Priority-driven self-optimizing power control scheme for interlinking converters of hybrid AC/DC microgrid clusters in decentralized manner

Hybrid AC/DC microgrid clusters are key building blocks of smart grid to support sustainable and resilient urban power systems. In microgrid clusters, the subgrid load-priorities and power quality requirements for different areas vary significantly. To realize optimal power exchanges among microgrid clusters, this paper proposes a decentralized self-optimizing power control scheme for interlinking converters (ILC) of hybrid microgrid clusters. A priority-driven optimal power exchange model of ILCs is built considering the priorities and capacities in subgrids. The optimization objective is to minimize the total DC-voltage/AC-frequency state deviations of subgrids. To realize the decentralized power flow control, an optimal-oriented quasi-droop control strategy of ILCs is introduced to not only achieve a flexible self-optimizing power flow management, but also provide an ancillary function of voltage support. Consequently, as each of ILCs only monitors the local AC-side frequency and DC-side voltage signals, the whole optimal power control of the wide-area microgrid clusters is achieved in a decentralized manner without any communication link. Thus, the proposed control algorithm has the features of decreased cost, increased scalability, reduced geographic restrictions and high resilience in terms of communication faults. Finally, the proposed method is validated by case studies with four interconnected microgrids through hardware-in-loop tests

Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens

<p>Abstract</p> <p>Background</p> <p>The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens.</p> <p>Results</p> <p>Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using <it>Drosophila </it>embryos [Additional files <supplr sid="S1">1</supplr>, <supplr sid="S2">2</supplr>], dataset for cell cycle phase identification using HeLa cells [Additional files <supplr sid="S1">1</supplr>, <supplr sid="S3">3</supplr>, <supplr sid="S4">4</supplr>] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a <it>Drosophila </it>genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms.</p> <p>Conclusion</p> <p>We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens.</p

Three-Dimensional Magnetic Reconnection With a Spatially Confined X-Line Extent: Implications for Dipolarizing Flux Bundles and the Dawn-Dusk Asymmetry

Using 3‐D particle‐in‐cell simulations, we study magnetic reconnection with the X‐line being spatially confined in the current direction. We include thick current layers to prevent reconnection at two ends of a thin current sheet that has a thickness on an ion inertial (di) scale. The reconnection rate and outflow speed drop significantly when the extent of the thin current sheet in the current direction is urn:x-wiley:jgra:media:jgra54890:jgra54890-math-0001. When the thin current sheet extent is long enough, we find that it consists of two distinct regions; a suppressed reconnecting region (on the ion‐drifting side) exists adjacent to the active region where reconnection proceeds normally as in a 2‐D case with a typical fast rate value ≃0.1. The extent of this suppression region is ≃O(10di), and it suppresses reconnection when the thin current sheet extent is comparable or shorter. The time scale of current sheet thinning toward fast reconnection can be translated into the spatial scale of this suppression region, because electron drifts inside the ion diffusion region transport the reconnected magnetic flux, which drives outflows and furthers the current sheet thinning, away from this region. This is a consequence of the Hall effect in 3‐D. While the existence of this suppression region may explain the shortest possible azimuthal extent of dipolarizing flux bundles at Earth, it may also explain the dawn‐dusk asymmetry observed at the magnetotail of Mercury, which has a global dawn‐dusk extent much shorter than that of Earth.publishedVersio

Refinement of the GINGF3 locus for hereditary gingival fibromatosis

Hereditary gingival fibromatosis (HGF) is a rare, clinically variable disorder characterized by slowly progressive fibrous overgrowth of the gingiva. Four gene loci have been mapped for autosomal dominant non-syndromic HGF (adHGF). The molecular basis of adHGF remains largely unknown, with only a single SOS1 gene mutation identified so far at the gingival fibromatosis 1 (GINGF1) locus in one family. We identified an adHGF family with ten affected individuals in whom onset of gingival fibromatosis concurred with the eruption of the primary teeth. In order to identify the molecular basis in this family, we tested for linkage of the disease to known adHGF loci. A maximal multipoint logarithm of the odds score of 3.91 was obtained with marker D2S390 (θ = 0) at the GINGF3 locus on chromosome 2p23.3–p22.3, and linkage to other known loci was excluded. Sequencing two candidate genes, ALK and C2orf18, and a single nucleotide polymorphisms array analysis did not reveal a mutation or copy number variation in a patient from the family. We refined the GINGF3 locus to a 6.56-cM, 8.27-Mb region containing 112 known and hypothetical genes, and our data and a search of the literature suggest that GINGF3 is a major adHGF locus

Genomic organisation and alternative splicing of mouse and human thioredoxin reductase 1 genes

