Application of An Improved Deviation Analysis of Double Mean Data in Student’S Teaching Evaluation Data

This paper analyzes the main problems of College Students’ evaluation of teaching, and proposes a new method to analyze and process the evaluation data.In this paper, we first use the deviation analysis of double mean data method. Through numerical examples, we find an advantage of this method that it can effectively eliminate invalid data in the teaching evaluation data, but the result has a certain deviation from the original teaching evaluation data, and can not directly reflect the specific gap between different teachers or define the maximum and minimum of the teaching evaluation score. In order to objectively reflect the effects of teachers’ classroom teaching, we make a little improvement on the basis of this method in this paper, and give each student a certain weight, so as to get a more real and effective comprehensive evaluation score of each teacher. Numerical examples are given to compare the results of the two methods, and the improved method of deviation analysis of double mean data is more reasonable and effective

A routing strategy for spatial networks based on harmonic centrality

With the rapid development of networks, the traffic in the networks has increased sharply, resulting in frequent congestion, especially in spatial networks, such as the railway network, aviation network, and sensor network, and congestion not only affects the user’s experience but also causes serious economic losses. Therefore, in this paper, we effectively identify the high-load nodes in spatial networks by considering harmony centrality and degree. On this basis, we design the HD routing strategy by avoiding these key nodes, which can enhance the traffic throughput of spatial networks efficiently. The results provide new ideas and directions for the design of routing strategies for spatial networks

Exploring the Potential of Flexible 8-bit Format: Design and Algorithm

Neural network quantization is widely used to reduce model inference complexity in real-world deployments. However, traditional integer quantization suffers from accuracy degradation when adapting to various dynamic ranges. Recent research has focused on a new 8-bit format, FP8, with hardware support for both training and inference of neural networks but lacks guidance for hardware design. In this paper, we analyze the benefits of using FP8 quantization and provide a comprehensive comparison of FP8 with INT quantization. Then we propose a flexible mixed-precision quantization framework that supports various number systems, enabling optimal selection of the most appropriate quantization format for different neural network architectures. Experimental results demonstrate that our proposed framework achieves competitive performance compared to full precision on various tasks, including image classification, object detection, segmentation, and natural language understanding. Our work furnishes critical insights into the tangible benefits and feasibility of employing FP8 quantization, paving the way for heightened neural network efficiency in tangible scenarios. Our code is available in the supplementary material

A prospective study of specimen eversion to lateral rectum and valgus resection for low rectal cancer

PurposeTo investigate the safety and efficacy of a reverse puncture device (RPD) and specimen eversion of the rectum for resection in total laparoscopic proctectomy.MethodsIn a prospective study from August 2019 to March 2021, 40 patients underwent a procedure with an RPD and specimen eversion of the rectum for total laparoscopic low rectal cancer resection, that is natural orifice specimen extraction surgery (NOSES), were included in the NOSES group. Forty patients in the control group underwent conventional laparoscopic radical resection for low rectal cancer and were included in the LAP group. Intraoperative- and postoperative-related indicators, recovery and inflammatory factors, quality of life (QOL) and mental health were compared.ResultsAll operations were successfully completed. Compared with the LAP group, the NOSES group showed better short-term outcomes, such as time to eating, postoperative pain, and especially postoperative incision-related complications. At the same time, postoperative inflammatory factor levels, psychological trauma, life-related anxiety and depression scores, and QOL were better in the NOSES group than in the LAP group.ConclusionsThe application of an RPD and specimen eversion of the rectum for total laparoscopic low rectal cancer resection is a technically feasible and safe approach with a short-term curative effect

Single-image based deep learning for precise atomic defects identification

Defect engineering has been profoundly employed to confer desirable functionality to materials that pristine lattices inherently lack. Although single atomic-resolution scanning transmission electron microscopy (STEM) images are widely accessible for defect engineering, harnessing atomic-scale images containing various defects through traditional image analysis methods is hindered by random noise and human bias. Yet the rise of deep learning (DL) offering an alternative approach, its widespread application is primarily restricted by the need for large amounts of training data with labeled ground truth. In this study, we propose a two-stage method to address the problems of high annotation cost and image noise in the detection of atomic defects in monolayer 2D materials. In the first stage, to tackle the issue of data scarcity, we employ a two-state transformation network based on U-GAT-IT for adding realistic noise to simulated images with pre-located ground truth labels, thereby infinitely expanding the training dataset. In the second stage, atomic defects in monolayer 2D materials are effectively detected with high accuracy using U-Net models trained with the data generated in the first stage, avoiding random noise and human bias issues. In both stages, we utilize segmented unit-cell-level images to simplify the model's task and enhance its accuracy. Our results demonstrate that not only sulfur vacancies, we are also able to visualize oxygen dopants in monolayer MoS2, which are usually overwhelmed by random background noise. As the training was based on a few segmented unit-cell-level realistic images, this method can be readily extended to other 2D materials. Therefore, our results outline novel ways to train the model with minimized datasets, offering great opportunities to fully exploit the power of machine learning (ML) applicable to a broad materials science community

