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This paper aims to consider numerical simulation for radionuclide transport calculations in geological radioactive waste repository.

The nonlinear two-point flux approximation is used to discretize the diffusion flux and has a fixed stencil. The cell-vertex unknowns are applied to define the auxiliary unknowns and can be interpolated by the cell-centered unknowns. The approximation of convection flux is based on the second-order upwind method with a slope limiter.

Numerical results illustrate that the positivity-preserving is satisfied in solving this convection-diffusion system and has a second-order convergence rate on the distorted meshes.

A new positivity-preserving nonlinear finite volume scheme is proposed to simulate the far-field model used in the geological radioactive waste repository. Numerical results illustrate that the positivity-preserving is satisfied in solving this convection-diffusion system and has a second-order convergence rate on the distorted meshes.

The purpose of this study is to examine the strategies used by consumers to control themselves in the Singles’ Day promotion. It also examines how promotion and social influence affect consumers’ purchase behavior and post-purchase evaluation.

A mixed methods approach including a quantitative study (N = 480) and a follow-up qualitative study (N = 35) was conducted to verify the hypotheses and provide deeper insights.

This study demonstrates that consumers allocate in-store slack in shopping budgets to restrict unplanned purchases and in-store slack is positively related to post-purchase evaluation. Social influence, which helps consumers rationalize purchase decisions, has positive effects on planned purchases and post-purchase evaluation. Both promotion strength and promotion range moderate the relationship between in-store slack and unplanned purchases.

Most studies investigate how promotion designs affect consumers’ in-store decision-making. This study focuses on the Singles’ Day promotion in China and examines the tactics consumers use to control purchase behavior in the promotion.

Three types of PbTe samples, e.g. nanoparticles, nanowires and bulk ingots, have been prepared. The investigation of the Seebeck coefficient of PbTe nanoparticles and nanowires clearly shows the sign change in the temperature range of 575~650 K, which is not observed for bulk ingots. Unfortunately, this temperature range is within the proposed operation temperature range for thermoelectric devices using PbTe and hence, such a change will affect their proper performance. The observed sign change of Seebeck coefficient is not simply caused by the composition variation at high temperature. It is mainly attributed to the extrinsic-to-intrinsic-semiconductor transition for PbTe nanocrystals due to the competing factors between quantum size effect increasing band gap and self-purification process decreasing their charge carrier concentration, which shift the transition point of nanocrystals to lower range as compare to that of bulk samples. Thus, such phenomenon should be considered carefully in the design of thermoelectric devices using semiconductor nanocrystals, which have attracted much attention recently.

Smoke and dust emissions from industrial furnaces can do great harm to the environment and human health. This paper aims to analyze the morphology, diameter and elements of the submicron particles from the furnace flues and the nearby ambient air by using two typical industrial furnaces, the sintering furnace and the electric furnace.

Two typical industrial furnaces, the sintering furnace and the electric furnace, were chosen in this study, to analyze the morphology, diameter and elements of the submicron particles from the furnace flues and the near-by ambient air.

The results show that the particles from the two furnaces are mainly in the small sizes of 0.3-0.6 μm. Particles from sintering plant flue are mainly spherical and rich in K and Cl, whereas those from the electric plant flue are mainly particles rich in metal elements, such as Zn and Fe, and have different morphology.

The particles in the atmosphere nearby the two furnaces contain aged particles from the flue, lots of spherical particles, rectangle particles and various aggregations. The elements of those particles are complex.

In order to improve the engine reliability and efficiency, an effective way is to reform the turbine blade tip conformation. The paper aims to discuss this issue.

The present research provides several novel tip-shaping structures, which are considered to control the blade tip loss. Four different tip geometries have been studied: flat tip, squealer tip, flat tip with streamwise ribs and squealer tip with streamwise ribs. The tip heat transfer and leakage flow are both analyzed in detail, for example the tip heat transfer coefficient, tip flow and local pressure distributions.

The results show that the squealer seal and streamwise rib can reduce the tip heat transfer and leakage loss, especially for the squealer tip with streamwise ribs. The tip and near-tip flow patterns at the different locations of axial chord reflect that both the squealer seal and streamwise rib structure can control the tip leakage flow loss. In addition, the analysis of the aerodynamic parameters (the static pressure and turbine efficiency) also indicates that the squealer tip with streamwise ribs obtains the highest adiabatic efficiency with an increase of 2.34 percent, compared with that of the flat tip case.

The analysis of aerothermal and dynamic performance can provide a reference for the blade tip design and treatment.

This study aims to focus on the submicron particles (with diameter of 0.2-1.0 μm) of the ambient air from a coal-fired power plant. A systematic examination of their morphology, particle size and chemical element will be analyzed, so as to provide more scientific information and theoretical basis for the formation and control method of inhalable particles, as well as data support for environmental impact and ecological effects assessments.

In this paper, the morphology, size distribution and elemental characteristics of submicron particles from ambient air of a coal-fired power plant are studied by single particle analysis.

