Peer-to-Peer EnergyTrade: A Distributed Private Energy Trading Platform

Blockchain is increasingly being used as a distributed, anonymous, trustless framework for energy trading in smart grids. However, most of the existing solutions suffer from reliance on Trusted Third Parties (TTP), lack of privacy, and traffic and processing overheads. In our previous work, we have proposed a Secure Private Blockchain-based framework (SPB) for energy trading to address the aforementioned challenges. In this paper, we present a proof-on-concept implementation of SPB on the Ethereum private network to demonstrates SPB's applicability for energy trading. We benchmark SPB's performance against the relevant state-of-the-art. The implementation results demonstrate that SPB incurs lower overheads and monetary cost for end users to trade energy compared to existing solutions

STS-CCL: Spatial-Temporal Synchronous Contextual Contrastive Learning for Urban Traffic Forecasting

Efficiently capturing the complex spatiotemporal representations from large-scale unlabeled traffic data remains to be a challenging task. In considering of the dilemma, this work employs the advanced contrastive learning and proposes a novel Spatial-Temporal Synchronous Contextual Contrastive Learning (STS-CCL) model. First, we elaborate the basic and strong augmentation methods for spatiotemporal graph data, which not only perturb the data in terms of graph structure and temporal characteristics, but also employ a learning-based dynamic graph view generator for adaptive augmentation. Second, we introduce a Spatial-Temporal Synchronous Contrastive Module (STS-CM) to simultaneously capture the decent spatial-temporal dependencies and realize graph-level contrasting. To further discriminate node individuals in negative filtering, a Semantic Contextual Contrastive method is designed based on semantic features and spatial heterogeneity, achieving node-level contrastive learning along with negative filtering. Finally, we present a hard mutual-view contrastive training scheme and extend the classic contrastive loss to an integrated objective function, yielding better performance. Extensive experiments and evaluations demonstrate that building a predictor upon STS-CCL contrastive learning model gains superior performance than existing traffic forecasting benchmarks. The proposed STS-CCL is highly suitable for large datasets with only a few labeled data and other spatiotemporal tasks with data scarcity issue.Comment: This work was accepted by the 49th IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP 2024). We will present our work in Seoul, Kore

Optimal integration of mobile battery energy storage in distribution system with renewables

published_or_final_versio

Blockchain technologies empowering peer‐to‐peer trading in multi‐energy systems:From advanced technologies towards applications

Algorithmic

Identification and characterization of the Remorin gene family in Saccharum and the involvement of ScREM1.5e-1/-2 in SCMV infection on sugarcane

IntroductionRemorins (REMs) are plant-specific membrane-associated proteins that play important roles in plant–pathogen interactions and environmental adaptations. Group I REMs are extensively involved in virus infection. However, little is known about the REM gene family in sugarcane (Saccharum spp. hyrid), the most important sugar and energy crop around world.MethodsComparative genomics were employed to analyze the REM gene family in Saccharum spontaneum. Transcriptomics or RT-qPCR were used to analyze their expression files in different development stages or tissues under different treatments. Yeast two hybrid, bimolecular fluorescence complementation and co-immunoprecipitation assays were applied to investigate the protein interaction.ResultsIn this study, 65 REMs were identified from Saccharum spontaneum genome and classified into six groups based on phylogenetic tree analysis. These REMs contain multiple cis-elements associated with growth, development, hormone and stress response. Expression profiling revealed that among different SsREMs with variable expression levels in different developmental stages or different tissues. A pair of alleles, ScREM1.5e-1/-2, were isolated from the sugarcane cultivar ROC22. ScREM1.5e-1/-2 were highly expressed in leaves, with the former expressed at significantly higher levels than the latter. Their expression was induced by treatment with H2O2, ABA, ethylene, brassinosteroid, SA or MeJA, and varied upon Sugarcane mosaic virus (SCMV) infection. ScREM1.5e-1 was localized to the plasma membrane (PM), while ScREM1.5e-2 was localized to the cytoplasm or nucleus. ScREM1.5e-1/-2 can self-interact and interact with each other, and interact with VPgs from SCMV, Sorghum mosaic virus, or Sugarcane streak mosaic virus. The interactions with VPgs relocated ScREM1.5e-1 from the PM to the cytoplasm.DiscussionThese results reveal the origin, distribution and evolution of the REM gene family in sugarcane and may shed light on engineering sugarcane resistance against sugarcane mosaic pathogens

Droplet-like Fermi surfaces in the anti-ferromagnetic phase of EuFe2_2As2_2, an Fe-pnictide superconductor parent compound

