The Impact of Trust and Collaboration Pattern on Farmers’ Learning Willingness and Enterprises’ Knowledge Transfer Intension: Evidence of China

The purpose of this paper is to explore the impact of trust and collaboration pattern on the learning willingness of the farmers and the enterprises’ knowledge transfer intension. The survey and literature research methodology are employed. 176 valid questionnaires were collected and OLS regression analysis is applied to answer whether trust and collaboration pattern have an impact on the learning willingness of the farmers and the enterprises’ knowledge transfer intension. The results indicate that the trust between the farmers and enterprise affects the learning willingness of the farmers and the enterprises’ knowledge transfer intension positively. The collaboration pattern affects the enterprises’ knowledge transfer intension significantly. The tighter the cooperation between the farmers and enterprise, the stronger the enterprises’ knowledge transfers intension is. The farmers’ learning willingness has no significant difference under different collaboration patterns

Variational Iteration Method for Solving the Generalized Degasperis-Procesi Equation

We introduce the variational iteration method for solving the generalized Degasperis-Procesi equation. Firstly, according to the variational iteration, the Lagrange multiplier is found after making the correction functional. Furthermore, several approximations of un+1(x,t) which is converged to u(x,t) are obtained, and the exact solutions of Degasperis-Procesi equation will be obtained by using the traditional variational iteration method with a suitable initial approximation u0(x,t). Finally, after giving the perturbation item, the approximate solution for original equation will be expressed specifically

Self-Supervised Texture Image Anomaly Detection By Fusing Normalizing Flow and Dictionary Learning

A common study area in anomaly identification is industrial images anomaly detection based on texture background. The interference of texture images and the minuteness of texture anomalies are the main reasons why many existing models fail to detect anomalies. We propose a strategy for anomaly detection that combines dictionary learning and normalizing flow based on the aforementioned questions. The two-stage anomaly detection approach already in use is enhanced by our method. In order to improve baseline method, this research add normalizing flow in representation learning and combines deep learning and dictionary learning. Improved algorithms have exceeded 95$\%$ detection accuracy on all MVTec AD texture type data after experimental validation. It shows strong robustness. The baseline method's detection accuracy for the Carpet data was 67.9%. The article was upgraded, raising the detection accuracy to 99.7%

Tourism impact on gender and minority equality: comparison of survey, census, and industry data

Tourism is widely credited as an economic driver for communities, but the role of tourism industry in promoting social and cultural human development goals is less researched and frequently disputed. The majority of existing studies are following the coarse scale. The goal of this study is to investigate the relationship between the development of tourism sector and progress towards the UNWTO equality goals on a fine scale of one US state with the objective of comparing the available indicators of gender and minority equality on a county basis. The study combines the objective data from industry and the US census with survey data on local community perceptions on tourism industry. We found that overall the equality indicators follow the Kuznets type U-shaped model. This result is supported with the survey of public perceptions on tourism which suggests a positive outlook of the local communities on tourism industry effects on gender and race equality. This positive outlook is however not fully shared by women, Black minority, and the youngest population, suggesting a need for future studies those groups

Spatiotemporal Characteristics of Particulate Matter and Dry Deposition Flux in the Cuihu Wetland of Beijing

In recent years, the rapid development of industrialization and urbanization has caused serious environmental pollution, especially particulate pollution. As the “Earth’s kidneys,” wetland plays a significant role in improving the environmental quality and adjusting the climate. To study how wetlands work in this aspect, from the early autumn of 2014 to 2015, we implemented a study to measure the PM concentration and chemical composition at three heights (1.5, 6, and 10 m) during different periods (dry, normal water, and wet periods) in the Cuihu wetland park in Beijing for analyzing the dry deposition flux and the effect of meteorological factors on the concentration. Results indicated that (1) the diurnal variations of the PM2.5 and PM10 concentrations at the three heights were similar in that the highest concentration occurred at night and the lowest occurred at noon, and the daytime concentration was lower than that at night; (2) the PM2.5 and PM10 concentrations also varied between different periods that wet period \u3e normal water period \u3e wet period, and the concentration at different heights during different periods varied. In general, the lowest concentration occurred at 10 m during the dry and normal water periods, and the highest concentration occurred at 1.5 m during the wet period. (3) SO4 2− , NO3 − , and Cl− are the dominant constituents of PM2.5, accounting for 42.22, 12.6, and 21.56%, respectively; (4) the dry depositions of PM2.5 and PM10 at 10 m were higher than those at 6 m, and the deposition during the dry period was higher than those during the wet and normal water periods. In addition, the deposition during the night-time was higher than that during the daytime. Moreover, meteorological factors affected the deposition, the temperature and wind speed being negatively correlated with the deposition flux and the humidity being positively correlated. (5) The PM10 and PM2.5 concentrations were influenced by meteorological factors. The PM2.5 and PM10 concentrations were negatively correlated with temperature and wind speed but positively correlated with relative humidity

