EVALUATION OF THE EFFECT OF EXTERNAL PRESTRESSED STEEL STRANDS ON CABLE-STAYED BRIDGES BASED ON FINITE ELEMENT ANALYSIS AND STATIC TEST

This article relies on the reinforcement project of the Mulinghe cable-stayed bridge to explore the changes in the mechanical properties of the reinforced concrete cable-stayed bridge before and after reinforcement. The bridge has large cable spacing, large internal force of a single cable, and the main beam is mainly Reinforced Concrete. Therefore, structural calculation, disease analysis, and damage state simulation are carried out. Afterwards, the bridge's commonly used reinforcement methods were compared, and suitable reinforcement schemes were selected. After the reinforcement, the field test was carried out on the cable-stayed bridge, the main beam deflection, the strain of the main beam and the main tower, and the increase in the cable force of the cable- stayed were analyzed. The results show that external prestressed reinforcement is the best way, which can significantly reduce the vertical displacement of the main beam and the horizontal displacement of the main tower, and also improve the stress on the upper and lower edges of the main beam. After the external prestressed reinforcement, the ratio of the observed value to the observed value in the filed load test of the cable-stayed bridge's decreased significantly. It is up to 31% increase in bending capacity of main beams and up to 24% increase in stiffness. This article is instructive for the reinforcement of the early-built sparse-cable reinforced concrete cable-stayed bridge, while also expanding the scope of implementation of external prestressed reinforcement technology

Comparative transcriptomics uncovers alternative splicing changes and signatures of selection from maize improvement

Background: Alternative splicing (AS) is an important regulatory mechanism that greatly contributes to eukaryotic transcriptome diversity. A substantial amount of evidence has demonstrated that AS complexity is relevant to eukaryotic evolution, development, adaptation, and complexity. In this study, six teosinte and ten maize transcriptomes were sequenced to analyze AS changes and signatures of selection in maize domestication and improvement. Results In maize and teosinte, 13,593 highly conserved genes, including 12,030 multiexonic genes, were detected. By identifying AS isoforms from mutliexonic genes, we found that AS types were not significantly different between maize and teosinte. In addition, the two main AS types (intron retention and alternative acceptor) contributed to more than 60% of the AS events in the two species, but the average unique AS events per each alternatively spliced gene in maize (4.12) was higher than that in teosinte (2.26). Moreover, 94 genes generating 98 retained introns with transposable element (TE) sequences were detected in maize, which is far more than 9 retained introns with TEs detected in teosinte. This indicates that TE insertion might be an important mechanism for intron retention in maize. Additionally, the AS levels of 3864 genes were significantly different between maize and teosinte. Of these, 151 AS level-altered genes that are involved in transcriptional regulation and in stress responses are located in regions that have been targets of selection during maize improvement. These genes were inferred to be putatively improved genes. Conclusions We suggest that both maize and teosinte share similar AS mechanisms, but more genes have increased AS complexity during domestication from teosinte to maize. Importantly, a subset of AS level-increased genes that encode transcription factors and stress-responsive proteins may have been selected during maize improvement

A new post-frac evaluation method for shale gas wells based on fracturing curves

AbstractPost-fracturing evaluation by using limited data is of great significance to continuous improvement of the fracturing programs. In this paper, a fracturing curve was divided into two stages (i.e., prepad fluid injection and main fracturing) so as to further understand the parameters of reservoirs and artificial fractures. The brittleness and plasticity of formations were qualitatively identified by use of the statistics of formation fracture frequency, and average pressure dropping range and rate during the prepad fluid injection. The composite brittleness index was quantitatively calculated by using the energy zones in the process of fracturing. It is shown from the large-scale true triaxial physical simulation results that the complexity of fractures is reflected by the pressure fluctuation frequency and amplitude in the main fracturing curve, and combined with the brittleness and plasticity of formations, the fracture morphology far away from the well can be diagnosed. Well P, a shale gas well in SE Chongqing, was taken as an example for post-fracturing evaluation. It is shown that the shale beds are of stronger heterogeneity along the extension directions of horizontal wells, and with GR 260 API as the dividing line between brittleness and plasticity in this area, complex fracture systems tend to form in brittleness-prone formations. In Well P, half of the fractures are single fractures, so it is necessary to carry out fine subsection and turnaround fracturing so as to improve development effects. This paper provides a theoretical basis for improving the fracturing well design and increasing the effective stimulated volume in this area

SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval

Legal case retrieval, which aims to find relevant cases for a query case, plays a core role in the intelligent legal system. Despite the success that pre-training has achieved in ad-hoc retrieval tasks, effective pre-training strategies for legal case retrieval remain to be explored. Compared with general documents, legal case documents are typically long text sequences with intrinsic logical structures. However, most existing language models have difficulty understanding the long-distance dependencies between different structures. Moreover, in contrast to the general retrieval, the relevance in the legal domain is sensitive to key legal elements. Even subtle differences in key legal elements can significantly affect the judgement of relevance. However, existing pre-trained language models designed for general purposes have not been equipped to handle legal elements. To address these issues, in this paper, we propose SAILER, a new Structure-Aware pre-traIned language model for LEgal case Retrieval. It is highlighted in the following three aspects: (1) SAILER fully utilizes the structural information contained in legal case documents and pays more attention to key legal elements, similar to how legal experts browse legal case documents. (2) SAILER employs an asymmetric encoder-decoder architecture to integrate several different pre-training objectives. In this way, rich semantic information across tasks is encoded into dense vectors. (3) SAILER has powerful discriminative ability, even without any legal annotation data. It can distinguish legal cases with different charges accurately. Extensive experiments over publicly available legal benchmarks demonstrate that our approach can significantly outperform previous state-of-the-art methods in legal case retrieval.Comment: 10 pages, accepted by SIGIR 202