Using angle resolved photoemission it is shown that the low lying electronic states of the iron pnictide parent compound EuFe$_2$As$_2$ are strongly modified in the magnetically ordered, low temperature, orthorhombic state compared to the tetragonal, paramagnetic case above the spin density wave transition temperature. Back-folded bands, reflected in the orthorhombic/ anti-ferromagnetic Brillouin zone boundary hybridize strongly with the non-folded states, leading to the opening of energy gaps. As a direct consequence, the large Fermi surfaces of the tetragonal phase fragment, the low temperature Fermi surface being comprised of small droplets, built up of electron and hole-like sections. These high resolution ARPES data are therefore in keeping with quantum oscillation and optical data from other undoped pnictide parent compounds.Comment: 4 figures, 6 page

Deep functional analysis of synII, a 770-kilobase synthetic yeast chromosome

INTRODUCTION Although much effort has been devoted to studying yeast in the past few decades, our understanding of this model organism is still limited. Rapidly developing DNA synthesis techniques have made a “build-to-understand” approach feasible to reengineer on the genome scale. Here, we report on the completion of a 770-kilobase synthetic yeast chromosome II (synII). SynII was characterized using extensive Trans-Omics tests. Despite considerable sequence alterations, synII is virtually indistinguishable from wild type. However, an up-regulation of translational machinery was observed and can be reversed by restoring the transfer RNA (tRNA) gene copy number. RATIONALE Following the “design-build-test-debug” working loop, synII was successfully designed and constructed in vivo. Extensive Trans-Omics tests were conducted, including phenomics, transcriptomics, proteomics, metabolomics, chromosome segregation, and replication analyses. By both complementation assays and SCRaMbLE (synthetic chromosome rearrangement and modification by loxP -mediated evolution), we targeted and debugged the origin of a growth defect at 37°C in glycerol medium. RESULTS To efficiently construct megabase-long chromosomes, we developed an I- Sce I–mediated strategy, which enables parallel integration of synthetic chromosome arms and reduced the overall integration time by 50% for synII. An I- Sce I site is introduced for generating a double-strand break to promote targeted homologous recombination during mitotic growth. Despite hundreds of modifications introduced, there are still regions sharing substantial sequence similarity that might lead to undesirable meiotic recombinations when intercrossing the two semisynthetic chromosome arm strains. Induction of the I- Sce I–mediated double-strand break is otherwise lethal and thus introduced a strong selective pressure for targeted homologous recombination. Since our strategy is designed to generate a markerless synII and leave the URA3 marker on the wild-type chromosome, we observed a tenfold increase in URA3 -deficient colonies upon I- Sce I induction, meaning that our strategy can greatly bias the crossover events toward the designated regions. By incorporating comprehensive phenotyping approaches at multiple levels, we demonstrated that synII was capable of powering the growth of yeast indistinguishably from wild-type cells (see the figure), showing highly consistent biological processes comparable to the native strain. Meanwhile, we also noticed modest but potentially significant up-regulation of the translational machinery. The main alteration underlying this change in expression is the deletion of 13 tRNA genes. A growth defect was observed in one very specific condition—high temperature (37°C) in medium with glycerol as a carbon source—where colony size was reduced significantly. We targeted and debugged this defect by two distinct approaches. The first approach involved phenotype screening of all intermediate strains followed by a complementation assay with wild-type sequences in the synthetic strain. By doing so, we identified a modification resulting from PCRTag recoding in TSC10 , which is involved in regulation of the yeast high-osmolarity glycerol (HOG) response pathway. After replacement with wild-type TSC10 , the defect was greatly mitigated. The other approach, debugging by SCRaMbLE, showed rearrangements in regions containing HOG regulation genes. Both approaches indicated that the defect is related to HOG response dysregulation. Thus, the phenotypic defect can be pinpointed and debugged through multiple alternative routes in the complex cellular interactome network. CONCLUSION We have demonstrated that synII segregates, replicates, and functions in a highly similar fashion compared with its wild-type counterpart. Furthermore, we believe that the iterative “design-build-test-debug” cycle methodology, established here, will facilitate progression of the Sc2.0 project in the face of the increasing synthetic genome complexity. SynII characterization. ( A ) Cell cycle comparison between synII and BY4741 revealed by the percentage of cells with separated CEN2-GFP dots, metaphase spindles, and anaphase spindles. ( B ) Replication profiling of synII (red) and BY4741 (black) expressed as relative copy number by deep sequencing. ( C ) RNA sequencing analysis revealed that the significant up-regulation of translational machinery in synII is induced by the deletion of tRNA genes in synII. </jats:sec