A Comprehensive Evaluation of the DFP Method for Geometric Constraint Solving Algorithm Using PlaneGCS

The development of open-source geometric constraint solvers is a pressing research topic, as commercially available solvers may not meet the research requirements. In this paper, we examine the use of numerical methods in PlaneGCS, an open-source geometric constraint solver within the FreeCAD CAD software. Our study focuses on PlaneGCS\u27s constraint solving algorithms and the three built-in single-subsystem solving methods: BFGS, LM, and Dogleg. Based on our research results, the DFP method was implemented in PlaneGCS and was successfully verified in FreeCAD. To evaluate the performance of the algorithms, we used the solving state of the constraint system as a test criterion, and analysed their solving time, adaptability, and number of iterations. Our results highlight the performance differences between the algorithms and provide empirical guidance for selection of constraint solving algorithms and research based on open-source geometric constraint solvers

Towards an Open-Source Industry CAD: A Review of System Development Methods

Due to the industry knowledge barrier, general computer aided design (CAD) software cannot do everything in digital manufacturing by itself, and industry CAD, therefore, occupies a crucial position in the CAD industry. To develop industry CAD smoothly, open-source is the best choice. We analyzed recent examples of industry CAD development and divided the development methods into four types: development based on the graphics development environment, development based on geometric modelling kernel, secondary development based on general CAD, and hybrid development. We analyzed the characteristics of various methods and believe that the method based on the hybrid development of the geometric modelling kernel and the graphics development environment is the best open-source industry CAD development method. We proposed a system architecture of open-source industry CAD for reference and conducted a preliminary exploration of the reference architecture to verify its feasibility

Self doping effect and successive magnetic transitions in superconducting Sr2_2VFeAsO3_3

We have studied a quinary Fe-based superconductor Sr$_2$VFeAsO$_3$ by the measurements of x-ray diffraction, x-ray absorption, M\"{o}ssbauer spectrum, resistivity, magnetization and specific heat. This apparently undoped oxyarsenide is shown to be self doped via electron transfer from the V$^{3+}$ ions. We observed successive magnetic transitions within the VO$_2$ layers: an antiferromagnetic transition at 150 K followed by a weak ferromagnetic transition at 55 K. The spin orderings within the VO$_2$ planes are discussed based on mixed valence of V$^{3+}$ and V$^{4+}$.Comment: One Table and more references are adde

Genetic Basis of Sexual Maturation Heterosis: Insights From Ovary lncRNA and mRNA Repertoire in Chicken

Sexual maturation is fundamental to the reproduction and production performance, heterosis of which has been widely used in animal crossbreeding. However, the underlying mechanism have long remained elusive, despite its profound biological and agricultural significance. In the current study, the reciprocal crossing between White Leghorns and Beijing You chickens were performed to measure the sexual maturation heterosis, and the ovary lncRNAs and mRNAs of purebreds and crossbreeds were profiled to illustrate molecular mechanism of heterosis. Heterosis larger than 20% was found for pubic space and oviduct length, whereas age at first egg showed negative heterosis in both crossbreeds. We identified 1170 known lncRNAs and 1994 putative lncRNAs in chicken ovary using a stringent pipeline. Gene expression pattern showed that nonadditivity was predominant, and the proportion of nonadditive lncRNAs and genes was similar between two crossbreeds, ranging from 44.24% to 49.15%. A total of 200 lncRNAs and 682 genes were shared by two crossbreeds, respectively. GO and KEGG analysis showed that the common genes were significantly enriched in the cell cycle, animal organ development, gonad development, ECM-receptor interaction, calcium signaling pathway and GnRH signaling pathway. Weighted gene co-expression network analysis (WGCNA) identified that 7 out of 20 co-expressed lncRNA-mRNA modules significantly correlated with oviduct length and pubic space. Interestingly, genes harbored in seven modules were also enriched in the similar biological process and pathways, in which nonadditive lncRNAs, such as MSTRG.17017.1 and MSTRG.6475.20, were strongly associated with nonadditive genes, such as CACNA1C and TGFB1 to affect gonad development and GnRH signaling pathway, respectively. Moreover, the results of real-time quantitative PCR (RT-qPCR) correlated well with the transcriptome data. Integrated with positive heterosis of serum GnRH and melatonin content detected in crossbreeds, we speculated that nonadditive genes involved in the GnRH signaling pathway elevated the gonad development, leading to the sexual maturation heterosis. We characterized a systematic landscape of ovary lncRNAs and mRNAs related to sexual maturation heterosis in chicken. The quantitative exploration of hybrid transcriptome changes lays foundation for genetic improvement of sexual maturation traits and provides insights into endocrine control of sexual maturation

Text feature extraction based on deep learning: a review

Abstract Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction

Fetal bovine serum, an important factor affecting the reproducibility of cell experiments

Abstract Fetal bovine serum (FBS) is a natural medium used in cell cultures containing the large amount of nutrients necessary for cell growth and is often used for in vitro cultures of animal cells. Although FBS plays a vital role in cell cultures, there are small molecules contained within FBS that remain unidentified, and their effects on cultured cells is poorly understood. Here, we report that different brands of FBS have varying influences on the background expression of IL-8, not TNFα and IL1β in epithelial cells. The endogenous small molecules in FBS and ERK pathways may contribute to these effects. In addition, FBS form the IL-8 stimulation and IL-8 non-responsive groups have different metabolome profiles. Overall, our study suggests that metabolites in FBS should be included in the quantitative considerations when conducting cell experiments, especially immune-related experiments, to improve the repeatability of experimental results in scientific papers; IL-8 could thus be an important factor in selecting FBS

A Novel Position Compensation Scheme for Cable-Pulley Mechanisms Used in Laparoscopic Surgical Robots

The tendon driven mechanism using a cable and pulley to transmit power is adopted by many surgical robots. However, backlash hysteresis objectively exists in cable-pulley mechanisms, and this nonlinear problem is a great challenge in precise position control during the surgical procedure. Previous studies mainly focused on the transmission characteristics of the cable-driven system and constructed transmission models under particular assumptions to solve nonlinear problems. However, these approaches are limited because the modeling process is complex and the transmission models lack general applicability. This paper presents a novel position compensation control scheme to reduce the impact of backlash hysteresis on the positioning accuracy of surgical robots’ end-effectors. In this paper, a position compensation scheme using a support vector machine based on feedforward control is presented to reduce the position tracking error. To validate the proposed approach, experimental validations are conducted on our cable-pulley system and comparative experiments are carried out. The results show remarkable improvements in the performance of reducing the positioning error for the use of the proposed scheme