The Zeros of Orthogonal Polynomials for Jacobi-Exponential Weights

This paper gives the estimates of the zeros of orthogonal polynomials for Jacobi-exponential weights

Adversarial Feature Stacking for Accurate and Robust Predictions

Deep Neural Networks (DNNs) have achieved remarkable performance on a variety of applications but are extremely vulnerable to adversarial perturbation. To address this issue, various defense methods have been proposed to enhance model robustness. Unfortunately, the most representative and promising methods, such as adversarial training and its variants, usually degrade model accuracy on benign samples, limiting practical utility. This indicates that it is difficult to extract both robust and accurate features using a single network under certain conditions, such as limited training data, resulting in a trade-off between accuracy and robustness. To tackle this problem, we propose an Adversarial Feature Stacking (AFS) model that can jointly take advantage of features with varied levels of robustness and accuracy, thus significantly alleviating the aforementioned trade-off. Specifically, we adopt multiple networks adversarially trained with different perturbation budgets to extract either more robust features or more accurate features. These features are then fused by a learnable merger to give final predictions. We evaluate the AFS model on CIFAR-10 and CIFAR-100 datasets with strong adaptive attack methods, which significantly advances the state-of-the-art in terms of the trade-off. Without extra training data, the AFS model achieves a benign accuracy improvement of 6% on CIFAR-10 and 9% on CIFAR-100 with comparable or even stronger robustness than the state-of-the-art adversarial training methods. This work demonstrates the feasibility to obtain both accurate and robust models under the circumstances of limited training data

Phase diagram and exotic spin-spin correlations of anisotropic Ising model on the Sierpi\'nski gasket

The anisotropic antiferromagnetic Ising model on the fractal Sierpi\'{n}ski gasket is intensively studied, and a number of exotic properties are disclosed. The ground state phase diagram in the plane of magnetic field-interaction of the system is obtained. The thermodynamic properties of the three plateau phases are probed by exploring the temperature-dependence of magnetization, specific heat, susceptibility and spin-spin correlations. No phase transitions are observed in this model. In the absence of a magnetic field, the unusual temperature dependence of the spin correlation length is obtained with $0 \leq$J$_b/$J$_a<1$, and an interesting crossover behavior between different phases at J$_b/$J$_a=1$ is unveiled, whose dynamics can be described by the J$_b/$J$_a$-dependence of the specific heat, susceptibility and spin correlation functions. The exotic spin-spin correlation patterns that share the same special rotational symmetry as that of the Sierpi\'{n}ski gasket are obtained in both the $1/3$ plateau disordered phase and the $5/9$ plateau partially ordered ferrimagnetic phase. Moreover, a quantum scheme is formulated to study the thermodynamics of the fractal Sierpi\'{n}ski gasket with Heisenberg interactions. We find that the unusual temperature dependence of the correlation length remains intact in a small quantum fluctuation.Comment: 9 pages, 12 figure

Personalized compression therapeutic textiles: digital design, development, and biomechanical evaluation

Physical-based external compression medical modalities could provide sustainable interfacial pressure dosages for daily healthcare prophylaxis and clinic treatment of chronic venous disease (CVD). However, conventional ready-made compression therapeutic textiles (CTs) with improper morphologies and ill-fitting of pressure exertions frequently limit patient compliance in practical application. Therefore, the present study fabricated the personalized CTs for various subjects through the proposed comprehensive manufacturing system. The individual geometric dimensions and morphologic profiles of lower extremities were characterized according to three-dimensional (3D) body scanning and reverse engineering technologies. Through body anthropometric analysis and pressure optimization, the knitting yarn and machinery variables were determined as the digital design strategies for 3D seamless fabrication of CTs. Next, to visually simulate the generated pressure mappings of developed CTs, the subject-specific 3D finite element (FE) CT-leg modelings with high accuracy and acceptability (pressure prediction error ratio: 11.00% ± 7.78%) were established based on the constructed lower limb models and determined tissue stiffness. Moreover, through the actual in vivo trials, the prepared customized CTs efficiently (Sig. &lt;0.05; ρ = 0.97) distributed the expected pressure requirements referring to the prescribed compression magnitudes (pressure error ratio: 10.08% ± 7.75%). Furthermore, the movement abilities and comfortable perceptions were evaluated subjectively for the ergonomic wearing comfort (EWC) assessments. Thus, this study promotes the precise pressure management and clinical efficacy for targeted users and leads an operable development approach for related medical biomaterials in compression therapy

Antitumor Efficacy and Mechanism in Hepatoma H22-Bearing Mice of Brucea javanica

Brucea javanica is a traditional herbal medicine in China, and its antitumor activities are of research interest. Brucea javanica oil, extracted with ether and refined with 10% ethyl alcohol from Brucea javanica seed, was used to treat hepatoma H22-bearing mice in this study. The antitumor effect and probable mechanisms of the extracted Brucea javanica oil were studied in H22-bearing mice by WBC count, GOT, GPT levels, and western blotting. The H22 tumor inhibition ratio of 0.5, 1, and 1.5 g/kg bw Brucea javanica oil were 15.64%, 23.87%, and 38.27%. Brucea javanica oil could inhibit the involution of thymus induced by H22 tumor-bearing, but it could not inhibit the augmentation of spleen and liver. Brucea javanica oil could decrease the levels of WBC count and GOT and GPT in H22-bearing mice. The protein levels of GAPDH, Akt, TGF-β1, and α-SMA in tumor tissues decreased after being treated with Brucea javanica oil. Disturbing energy metabolism and neoplastic hyperplasia controlled by Akt and immunoregulation activity were its probable antitumor mechanisms in hepatoma H22-bearing mice

Planar carbon nanotube-graphene hybrid films for high-performance broadband photodetectors

Graphene has emerged as a promising material for photonic applications fuelled by its superior electronic and optical properties. However, the photoresponsivity is limited by the low absorption cross section and ultrafast recombination rates of photoexcited carriers. Here we demonstrate a photoconductive gain of $\sim$ 10$^5$ electrons per photon in a carbon nanotube-graphene one dimensional-two dimensional hybrid due to efficient photocarriers generation and transport within the nanostructure. A broadband photodetector (covering 400 nm to 1550 nm) based on such hybrid films is fabricated with a high photoresponsivity of more than 100 AW$^{-1}$ and a fast response time of approximately 100 {\mu}s. The combination of ultra-broad bandwidth, high responsivities and fast operating speeds affords new opportunities for facile and scalable fabrication of all-carbon optoelectronic devices.Comment: 21 pages, 3 figure