BACKGROUND: Thioredoxin reductase (TR) is a redox active protein involved in many cellular processes as part of the thioredoxin system. Presently there are three recognised forms of mammalian thioredoxin reductase designated as TR1, TR3 and TGR, that represent the cytosolic, mitochondrial and novel forms respectively. In this study we elucidated the genomic organisation of the mouse (Txnrd1) and human thioredoxin reductase 1 genes (TXNRD1) through library screening, restriction mapping and database mining. RESULTS: The human TXNRD1 gene spans 100 kb of genomic DNA organised into 16 exons and the mouse Txnrd1 gene has a similar exon/intron arrangement. We also analysed the alternative splicing patterns displayed by the mouse and human thioredoxin reductase 1 genes and mapped the different mRNA isoforms with respect to genomic organisation. These isoforms differ at the 5' end and encode putative proteins of different molecular mass. Genomic DNA sequences upstream of mouse exon 1 were compared to the human promoter to identify conserved elements. CONCLUSIONS: The human and mouse thioredoxin reductase 1 gene organisation is highly conserved and both genes exhibit alternative splicing at the 5' end. The mouse and human promoters share some conserved sequences

First insights into the phylogenetic diversity of Mycobacterium tuberculosis in Nepal

BACKGROUND: Tuberculosis (TB) is a major public health problem in Nepal. Strain variation in Mycobacterium tuberculosis may influence the outcome of TB infection and disease. To date, the phylogenetic diversity of M. tuberculosis in Nepal is unknown. METHODS AND FINDINGS: We analyzed 261 M. tuberculosis isolates recovered from pulmonary TB patients recruited between August 2009 and August 2010 in Nepal. M. tuberculosis lineages were determined by single nucleotide polymorphisms (SNP) typing and spoligotyping. Drug resistance was determined by sequencing the hot spot regions of the relevant target genes. Overall, 164 (62.8%) TB patients were new, and 97 (37.2%) were previously treated. Any drug resistance was detected in 50 (19.2%) isolates, and 16 (6.1%) were multidrug-resistant. The most frequent M. tuberculosis lineage was Lineage 3 (CAS/Delhi) with 106 isolates (40.6%), followed by Lineage 2 (East-Asian lineage, includes Beijing genotype) with 84 isolates (32.2%), Lineage 4 (Euro-American lineage) with 41 (15.7%) isolates, and Lineage 1 (Indo-Oceanic lineage) with 30 isolates (11.5%). Based on spoligotyping, we found 45 different spoligotyping patterns that were previously described. The Beijing (83 isolates, 31.8%) and CAS spoligotype (52, 19.9%) were the dominant spoligotypes. A total of 36 (13.8%) isolates could not be assigned to any known spoligotyping pattern. Lineage 2 was associated with female sex (adjusted odds ratio [aOR] 2.58, 95% confidence interval [95% CI] 1.42-4.67, p = 0.002), and any drug resistance (aOR 2.79; 95% CI 1.43-5.45; p = 0.002). We found no evidence for an association of Lineage 2 with age or BCG vaccination status. CONCLUSIONS: We found a large genetic diversity of M. tuberculosis in Nepal with representation of all four major lineages. Lineages 3 and 2 were dominating. Lineage 2 was associated with clinical characteristics. This study fills an important gap on the map of the M. tuberculosis genetic diversity in the Asian reg

Multiple ITS Copies Reveal Extensive Hybridization within Rheum (Polygonaceae), a Genus That Has Undergone Rapid Radiation

During adaptive radiation events, characters can arise multiple times due to parallel evolution, but transfer of traits through hybridization provides an alternative explanation for the same character appearing in apparently non-sister lineages. The signature of hybridization can be detected in incongruence between phylogenies derived from different markers, or from the presence of two divergent versions of a nuclear marker such as ITS within one individual.In this study, we cloned and sequenced ITS regions for 30 species of the genus Rheum, and compared them with a cpDNA phylogeny. Seven species contained two divergent copies of ITS that resolved in different clades from one another in each case, indicating hybridization events too recent for concerted evolution to have homogenised the ITS sequences. Hybridization was also indicated in at least two further species via incongruence in their position between ITS and cpDNA phylogenies. None of the ITS sequences present in these nine species matched those detected in any other species, which provides tentative evidence against recent introgression as an explanation. Rheum globulosum, previously indicated by cpDNA to represent an independent origin of decumbent habit, is indicated by ITS to be part of clade of decumbent species, which acquired cpDNA of another clade via hybridization. However decumbent and glasshouse morphology are confirmed to have arisen three and two times, respectively.These findings suggested that hybridization among QTP species of Rheum has been extensive, and that a role of hybridization in diversification of Rheum requires investigation