Dilemma and Breakthrough: Innovation on Models of Public Legal Education in China Based on Knowledge Graph

In over 30 years, the forms of public legal education activities have become increasingly rich. However, with the technology refresh, the traditional public legal education model characterized by one-way communication has gradually become out of touch, which can not adapt to the return of the people’s subjectivity and meet the personalized needs of different groups of people. As an important part of advancing the Rule of Law in China, public legal education should be timely innovated with the help of new technology. By combining the knowledge graph technology in the era of artificial intelligence with the work of public legal education, this paper studies how to use the knowledge graph technology to build public legal education network platform, introduce customized legal education content, and establish a sound mechanism for intelligent public legal education work, so that users can complete the important transformation from the object of legal education to the subject of law learning. This will enrich the theoretical research results of public legal education

Physical functioning and menopause in middle aged women

Aim: It has been reported that women in their midlife were more likely to have worse physical functioning (PF) limitations than men of a similar age. Since PF limitations are significant predictors for disability, healthcare utility, healthcare cost, and mortality in the elderly, the higher prevalence of PF limitations reported in middle-aged women is considered a public health issue. Given that the accelerated decline of PF is coincident with the menopausal transition, whether the menopausal transition, rather than normal aging, is related to lower levels of physical functioning in middle aged women remains uncertain. The primary aim of this work was to review systematically the literature that evaluates the associations between menopausal status and measures of PF. Related literature addressing the associations between sex hormones and PF were also reviewed. Methods: Published articles between March 24, 1999 and March 24, 2014 were retrieved from the Pubmed database using selective keywords in the “Title/Abstract”. Only English non-review articles in Humans that evaluated PF measures as outcome variables and menopausal status or sex hormones as independent variables were included in this literature review. Results: Nineteen articles were reviewed. In summary, the natural transition through the menopause was associated with declines in PF independent of the effect of aging. However, few studies used performance-based measurements to evaluate PF declines. Additionally, women undergoing surgical menopause were more likely to experience lower levels of PF compared to premenopausal women. These studies, however, did not evaluate comprehensively the impact of underlying medical conditions leading to surgical menopause on the levels of PF. Finally, the association between sex hormones and PF was still not clear. Conclusion: First, further studies that use performance-based measures of PF, are needed to support the findings that natural menopause is associated with lower level of PF as reported in studies used self-reported measures. Second, underlying medical conditions of surgical menopause should be considered in future studies evaluating surgical menopause and PF. Lastly, the role of the dynamic changes of sex hormones during the menopausal transition in the corresponding changes of PF needs to be explored further

NANO-FE AND MWCNTS BASED NON-ENZYMATIC SENSOR FOR DETERMINATION OF GLUCOSE IN SERUUM

The enzyme sensors based on glucose oxidase have been widely used for the detection of blood glucose. However, the activity of enzyme can be easily affected by temperature, pH, humidity and toxic chemical. Nanostructured metal-oxides have been extensively explored to develop nonenzymatic glucose sensors. An amperometric electrode based on multiwall carbon nanotubes (MWCNTs) and Fe nanoparticles has been successfully fabricated. The electrode exhibits the linear regression equation is: I = -0.1985 + 1.7499 CG (correlation coefficient is 0.9994). Linear response range: 0.2-20.0 mM, sensitivity: 1.75 a/am, the LOD was evaluated to be 0.03 mM according to IUPAC regulations (S/N = 3). Interference tests illustrated that 0.2 me of ascorbic acid and uric acid didn't have effect on the determination of glucose. In the presence of 0.02 M chloride ion, the current signal of 0.2 mM glucose almost keeps unchanged at the sensor, revealing that this new sensor has high tolerance level to chloride ion. The sensor has been successfully applied to determine glucose in the serum samples and obtained consist results with conventional spectrometry

The arabidopsis RCC1 family protein TCF1 regulates freezing tolerance and cold acclimation through modulating lignin biosynthesis

