Research on Method of Health Assessment about the Destruction Equipment for High-risk Hazardous Chemical Waste

AbstractThe destroying tasks of high-risk hazardous chemical waste have a strict request to the health status of destruction equipment.The paper proposes the health status classification method based on time between failures for the destruction of equipment, set up health status assessment model based on Time-varying Bayesian Networks and the time slice, which can take advantage of history fault information and health status monitoring indicator information to health status assessment for the destruction equipment, and which provides a reliable and safe evaluation method

The upstream sequence of the phycocyanin \u3b2 subunit gene from Arthrospira platensis regulates expression of gfp gene in response to light intensity

In cyanobacteria, few details are known of the mechanisms through which the expression of the light-harvesting pigment c-phycocyanin is regulated. In the present study, a 419 bp upstream sequence of the phycocyanin \u3b2 subunit (cpcB) gene from Arthrospira platensis FACHB341 was fused with green fluorescent protein (gfp) gene, and a heterologous reporting system was built up to investigate the influence of light intensity on the expression of gfp gene, and the regulation function of different region of the upstream sequence of cpcB gene. Results showed that the upstream sequence of cpcB gene could drive the expression of gfp gene in Synechococcus sp. strain PCC7942, and the expression was influenced by light intensity, the lower the light intensity, the higher the gfp level. Deletion analysis revealed that a light-responsive element was located in the region -276 to-218, a promoter sequence was in the region -85 to -1, and two positive cis elements were in the -419 to -276 and the -218 to -130 regions, respectively

Routing Optimization of Electric Vehicles for Charging With Event-Driven Pricing Strategy

With the increasing market penetration of electric vehicles (EVs), the charging behavior and driving characteristics of EVs have an increasing impact on the operation of power grids and traffic networks. Existing research on EV routing planning and charging navigation strategies mainly focuses on vehicle-road-network interactions, but the vehicle-to-vehicle interaction has rarely been considered, particularly in studying simultaneous charging requests. To investigate the interaction of multiple vehicles in routing planning and charging, a routing optimization of EVs for charging with an event-driven pricing strategy is proposed. The urban area of a city is taken as a case for numerical simulation, which demonstrates that the proposed strategy can not only alleviate the long-time queuing for EV fast charging but also improve the utilization rate of charging infrastructures. Note to Practitioners - This article was inspired by the concerns of difficulties for electric vehicle (EV)'s fast charging and the imbalance of the utilization rate of charging facilities. Existing route optimization and charging navigation research are mainly applicable to static traffic networks, which cannot dynamically adjust driving routes and charging strategies with real-time traffic information. Besides, the mutual impact between vehicles is rarely considered in these works in routing planning. To resolve the shortcomings of existing models, a receding-horizon-based strategy that can be applied to dynamic traffic networks is proposed. In this article, various factors that the user is concerned about within the course of driving are converted into driving costs, through which each road section of traffic networks is assigned the corresponding values. Combined with the graph theory analysis method, the mathematical form of the dynamic traffic network is presented. Then, the article carefully plans and adjusts EV driving routes and charging strategies. Numerical results demonstrate that the proposed method can significantly increase the adoption of EV fast charging while alleviating unreasonable distributions of regional charging demand.</p

Towards Consistent Video Editing with Text-to-Image Diffusion Models

Existing works have advanced Text-to-Image (TTI) diffusion models for video editing in a one-shot learning manner. Despite their low requirements of data and computation, these methods might produce results of unsatisfied consistency with text prompt as well as temporal sequence, limiting their applications in the real world. In this paper, we propose to address the above issues with a novel EI$^2$ model towards \textbf{E}nhancing v\textbf{I}deo \textbf{E}diting cons\textbf{I}stency of TTI-based frameworks. Specifically, we analyze and find that the inconsistent problem is caused by newly added modules into TTI models for learning temporal information. These modules lead to covariate shift in the feature space, which harms the editing capability. Thus, we design EI$^2$ to tackle the above drawbacks with two classical modules: Shift-restricted Temporal Attention Module (STAM) and Fine-coarse Frame Attention Module (FFAM). First, through theoretical analysis, we demonstrate that covariate shift is highly related to Layer Normalization, thus STAM employs a \textit{Instance Centering} layer replacing it to preserve the distribution of temporal features. In addition, {STAM} employs an attention layer with normalized mapping to transform temporal features while constraining the variance shift. As the second part, we incorporate {STAM} with a novel {FFAM}, which efficiently leverages fine-coarse spatial information of overall frames to further enhance temporal consistency. Extensive experiments demonstrate the superiority of the proposed EI$^2$ model for text-driven video editing

Identification of phase relative genes in tetrasporophytes and female gametophytes of Gracilaria/Gracilariopsis lemaneiformis (Gracilariales, Rhodophyta)

Genes differentially expressed between tetrasporophytes and female gametophytes of Gracilaria/Gracilariopsis lemaneiformis were isolated by suppression subtractive hybridization (SSH) and screened by dot-blot macro-arrays. Different expression profiles of selected clones based on the results of dot-blot macro-arrays were verified using virtual Northern blots. Totally, 14 phase relative cDNAs had been isolated and sequence identified. Among them, seven cDNAs were respectively homologous to crucial metabolic enzymes, Rab GTPase, RP42 homolog, and two hypothetical proteins, while the rest did not have significant hits in the databases examined. The results of virtual Northern blots revealed that 11 cDNAs were differentially expressed between the two samples, including 7 genes up-regulated in tetrasporophytes, 1 expressed exclusively in tetrasporophytes and 3 up-regulated in female gametophytes. By densitometric analysis relative to GAPDH, 8 cDNAs increased 1.3-4.2 fold and 3 decreased about 0.4-0.7 fold in tetrasporophytes compared to female gametophytes. The present study provides the first insight into genes that may involve in phase differentiation in G. lemaneiformis