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Sapindaceae is a family of flowering plants, also known as the soapberry family, comprising 141 genera and about 1900 species (Pedro et al., 2010). Most of them are distributed in tropical and subtropical regions, including trees, shrubs, also woody or herbaceous vines. Some are dioecious, while others are monoecious. Many Sapindaceae species possess great economic value; some furnish delicious fruits, like lychee (Litchi chinensis), longan (Dimocarpus longan), rambutan (Nephelium lappaceum); and ackee (Blighia sapida) - the national fruit of Jamaica; some produce abundance secondary metabolites, like saponin from soapberry (Sapindus mukorossi), and seed oil from yellowhorn (Xanthoceras sorbifolium); some yield valuable timber including maple (Acer spp.) and buckeye (Aesculus glabra); and some are of great herbal medicinal value, like balloon-vine (Cardiospermum halicacabum).In the last decade, with the rocketing of next generation sequencing (NGS) and genomic technologies, the full genome sequences of several Sapindaceae plants have been resolved (Lin et al., 2017; Liang et al., 2019; Yang et al., 2019; Zhang et al., 2021; Hu et al., 2022; Xue et al., 2022). Among them, our recent publication of the lychee genome attracted broad attention (Edger, 2022; Hu et al., 2022; Lyu, 2022). Now the post-genome era arrives for Sapindaceae, however, there is no public genomic database available for any Sapindaceae species, let alone an integrative database for the whole Sapindaceae family. A unified data platform is in urgent need to collect, manage and share relevant data resources. Therefore, we integrated our home-brew NGS data with all publicly available data for seven Sapindaceae plants and constructed theSapinaceae Genomic DataBase, named SapBase (www.sapindaceae.com), in order to provide genomic resources and an online powerful analytic platform for scientific research on Sapinaceae species and comparative studies with other plants.

For the multi-rope structure of the container crane system and its large mass payload anti-swing positioning problem, an equivalent double-swing model based on radial spring-dampers is established and a time-varying PD sliding mode controller (TVPD-SMC) with improved transient performance is proposed. In particular, the dynamics of the container crane system are first analyzed using the Lagrange method, and an equivalent double pendulum dynamics model of the crane is established. Compared with the traditional double pendulum model, this model ensures the accuracy of modeling without measuring the second pendulum angle. On this basis, an enhanced coupled time-varying sliding mode control method is designed to eliminate the sliding mode control method’s reaching phase and improves the robustness of the controller. Finally, the convergence and stability of the closed-loop system are proved using the Lyapunov technique and the Lasalle invariance theorem, and the simulation results demonstrate the effectiveness of the method.

As an essential element in industrial steel, automatic defect recognition can guarantee the surface quality through focused supervised learning with ample labelled samples. However, defect recognition inevitably features with data‐limiting characteristic under the influence of costly expert labelling. To address this problem, a novel framework, Instance Contrast (InCo), is proposed with the inspiration of contrastive learning. This framework consists of two streams. One with instance labels attributed to the unlabelled data in each batch for classification, which is called Batch Instance Discrimination (BID). The other with different enhanced samples embedding of the same image aggregated by a new function named dynamic weighted variance loss (DWV loss). Therefore, better semantic features can be learned by model due to the moderation of embedding distance between similar steel defect images. Experimental results on the NEU‐CLS database validate that the proposed method achieves 89.86% classification accuracy with only fine‐tuning on the 1:32 training data, outperforming other general contrastive learning methods.

In this paper, we propose an efficient algorithm to accelerate the existing Broad Learning System (BLS) algorithm for new added nodes. The existing BLS algorithm computes the output weights from the pseudoinverse with the ridge regression approximation, and updates the pseudoinverse iteratively. As a comparison, the proposed BLS algorithm computes the output weights from the inverse Cholesky factor of the Hermitian matrix in the calculation of the pseudoinverse, and updates the inverse Cholesky factor efficiently. Since the Hermitian matrix in the definition of the pseudoinverse is smaller than the pseudoinverse, the proposed BLS algorithm can reduce the computational complexity, and usually requires less than $\frac {2}{3}$ of complexities with respect to the existing BLS algorithm. Our experiments on the Modified National Institute of Standards and Technology (MNIST) dataset show that the speedups in accumulative training time and each additional training time of the proposed BLS over the existing BLS are 24.81%~ 37.99% and 36.45%~ 58.96%, respectively, and the speedup in total training time is 37.99%. In our experiments, the proposed BLS and the existing BLS both achieve the same testing accuracy when the tiny differences (≤ 0.05%) caused by the numerical errors are neglected, and the above-mentioned tiny differences and numerical errors become zeroes and ignorable, respectively, when the ridge parameter is not too small.

