The Verification of Rail Thermal Stress Measurement System

Continuous Welded Rail (CWR) is widely used in modern railways. With the absence of the expansion joints, CWR cannot expansion freely when the temperature changes, which could cause buckling in hot weather or breakage in cold weather. Therefore, rail thermal stress measuring system plays an important role in the safe operation of railways. This paper designed a thermal stress measurement system based on the acoustoelastic effect of the ultrasonic guided wave. A large-scale rail testbed was built to simulate the thermal stress in the rail track, and to establish the relationship of time-delay of guided wave and thermal stress. After laboratory testing, the system was installed in several railway lines in China for field tests. The results showed that the system was stable and accurate in stress measurement. The performance and potentials of the system were discussed

Network Binarization via Contrastive Learning

Neural network binarization accelerates deep models by quantizing their weights and activations into 1-bit. However, there is still a huge performance gap between Binary Neural Networks (BNNs) and their full-precision (FP) counterparts. As the quantization error caused by weights binarization has been reduced in earlier works, the activations binarization becomes the major obstacle for further improvement of the accuracy. BNN characterises a unique and interesting structure, where the binary and latent FP activations exist in the same forward pass (i.e., $\text{Binarize}(\mathbf{a}_F) = \mathbf{a}_B$). To mitigate the information degradation caused by the binarization operation from FP to binary activations, we establish a novel contrastive learning framework while training BNNs through the lens of Mutual Information (MI) maximization. MI is introduced as the metric to measure the information shared between binary and FP activations, which assists binarization with contrastive learning. Specifically, the representation ability of the BNNs is greatly strengthened via pulling the positive pairs with binary and FP activations from the same input samples, as well as pushing negative pairs from different samples (the number of negative pairs can be exponentially large). This benefits the downstream tasks, not only classification but also segmentation and depth estimation, etc. The experimental results show that our method can be implemented as a pile-up module on existing state-of-the-art binarization methods and can remarkably improve the performance over them on CIFAR-10/100 and ImageNet, in addition to the great generalization ability on NYUD-v2.Comment: Accepted to ECCV 202

Free-standing kinked nanowire transistor probes for targeted intracellular recording in three dimensions

Recording intracellular bioelectrical signals is central to understanding the fundamental behaviour of cells and cell-networks in, for example, neural and cardiac systems1–4. The standard tool for intracellular recording, the patch-clamp micropipette5 is widely applied, yet remains limited in terms of reducing the tip size, the ability to reuse the pipette5, and ion exchange with the cytoplasm6. Recent efforts have been directed towards developing new chip-based tools1–4,7–13, including micro-to-nanoscale metal pillars7–9, transistor-based kinked nanowire10,11 and nanotube devices12,13. These nanoscale tools are interesting with respect to chip-based multiplexing, but, to date, preclude targeted recording from specific cell regions and/or subcellular structures. Here we overcome this limitation in a general manner by fabricating free-standing probes where a kinked silicon nanowire with encoded field-effect transistor detector serves as the tip end. These probes can be manipulated in three dimensions (3D) within a standard microscope to target specific cells/cell regions, and record stable full-amplitude intracellular action potentials from different targeted cells without the need to clean or change the tip. Simultaneous measurements from the same cell made with free-standing nanowire and patch-clamp probes show that the same action potential amplitude and temporal properties are recorded without corrections to the raw nanowire signal. In addition, we demonstrate real-time monitoring of changes in the action potential as different ion-channel blockers are applied to cells, and multiplexed recording from cells by independent manipulation of two free-standing nanowire probes

Lipschitz Continuity Retained Binary Neural Network

Relying on the premise that the performance of a binary neural network can be largely restored with eliminated quantization error between full-precision weight vectors and their corresponding binary vectors, existing works of network binarization frequently adopt the idea of model robustness to reach the aforementioned objective. However, robustness remains to be an ill-defined concept without solid theoretical support. In this work, we introduce the Lipschitz continuity, a well-defined functional property, as the rigorous criteria to define the model robustness for BNN. We then propose to retain the Lipschitz continuity as a regularization term to improve the model robustness. Particularly, while the popular Lipschitz-involved regularization methods often collapse in BNN due to its extreme sparsity, we design the Retention Matrices to approximate spectral norms of the targeted weight matrices, which can be deployed as the approximation for the Lipschitz constant of BNNs without the exact Lipschitz constant computation (NP-hard). Our experiments prove that our BNN-specific regularization method can effectively strengthen the robustness of BNN (testified on ImageNet-C), achieving state-of-the-art performance on CIFAR and ImageNet.Comment: Paper accepted to ECCV 202

Design and Synthesis of Diverse Functional Kinked Nanowire Structures for Nanoelectronic Bioprobes

Functional kinked nanowires (KNWs) represent a new class of nanowire building blocks, in which functional devices, for example, nanoscale field-effect transistors (nanoFETs), are encoded in geometrically controlled nanowire superstructures during synthesis. The bottom-up control of both structure and function of KNWs enables construction of spatially isolated point-like nanoelectronic probes that are especially useful for monitoring biological systems where finely tuned feature size and structure are highly desired. Here we present three new types of functional KNWs including (1) the zero-degree KNW structures with two parallel heavily doped arms of U-shaped structures with a nanoFET at the tip of the “U”, (2) series multiplexed functional KNW integrating multi-nanoFETs along the arm and at the tips of V-shaped structures, and (3) parallel multiplexed KNWs integrating nanoFETs at the two tips of W-shaped structures. First, U-shaped KNWs were synthesized with separations as small as 650 nm between the parallel arms and used to fabricate three-dimensional nanoFET probes at least 3 times smaller than previous V-shaped designs. In addition, multiple nanoFETs were encoded during synthesis in one of the arms/tip of V-shaped and distinct arms/tips of W-shaped KNWs. These new multiplexed KNW structures were structurally verified by optical and electron microscopy of dopant-selective etched samples and electrically characterized using scanning gate microscopy and transport measurements. The facile design and bottom-up synthesis of these diverse functional KNWs provides a growing toolbox of building blocks for fabricating highly compact and multiplexed three-dimensional nanoprobes for applications in life sciences, including intracellular and deep tissue/cell recordings.Chemistry and Chemical Biolog

Fast Ionic Diffusion-Enabled Nanoflake Electrode by Spontaneous Electrochemical Pre-Intercalation for High-Performance Supercapacitor

Layered intercalation compounds Na$_{x}$MnO$_{2}$ (x = 0.7 and 0.91) nanoflakes have been prepared directly through wet electrochemical process with Na$^{+}$ ions intercalated into MnO$_{2}$ interlayers spontaneously. The as-prepared Na$_{x}$MnO$_{2}$ nanoflake based supercapacitors exhibit faster ionic diffusion with enhanced redox peaks, tenfold-higher energy densities up to 110 Wh·kg$^{-1}$ and higher capacitances over 1000 F·g$^{-1}$ in aqueous sodium system compared with traditional MnO$_{2}$ supercapacitors. Due to the free-standing electrode structure and suitable crystal structure, Na$_{x}$MnO$_{2}$ nanoflake electrodes also maintain outstanding electrochemical stability with capacitance retention up to 99.9% after 1000 cycles. Besides, pre-intercalation effect is further studied to explain this enhanced electrochemical performance. This study indicates that the suitable pre-intercalation is effective to improve the diffusion of electrolyte cations and other electrochemical performance for layered oxides, and suggests that the as-obtained nanoflakes are promising materials to achieve the hybridization of both high energy and power density for advanced supercapacitors.Chemistry and Chemical Biolog