Establishing Ohmic Contact of a Radial Compressed CNT Bundle with High Work Function Metal.

Establishing low-resistance ohmic contact is critical for developing electronic devices based on traditional silicon and new low-dimensional materials. Due to unprecedented electronic and mechanical properties, the one-dimensional carbon nanotubes (CNTs) have been used as source/drain, gate, or tunnel to fabricate transistors. However, the mechanism causing low-resistance ohmic contact is not clear yet. Here, the hybrid atomic force microscopy-scanning electron microscopy (AFM-SEM) instrument was developed to establish lower-resistance ohmic contact between a radial compressed deformed multiwalled CNT bundle and high work function metal (platinum and gold). The radial compression structure under strong van der Waals attraction was in situ characterized through the SEM image to obtain the diameter and width and through AFM to get height and to perform nanoindentation, indicating that Pt has the smaller radial compression deformation. Molecular dynamics simulations exhibit that compared to Pt, a wider ribbon-like graphene layer formed when the radial compressed CNTs contacted with Au. The bond forming and electron orbital overlapping between C atoms of deformed CNTs and the high work function metal atom is beneficial for good electrical contact.

Research on the Influence of Geometric Structure Parameters of Eddy Current Testing Probe on Sensor Resolution.

To study the influence of the geometric structure of the probe coil on the electromagnetic characteristics of the eddy current probe in the process of eddy current testing, based on the principle of eddy current testing, different probe coil models were established using finite element software. These geometric structure parameters include the difference between the inner and outer radius, thickness, and equivalent radius. The magnetic field distribution around the probe is simulated and analyzed under different parameters, and the detection performance of the probe is judged in combination with the change rate of the magnetic field around the probe coil. The simulation results show that at a closer position, increasing the difference between the inner and outer radii, reducing the thickness, and reducing the equivalent radius are beneficial to improve the resolution of the probe coil. At a far position, reducing the difference between the inner and outer radii, increasing the thickness, and reducing the equivalent radius are beneficial to improve the resolution of the probe coil. At the same time, the accuracy of the simulation data is verified by comparing the theoretical values with the simulated values under different conditions. Therefore, the obtained conclusions can provide a reference and basis for the optimal design of the probe structure.

Effect of photoperiod on development and demographic parameters of Neoseiulus barkeri (Acari: Phytoseiidae) fed on Tyrophagus putrescentiae (Acari: Acaridae).

Effects of five photoperiods (Light:Dark = 4:20, 8:16; 12:12, 16:8, 20:4) on the development, survival and reproduction of Neoseiulus barkeri Hughes fed on storage mite Tyrophagus putrescentiae (Schrank) were examined under laboratory conditions at 85 % relative humidity and 24 °C. Development time of almost all immature stages in N. barkeri was the shortest (5.43 ± 0.12 days) under 12 h of daylight. Total duration of immature stages was as high as 8.55 ± 0.16 days during the longest photoperiod. Photoperiod had no effect on hatching rate, but did affect survival of larvae, protonymphs and deutonymphs. Total survivorship ranged from 20 (4:20) to 60 % (12:12). Under 12 h daylight, female adults had the shortest pre- and post-oviposition period, longest oviposition period and longevity, largest total number of eggs (15.95) and and highest daily egg production (1.43) per female. Under 12 h light, N. barkeri experienced its highest net reproductive rate (R 0  = 11.791), intrinsic rate of increase (r m  = 0.180), and finite rate of increase (λ = 1.197), and lowest mean generation time (t = 13.71 days) and population doubling time (DT = 3.86 days). All demographic parameters displayed a parabolic relationship with photoperiod. The results of the present study indicated that the photoperiod of 12:12 is optimal for the development and reproduction of N. barkeri fed on T. putrescentiae, and that N. barkeri may serve most efficiently as a biological control agent under this regime.

Enhancing deep neural network training efficiency and performance through linear prediction.

