A Decomposition Algorithm for Learning Bayesian Networks Based on Scoring Function

Learning Bayesian network (BN) structure from data is a typical NP-hard problem. But almost existing algorithms have the very high complexity when the number of variables is large. In order to solve this problem(s), we present an algorithm that integrates with a decomposition-based approach and a scoring-function-based approach for learning BN structures. Firstly, the proposed algorithm decomposes the moral graph of BN into its maximal prime subgraphs. Then it orientates the local edges in each subgraph by the K2-scoring greedy searching. The last step is combining directed subgraphs to obtain final BN structure. The theoretical and experimental results show that our algorithm can efficiently and accurately identify complex network structures from small data set

Comparative Analysis of Static Loading Performance of Rigid and Flexible Road Wheel based on Finite Element Method

To overcome the shortcomings of traditional rigid road wheel, such as poor damping effect and low load-bearing efficiency, a new type of flexible road wheel, having a unique suspension-bearing mode, was introduced. The three-dimensional nonlinear finite element model of rigid and flexible road wheel, considering the triple nonlinear characteristics of geometry, material and contact, is established for numerical investigation of static loading performance. The accuracy of the finite element model of the rigid and flexible road wheel is verified by static loading experiment. The static loading performance of the rigid and flexible road wheels is numerically analyzed. The influence of vertical load on maximum stress and deformation of the rigid and flexible wheels is also studied. The results show that the contact pressure uniformity of the flexible road wheel is better than that of the rigid road wheel under the static vertical load, but the maximum stress and deformation of the flexible road wheel are greater than that of the rigid road wheel. However, this problem can be solved by increasing the number of hinge sets and optimising the joints. The research results provide theoretical basis for replacing rigid road wheel with flexible road wheel, and also provide reference for structural optimisation of flexible road wheel

Equivalent stiffness and dynamic response of new mechanical elastic wheel

To investigate the stiffness characteristics of the new mechanical elastic wheel (MEW), the elastic foundation closed circle curved beam model of MEW was established by curved beam theory. With the Laplace transformation and boundary conditions of the governing differential equations, the analytical relations among the radial deformation, bending stiffness of elastic wheel, the elastic foundation stiffness of hinges, elastic wheel laminated structure parameters and excitation frequency were analyzed. The correctness of the curved beam model was validated by the finite element method. Curved beam model validation and the application of the nonlinear finite element model show that the influence of elastic wheel laminated structure and deformation on dynamic response is equal to the equivalent stiffness. The results indicate that the equivalent stiffness and dynamic response of MEW become increased nonlinearly with component content of elastic bead ring, moreover, the equivalent stiffness and dynamic response of MEW increase nonlinearly with the deformation amount of MEW, and the dynamic response significantly decreases with the increase of excitation frequency, under this circumstance that the laminated structure of elastic wheel has been unchanged

Learning Bayesian Networks in the Space of Structures by a Hybrid Optimization Algorithm

Bayesian networks (BNs) are one of the most widely used class for machine learning and decision making tasks especially in uncertain domains. However, learning BN structure from data is a typical NP-hard problem. In this paper, we present a novel hybrid algorithm for BN structure learning, called MMABC. It’s based on a recently introduced meta-heuristic, which has been successfully applied to solve a variety of optimization problems: Artificial Bee Colony (ABC). MMABC algorithm consists of three phases: (i) obtain an initial undirected graph by the subroutine MMPC. (ii) Generate the initial population of solutions based on the undirected graph and (iii) perform the ABC algorithm to orient the edges. We describe all the elements necessary to tackle our learning problem, and experimentally compare the performance of our algorithm with two state-of-the-art algorithms reported in the literature. Computational results demonstrate that our algorithm achieves better performance than other two related algorithms

Align, Perturb and Decouple: Toward Better Leverage of Difference Information for RSI Change Detection

Change detection is a widely adopted technique in remote sense imagery (RSI) analysis in the discovery of long-term geomorphic evolution. To highlight the areas of semantic changes, previous effort mostly pays attention to learning representative feature descriptors of a single image, while the difference information is either modeled with simple difference operations or implicitly embedded via feature interactions. Nevertheless, such difference modeling can be noisy since it suffers from non-semantic changes and lacks explicit guidance from image content or context. In this paper, we revisit the importance of feature difference for change detection in RSI, and propose a series of operations to fully exploit the difference information: Alignment, Perturbation and Decoupling (APD). Firstly, alignment leverages contextual similarity to compensate for the non-semantic difference in feature space. Next, a difference module trained with semantic-wise perturbation is adopted to learn more generalized change estimators, which reversely bootstraps feature extraction and prediction. Finally, a decoupled dual-decoder structure is designed to predict semantic changes in both content-aware and content-agnostic manners. Extensive experiments are conducted on benchmarks of LEVIR-CD, WHU-CD and DSIFN-CD, demonstrating our proposed operations bring significant improvement and achieve competitive results under similar comparative conditions. Code is available at https://github.com/wangsp1999/CD-Research/tree/main/openAPDComment: To appear in IJCAI 202

