Taxonomy, Semantic Data Schema, and Schema Alignment for Open Data in Urban Building Energy Modeling

Urban Building Energy Modeling (UBEM) is a critical tool to provide quantitative analysis on building decarbonization, sustainability, building-to-grid integration, and renewable energy applications on city, regional, and national scales. Researchers usually use open data as inputs to build and calibrate UBEM. However, open data are from thousands of sources covering various perspectives of weather, building characteristics, etc. Besides, a lack of semantic features of open data further increases the engineering effort to process information to be directly used for UBEM as inputs. In this paper, we first reviewed open data types used for UBEM and developed a taxonomy to categorize open data. Based on that, we further developed a semantic data schema for each open data category to maintain data consistency and improve model automation for UBEM. In a case study, we use three popular open data to show how they can be automatically processed based on the proposed schematic data structure using large language models. The accurate results generated by large language models indicate the machine-readability and human-interpretability of the developed semantic data schema

Strigolactone regulation of shoot branching in chrysanthemum (Dendranthema grandiflorum).

Previous studies of highly branched mutants in pea (rms1-rms5), Arabidopsis thaliana (max1-max4), petunia (dad1-dad3), and rice (d3, d10, htd1/d17, d14, d27) identified strigolactones or their derivates (SLs), as shoot branching inhibitors. This recent discovery offers the possibility of using SLs to regulate branching commercially, for example, in chrysanthemum, an important cut flower crop. To investigate this option, SL physiology and molecular biology were studied in chrysanthemum (Dendranthema grandiflorum), focusing on the CCD8/MAX4/DAD1/RMS1/D10 gene. Our results suggest that, as has been proposed for Arabidopsis, the ability of SLs to inhibit bud activity depends on the presence of a competing auxin source. The chrysanthemum SL biosynthesis gene, CCD8 was cloned, and found to be regulated in a similar, but not identical way to known CCD8s. Expression analyses revealed that DgCCD8 is predominantly expressed in roots and stems, and is up-regulated by exogenous auxin. Exogenous SL can down-regulate DgCCD8 expression, but this effect can be overridden by apical auxin application. This study provides evidence that SLs are promising candidates to alter the shoot branching habit of chrysanthemum

Towards Privacy-Aware Causal Structure Learning in Federated Setting

Causal structure learning has been extensively studied and widely used in machine learning and various applications. To achieve an ideal performance, existing causal structure learning algorithms often need to centralize a large amount of data from multiple data sources. However, in the privacy-preserving setting, it is impossible to centralize data from all sources and put them together as a single dataset. To preserve data privacy, federated learning as a new learning paradigm has attracted much attention in machine learning in recent years. In this paper, we study a privacy-aware causal structure learning problem in the federated setting and propose a novel Federated PC (FedPC) algorithm with two new strategies for preserving data privacy without centralizing data. Specifically, we first propose a novel layer-wise aggregation strategy for a seamless adaptation of the PC algorithm into the federated learning paradigm for federated skeleton learning, then we design an effective strategy for learning consistent separation sets for federated edge orientation. The extensive experiments validate that FedPC is effective for causal structure learning in a federated learning setting.Comment: This paper has been accepted by the journal IEEE Transactions on Big Data, and it contains 21 pages, 9 figures and 15 table

Monte Carlo localization algorithm based on particle swarm optimization

In wireless sensor networks, Monte Carlo localization for mobile nodes has a large positioning error and slow convergence speed. To address the challenges of low sampling efficiency and particle impoverishment, a time sequence Monte Carlo localization algorithm based on particle swarm optimization (TSMCL-BPSO) is proposed in this paper. Firstly, the sampling region is constructed according to the overlap of the initial sampling region and the Monte Carlo sampling region. Then, particle swarm optimization (PSO) strategy is adopted to search the optimum position of the target node. The velocity of particle swarm is updated by adaptive step size and the particle impoverishment is improved by distributed estimation and particle replication, which avoids the local optimum caused by the premature convergence of particles. Experiment results indicate that the proposed algorithm improves the particle fitness, increases the particle searching efficiency, and meanwhile the lower positioning error can be obtained at the node\u27s maximum speed of 70 m/s

