Composite Disturbance Filtering: A Novel State Estimation Scheme for Systems With Multi-Source, Heterogeneous, and Isomeric Disturbances

State estimation has long been a fundamental problem in signal processing and control areas. The main challenge is to design filters with ability to reject or attenuate various disturbances. With the arrival of big data era, the disturbances of complicated systems are physically multi-source, mathematically heterogenous, affecting the system dynamics via isomeric (additive, multiplicative and recessive) channels, and deeply coupled with each other. In traditional filtering schemes, the multi-source heterogenous disturbances are usually simplified as a lumped one so that the "single" disturbance can be either rejected or attenuated. Since the pioneering work in 2012, a novel state estimation methodology called {\it composite disturbance filtering} (CDF) has been proposed, which deals with the multi-source, heterogenous, and isomeric disturbances based on their specific characteristics. With the CDF, enhanced anti-disturbance capability can be achieved via refined quantification, effective separation, and simultaneous rejection and attenuation of the disturbances. In this paper, an overview of the CDF scheme is provided, which includes the basic principle, general design procedure, application scenarios (e.g. alignment, localization and navigation), and future research directions. In summary, it is expected that the CDF offers an effective tool for state estimation, especially in the presence of multi-source heterogeneous disturbances

Interactive reweighting for mitigating label quality issues

Label quality issues, such as noisy labels and imbalanced class distributions, have negative effects on model performance. Automatic reweighting methods identify problematic samples with label quality issues by recognizing their negative effects on validation samples and assigning lower weights to them. However, these methods fail to achieve satisfactory performance when the validation samples are of low quality. To tackle this, we develop Reweighter, a visual analysis tool for sample reweighting. The reweighting relationships between validation samples and training samples are modeled as a bipartite graph. Based on this graph, a validation sample improvement method is developed to improve the quality of validation samples. Since the automatic improvement may not always be perfect, a co-cluster-based bipartite graph visualization is developed to illustrate the reweighting relationships and support the interactive adjustments to validation samples and reweighting results. The adjustments are converted into the constraints of the validation sample improvement method to further improve validation samples. We demonstrate the effectiveness of Reweighter in improving reweighting results through quantitative evaluation and two case studies

Identification of E1-E4 allele combinations and ecological adaptability of soybean varieties from different geographical origins in China

The duration of soybean growth and development is regulated by E1-E4 allele genes, which form the basis for ecological adaptation related to biomass accumulation, flowering and pod formation, maturation, and yield. To elucidate the effects of different combinations of E1-E4 allele genes on soybean ecological adaptation, this study conducted competitive allele-specific PCR (KASP) analysis and photoperiod gene typing on 101 main soybean cultivars from different latitudes in China. The ecological adaptation of these cultivars in Sichuan was also investigated. The results showed that within a certain range (60-95 days), soybean varieties with a genotype combination of E1/e2-ns/E3/E4 exhibited a longer growth period and demonstrated higher biomass and yield, displaying overall better performance. These varieties showed strong ecological adaptation in the Chengdu Plain region and are suitable for introduction in similar low to mid-latitude areas like the Chengdu Plain (30°N~32°N). Conversely, soybean varieties carrying a higher number of recessive alleles of E1-E4 are not suitable for introduction in this region

MiR-34a Enhances Chondrocyte Apoptosis, Senescence and Facilitates Development of Osteoarthritis by Targeting DLL1 and Regulating PI3K/AKT Pathway

Background/Aims: Osteoarthritis (OA) is the prevalent degenerative disease caused by various factors. MicroRNAs are important regulators in the inflammation and immune response. The aim of this study was to investigate the effect of microRNA-34a (MiR-34a) on the death of chondrocytes, senescence, as well as its role in OA progression. Methods: A series of experiments involving CCK-8, flow cytometry, β-galactosidase staining and wound healing assays were conducted to determine the cellular capabilities of proliferation, cell apoptosis, senescence and the ability of cells to recover from injury, respectively. Binding sites between miR-34a and delta-like protein 1 (DLL1) were identified using a luciferase reporter system, whereas mRNA and protein expression of target genes was determined by RT-PCR and immunoblot, respectively. OA model was generated via surgery. Results: We found that miR-34a expression was increased in the cartilage of OA patients. In rat chondrocytes and chondrosarcoma cells, miR-34a transfections noticeably inhibited the expression of DLL1, triggered cell death and senescence, suppressed proliferation, and prevented scratch assay wound closure. However, transfection of a miR-34a inhibitor displayed adverse effects. Additionally, secretion and expression of factors associated with cartilage degeneration were altered via miR-34a. Moreover, miR-34a directly inhibits DLL1 mRNA. Furthermore, concentrations of DLL1, total PI3K, and p-AKT declined in chondrocytes that overexpress miR-34a. DLL1 overexpression elevated PI3K and p-AKT levels, and eliminated cell death triggered by a miR-34a mimic. In vivo, miR-34a remarkably inhibited miR-34a up-regulation, while enhanced the level of DLL1 expression. In the knee joints of surgery-induced OA rats, articular chondrocyte death and loss of cartilage were attenuated via miR-34a antagomir injection. Conclusions: These findings indicate that miR-34a contributes to chondrocyte death, causing OA progression through DLL1 and modulation of the PI3K/AKT pathway

