Assessing and predicting small industrial enterprises’ credit ratings:A fuzzy decision-making approach

Corporate credit-rating assessment plays a crucial role in helping financial institutions make their lending decisions and in reducing the financial constraints of small enterprises. This paper presents a new approach for small industrial enterprises’ credit-rating assessment using fuzzy decision-making methods, and tests it using real bank loan data from 1,820 small industrial enterprises in China. The procedure of the proposed rating approach includes (1) using triangular fuzzy numbers to quantify the qualitative evaluation indicators; (2) adopting a correlation analysis, univariate analysis and stepping backwards feature selection method to select the input features; (3) employing the best-worst method (BWM) combined with the entropy weight method (EWM), the fuzzy c-means algorithm and the technique for order of preference by similarity to ideal solution (TOPSIS) to classify small enterprises into rating classes; and (4) applying the lattice degree of nearness to predict a new loan applicant’s rating. We also conduct a 10-fold cross-validation to evaluate the predictive performance of our proposed approach. The predictive results demonstrate that our proposed data-processing and feature selection approaches have better accuracy than the alternative approaches in predicting default, offering bankers a new valuable rating system to assist their decision making

Dynamic dependence of futures basis between the Chinese and international grains markets

Basis trading has emerged as a prominent trading strategy in the global grains markets. Understanding basis trading dynamics in this context requires an investigation of the interrelationships among futures basis values across different markets. Using data of corn and wheat over the period 2012-2022, we investigate the high-dimensional linkages of basis at various frequencies between the Chinese and international grains markets. We find a strong positive dynamic correlation between the basis of grains in international markets. However, the basis of Chinese corn (and wheat) exhibits weaker positive correlations with their international counterparts. Our further exploration uncovers temporal variations in the multi-dimensional interdependence structures among these basis values, with the international corn consistently occupying a pivotal central position. Given China's preeminent status as a grain importer, the implications of our study extend to the realm of adept risk management in the context of global grain trading amid an uncertain world

Traditional Chinese Medicine Improves Activities of Daily Living in Parkinson's Disease

We evaluated the effects of a traditional Chinese medicine (TCM), named Zeng-xiao An-shen Zhi-chan 2 (ZAZ2), on patients with Parkinson's disease (PD). Among 115 patients with idiopathic PD enrolled (mean age, 64.7 ± 10.2 years old), 110 patients (M = 65, F = 45; mean age, 64.9 ± 10.7 years old) completed the study. Patients took either ZAZ2 (n = 59) or placebo granule (n = 56) in a blind manner for 13 weeks while maintaining other anti-Parkinson medications unchanged. All participants wore a motion logger, and we analyzed the power-law temporal autocorrelation of the motion logger records taken on 3 occasions (before, one week, and 13 weeks after the drug administration). Drug efficacy was evaluated with the conventional Unified Parkinson Disease Rating Scale (UPDRS), as well as the power-law exponent α, which corresponds to the level of physical activity of the patients. ZAZ2 but not placebo granule improved the awake-sleep rhythm, the UPDRS Part II, Part II + III, and Part IV scores, and the α values. The results indicate that ZAZ2 improved activities of daily living (ADL) of parkinsonism and, thus, is a potentially suitable drug for long-term use

The Impact of Variational Primary Collaterals on Cerebral Autoregulation

The influence of the anterior and posterior communicating artery (ACoA and PCoA) on dynamic cerebral autoregulation (dCA) is largely unknown. In this study, we aimed to test whether substantial differences in collateral anatomy were associated with differences in dCA in two common types of stenosis according to digital subtraction angiography (DSA): either isolated basal artery and/or bilateral vertebral arteries severe stenosis/occlusion (group 1; group 1A: with bilateral PCoAs; and group 1B: without bilateral PCoAs), or isolated unilateral internal carotid artery severe stenosis/occlusion (group 2; group 2A: without ACoA and with PCoA; group 2B: with ACoA and without PCoAs; and group 2C: without both ACoA and PCoA). The dCA was calculated by transfer function analysis (a mathematical model), and was evaluated in middle cerebral artery (MCA) and/or posterior cerebral artery (PCA). Of a total of 231 non-acute phase ischemic stroke patients who received both dCA assessment and DSA in our lab between 2014 and 2017, 51 patients met inclusion criteria based on the presence or absence of ACoA or PCoA, including 21 patients in the group 1, and 30 patients in the group 2. There were no significant differences in gender, age, and mean blood pressure between group 1A and group 1B, and among group 2A, group 2B, and group 2C. In group 1, the PCA phase difference values (autoregulatory parameter) were significantly higher in the subgroup with patent PCoAs, compared to those without. In group 2, the MCA phase difference values were higher in the subgroup with patent ACoA, compared to those without. This pilot study found that the cross-flow of the ACoA/PCoA to the affected area compensates for compromised dCA in the affected area, which suggests an important role of the ACoA/PCoA in stabilizing cerebral blood flow