MAGEA1 inhibits the expression of BORIS via increased promoter methylation

Melanoma-associated antigen A1 (MAGEA1) and BORIS (also known as CTCFL) are members of the cancer testis antigen (CTA) family. Their functions and expression-regulation mechanisms are not fully understood. In this study, we reveal new functions and regulatory mechanisms of MAGEA1 and BORIS in breast cancer cells, which we investigated in parental and genetically manipulated breast cancer cells via gene overexpression or siRNA-mediated downregulation. We identified the interaction between MAGEA1 and CTCF, which is required for the binding of MAGEA1 to the BORIS promoter and is critical for the recruitment of DNMT3a. A protein complex containing MAGEA1, CTCF and DNMT3a was formed before or after conjunction with the BORIS promoter. The binding of this complex to the BORIS promoter accounts for the hypermethylation and repression of BORIS expression, which results in cell death in the breast cancer cell lines tested. Multiple approaches were employed, including co-immunoprecipitation, glutathione S-transferase pull-down assay, co-localization and cell death analyses using annexin V-FITC/propidium iodide double-staining and caspase 3 activation assays, chromatin immunoprecipitation and bisulfite sequencing PCR assays for methylation. Our results have implications for the development of strategies in CTA-based immune therapeutics

Sevoflurane Pre-conditioning Ameliorates Diabetic Myocardial Ischemia/Reperfusion Injury Via Differential Regulation of p38 and ERK.

Diabetes mellitus (DM) significantly increases myocardial ischemia/reperfusion (MI/R) injury. During DM, cardioprotection induced by conventional pre-conditioning (PreCon) is decreased due to impaired AMP-activated protein kinase (AMPK) signaling. The current study investigated whether PreCon with inhaled anesthetic sevoflurane (SF-PreCon) remains cardioprotective during DM, and identified the involved mechanisms. Normal diet (ND) and high-fat diet (HFD)-induced DM mice were randomized into control and SF-PreCon (3 cycles of 15-minute period exposures to 2% sevoflurane) groups before MI/R. SF-PreCon markedly reduced MI/R injury in DM mice, as evidenced by improved cardiac function (increased LVEF and ±Dp/dt), decreased infarct size, and decreased apoptosis. To determine the relevant role of AMPK, the effect of SF-PreCon was determined in cardiac-specific AMPKα2 dominant negative expressing mice (AMPK-DN). SF-PreCon decreased MI/R injury in AMPK-DN mice. To explore the molecular mechanisms responsible for SF-PreCon mediated cardioprotection in DM mice, cell survival molecules were screened. Interestingly, in ND mice, SF-PreCon significantly reduced MI/R-induced activation of p38, a pro-death MAPK, without altering ERK and JNK. In DM and AMPK-DN mice, the inhibitory effect of SF-PreCon upon p38 activation was significantly blunted. However, SF-PreCon significantly increased phosphorylation of ERK1/2, a pro-survival MAPK in DM and AMPK-DN mice. We demonstrate that SF-PreCon protects the heart via AMPK-dependent inhibition of pro-death MAPK in ND mice. However, SF-PreCon exerts cardioprotective action via AMPK-independent activation of a pro-survival MAPK member in DM mice. SF-PreCon may be beneficial compared to conventional PreCon in diabetes or clinical scenarios in which AMPK signaling is impaired

Adiponectin at Physiologically Relevant Concentrations Enhances the Vasorelaxative Effect of Acetylcholine via Cav-1/AdipoR-1 Signaling.

