SIGIFSDP: A Service Id Guided Intelligent Forwarding Service Discovery Protocol in Pervasive Computing Environments

Service discovery constructs a bridge between the service providers and the service consumers, and is a key point in pervasive computing environments. In group-based service discovery protocols, selective forwarding service requests only based on the service group maybe lead to unnecessary forwarding, which produces large packet redundancy. This paper proposes an efficient service discovery protocol: SIGIFSDP (Service Id Guided Intelligent Forwarding Service Discovery Protocol). In SIGIFSDP, based on GSD, SIGIF (Service Id Guided Intelligent Forwarding) is introduced to select the exact forwarding nodes based on the service id. Theoretical analysis and simulation results using GloMosim verify that SIGIFSDP can save the response time, reduce the service request packets, and improve the efficiency of service discovery

The complete chloroplast genomes of three Betulaceae species: implications for molecular phylogeny and historical biogeography

Background Previous phylogenetic conclusions on the family Betulaceae were based on either morphological characters or traditional single loci, which may indicate some limitations. The chloroplast genome contains rich polymorphism information, which is very suitable for phylogenetic studies. Thus, we sequenced the chloroplast genome sequences of three Betulaceae species and performed multiple analyses to investigate the genome variation, resolve the phylogenetic relationships, and clarify the divergence history. Methods Chloroplast genomes were sequenced using the high-throughput sequencing. A comparative genomic analysis was conducted to examine the global genome variation and screen the hotspots. Three chloroplast partitions were used to reconstruct the phylogenetic relationships using Maximum Likelihood and Bayesian Inference approaches. Then, molecular dating and biogeographic inferences were conducted based on the whole chloroplast genome data. Results Betulaceae chloroplast genomes consisted of a small single-copy region and a large single copy region, and two copies of inverted repeat regions. Nine hotspots can be used as potential DNA barcodes for species delimitation. Phylogenies strongly supported the division of Betulaceae into two subfamilies: Coryloideae and Betuloideae. The phylogenetic position of Ostryopsis davidiana was controversial among different datasets. The divergence time between subfamily Coryloideae and Betuloideae was about 70.49 Mya, and all six extant genera were inferred to have diverged fully by the middle Oligocene. Betulaceae ancestors were probably originated from the ancient Laurasia. Discussions This research elucidates the potential of chloroplast genome sequences in the application of developing molecular markers, studying evolutionary relationships and historical dynamic of Betulaceae.It also reveals the advantages of using chloroplast genome data to illuminate those phylogenies that have not been well solved yet by traditional approaches in other plants

In vivo assessment of supra-cervical fetal membrane by MRI 3D CISS: A preliminary study

In approximately 8% of term births and 33% of pre-term births, the fetal membrane (FM) ruptures before delivery

Seasonal Changes in Soil Microbial Community and Co-Occurrence Network of Species of the Genus Corylus

Hazelnut is one of the four major nuts in the world and has high nutritional and economic value. This study employed Illumina sequencing of ITS rDNA and 16S rRNA genes to identify the seasonal changes in soil microbial community, the predominant environmental factors driving microbial community composition, and the differences in soil microbial composition among different species of the genus Corylus. We found that the soil microbial community composition of species of Corylus changed significantly with the change in seasons. Corylus heterophylla and Corylus kweichowensis had more ectomycorrhiza in their soil compared to Corylus avellane. The main factor influencing fungal community composition in soil was the available potassium, while that of bacteria was the total phosphorus content. Co-occurrence network analysis revealed that the ratio of positive interaction to negative interaction in soil of C. heterophylla and Ping’ou (C. heterophylla × C. avellane) was higher, while the negative interaction of soil community structure in C. avellane was greater. The bacterial community was more stable than the fungal community according to microbial diversity and co-occurrence network analyses. The findings of this research may facilitate improvements to the production and soil system management in hazel planting processes

Algorithm for Object Detection using Multi-Core Parallel Computation

AbstractFuzzy support vector machine (FSVM) and template matching are both widely used in object detection. To improve the computational efficiency, an algorithm combining the FSVM classifier with template matching is proposed and we parallelize the template matching algorithm on a multicore platform with OpenMP. The samples are firstly classified by the template matching, and then refined by the FSVM classifier. A three-tier hierarchical pyramid is used in fast matching and a second-order polynomial kernel function is used in the FSVM classifier. The experimental results show that the proposed parallel algorithm significantly improves the computation performance compared with traditional serial algorithms

