公众食品药品网络谣言和虚假宣传辨识能力调查——以贵州省某少数民族自治地区为例

目的 了解公众对网络食品药品谣言信息及虚假宣传甄别能力和行为态度，探索防范谣言传播、维护社会稳定的有效措施和途径。方法 采用随机抽样研究方法，对贵州省某少数民族自治州公众开展食品药品网络谣言及虚假宣传辨识能力、行为态度问卷调查。结果 当地公众食品药品网络谣言及虚假宣传辨识能力总体较低，经济发展落后地区的青少年人群对网络谣言及虚假宣传的辨识能力较弱。大部分公众处理网络食品药品安全信息较为理性，更愿意通过国家监管部门权威网站了解信息，基本具备了确认信息真实性的主观意识，但辟除谣言的行动能力不高。结论 地方党委政府及有关部门应加强食品药品网络谣言和虚假宣传治理，加大当地谣言及虚假宣传的监测和系统性分析研究，有针对性、预判性地进行治理和科普宣传。     

Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

Methodology for dependence-based integrated constitutive modelling: An illustrative application to SiCp/Al composites

In industrial forming and machining process, the large plastic deformation of material takes place in wide loading ranges of strain-rate and forming temperature. A satisfactory modelling of quasi-static and dynamic material behaviors is of great importance for understanding physical process and processes optimization. A dependence-based integrated methodology, together with an improved weighted multi-objective parameter identification strategy is presented for the development of phenomenological constitutive model and the parameter identification using experimental data from quasi-static and dynamic tests with instantaneous strain rate variations and plastic strain-related temperature changes. The improved multi-objective parameter identification model is reformulated by introducing three weighting factors for valuing different measure errors and fit standard errors in individual objective function corresponding to each test, considering the sampling point number and active material parameter number under different loading conditions, and balancing optimization opportunity of quasi-static and dynamic sub-objective functions. The methodology is verified for feasibility through illustrative constitutive identification for SiC_p/Al composites. This may provide a methodology of constitutive modelling for predicting material behaviors in quasi-static and dynamic modes equally well.     

Minimization of the Theoretical Error of Input Parameters for a Vapor Permeation Apparatus

All input experimental errors for membrane flux determination were analyzed. The overall error in pressure did not largely influence the determination of membrane flux. The main contribution to errors was ascribed to flow meters and membrane thickness. The choice of an optimal operational range for input parameters led to elimination of at least 2/3 of the theoretical relative error for subsequent evaluation of the permeability of individual species. This is especially valuable for low‐permeable membranes, whereas a very low relative theoretical error can be obtained in the case of highly permeable materials.     

Effects of the ARCS-V-based motivational strategies on online learners' academic performance,motivation, volition,and course interest

This exploratory experimental study investigates the impact of motivational strategies based on the Attention, Relevance, Confidence, Satisfaction, and Volition (ARCS-V) model on online learners' academic performance, motivation, volition, and course interest. The research was conducted over an 11-week semester with 122 undergraduate online learners within two groups. One group received a traditional e-course, while the other group was offered the course with extra motivational strategies derived from the ARCS-V model. The results revealed that the group who used motivational strategies showed significantly higher gains in motivation, academic performance, and course interest scores. However, there were no significant differences between the groups regarding the volition. Furthermore, the motivation and interest variables were measured with Attention, Relevance, Confidence, and Satisfaction subscales of the ARCS-V model. In terms of interest variable, there was only a statistically significant difference on the Attention subscale. Regarding motivation variable, the results also showed a statistically significant difference on the attention, confidence, and satisfaction subsections of the ARCS-V model. The findings of the present study offer insights into ARCSV model-based research by examining the effects of the model as a valid and reliable framework for online learning environments. The implications and directions for future research are then discussed.     

上榆泉煤矿煤泥水多参数在线检测系统应用研究

针对上榆泉煤矿煤泥水性质参数人工检测周期长、误差大、滞后性严重的问题,采用多参数传感器和PLC,开发了煤泥水多参数在线检测系统。经过8 h稳定运行,平均结果显示该厂煤泥水参数为pH值为7.71、浓度9.45%、中值直径(D50)39.56μm、流量2 440 m3/h、水质硬度428.94 mg/L,与人工检测结果相一致。应用结果表明,该检测系统能够实现煤泥水多参数在线监测和数据分析功能,使煤泥水的处理更高效。     

Optimal parameter estimation for PEMFC using modified monarch butterfly optimization

The present study develops a new optimization method called monarch butterfly optimization algorithm for optimal parameter estimation of the polymer electrolyte membrane fuel cell (PEMFC). After designing the proposed methodology, it is implemented to 250 MW PEMFC stack under different operating conditions to show the system efficiency and the results are compared with some state-of-the-art methods including Grass Fibrous Root Optimization Algorithm, hybrid Teaching Learning Based Optimization-Differential Evolution Algorithm, and the basic MBO algorithm. Two operational conditions in 3/5 bar and 80°C and 2.5/3 bar, 70°C are used for model verification. The main idea is to minimize the sum of square error (SSE) between the estimated and the actual data. Simulation results in the first condition give an SSE of value 7.277667729 with 9.28434e−16 SD value and in the second condition, an SSE of value 4.52810115 with 0.043581628 standard deviations has been reached as the minimum value among the other compared methods that indicate the accuracy and the robustness of the suggested method toward the analyzed methods. The algorithm also gives a convergence speed of 540 iterations and 370 iterations for conditions 1 and 2, respectively that are the fastest in the study.     

Identification of hydrogen permeability parameters of membrane materials in an aggregated experiment

The study of the hydrogen permeability of materials for membrane-based separation/purification technologies employs a variety of experimental methods with their own specific features, advantages and shortfalls. The method of penetration with vacuum pumping allows determining the diffusion coefficient from so-called lag time. The accuracy of the estimation depends on the degree of proximity to the DLR (diffusion limited regime) mode. The method of “communicating vessels” is more sensitive to surface processes. The thermal desorption (TDS) technique permits “scanning” the material dynamically across a wide range of temperatures. “Separate” application of these methods leads to a situation where the materials studied are in fact somewhat different (for example, due to different impacts on the surface), and significant differences in parameter estimates ensue. This paper suggests and implements a technique for a combined three-stage ‹‹penetration (with and without vacuum pumping)+TDS›› experiment and the corresponding mathematical toolkit. The informative capacity of the experiments and the accuracy of the estimation of hydrogen permeability parameters (adsorption, dissolution, diffusion and desorption) of the membrane materials under study are thus enhanced.