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Machine learning (ML) models have been applied to monthly streamflow forecasting in recent decades. In this study, forecasting skills of eight ML models are evaluated based on the Model Parameter Estimation Experiment (MOPEX) dataset. We consider two skill scores, i.e., the Nash–Sutcliffe efficiency (NSE) and the adjusted NSE (ANSE), and the latter is the skill score based on the interannual mean monthly value (MMV) as the reference (benchmark) model. Furthermore, NSE of the MMV model (NSEmmv) is used as a measure of the seasonality of monthly streamflow, as it is the ratio of variance explained by the MMV process. An important result is that forecasting skills of ML models for monthly streamflow are largely controlled by NSEmmv. Moreover, based on comparisons of different ML models, we have found that the selection of models is not a dominating factor impacting the final skill. Three key factors influencing NSE, i.e., NSEmmv, the base flow index (BFI) and the aridity index (AI), are explored in this paper. Specifically, NSEmmv impacts NSE directly and is the predominant factor; BFI influences the memory of the monthly streamflow and therefore influences NSE. The relationship between AI and NSE is much complex and indirect. Firstly, basins with higher AI tend to have lower NSEmmv, and this will lead to lower NSE; secondly, basins with higher AI tend to have lower BFI, which will also lead to lower NSE; thirdly, for a given BFI level, basins with higher AI tend to have higher memory and higher NSE. For ANSE, basins with AI between 1 and 2 show higher ANSE, which corresponds to higher autocorrelation coefficients.

Introduction Uterine fibroids are a common benign genital tumor disease in gynecological diseases. It is mainly a change in physical function caused by the growth of smooth muscle cells in the factor uterus. Modern medicine's treatment of this disease is based on the dependence of uterine fibroids on sex hormones. Treatment with antiprogestin and estrogen drugs can reduce the volume of fibroids or slow the rate of increase in volume, thereby achieving the goal of alleviating clinical symptoms. In order to meet the needs of the majority of women of childbearing age and to maintain fertility, acupuncture treatment of uterine fibroids has a broad prospect for development. Methods/design This study plans to select 60 cases that meet the corresponding selection criteria. According to the random principle, they will be divided into intervention group and control group, with 30 cases in each group. The general information, fibroid size, and TCM syndrome scores of the two groups of patients will be compared before treatment. In terms of treatment, the intervention group will be given acupuncture combined therapy; the control group will be given Chinese patent medicine. The treatment cycles in both groups will be three menstrual cycles. After the treatment is completed, the data of the relevant curative effect indicators are analyzed by using SPSS software to draw conclusions. Discussion We aim to provide higher evidence-based medical evidence for acupuncture treatment of uterine fibroids. Trial registration ClinicalTrials.gov, ChiCTR2000030438, Registered on March 01, 2020.

Correction for ‘Cu2O template synthesis of high-performance PtCu alloy yolk–shell cube catalysts for direct methanol fuel cells’ by Sheng-Hua Ye et al., Chem. Commun., 2014, 50, 12337–12340, DOI: 10.1039/C4CC04108A.

Set pair potential, indicates an identical-discrepancy-contrary trend of two sets discussed in the case of specific problems. This trend can show weak tendency of regional water environmental system vulnerability, consequently set pair potential has been used to analyze its driving factors. In traditional set pair, contrary degree is restricted since that contrary degree does not vanish is the necessary condition by definition, as a result that traditional set pair potential does not have general validity. Therefore taking advantage of exponential function to improve the traditional set pair potential, and a new definition of set pair exponential potential was proposed. Then an analysis model of driving factors of regional water environmental system vulnerability was established based on this new potential and the model was used to analyze the factors in Anhui province, China. Some results have been obtained that the driving factors of water environmental system vulnerability in Anhui province mainly include: degree of regional development level, per capita water resources, marsh area ratio, soil erosion area ratio, industrial wastewater standard discharge rate and the ratio of investment in water environmental governance (protection) to GDP.

Novel PtCu alloy yolk–shell cubes were fabricated via the disproportionation and displacement reactions in Cu2O yolk–shell cubes, and they exhibit significantly improved catalytic activity and durability for methanol electrooxidation.

According to the research status of the public buildings benefit evaluation, this thesis proposes that the evaluation should pay more attention to the comprehensive benefit. On this basis, a new evaluation model for the comprehensive benefit has been constructed by better using FAHP in this field, which has been proved by the Xuzhou Olympic Sports Center project. The research shows that applying FAHP to the public buildings benefit evaluation can make the result more reliable, which has good practicability and application value.

Central air-conditioning systems consume a lot of energy. Determining how to economize energy and enhance efficiency becomes urgently. In this article, the energy-saving measures of the central air-conditioning system are proposed from some aspects which include reasonable design, the momentum energy consumption, the hidden energy consumption, the new energy-saving technologies, etc.

Novel PtCu alloy yolk-shell cubes were fabricated via the disproportionation and displacement reactions in Cu2O yolk-shell cubes, and they exhibit significantly improved catalytic activity and durability for methanol electrooxidation.

The flood disaster is one of the most serious natural disasters. It is the important basis of making plan for flood control to assess flood losses accurately. The results of the common assessment methods are discrete values and low resolution which are applied widely at present. The research to more precise, more intuitive method of loss evaluation for flood disaster is the focus. The set pair analysis assessment model was established by the α-cut set of triangle fuzzy number A in this paper. The case study shows this method not only presents the concrete rank of flood lose, but also finds that the evaluating rank is a confidence interval; in addition, we can obtain priorities of different areas by the expectation and square difference method for priorities of interval numbers.

Benefit and loss matrix of uncertain decision-making analysis reflects both the objective information structure of uncertain decision-making problem and the risk information of benefit chance and loss chance faced by decision-maker. The transform vector consisted of the natural state weights is quantitative expression of uncertain decision-making rule adopted by decision-maker. The essential for resolving uncertain decision-making problem is how to transform benefit and loss matrix into compressed real vector with one dimension, where the biggest weight of the vector corresponds to the best action scheme. Now the information of benefit and loss matrix has been not mined sufficiently using the common methods for uncertain decision-making problems. Therefore in this paper, the whole difference weights of the natural states can be determined using projection pursuit method, the local difference weights of the natural states can be determined directly using information entropy and accelerating genetic algorithm based fuzzy analytic hierarchy process, and the two kinds of weights can be combined into comprehensive weights according to the minimum relative information entropy principle, which can form a new uncertain decision-making analysis method based on information entropy principles, named UDM-IEP for short. The application result show that the information of benefit and loss matrix can be mined more sufficiently using UDM-IEP than the common methods, that the decision-making information can be more provided by UDM-IEP than the common methods, that decision-maker can actively or safely choose the best scheme based on the comparison between of benefit chance risk and loss chance risk contained in the benefit and loss matrix, that UDM-IEP is both simple and general, that its computation result is objective and stability, and that UDM-IEP can be widely applied in theory and practice of systems engineering.