Safety evaluation method of bridge plate rubber bearing based on SVM

In order to comprehensively evaluate the working state and safety performance of the bridge plate rubber bearing (PRB), the basic principle and method of SVM in machine learning theory (Support Vector Machine) was introduced in this paper. Firstly, the performance indices (such as the average compression stress, tangent value of the shear angle and the rotation angle of the PRB) were analyzed and calculated through its finite element model considering the different working conditions (axial compression, shear deformation and the rotation deformation of the PRB). Subsequently, considering the relevant indices affecting the safety performance of the PRB, the Pearson Correlation Coefficients (PCC) were calculated by SVM method for assessing the internal correlation of the performance indices of the PRB for different cases, respectively. The threshold values of the influential factors for different cases considering the PCC and the weight coefficient were obtained for grading the working state of the PRB as five levels. Moreover, in order to verify the validity and suitability of the evaluation of the working state of the plate rubber bearing by the SVM method, three apparent indices for grading the performance level of the PRB such as the crack, the undistributed spalling deformation and the dislocation of the PRB were analyzed and compared with the qualitative descriptions and the quantitative values. Finally, the corresponding threshold values for grading the performance levels of the PRB working states were proposed. It was shown that the SVM based evaluation method for the PRB is feasible and convenient, especially for the bridges with real-time monitoring devices to get the response data of the PRB

Meta-analysis of preclinical studies of mesenchymal stromal cells to treat rheumatoid arthritis.

BackgroundThis study aims to evaluate the quality of preclinical data, determine the effect sizes, and identify experimental measures that inform efficacy using mesenchymal stromal (or stem) cells (MSC) therapy in animal models of rheumatoid arthritis (RA).MethodsLiterature searches were performed on MSC preclinical studies to treat RA. MSC treatment effect sizes were determined by the most commonly used outcome measures, including paw thickness, clinical score, and histological score.FindingsA total of 48 studies and 94 treatment arms were included, among which 42 studies and 79 treatment arms reported that MSC improved outcomes. The effect sizes of RA treatments using MSC, when compared to the controls, were: paw thickness was ameliorated by 53.6% (95% confidence interval (CI): 26.7% -80.4%), histological score was decreased by 44.9% (95% CI: 33.3% -56.6%), and clinical score was decreased by 29.9% (95% CI: 16.7% -43.0%). Specifically, our results indicated that human umbilical cord derived MSC led to large improvements of the clinical score (-42.1%) and histological score (-51.4%).InterpretationTo the best of our knowledge, this meta-analysis is to quantitatively answer whether MSC represent a robust RA treatment in animal models. It suggests that in preclinical studies, MSC have consistently exhibited therapeutic benefits. The findings demonstrate a need for considering variations in different animal models and treatment protocols in future studies using MSC to treat RA in humans to maximise the therapeutic gains in the era of precision medicine.FundsNIH [1DP2CA195763], Baylx Inc.: BI-206512, NINDS/NIH Training Grant [Award# NS082174]

Convergence analysis of a spectral-Galerkin-type search extension method for finding multiple solutions to semilinear problems

In this paper, we develop an efficient spectral-Galerkin-type search extension method (SGSEM) for finding multiple solutions to semilinear elliptic boundary value problems. This method constructs effective initial data for multiple solutions based on the linear combinations of some eigenfunctions of the corresponding linear eigenvalue problem, and thus takes full advantage of the traditional search extension method in constructing initials for multiple solutions. Meanwhile, it possesses a low computational cost and high accuracy due to the employment of an interpolated coefficient Legendre-Galerkin spectral discretization. By applying the Schauder's fixed point theorem and other technical strategies, the existence and spectral convergence of the numerical solution corresponding to a specified true solution are rigorously proved. In addition, the uniqueness of the numerical solution in a sufficiently small neighborhood of each specified true solution is strictly verified. Numerical results demonstrate the feasibility and efficiency of our algorithm and present different types of multiple solutions.Comment: 23 pages, 7 figures; Chinese version of this paper is published in SCIENTIA SINICA Mathematica, Vol. 51 (2021), pp. 1407-143

More is Less? Design Free Sample Strategy via Field Experiment and Double/Debiased Machine Learning