A Novel Signal Transduction Pathway that Modulates <i>rhl</i> Quorum Sensing and Bacterial Virulence in <i>Pseudomonas aeruginosa</i>

The rhl quorum-sensing (QS) system plays critical roles in the pathogenesis of P. aeruginosa. However, the regulatory effects that occur directly upstream of the rhl QS system are poorly understood. Here, we show that deletion of gene encoding for the two-component sensor BfmS leads to the activation of its cognate response regulator BfmR, which in turn directly binds to the promoter and decreases the expression of the rhlR gene that encodes the QS regulator RhlR, causing the inhibition of the rhl QS system. In the absence of bfmS, the Acka-Pta pathway can modulate the regulatory activity of BfmR. In addition, BfmS tunes the expression of 202 genes that comprise 3.6% of the P. aeruginosa genome. We further demonstrate that deletion of bfmS causes substantially reduced virulence in lettuce leaf, reduced cytotoxicity, enhanced invasion, and reduced bacterial survival during acute mouse lung infection. Intriguingly, specific missense mutations, which occur naturally in the bfmS gene in P. aeruginosa cystic fibrosis (CF) isolates such as DK2 strains and RP73 strain, can produce BfmS variants (BfmSL181P, BfmSL181P/E376Q, and BfmSR393H) that no longer repress, but instead activate BfmR. As a result, BfmS variants, but not the wild-type BfmS, inhibit the rhl QS system. This study thus uncovers a previously unexplored signal transduction pathway, BfmS/BfmR/RhlR, for the regulation of rhl QS in P. aeruginosa. We propose that BfmRS TCS may have an important role in the regulation and evolution of P. aeruginosa virulence during chronic infection in CF lungs.</p

Tumor-associated M2 macrophages in the immune microenvironment influence the progression of renal clear cell carcinoma by regulating M2 macrophage-associated genes

BackgroundRenal clear cell carcinoma (RCC) has negative prognosis and high mortality due to its early diagnosis difficulty and early metastasis. Although previous studies have confirmed the negative progression of RCC is closely related to M2 macrophages in tumor-associated macrophages (TAMs), the specific mechanism is still unknownMethodsWe used immunofluorescence labeling and flow cytometry to detect the proportion of M2 macrophages in RCC tissues. And bioinformatics technique was used to obtain 9 M2 macrophage-related model genes, including SLC40A1, VSIG4, FUCA1, LIPA, BCAT1, CRYBB1, F13A, TMEM144, COLEC12. Using these genes, model formulas are constructed to devide samples into high and low risk groups, and then the overall survival (OS), progression-free survival (PFS) and Gene set enrichment analysis (GSEA) of the high and low risk groups were analyzed. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to measure the expression of model genes between normal kidney tissue and RCC tissue, as well as between HK-2 cell and 786-O cell. Besides, we induced the M2 differentiation of THP-1 cell, and then co-cultured with the RCC cell 786-O in transwell to observe what effect M2 macrophages will cause on the invasion, migration and the expression of model genes of RCC.ResultsOur study demonstrated M2 macrophages in RCC was about 2 folds that of normal renal tissue (P&lt;0.0001) and M2 macrophages affected the prognosis of patients with RCC by affecting the co-expressed genes, which were mainly enriched in immune-related pathways. The results of in vitro experiments showed that in RCC tissues and 786-O cells, the model gene FUCA1 was down-regulated, and SLC40A1, VSIG4, CRYBB1 and LIPA were up-regulated. Besides, the results of co-culture showed that after 786-O co-culture with M2 macrophages, the ability of migration and invasion was promoted and the expressions of FUCA1, SLC40A1, VSIG4, CRYBB1, LIPA and TMEM144 were all up-regulated.ConclusionThe proportion of tumor-associated M2 macrophages in RCC tissues is upregulated, and M2 macrophages promote the progression of RCC by regulating the expression of SLC40A1, VSIG4, FUCA1, LIPA, BCAT1, CRYBB1, F13A, TMEM144, COLEC12 genes, thereby affecting the prognosis of patients with RCC