Deep neural networks have achieved remarkable success in various fields. However, training an effective deep neural network still poses challenges. This paper aims to propose a method to optimize the training effectiveness of deep neural networks, with the goal of improving their performance. Firstly, based on the observation that parameters (weights and bias) of deep neural network change in certain rules during training process, the potential of parameters prediction for improving training efficiency is discovered. Secondly, the potential of parameters prediction to improve the performance of deep neural network by noise injection introduced by prediction errors is revealed. And then, considering the limitations comprehensively, a deep neural network Parameters Linear Prediction method is exploit. Finally, performance and hyperparameter sensitivity validations are carried out on some representative backbones. Experimental results show that by employing proposed Parameters Linear Prediction method, as opposed to SGD, has led to an approximate 1% increase in accuracy for optimal model, along with a reduction of about 0.01 in top-1/top-5 error. Moreover, it also exhibits stable performance under various hyperparameter settings, shown the effectiveness of the proposed method and validated its capacity in enhancing network's training efficiency and performance.

Radiomic Analysis of Contrast-Enhanced CT Predicts Glypican 3-Positive Hepatocellular Carcinoma.

BACKGROUND: The Glypican 3 (GPC3)-positive expression in Hepatocellular Carcinoma (HCC) is associated with a worse prognosis. Moreover, GPC3 has emerged as an immunotherapeutic target in advanced unresectable HCC systemic therapy. It is significant to diagnose GPC3-positive HCCs before therapy. Regarding imaging diagnosis of HCC, dynamic contrast-enhanced CT is more common than MRI in many regions. OBJECTIVE: The aim of this study was to construct and validate a radiomics model based on contrast-enhanced CT to predict the GPC3 expression in hepatocellular carcinoma. METHODS: This retrospective study included 141 (training cohort: n = 100; validation cohort: n = 41) pathologically confirmed HCC patients. Radiomics features were extracted from the Artery Phase (AP) images of contrast-enhanced CT. Logistic regression with the Least Absolute Shrinkage and Selection Operator (LASSO) regularization was used to select features to construct radiomics score (Rad-score). A final combined model, including the Rad-score of the selected features and clinical risk factors, was established. Receiver Operating Characteristic (ROC) curve analysis, Delong test, and Decision Curve Analysis (DCA) were used to assess the predictive performance of the clinical and radiomics models. RESULTS: 5 features were selected to construct the AP radiomics model of contrast-enhanced CT. The radiomics model of AP from contrast-enhanced CT was superior to the clinical model of AFP in training cohorts (P < 0.001), but not superior to the clinical model in validation cohorts (P = 0.151). The combined model (AUC = 0.867 vs. 0.895), including AP Rad-score and serum Alpha-Fetoprotein (AFP) levels, improved the predictive performance more than the AFP model (AUC = 0.651 vs. 0.718) in the training and validation cohorts. The combined model, with a higher decision curve indicating more net benefit, exhibited a better predictive performance than the AP radiomics model. DCA revealed that at a range threshold probability approximately above 60%, the combined model added more net benefit compared to the AP radiomics model of contrastenhanced CT. CONCLUSION: A combined model including AP Rad-score and serum AFP levels based on contrast-enhanced CT could preoperatively predict GPC3-positive expression in HCC.

Fault Diagnosis of Planetary Gearbox Based on Dynamic Simulation and Partial Transfer Learning.

To address the problem of insufficient real-world data on planetary gearboxes, which makes it difficult to diagnose faults using deep learning methods, it is possible to obtain sufficient simulation fault data through dynamic simulation models and then reduce the difference between simulation data and real data using transfer learning methods, thereby applying diagnostic knowledge from simulation data to real planetary gearboxes. However, the label space of real data may be a subset of the label space of simulation data. In this case, existing transfer learning methods are susceptible to interference from outlier label spaces in simulation data, resulting in mismatching. To address this issue, this paper introduces multiple domain classifiers and a weighted learning scheme on the basis of existing domain adversarial transfer learning methods to evaluate the transferability of simulation data and adaptively measure their contribution to label predictor and domain classifiers, filter the interference of unrelated categories of simulation data, and achieve accurate matching of real data. Finally, partial transfer experiments are conducted to verify the effectiveness of the proposed method, and the experimental results show that the diagnostic accuracy of this method is higher than existing transfer learning methods.

Research on electromagnetic characteristics of traction motor rotary shafts with variable parameter defects based on finite element method.

In view of the breakage of the rotary shaft of the traction motor of the locomotive, in order to ensure the reliability and safety of the equipment, this paper studies the magnetic field containing rich information in the space around the rotary shaft, so that the crack defect can be detected and the crack size can be judged in time. In order to study the influence of defect geometric parameters (width, depth and hidden depth) on the spatial magnetic field distribution around the defect in the process of eddy current testing of metal shafts, based on the principle of eddy current testing, a metal rotary shaft detection model with different defect parameters was established by COMSOL software for simulation. The horizontal magnetic induction intensity, vertical magnetic induction intensity and their respective phases are used to analyze the magnetic field distribution around the defect under different parameters. The results show that the magnetic field related parameters can qualitatively and quantitatively evaluate the crack width, qualitatively evaluate the relative size of the crack depth, and qualitatively judge whether there are hidden cracks.

