经鼻盲探插管术在张口受限患者的应用

目的研究经鼻盲探插管术在张口受限患者中的应用。方法选择2013年7月—2014年5月收治的口腔科手术患者52例,ASA评分Ⅰ∽Ⅱ级。其中32例张口度﹤2 cm,完全张口受限患者20例。导管选择ID 4.0∽7.0 mm。麻醉前给予足量抗胆碱药物,必要时给予小剂量咪唑安定和芬太尼静脉注射,在充分表面麻醉下行经鼻盲探插管术,观察在操作过程中血压、心率、脉搏血氧饱和度的变化。结果该组52例患者在充足的麻醉前准备和完善的表面麻醉下经鼻盲探插管全部成功。在插管前与插管后即刻SBP分别为（123.0±9.3）mm Hg、（129.0±9.7）mm Hg,DBP分别为（72.0±6.2）mm Hg、（74.0±6.5）mm Hg,HR分别为（82.0±2.4）次/min、（85.3±2.6）次/min,SPO2分别为（99.7±0.5）%、（99.6±0.6）%,盲探插管操作过程的血压、心率、脉搏血氧饱和度无明显变化。术后随访患者无喉痛、声嘶、喉头水肿等并发症。结论经鼻盲探插管在张口受限患者的应用是切实安全、有效地。     

2011年微生物实验室质控盲样结果分析

目的通过质量控制考核评价实验室的检测能力,提高实验室的检测水平,保证检测结果准确、可靠。方法依据《中华人民共和国国家标准食品卫生微生物检验方法》及河南省和洛阳市下发的《卫生微生物质控作业指导书》对4份盲样菌株进行检验。结果从4份盲样菌株中检出1株志贺氏菌、2株金黄色葡萄球菌、1株阪崎肠杆菌,检测结果正确率为100%。结论实验室质控有助于提高检验水平。     

盲探气管插管装置在困难气管患者中的临床应用

目的探讨盲探气管插管装置引导下经鼻气管插管对患者临床应用的价值。方法 59例择期行手术患者,ASA分级I～Ⅱ级,分为2组。A组：26例,采用盲探气管插管装置引导下经鼻气管插管。B组：33例,采用经喉镜直视下行气管插管。比较2组之间氧合、心血管反应及鼻口腔损伤情况。结果 2组对比对患者氧合、心血管反应及鼻口腔损伤差异无统计学意义（P〉0.05）。结论盲探气管插管装置在困难气管插管患者中应用具有安全性高、操作简便、对患者影响小等优点,值得推广。     

空肠盲袢在胆道结石手术中应用的效果观察

目的：研究阻道术后残石存留及结石复发的治疗。方法：30例病人作胆总管或肝总管空肠Roux-en-y吻合的同时，将空肠盲袢埋置于右前腹壁皮下，以利胆道结石残存或结石复发时，使用纤维胆道镜经皮经空肠盲袢进入胆道取石。结果：本组病例手术效果满意，无术后并发症。术后11例残石、5例复发结石经皮空肠盲袢纤维胆道镜取石成功。结论：胆道结石作空肠盲袢埋置术可提供一条从体外通向胆道最简易的永久通道，对结石残留和结石复发的病人可避免再次手术，减轻其痛苦。     

ACTBP2-nomenclature recommendations of GEDNAP

A system of nomenclature is proposed for the complex STR system ACTBP2 (SE33) in order to facilitate data exchange between laboratories.The nomenclature conforms to the ISFH recommendations as far as it is possible for such complex systems. A blind trial was carried out between up to 20 laboratories to ascertain the reproducibility of the nomenclature under working conditions. The population studies carried out have established that there are minimal regional differences in the allele frequencies and that the system of nomenclature is robust. Received: 18 June 1997 / Received in revised form: 27 August 1997     

Automatic removal of eye movement and blink artifacts from EEG data using blind component separation

Signals from eye movements and blinks can be orders of magnitude larger than brain-generated electrical potentials and are one of the main sources of artifacts in electroencephalographic (EEG) data. Rejecting contaminated trials causes substantial data loss, and restricting eye movements/blinks limits the experimental designs possible and may impact the cognitive processes under investigation. This article presents a method based on blind source separation (BSS) for automatic removal of electroocular artifacts from EEG data. BBS is a signal-processing methodology that includes independent component analysis (ICA). In contrast to previously explored ICA-based methods for artifact removal, this method is automated. Moreover, the BSS algorithm described herein can isolate correlated electroocular components with a high degree of accuracy. Although the focus is on eliminating ocular artifacts in EEG data, the approach can be extended to other sources of EEG contamination such as cardiac signals, environmental noise, and electrode drift, and adapted for use with magnetoencephalographic (MEG) data, a magnetic correlate of EEG.     

