Numerical Modeling of AC Loss in HTS Coated Conductors and Roebel Cable Using T-A Formulation and Comparison with H Formulation

With recent advances in second-generation high temperature superconductors (2G HTS) and cable technologies, various numerical models based on finite-element method (FEM) have been proposed to help interpret measured AC loss and assist cable design. The T-A formulation, implemented in COMSOL, shows great potential for reducing the overall computation costs. In this paper, the performance of the T-A formulation for calculating the AC loss of coated superconductors and cables were assessed and compared against the widely accepted H formulation, with benchmark model of a single REBCO tape in 2D/3D and a 14-strand Roebel cable. Evaluation and comparison on key metrics including the computation time, the number of degrees of freedom and the numerical accuracy were presented, which could provide a reference for researchers in applying the T-A formulation for AC loss calculation

Invariant Random Forest: Tree-Based Model Solution for OOD Generalization

Out-Of-Distribution (OOD) generalization is an essential topic in machine learning. However, recent research is only focusing on the corresponding methods for neural networks. This paper introduces a novel and effective solution for OOD generalization of decision tree models, named Invariant Decision Tree (IDT). IDT enforces a penalty term with regard to the unstable/varying behavior of a split across different environments during the growth of the tree. Its ensemble version, the Invariant Random Forest (IRF), is constructed. Our proposed method is motivated by a theoretical result under mild conditions, and validated by numerical tests with both synthetic and real datasets. The superior performance compared to non-OOD tree models implies that considering OOD generalization for tree models is absolutely necessary and should be given more attention.Comment: AAAI Conference on Artificial Intelligence, 2024 (Oral Presentation

Probing Single-molecule Enzyme Active-site Conformational State Intermittent Coherence

The relationship between protein conformational dynamics and enzymatic reactions has been a fundamental focus in modern enzymology. Using single-molecule fluorescence resonance energy transfer (FRET) with a combined statistical data analysis approach, we have identified the intermittently appearing coherence of the enzymatic conformational state from the recorded single-molecule intensity-time trajectories of enzyme 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase (HPPK) in catalytic reaction. The coherent conformational state dynamics suggests that the enzymatic catalysis involves a multistep conformational motion along the coordinates of substrate-enzyme complex formation and product releasing, presenting as an extreme dynamic behavior intrinsically related to the time bunching effect that we have reported previously. The coherence frequency, identified by statistical results of the correlation function analysis from single-molecule FRET trajectories, increases with the increasing substrate concentrations. The intermittent coherence in conformational state changes at the enzymatic reaction active site is likely to be common and exist in other conformation regulated enzymatic reactions. Our results of HPPK interaction with substrate support a multiple-conformational state model, being consistent with a complementary conformation selection and induced-fit enzymatic loop-gated conformational change mechanism in substrate-enzyme active complex formation

Farthest Greedy Path Sampling for Two-shot Recommender Search

Weight-sharing Neural Architecture Search (WS-NAS) provides an efficient mechanism for developing end-to-end deep recommender models. However, in complex search spaces, distinguishing between superior and inferior architectures (or paths) is challenging. This challenge is compounded by the limited coverage of the supernet and the co-adaptation of subnet weights, which restricts the exploration and exploitation capabilities inherent to weight-sharing mechanisms. To address these challenges, we introduce Farthest Greedy Path Sampling (FGPS), a new path sampling strategy that balances path quality and diversity. FGPS enhances path diversity to facilitate more comprehensive supernet exploration, while emphasizing path quality to ensure the effective identification and utilization of promising architectures. By incorporating FGPS into a Two-shot NAS (TS-NAS) framework, we derive high-performance architectures. Evaluations on three Click-Through Rate (CTR) prediction benchmarks demonstrate that our approach consistently achieves superior results, outperforming both manually designed and most NAS-based models.Comment: 9 pages, 5 figure

Serum spexin differed in newly diagnosed type 2 diabetes patients according to body mass index and increased with the improvement of metabolic status

ObjectiveThe aim of this study was to explore serum spexin levels in newly diagnosed type 2 diabetes mellitus (T2DM) patients with different body mass indexes (BMIs) and to investigate the changes of spexin after improvement of metabolic indicators.MethodsA total of 323 newly diagnosed T2DM patients from national Metabolic Management Center (MMC) in Shanghai General Hospital were recruited. T2DM patients were categorized into three groups: diabetes with obesity group (DM-OB group, BMI≥28 kg/m2, n=89), diabetes with overweight group (DM-OV group, 24≤BMI<28 kg/m2, n=161), and diabetes with normal weight group (DM-NW group, 18≤BMI<24 kg/m2, n=73). In addition, 41 volunteers with normal glucose tolerance (NGT) were used as controls. Spexin and metabolic parameters were compared at baseline, and changes after MMC follow-up in 100 DM patients were investigated.ResultsIn the DM-OB group, the level of spexin was significantly lower than that in the DM-OV group and the DM-NW group (P < 0.01). Spexin was significantly negatively related to body mass index (BMI, β=-0.214, P<0.001), waist circumference (β=-0.249, P<0.001), visceral fat area (VFA, β=-0.214, P<0.001), and subcutaneous fat area (SFA, β=-0.265, P<0.001) after adjustment for age and sex. Among all the metabolic indicators, the decline in BMI in the DM-OB group was the most obvious among those in the three groups (-3.7 ± 0.8 kg/m2 vs. -0.9 ± 0.3 kg/m2 vs. 0.7 ± 0.6 kg/m2, P<0.01) after one year of MMC standardized management. The serum spexin level in the DM-OB group increased the most (1.00 ± 0.10 ng/mL vs. 0.49 ± 0.06 ng/mL in DM-OV group and 0.58 ± 0.09 ng/mL in DM-NW group, P < 0.001).ConclusionsSerum spexin differed in newly diagnosed T2DM patients according to BMI and was lowest in the DM-OB group. With the improvement of metabolic indicators, especially the decline in BMI, serum spexin increased significantly after MMC management

Modeling of Bimodular Bone Specimen under Four-Point Bending Fatigue Loading

The fatigue damage behavior of bone has attracted significant attention in both the mechanical and orthopedic fields. However, due to the complex and hierarchical structure of bone, describing the damage process quantitively or qualitatively is still a significant challenge for researchers in this area. In this study, a nonlinear bi-modulus gradient model was proposed to quantify the neutral axis skewing under fatigue load in a four-point bending test. The digital image correlation technique was used to analyze the tensile and compressive strains during the fatigue process. The results showed that the compressive strain demonstrated an obvious two-stage ascending behavior, whereas the tensile strain revealed a slow upward progression during the fatigue process. Subsequently, a theoretical model was proposed to describe the degradation process of the elastic modulus and the movement of the neutral axis. The changes in the bone properties were determined using the FEM method based on the newly developed model. The results obtained from two different methods exhibited a good degree of consistency. The results obtained in this study are of help in terms of effectively exploring the damage evolution of the bone materials