Deep- to ultradeep-strata carbonate reservoirs are a crucial strategic area for increasing oil and gas reserves and production in my country. These reservoirs are characterized by their great depth, strong heterogeneity, and complex pore structure. The high-temperature and high-pressure environment makes the seismic response mechanism unclear, posing a severe challenge to traditional rock physics models and seismic inversion methods. This paper systematically reviews the recent research progress in rock physics and seismic inversion methods for deep-strata carbonate reservoirs. In rock physics, the paper focuses on the achievements in high-temperature and high-pressure experiments, pore structure characterization, and theoretical model improvements. In seismic inversion, the paper reviews the current development status of pre-stack inversion, multi-information constraints, and artificial intelligence-assisted methods. Based on this, the paper points out the shortcomings of current research in terms of theoretical foundation and prediction accuracy, and proposes development trends and key research directions of deep-strata integration, refinement, and intelligence.

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The carbon emissions of concrete run through its entire lifecycle, and reducing the carbon footprint of concrete has become an important issue in the field of building materials. Although various research systems for low-carbon concrete have gradually improved, there is still a lack of systematic comparison of the economic and carbon reduction potential of different technological paths in practical engineering. This article divides the sources of carbon emissions into three stages: clinker production, aggregate mining and processing, and mixing and construction. Based on the core principles of optimizing the cementitious material system and coordinating mineral admixtures, a systematic review is conducted on the technical paths of high-dosage mineral compounding, alkali-activated cementitious materials, and solid waste synergistic utilization. The carbon emission reduction and engineering application conditions of each scheme are compared horizontally. The carbon reduction range of the high-dosage compound scheme is 20% to 45%, and the engineering acceptance is the highest. The carbon reduction potential of alkali-activated materials can reach about 70%, but it is limited by material shrinkage cracking and construction adaptability. The carbon reduction rate of the solid waste collaborative utilization plan is between 10% and 40%. The promotion of the three types of schemes is constrained by fluctuations in the quality of raw materials.

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In today's era, the marginal benefits of transistor scaling are continuously decreasing, and Chiplet heterogeneous integration has become the mainstream path for scaling AI chip computing power. Meanwhile, on-chip interconnect performance is increasingly becoming the key factor limiting system computing power and energy efficiency. This paper focuses on on-chip network technology for Chiplet-integrated AI chip architectures, providing a systematic review and analysis of its technical principles, research status, existing limitations, and development directions. The study first breaks down the on-chip network's dual-layer architecture of 'physical architecture layer - protocol mechanism layer,' clarifying the functional roles of each core hardware unit and protocol mechanism and the complete data transmission logic. Next, from the perspectives of topology, routing algorithms, switching mechanisms, and flow control mechanisms, it summarizes the evolution of on-chip network technology and the customized research results for AI computing features and Chiplet heterogeneous scenarios. It then identifies two core current issues—inter-chiplet interconnect performance bottlenecks and lack of cross-layer collaborative design, as well as insufficient dynamic load adaptation and lagging industry standards — and outlines the key paths for future technology optimization. This research can provide clear insights into the technological development path for researchers in the field and offer theoretical support and direction for the interconnect architecture design and industrial implementation of the next-generation highly integrated AI chips.

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The safety of construction slopes holds significant importance in engineering and architecture, with the lack of resilience against extreme weather conditions being particularly critical. This paper systematically examines the fundamental flaws in traditional design theories regarding the limitations of compression-shear stress paths and the assumption of constant soil parameters. It delves into the systemic vulnerabilities in resilience across the entire lifecycle caused by operational supervision gaps and post-event regulatory gaps in the current construction system. Additionally, it reveals the consequences of mechanistic isolation between structural support and ecological protection, as well as the oversimplified engineering approach resulting from outdated drainage system standards, through real-world disaster case studies. Based on this, this article proposes a theoretical revision direction for constructing a tension shear fluid-solid coupling unsaturated soil mechanics system, explores a differentiated zoning control mechanism based on quantitative risk analysis (QRA), and integrates digital Bayesian pre-evaluation methods with on-site observations. The research aims to provide rigorous theoretical support for the disaster-resistant design of high-risk building slope engineering, and promote the transformation of slope engineering from static defense to a dynamic resilience management paradigm throughout its lifecycle.

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