Multi-Objective Robust Optimization for the Sustainable Location-Inventory-Routing Problem of Auto Parts Supply Logistics

A great loss of transportation capacity has been caused in auto parts supply logistics due to the independent transportation from auto parts suppliers (APSs) to the automobile production line (APL). It is believed that establishing distribution centers (DCs) for centralized collection and unified distribution is one effective way to address this problem. This paper proposes a unified framework simultaneously considering the location-inventory-routing problem (LIRP) in auto parts supply logistics. Integrating the idea of sustainable development, a multi-objective MIP model is developed to determine the location and inventory capacity of DCs and routing decisions to minimize the total system cost and carbon emissions while concerning multi-period production demand. In addition, a robust optimization model is developed further in the context of uncertain demand. Numerical experiments and sensitivity analyses are conducted to verify the effectiveness of our proposed deterministic and robust models. The results show that synergistically optimizing the location and capacity of DCs and routing decisions are beneficial in reducing total system cost and carbon emissions. The analysis can provide guidelines to decision-makers for the effective management of auto parts supply logistics

Study on Evaluation Indicators of Agricultural Science and Technology Project Based on the Perspective of Innovation——Case in Basic Research Project

Firstly, the related theories about agricultural science and technology innovation and project approval evaluation are combed and summarized. By combining application and finish books of science and technology support plan project in agricultural field of Ministry of Science and Technology with stronger innovation, case analysis and expert interview are conducted. Evaluation indexes of agricultural science and technology project based on innovation value are proposed initially, and there are 50 initial indexes. After that, via focus group talk, qualitative research is conducted to further adjust innovative evaluation indexes, and 50 initial indexes are deleted to 41. The importance of the 41 indexes is scored by the experts, and index screening and classification are conducted by verification factor analysis in structural equation model. It not only obtains index classification but also finds action mechanism among innovation demand, innovation mode, research thinking, treatment method of difficulty, and predicted risk. The research could straighten up ideas of project review experts in agricultural field and provide reference for applicant designing project

Study on the Factors Influencing the Level of Innovation in Agricultural Science and Technology Projects

This paper carries out a questionnaire survey of persons in charge of the agricultural project in the "Eleventh Five-Year National Support Program" on the level of innovation in projects and the factors influencing innovation. After the linear regression analysis of the survey data, it is found that the factors influencing the innovation in agricultural science and technology projects include the level of innovation in scientific achievements, efficiency of research methods and creation of innovation environment. Through the variance analysis of the level of innovation and its influencing factors related to different innovators, it is found that there are differences in the statistical significance of level of innovation in projects among universities, research institutes, research and extension departments directly under the government, and enterprises; there are no significant differences in the understanding of factors influencing innovation, that is, different innovators basically have the same understanding of factors influencing innovation, but the assessment on level of innovation in projects completed is different to some extent. On this basis, this paper proposes the recommendations for further strengthening the level of innovation in agricultural science and technology projects in order to provide a theoretical reference and practical basis for the project managers to effectively improve the level of agricultural science and technology project management, and enhance the level of innovation in projects

Analysis of Social Capital’s Effect on Income of Poor Households: A Case Study in Sichuan Province

Looking from the existing research, improving the social capital of the poverty population is an effective way to promote the population quality and the income growth of the poor people. Based on the existing research, with the rural poor households in Sichuan Liangshan as the research object, this article used factor analysis to measure social capital stock, and then analyzed the influence of social capital on the income of the poor peasant households in that region, through the reconstructed production function. The results show that the poor households’ social capital has a significant impact on their income level, and the effect degree varies in different income levels