Epitope-optimization creates highly immunogenic alpha fetoprotein antigen to break immune tolerance and potently activates CD8 T cells to prevents autochthonous hepatocellular carcinoma

In this study, we investigated whether mouse alpha fetoprotein (mAFP), the shared self/tumor antigen of hepatocellular carcinoma (HCC), could be rationally engineered to create effective vaccine to break tolerance and potently activate CD8 T cells to prevent clinically-relevant carcinogen-induced autochthonous HCC. We found that the computer-guided epitope-optimization created optimized opt-mAFP and that immunization with lentivector (lv) expressing opt-mAFP, but not wt-mAFP, potently activated CD8 cells specific for three novel H-2b restricted CD8 epitopes, which cross-recognized wt-mAFP epitopes naturally processed and presented by wt-mAFP+ tumor cells. Immunization with opt-mAFP-lv, but not wt-mAFP-lv, completely protected mice from wt-mAFP+ tumor challenge and effectively prevented carcinogen-induced autochthonous HCC. Prime-boost with opt-mAFP-lv and vaccinia vector opt-mAFP-vv significantly increased the wt-mAFP-specific CD8 T cells that were highly responsive to emerging HCC tumor cells in the liver, enhancing prevention of autochthonous HCC. Our data demonstrate that epitope-optimization creates immunogenic opt-mAFP that is able to break tolerance and activate potent CD8 responses, which can cross-recognize wt-mAFP peptides, but also recognize and kill mAFP+ tumor cells. Our study provides a practical roadmap to develop effective human vaccines that should have a better chance of success than the current human HCC vaccines based on native wt-AFP

Interactive Effects and Mediating Roles of Multiple Factors That Influence Learning Adaptative Growth of International Students: Evidence from China

The learning adaptability of international students is pivotal to the success of sustainable international higher education development. The purpose of this study was to explore what factors affect the learning adaptability of international students in China through structural equation modelling and mediation analysis. The data collected through a questionnaire from the overseas students were analysed, and the reliability and validity were also tested. The findings show that the influencing factors that affect learning adaptability of international students in China comprise seven variables: learning attitude, motivation to study abroad, learning ability, language proficiency, learning environment, teaching management and social relations. In addition, when language proficiency is used as the mediating variable, the motivation to study abroad has a significant positive impact on learning attitudes, with an influence coefficient of 0.185 and an effect proportion of 35%, which is a partial mediator. When social relationships are used as the mediating variable, study abroad motivation has a significant positive impact on learning attitude, with an influence coefficient of 0.058, which is completely mediating

Experimental Research on the Mechanical Performance of the Bolted Rock under Lateral Impact Load: Effect of Prestress, Body Material, and Anchorage Style

In order to reveal the impact mechanical properties and their key influencing factors of the bolted rock under the lateral impact load, through the lateral drop hammer impact test, the time-history curve of impact force, axial force of the bolt, and surface strain of the sample under different combination types of influencing factors is obtained, and the whole process of deformation and failure of the bolted rock is recorded. The test results show that the material of the bolt has a significant influence on the impact force and axial force of the bolt. There is a positive correlation between bolt strength and impact peak and impact attenuation slope and a negative correlation between bolt strength and impact action time. The effect of prestress on the impact resistance of the bolted rock was also evaluated by the test which suggested that prestress of the bolt can significantly reduce both impact time and bolt axial force of the bolted rock but has limited effect on the impact force. It was also found that the time-history curve of the impact force of anchoring rock mass had significant difference with full-length anchoring and nonanchoring. Compared with the nonanchoring bolt, the full-length anchored rock mass has a larger impact peak and shorter action time, which means that the impact resistance of the full-length bolted rock has a certain degree of weakening. Through scientific research, determining the reasonable bolt material, prestress value, and anchorage style can improve the impact resistance of the sample