Cell water permeability and cell wall properties are critical to survival of plant cells during freezing, however the underlying molecular mechanisms remain elusive. Here, we report that a specifically cold-induced nuclear protein, Tolerant to Chilling and Freezing 1 (TCF1), interacts with histones H3 and H4 and associates with chromatin containing a target gene, BLUE-COPPER-BINDING PROTEIN (BCB), encoding a glycosylphosphatidylinositol-anchored protein that regulates lignin biosynthesis. Loss of TCF1 function leads to reduced BCB transcription through affecting H3K4me2 and H3K27me3 levels within the BCB gene, resulting in reduced lignin content and enhanced freezing tolerance. Furthermore, plants with knocked-down BCB expression (amiRNA-BCB) under cold acclimation had reduced lignin accumulation and increased freezing tolerance. The pal1pal2 double mutant (lignin content reduced by 30% compared with WT) also showed the freezing tolerant phenotype, and TCF1 and BCB act upstream of PALs to regulate lignin content. In addition, TCF1 acts independently of the CBF (C-repeat binding factor) pathway. Our findings delineate a novel molecular pathway linking the TCF1-mediated cold-specific transcriptional program to lignin biosynthesis, thus achieving cell wall remodeling with increased freezing tolerance

A Method for SINS Alignment with Large Initial Misalignment Angles Based on Kalman Filter with Parameters Resetting

In the initial alignment process of strapdown inertial navigation system (SINS), large initial misalignment angles always bring nonlinear problem, which causes alignment failure when the classical linear error model and standard Kalman filter are used. In this paper, the problem of large misalignment angles in SINS initial alignment is investigated, and the key reason for alignment failure is given as the state covariance from Kalman filter cannot represent the true one during the steady filtering process. According to the analysis, an alignment method for SINS based on multiresetting the state covariance matrix of Kalman filter is designed to deal with large initial misalignment angles, in which classical linear error model and standard Kalman filter are used, but the state covariance matrix should be multireset before the steady process until large misalignment angles are decreased to small ones. The performance of the proposed method is evaluated by simulation and car test, and the results indicate that the proposed method can fulfill initial alignment with large misalignment angles effectively and the alignment accuracy of the proposed method is as precise as that of alignment with small misalignment angles

Tin-graphene tubes as anodes for lithium-ion batteries with high volumetric and gravimetric energy densities.

Limited by the size of microelectronics, as well as the space of electrical vehicles, there are tremendous demands for lithium-ion batteries with high volumetric energy densities. Current lithium-ion batteries, however, adopt graphite-based anodes with low tap density and gravimetric capacity, resulting in poor volumetric performance metric. Here, by encapsulating nanoparticles of metallic tin in mechanically robust graphene tubes, we show tin anodes with high volumetric and gravimetric capacities, high rate performance, and long cycling life. Pairing with a commercial cathode material LiNi0.6Mn0.2Co0.2O2, full cells exhibit a gravimetric and volumetric energy density of 590 W h Kg-1 and 1,252 W h L-1, respectively, the latter of which doubles that of the cell based on graphite anodes. This work provides an effective route towards lithium-ion batteries with high energy density for a broad range of applications

Feature-Enhanced Network with Hybrid Debiasing Strategies for Unbiased Learning to Rank

Unbiased learning to rank (ULTR) aims to mitigate various biases existing in user clicks, such as position bias, trust bias, presentation bias, and learn an effective ranker. In this paper, we introduce our winning approach for the "Unbiased Learning to Rank" task in WSDM Cup 2023. We find that the provided data is severely biased so neural models trained directly with the top 10 results with click information are unsatisfactory. So we extract multiple heuristic-based features for multi-fields of the results, adjust the click labels, add true negatives, and re-weight the samples during model training. Since the propensities learned by existing ULTR methods are not decreasing w.r.t. positions, we also calibrate the propensities according to the click ratios and ensemble the models trained in two different ways. Our method won the 3rd prize with a DCG@10 score of 9.80, which is 1.1% worse than the 2nd and 25.3% higher than the 4th.Comment: 5 pages, 1 figure, WSDM Cup 202