Cu2O@PNIPAM core–shell microgels as novel inkjet materials for the preparation of CuO hollow porous nanocubes gas sensing layers

There has been long-standing interest in developing metal oxide-based sensors with high sensitivity, selectivity, fast response and low material consumption. Here we report for the first time the utilization of Cu2O@PNIPAM core–shell microgels with a nanocube-shaped core structure for construction of novel CuO gas sensing layers. The hybrid microgels show significant improvement in colloidal stability as compared to native Cu2O nanocubes. Consequently, a homogeneous thin film of Cu2O@PNIPAM nanoparticles can be engineered in a quite low solid content (1.5 wt%) by inkjet printing of the dispersion at an optimized viscosity and surface tension. Most importantly, thermal treatment of the Cu2O@PNIPAM microgels forms porous CuO nanocubes, which show much faster response to relevant trace NO2 gases than sensors produced from bare Cu2O nanocubes. This outcome is due to the fact that the PNIPAM shell can successfully hinder the aggregation of CuO nanoparticles during pyrolysis, which enables full utilization of the sensor layers and better access of the gas to active sites. These results point out great potential of such an innovative system as gas sensors with low cost, fast response and high sensitivitH. J. gratefully acknowledges financial support of the CSC scholarship. S. P. acknowledges funding from the Community of Madrid under grant number 2016-T1/AMB-1695

An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation

Despite making significant progress in multi-modal tasks, current Multi-modal Large Language Models (MLLMs) encounter the significant challenge of hallucination, which may lead to harmful consequences. Therefore, evaluating MLLMs' hallucinations is becoming increasingly important in model improvement and practical application deployment. Previous works are limited in high evaluation costs (e.g., relying on humans or advanced LLMs) and insufficient evaluation dimensions (e.g., types of hallucination and task). In this paper, we propose an LLM-free multi-dimensional benchmark AMBER, which can be used to evaluate both generative task and discriminative task including object existence, object attribute and object relation hallucination. Based on AMBER, we design a low-cost and efficient evaluation pipeline. Additionally, we conduct a comprehensive evaluation and detailed analysis of mainstream MLLMs including GPT-4V(ision), and also give guideline suggestions for mitigating hallucinations. The data and code of AMBER are available at https://github.com/junyangwang0410/AMBER.Comment: 11 pages, 4 figure

BARNet:Boundary-Aware Refined Network for Automatic Building Extraction in Very High-Resolution Urban Aerial Images

The convolutional neural networks (CNNs), such as U-Net, have shown competitive performance in automatic extraction of buildings from very high-resolution (VHR) remotely sensed imagery. However, due to the unstable multi-scale context aggregation, the insufficient combination of multi-level features, and the lack of consideration about semantic boundary, most existing CNNs produce incomplete segmentation for large-scale buildings and result in predictions with huge uncertainty at building boundaries. This paper presents a novel network embedded a special boundary-aware loss, called Boundary-aware Refined Network (BARNet), to address the gap above. The unique property of BARNet is the gated-attention refined fusion unit (GARFU), the denser atrous spatial pyramid pooling (DASPP) module, and the boundary-aware (BA) loss. The performance of BARNet is tested on two popular benchmark datasets that include various urban scenes and diverse patterns of buildings. Experimental results demonstrate that the proposed method outperforms several state-of-the-art (SOTA) benchmark approaches in both visual interpretation and quantitative evaluations

2′-Methyl-3,5-diphenyl­spiro­[4,6-dioxa-2-aza­bicyclo­[3.2.0]hept-2-ene-7,4′-iso­quinoline]-1′,3′(2′H,4′H)-dione

In the title compound, C25H18N2O4, the tetra­hydro­pyridine ring adopts a distorted envelope conformation with the spiro C atom at the flap position [deviation = 0.470 (2) Å]. The dihydro–oxazole ring is planar (r.m.s. deviation = 0.013 Å) and it makes dihedral angles of 73.43 (8) and 4.24 (8)° with the two attached phenyl rings. The dihedral angle between oxetane and oxazole planes is 67.44 (9)°. In the crystal structure, C—H⋯O hydrogen bonds link neighbouring mol­ecules into zigzag chains along the b axis and these chains are linked via C—H⋯π inter­actions

The structural and optical properties of GaSb/InGaAs type-II quantum dots grown on InP (100) substrate

We have investigated the structural and optical properties of type-II GaSb/InGaAs quantum dots [QDs] grown on InP (100) substrate by molecular beam epitaxy. Rectangular-shaped GaSb QDs were well developed and no nanodash-like structures which could be easily found in the InAs/InP QD system were formed. Low-temperature photoluminescence spectra show there are two peaks centered at 0.75eV and 0.76ev. The low-energy peak blueshifted with increasing excitation power is identified as the indirect transition from the InGaAs conduction band to the GaSb hole level (type-II), and the high-energy peak is identified as the direct transition (type-I) of GaSb QDs. This material system shows a promising application on quantum-dot infrared detectors and quantum-dot field-effect transistor