Research on Relationships between the Pigment of Dunhuang Mogao Grottoes Frescoes and Ecological Microorganism

Dunhuang Mogao Grottoes is one of the largest art treasures in the world. She has a large number of murals, sculptures, beautiful and vivid; There are precious Buddhist scriptures, documents, noble and elegant. Spanning more than 1,600 years, the Mogao Grottoes show the world the extensive and profound Chinese culture with a long history. But over time, the murals in the Mogao Grottoes have also changed a lot. Thousands of years of wind and rain erosion, changes in the surrounding environment, and the influence of various biological communities have caused serious color changes and fading of murals in Mogao Grottoes. To slow down the color change of Dunhuang frescoes, protection measures should be taken from the perspective of ecological microorganisms. At present, Cladosporium, Planococcus, Phoma, Chaetomium, and other strains have caused serious discoloration or discoloration of murals to a certain extent. This paper studies the main color of Dunhuang frescoes, red, and summarizes the discoloration factors and mechanism of red lead. On this level, one should try to keep the murals and control the indoor temperature. Humidity, people, and other factors slow the fading of the murals. But these are often insufficient to protect the integrity of the murals, so we have conducted a review of the literature to provide an updated overview of the available evidence on the subject

Multi-category Comparative Analysis of Factors Affecting E-commerce Sales

With the continuous development of e-commerce, more and more types of goods are sold online, so merchants should develop different sales strategies for different types of goods. This paper firstly selects 15 variables to build a stepwise regression model. In the analysis of influencing factors on sales of products in different categories, we find that there are significant differences in the impact of the number of appended reviews and pictures reviews on the sales of utilitarian and hedonic products. In the analysis of influencing factors on sales of products in the same category, we find that the factors influencing the sales of different clothing products are also different to some extent. At last, we put forward some suggestions on adjusting price and title length, and writing product details. This paper is more detailed in variable selection and product classification than some previous studies. It is meaningful for merchants to optimize sales plans and improve product sales

Understanding Continuance Intention to Use Mobile Fitness Services: The Roles of Technological Characteristics and Network Effects

Mobile fitness platforms are effective in promoting healthy behaviors but these platforms generally suffer from low retention rates. It is necessary to study how to retain users of mobile fitness platforms. Based on customer value theory and Socio-technical approach, this study proposed a theoretical model to study the factors that affect users’ continuance intention to use mobile fitness platforms from a holistic perspective. A total of 320 valid questionnaires were collected to verify the model. The results indicate that utilitarian value and hedonic value are positively related to continuance intention. Social ties are negatively related to continuance intention. Meanwhile, it is found that technological characteristics have significant positive influences on utilitarian value, hedonic value and social ties. Network effects have significant positive influences on hedonic value and social ties. These findings extend our understanding of users’ continued usage of mobile fitness platforms and provide practical implications for mobile fitness service providers

SFCDecomp: Multicriteria Optimized Tool Path Planning in 3D Printing using Space-Filling Curve Based Domain Decomposition

We explore efficient optimization of toolpaths based on multiple criteria for large instances of 3D printing problems. We first show that the minimum turn cost 3D printing problem is NP-hard, even when the region is a simple polygon. We develop SFCDecomp, a space filling curve based decomposition framework to solve large instances of 3D printing problems efficiently by solving these optimization subproblems independently. For the Buddha model, our framework builds toolpaths over a total of 799,716 nodes across 169 layers, and for the Bunny model it builds toolpaths over 812,733 nodes across 360 layers. Building on SFCDecomp, we develop a multicriteria optimization approach for toolpath planning. We demonstrate the utility of our framework by maximizing or minimizing tool path edge overlap between adjacent layers, while jointly minimizing turn costs. Strength testing of a tensile test specimen printed with tool paths that maximize or minimize adjacent layer edge overlaps reveal significant differences in tensile strength between the two classes of prints.Comment: Minor edits to incorporate reviewers' comments. Published in IJCG

The Role of Internet Search Index for Tourist Volume Prediction Based on GDFM Model

Tourist volume is increasing with the expansion of the scale of tourism, and improving the prediction of tourist volume is helpful for tourism managers to make decisions. Internet search index can be applied to predict the behavior of users, which is widely used in the study of tourist volume prediction and infectious disease prediction. However, the high dimension and correlation of Internet search index tends to reduce the accuracy of the models, which increases the average prediction error of common time-series models. The dynamic factor model (DFM) proposed in our study can be used to solve the problem. This study selects 23 variables and introduces the generalized dynamic factor model (GDFM) to predict tourist volume. The model cannot only reduce the dimensionality of high-dimensional Internet search index data, but also reflects the dynamic correlation between Internet search index data. The results show that the prediction accuracy is improved in our method, and the prediction accuracy of tourist volume is improved by over 10%, with an average error of only 4.3% when compared with the neural network (NN) model. Our study not only provides implications for decision-makers to predict tourist volume timely and accurately, but also helps companies understand tourist’ behavior and make the best strategic decisions

Spatially and Temporally Resolved Measurements of NO Adsorption/Desorption over NOx‐Storage Catalyst

The two‐dimensional (2D) temporal evolution of the NO‐concentration over a NOx‐storage catalyst is investigated in situ with planar laser‐induced fluorescence (PLIF) in an optically accessible parallel wall channel reactor. Signal accumulated phase‐correlated 2D‐recordings of repetitive adsorption/desorption cycles are obtained by synchronizing the switching of the NO gas flow (on/off) with the laser and detection system, thereby significantly increasing the signal‐to‐noise ratio. The gas compositions at the reactor outlet are additionally monitored by ex‐situ analytics. The impacts of varying feed concentration, temperature and flow velocities are investigated in an unsteady state. Transient kinetics and the mass transfer limitations can be interpreted in terms of the NO concentration gradient changes. The technique presented here is a very useful tool to investigate the interaction between surface kinetics and the surrounding gas flow, especially for transient catalytic processes

Bibliometric and visualization analysis of research trend in mental health problems of children and adolescents during the COVID-19 pandemic

ObjectivesTo analyze the evolution of research on children and adolescents mental health issues during COVID-19 pandemic and discuss research hotspots and cutting-edge developments.MethodsThe literature obtained from the web of science core collection as of June 28, 2022, was analyzed using Citespace, VOSviewer bibliometric visualization mapping software.ResultsA total of 6,039 relevant papers were found, of which 5,594 were included in the study. The number of literatures is growing since 2020; and the country, institution, and journal publications were analyzed. The co-citation analysis shows that there are more research articles among the highly cited articles and a lack of systematic reviews that use critical thinking for review. In the cluster analysis, mental health and life change were the most representative. The timeline view of the keywords shows that Online learning (#0), Public health (#1), and Mental health (#2) are the three largest clusters and shows the change over time.ConclusionThis study helped analyze the mental health of children and adolescents during the COVID-19 pandemic and identified hot trends and shortcomings, which are important references for the theoretical basis of future research and decision making and technical guidance for systematic reviews