缺血预处理对大鼠压疮缺血再灌注损伤保护作用的实验研究

目的比较不同缺血处理方法对大鼠皮肤及皮下组织的保护作用,为临床判断压疮损伤的程度及压疮干预效果提供理论依据。方法将60只SD大鼠随机分为对照组（S组）、缺血再灌注组（RI组）和缺血预处理组（IPC组）,每组20只．建立大鼠压疮缺血再灌注损伤处理模型,通过肉眼观察受压程度,检测血清氧自由基的水平,以判断压疮缺血再灌注损伤程度。结果RI组和IPC组大鼠出现I期压疮的发生率为100％。IPC组血清一氧化氮、丙二醛含量高于S组,明显低于RI组．超氧化物歧化酶活性低于S组,明显高于RI组。结论缺血预处理对压疮缺血再灌注损伤具有保护作用。     

一种提高直肠癌诊断精度的基于U型网络和残差块的电子计算机断层扫描图像分割算法EI北大核心CSCD

作为确定病灶与诊断的重要基础,医学图像分割已成为生物医学领域中极其重要的热门研究领域之一,其中基于全卷积神经网络和U型网络(U-net)等神经网络的医学图像分割算法得到越来越多研究人员的重视。目前,医学图像分割算法应用于直肠癌诊断的研究报道较少,且已有的研究对直肠癌的分割结果精度不高。本文提出了一种结合图像裁剪和预处理方法的编码—解码卷积网络模型。该模型在U型网络的基础上,借鉴残差网络思想,用残差块代替传统的卷积块,有效避免了梯度消失的问题。此外,本文还采用了图像增广的方法提高了所提模型的泛化能力,并在"泰迪杯"数据挖掘挑战赛所提供的数据集进行测试。测试结果表明,本文提出的基于残差块的改进U型网络模型结合图像裁剪预处理,可以大大提高直肠癌的分割精度,得到的戴斯系数在验证集上达到0.97。     

A scanning protocol for a sensorimotor rhythm-based brain-computer interface

Auditory size perception refers to the ability to make accurate judgements of the size of a sound source based solely upon the sound emitted from the source. Electro-physiological and behavioural data were collected to test whether sound-source size parameters are detected from task-irrelevant sequences in adults and newborn infants. The mismatch negativity (MMN) obtained from adults indexed automatic detection of changes in size for voices, musical instruments and animal calls, regardless of whether the acoustic change indicated larger or smaller sources. Neonates detected changes in the size of a musical instrument. The data are consistent with the notion that auditory size-deviant detection in humans is an innate automatic process. This conclusion is compatible with the theory that the ability to assess the size of sound sources evolved because it provided selective advantage of being able to detect larger (more competent) suitors and larger (more dangerous) predators.     

Early Detection of Lung Cancer Risk Using Data Mining

Background: Lung cancer is the leading cause of cancer death worldwide Therefore, identification of geneticas well as environmental factors is very important in developing novel methods of lung cancer prevention.However, this is a multi-layered problem. Therefore a lung cancer risk prediction system is here proposed whichis easy, cost effective and time saving. Materials and Methods: Initially 400 cancer and non-cancer patients’data were collected from different diagnostic centres, pre-processed and clustered using a K-means clusteringalgorithm for identifying relevant and non-relevant data. Next significant frequent patterns are discovered usingAprioriTid and a decision tree algorithm. Results: Finally using the significant pattern prediction tools for alung cancer prediction system were developed. This lung cancer risk prediction system should prove helpful indetection of a person’s predisposition for lung cancer. Conclusions: Most of people of Bangladesh do not evenknow they have lung cancer and the majority of cases are diagnosed at late stages when cure is impossible.Therefore early prediction of lung cancer should play a pivotal role in the diagnosis process and for an effectivepreventive strategy.     