The Association between Breakfast Skipping and Body Weight, Nutrient Intake, and Metabolic Measures among Participants with Metabolic Syndrome

The effect of skipping breakfast on health, especially in adults, remains a controversial topic. A secondary data analysis was conducted to examine associations between breakfast eating patterns and weight loss, nutrient intake, and metabolic parameters among participants with metabolic syndrome (MetS) (n = 240). Three randomly selected 24-h dietary recalls were collected from each participant at baseline and at the one-year visit. Skipped breakfast was seen in 32.9% at baseline and in 17.4% at the one-year visit, respectively. At baseline, after adjustment for demographics and physical activity, participants who ate breakfast had a higher thiamin, niacin, and folate intake than did breakfast skippers (p \u3c 0.05); other selected parameters including body weight, dietary quality scores, nutrient intake, and metabolic parameters showed no significant differences between the two groups (p ≥ 0.05). From baseline to one year, after adjustment for covariates, mean fat intake increased by 2.7% (95% confidence intervals (CI): −1.0, 6.5%) of total energy in breakfast skippers in comparison to the 1.2% decrease observed in breakfast eaters (95% CI: −3.4, 1.1%) (p = 0.02). Mean changes in other selected parameters showed no significant differences between breakfast skippers and eaters (p \u3e 0.05). This study did not support the hypothesis that skipping breakfast has impact on body weight, nutrient intakes, and selected metabolic measures in participants with MetS

Tacit Knowledge Based on the Cultivation of Innovative Ability for Graduate Students

Poland's tacit knowledge theory believes that tacit knowledge exists of coding, individuality and practicality, as well as the relative priority of explicit knowledge in theory. Study on the tacit knowledge theory to improve the level of postgraduate education, optimize the structure of smart graduate students, raising graduate students' innovative ability is of important guiding significance. Including postgraduates' innovative ability of the tacit knowledge based on the reasonable knowledge structure, creativity, creative thinking, creative skills, and so on. This perspective development of postgraduates’ innovative ability through interdisciplinary integration, build up the academic atmosphere, enhance good research practice, build harmonious relationship between teachers and students to be achieved.Poland's tacit knowledge theory believes that tacit knowledge exists of coding, individuality and practicality, as well as the relative priority of explicit knowledge in theory. Study on the tacit knowledge theory to improve the level of postgraduate education, optimize the structure of smart graduate students, raising graduate students' innovative ability is of important guiding significance. Including postgraduates' innovative ability of the tacit knowledge based on the reasonable knowledge structure, creativity, creative thinking, creative skills, and so on. This perspective development of postgraduates’ innovative ability through interdisciplinary integration, build up the academic atmosphere, enhance good research practice, build harmonious relationship between teachers and students to be achieved

Involvement of TNF-alpha and IL-10 in breast cancer and patient survival

Purpose: To investigate the involvement of tumor necrosis factor α (TNF-α) and interleukin 10 (IL-10) in the pathogenesis of breast cancer in vivo as well as the activity of ten Chinese herbal compounds in human breast cancer (MCF-7) cell proliferation in vitro.Methods: In the in vivo study, the association of serum TNF-α and IL-10 with breast cancer cell invasiveness and prognosis was determined in female patients (n = 192) with breast cancer, while in the in vitro study, ten herbal Chinese compounds were screened for their effectiveness against MCF-7 cells. The levels of TNF-α, IL-10, estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER2/neu) were assayed using their respective enzyme-linked immunosorbent assay (ELISA) kits. Molecular docking was used to determine the lead compound(s) that can effectively inhibit TNF-α and IL-10.Results: Raised serum levels of TNF-α and IL-10 were significantly associated with breast cancer cell invasiveness and poor prognosis (p < 0.05). Moreover, there was a strong association between breast cancer prognosis and the expression levels of ER, PR and HER2/neu. Serum TNF-α and IL-10 levels were significantly elevated in stages II and III patients and in those with lymph node metastasis. Treatment of MCF-7 cells with the herbal compounds significantly reduced the synthesis and release of TNF-α and IL-10 (p < 0.05). The results of molecular docking showed that baicalein and oridonin significantly inhibited TNF- α and IL-10. The two herbal compounds had the highest docking scores for inhibition of cytokines, as well as favorable interaction energies.Conclusion: These results indicate that TNF-α and IL-10 are involved in the pathogenesis of breast cancer, and that baicalein and oridonin effectively inhibit the proliferation of the cells. Keywords: Baicalein, Breast cancer, Interleukin 10, Oridonin, Tumor necrosis factor alph