Existence of positive solutions for nth-order boundary value problem with sign changing nonlinearity

In this paper, we investigate the existence of positive solutions for singular $n$th-order boundary value problem $u^{(n)}(t)+a(t)f(t,u(t))=0,\quad 0\le t\le1,$ $u^{(i)}(0)=u^{(n-2)}(1)=0,\quad 0\le i\le n-2,$ where $n\ge2$, $a\in C((0,1),[0,+\infty))$ may be singular at $t=0$ and (or) $t=1$ and the nonlinear term $f$ is continuous and is allowed to change sign. Our proofs are based on the method of lower solution and topology degree theorem

Positive solutions for nonlinear semipositone nth-order boundary value problems

In this paper, we investigate the existence of positive solutions for a class of nonlinear semipositone $n$th-order boundary value problems. Our approach relies on the Krasnosel'skii fixed point theorem. The result of this paper complement and extend previously known result

A Dynamical Reliability Prediction Algorithm for Composite Service

Dynamic selection and dynamic binding and rebinding at runtime are new characters of composite services. The traditional static reliability prediction models are unsuitable to dynamic composite services. A new reliability predicting algorithm for composite services is proposed in this paper. Firstly, a composite service is decomposed into composition unites (executing path, composite module and atomic service) according to their constituents. Consequently, a hierarchical graph of all composite units is constructed. Lastly, a new dynamic reliability prediction algorithm is presented. Comparing with the traditional reliability model, the new dynamic reliability approach is more flexible, which does not recompute reliability for all composite units and only computes the reliability of the effected composite units. In addition, an example to show how to measure the reliability based on our algorithm is designed. The experimental results show our proposed methods can give an accurate estimation of reliability. Furthermore, a more flexible sensitivity analysis is performed to determine which service component has the most significant impact on the improvement of composite service reliability

Shape-Controlled Generation of Gold Nanoparticles Assisted by Dual-Molecules: The Development of Hydrogen Peroxide and Oxidase-Based Biosensors

With the assist of dual-molecules, 2-(N-morpholino)ethanesulfonic acid (MES) and sodium citrate, gold nanoparticles (GNPs) with different shapes can be generated in the H2O2-mediated reduction of chloroauric acid. This one-pot reaction can be employed to sensitively detect H2O2, probe substrates or enzymes in oxidase-based reactions as well as prepare branched GNPs controllably. By the “naked eye,” 20 μM H2O2, 0.1 μM glucose, and 0.26 U/mL catalase could be differentiated, respectively. By spectrophotometer, the detected limits of H2O2, glucose, and catalase were 1.0 μM, 0.01 μM, and 0.03 U/mL, respectively, and the detection linear ranges for them were 5.0–400 μM, 0.01–0.3 mM, and 0.03–0.78 U/mL, respectively. The proposed “dual-molecules assist” strategy probably paves a new way for the fabrication of nanosensors based on the growth of anisotropic metal nanoparticles, and the developed catalase sensor can probably be utilized to fabricate ultrasensitive ELISA methods for various analytes

A Cycle Deep Belief Network Model for Multivariate Time Series Classification

Multivariate time series (MTS) data is an important class of temporal data objects and it can be easily obtained. However, the MTS classification is a very difficult process because of the complexity of the data type. In this paper, we proposed a Cycle Deep Belief Network model to classify MTS and compared its performance with DBN and KNN. This model utilizes the presentation learning ability of DBN and the correlation between the time series data. The experimental results showed that this model outperforms other four algorithms: DBN, KNN_ED, KNN_DTW, and RNN

Chromosome-Level Genome Assembly for Acer pseudosieboldianum and Highlights to Mechanisms for Leaf Color and Shape Change

Acer pseudosieboldianum (Pax) Komarov is an ornamental plant with prominent potential and is naturally distributed in Northeast China. Here, we obtained a chromosome-scale genome assembly of A. pseudosieboldianum combining HiFi and Hi-C data, and the final assembled genome size was 690.24 Mb and consisted of 287 contigs, with a contig N50 value of 5.7 Mb and a BUSCO complete gene percentage of 98.4%. Genome evolution analysis showed that an ancient duplication occurred in A. pseudosieboldianum. Phylogenetic analyses revealed that Aceraceae family could be incorporated into Sapindaceae, consistent with the present Angiosperm Phylogeny Group system. We further construct a gene-to-metabolite correlation network and identified key genes and metabolites that might be involved in anthocyanin biosynthesis pathways during leaf color change. Additionally, we identified crucial teosinte branched1, cycloidea, and proliferating cell factors (TCP) transcription factors that might be involved in leaf morphology regulation of A. pseudosieboldianum, Acer yangbiense and Acer truncatum. Overall, this reference genome is a valuable resource for evolutionary history studies of A. pseudosieboldianum and lays a fundamental foundation for its molecular breeding

RPL22 Overexpression Promotes Psoriasis-Like Lesion by Inducing Keratinocytes Abnormal Biological Behavior

BackgroundKeratinocytes of psoriasis have anti-apoptotic properties including delayed apoptosis process, accelerated proliferation metabolism and postponed differentiation process. However, the specific mechanism leading to the abnormal biological behavior of keratinocytes remains unclear.ObjectivesWe investigated the role of increased RPL22 expression in regulating the abnormal biological behavior of keratinocytes and the mechanism of regulation of RPL22 expression in skin lesions of psoriatic patients.MethodsWe examined clinical samples and utilized cytokine-induced cell and IMQ-treated mouse models. We determined the expression and functions of RPL22 in vitro and in vivo.ResultsWe showed that RPL22 expression was significantly increased in the skin lesions of psoriasis patients and IMQ-treated psoriatic-like mice. Such increased expression is attributed to hyperacetylation of histone H3K27 in the promoter region of RPL22. Interestingly, overexpression of RPL22 enhanced keratinocyte proliferation by increasing cyclinD1 expression and accelerated CD4+T cells recruitment via upregulating CXCL10 expression. Finally, we demonstrated that RPL22 overexpression promoted psoriasiform phenotypes in IMQ-induced mouse skins.ConclusionsThese findings suggested that RPL22 regulates keratinocytes abnormal biological behavior and contributes to the development of psoriatic phenotypes. Thus, RPL22 might be a novel potential molecular target for treatment of psoriasis