Dimensionality Reduction of SPD Data Based on Riemannian Manifold Tangent Spaces and Isometry

Symmetric positive definite (SPD) data have become a hot topic in machine learning. Instead of a linear Euclidean space, SPD data generally lie on a nonlinear Riemannian manifold. To get over the problems caused by the high data dimensionality, dimensionality reduction (DR) is a key subject for SPD data, where bilinear transformation plays a vital role. Because linear operations are not supported in nonlinear spaces such as Riemannian manifolds, directly performing Euclidean DR methods on SPD matrices is inadequate and difficult in complex models and optimization. An SPD data DR method based on Riemannian manifold tangent spaces and global isometry (RMTSISOM-SPDDR) is proposed in this research. The main contributions are listed: (1) Any Riemannian manifold tangent space is a Hilbert space isomorphic to a Euclidean space. Particularly for SPD manifolds, tangent spaces consist of symmetric matrices, which can greatly preserve the form and attributes of original SPD data. For this reason, RMTSISOM-SPDDR transfers the bilinear transformation from manifolds to tangent spaces. (2) By log transformation, original SPD data are mapped to the tangent space at the identity matrix under the affine invariant Riemannian metric (AIRM). In this way, the geodesic distance between original data and the identity matrix is equal to the Euclidean distance between corresponding tangent vector and the origin. (3) The bilinear transformation is further determined by the isometric criterion guaranteeing the geodesic distance on high-dimensional SPD manifold as close as possible to the Euclidean distance in the tangent space of low-dimensional SPD manifold. Then, we use it for the DR of original SPD data. Experiments on five commonly used datasets show that RMTSISOM-SPDDR is superior to five advanced SPD data DR algorithms

Seasonal Changes in Soil Microbial Community and Co-Occurrence Network of Species of the Genus <i>Corylus</i>

Hazelnut is one of the four major nuts in the world and has high nutritional and economic value. This study employed Illumina sequencing of ITS rDNA and 16S rRNA genes to identify the seasonal changes in soil microbial community, the predominant environmental factors driving microbial community composition, and the differences in soil microbial composition among different species of the genus Corylus. We found that the soil microbial community composition of species of Corylus changed significantly with the change in seasons. Corylus heterophylla and Corylus kweichowensis had more ectomycorrhiza in their soil compared to Corylus avellane. The main factor influencing fungal community composition in soil was the available potassium, while that of bacteria was the total phosphorus content. Co-occurrence network analysis revealed that the ratio of positive interaction to negative interaction in soil of C. heterophylla and Ping’ou (C. heterophylla × C. avellane) was higher, while the negative interaction of soil community structure in C. avellane was greater. The bacterial community was more stable than the fungal community according to microbial diversity and co-occurrence network analyses. The findings of this research may facilitate improvements to the production and soil system management in hazel planting processes

Characterization of the Relationship of CDKL5 with MeCP2 and Dnmt1 in PrimaryRat Cortical Neurons

ABSTRACT Cyclin-dependent kinase-like 5 (CDKL5) is a protein kinase that is homologous to mitogen-activated protein kinases (MAPKs) and cyclin-dependent kinases (CDKs). Mutations in the CDKL5 gene cause X-linked infantile spasms and phenotypes that overlap with that of Rett syndrome, which is a neurodevelopmental disorder caused primarily by mutations in the methyl CpG binding protein 2 gene (MECP2). Previous studies in transfected cell lines showed that CDKL5 interacts with MeCP2 and DNA (cytosine-5)-methyltransferase 1 (Dnmt1). However, little is known about the relationships of CDKL5 with interacting proteins in primary neuronal cultures. In this study, we investigated the expression patterns of CDKL5, MeCP2 and Dnmt1, and their interaction in cultured rat cortical neurons. Using real-time PCR analysis, we found that CDKL5, MeCP2 and Dnmt1 have similar expression patterns at the mRNA level. In contrast, the expression patterns of those proteins at the protein level are different and could be inversely correlated, as shown by western blotting. Using co-immunoprecipitation, we further demonstrated that CDKL5 interacts with MeCP2 and Dnmt1 in primary rat cortical neurons. These data suggest that a functional link exists among CDKL5, MeCP2 and Dnmt1 during neuronal development and may provide further insight into the pathogenesis of Rett syndrome