The Democratic “Globalization” and “Localization” Under the Culture Diversification

Political culture is a set of political attitudes, convictions, and emotions that prevail in a special period for a nationality, which influences the actions of the various political actors and the democratic process of a country. In the global era, the different nationalities and areas still maintain their own culture, exploring the suitable developing routes and having formed different democratic developing models. The political practices of such countries indicate that a stable and effective democratic government not only depends on the reasonable political systems and governmental structures, but also on the political values of the people. The world order should be more tolerant and plural, thereby supplying broader space for non-Western countries to choose suitable ways for themselves and combine the democratic globalization and localization together

Brownian motion of a charged test particle near a reflecting boundary at finite temperature

We discuss the random motion of charged test particles driven by quantum electromagnetic fluctuations at finite temperature in both the unbounded flat space and flat spacetime with a reflecting boundary and calculate the mean squared fluctuations in the velocity and position of the test particle. We show that typically the random motion driven by the quantum fluctuations is one order of magnitude less significant than that driven by thermal noise in the unbounded flat space. However, in the flat space with a reflecting plane boundary, the random motion of quantum origin can become much more significant than that of thermal origin at very low temperature.Comment: 11 pages,no figures, Revtex

Multifunctional Optoelectronic Device Based on Resistive Switching Effects

Optoelectronic resistive switching devices, utilizing optical and electrical hybrid methods to control the resistance states, offer several advantages of both photons and electrons for high-performance information detecting, demodulating, processing, and memorizing. In the past decades, optoelectronic resistive switching devices have been widely discussed and studied due to the potential for parallel information transmission and processing. In this chapter, recent progresses on the optoelectronic resistive switching mechanism, materials, and devices will be introduced. Then, their performance such as photoresponsivity, on/off ratio, as well as retention will be investigated. Furthermore, possible applications of the optoelectronic resistive switching considering logic, memory, neuromorphic, and image-processing devices will be summarized. In the end, the challenges and possible solutions of optoelectronic resistive switching devices for the next-generation information technology will be discussed and prospected

Causal association of peripheral immune cell counts and atrial fibrillation: A Mendelian randomization study

BackgroundAtrial fibrillation (AF) is the most common and persistent form of arrhythmia. Recently, increasing evidence has shown a link between immune responses and atrial fibrillation. However, whether the immune response is a cause or consequence of AF remains unknown. We aimed to determine whether genetically predicted peripheral immunity might have a causal effect on AF.MethodsFirst, we performed Mendelian randomization (MR) analyses using genetic variants strongly associated with neutrophil, eosinophil, basophil, lymphocyte, and monocyte cell counts as instrumental variables (IVs). Lymphocyte counts were then subjected to further subgroup analysis. The effect of immune cell counts on AF risk was measured using summary statistics from genome-wide association studies (GWAS).ResultsTwo-sample MR analysis revealed that a higher neutrophil count, basophil count and lymphocyte count had a causal effect on AF [Odds ratio (OR), 1.06, 95% confidence interval (CI), 1.01–1.10, P = 0.0070; OR, 1.10; 95% CI, 1.04–1.17; P = 0.0015; OR, 0.96; 95% CI, 0.93–0.99; P = 0.0359]. In addition, in our further analysis, genetically predicted increases in CD4 + T-cell counts were also associated with an increased risk of AF (OR, 1.04; 95% CI, 1.0–.09; P = 0.0493).ConclusionOur MR analysis provided evidence of a genetically predicted causal relationship between higher peripheral immune cell counts and AF. Subgroup analysis revealed the key role of peripheral lymphocytes in AF, especially the causal relationship between CD4 + T cell count and AF. These findings are beneficial for future exploration of the mechanism of AF

Macrophages: A communication network linking Porphyromonas gingivalis infection and associated systemic diseases

Porphyromonas gingivalis (P. gingivalis) is a Gram-negative anaerobic pathogen that is involved in the pathogenesis of periodontitis and systemic diseases. P. gingivalis has recently been detected in rheumatoid arthritis (RA), cardiovascular disease, and tumors, as well as Alzheimer’s disease (AD), and the presence of P. gingivalis in these diseases are correlated with poor prognosis. Macrophages are major innate immune cells which modulate immune responses against pathogens, however, multiple bacteria have evolved abilities to evade or even subvert the macrophages’ immune response, in which subsequently promote the diseases’ initiation and progression. P. gingivalis as a keystone pathogen of periodontitis has received increasing attention for the onset and development of systemic diseases. P. gingivalis induces macrophage polarization and inflammasome activation. It also causes immune response evasion which plays important roles in promoting inflammatory diseases, autoimmune diseases, and tumor development. In this review, we summarize recent discoveries on the interaction of P. gingivalis and macrophages in relevant disease development and progression, such as periodontitis, atherosclerosis, RA, AD, and cancers, aiming to provide an in-depth mechanistic understanding of this interaction and potential therapeutic strategies

A robust approach for multi-type classification of brain tumor using deep feature fusion

Brain tumors can be classified into many different types based on their shape, texture, and location. Accurate diagnosis of brain tumor types can help doctors to develop appropriate treatment plans to save patients’ lives. Therefore, it is very crucial to improve the accuracy of this classification system for brain tumors to assist doctors in their treatment. We propose a deep feature fusion method based on convolutional neural networks to enhance the accuracy and robustness of brain tumor classification while mitigating the risk of over-fitting. Firstly, the extracted features of three pre-trained models including ResNet101, DenseNet121, and EfficientNetB0 are adjusted to ensure that the shape of extracted features for the three models is the same. Secondly, the three models are fine-tuned to extract features from brain tumor images. Thirdly, pairwise summation of the extracted features is carried out to achieve feature fusion. Finally, classification of brain tumors based on fused features is performed. The public datasets including Figshare (Dataset 1) and Kaggle (Dataset 2) are used to verify the reliability of the proposed method. Experimental results demonstrate that the fusion method of ResNet101 and DenseNet121 features achieves the best performance, which achieves classification accuracy of 99.18 and 97.24% in Figshare dataset and Kaggle dataset, respectively