QuEChERS-UPLC-MS/MS快速测定猪肝中20种磺胺类药物残留

目的:建立了一种以QuEChERS方法做为样品前处理技术,超高效液相色谱-串联质谱法快速测定猪肝中20种磺胺类药物残留量的方法。方法:猪肝样品以磺胺二甲氧嘧啶-D6为内标,经DisQuE萃取管用乙腈提取,DisQuE净化管净化,浓缩后经超高效液相色谱分离,三重串联四极杆质谱法测定。结果:在10～200μg.kg-1范围内各磺胺类药物均呈良好的线性关系,高中低浓度回收率在70%～115%,精密度小于15%。结论:本方法快速、简便,适用于猪肝中磺胺类药物的多残留批量测定。     

Photoshop仿真运动模糊的缺陷: 分析与处理

在运动模糊图像恢复处理中,以Photoshop生成的运动模糊仿真图像存在着缺陷,导致恢复时有失败.对此,本文根据运动模糊成像的物理过程,分析了缺陷产生的原因,解释了恢复失败时的周期性波纹现象;提出了根据运动位移量对场景边际区域作置零预处理后再作Photoshop处理的对策.试验结果表明,这样生成的运动模糊图像完全符合仿真要求.     

大孔吸附树脂在中药新药研究和生产中的应用

在我国大孔收附脂在中药和天然药物活性成份和有效部位的分离纯化中虽已广泛应用，但由于基础研究滞后，以致树脂在新药研究和生产应用中不断出现新问题，严重影响了树脂的有效利用。作者在研究实验的基础上总结了大孔吸附树脂的种类、性能、预处理和再生方法，探讨了大孔吸附树脂在中药新药研究和生产中应注意的一些技术问题，为新药研究和中药生产提供参者．并提出应进行荔用树脂的开发生产．     

Pattern Detection of Atherosclerosis from Carotid Artery Doppler Signals using Fuzzy Weighted Pre-Processing and Least Square Support Vector Machine (LSSVM)

Carotid Artery Doppler Signals were recorded from 114 subjects, 60 of whom had Atherosclerosis disease while the rest were healthy controls. Diagnosis of Atherosclerosis from Carotid Artery Doppler Signals was conducted using Fuzzy weighted pre-processing and Least Square Support Vector Machine (LSSVM). First, in order to determine the LSSVM inputs, spectral analysis of Carotid Artery Doppler Signals was performed via Autoregressive (AR) modeling. Then, fuzzy weighted pre-processing based is proposed expert system, applied to inputs obtained from spectral analysis of Carotid Artery Doppler Signals. LSSVM was used to detect Atherosclerosis from Carotid Artery Doppler Signals. All data set were obtained from Carotid Artery Doppler Signals of healthy subjects and subjects suffering from Atherosclerosis disease. The employed expert system has achieved 100% classification accuracy using a 10-fold Cross Validation (CV) method.     

An automatic pre-processing pipeline for EEG analysis (APP) based on robust statistics

Objective

With the advent of high-density EEG and studies of large numbers of participants, yielding increasingly greater amounts of data, supervised methods for artifact rejection have become excessively time consuming. Here, we propose a novel automatic pipeline (APP) for pre-processing and artifact rejection of EEG data, which innovates relative to existing methods by not only following state-of-the-art guidelines but also further employing robust statistics.

痰标本前处理的临床意义

目的探讨痰标本前处理对检测结果的影响及临床意义。方法选取2016年2月至2016年4月于该院住院患者痰标本124例,采取肉眼观察和痰涂片革兰染色镜检等前处理,分析其对痰标本分离鉴定结果的影响。结果 124例痰标本中,合格痰标本90例,不合格痰标本34例;无色痰标本合格率(30%)低于黄色痰标本合格率(94.7%)、铁锈色痰标本合格率(100%)、红色痰标本合格率(100%)和白色痰标本合格率(87.5%);泡沫或水样痰标本合格率(22.2%)低于脓性痰标本合格率(96.2%)、血性痰标本合格率(100%)和黏液痰标本合格率(83.3%);34例不合格标本培养结果为口腔、咽部正常菌群,均有杂菌生长;90例合格标本中,58例标本呈纯培养或呈优势生长,32例标本有杂菌生长。结论痰标本前处理是提高痰液检测结果准确性的较好方法,具有重要临床意义。