Recursive reasoning models solve complex reasoning tasks through iterative refinement, enabling tiny networks to rival far larger language models. However, training remains expensive: prior work reports 36 GPU-hours for Sudoku-Extreme. We propose CGAR, a training methodology that applies curriculum learning to architectural depth rather than data ordering. CGAR combines Progressive Depth Curriculum (PDC), which adjusts recursion depth from shallow to deep configurations during training, and Hierarchical Supervision Weighting (HSW), which applies exponentially decaying importance to supervision steps to align loss weighting with observed gradient magnitude decay. On Sudoku-Extreme (423,168 test puzzles), CGAR achieves 1.71 × training speedup (10.93 to 6.38 hours, 42% cost reduction) with only 0.63% accuracy drop (86.65% to 86.02%), while preventing late-stage overfitting that degrades baseline to 86.31%. Ablations reveal PDC alone achieves 2.26 × speedup at 85.47% accuracy, improving training efficiency and accuracy at once. The speedup reproduces on Maze-Hard and ARC-AGI-1 (1.25–1.71 × over three tasks), with the fixed-depth baseline failing to learn ARC-AGI-1 under matched budget. CGAR-trained models exhibit near-perfect halting accuracy (99.5% for full CGAR; 100% for the PDC-only configuration) and 6% fewer reasoning steps. Curriculum on architectural depth enables efficient training of recursive reasoners on modest hardware. Code: https://github.com/Kaleemullahqasim/CGAR.
The integration of multifunctional modules into ultrathin, spatially constrained flexible electronics often leads to localized heat accumulation, challenging device reliability under conformal operation. Achieving precise heatflux manipulation, mechanical flexibility, and scalable fabrication within a unified platform remains an open challenge. Here, we report a gradient-discretized design strategy for flexible thermal metamaterials that combines multiscale topology optimization with transformation thermotics. This framework links microstructural geometry, deformation-induced effects, and macroscopic thermal functionality, including thermal cloaking and thermal concentration. Using flexible printed-circuit fabrication, we fabricate gradient arrays containing 6 & times; 6 to 20 & times; 20 unit cells, with pitches ranging from 10 to 3 mm, within a fixed 60 & times; 60 mm2 footprint. We also develop a coupled thermomechanical resistance model to quantify bending-induced perturbations. In the flat state, the thermal-cloaking function suppresses the temperature gradient within the protected region to approximately 1% of the surrounding background gradient, thereby enabling thermal concealment of embedded heterogeneous structures. The thermal-concentration function enhances local heat focusing by nearly one order of magnitude, increasing the temperature difference available to a thermoelectric module. Both functions remain effective under bending at a radius of 19 mm, with only moderate performance degradation. These results establish a scalable and mechanically compliant platform for programmable heat-flux control in next-generation conformal and wearable electronics.
Electric vertical take-off and landing vehicles (eVTOLs) can provide fast, potentially lower-carbon trunk services for long-distance urban commuting, but they require coordination with ground feeder modes because they cannot provide door-to-door service. Under fluctuating passenger arrivals, fixed timetables are easy to operate but inflexible, whereas load-based departure rules improve utilization but create unpredictable waiting. This study proposes an adaptive soft-target dispatch strategy that schedules eVTOL departures based on passenger accumulation, stranded demand, and vehicle availability. The integrated land-air dispatch problem is formulated as an event-driven, multi-line decision process and solved using multi-agent reinforcement learning. Numerical experiments show that the proposed strategy reduces average system cost by 22.57% relative to fixed timetables and 0.51% relative to full-match rules, with the largest gains under low-to-medium demand and medium-to-high values of time. A Chengdu airport case study further confirms its cost-saving potential.
Traditional phase selection method is influenced by control strategy of double-side converters in Low-Frequency Transmission System of Offshore Wind Power, resulting in reduced reliability and difficulty in adaptation. Aiming at to the above issues, proposes a transient fault phase selection method suitable for LFTSOWP. Then, a reasonable frequency range for traveling wave analysis is selected, and a phase-selection method based on the Generalized S-Transform using the energy ratio of line voltage traveling waves is proposed. In addition, the positive and negative energy ratios of phase voltages are adopted as auxiliary criteria to solve the problem of identifying the faulty phase in phase-to-phase ground faults under a certain fault startup Angle. Finally, a typical LFTSOWP model is built in PSCAD/EMTDC. The verification results indicate that the proposed method can rapidly identify the fault phase, has good robustness.
Radiant heat flux serves as a direct indicator for assessing the spread of wildland fires and the extent of thermal injury. It is of primary importance for wildland managers and firefighters to estimate the thermal radiation from a flame front and the safety distances of persons and houses within the Wildland-Urban Interface. In the presence of ambient wind, wildland fires frequently develop flames with a tilted, triangular prism morphology. Hence the estimation of incident radiant heat flux and safety distance can be realized based on solid flame model by solving the view factor. This work presents an analytical model for both horizontal and vertical view factors from a tilted rectangular flame to a target at any position. The proposed model was validated by comparing its results with previous studies. The calculated view factors were applied in the determination of radiant heat fluxes for smallscale and large-scale wildland fires based on some assumptions. The distribution patterns of horizontal and vertical radiant heat fluxes along the central vertical section of the fire source were revealed. The safety distances respectively for persons without protection and firefighters with protection were determined as a function of the fire width or flame height. The maximum ignition distance of houses built with wood for a large wildland fire was determined as 70 m. Then some useful loss mitigation measures were proposed. This work helps enhance the understanding of wildland fire spread potential and radiation-induced ignition likelihood, while also contributing to wildland fire modeling and wildland area planning.
