Modal parameter identification and finite element model updating of a long-span aqueduct structure based on ambient excitation

In this paper, PSV-500 laser vibration detector and 941B vibration pick-up are used to measure the ambient vibration of an actual aqueduct in China, and the peak picking method is used to identify the modal parameters of the aqueduct. The finite element model of the aqueduct is established, and a model updating method based on multi-objective optimization algorithm is proposed. Based on the sensitivity analysis, the parameters to be updated are selected. The model is updated by the fast non dominated sorting genetic algorithm, and the Pareto optimal solution set of the multi-objective optimization problem is obtained. The comparison between the measured and calculated results shows that the results of static displacement and modal parameters are in good agreement with the measured values. The result of the research shows that the static and dynamic finite element model updating method based on multi-objective optimization can achieve satisfactory results for long-span aqueduct structure, and the updated finite element model can accurately and comprehensively simulate the actual structure

Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases

Large Language Models (LLMs) have demonstrated remarkable performance in code completion. However, due to the lack of domain-specific knowledge, they may not be optimal in completing code that requires intensive domain knowledge for example completing the library names. Although there are several works that have confirmed the effectiveness of fine-tuning techniques to adapt language models for code completion in specific domains. They are limited by the need for constant fine-tuning of the model when the project is in constant iteration. To address this limitation, in this paper, we propose $k$NM-LM, a retrieval-augmented language model (R-LM), that integrates domain knowledge into language models without fine-tuning. Different from previous techniques, our approach is able to automatically adapt to different language models and domains. Specifically, it utilizes the in-domain code to build the retrieval-based database decoupled from LM, and then combines it with LM through Bayesian inference to complete the code. The extensive experiments on the completion of intra-project and intra-scenario have confirmed that $k$NM-LM brings about appreciable enhancements when compared to CodeGPT and UnixCoder. A deep analysis of our tool including the responding speed, storage usage, specific type code completion, and API invocation completion has confirmed that $k$NM-LM provides satisfactory performance, which renders it highly appropriate for domain adaptive code completion. Furthermore, our approach operates without the requirement for direct access to the language model's parameters. As a result, it can seamlessly integrate with black-box code completion models, making it easy to integrate our approach as a plugin to further enhance the performance of these models.Comment: Accepted by ASE202

End-to-End Insulator String Defect Detection in a Complex Background Based on a Deep Learning Model

Normal power line insulators ensure the safe transmission of electricity. The defects of the insulator reduce the insulation, which may lead to the failure of power transmission systems. As unmanned aerial vehicles (UAVs) have developed rapidly, it is possible for workers to take and upload aerial images of insulators. Proposing a technology to detect insulator defects with high accuracy in a short time can be of great value. The existing methods suffer from complex backgrounds so that they have to locate and extract the insulators at first. Some of them make detection relative to some specific conditions such as angle, brightness, and object scale. This study aims to make end-to-end detections using aerial images of insulators, giving the locations of insulators and defects at the same time while overcoming the disadvantages mentioned above. A DEtection TRansformer (DETR) having an encoder–decoder architecture adopts convolutional neural network (CNN) as the backbone network, applies a self-attention mechanism for computing, and utilizes object queries instead of a hand-crafted process to give the direct predictions. We modified this for insulator detection in complex aerial images. Based on the dataset we constructed, our model can get 97.97 in mean average precision when setting the threshold of intersection over union at 0.5, which is better than Cascade R-CNN and YOLOv5. The inference speed of our model can reach 25 frames per second, which is qualified for actual use. Experimental results demonstrate that our model meets the robustness and accuracy requirements for insulator defect detection

Evaluation of Natural Gas Hydrate Fault System: A Case from a Sag in Deep-Water Slope Area of the Northern South China Sea

AbstractThe fault system is one of the structural carrier systems of gas hydrate accumulation, which plays a vital role in controlling the distribution of natural gas hydrate (NGH) accumulation. The previous studies mainly focus on summarizing the vertical migration mode of high flux fluid along the fault with obvious geophysical response characteristics on the seismic profile, such as “fault with gas chimney,” “fault with mud diapir,” and “fault with submarine collapse”, but lack of evaluation methods for the fault carrier system. We use the X sag in the deep-water continental margin slope area of the northern South China Sea as an example to study the fault systems closely related to NGH. This paper puts to use attribute technologies, such as coherence, curvature, and fusion, to analyze the characteristics and combination of the fault systems. We discussed migration patterns and evaluation methods of dominant fault carrier systems. This research proves that the strike-slip fault system in the platform area can directly connect the gas source bed with high-quality hydrocarbon generation to the gas hydrate stability zone (GHSZ). The activity of this fault system is more conducive to the accumulation of hydrocarbon in the GHSZ. This area has a good site for pore-filling gas hydrate prospecting and a preferential favorable fault carrier system. The composite fault system, consisting of a normal dip-slip fault system and a polygonal fault system, in the slope area can jointly communicate the biogenic gas-rich reservoir. Its activity and well-migration performance are the main reasons for the submarine gas leakage and collapse. It is a secondary favorable fault carrier system in the study area. There may be massive and vein natural gas hydrate formation in fractures in the leakage passage, and pore-filled gas hydrate may exist in the submarine nonleakage area. In this work, a three-factor evaluation method of the fault carrier system is proposed for the first time. This method is of great significance for the evaluation and exploration of NGH reservoirs in the continental margin slope area of the northern South China Sea

