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101.
Mutated COX-2 has become the new molecular marker of aspirin resistance. However, there is still a technical ‘bottleneck’ for direct and sensitive detection of circulating COX-2 mutant gene. In this work, we reported a simple and ultrasensitive electrochemical method for COX-2–765G/C (rs20417) detection for the first time. Polyallylamine (PAA) functionalised Pt nanostructures with long-spined sea urchin-like morphology (Pt-LSSUs@PAA) was synthesised by a simple chemical method for the construction of nano-sensing interface. Ru(NH3)63+ is used as a primary electron acceptor that is electrostatically attracted to peptide nucleic acid modified electrodes and Fe(CN)63? is introduced into the redox system as secondary electron acceptor to regenerate Ru3+ after electrochemical reduction for multiple redox cycles. Different pulse voltammetry was applied to record the electrochemical signals. Under optimal conditions, the DNA sensors showed a wide linear relationship, from 10?fM to 1?nM, with detection limits of 3.3?fM (S/N?=?3). This study will provide the basis for the precise use of aspirin, and it has important guiding value for individual drug testing of cardiovascular disease.  相似文献   
102.
针对经典的基于卷积神经网络的单幅图像超分辨率重建方法网络较浅、提取的特征少、重建图像模糊等问题,提出了一种改进的卷积神经网络的单幅图像超分辨率重建方法,设计了由密集残差网络和反卷积网络组成的新型深度卷积神经网络结构。原始低分辨率图像输入网络,利用密集残差学习网络获取更丰富的有效特征并加快特征梯度流动,其次通过反卷积层将图像特征上采样到目标图像大小,再利用密集残差学习高维特征,最后融合不同卷积核提取的特征得到最终的重建图像。在Set5和Set14数据集上进行了实验,并和Bicubic、K-SVD、SelfEx、SRCNN等经典重建方法进行了对比,重建出的图像在整体清晰度和边缘锐度方面更好,另外峰值信噪比(PSNR)平均分别提高了2.69?dB、1.68?dB、0.74?dB和0.61?dB。实验结果表明,该方法能够获取更丰富的细节信息,得到更好的视觉效果,达到了图像超分辨率的增强任务。  相似文献   
103.
In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.  相似文献   
104.
The rapid development of the construction industry in China has introduced unprecedented quality-related problems in the country’s building industry. In response to this issue, the government has established various complaint channels to report quality problems. Therefore, building quality complaints (BQCs) need to be classified and solved by respective agencies or departments rapidly for avoiding adverse impact on the safety, health, and well-being of people. However, the current process of classifying BQCs is labor intensive, time consuming, and error prone. An automatic complaint classification is required to improve the effectiveness and efficiency of complaint handling, but studies on this issue are limited. Prevailing text classification research in construction has focused on utilizing conventional shallow machine learning. By contrast, this study explores a novel convolutional neural network (CNN)-based approach that incorporates a deep-learning method to automatically classify the short texts contained within BQCs. The presented approach enables capturing the semantic features in BQC texts and automatic classification of the BQCs into predefined categories. After the model optimization, tests are conducted to examine the practical application of the text classification approach compared with Bayes-based and support vector machine classifiers. Results indicate that the developed CNN-based approach performs well in the Chinese BQC classification with limited manual intervention and few complicated feature engineering.  相似文献   
105.
Classification process plays a key role in diagnosing brain tumors. Earlier research works are intended for identifying brain tumors using different classification techniques. However, the False Alarm Rates (FARs) of existing classification techniques are high. To improve the early-stage brain tumor diagnosis via classification the Weighted Correlation Feature Selection Based Iterative Bayesian Multivariate Deep Neural Learning (WCFS-IBMDNL) technique is proposed in this work. The WCFS-IBMDNL algorithm considers medical dataset for classifying the brain tumor diagnosis at an early stage. At first, the WCFS-IBMDNL technique performs Weighted Correlation-Based Feature Selection (WC-FS) by selecting subsets of medical features that are relevant for classification of brain tumors. After completing the feature selection process, the WCFS-IBMDNL technique uses Iterative Bayesian Multivariate Deep Neural Network (IBMDNN) classifier for reducing the misclassification error rate of brain tumor identification. The WCFS-IBMDNL technique was evaluated in JAVA language using Disease Diagnosis Rate (DDR), Disease Diagnosis Time (DDT), and FAR parameter through the epileptic seizure recognition dataset.  相似文献   
106.