Research on fault diagnosis method of planetary gearbox based on dynamic simulation and deep transfer learning.

To address the issue of not having enough labeled fault data for planetary gearboxes in actual production, this research develops a simulation data-driven deep transfer learning fault diagnosis method that applies fault diagnosis knowledge from a dynamic simulation model to an actual planetary gearbox. Massive amounts of different fault simulation data are collected by creating a dynamic simulation model of a planetary gearbox. A fresh deep transfer learning network model is built by fusing one-dimensional convolutional neural networks, attention mechanisms, and domain adaptation methods. The network model is used to learn domain invariant features from simulated data, thereby enabling fault diagnosis on real data. The fault diagnosis experiment is verified by using the Drivetrain Diagnostics Simulator test bench. The validity of the proposed means is evaluated by comparing the diagnostic accuracy of various means on various diagnostic tasks.

Investigation of the bio-stimulation of children's reading interest by chromatic pattern visual evoked potential.

PURPOSE: The characteristics of children's reading interest, stimulated by the visual evoked potentials of colour graphics in children's picture books, were tested to explore their normal reference value. The characteristics of chromatic pattern visual evoked potential (CP-VEP) can be harnessed by our methodology and may be applied to the visual screening of children in clinical ophthalmology. METHODS: The PR-650 spectral colour metre can strictly control factors, such as brightness and colour retention, based on colour contrast. This is performed in order to reduce the brightness contrast method. In our paper, we set up three kinds of visual stimulation conditions and performed CP-VEP inspections of the eye, based on 64 cases (128 eyes) of normal children (32 males and 32 females). Using CP-VEP detection, the latency and amplitude of the P100 wave were recorded and the waveforms of each group, under different spectral modes were compared. Art therapy combined with children's colour physiology and psychology will be more skilfully practiced in clinical practice. RESULTS: There was no significant difference in the amplitude and peak time of visual evoked potential (VEP) waveforms between the left and right eyes of the children using the three stimuli, indicating that the visual function and visual conduction pathway of children can vary. There was no significant difference in the latency and amplitude of the NPN complex wave. Note that the P1 wave of the right and left eyes of normal children is not statistically different (P > 0.05). We also found that there is insignificant difference in the visual impact of the colours for both male and female children in terms of reading interest, and red is a more stimulating colour for both sexes. CONCLUSION: Our study can provide normal reference value and methodological reference for clinical visual acuity detection in children. Combined with the visual characteristics of children, this paper selects the visual impact created by the colour of picture books and combines it with medical treatment. Make the whole test cover the scope of ophthalmology clinical more comprehensive.

Electrical Conductivity of Multiwall Carbon Nanotube Bundles Contacting with Metal Electrodes by Nano Manipulators inside SEM.

Determining the metallicity and semiconductivity of a multi-walled carbon nanotube (MWCNT) bundle plays a particularly vital role in its interconnection with the metal electrode of an integrated circuit. In this paper, an effective method is proposed to determine the electrical transport properties of an MWCNT bundle using a current-voltage characteristic curve during its electrical breakdown. We established the reliable electrical nanoscale contact between the MWCNT bundle and metal electrode using a robotic manipulation system under scanning electron microscope (SEM) vacuum conditions. The experimental results show that the current-voltage curve appears as saw-tooth-like current changes including up and down steps, which signify the conductance and breakdown of carbon shells in the MWCNT bundle, respectively. Additionally, the power law nonlinear behavior of the current-voltage curve indicates that the MWCNT bundle is semiconducting. The molecular dynamics simulation explains that the electron transport between the inner carbon shells, between the outermost carbon shells and gold metal electrode and between the outermost carbons shells of two adjacent individual three-walled carbon nanotubes (TWCNTs) is through their radial deformation. Density functional theory (DFT) calculations elucidate the electron transport mechanism between the gold surface and double-wall carbon nanotube (DWCNT) and between the inner and outermost carbon shells of DWCNT using the charge density difference, electrostatic potential and partial density of states.