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Planning and problem solving are cornerstones of higher brain function. But we do not know how the brain does that. We show that learning of a suitable cognitive map of the problem space suffices. Furthermore, this can be reduced to learning to predict the next observation through local synaptic plasticity. Importantly, the resulting cognitive map encodes relations between actions and observations, and its emergent high-dimensional geometry provides a sense of direction for reaching distant goals. This quasi-Euclidean sense of direction provides a simple heuristic for online planning that works almost as well as the best offline planning algorithms from AI. If the problem space is a physical space, this method automatically extracts structural regularities from the sequence of observations that it receives so that it can generalize to unseen parts. This speeds up learning of navigation in 2D mazes and the locomotion with complex actuator systems, such as legged bodies. The cognitive map learner that we propose does not require a teacher, similar to self-attention networks (Transformers). But in contrast to Transformers, it does not require backpropagation of errors or very large datasets for learning. Hence it provides a blue-print for future energy-efficient neuromorphic hardware that acquires advanced cognitive capabilities through autonomous on-chip learning. The task of planning a sequence of actions, and dynamically adjusting the plan in dependence of unforeseen circumstances, remains challenging for artificial intelligence frameworks. The authors introduce a learning approach inspired by cognitive functions, that demonstrates high flexibility and generalization capability in planning tasks, suitable for on-chip learning.

In this paper, X70 steel pipe with a diameter of 600mm and a thickness of 15mm was selected. In combination with the actual production situation, the welding process under the condition of electrode arc welding is established for the horizontal fixed (5G) position. After the welding is completed, the rationality of the process formulation is verified by the corresponding non-destructive testing methods and related mechanical properties tests. The temperature field of the joint was simulated by numerical simulation software, and the temperature field variation of the joint under different conditions was analyzed.

In the context of the “double carbon” initiative, the exploration of strategies for energy conservation and emission reduction through both policy and technological approaches has emerged as a significant area of contemporary research. Based on this, a low-carbon economic dispatch model of the integrated energy system (IES) including oxygen-enriched combustion power plant (OCPP), two-stage power-to-gas (P2G), and combined heat and power (CHP) units is constructed. The objective of the model is to optimize total operational expenditures while simultaneously improving carbon resource recovery and mitigating emissions. Notable advancements encompass the transformation of traditional thermal power units into OCPP, the formulation of mathematical models for OCPP, the implementation of two-stage P2G systems, and CHP systems, as well as the incorporation of a demand response (DR) mechanism. The findings from the simulation demonstrate that the OCPP-P2G-CHP integrated system exhibits a marked enhancement in carbon capture efficiency when juxtaposed with conventional systems. Additionally, it results in a 7.8% reduction in overall costs and a 30.2% decrease in carbon emissions. This research substantiates the viability and innovative nature of the proposed model, underscoring its potential for scalable application within industrial and urban energy networks.

The integration of renewable energy sources, such as wind and solar power, into the grid is essential for achieving carbon peaking and neutrality goals. However, the inherent variability and unpredictability of these energy sources pose significant challenges to power system stability. Advanced energy storage systems (ESS) are critical for mitigating these challenges, with gravity energy storage systems (GESS) emerging as a promising solution due to their scalability, economic viability, and environmental benefits. This paper proposes a multi-objective economic capacity optimization model for GESS within a novel power system framework, considering the impacts on power network stability, environmental factors, and economic performance. The model is solved using an enhanced Grasshopper Optimization Algorithm (W-GOA) incorporating a whale spiral motion strategy to improve convergence and solution accuracy. Simulations on the IEEE 30-node system demonstrate that GESS reduces peak-to-valley load differences by 36.1% and curtailment rates by 42.3% (wind) and 18.7% (PV), with a 15% lower levelized cost than CAES. The results indicate that GESS effectively mitigates peak load pressures, stabilizes the grid, and provides a cost-effective solution for integrating high shares of renewable energy. This study highlights the potential of GESS as a key component in future low-carbon power systems, offering both technical and economic advantages over traditional energy storage technologies.

0Cr18Ni9 stainless steel pipe is a commonly used welding material, which has great demand in shipbuilding, boiler pressure vessel and construction engineering. In this paper, for a given welding process condition, select reasonable parameters, carry out numerical simulation process on welded joints, analyze the temperature field distribution law and stress field value of welded joints, and judge whether it is consistent with the actual.

