Analytical quality-by-design approach for sample treatment of BSA-containing solutions

The sample preparation of samples conlaining bovine serum albumin（BSA）,e.g..as used in transdermal Franz diffusion cell（FDC） solutions,was evaluated using an analytical qualily-by-design（QbD）approach.Traditional precipitation of BSA by adding an equal volume of organic solvent,often successfully used with conventional HPLC-PDA,was found insufficiently robust when novel fused-core HPLC and/or UPLC-MS methods were used.In this study,three factors（acetonitrile（%）.formic acid（%） and boiling time（min）） were included in the experimental design to determine an optimal and more suitable sample treatment of BSAcontaining FDC solutions.Using a QbD and Derringer desirability（D） approach,combining BSA loss,dilution factor and variability,we constructed an optimal working space with the edge of failure defined as D〈0.9.The design space is modelled and is confirmed to have an ACN range of 83 ± 3% and FA content of 1 ±0.25%.

Some results of modeling D-D seismogenic pattern by the fracture model experiment of large-scale rock samples(I)

sing the natural limestone samples taken from the field with dimension of 500 mm×500 mm×1 000 mm, the D-D (dilatancy-diffusion) seismogeny pattern was modeled under the condition of water injection, which observes the time-space evolutionary features about the relative physics fields of the loaded samples from deformation, formation of microcracks to the occurrence of main rupture. The results of observed apparent resistivity show: ① The process of the deformation from microcrack to main rupture on the loaded rock sample could be characterized by the precursory spatial-temporal changes in the observation of apparent resistivity; ② The precursory temporal changes of observation in apparent resistivity could be divided into several stages, and its spatial distribution shows the difference in different parts of the rock sample; ③ Before the main rupture of the rock sample the obvious ″tendency anomaly′ and ′short-term anomaly″ were observed, and some of them could be likely considered as the ″impending earthquake ″anomaly precursor of apparent resistivity. The changes and distribution features of apparent resistivity show that they are intrinsically related to the dilatancy phenomenon of the loaded rock sample. Finally, this paper discusses the mechanism of resistivity change of loaded rock sample theoretically.

Prediction to the Efficiency of Soft Clay Sample Preparation with Vacuum Loading

Vacuum loading has been examined as a way of preparing uniformly consolidated soft clay samples. The facility and loading procedure are described in this paper. An analytical solution to the three dimensional consolidation equation is derived for estimating the degree of consolidation of the soil sample with vacuum loading. The given example shows that the predicted degree of consolidation of a soft clay bulk with vacuum loading is close to that measured in the consolidation process.

基于CD-BSMOTE的D-S证据融合变压器故障诊断

针对变压器油中溶解气体数据集不均衡特性对故障诊断结果的影响,提出一种基于清除临界点改进的边界合成少数类过采样算法均衡数据集和Pearson冲突距离改进D-S证据融合的变压器故障诊断模型。首先,对少数类样本进行均衡化处理,根据K-means聚类结果清除处于临界位置的样本;其次,搭建梯度提升树、随机森林、BP神经网络的故障诊断模型,实现变压器故障初步诊断;接着引入Pearson冲突距离改进D-S证据融合模型,实现诊断结果的融合决策;最后,经实际算例分析,诊断精确率达到92.65%。结果表明,所建模型能有效解决数据不平衡对诊断结果的影响,提高故障诊断精度。

Determination of the full-field stress and displacement using photoelasticity and sampling moirémethod in a 3D-printed model

The quantitative characterization of the full-field stress and displacement is significant for analyzing the failure and instability of engineering materials.Various optical measurement techniques such as photoelasticity,moiréand digital image correlation methods have been developed to achieve this goal.However,these methods are difficult to incorporate to determine the stress and displacement fields simultaneously because the tested models must contain particles and grating for displacement measurement;however,these elements will disturb the light passing through the tested models using photoelasticity.In this study,by combining photoelasticity and the sampling moirémethod,we developed a method to determine the stress and displacement fields simultaneously in a three-dimensional(3D)-printed photoelastic model with orthogonal grating.Then,the full-field stress was determined by analyzing 10 photoelastic patterns,and the displacement fields were calculated using the sampling moirémethod.The results indicate that the developed method can simultaneously determine the stress and displacement fields.