Clinical studies have identified hypoadiponectinemia as an independent hypertension risk factor. It is known that adiponectin (APN) can directly cause vasodilation, but the doses required exceed physiologic levels several fold. In the current study, we determine the effect of physiologically relevant APN concentrations upon vascular tone, and investigate the mechanism(s) responsible. Physiologic APN concentrations alone induced no significant vasorelaxation. Interestingly, pretreatment of wild type mouse aortae with physiologic APN levels significantly enhanced acetylcholine (ACh)-induced vasorelaxation (

Millennial-Scale Asian Monsoon Influenced Longjie Lake Evolution during Marine Isotope Stage 3, Upper Stream of Changjiang (Yangtze) River, China

Millennial-scale climate change in Asian monsoon region during MIS 3 has been studied using stalagmite, loess, and peat sediments. However, records from more materials are essential to further illustrate dynamics of these events. In the present study, a time-series of grain size covering 60–30 ka was reconstructed from lake sediments in the Yunnan Province, southwestern China. The time-series contains 14 obvious millennial-scale events during the period. On millennial-scale, the grain size record is generally consistent with mean stalagmite δ18O from Hulu Cave, grain size of Gulang loess sequence, Chinese Loess Plateau, and Greenland ice core δ18O. The results show that the millennial-scale variation was well compared with the Dansgaard-Oeschger (DO) events, indicating that those global events were well documented in lake sediments in the Asian monsoon region. Because the grain size can be used as a proxy for water discharge, we suggest that signal of the DO events might be transmitted to lake evolution by Asian monsoon

Identification of Unique α4 Chain Structure and Conserved Antiangiogenic Activity of α3NC1 Type IV Collagen in Zebrafish

BACKGROUND: Type IV collagen is an abundant component of basement membranes in all multicellular species and is essential for the extracellular scaffold supporting tissue architecture and function. Lower organisms typically have two type IV collagen genes, encoding α1 and α2 chains, in contrast with the six genes in humans, encoding α1-α6 chains. The α chains assemble into trimeric protomers, the building blocks of the type IV collagen network. The detailed evolutionary conservation of type IV collagen network remains to be studied. RESULTS: We report on the molecular evolution of type IV collagen genes. The zebrafish α4 non-collagenous (NC1) domain, in contrast with its human ortholog, contains an additional cysteine residue and lacks the M93 and K211 residues involved in sulfilimine bond formation between adjacent protomers. This may alter α4 chain interactions with other α chains, as supported by temporal and anatomic expression patterns of collagen IV chains during the zebrafish development. Despite the divergence between zebrafish and human α3 NC1 domain (endogenous angiogenesis inhibitor, Tumstatin), the zebrafish α3 NC1 domain exhibits conserved antiangiogenic activity in human endothelial cells. CONCLUSIONS: Our work supports type IV collagen is largely conserved between zebrafish and humans, with a possible difference involving the α4 chain

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020

It is crucial to estimate the theoretical carrying capacity of grasslands in Xinjiang to attain a harmonious balance between grassland and livestock, thereby fostering sustainable development in the livestock industry. However, there has been a lack of quantitative assessments that consider long-term, multi-scale grass-livestock balance and its impacts in the region. This study utilized remote sensing and empirical models to assess the theoretical livestock carrying capacity of grasslands. The multi-scale spatiotemporal variations of the theoretical carrying capacity in Xinjiang from 1982 to 2020 were analyzed using the Sen and Mann-Kendall tests, as well as the Hurst index. The study also examined the county-level grass-livestock balance and inter-annual trends. Additionally, the study employed the geographic detector method to explore the influencing factors. The results showed that: (1) The overall theoretical livestock carrying capacity showed an upward trend from 1982 to 2020; The spatial distribution gradually decreased from north to south and from east to west. In seasonal scale from large to small is: growing season > summer > spring > autumn > winter; at the monthly scale, the strongest livestock carrying capacity is in July. The different grassland types from largest to smallest are: meadow > alpine subalpine meadow > plain steppe > desert steppe > alpine subalpine steppe. In the future, the theoretical livestock carrying capacity of grassland will decrease. (2) From 1988 to 2020, the average grass-livestock balance index in Xinjiang was 2.61%, showing an overall increase. At the county level, the number of overloaded counties showed an overall increasing trend, rising from 46 in 1988 to 58 in 2020. (3) Both single and interaction factors of geographic detectors showed that annual precipitation, altitude and soil organic matter were the main drivers of spatiotemporal dynamics of grassland load in Xinjiang. The results of this study can provide scientific guidance and decision-making basis for achieving coordinated and sustainable development of grassland resources and animal husbandry in the region