Correlation of 3'-phosphoadenosine-5'-phosphosulfate synthase 1 (PAPSS1) expression with clinical parameters and prognosis in esophageal squamous cell carcinoma

Background. In recent years, 3'- phosphoadenosine-5'-phosphosulfate synthase 1 (PAPSS1) has been found to be highly expressed in some cancers and significantly associated with prognosis. Nevertheless, the role of PAPSS1 in esophageal squamous cell carcinoma (ESCC) is poorly understood. Methods. In this study, PAPSS1 expression in ESCC samples was researched through real-time quantitative polymerase chain reaction (qPCR), immunohistochemistry (IHC), and western blot (WB) techniques. siRNA technology was then used to inhibit PAPSS1 expression in ESCC cells, and cytologic tests were conducted to research gene affection on cell apoptosis, proliferation, and migration. Then, the expression of Bcl2, Ki67, and Snail was detected using qPCR and WB tests. These experimental data were analyzed by GraphPad software, where the P-value <0.05 was statistically significant. Results. The results showed that PAPSS1 expression level in ESCC tissues was higher than in the adjacent tissues. The data also showed that PAPSS1 was significantly correlated with N stage, and that the patients with high expressions had longer survival time. After transfection for 48 hours, the cell apoptosis rate of siRNA-PAPSS1 transfected groups decreased significantly, whereas the cell proliferation rate and migration ability increased relative to the control. At the same time, the expression levels of Bcl2, Ki67 and Snail were all upregulated by siRNA-PAPSS1. PAPSS1, however, was suppressed. Conclusions. PAPSS1 may be an ESCC suppressor gene, and its specific molecular mechanism in ESCC needs to be further studied

Equivalent stiffness and dynamic response of new mechanical elastic wheel

To investigate the stiffness characteristics of the new mechanical elastic wheel (MEW), the elastic foundation closed circle curved beam model of MEW was established by curved beam theory. With the Laplace transformation and boundary conditions of the governing differential equations, the analytical relations among the radial deformation, bending stiffness of elastic wheel, the elastic foundation stiffness of hinges, elastic wheel laminated structure parameters and excitation frequency were analyzed. The correctness of the curved beam model was validated by the finite element method. Curved beam model validation and the application of the nonlinear finite element model show that the influence of elastic wheel laminated structure and deformation on dynamic response is equal to the equivalent stiffness. The results indicate that the equivalent stiffness and dynamic response of MEW become increased nonlinearly with component content of elastic bead ring, moreover, the equivalent stiffness and dynamic response of MEW increase nonlinearly with the deformation amount of MEW, and the dynamic response significantly decreases with the increase of excitation frequency, under this circumstance that the laminated structure of elastic wheel has been unchanged

Bone marrow mesenchymal stem cells in premature ovarian failure: Mechanisms and prospects

Premature ovarian failure (POF) is a common female reproductive disorder and characterized by menopause, increased gonadotropin levels and estrogen deficiency before the age of 40 years old. The etiologies and pathogenesis of POF are not fully clear. At present, hormone replacement therapy (HRT) is the main treatment options for POF. It helps to ameliorate perimenopausal symptoms and related health risks, but can’t restore ovarian function and fertility fundamentally. With the development of regenerative medicine, bone marrow mesenchymal stem cells (BMSCs) have shown great potential for the recovery of ovarian function and fertility based on the advantages of abundant sources, high capacity for self-renewal and differentiation, low immunogenicity and less ethical considerations. This systematic review aims to summarize the possible therapeutic mechanisms of BMSCs for POF. A detailed search strategy of preclinical studies and clinical trials on BMSCs and POF was performed on PubMed, MEDLINE, Web of Science and Embase database. A total of 21 studies were included in this review. Although the standardization of BMSCs need more explorations, there is no doubt that BMSCs transplantation may represent a prospective therapy for POF. It is hope to provide a theoretical basis for further research and treatment for POF