The results show that atmospheric particles in coal-fired power plant are mainly spherical particles, and most of them are soot aggregates adhered or coated with other particles with few rectangle particles. The particles collected in the afternoon and evening are mainly of spherical particles, and small-sized particles collected in the morning are mainly spherical ones, while the overall concentration is larger than that of the spherical particles in the size range above 0.5 μm. The results indicated that the larger-sized spherical particles have a lower concentration.

Coal-fired power plants are still the main supply of electricity in China, but the inhalable particles, especially sub-micron particles (0.1-1.0 μm) cannot be effectively captured by the dust removal device from the coal-fired power plant. Thus, a large amount of inhalable particles is emitted into the atmosphere, becoming the major air pollutants in China.

The purpose of this paper is to explore the features of health misinformation on social media sites (SMSs). The primary goal of the study is to investigate the salient features of health misinformation and to develop a tool of features to help users and social media companies identify health misinformation.

Empirical data include 1,168 pieces of health information that were collected from WeChat, a dominant SMS in China, and the obtained data were analyzed through a process of open coding, axial coding and selective coding. Then chi-square test and analysis of variance (ANOVA) were adopted to identify salient features of health misinformation.

The findings show that the features of health misinformation on SMSs involve surface features, semantic features and source features, and there are significant differences in the features of health misinformation between different topics. In addition, the list of features was developed to identify health misinformation on SMSs.

This study raises awareness of the key features of health misinformation on SMSs. It develops a list of features to help users distinguish health misinformation as well as help social media companies filter health misinformation.

Theoretically, this study contributes to the academic discourse on health misinformation on SMSs by exploring the features of health misinformation. Methodologically, the paper serves to enrich the literature around health misinformation and SMSs that have hitherto mostly drawn data from health websites.

Mobile Applications (App) privacy has become a prominent social problem. Compared with privacy concerns, this study examines a relatively novel concept of privacy fatigue and explores its effect on the users’ intention to disclose their personal information via mobile Apps. In addition, the personality traits are proposed as antecedents that will induce the personal perception of privacy fatigue and privacy concerns differently.

Data were collected from 426 respondents. Structure equation modeling was used to test the hypotheses.

The findings describe that App users’ intention toward personal information disclosure is determined by privacy fatigue and privacy concerns, but the former has a greater impact. With minor exceptions, the two factors are also influenced by different personality traits. Specifically, neuroticism has positive effects on privacy fatigue, but agreeableness and extraversion have presented the opposite results on the two variables.

This research is very scarce to examine the joint effects of privacy fatigue, privacy concerns and personality traits on App users’ disclosing intention. In doing so, these results will be of benefit to App providers and platform managers and can be the basis for a variety of follow-up studies.

While previous research just focuses on privacy concerns, this study explores the critical roles of privacy fatigue and opens up a new avenue of emotion-attitude analysis that can further increase the specificity and richness of users’ privacy research. Additionally, implications for personality traits as antecedents in the impact of App users’ privacy emotions and attitudes are discussed.

The emergence of a coronavirus disease 2019 (COVID-19) epidemic has had a tremendous impact on the world, and the characteristics of its evolution need to be better understood.

To explore the changes of cases and control them effectively, this paper analyzes and models the fluctuation and dynamic characteristics of the daily growth rate based on the data of newly confirmed cases around the world. Based on the data, the authors identify the inflection points and analyze the causes of the new daily confirmed cases and deaths worldwide.

The study found that the growth sequence of the number of new confirmed COVID-19 cases per day has a significant cluster of fluctuations. The impact of previous fluctuations in the future is gradually attenuated and shows a relatively gentle long-term downward trend. There are four inflection points in the global time series of new confirmed cases and the number of deaths per day. And these inflection points show the state of an accelerated rise, a slowdown in the rate of decline, a slowdown in the rate of growth and an accelerated decline in turn.

This paper has a certain guiding and innovative significance for the dynamic research of COVID-19 cases in the world.

The purpose of this paper is to discuss the animal diet problem in grey environment which is adapted to the real situations. In particular, a new approach to solve these problems is proposed.

With the objective to produce the least-cost diet, in the traditional model for optimizing the diet problem, the price of foods, the nutrients requirements and the necessity of foods requirement have been considered as grey interval numbers. Grey linear programming approach has been employed to solve the grey diet problem. Grey linear programming with flexibility in selection of the coefficients can be more effective for solving the diet problems. In this research, only the positioned method has been used. The grey diet model is solved by using GAMS software based on the positioned method.

The main contribution of this work is to introduce a new model in the practical case that is concerned with diet problem under a kind of uncertainty environment and furthermore, proposing a novel method to solve the formulated problem. In this way, using a grey model and applying all restrictions, the least cost for one kilogram of total mixed ration was 6,893-10,163 Rials, and at this level, cow’s nutrient requirement was met. Based on the numerical examination, which was done on the real case, the achieved results have showed that the uncertainty of foods requirement and nutrients requirements had slight effect on the animal budget diet.

This problem must be viewed from another perspective because of the uncertainty regarding the amount of nutrients per unit of foods and the diversity of animals’ daily needs to receive them. In particular, a new method to optimize the fully mixed diet of lactating cows in early lactation that are readily available in the northeast of Iran in uncertainty environment has been proposed.