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161.
162.
An exact method based on Green's equation is used to find the diffusion-controlled faradaic current for certain electrode geometries that incorporate edges and vertices. Thereby the magnitudes of the time-independent current density associated with angled electrode/electrode and electrode/insulator junctions are calculated. As well, the square-root-of-time-dependent currents associated with vertices, receive attention. These terms extend to longer times, the Cottrell formulation appropriate for short times. Though most of the problems solved here have been tackled previously, the novel Green function approach is shown to be straightforward and intuitive. 相似文献
163.
Lamellar crystals of diblock, triblock and four-arm poly(ethylene glycol)-b-poly(ε-caprolactone) (PEG-b-PCL) crystalline-crystalline copolymers were successfully obtained from their solution. Morphology and structure of lamellar crystals of crystalline-crystalline copotymers were investigated using tapping-mode atomic force microscopy (AFM) and selected area electron diffraction (SAED). All of these samples showed the truncated-lozenge multilayer basal shapes with central screw dislocation or central stack, which were all obtained simultaneously from the oil bath. The diffraction pattern of PEG block lamellar crystal is attributed to the (120) diffracting planes and the pattern of PCL block lamellar crystal is attributed to the (1 I0) diffracting planes and (200) diffracting planes according to the SAED results. Four (110) crystal growth planes and two (200) crystal growth planes are discovered for the PCL blocks, but the (120) crystal growth planes of PEG blocks are hided in the figure of AFM. The crystalline structure of the four-arm copolymers (FA) is more disorder and confused than that of the diblock (DI) copolymer and the striated fold surface structures of lamellar crystals of four-arm copolymers (FA) are smoother than these of linear analogues, owing to the confused crystallization of blocks caused by the mutual restriction of blocks and the hindrance of the dendritic cores. In addition, the aspect ratio of FA is greater than that of the others. It is hypothesized that there are two reasons for the change of aspect ratios. First, the (200) diffracting planes of PCL crystals grew slowly compared to their (110) diffracting planes because of difference in the energy barrier. Secondly, edge dislocations on the (200) diffracting planes are also responsible for the variation of the aspect ratio. Consequently, the crystalline defects are augmented by the competing blocks crystallized simultaneously and the hindrance of the dendritic cores. 相似文献
164.
H. R. Schulten Si-En Sun 《International journal of environmental analytical chemistry》2013,93(3-4):247-263
The characteristic behaviour of four groups of commonly used organophosphorus pesticides such as phosphates, phosphorothionates, phosphorothiolates and phosphorodithioates has been investigated by field desorption mass spectrometry. Their spectra show molecular ions of high abundance and characteristic fragmentation patterns. The phosphates and phosphorothionates usually show the α-cleavage with respect to the P-atom with and without proton transfer. In contrast, the phosphorothiolates and phosphorodithioates usually show the β-cleavage from the P-atom. The fragments with the charge retention on the phosphorus moiety were also observed in the field desorption mass spectra, although their abundances were often relatively low. The analyses of standard mixtures as well as some waste water samples indicate that field desorption mass spectrometry is suitable for the identification of organophosphorus pesticides at nanogram level in mixtures and environmental samples without preliminary separation and purification. 相似文献
165.
多层Mini型金属化边PCB作为印制电路板的一种特殊产品,在电子元器件向轻、薄、短、小的发展要求下,而得到广泛应用。然而此类PCB在实际生产过程中仍有一些与普通PCB板制作的不同点。Mini型金属化边,顾名思义,就是指成品尺寸在30 mm×30 mm以下,且板边有小于6 mm长度的电镀金属化边,并且整个PCB的成型尺寸也十分小,没有定位孔,制作难高十分高,需要就包括制前设计、过程控制、成品铣板和成品尺寸测量等问题进行综合考虑。针对多层金属化边Mini型PCB的特征,从设计方法进行了详述,并对其制作技术难点分别提出了解决方案。可帮助读者清晰的了解此类产品的特性和制作方法,以为业者提供一些可以借鉴的行业经验。 相似文献
166.
167.
A novel technique for binarization with stroke preservation of faint characters in degraded documents is proposed. It works in a multi-scale framework with an adaptive–interpolative thresholding technique. Instead of computing a global threshold value, it computes the local threshold values for a small set of grid points by observing the intensity pattern of the pixels lying in the concerned grid cells. Estimated thresholds are used, in turn, to compute the threshold values of all the remaining pixels using a fast-yet-efficient interpolation procedure. To handle noises in degraded images, this grid-based adaptive thresholding is applied in successively reducing scales to obtain the near-optimal binarization as a set of connected components. After a post-processing meant for stroke preservation with these connected components, we get the final output. Exhaustive experimentation and comparison with other existing methods have been successfully carried out with benchmark datasets and also with our own datasets. 相似文献
168.
169.