口语理解是对话系统重要的功能模块,语义槽填充和意图识别是面向任务口语理解的两个关键子任务。近年来,联合识别方法已经成为解决口语理解中语义槽填充和意图识别任务的主流方法,介绍两个任务由独立建模到联合建模的方法,重点介绍基于深度神经网络的语义槽填充和意图识别联合建模方法,并总结了目前存在的问题以及未来的发展趋势。  相似文献   
107.
Glass fibre is a random network structure composed of [SiO4] tetrahedra. The structure contains a large number of defects, which act as crack initiation points. Under tensile stress, cracks undergo crack initiation, stable propagation, failure propagation, and fracture, and the stress that begins after unstable propagation is called the critical fracture stress. When the stress is less than the critical value, the crack is subject to the force of chemical bonds during the crack propagation process, and crack arrest occurs. When the stress is greater than the critical value, the glass fibre will undergo destructive fracture. In this paper, long-term tensile tests were carried out on glass fibre and a glass fibre composite under different constant tensile stress conditions. The fracture times of the glass fibre and glass fibre composite under different tensile stresses were obtained, the critical fracture stress of glass fibre was inferred, and the fracture mechanism was explained.  相似文献   
108.
In this study, a novel micro porous honeycomb structured Crg-GG-IPN material was incepted to be applicable as scaffold and accomplished. The hydrophilicity was confirmed by FT-IR and OCA. Amorphous nature and micro-rough surface were confirmed by XRD and AFM. Void fraction was 0.61?±?0.04. Void space, hemocompatibility and platelet adhesion were captured by SEM. Degradability of the material was confirmed by in-vitro degradation study. Incision method using mice model was a clear evidence for cell attachment and non-toxicity and was confirmed from hematology and histopathology. Thus, it appears that Crg-GG scaffolds can be useful as wound healing material for clinical applications.  相似文献   
109.
针对现实网络中诸如侧信道攻击、HID 攻击等传统的物理攻击,物理隔离被认为是一种较为彻底的抵御网络攻击的安全防护手段。2018 年,业界首次提出了一种物理隔离环境下的 Wi-Fi 隐蔽信道方法——Ghost Tunnel,即在Wi-Fi尚未连接的状态下,无线AP可成功将数据传给发起连接请求的计算机。提出了一种基于Ghost Tunnel方法的攻击框架—— GreyFan,利用该攻击框架攻击者可以对未连接Wi-Fi的用户实施无感知攻击,如文件隐蔽传输、任意代码执行等,并分析了相应的防御技术。  相似文献   
110.
Fault isolation is known to be a challenging problem in machinery troubleshooting. It is not only because the isolation of multiple faults contains considerable number of uncertainties due to the strong correlation and coupling between different faults, but often massive prior knowledge is needed as well. This paper presents a Bayesian network-based approach for fault isolation in the presence of the uncertainties. Various faults and symptoms are parameterized using state variables, or the so-called nodes in Bayesian networks (BNs). Probabilistically causality between a fault and a symptom and its quantization are described respectively by a directed edge and conditional probability. To reduce the qualitative and quantitative knowledge needed, particular considerations are given to the simplification of Bayesian networks structures and conditional probability expressions using rough sets and noisy-OR/MAX model, respectively. By adopting the simplified approach, symptoms under multiple-fault are decoupled into the ones under every single fault, while the quantity of the conditional probabilities is simplified into the linear form of the faults quantity. Prior knowledge needed in Bayesian network-based diagnostic model is reduced significantly, which decreases the complexity in establishing and applying this diagnosis model. The computational efficiency is improved accordingly in the simplified BN model, after eliminating the redundant symptoms. The fault isolation methodology is illustrated through an example of diesel engine fuel injection system to verify the developed model.  相似文献   
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