Lightweight Self-Knowledge Distillation with Multi-source Information Fusion

Knowledge Distillation (KD) is a powerful technique for transferring knowledge between neural network models, where a pre-trained teacher model is used to facilitate the training of the target student model. However, the availability of a suitable teacher model is not always guaranteed. To address this challenge, Self-Knowledge Distillation (SKD) attempts to construct a teacher model from itself. Existing SKD methods add Auxiliary Classifiers (AC) to intermediate layers of the model or use the history models and models with different input data within the same class. However, these methods are computationally expensive and only capture time-wise and class-wise features of data. In this paper, we propose a lightweight SKD framework that utilizes multi-source information to construct a more informative teacher. Specifically, we introduce a Distillation with Reverse Guidance (DRG) method that considers different levels of information extracted by the model, including edge, shape, and detail of the input data, to construct a more informative teacher. Additionally, we design a Distillation with Shape-wise Regularization (DSR) method that ensures a consistent shape of ranked model output for all data. We validate the performance of the proposed DRG, DSR, and their combination through comprehensive experiments on various datasets and models. Our results demonstrate the superiority of the proposed methods over baselines (up to 2.87%) and state-of-the-art SKD methods (up to 1.15%), while being computationally efficient and robust. The code is available at https://github.com/xucong-parsifal/LightSKD.Comment: Submitted to IEEE TNNL

Design and Simulation of a Single Piezoelectric-Driven Rotary Actuator with Double-Layer Flexible Mechanism

A novel pure rotary actuator with a double-layer flexible mechanism (RA-DFM), which is driven by a single piezoelectric ceramic in the lower mechanism and generates rotational motion in the upper mechanism, is proposed in this paper. The output of piezoelectric ceramic is successively amplified using an enhanced double Scott–Russell mechanism and two lever-type mechanisms to obtain a large rotation range. The static, kinematic and dynamic properties of the RA-DFM are numerically analyzed, and the actual output of the piezoelectric is analyzed considering the input stiffness. The geometric parameters of the RA-DFM are optimized based on the constructed numerical models. Finite element analysis has been implemented to validate the correctness of the theoretical models and further evaluate the output property. The simulation results show the maximal rotation angle of the RA-DFM is 15.14 mrad with 0.44% center drift

Numerical Analysis of the Forming Mechanism of Exit Burrs in Metal Milling under Ice Boundary Constraint

In metal processing, exit burrs are usually inevitable, which is a huge challenge for high-precision manufacturing. This paper innovatively proposes an ice boundary constraint (IBC) method to actively suppress exit burrs to obtain better workpiece edge quality. Firstly, the formation mechanism of the exits burr is analyzed from the perspective of material flow at the edge of the workpiece, and the principle of the IBC method is explained. Secondly, a finite element model (FEM) is established to analyze the stress distribution and flow at the edge of the workpiece, so as to reveal the suppression mechanism of IBC on the exit burrs. Finally, the feasibility of IBC method and the validity of FEM are verified by the milling experiments. The experimental results show that the IBC method can reduce the exit burr height by 51.4% on average, and FEM can effectively predict the height of the exit burr. The IBC method proposed in this study can provide some reference and guidance for the active suppression of exit burrs in industry

Structural Characterization and Functional Analysis of Mevalonate Kinase from <i>Tribolium castaneum</i> (Red Flour Beetle)

Mevalonate kinase (MevK) is an important enzyme in the mevalonate pathway that catalyzes the phosphorylation of mevalonate into phosphomevalonate and is involved in juvenile hormone biosynthesis. Herein, we present a structure model of MevK from the red flour beetle Tribolium castaneum (TcMevK), which adopts a compact α/β conformation that can be divided into two parts: an N-terminal domain and a C-terminal domain. A narrow, deep cavity accommodating the substrate and cofactor was observed at the junction between the two domains of TcMevK. Computational simulation combined with site-directed mutagenesis and biochemical analyses allowed us to define the binding mode of TcMevK to cofactors and substrates. Moreover, TcMevK showed optimal enzyme activity at pH 8.0 and an optimal temperature of 40 °C for mevalonate as the substrate. The expression profiles and RNA interference of TcMevK indicated its critical role in controlling juvenile hormone biosynthesis, as well as its participation in the production of other terpenoids in T. castaneum. These findings improve our understanding of the structural and biochemical features of insect Mevk and provide a structural basis for the design of MevK inhibitors

Biosynthesis and Characterization of AgNPs–Silk/PVA Film for Potential Packaging Application

Bionanocomposite packaging materials have a bright future for a broad range of applications in the food and biomedical industries. Antimicrobial packaging is one of the bionanocomposite packaging materials. Silver nanoparticle (AgNP) is one of the most attractive antimicrobial agents for its broad spectrum of antimicrobial activity against microorganisms. However, the traditional method of preparing AgNPs-functionalized packaging material is cumbersome and not environmentally friendly. To develop an efficient and convenient biosynthesis method to prepare AgNPs-modified bionanocomposite material for packaging applications, we synthesized AgNPs in situ in a silk fibroin solution via the reduction of Ag+ by the tyrosine residue of fibroin, and then prepared AgNPs–silk/poly(vinyl alcohol) (PVA) composite film by blending with PVA. AgNPs were synthesized evenly on the surface or embedded in the interior of silk/PVA film. The prepared AgNPs–silk/PVA film exhibited excellent mechanical performance and stability, as well as good antibacterial activity against both Gram-negative and Gram-positive bacteria. AgNPs–silk/PVA film offers more choices to be potentially applied in the active packaging field

Dual-targeting inhibition of TNFR1 for alleviating rheumatoid arthritis by a novel composite nucleic acid nanodrug

Selective suppression of tumor necrosis factor (TNF) α-TNF receptor 1 (TNFR1) signaling is a potent solution for rheumatoid arthritis (RA). Herein, novel composite nucleic acid nanodrugs that simultaneously restrain TNF α binding and TNFR1 multimerization were designed to reinforce inhibition of TNF α-TNFR1 signaling for RA therapy. Towards this end, a novel peptide Pep4‐19 that suppresses TNFR1 clustering was extracted from TNFR1. The resulting peptide and a DNA aptamer Apt2‐55, which inhibits TNF α binding, were integrally or separately anchored on DNA tetrahedron (TD) to obtain nanodrugs with different spatial distribution of Apt2‐55 and Pep4‐19 (TD-3A-3P and TD-3(A-P)). Our results showed that Pep4‐19 enhanced the viability of inflammatory L929 cells. Both TD-3A-3P and TD-3(A-P) suppressed caspase 3, reduced cell apoptosis, and inhibited FLS-RA migration. Compared to TD-3(A-P), TD-3A-3P supplied sufficient flexibility for Apt2‐55 and Pep4‐19, and showed better anti-inflammation properties. Furthermore, TD-3A-3P significantly relieved symptoms in collagen-induced arthritis (CIA) mice, and the anti-RA efficacy through intravenous injection was comparable to transdermal administration via microneedles. Overall, the work provides an effective strategy for RA treatment by dual-targeting TNFR1, and demonstrates that microneedles are promising approach to drug administration in the treatment of RA