An empirical study on the status quo and influencing factors of College students' sense of gain from ideological and political theory courses —Taking the Conspectus of Chinese Modern History course as an example

Taking the Conspectus of Chinese Modern History Course as an example, this study adopts the method of empirical research to explore the status quo and influencing factors of College students' sense of gain from ideological and political theory courses.A sample of 831 undergraduate students in school has carried on the questionnaire survey, the difference comparison, multiple regression, structural equation model analysis are used for data analysis, and the results show that college students' overall sense of gain from the Conspectus of Chinese Modern History Course is good, and there is no significant difference in gender and nationality, but there is a significant difference in major. Social support, family rendering and school teaching have a significant impact on college students' sense of gain in the Conspectus of Chinese Modern History Course. According to the research results, a series of Suggestions are provided on how to improve college students' sense of gain from the Conspectus of Chinese Modern History Course.&nbsp

An Empirical Study on the Influencing Factors of University Students’ Sense of Gain in Ideological and Political Theory Course -- Take the Course of “Ideological and Moral Cultivation and Legal Basis”as An Example

The self-made questionnaire was administered to a random sample of 1000 undergraduates, the result of data analysis shows that the “Mechanism model of influencing factors on university students’ ‘Basic Course’  gain” proposed in this paper can partly explain the influence of personal, family, school and social factors on college students’ “Basic Course” acquisition; The factors of family, school and society are the external factors which affect the students’ sense of gain of“Basic Course”, and the personal factors are the internal factors which affect the students’ sense of gain of “Basic Course”; External factors act through internal factors. Based on that, this paper puts forward some suggestions and countermeasures to enhance the sense of gain of university students’“Basic courses”

Blow up of positive initial energy solutions for a wave equation with fractional boundary dissipation

AbstractIn this paper, we consider a strongly damped wave equation with fractional damping on part of its boundary and also with an internal source. Under some appropriate assumptions on the parameters, and with certain initial data, a blow-up result with positive initial energy is established

Painterly Image Harmonization using Diffusion Model

Painterly image harmonization aims to insert photographic objects into paintings and obtain artistically coherent composite images. Previous methods for this task mainly rely on inference optimization or generative adversarial network, but they are either very time-consuming or struggling at fine control of the foreground objects (e.g., texture and content details). To address these issues, we propose a novel Painterly Harmonization stable Diffusion model (PHDiffusion), which includes a lightweight adaptive encoder and a Dual Encoder Fusion (DEF) module. Specifically, the adaptive encoder and the DEF module first stylize foreground features within each encoder. Then, the stylized foreground features from both encoders are combined to guide the harmonization process. During training, besides the noise loss in diffusion model, we additionally employ content loss and two style losses, i.e., AdaIN style loss and contrastive style loss, aiming to balance the trade-off between style migration and content preservation. Compared with the state-of-the-art models from related fields, our PHDiffusion can stylize the foreground more sufficiently and simultaneously retain finer content. Our code and model are available at https://github.com/bcmi/PHDiffusion-Painterly-Image-Harmonization.Comment: Accepted by ACMMM 202

The Use of Fuzzy BackPropagation Neural Networks for the Early Diagnosis of Hypoxic Ischemic Encephalopathy in Newborns

Objective. To establish an early diagnostic system for hypoxic ischemic encephalopathy (HIE) in newborns based on artificial neural networks and to determine its feasibility. Methods. Based on published research as well as preliminary studies in our laboratory, multiple noninvasive indicators with high sensitivity and specificity were selected for the early diagnosis of HIE and employed in the present study, which incorporates fuzzy logic with artificial neural networks. Results. The analysis of the diagnostic results from the fuzzy neural network experiments with 140 cases of HIE showed a correct recognition rate of 100% in all training samples and a correct recognition rate of 95% in all the test samples, indicating a misdiagnosis rate of 5%. Conclusion. A preliminary model using fuzzy backpropagation neural networks based on a composite index of clinical indicators was established and its accuracy for the early diagnosis of HIE was validated. Therefore, this method provides a convenient tool for the early clinical diagnosis of HIE

Prevalence of workplace violence against healthcare workers: a systematic review and meta-analysis

We aim to quantitatively synthesise available epidemiological evidence on the prevalence rates of workplace violence (WPV) by patients and visitors against healthcare workers. We systematically searched PubMed, Embase and Web of Science from their inception to October 2018, as well as the reference lists of all included studies. Two authors independently assessed studies for inclusion. Data were double-extracted and discrepancies were resolved by discussion. The overall percentage of healthcare worker encounters resulting in the experience of WPV was estimated using random-effects meta-analysis. The heterogeneity was assessed using the I2 statistic. Differences by study-level characteristics were estimated using subgroup analysis and meta-regression. We included 253 eligible studies (with a total of 331 544 participants). Of these participants, 61.9% (95% CI 56.1% to 67.6%) reported exposure to any form of WPV, 42.5% (95% CI 38.9% to 46.0%) reported exposure to non-physical violence, and 24.4% (95% CI 22.4% to 26.4%) reported experiencing physical violence in the past year. Verbal abuse (57.6%; 95% CI 51.8% to 63.4%) was the most common form of non-physical violence, followed by threats (33.2%; 95% CI 27.5% to 38.9%) and sexual harassment (12.4%; 95% CI 10.6% to 14.2%). The proportion of WPV exposure differed greatly across countries, study location, practice settings, work schedules and occupation. In this systematic review, the prevalence of WPV against healthcare workers is high, especially in Asian and North American countries, psychiatric and emergency department settings, and among nurses and physicians. There is a need for governments, policymakers and health institutions to take actions to address WPV towards healthcare professionals globally

pT1-2 gastric cancer with lymph node metastasis predicted by tumor morphologic features on contrast-enhanced computed tomography