Monocular 3D object detection with Pseudo-LiDAR confidence sampling and hierarchical geometric feature extraction in 6G network

The high bandwidth and low latency of 6G network technology enable the successful application of monocular 3D object detection on vehicle platforms.Monocular 3D-object-detection-based Pseudo-LiDAR is a low-cost,lowpower solution compared to LiDAR solutions in the field of autonomous driving.However,this technique has some problems,i.e.,(1)the poor quality of generated Pseudo-LiDAR point clouds resulting from the nonlinear error distribution of monocular depth estimation and(2)the weak representation capability of point cloud features due to the neglected global geometric structure features of point clouds existing in LiDAR-based 3D detection networks.Therefore,we proposed a Pseudo-LiDAR confidence sampling strategy and a hierarchical geometric feature extraction module for monocular 3D object detection.We first designed a point cloud confidence sampling strategy based on a 3D Gaussian distribution to assign small confidence to the points with great error in depth estimation and filter them out according to the confidence.Then,we present a hierarchical geometric feature extraction module by aggregating the local neighborhood features and a dual transformer to capture the global geometric features in the point cloud.Finally,our detection framework is based on Point-Voxel-RCNN(PV-RCNN)with high-quality Pseudo-LiDAR and enriched geometric features as input.From the experimental results,our method achieves satisfactory results in monocular 3D object detection.

Influence of sampling on face measuring system based on composite structured light

Human face can be rebuilt to a three-dimensional (3 D) digital profile based on an optical 3D sensing system named Composite Fourier-Transform Profilometry (CFTP) where a composite structured light will be used. To study the sampling effect during the digitization process in practical CFTP, the pectinate function and convolution theorem were introduced to discuss the potential phase errors caused by sampling the composite pattern along two orthogonal directions. The selecting criterions of sampling frequencies are derived and the results indicate that to avoid spectral aliasing, the sampling frequency along the phrase variation direction must be at least four times as the baseband and along the orthogonal direction it must be at least three times as the larger frequency of the two carrier frequencies. The practical experiment of a model face reconstruction verified the theories.

SGT-Net: A Transformer-Based Stratified Graph Convolutional Network for 3D Point Cloud Semantic Segmentation

In recent years,semantic segmentation on 3D point cloud data has attracted much attention.Unlike 2D images where pixels distribute regularly in the image domain,3D point clouds in non-Euclidean space are irregular and inherently sparse.Therefore,it is very difficult to extract long-range contexts and effectively aggregate local features for semantic segmentation in 3D point cloud space.Most current methods either focus on local feature aggregation or long-range context dependency,but fail to directly establish a global-local feature extractor to complete the point cloud semantic segmentation tasks.In this paper,we propose a Transformer-based stratified graph convolutional network(SGT-Net),which enlarges the effective receptive field and builds direct long-range dependency.Specifically,we first propose a novel dense-sparse sampling strategy that provides dense local vertices and sparse long-distance vertices for subsequent graph convolutional network(GCN).Secondly,we propose a multi-key self-attention mechanism based on the Transformer to further weight augmentation for crucial neighboring relationships and enlarge the effective receptive field.In addition,to further improve the efficiency of the network,we propose a similarity measurement module to determine whether the neighborhood near the center point is effective.We demonstrate the validity and superiority of our method on the S3DIS and ShapeNet datasets.Through ablation experiments and segmentation visualization,we verify that the SGT model can improve the performance of the point cloud semantic segmentation.

Three-dimensional(3D)parametric measurements of individual gravels in the Gobi region using point cloud technique

Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gravels.The proposed workflow yields accurate calculations of relevant parameters for Gobi gravels,providing essential data support for subsequent studies on Gobi environments.

Increasing the Resolution and SNR of an ADC′s Measurement with a Method of Over- Sampling and Averaging

By analyzing the theory of over-sampling and averaging, the conclusion is educed that white noise accompanies the signal and the addition of each bit of resolution can be achieved via a fourfold sampling frequency. The addition of each bit will approximately increase the SNR （signal to noise ratio） to 6dB.

Seismic data analysis based on spatial subsets

There are some limitations when we apply conventional methods to analyze the massive amounts of seismic data acquired with high-density spatial sampling since processors usually obtain the properties of raw data from common shot gathers or other datasets located at certain points or along lines. We propose a novel method in this paper to observe seismic data on time slices from spatial subsets. The composition of a spatial subset and the unique character of orthogonal or oblique subsets are described and pre-stack subsets are shown by 3D visualization. In seismic data processing, spatial subsets can be used for the following aspects： （1） to check the trace distribution uniformity and regularity; （2） to observe the main features of ground-roll and linear noise; （3） to find abnormal traces from slices of datasets; and （4） to QC the results of pre-stack noise attenuation. The field data application shows that seismic data analysis in spatial subsets is an effective method that may lead to a better discrimination among various wavefields and help us obtain more information.