Response of Chinese cabbage (Brassica rapa subsp. pekinensis) to bacterial soft rot infection by change of soil microbial community in root zone

Chinese cabbage, scientifically known as Brassica rapa subsp. pekinensis, is a highly popular vegetable in China for its delectable taste. However, the occurrence of bacterial soft rot disease poses a significant threat to its growth and overall development. Consequently, this study aimed to explore the defense mechanisms employed by Chinese cabbage against bacterial soft rot disease. Specifically, the investigation focused on understanding the relationship between the disease and the microbial communities present in the soil surrounding the roots of Chinese cabbage. Significant disparities were observed in the composition of microbial communities present in the root-zone soil of healthy Chinese cabbage plants compared to those affected by Pectobacterium brasiliense-caused soft rot disease. The analysis of 16S rRNA gene high-throughput sequencing results revealed a lower abundance of Proteobacteria (8.39%), Acidobacteriot (0.85), Sphingomonas (3.51%), and Vicinamibacteraceae (1.48%), whereas Firmicutes (113.76%), Bacteroidota (8.71%), Chloroflexi (4.89%), Actinobacteriota (1.71%), A4b (15.52%), Vicinamibacterales (1.62%), and Gemmatimonadaceae (1.35%) were more prevalent in healthy plant soils. Similarly, the analysis of ITS gene high-throughput sequencing results indicated a reduced occurrence of Chytridiomycota (23.58%), Basidiomycota (21.80%), Plectosphaerella (86.22%), and Agaricomycetes (22.57%) in healthy soils. In comparison, Mortierellomycota (50.72%), Ascomycota (31.22%), Podospora (485.08%), and Mortierella (51.59%) were more abundant in healthy plant soils. In addition, a total of 15 bacterial strains were isolated from the root-zone soil of diseased Chinese cabbage plants. These isolated strains demonstrated the ability to fix nitrogen (with the exception of ZT20, ZT26, ZT41, ZT45, and ZT61), produce siderophores and indole acetic acid (IAA), and solubilize phosphate. Notably, ZT14 (Citrobacter freundii), ZT33 (Enterobacter cloacae), ZT41 (Myroides odoratimimus), ZT52 (Bacillus paramycoides), ZT58 (Klebsiella pasteurii), ZT45 (Klebsiella aerogenes), and ZT32 (Pseudomonas putida) exhibited significant growth-promoting effects as determined by the plant growth promotion (PGP) tests. Consequently, this investigation not only confirmed the presence of the soft rot pathogen in Chinese cabbage plants in Hangzhou, China, but also advanced our understanding of the defense mechanisms employed by Chinese cabbage to combat soft rot-induced stress. Additionally, it identified promising plant-growth-promoting microbes (PGPMs) that could be utilized in the future to enhance the Chinese cabbage industry

High Prevalence and Genetic Diversity of HCV among HIV-1 Infected People from Various High-Risk Groups in China

BACKGROUND: Co-infection with HIV-1 and HCV is a significant global public health problem and a major consideration for anti-HIV-1 treatment. HCV infection among HIV-1 positive people who are eligible for the newly launched nationwide anti-HIV-1 treatment program in China has not been well characterized. METHODOLOGY: A nationwide survey of HIV-1 positive injection drug uses (IDU), former paid blood donors (FBD), and sexually transmitted cases from multiple provinces including the four most affected provinces in China was conducted. HCV prevalence and genetic diversity were determined. We found that IDU and FBD have extremely high rates of HCV infection (97% and 93%, respectively). Surprisingly, people who acquired HIV-1 through sexual contact also had a higher rate of HCV infection (20%) than the general population. HIV-1 subtype and HCV genotypes were amazingly similar among FBD from multiple provinces stretching from Central to Northeast China. However, although patterns of overland trafficking of heroin and distinct HIV-1 subtypes could be detected among IDU, HCV genotypes of IDU were more diverse and exhibited significant regional differences. CONCLUSION: Emerging HIV-1 and HCV co-infection and possible sexual transmission of HCV in China require urgent prevention measures and should be taken into consideration in the nationwide antiretroviral treatment program

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve