Resonant Charge Relaxation as a Likely Source of the Enhanced Thermopower in FeSi

The enhanced thermopower of the correlated semiconductor FeSi is found to be robust against the sign of the relevant charge carriers. At $T$\,$\approx$\,70 K, the position of both the high-temperature shoulder of the thermopower peak and the nonmagnetic-enhanced paramagnetic crossover, the Nernst coefficient $\nu$ assumes a large maximum and the Hall mobility $\mu _H$ diminishes to below 1 cm$^2$/Vs. These cause the dimension-less ratio $\nu$/$\mu_H$ $-$ a measure of the energy dispersion of the charge scattering time $\tau(\epsilon)$ $-$ to exceed that of classical metals and semiconductors by two orders of magnitude. Concomitantly, the resistivity exhibits a hump and the magnetoresistance changes its sign. Our observations hint at a resonant scattering of the charge carriers at the magnetic crossover, imposing strong constraints on the microscopic interpretation of the robust thermopower enhancement in FeSi.Comment: 5 pages, 3 figure

DisWOT: Student Architecture Search for Distillation WithOut Training

Knowledge distillation (KD) is an effective training strategy to improve the lightweight student models under the guidance of cumbersome teachers. However, the large architecture difference across the teacher-student pairs limits the distillation gains. In contrast to previous adaptive distillation methods to reduce the teacher-student gap, we explore a novel training-free framework to search for the best student architectures for a given teacher. Our work first empirically show that the optimal model under vanilla training cannot be the winner in distillation. Secondly, we find that the similarity of feature semantics and sample relations between random-initialized teacher-student networks have good correlations with final distillation performances. Thus, we efficiently measure similarity matrixs conditioned on the semantic activation maps to select the optimal student via an evolutionary algorithm without any training. In this way, our student architecture search for Distillation WithOut Training (DisWOT) significantly improves the performance of the model in the distillation stage with at least 180$\times$ training acceleration. Additionally, we extend similarity metrics in DisWOT as new distillers and KD-based zero-proxies. Our experiments on CIFAR, ImageNet and NAS-Bench-201 demonstrate that our technique achieves state-of-the-art results on different search spaces. Our project and code are available at https://lilujunai.github.io/DisWOT-CVPR2023/.Comment: Accepted by CVPR202

AGE-RELATED SARCOPENIA: AN ELECTROMYOGRAPHIC AND MECHANOMYOGRAPHYIC STUDY

The purpose of this study was to investigate the effects of age-related sarcopenia on muscle mass, relative muscle strength/power performance in the lower limbs, and the responses of electromyography (EMG) and mechanomyography (MMG) on the activation patterns of motor units under leg extension muscle power performance in the elderly. Subjects were healthy old (n=10, 64.5 ± 4.5 yrs) and young (n=10, 22.6 ± 2.8yrs) people. All subjects performed quadriceps maximal voluntary contraction (MVC) and fastest speed leg extension with different levels (75%, 60%, 45% 1RM), and 45% fatigue test to all-outThe results indicate the declines of muscle mass, neuromuscular performance and changes of MU activation patterns may result from age-related sarcopenia, and the age affects muscle power more than muscle strength

EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization

Mixed-Precision Quantization~(MQ) can achieve a competitive accuracy-complexity trade-off for models. Conventional training-based search methods require time-consuming candidate training to search optimized per-layer bit-width configurations in MQ. Recently, some training-free approaches have presented various MQ proxies and significantly improve search efficiency. However, the correlation between these proxies and quantization accuracy is poorly understood. To address the gap, we first build the MQ-Bench-101, which involves different bit configurations and quantization results. Then, we observe that the existing training-free proxies perform weak correlations on the MQ-Bench-101. To efficiently seek superior proxies, we develop an automatic search of proxies framework for MQ via evolving algorithms. In particular, we devise an elaborate search space involving the existing proxies and perform an evolution search to discover the best correlated MQ proxy. We proposed a diversity-prompting selection strategy and compatibility screening protocol to avoid premature convergence and improve search efficiency. In this way, our Evolving proxies for Mixed-precision Quantization~(EMQ) framework allows the auto-generation of proxies without heavy tuning and expert knowledge. Extensive experiments on ImageNet with various ResNet and MobileNet families demonstrate that our EMQ obtains superior performance than state-of-the-art mixed-precision methods at a significantly reduced cost. The code will be released.Comment: Accepted by ICCV202