基于DSP和FPGA的数字示波器设计

为了测量激光发生器电源模块的重要参数,提出了一种基于DSP和FPGA的数字示波器。分别分析了实时采样和等效采样的基本原理、基于DESO滤波器的滤波原理及其数学表达式;在此基础上,给出了幅度类参数和周期类参数的计算方法,并对各类指标进行了详细计算。整个数字示波器嵌入在激光发生器整体系统中,工程应用性强、集成度高。测试结果表明,数字示波器运行稳定可靠,能够满足设计要求,具有很高的应用价值。

基于STM32的A/D采样软件滤波改进算法研究

在工程实践和实验中,经常要对经过A/D转换后的数据进行采集,但由于存在外界干扰和电路设计不合理等因素,将会导致数据不停的跳变,非常不稳定。为了改善这种情况,有效地去除干扰,提出一种改进的软件滤波算法。采用STM32作为高速处理器,对16个通道的A/D连续采样1 600次,每个通道采集100次,将采样到的数据通过内部的高速DMA通道传送到内存的数组中。首先对每个通道的100个数据进行冒泡排序,去掉排序后的前后各10个数据,用剩余的80个数据再取平均值。测试结果表明:这种改进的均值滤波算法,能够有效的去除跳变的干扰数据,使得处理后的数据变得稳定、可靠,提高了精度和稳定性。

高精度A/D采样电路的干扰分析与电路设计

分析了A/D采样电路的特点及干扰形式,总结了高精度A/D采样电路的PCB设计规则,完整设计了一个基于CPLD和ADS7809的高精度A/D采样电路,应用结果表明,该高精度采样电路板抗干扰能力强,工作稳定,采样精度符合设计要求。

高速A/D转换器测试采样技术研究

高速A/D转换器是电子器件中比较特殊而又关键的器件。关于高速A/D转换器的动态参数测试方法比较多,文章主要讨论相干采样与加窗采样在高速A/D转换器参数测试中的应用,两种方法各自的优缺点,以及应用中应该注意的问题。

24位A/D转换器ADS1255及其应用

ADS1255是TI公司推出的微功耗、高精度、24位Δ-∑型模数转换器,其内部集成了输入模拟多路开关、输入缓冲器、可编程增益放大器、可编程数字滤波器.文中介绍了ADS1255的主要特点、工作原理、典型应用实例及应用程序,最后给出了ADS1255的一些使用要点及设计经验.

基于FPGA的高速A/D转换控制模块的设计

采用FPGA器件EPF 10K 10LC 84-4实现了对高速A/D转换芯片TLC 5540的实时采样控制,并利用片内嵌入式阵列块-EAB作为F IFO缓冲器进行高速采样数据存储,完成数据的缓冲、处理、传输等功能.该模块可广泛应用于通信、打印机、数字电视等设备中.

软件无线电设计的A/D采样分析

模数变换 (A/ D)是实现软件无线电的关键技术之一。本文首先介绍了软件无线电的概念 ,然后着重分析了 A/ D变换器的各项技术指标 ,并结合实例 ,详细论述了 A/

基于超声波A/D采样法的相位差位移测量方法

为了提高超声波位移测量分辨率，提出一种基于超声波A／D采样法的超声波相位差位移测量方法，利用超声波信号的相邻采样数据之差，消除了超声波信号中的直流成分对相位差位移测量的影响，再通过不同相邻采样数据之差的比值建立了相位差位移测量的数学模型，由此获得较高的相位差位移测量分辨率。该方法的采样电路简单，不需要高倍数超声波信号采样率，仅需在一个超声波信号周期里采样10几个数据，就可获得亚微米级的位移测量分辨率。实验结果验证了该方法的有效性。基于该方法研制的超声波位移测量平台，若超声波频率选用40kHz，则位移测量分辨率可达1μm。

基于多路Σ-ΔA/D转换器的同步数据采集系统

介绍一种结构简单、精度高、成本低的数据采集装置。它使用简单可靠的硬件高速锁相环电路,控制6通道Σ-ΔA/D转换器,以实现同步整周期采样和跟踪滤波,实现对相互关联的6路信号进行同步数据采集和数据分析。