Through the pseudo-static experiment, test research is made on 4 pieces of reinforced concrete hollow shear wall under low reversed cyclic loading, analysis is made on the damage characteristics and deformation performance of the shear walls. Research shows that: by setting up vertical seams, the damage form of components is changed from the sheared destruction to the curved-sheared destruction, By setting up vertical seams, the ductility and deformation performance of the shear wall can be improved, adopting the form of confine of a row of reinforced bar can greatly improve the ductility and deformation performance of the seam shear wall, and the bearing capacity can be guaranteed.
Reasoning is a fundamental capability of Large Language Models. While prior research predominantly focuses on enhancing narrow skills like math or code generation, improving performance on many other reasoning tasks remains challenging due to sparse and fragmented training data. To address this issue, we propose CodeI/O, a novel approach that systematically condenses diverse reasoning patterns inherently embedded in contextually-grounded codes, through transforming the original code into a code input-output prediction format. By training models to predict inputs/outputs given code and test cases entirely in natural language as Chain-of-Thought (CoT) rationales, we expose them to universal reasoning primitives -- like logic flow planning, state-space searching, decision tree traversal, and modular decomposition -- while decoupling structured reasoning from code-specific syntax and preserving procedural rigor. Experimental results demonstrate CodeI/O leads to consistent improvements across symbolic, scientific, logic, math & numerical, and commonsense reasoning tasks. By matching the existing ground-truth outputs or re-executing the code with predicted inputs, we can verify each prediction and further enhance the CoTs through multi-turn revision, resulting in CodeI/O++ and achieving higher performance. Our data and models are available at https://github.com/hkust-nlp/CodeIO.
The rapid development of large language models has revolutionized code intelligence in software development. However, the predominance of closed-source models has restricted extensive research and development. To address this, we introduce the DeepSeek-Coder series, a range of open-source code models with sizes from 1.3B to 33B, trained from scratch on 2 trillion tokens. These models are pre-trained on a high-quality project-level code corpus and employ a fill-in-the-blank task with a 16K window to enhance code generation and infilling. Our extensive evaluations demonstrate that DeepSeek-Coder not only achieves state-of-the-art performance among open-source code models across multiple benchmarks but also surpasses existing closed-source models like Codex and GPT-3.5. Furthermore, DeepSeek-Coder models are under a permissive license that allows for both research and unrestricted commercial use.
The determination of predominant period of site is very important to the earthquake-resistance designs of many kinds of buildings and structures on the site.The actual earthquake disaster shows that the role of structural sympathetic vibration is the main reason for the disaster when the natural vibration period of structure is close to the predominant period of site.There are many ways to analyse and calculate the predominant period, and the comparatively accurate period can be got by the spectral analysis of microtremor.It is complicated to achieve the calculation procedure of Fast Fourier Transform(FFT),but it is convenient to realize the transform by the spectral analysis tool of MATLAB.Thus,the predominant period is effectively and rapidly got to supply it for the engineering.
In this paper the complete stress-strain curves of recycled aggregate concrete with different recycled coarse aggregate replacement percentages are carried out,and the influences of varying recycled coarse aggregate contents on the complete stress-strain curve,peak stress,peak strain and elastic modulus are analyzed.The results show that the stress-strain curves of recycled aggregate concrete are similar to those of the conventional concrete,however,in terms of the recycled aggregate concrete,the peak strain is higher,and the elastic modulus is lower than those of the ordinary concrete.
In order to investigate the seismic energy consumption behavior of this structure, the low cyclic reversed lateral loading tests on six pieces of shale hollow brick masonry walls which used three bricklaying patterns have been carried out. In this paper, the failure proceeding of the specimens have been represented, and the failure modes, hysteretic characteristics, skeleton curves and energy dissipation were investigated. The result of investigation showed that the steel reinforcement not only can improve the bearing capacity of the masonry wall, but also can greatly enforce the seismic behavior and the deformation behavior of the wall. Putting steel reinforcement in the masonry wall is very essential in the real structure.
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