Background Psoriasis is a chronic recurrent inflammatory disease. Mesenchymal stem cells (MSCs) can regulate the inflammatory microenvironment, thereby controlling the proliferation, differentiation, and migration of immune cells. Connexin 43(Cx43), a key gap junction protein, has been shown to form gap junctions for communication between neighboring cells. Objective We investigated the expression of Cx43 in dermal mesenchymal stem cells (DMSCs) derived from psoriasis patients and explored the relationship between the Cx43-mediated gap junction intercellular communication (GJIC) and DMSCs. Methods Human DMSCs were isolated and propagated in adherent culture. Quantitative real-time reverse transcription PCR and western blot and immunofluorescence were used to detect the expression and localization of Cx43 in DMSCs. Fluorescence redistribution after photobleaching was performed to assess adjacent DMSCs GJIC. CCK8 was used to detect the proliferation of DMSCs before and after gap junction blocker (18α-glycyrrhetinic acid; AGA) treatment. Cell energy metabolism was analyzed with an energy metabolism analyzer. Results Cx43 was located in the cytoplasm and cytomembrane, as well as partially in the nucleus of DMSCs. The expression of Cx43 in psoriasis DMSCs was higher than that in control samples and the gap junction function was enhanced. In addition, the glycolysis and mitochondrial respiration of psoriasis DMSCs were also enhanced. However, AGA inhibited the expression of Cx43, attenuated GJIC function, and inhibited the proliferation of DMSCs. Conclusions Our results indicated that the expression of Cx43 in DMSCs from psoriasis lesions is increased and that the inhibition of Cx43 leads to the inhibition of both GJIC and DMSCs proliferation.

Background Genome-wide association studies have identified over 120 risk loci for psoriasis. However, most of the variations are located in non-coding region with high frequency and small effect size. Pathogenetic variants are rarely reported except HLA-C*0602 with the odds ratio being approximately 4.0 in Chinese population. Although rare variations still account for a small proportion of phenotypic variances in complex diseases, their effect on phenotypes is large. Recently, more and more studies focus on the low-frequency functional variants and have achieved a certain amount of success. Method Whole genome sequencing and sanger sequencing was performed on 8 MZ twin pairs discordant for psoriasis to scan and verified the de novo mutations (DNMs). Additionally, 665 individuals with about 20 years' medical history versus 2054 healthy controls and two published large population studies which had about 8 years’ medical history (including 10,727 cases versus 10,582 controls) were applied to validate the enrichment of rare damaging mutations in two DNMs genes. Besides, to verify the pathogenicity of candidate DNM in C3, RNA-sequencing for CD4+, CD8+ T cells of twins and lesion, non-lesion skin of psoriasis patients were carried out. Meanwhile, the enzyme-linked immunosorbent assay kit was used to detect the level of C3, C3b in the supernatant of peripheral blood. Result A total of 27 DNMs between co-twins were identified. We found six of eight twins carry HLA-C∗0602 allele which have large effects on psoriasis. And it is interesting that a missense mutation in SPRED1 and a splice region mutation in C3 are found in the psoriasis individuals in the other two MZ twin pairs without carrying HLA-C*0602 allele. In the replication stage, we found 2 loss-of-function (LOF) variants of C3 only in 665 cases with about 20 years' medical history and gene-wise analysis in 665 cases and 2054 controls showed that the rare missense mutations in C3 were enriched in cases (OR = 1.91, P = 0.0028). We further scanned the LOF mutations of C3 in two published studies (about 8 years’ medical history), and found one LOF mutation in the case without carrying HLA-C*0602. In the individual with DNM in C3, RNA sequencing showed the expression level of C3 in skin was significant higher than healthy samples in public database (TPM fold change = 1.40, P = 0.000181) and ELISA showed protein C3 in peripheral blood was higher (~2.2-fold difference) than the other samples of twins without DNM in C3. Conclusion To the best of our knowledge, this is the first report that DNM in C3 is the likely pathological mutations, and it provided a better understanding of the genetic etiology of psoriasis and additional treatments for this disease.