Free sample strategy has attracted considerable interest among practitioners and academics, it has been widely adopted in digital content industries (e.g., e-books, music, and videos). There are two issues that have been the continuous concerning and constantly optimized focus. How many free samples should be taken? How to design a personalized free samples strategy considering the contexts? To better understand these issues, we collaborated with an online reading platform in China to design and conduct a field experiment based on Construal Level Theory. The results showed an inverted U-shaped relationship between free sample quantity and consumer purchase decisions and also suggested when free chapters were offered, book popularity and quality were also found to positively moderate consumers’ purchase decisions. Moreover, by combining the causal forest (CF) technique and the double/debiased machine learning model (DML), we develop a personalized free sample strategy and provide managerial implications

Exploring Gut Microbiota in Patients with Colorectal Disease Based on 16S rRNA Gene Amplicon and Shallow Metagenomic Sequencing

The gastrointestinal tract, the largest human microbial reservoir, is highly dynamic. The gut microbes play essential roles in causing colorectal diseases. In the present study, we explored potential keystone taxa during the development of colorectal diseases in central China. Fecal samples of some patients were collected and were allocated to the adenoma (Group A), colorectal cancer (Group C), and hemorrhoid (Group H) groups. The 16S rRNA amplicon and shallow metagenomic sequencing (SMS) strategies were used to recover the gut microbiota. Microbial diversities obtained from 16S rRNA amplicon and SMS data were similar. Group C had the highest diversity, although no significant difference in diversity was observed among the groups. The most dominant phyla in the gut microbiota of patients with colorectal diseases were Bacteroidetes, Firmicutes, and Proteobacteria, accounting for >95% of microbes in the samples. The most abundant genera in the samples were Bacteroides, Prevotella, and Escherichia/Shigella, and further species-level and network analyses identified certain potential keystone taxa in each group. Some of the dominant species, such as Prevotella copri, Bacteroides dorei, and Bacteroides vulgatus, could be responsible for causing colorectal diseases. The SMS data recovered diverse antibiotic resistance genes of tetracycline, macrolide, and beta-lactam, which could be a result of antibiotic overuse. This study explored the gut microbiota of patients with three different types of colorectal diseases, and the microbial diversity results obtained from 16S rRNA amplicon sequencing and SMS data were found to be similar. However, the findings of this study are based on a limited sample size, which warrants further large-scale studies. The recovery of gut microbiota profiles in patients with colorectal diseases could be beneficial for future diagnosis and treatment with modulation of the gut microbiota. Moreover, SMS data can provide accurate species- and gene-level information, and it is economical. It can therefore be widely applied in future clinical metagenomic studies

Investigating Factors Influencing Telemedicine Usage in Developing Countries

Telemedicine has a strategic role in providing timely medical care and containing the spread of infectious diseases. Despite its importance, telemedicine is largely underdeveloped in developing countries. This paper attempts to explore the factors influencing telemedicine usage by conducting case studies in two Chinese hospitals. Based on a research model we proposed, factors are identified that are likely to affect the use of telemedicine

Phenotypic comparison and DNA sequencing analysis of a wild-type and a pediocin-resistant mutant of Listeria ivanovii

Listeria ivanovii is one of the two pathogenic species within the genus Listeria, the other being L. monocytogenes. In this study, we generated a stable pediocin resistant mutant Liv-r1 of a L. ivanovii strain, compared phenotypic differences between the wild-type and the mutant, localised the pediocin-induced mutations in the chromosome, and analysed the mechanisms behind the bacteriocin resistance. In addition to pediocin resistance, Liv-r1 was also less sensitive to nisin. The growth of Liv-r1 was significantly reduced with glucose and mannose, but less with cellobiose. The cells of Liv-r1 adsorbed less pediocin than the wild-type cells. Consequently, with less pediocin on the cell surface, the mutant was also less leaky, as shown as the release of intracellular lactate dehydrogenase to the supernatant. The surface of the mutant cells was more hydrophobic than that of the wild-type. Whole genome sequencing revealed numerous changes in the Liv-r1 chromosome. The mutations were found e.g., in genes encoding sigma-54-dependent transcription regulator and internalin B, as well as in genes involved in metabolism of carbohydrates such as glucose and cellobiose. Genetic differences observed in the mutant may be responsible for resistance to pediocin but no direct evidence is provided.Peer reviewe