ParZC: Parametric Zero-Cost Proxies for Efficient NAS

Recent advancements in Zero-shot Neural Architecture Search (NAS) highlight the efficacy of zero-cost proxies in various NAS benchmarks. Several studies propose the automated design of zero-cost proxies to achieve SOTA performance but require tedious searching progress. Furthermore, we identify a critical issue with current zero-cost proxies: they aggregate node-wise zero-cost statistics without considering the fact that not all nodes in a neural network equally impact performance estimation. Our observations reveal that node-wise zero-cost statistics significantly vary in their contributions to performance, with each node exhibiting a degree of uncertainty. Based on this insight, we introduce a novel method called Parametric Zero-Cost Proxies (ParZC) framework to enhance the adaptability of zero-cost proxies through parameterization. To address the node indiscrimination, we propose a Mixer Architecture with Bayesian Network (MABN) to explore the node-wise zero-cost statistics and estimate node-specific uncertainty. Moreover, we propose DiffKendall as a loss function to directly optimize Kendall's Tau coefficient in a differentiable manner so that our ParZC can better handle the discrepancies in ranking architectures. Comprehensive experiments on NAS-Bench-101, 201, and NDS demonstrate the superiority of our proposed ParZC compared to existing zero-shot NAS methods. Additionally, we demonstrate the versatility and adaptability of ParZC by transferring it to the Vision Transformer search space

Research on bionic composite guidance law considering field of view angle

Due to the use of strapdown seeker in small missiles, a small field of view angle is required to ensure effective tracking and strike of the target during the final interception. Based on the tracking strategy of dragonfly chasing targets, a composite guidance law is studied. In the initial guidance section, the parallax angle is controlled by the sliding mode control law to adjust the missile to the tail following attitude. The final guidance section used the motion camouflage guidance law with the focus at infinity for target tracking,and between the initial guidance and the final guidance. The second-order smooth interface law is used for the transition. The simulation results show that compared with the traditional proportional guidance law, the required overload of the missile in the final guidance is small,and the target is closer to the center of the field of view, which can reduce the missile in the final guidance. The overload and the field of view of the seeker can be used to effectively improve the attack accuracy

OR-026 Exercise induces HIF-1α redistribution in the small intestine

Objective Intestinal epithelial cells are positioned between an anaerobic lumen and a highly metabolic lamina propria, affected by reduced blood flow and tissue hypoxia. Exercise induces blood flow redistribution, leading to hypoperfusion and gastrointestinal (GI) compromise. The hypoxia-inducible factor (HIF) 1α is pivotal in the transcriptional response to oxygen flux. In this study, we hypothesized that exercise induces GI system hypoxia and accumulates HIF-1α. Methods (1) ROSA26 ODD-Luc/+ mouse model (ODD-Luc) was used to detect HIF-1α expression in the intestine (female, 8-week, n=6/group). ODD-Luc mice were randomized into 4 groups: stayed in 21% O2 as the normoxic control (C), exercise (E), injected HIF-1α inhibitor PX-478 before swimming (PS), placed in the chamber containing 9% O2 for 4 hours as the positive control (PC). (2) Exercise models were conducted by volume: Moderate Exercise (ME): mice voluntarily swam for 30 min; Heavy-intensity Exercise (HE): mice swam for 1.5 hours with 5% body weight loads attached to their tails; Long-time Exercise (LE): mice voluntarily swam for 3 hours or till fatigue. Results (1) Exercise increased HIF-1α in the abdominal area. The luciferase activities boosted after exercise, compared to the controls (ME v.s. C, P<0.05; HE v.s. C, P<0.05; LE v.s. C, P<0.05) but no differences among three exercise groups (ME v.s. HE, P>0.99; ME v.s. LE, P>0.99; HE v.s. LE, P>0.99); (2) Exercise altered HIF-1α distribution in the small intestine in a time-dependent manner. The expression of HIF-1α was significantly increased after exercise and gradually reduced to the rest level. The photons increased at the 0th hour after exercise compared to that of the normoxic control (P<0.01). The level of photons then reduced over time, while the 2nd, 4th and 6th hour post-exercise were still greater than that of the normoxic control  (2nd hour v.s. C, P<0.01; 4th hour v.s. C, P<0.01; 6th hour v.s. C, P<0.05), and returned to normal after 24 hours (24th hour v.s. C, P>0.99). Conclusions Exercise induced the distribution of HIF-1α in the small intestine. The expression of HIF-1α is shown in a time-dependent manner after exercise