流产后宫内胎物组织残留的超声诊断

回顾性分析了４６例临床被证实为宫内胎物组织残留的病例。结果表明，流产后较长时间有不规则阴道流血，而作Ｂ超检查能发现特征性改变。声像图显示，子宫增大，宫内有异常光团和不规则液性暗区或宫腔局部膨隆，周边见很亮光条。认为诊断宫内残留组织，可以结合病只与声像技术较易诊断出来。本组超声诊断符合率达９８％。对减少因宫内残留造成的子宫收缩不良、不规则阴道流血等现象，避免并发感染及导致绒癌发生等不良后果，有重要的     

Some fractal properties of the percolating backbone in two dimensions

A new algorithm is presented, based on elements of artificial intelligence theory, to determine the fractal properties of the backbone of the incipient infinite cluster. It is found that the fractal dimensionality of the backbone isd _f ^BB =1.61±0.01, the chemical dimensionality isd _t=1.40±0.01, and the fractal dimension of the minimum pathd _min=1.15 ± 0.02 for the two-dimensional triangular lattice.     

A Small-Molecule Diketopyrrolopyrrole-Based Dye for in vivo NIR-IIa Fluorescence Bioimaging

Organic small-molecule fluorophores with near-infrared IIa (NIR-IIa) emission have great potential in pre-clinical detection and inoperative imaging due to the high-spatial resolution and deep penetration. However, developments of the NIR-IIa fluorophores are still facing considerable challenges. In this work, a series of diketopyrrolopyrrole (DPP)-based fluorophores were designed and synthesized. Subsequently, nanomaterial T25@F127 with significant NIR-IIa emission properties was rationally prepared by encapsulating DPP-based fluorophore T25 , and was selected for fluorescence angiography and cerebral vascular microscopic imaging with nearly 800 μm penetrating depth and excellent signal-background ratio of 4.07 and 2.26 (at 250 and 400 μm), respectively. Furthermore, the nanomaterial T25@cRGD with tumor targeting ability can image tiny metastatic tumor on intestine with a small size of 0.3 mm×1.0 mm and high-spatial resolution (SBR=3.84). This study demonstrates that the nanomaterials which encapsulated T25 behave as excellent NIR-IIa fluorescence imaging agents and have a great potential for in vivo biological application.     

Mechanism of interaction of pressure waves at a discrete partial blockage

This paper analyses the mechanism of interaction between an incident pressure wave and blockages of different geometrical characteristics (i.e., a butterfly and a ball valves, two short stretches of pipe with a reduced diameter, and a device simulating a longitudinal body blockage) by means of laboratory and numerical tests. Experiments have shown that the mechanism of interaction with pressure waves is influenced by their path through the device: sinuous because of the device body for partially closed in-line valves (type I mechanism), and straight for the small bore pipe devices (type II mechanism). Type I mechanism is characterized by a rise followed by an almost constant value whereas in type II one a drop occurs after the rise. To complete the investigation the effect of the pre-transient condition is discussed.     

Mechanisms of martensitic transformations in boron nitride and conditions of their development

Abstract

The dependence of the pressure threshold of martensitic transformations on the disordering degree of starting structures is considered for graphite-like BN into diamond-like BN modifications transitions. The effect of loading conditions on transformation mechanisms of rhombohedral BN into zinc blende or wurtzite modifications is analyzed also. Analytical relations obtained allow to explain the experimental data and to predict a behavior of various graphite-like structures under different p, T conditions.     

Application of nanodiamonds in human body fluid analysis by matrix-assisted laser desorption/ionization mass spectrometry

Direct mass spectrometric analysis of complex biological samples is very important and challenging. In this paper, nanodiamonds have been successfully used in matrix-assisted laser desorption/ionization mass spectrometric analysis of human serum and urine. As a practical tool and platform, it can be widely used in the field of humoral proteomics, and it plays a very promising role in clinical diagnosis, including identification of novel disease-associated biomarkers.     

Laser absorption spectroscopy for combustion diagnosis in reactive flows: A review

Laser absorption spectroscopy (LAS) has been rapidly developed and widely applied to combustion diagnosis in recent decades. As a cost-effective tool for measuring multiple combustion parameters, LAS provides unique properties in terms of accuracy and sensitivity for understanding the reactions and kinetics in reactive flows. Line-of-sight and tomographic LAS techniques have stimulated numerous applications and been proved to be robust for in situ combustion diagnosis in uniform and non-uniform combustion fields, respectively. This review highlights the breakthroughs in the evolution of LAS techniques from the viewpoints of key principles, sensors and instrumentations developed for combustion diagnosis, with particular emphasis on a series of spatially-resolved LAS techniques with their recent applications on obtaining high-fidelity measurement results with minimal intrusion to the practical combustors. Along the way, we note some challenges and requirements for further development of the LAS-based combustion diagnosis.     

新疆富蕴县萨尔布拉克金矿预测区断裂特征及其控矿规律

在全面、系统收集和研究新疆富蕴县萨尔布拉克地区地质、地球物理、地球化学、矿产普查和科研资料的基础上，深入分析金矿成矿地质条件、控矿因素和找矿方法组合，对萨尔布拉克预测区95条断裂的地质、地球物理、地球化学特征进行了全面统计分析，确定了42条赋金断裂．其中早期断裂8条，占19％；晚期断裂34条，占81％．赋金断裂以晚期南北向为主，次为东西向和北西向．航磁异常向上延拓高度大者，即赋金断裂延深大者对金的成矿有利．     

Intelligent Fault Identification for Rolling Bearings Fusing Average Refined Composite Multiscale Dispersion Entropy-Assisted Feature Extraction and SVM with Multi-Strategy Enhanced Swarm Optimization

Rolling bearings act as key parts in many items of mechanical equipment and any abnormality will affect the normal operation of the entire apparatus. To diagnose the faults of rolling bearings effectively, a novel fault identification method is proposed by merging variational mode decomposition (VMD), average refined composite multiscale dispersion entropy (ARCMDE) and support vector machine (SVM) optimized by multistrategy enhanced swarm optimization in this paper. Firstly, the vibration signals are decomposed into different series of intrinsic mode functions (IMFs) based on VMD with the center frequency observation method. Subsequently, the proposed ARCMDE, fusing the superiorities of DE and average refined composite multiscale procedure, is employed to enhance the ability of the multiscale fault-feature extraction from the IMFs. Afterwards, grey wolf optimization (GWO), enhanced by multistrategy including levy flight, cosine factor and polynomial mutation strategies (LCPGWO), is proposed to optimize the penalty factor C and kernel parameter g of SVM. Then, the optimized SVM model is trained to identify the fault type of samples based on features extracted by ARCMDE. Finally, the application experiment and contrastive analysis verify the effectiveness of the proposed VMD-ARCMDE-LCPGWO-SVM method.