PURPOSETo investigate the value of tumor morphologic features of pT1-2 gastric cancer (GC) on contrast-enhanced computed tomography (CT) in assessing lymph node metastasis (LNM) with reference to histopathological results.METHODSEighty-six patients seen from October 2017 to April 2019 with pT1‐2 GC proven by histopathology were included. Tumor volume and CT densities were measured in the plain scan and the portal-venous phase (PVP), and the percent enhancement was calculated. The correlations between tumor morphologic features and the N stages were analyzed. The diagnostic capability of tumor volume and enhancement features in predicting the LN status of pT1-2 GCs was further investigated using receiver operating characteristic (ROC) analysis.RESULTSTumor volume, CT density in the PVP, and tumor percent enhancement in the PVP correlated significantly with the N stage (rho: 0.307, 0.558, and 0.586, respectively). Tumor volumes were significantly lower in the LNM− group than in the LNM+ group (14.4 mm3 vs. 22.6 mm3, P = 0.004). The differences between the LNM− and LNM+ groups in the CT density in the PVP and the percent enhancement in the PVP were also statistically significant (68.00 HU vs. 87.50 HU, P < 0.001; and 103.06% vs. 179.19%, P < 0.001, respectively). The area under the ROC curves for identifying the LNM+ group was 0.69 for tumor volume and 0.88 for percent enhancement in the PVP, respectively. The percent enhancement in the PVP of 145.2% and tumor volume of 17.4 mL achieved good diagnostic performance in determining LNM+ (sensitivity: 71.4%, 82.1%; specificity: 91.4%, 58.6%; and accuracy: 84.9%, 66.3%, respectively).CONCLUSIONTumor volume and percent enhancement in the PVP of pT1-2 GC could improve the diagnostic accuracy of LNM and would be helpful in image surveillance of these patients

Regulatory network and interplay of hepatokines, stellakines, myokines and adipokines in nonalcoholic fatty liver diseases and nonalcoholic steatohepatitis

Fatty liver disease is a spectrum of liver pathologies ranging from simple hepatic steatosis to non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), and culminating with the development of cirrhosis or hepatocellular carcinoma (HCC). The pathogenesis of NAFLD is complex and diverse, and there is a lack of effective treatment measures. In this review, we address hepatokines identified in the pathogenesis of NAFLD and NASH, including the signaling of FXR/RXR, PPARα/RXRα, adipogenesis, hepatic stellate cell activation/liver fibrosis, AMPK/NF-κB, and type 2 diabetes. We also highlight the interaction between hepatokines, and cytokines or peptides secreted from muscle (myokines), adipose tissue (adipokines), and hepatic stellate cells (stellakines) in response to certain nutritional and physical activity. Cytokines exert autocrine, paracrine, or endocrine effects on the pathogenesis of NAFLD and NASH. Characterizing signaling pathways and crosstalk amongst muscle, adipose tissue, hepatic stellate cells and other liver cells will enhance our understanding of interorgan communication and potentially serve to accelerate the development of treatments for NAFLD and NASH

Tooth loss and the risk of cognitive decline and dementia: A meta-analysis of cohort studies

IntroductionEpidemiological studies have shown that tooth loss may be associated with an increased risk of cognitive decline and dementia. However, some results do not show a significant association. Therefore, we performed a meta-analysis to evaluate this association.MethodsRelevant cohort studies were searched in PubMed, Embase, Web of Science (up to May 2022), and the reference lists of retrieved articles. The pooled relative risk (RR) and 95% confidence intervals were computed using a random-effects model (CI). Heterogeneity was evaluated using the I2 statistic. Publication bias was evaluated using the Begg's and Egger's tests.ResultsEighteen cohort studies met the inclusion criteria. Original studies with 356,297 participants with an average follow-up of 8.6 years (ranging from 2 to 20 years) were included in this study. The pooled RRs of tooth loss on dementia and cognitive decline were 1.15 (95% CI: 1.10–1.20; P &lt; 0.01, I2 = 67.4%) and 1.20 (95% CI: 1.14–1.26; P = 0.04, I2 = 42.3%), respectively. The results of the subgroup analysis showed an increased association between tooth loss and Alzheimer's disease (AD) (RR = 1.12, 95% CI: 1.02–1.23) and vascular dementia (VaD) (RR = 1.25, 95% CI: 1.06–1.47). The results of the subgroup analysis also showed that pooled RRs varied by geographic location, sex, use of dentures, number of teeth or edentulous status, dental assessment, and follow-up duration. None of the Begg's and Egger's tests or funnel plots showed evidence of publication bias.DiscussionTooth loss is associated with a significantly increased risk of cognitive decline and dementia, suggesting that adequate natural teeth are important for cognitive function in older adults. The likely mechanisms mostly suggested include nutrition, inflammation, and neural feedback, especially deficiency of several nutrients like vitamin D