An Object-Oriented Approach for Temporal Data

There is a growing need for easier access to temporal data. Recent developments of object-oriented data models represent the most promising approach to modeling complex aspects of the real world. Here, we present an object-oriented data model for supporting the storage and access of temporal information. The model consists of two parts. In the first part, we present the definition of a class for time object. The class is general enough so that it can be applied for various applications. Another part of the data model integrates time objects with entity objects and their attributes by following the pervasive three-dimensional metaphor of time. Particularly, the model incorporates with object-oriented technique all the three primary dimensions, which are time, entity, and attribute, of the metaphor

Investigation on selection crystal behavior of a Ni3Al-based single crystal superalloy IC6SX

AbstractThe grain selection occurring during the solidification of a Ni3Al-base single crystal superalloy IC6SX prepared by spiral grain selection method was studied systematically. Results showed that the equiaxed grains were transformed into columnar grains within starter block and most of columnar grains then will be eliminated. The crystal were formed after the remained columnar grains were eliminated through preferred growth and coupling of spiral structure in Spiral grain selection. The results can explain the competitive growth mechanism of the spiral grain selection and can be used to optimize process design to lay an important foundation for improving preparation processes of single crystal superalloy

Geochemical characteristics and implications of shale gas from the Longmaxi Formation, Sichuan Basin, China

AbstractGas geochemical analysis was conducted on the shale gas from the Longmaxi Formation in the Weiyuan-Changning areas, Sichuan Basin, China. Chemical composition was measured using an integrated method of gas chromatography combined with mass spectrometry. The results show that the Longmaxi shale gas, after hydraulic fracturing, is primarily dominated by methane (94.0%–98.6%) with low humidity (0.3%–0.6%) and minor non-hydrocarbon gasses which are primarily comprised of CO2, N2, as well as trace He. δ13CCO2 = −2.5‰−6.0‰3He/4He = 0.01–0.03Ra.The shale gas in the Weiyuan and Changning areas display carbon isotopes reversal pattern with a carbon number (δ13C1 > δ13C2) and distinct carbon isotopic composition. The shale gas from the Weiyuan pilot has heavier carbon isotopic compositions for methane (δ13C1: from −34.5‰ to −36.8‰), ethane (δ13C2: −37.6‰ to −41.9‰), and CO2 (δ13CCO2: −4.5‰ to −6.0‰) than those in the Changning pilot (δ13C1: −27.2‰ to −27.3‰, δ13C2: −33.7‰ to −34.1‰, δ13CCO2: −2.5‰ to −4.6‰). The Longmaxi shale was thermally high and the organic matter was in over mature stage with good sealing conditions. The shale gas, after hydraulic fracturing, could possibly originate from the thermal decomposition of kerogen and the secondary cracking of liquid hydrocarbons which caused the reversal pattern of carbon isotopes. Some CO2 could be derived from the decomposition of carbonate. The difference in carbon isotopes between the Weiyuan and Changning areas could be derived from the different mixing proportion of gas from the secondary cracking of liquid hydrocarbons caused by specific geological and geochemical conditions

Molecular Mechanism Underlying Persistent Induction of LCN2 by Lipopolysaccharide in Kidney Fibroblasts

The neutrophil gelatinase-associated lipocalin 2 (LCN2) is a critical inflammatory mediator persistently induced during endotoxemia, contributing to tubular damage and kidney failure. The intracellular process responsible for persistent induction of LCN2 by bacterial endotoxin Lipopolysaccharide (LPS) is not well understood. Using primary kidney fibroblasts, we observed that LPS-induced LCN2 expression requires a coupled circuit involving an early transient phase of AP-1 path and a late persistent phase of C/EBPδ path, both of which are dependent upon the interleukin 1 receptor associated kinase 1 (IRAK-1). Using immunoprecipitation analysis we observed transient binding of AP-1 to the promoters of both TNFα and C/ebpδ. On the other hand, we only observed persistent binding of C/EBPδ to its own promoter but not on TNFα. Blockage of new protein synthesis using cyclohexamide significantly reduced the expression of C/EBPδ as well as LCN2. By chromatin immunoprecipitation analyses, we demonstrated that LPS recruited C/EBPδ to the Lcn2 promoter in WT, but not IRAK-1 deficient fibroblasts. A differential equation-based computational model captured the dynamic circuit leading to the persistent induction of LCN2. In vivo, we observed elevated levels of LCN2 in kidneys harvested from LPS-injected WT mice as compared to IRAK-1 deficient mice. Taken together, this study has identified an integrated intracellular network involved in the persistent induction of LCN2 by LPS