This brief applies the synchronization to solve control problem of redundantly actuated parallel manipulators. With the synchronization method, a new controller termed active joint-synchronization (AJ-S) controller is developed for a 2-degree-of-freedom (DOF) redundantly actuated parallel manipulator. The dynamic model of the parallel manipulator is formulated in the active joint space, in which the internal force is calculated by the projection method and the friction is depicted with the Coulomb + viscous friction model. By defining the tracking error, synchronization error, coupled error, and the referenced trajectory vector of the active joints, the AJ-S controller based on the dynamic model is designed. And the AJ-S controller is proven to guarantee asymptotic convergence to zero of both tracking and synchronization errors by the Barbalat's lemma. The AJ-S controller is implemented in the trajectory tracking experiments of an actual 2-DOF redundantly actuated parallel manipulator, and the superiority of the AJ-S controller over the well-known tracking controller is studied.

For the position tracking in DC motor with unknown bound time-varying dead zone uncertainties, a novel sliding mode adaptive controller is proposed by means of sliding mode and function approximation technique in this paper. First, control law with an uncertain term and another compensative term is obtained using sliding mode technique, and then the function approximation technique is employed to transform the uncertain term into finite combinations of orthonormal basis functions. The concrete expressions of uncertain term and compensative term can thus be derived based on the Lyapunov design. Actual system control experiments of the sliding adaptive control proposed are given.

In order to reduce the chattering, which is the chief backward of sliding mode controller. This paper is devoted to the chattering phenomenon in sliding mode control system with Adaptive Exponential Reaching Law(AERL). According the distance between the current states and the sliding switching surface, the AERL changes the reaching speed dynamically. That is, the system states can reach the switching surface fast when far away from it, and the speed slow down when the states enter into certain scope. It is proved that the AERL meets the sliding mode existence condition and the reaching condition. The variable structure controller based on AERL satisfies the requirements of system rapidness and stability. The effectiveness of the AERL in reducing the chattering of the Variable Structure Control(VSC) is validated by simulation results.

This paper proposes a position tracking control scheme for the ball and plate system. At first, the property of the ball and plate control system is analyzed, and the path tracking control problem is divided into subproblems of ball position control and plate angle control. Afterwards, a path tracking sliding mode control algorithm is proposed for the ball position control based on dynamic model of the ball motion system and basic principle of sliding mode control, asymptotical stability of the close-loop system is proved mathematically through Lyapunov stability theory as well. The proposed sliding mode control algorithm eliminates the effect of time-varying uncertain friction while the ball is rolling on the plate surface, and thus the path tracking precision is improved. Finally, control performance of the proposed sliding mode control algorithm is validated by simulation experiment.

Dead zone characteristics exist in many physical components of control systems. They are nonlinear features particularly in direct current (DC) motor position tracking control systems, mainly caused by the uncertain time-varying nonlinear friction. They can severely limit the control performance owing to their non-smooth nonlinearities. However, dead zone characteristics usually are not easy to be known exactly and may vary with time in practical. In addition to the uncertainties in the linear part of the plant, controllers are often required to accommodate time-varying dead zone uncertainties. In general, there are two usual methods treating the systems with uncertain time-varying dead zone characteristics caused by uncertain nonlinear frictions in DC motor position control systems. The first one is to separate the unknown dead zone from the original DC motor systems and construct an adaptive dead zone inverse, and then compensate the effects of unknown dead zone characteristics (Gang & Kokotovic, 1994; Cho & Bai, 1998; Wang et al., 2004; Zhou et al., 2006). The second method is to deal with both the unknown dead zone characteristics and all the other uncertainties as one uniform uncertainty, thereupon design proper compensator (Wang et al., 2004) or adaptive controller which can counteract the effects of uncertainty(Selmic & Lewis, 2000; Tian-Ping et al., 2005). Furthermore, dead zone uncertainties' bounds remain unknown in many practical DC motor control systems. This problem can't be coped with conventional sliding mode controller (Young et al., 1999; Hung et al., 1993) and general adaptive controller (Gang & Kokotovic, 1994; Cho & Bai, 1998; Wang et al., 2004; Zhou et al., 2006; Wang et al., 2004; Selmic & Lewis, 2000; Tian Ping et al., 2005; Young et al., 1999; Hung et al., 1993). In order to deal with nonlinear systems with unknown bound time-varying uncertainties, adaptive control schemes combined with sliding mode technique have been developed (Chyau-An & Yeu-Shun, 2001; Chyau-An & Yuan-Chih, 2004; Huang & Chen, 2004; Chen & Huang, 2004). These control schemes can transform the unknown bound time-varying uncertainties into finite combinations of Fourier series as long as the uncertainties satisfy Dirichlet condition, so that they can be estimated by updating the Fourier coefficients. Since the coefficients are timeinvariant, update laws are easily obtained from the Lyapunov design to guarantee output error convergence. This chapter is devided into two parts. In the first part, for the position tracking in DC motor with unknown bound time-varying dead zone uncertainties, we’ll propose a Function