methods were used to generate the distribution matrixes from a 300-point RR interval (i.e., the time interval between the successive cardiac cycles) time series, which are Sample entropy, fuzzy local measure entropy, and fuzzy global measure entropy. Then, three high representative CNN models, i.e., AlexNet, DenseNet, and SE_Inception_v4 were chosen to learn the pattern of the data distributions hidden in the generated distribution matrixes. All data used in our experiments were gathered from the MIT-BIH RR Interval Databases ( http://www.physionet.org ). A total of 29 CHF patients and 54 normal sinus rhythm subjects were included in this paper. The results showed that the combination of FuzzyGMEn-generated DDM and Inception_v4 model yielded the highest accuracy of 81.85% out of all proposed combinations.Published versio

Cost-effectiveness analysis of aspirin for primary prevention of cardiovascular events among patients with type 2 diabetes in China.

The use of aspirin for primary prevention of cardiovascular disease (CVD) in patients with diabetes mellitus (DM) is associated with lower rates of cardiovascular events but increased risks of bleeding complications. We aimed to examine the cost-effectiveness of aspirin therapy for primary prevention of CVD in Chinese DM patients. A life-long Markov model was developed to compare aspirin therapy (100mg daily) versus no use of aspirin in DM patients with no history of CVD. Model validation was conducted by comparing the simulated event rates with data reported in a clinical trial. Direct medical costs and quality-adjusted life-years gained (QALYs) were the primary outcomes from the perspective of healthcare system in China. Sensitivity analyses were performed to examine the uncertainty of model inputs. Base-case analysis showed aspirin therapy was more costly (USD1,086 versus USD819) with higher QALYs gained (11.94 versus 11.86 QALYs) compared to no use of aspirin. The base-case results were sensitive to the odds ratio of all-cause death in aspirin therapy versus no use of aspirin. Probabilistic sensitivity analysis found that aspirin therapy gained an additional 0.066 QALYs (95% CI: -0.167 QALYs-0.286 QALYs) at higher cost by USD352 (95% CI: USD130-644)). Using 30,000 USD/QALY as willingness-to-pay threshold, aspirin therapy and no use of aspirin were the preferred option in 68.71% and 31.29% of 10,000 Monte Carlo simulations, respectively. In conclusion, aspirin therapy appears to be cost-effective compared with no use of aspirin in primary prevention of CVD in Chinese DM patients

Protective effect and mechanism of citrulline on intestinal injury induced by radiation in mice

BackgroundIonizing radiation can cause damage to animal's intestinal tissue. Citrulline is produced in the intestinal epithelial cell and has been proven to possess a protective effect on the gastrointestinal tract.PurposeThis study aims to investigate the protective effects and the underlying mechanisms of citrulline in the context of radiation-induced intestinal injuries.MethodsFirstly, a mouse model of an acute radiation-induced intestinal injury was established, incorporating a normal control, a simple irradiation, and an irradiation plus citrulline group. Then, these groups were employed to scrutinize the protective effects and mechanisms associated with citrulline. Subsequently, hematoxylin-eosin staining was used to examine the morphology of the mice's intestinal tissue, and the Elisa kit was employed to quantify endotoxin levels in plasma, as well as nitric oxide and inducible nitric oxide synthase in the intestinal tissue. Finally, focal adhesion kinase and Occludin levels in the intestinal tissue were assessed using western blotting.ResultsThe experimental results demonstrate that intraperitoneal injection of 1 g∙kg-1∙d-1 citrulline for one week following irradiation significantly extend the median survival time of irradiated mice and increase their body weight. Moreover, it markedly reduces plasma endotoxin levels, elevate the expression levels of focal adhesion kinase (FAK) and intestinal tight junction protein (Occludin), and decreases the expression levels of nitric oxide (NO) and inducible nitric oxide synthase (iNOS) in the intestinal tissue.ConclusionsCitrulline enhances the integrity of the intestinal barrier in irradiated mice, improves barrier function, mitigates nitrosative stress, and demonstrates a protective impact on radiation-induced intestinal damage in mice