The Efficacy and Safety of the Combination of Total Glucosides of Peony and Leflunomide for the Treatment of Rheumatoid Arthritis: A Systemic Review and Meta-Analysis

Objective. To evaluate the efficacy and safety of the total glucosides of peony (TGP) and leflunomide (LEF) for the treatment of rheumatoid arthritis (RA). Methods. Randomized controlled trials (RCTs) on the efficacy and safety of the combination of TGP and LEF versus LEF alone for the treatment of RA were retrieved by searching PubMed, EMBASE, Cochrane Library, the China National Knowledge Infrastructure database, and Wanfang database. Results. Eight RCTs including 643 RA patients were included in the present meta-analysis. The quality of included studies was poor. The levels of ESR ( < 0.0001), CRP ( < 0.0001), and RF ( < 0.0001) in RA patients who received the combination of TGP and LEF were significantly lower than RA patients who received LEF therapy alone. The pooled results suggest that the combination of TGP and LEF caused less abnormal liver function than LEF alone ( = 0.02). No significant difference in the gastrointestinal discomfort was identified between the combination of TGP and LEF and LEF alone groups ( = 0.18). Conclusion. The combination of TGP and LEF in treatment of RA presented the characteristics of notably decreasing the levels of laboratory indexes and higher safety in terms of liver function. However, this conclusion should be further investigated based on a larger sample size

Development of a Mixed Halide-chalcogenide Bismuth-based Perovskite MABiI2S with Small Bandgap and Wide Absorption Range

During the last years, lead perovskites have achieved high power conversion efficiency of 23%. However, their long-term stability and toxicity are still crucial issues that required attention. In this study, we are the first to report on the synthesis and characterizations of a new lead-free mixed halide-chalcogenide perovskite MABiI2S (MBIS), and have determined its physical and optical properties by various testing methods. The MBIS has a low bandgap of 1.52 eV, with an extended absorption onset up to over 1000 nm. Solar cells fabricated with the MBIS were inspected and device improvements were applied

The Change of Teleost Skin Commensal Microbiota Is Associated With Skin Mucosal Transcriptomic Responses During Parasitic Infection by Ichthyophthirius multifillis

Teleost skin serves as the first line of defense against invading pathogens, and contain a skin-associated lymphoid tissue (SALT) that elicit gut-like immune responses against antigen stimulation. Moreover, exposed to the water environment and the pathogens therein, teleost skin is also known to be colonized by diverse microbial communities. However, little is known about the interactions between microbiota and the teleost skin mucosal immune system, especially dynamic changes about the interactions under pathogen infection. We hypothesized that dramatic changes of microbial communities and strong mucosal immune response would be present in the skin of aquatic vertebrate under parasite infection. To confirm this hypothesis, we construct an infected model with rainbow trout (Oncorhynchus mykiss), which was experimentally challenged by Ichthyophthirius multifiliis (Ich). H & E staining of trout skin indicates the successful invasion of Ich and shows the morphological changes caused by Ich infection. Critically, increased mRNA expression levels of immune-related genes were detected in trout skin from experimental groups using qRT-PCR, which were further studied by RNA-Seq analysis. Here, through transcriptomics, we detected that complement factors, pro-inflammatory cytokines, and antimicrobial genes were strikingly induced in the skin of infected fish. Moreover, high alpha diversity values of microbiota in trout skin from the experimental groups were discovered. Interestingly, we found that Ich infection led to a decreased abundance of skin commensals and increased colonization of opportunistic bacteria through 16S rRNA pyrosequencing, which were mainly characterized by lose of Proteobacteria and increased intensity of Flavobacteriaceae. To our knowledge, our results suggest for the first time that parasitic infection could inhibit symbionts and offer opportunities for other pathogens' secondary infection in teleost skin