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Climate change is causing permafrost in the Qinghai–Tibet Plateau to degrade, triggering thermokarst hazards and impacting the environment. Despite their ecological importance, the distribution and risks of thermokarst lakes are not well understood due to complex influencing factors. In this study, we introduced a new interpretable ensemble learning method designed to improve the global and local interpretation of susceptibility assessments for thermokarst lakes. Our primary aim was to offer scientific support for precisely evaluating areas prone to thermokarst lake formation. In the thermokarst lake susceptibility assessment, we identified ten conditioning factors related to the formation and distribution of thermokarst lakes. In this highly accurate stacking model, the primary learning units were the random forest (RF), extremely randomized trees (EXTs), extreme gradient boosting (XGBoost), and categorical boosting (CatBoost) algorithms. Meanwhile, gradient boosted decision trees (GBDTs) were employed as the secondary learning unit. Based on the stacking model, we assessed thermokarst lake susceptibility and validated accuracy through six evaluation indices. We examined the interpretability of the stacking model using three interpretation methods: accumulated local effects (ALE), local interpretable model-agnostic explanations (LIME), and Shapley additive explanations (SHAP). The results showed that the ensemble learning stacking model demonstrated superior performance and the highest prediction accuracy. Approximately 91.20% of the total thermokarst hazard points fell within the high and very high susceptible areas, encompassing 20.08% of the permafrost expanse in the QTP. The conclusive findings revealed that slope, elevation, the topographic wetness index (TWI), and precipitation were the primary factors influencing the assessment of thermokarst lake susceptibility. This comprehensive analysis extends to the broader impacts of thermokarst hazards, with the identified high and very high susceptibility zones affecting significant stretches of railway and highway infrastructure, substantial soil organic carbon reserves, and vast alpine grasslands. This interpretable ensemble learning model, which exhibits high accuracy, offers substantial practical significance for project route selection, construction, and operation in the QTP. [ABSTRACT FROM AUTHOR]

The Rubik's Cube mechanism (RCM) is a kind of reconfigurable mechanism with multiple characteristics such as multiple configurations, variable topology, strong coupling, and reconfigurability. Crossover research on the RCM with mathematics, chemistry, cryptography, and other disciplines has led to important breakthroughs and progress. It is obvious that the invention and creation of a new RCM can provide important ideological inspiration and theoretical guidance for the accelerated iterative updating of Rubik's Cube products and the expansion of their applications. This paper investigates the type synthesis method for a regular hexagonal prism (RHP) RCM (RHPRCM). Through analysis of the reconfigurable movement process of the RCM, two mechanism factors are abstracted, a type synthesis process for the RHPRCM is proposed, a symmetry layout method for the RCM's revolute axis based on the RHP space polyhedron is proposed, and an analysis method for the intersection of the revolute pair contact surfaces (RPCSs) based on the adjacency matrix is proposed. Taking a revolute axis passing through the center of an RHP and having only one RPCS for each revolute axis as an example, an RHPRCM with different topological structures is synthesized. The relevant research in this paper can provide methodological guidance for the synthesis of other spatial RCMs. [ABSTRACT FROM AUTHOR]

Engineering efficient catalyst interfaces offers a constructive way to boost activity and stability in the field of water electrolysis. Here, unique core–shell FeCoS@CoMoP heterostructure nanoparticles are rationally fabricated on a porous Ni foam through hydrothermal and electrodeposition methods. The as-prepared electrocatalyst exhibits efficient pH-universal hydrogen evolution reaction (HER) activity along with a satisfactory alkaline oxygen evolution reaction (OER) performance, extremely small overpotentials, and Tafel values, achieving prominent durability and stability. A series of structural characterizations help identify the reactive centers during the catalytic procedure and the tight interfacial interaction between the shell and core materials. Density functional theory (DFT) calculations reveal that the surface electrodeposition of CoMoP not only tunes the d-band center but also obviously decreases the Gibbs free energies in the HER/OER processes. It can be expected that the three-dimensional self-supported catalytic system will hold strong promise for effective water splitting, energy storage, and energy transformation devices. [ABSTRACT FROM AUTHOR]

With the significant growth in modern computing systems, dynamic random access memory (DRAM) has become a power/performance/energy bottleneck in data-intensive applications. Both the power management mechanism and downscaling method face decreasing performance or difficulties in the smaller footprint of the DRAM capacitor. Since optimizing the circuit of sense amplifier (SA) is an efficient method to reduce energy consumption, we propose two single bitline load sense amplifier (SBLSA) circuits, i.e., a redundant voltage discharged SBLSA (RVD-SBLSA) circuit and a bit aware SBLSA (BA-SBLSA) circuit, to improve conventional and single bitline write (SBW) circuits. The RVD-SBLSA circuit utilizes a clamp diode to discharge redundant voltage over VDD/2 with an additional working stage. The BA-SBLSA circuit abandons the single bitline load (SBL) circuit during read and write '1' operations. The RVD-SBLSA circuit can offer the lowest total energy consumption, and the BA-SBLSA circuit can make a better balance between energy consumption and latency. Through the simulation results, the proposed circuits can efficiently reduce energy consumption or balance energy consumption and latency and show huge potentials in very large-scale integrated circuits. [ABSTRACT FROM AUTHOR]