Background The surgical safety of cataract patients with high myopia after pars plana vitrectomy (PPV) surgery deserves more attention. Currently, there are limited reported studies on the use of femtosecond laser-assisted cataract surgery (FLACS) to treat cataracts following PPV surgery in patients with high myopia. This study was designed to compare the clinical effects of FLACS and conventional phacoemulsification surgery (CPS) in these patients. Methods A retrospective comparative cohort was conducted. The primary endpoint was best-corrected visual acuity (BCVA, logMAR) at 1 month after surgery. Confounding by indication was addressed using stabilized inverse probability of treatment weighting (IPTW) based on prespecified baseline covariates, with a doubly robust ANCOVA adjusting for baseline BCVA and clinical covariates. Longitudinal BCVA and intraocular pressure (IOP) were analyzed using linear mixed-effects models. Secondary endpoints were prespecified into families (Vision, IOP, Complication and adverse events). Per-time-point contrasts were descriptive and not multiplicity-adjusted; primary inference relied on Type III omnibus tests. Results Seventy-seven eyes were included (FLACS, n  = 33; CPS, n  = 44). Post-weighting covariate balance was excellent (all standardized mean differences ≤ 0.07). The adjusted mean difference in Month-1 BCVA (FLACS − CPS) was − 0.17 logMAR (95% CI − 0.36 to 0.03), suggesting a possible benefit with uncertainty spanning negligible to moderate improvement. Early vision favored FLACS at Day-1 (− 0.29 logMAR; 95% CI − 0.53 to − 0.06) and the difference at Week-1 was small and imprecise (− 0.22 logMAR; 95% CI − 0.45 to 0.02); estimates converged by Month-1 to Month-3. IOP changed over time without an overall group difference; a small and imprecise higher IOP at Week-1, with estimates crossing zero. Nd: YAG capsulotomy rates were low and similar between groups. Conclusions In highly myopic post-PPV eyes, FLACS was associated with faster early visual recovery versus CPS, whereas 1–3 month outcomes were broadly similar. Findings are associative and may be influenced by residual confounding.

This study investigates the progressive compressive behavior of modular interior frames with rotary-type module-to-module inter-modular (M2M) connections under sequential column failure. A novel two-stage testing protocol was applied, compressing the left upper column to failure, followed by the right, to simulate realistic loading progression in prefabricated column-supported volumetric modular steel structures. Detailed refined finite-element models (FEMs) were developed and validated against experimental results, accurately capturing local and global responses with an average prediction error of 2–10% for strength and stiffness. An extensive parametric study involving varying frame configurations evaluated the influence of frame member geometric properties, connection details, and column/beam gap interaction on progressive collapse behavior. The results demonstrated that upper columns govern failure through elastic–plastic buckling near M2M joints while other members/connections remain elastic/unyielded. Increasing column cross section and thickness significantly enhanced strength and stiffness, while longer columns and prior damage reduced capacity, particularly during right-column loading. Conventional steel design codes overestimated column strength, with mean Pu,FEM/Pu,code ratios below unity and high scatter (Coefficient of variation ~0.25–0.27), highlighting the inadequacy of isolated member-based design equations for modular assemblies. The findings emphasize the need for frame-based stability approaches that account for M2M joint semi-rigidity, sway sensitivity, and sequential failure effects to ensure the reliable design of modular steel frames under progressive compressive loads.

In order to investigate the antioxidant activity of Elaeagnus umbellata polysaccharides, the physicochemical characteristics of purified Elaeagnus umbellata polysaccharides (EUP, consisting of two fractions, EUP1 and EUP2) were investigated using UV spectrophotometry, high-performance liquid chromatography (HPLC), high-performance gel permeation chromatography (HPGPC), and Fourier transform infrared spectroscopy (FT-IR). This revealed that EUP1 and EUP2 were acidic polysaccharides with an average molecular weight (MW) of 63 and 38 kDa, respectively. EUP1 mainly consisted of L-rhamnose and D-galactose in a molar ratio of 2.05:1, and EUP2 consisted of D-mannose, L-rhamnose, D-galactose, and D-arabinose in a molar ratio of 2.06:1:2.78:1. Furthermore, EUP exhibited considerable antioxidant potential for scavenging hydroxyl, superoxide anion, DPPH, and ABTS radicals. Therefore, EUP can be developed as a potential antioxidant for the functional food or pharmaceutical field.

In this paper, the weld of Q235 steel pipe with diameter of 60 mm and thickness of 4 mm is simulated and analyzed by MSC. Marc software. After modeling, applying material physical properties, setting weld bead and welding path, and applying boundary conditions, the operation results are analyzed and processed by submitting the work. According to the simulation results, different joints are selected to study the thermal cycle process and temperature distribution of joints under different joints.

Polymers maintain colloidal stability by adsorbing onto the surface of sepiolite particles, and changes in temperature and salinity can affect this process. We chose three typical polymers to investigate their interactions with sepiolite under high-salinity (15 wt.% NaCl) conditions at >180°C. Sepiolite samples were characterized using infrared testing, X-ray diffraction testing, contact angle testing, thermogravimetric testing, filtration loss testing and rheological testing. The experimental results showed that the desorption of the polymers under high-temperature and high-salinity conditions reduces the stability and filtration control of the suspension significantly. Adding polymers to sepiolite suspensions can maintain good stability even after thermal ageing at 240°C. In terms of drilling fluid regulation, sepiolite can play a role in regulating rheological properties, and the interactions between various polymers and sepiolite can be utilized to maintain the stable colloidal state of the drilling fluid. Studying the adsorption behaviour of various types of polymers on the surface of sepiolite under high-temperature and high-salinity conditions has important implications for the design and selection of sepiolite drilling fluid treatment agents.