A Mathematical Model for the Reciprocal Differentiation of T Helper 17 Cells and Induced Regulatory T Cells

The reciprocal differentiation of T helper 17 (TH17) cells and induced regulatory T (iTreg) cells plays a critical role in both the pathogenesis and resolution of diverse human inflammatory diseases. Although initial studies suggested a stable commitment to either the TH17 or the iTreg lineage, recent results reveal remarkable plasticity and heterogeneity, reflected in the capacity of differentiated effectors cells to be reprogrammed among TH17 and iTreg lineages and the intriguing phenomenon that a group of naïve precursor CD4+ T cells can be programmed into phenotypically diverse populations by the same differentiation signal, transforming growth factor beta. To reconcile these observations, we have built a mathematical model of TH17/iTreg differentiation that exhibits four different stable steady states, governed by pitchfork bifurcations with certain degrees of broken symmetry. According to the model, a group of precursor cells with some small cell-to-cell variability can differentiate into phenotypically distinct subsets of cells, which exhibit distinct levels of the master transcription-factor regulators for the two T cell lineages. A dynamical control system with these properties is flexible enough to be steered down alternative pathways by polarizing signals, such as interleukin-6 and retinoic acid and it may be used by the immune system to generate functionally distinct effector cells in desired fractions in response to a range of differentiation signals. Additionally, the model suggests a quantitative explanation for the phenotype with high expression levels of both master regulators. This phenotype corresponds to a re-stabilized co-expressing state, appearing at a late stage of differentiation, rather than a bipotent precursor state observed under some other circumstances. Our simulations reconcile most published experimental observations and predict novel differentiation states as well as transitions among different phenotypes that have not yet been observed experimentally

CLIP Brings Better Features to Visual Aesthetics Learners

The success of pre-training approaches on a variety of downstream tasks has revitalized the field of computer vision. Image aesthetics assessment (IAA) is one of the ideal application scenarios for such methods due to subjective and expensive labeling procedure. In this work, an unified and flexible two-phase \textbf{C}LIP-based \textbf{S}emi-supervised \textbf{K}nowledge \textbf{D}istillation paradigm is proposed, namely \textbf{\textit{CSKD}}. Specifically, we first integrate and leverage a multi-source unlabeled dataset to align rich features between a given visual encoder and an off-the-shelf CLIP image encoder via feature alignment loss. Notably, the given visual encoder is not limited by size or structure and, once well-trained, it can seamlessly serve as a better visual aesthetic learner for both student and teacher. In the second phase, the unlabeled data is also utilized in semi-supervised IAA learning to further boost student model performance when applied in latency-sensitive production scenarios. By analyzing the attention distance and entropy before and after feature alignment, we notice an alleviation of feature collapse issue, which in turn showcase the necessity of feature alignment instead of training directly based on CLIP image encoder. Extensive experiments indicate the superiority of CSKD, which achieves state-of-the-art performance on multiple widely used IAA benchmarks

Emerging CO2 utilization technologies for construction materials: a review

The construction industry is a major contributor of CO2 emissions. Carbonation, involving the reaction of CO2 with alkaline reactants, immobilizes CO2 into thermodynamically stable carbonates used in construction materials such as concrete and aggregates. The utilization of CO2 in construction materials is considered as one of the most promising routes for carbon sequestration, with a $400 billion market opportunity and a potential to reduce annual CO2 emissions by up to 3 Gt by 2030. This paper reviews the current status of the utilization of CO2 in construction materials from the perspective of scientific research and commercial applications. The explanation of the fundamental carbonation reaction mechanisms was extended to cover different binder systems involving Portland cement, non-hydraulic calcium silicate, industrial solid wastes and magnesium-based materials. Factors affecting the kinetics of the carbonation reaction and properties of the final products were reviewed. Furthermore, the current state of research and commercial initiatives involving the utilization of CO2 in the production of various building components were presented. Finally, key issues regarding the challenges faced in the scaling up of CO2 utilization technologies from the perspective of academia, industry and relevant regulatory bodies were highlighted. Recommendations to address the current utilization dilemma and promote large-scale application of CO2 in the production and development of construction materials were provided