Ocular Reduction in EEG Signals Based on Adaptive Filtering,Regression and Blind Source Separation

Quantitative electroencephalographic (EEG) analysis is very useful for diagnosing dysfunctional neural states and for evaluating drug effects on the brain, among others. However, the bidirectional contamination between electrooculographic (EOG) and cerebral activities can mislead and induce wrong conclusions from EEG recordings. Different methods for ocular reduction have been developed but only few studies have shown an objective evaluation of their performance. For this purpose, the following approaches were evaluated with simulated data: regression analysis, adaptive filtering, and blind source separation (BSS). In the first two, filtered versions were also taken into account by filtering EOG references in order to reduce the cancellation of cerebral high frequency components in EEG data. Performance of these methods was quantitatively evaluated by level of similarity, agreement and errors in spectral variables both between sources and corrected EEG recordings. Topographic distributions showed that errors were located at anterior sites and especially in frontopolar and lateral–frontal regions. In addition, these errors were higher in theta and especially delta band. In general, filtered versions of time-domain regression and of adaptive filtering with RLS algorithm provided a very effective ocular reduction. However, BSS based on second order statistics showed the highest similarity indexes and the lowest errors in spectral variables.     

离散余弦变换(DCT)在彩色图像盲水印技术中的应用

研究了基于离散余弦变换(DCT)的图像水印技术在彩色图像中的应用,提出了一种基于DCT域的彩色图像水印算法,该算法在保证水印不可见和鲁棒性的前提下,可以实现水印的盲提取。实验结果表明,此算法可以很好地保护图像的质量,并且对常用的图像处理具有较强的鲁棒性。     

A comparative study of automatic techniques for ocular artifact reduction in spontaneous EEG signals based on clinical target variables: a simulation case

Eye movement artifacts represent a critical issue for quantitative electroencephalography (EEG) analysis and a number of mathematical approaches have been proposed to reduce their contribution in EEG recordings. The aim of this paper was to objectively and quantitatively evaluate the performance of ocular filtering methods with respect to spectral target variables widely used in clinical and functional EEG studies. In particular the following methods were applied: regression analysis and some blind source separation (BSS) techniques based on second-order statistics (PCA, AMUSE and SOBI) and on higher-order statistics (JADE, INFOMAX and FASTICA). Considering blind source decomposition methods, a completely automatic procedure of BSS based on logical rules related to spectral and topographical information was proposed in order to identify the components related to ocular interference. The automatic procedure was applied in different montages of simulated EEG and electrooculography (EOG) recordings: a full montage with 19 EEG and 2 EOG channels, a reduced one with only 6 EEG leads and a third one where EOG channels were not available. Time and frequency results in all of them indicated that AMUSE and SOBI algorithms preserved and recovered more brain activity than the other methods mainly at anterior regions. In the case of full montage: (i) errors were lower than 5% for all spectral variables at anterior sites; and (ii) the highest improvement in the signal-to-artifact (SAR) ratio was obtained up to 40dB at these anterior sites. Finally, we concluded that second-order BSS-based algorithms (AMUSE and SOBI) provided an effective technique for eye movement removal even when EOG recordings were not available or when data length was short.     

Independent component analysis: comparison of algorithms for the investigation of surface electrical brain activity

We compared the performance of 22 algorithms for independent component analysis with the aim to find suitable algorithms for applications in the field of surface electrical brain activity analysis. The quality of the separation is assessed with four performance measures: a correlation coefficient based index, a signal-to-interference ratio, a signal-to-distortion-ratio and the computational demand. Artificial data are used consisting of typical electroencephalogram and evoked potentials signal patterns, e.g. spikes, polyspikes, sharp waves and spindles. We evaluate different noise scenarios and the influence of pre-whitening. The comparisons reveal considerable differences between the algorithms, especially concerning the computational load. Algorithms based on the time structure of the data set seem to have advantages in separation quality especially for sine-shaped signals. Derivates of FastICA and Infomax also attain good results. Our results can serve as a reference for selecting a task-specific algorithm to analyze a large number of signal patterns occurring in the surface electrical brain activity. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.