In this work, the electrochemical behavior of ferrocene (Fc) was investigated by cyclic voltammetry (CV) in room temperature ionic liquids (RTILs) of 1‐ethyl‐3‐methylimidazolium tetrafluoroborate (EMIBF4) on glass carbon (GC), edge plane pyrolytic graphite (EPPG) and multi‐walled carbon nanotube (MWCNTs)‐modified EPPG electrodes, respectively. The results demonstrated that on GC electrode, pairs of well‐defined reversible peaks were observed, while for the electrode of EPPG, the peak potential separation (ΔEp) is obviously larger than the theoretical value of 59 mV, hinting that the electrode of EPPG is distinguished from the commonly used electrode, consistent with the previous proposition that EPPG has many “defects”. To obtain an improved electrochemical response, multi‐walled carbon nanotubes (MWCNTs) were modified on the electrode of EPPG; the increased peak current and promoted peak potential separation not only proved the existence of “defects” in MWCNTs, but also supported that “creating active points” on an electrode is the main contribution of MWCNTs. Initiating the electrochemical research of Fc on the MWCNTs‐modified EPPG electrode in RTILs and verifying the presence of “defects” on both EPPG and MWCNTs using cyclic voltammograms (CVs) of Fc obtained in RTILs of EMIBF4, is the main contribution of this preliminary work. 相似文献
170.
HUANG Hong;YANG Yichuan;WANG Long;ZHENG Fujian;WU Jian 《光子学报》2024,53(1):78-90
In clinical practice, segmentation and quantitative evaluation of target objects in pathological images provide valuable information for histopathological analysis, which is of great significance to auxiliary diagnosis and subsequent treatment. However, due to the dense distribution of cells and great morphological similarities between the cancer cells and normal cells, there are some challenges such as difficulty in feature extraction and unclear segmentation boundaries in the segmentation task of pathological images. At the same time, the traditional image segmentation methods are time-consuming and labor-intensive. They can only extract low level manual features, and the expression ability of deep discrimination features is insufficient, resulting in limited performance of traditional methods. Meanwhile, previous deep learning algorithms still suffer from two significant problems. Firstly, most networks ignore pixels that are difficult to segment, such as the boundaries of targets, which is particularly important for accurate segmentation. In addition, the problem of inconsistent semantic levels between different features are not solved, leading to low training efficiency. To address the above-mentioned problems, an end-to-end histopathological image segmentation network called Boundary Perception Network (BPNet) is proposed for improving the segmentation accuracy of histopathological images. Based on encoder-decoder structure, the encoder performs the convolutional downsampling operation to extract the feature information of the image through the Convolutional Neural Network (CNN). And the encoding process uses the feature encoder based on the EfficientNet-B4 network which is specifically used for pathological image segmentation. The decoder mainly consists of decooding blocks, Boundary Perception Module (BPM) and Adative Shuffle Channel Attention Moudule (ASCAM). In detail, the decoding block performs deconvolution operation to complete the decoding process of the feature information. Then, the BPM in the decoder stage aims to strengthen the ability of mining for difficult segmentation regions, so that the network focuses on the higher uncertainty as well as more complex edge regions, achieving feature complementarity and precision prediction results. For implementation, the BPM extracts the edge from the decoder output of each layer, and superimposes the edge information onto the encoded feature to strengthen the boundary feature information extracted from pathological images, outputting the enhanced edge perception feature map. Subsequently, the ASCAM is an improved chanel attention moudule which is used to make up the semantic gap between different levels of features, extrated by encoder, decoder and BPM, so as to further strengthens the feature understanding ability of the BPNet. This module exploits adaptive kernel size one-dimensional convolusion to capture the interactive information of local channels, at the same time ensures the efficiency and effectiveness of the training process. The obtained channel attention coefficient is multiplied by the module input feature layer to obtain the fusion feature, helping effectively learn the channel interaction information between features to improve the feature representation ability. Furthermore, a joint loss function based on structure and boundary is designed to optimize the targeting and detail processing capabilities of this method, achieving the better segmentation result of pathological images. Experiments are carried out on the Gland segmentation (GlaS) and MoNuSeg dataset, respectively. Both of the two datasets are devided into 4∶1 for training and validation. At the same time, in order to make up for the overfitting caused by the lack of training data, two kinds of online data enhancement methods of horizontal flipping and vertical flipping were carried out on the training set data in the experiment. And the four evaluation index, the Dice coefficient score, Intersection Over Union (IoU), Accuracy (ACC) and Precision (PRE), are used to evaluate the performance of this method propsed in this paper. The Dice coefficient score of the proposed method is 92.21% and 81.18%, the IoU is 85.55% and 68.34%, the ACC is 92.14% and 92.50%, the PRE is 92.07% and 75.46% on the GlaS and MoNuSeg datasets, respectively. Compared with the previous classical methods, such as U-Net, UNet++, MultiResUNet, TransUNet, UCTransNet and so on, the BPNet proposed gets the best segmentation result, especially retains more details in the segmentation boundary. Moreover, ablation experiments are carried out on the same two datasets for indicating the impacts of BPM and ASCAM. The results shows that the proposed BPM significantly optimizes the segmentation effect of the network for the edge, as well as the ASCAM makes up the semantic gap between features at different levels and further strengthens the feature understanding ability of the network. In conclusion, the BPNet proposed in this paper exploits BPM to generate edge enhancement feature maps, and uses ASCAM to seize crucial features. Finally, a joint loss function is used to capture the information of features at different levels in the output layer to achieve optimal segmentation performance. The experimental results have demonstrated that the effectiveness of each part of proposed method in the segmentation task of pathological images. 相似文献