Search

Porphyromonas gingivalis (P. gingivalis) is closely related to the occurrence and development of periodontitis. It is considered to be one of the important pathogens leading to alveolar bone resorption. At present, research on P. gingivalis mostly adopts standard laboratory strains whose genetic characteristics have been confirmed, are guaranteed and are traceable, such as ATCC 33277. The virulence phenotypes (endotoxin, firmbria, etc.) of clinically extracted isolates are quite different from those of standard strains, and the pathogenic effects and ability of the host are also widely different. In addition, P. gingivalis is considered to have a significant correlation with a variety of systemic diseases, and the virulence characteristics and pathogenic ability of different strains will have different effects on systemic diseases. However, at present, there is a lack of research on clinical strains and standard strains, and there is a lack of systematic comparison between the two sources of bacteria. In this paper, the differences in the virulence phenotypes and pathogenic effects between clinical isolates and standard strains of P. gingivalis in the last 5-10 years are reviewed. The aim is to elucidate the important virulence gene loci in the P. gingivalis gene sequence, which will play an important role in improving therapeutic methods and the development of related drugs.

The purpose of this study was to verify a Chinese version of Community of Inquiry (CoI) instrument with learning presence and explore the causal relationships of the factors in the instrument. This study first examined the reliability and validity of the instrument. All four presences had acceptable levels of reliability (all Cronbach's a > 0.765 or higher). The confirmatory factor modeling approach was used to assess its validity. Then, the study used path analysis and regression analysis to explore the causal relationships of the presences. The key findings showed that teaching and social presences directly influenced the perceptions of learning presence. Learning presence was a partial mediating variable of interactional relationship within CoI constructs.

In remote dynamic hand-gesture recognition, uncertainties in timing and distance of gesture occurrences, coupled with the subtle bodily perturbations induced by arm movements, pose substantial challenges to the accurate extraction of gesture features. In this paper, we propose a lightweight real-time gesture recognition system based on support vector machines. By analyzing the Doppler features of different motion states, a Doppler weighting factor was constructed to suppress bodily micro-motion interference in the range-time spectrum, and achieve foreground extraction of gesture signals concurrently. Furthermore, prior to the extraction of HOG features, we employ Gaussian filtering to suppress abrupt transitions and noise inherent in the gesture signals. This preprocessing significantly enhances the stability of feature extraction. Subsequently, the extracted features are input into an SVM for training and classification. Experimental results demonstrate that, for five distinct gestures exhibited in two different states –– standing and seated –– within a range of 1 to 5 meters, the recognition accuracy reaches 96%. This proves the feasibility of the proposed methodology, and its potential to realize real-time gesture recognition. [ABSTRACT FROM AUTHOR]

The subsurface defects (SSD) of optical elements have a significant impact on the service life and laser damage threshold of the inertial confinement nuclear fusion optical system. Due to the optical diffraction limit, fluorescence microscopy has limited image resolution for detecting SSD in optical elements, making it challenging to meet the requirements for precision detection. A super-resolution method is proposed in this paper for detecting SSD in optical elements based on the fluorescence polarization characteristics of CdSe/ZnS quantum dots fluorescence dichroism. By enhancing the imaging sparsity of adjacent fluorophores through a polarization modulated excitation laser and utilizing the fluorescence polarization modulation algorithm, the resolution is achieved beyond the optical diffraction limit. The results demonstrate that the proposed method in this paper can obtain super-resolution images of SSD in optical elements with at least a two-fold increase in lateral resolution. This approach effectively improves detection accuracy for SSD and holds significant guiding significance. In addition, it also has application value for assessing the quality of high-precision optical elements. [ABSTRACT FROM AUTHOR]