Combined Extracting Process and Activity Detection of Porcine Blood Superoxide Dismutase

[Objective] TO study the combined extracting process of porcine blood superoxide dismutase （SOD） and other bioactive substances and thus to provide technical basis for making full use of blood resources and large-scale production of SOD. [Method] Fibronectin, immunoglobulin, and hemoglobin were isolated from porcine blood, and SOD was extracted. Trace pyrogallol self-oxidation method to determine SOD activity was modified by optimizing the volume of pyrogallol and SOD samples, reaction temperature, and buffer pH. The specific activity of SOD was determined with the optimized extraction conditions. [ Result] The improved experimental conditions of SOD activity detection were as follows： 7 pyrogallol （50 mmol/L）, 3 ml Tris-HCI （50 mmol/L, pH 8.2）, reactive temperature at 25（3, and 10 pl SOD sample solution. The specific activity of extracted SOD was 5 056 U/mg protein. [ Conclusion] Four kinds of bioactive substance can be isolated from porcine blood by modern biological engi- neering integration technology, and the extracted SOD has better activity.

Combined detection tumor markers for diagnosis and prognosis of gallbladder cancer

AIM: To clarify the value of combined use of markers for the diagnosis of gallbladder cancer and prediction of its prognosis. METHODS: Serum cancer antigens (CA) 199, CA242, carcinoembryonic antigen (CEA), and CA125 levels were measured in 78 patients with gallbladder cancer (GBC), 78 patients with benign gallbladder diseases, and 78 healthy controls using electrochemiluminescence. CA199, CA242, CEA, and CA125 levels and positive rates were analyzed and evaluated pre-and post-operatively. Receiver operator characteristic curves were used to determine diagnostic sensitivity and specificity of GBC. Survival time analysis, including survival curves, and multivariate survival analysis of a Cox proportional hazards model was performed to evaluate independent prognostic factors. RESULTS: Serum CA242, CA125, and CA199 levels in the GBC group were significantly higher when compared with those in the benign gallbladder disease and healthy control groups (P < 0.01). With a single tumor marker for GBC diagnosis, the sensitivity of CA199 was the highest (71.7%), with the highest specificity being in CA242 (98.7%). Diagnostic accuracy was highest with a combination of CA199, CA242, and CA125 (69.2%). CA242 could be regarded as a tumor marker of GBC infiltration in the early stage. The sensitivity of CA199 and CA242 increased with progression of GBC and advanced lymph node metastasis (P < 0.05). The 78 GBC patients were followed up for 6-12 mo (mean: 8 mo), during which time serum CA199, CA125, and CA242 levels in the recurrence group were significantly higher than in patients without recurrence (P < 0.01). The post-operative serum CA199, CA125, and CA242 levels in the non- recurrence group were significantly lower than those in the GBC group (P < 0.01). Multivariate survival analysis using a Cox proportional hazards model showed that cancer of the gallbladder neck and CA199 expression level were independent prognostic factors. CONCLUSION: CA242 is a marker of GBC infiltration in the early stage. CA199 and cancer of the gallbladder neck are therapeutic and prognostic markers. (C) 2014 Baishideng Publishing Group Co., Limited. All rights reserved.

Beam pointing correction of variable polarization MMW/IR combined detection

A kind of beam-scanning algorithm of variable polarization millimeter array antenna based on the phased array technology is put forward in this paper. The algorithm can be successfully applied to deal with beam directivities inconsistency of millimeter wave/infrared（ MMW/IR ） multimode detector, it can keep electric axis and optical axis coincident. Accordingly, this method can decrease the data fusion difficulty and improve the accuracy of angle measurement. Simulation results show that variable polarization millimeter array antenna has flexible beam-scanning abibility within ±0.5° after the algorithm was adopted, simultaneously, antenna polarization purity is better than 20 dB within the half power beamwidth, sidelobe imbalance keeps high available and antenna gain of the sum beam is over 26.8 dB.

Defect detection of gear parts in virtual manufacturing

Gears play an important role in virtual manufacturing systems for digital twins;however,the image of gear tooth defects is difficult to acquire owing to its non-convex shape.In this study,a deep learning network is proposed to detect gear defects based on their point cloud representation.This approach mainly consists of three steps:(1)Various types of gear defects are classified into four cases(fracture,pitting,glue,and wear);A 3D gear dataset was constructed with 10000 instances following the aforementioned classification.(2)Gear-PCNet++introduces a novel Combinational Convolution Block,proposed based on the gear dataset for gear defect detection to effectively extract the local gear information and identify its complex topology;(3)Compared with other methods,experiments show that this method can achieve better recognition results for gear defects with higher efficiency and practicability.

Combination of Loop-Mediated Isothermal Amplification Assay and Nested PCR for Detection of Borrelia burgdorferi sensu lato in Human Serum Samples

A set of universal loop-mediated isothermal amplification （LAMP） primers targeting the flo gene was designed to detect Borrelia burgdorferi sensu lato （B. burgdorferi s.I.） in human samples. The sensitivity of LAMP was 20 copies/reaction, and the assay did not detect false positives among 11 other related bacteria. A positive LAMP result was obtained for 9 of the 24 confirmed cases and for 12 of 94 suspected cases. The positive rate of LAMP was the same as that of nested PCR. The LAMP is a useful diagnostic method that can be developed for rapid detection of B. burgdorferi s.I. in human sera. Combination of the LAMP and nested PCR was more sensitive for detecting B. burgdorferi s.I. in human serum samples.

Enhanced Side-Channel Leakage Detection Method by Considering Combinational Logic

In this paper,we propose a hybrid power model that includes the power consumption of not only the registers but also part of the combinational logic.By doing knownkey analysis with this hybrid model,power side-channel leakage caused by correct keys can be detected.In experiment,PRINTcipher and DES algorithms were chosen as analysis targets and combinational logic s-box unit was selected to build power template.The analysis results showed the signal-to-noise ratio(SNR) power consumption increase of more than 20%after considering s-box's power consumption so that the information of keys can be obtained with just half number of power traces.In addition,the side channel-leakage detection capability of our method also shows better effectiveness that can identify the correct keys.

Detection of Antibodies in Serum Specimens from Dogs with Blastomycosis with Lysate Antigens Prepared from Four <i>Blastomyces dermatitidis</i>Dog Isolates: Individual Antigens vs Antigen Combinations

Blastomycosis, the systemic fungal infection of humans and animals, has presented a diagnostic challenge to clinicians and laboratory personnel for many years. Our laboratory has been concentrating on attempting to develop antigenic reagents from the yeast phase of various isolates of Blastomyces dermatitidis and to evaluate these lysate antigens with regard to antibody detection in blastomycosis. The aim of this current study was to evaluate yeast phase antigens prepared from four dog isolates of B. dermatitidis and to evaluate their efficacy, when used individually or in combination, for antibody detection in sera from dogs with blastomycosis. Mean absorbance values using the ELISA to assay 24 serum specimens (Trial 1) ranged from 0.588 with an individual lysate antigen to 0.992 when three reagents were combined. Eight of the lysates exhibited mean absorbance values ranging from 0.992 to 0.915 with 7 out of 8 being lysate antigen combinations. Mean absorbance values with the other 6 lysates ranged from 0.899 to 0.588. In Trial 2, the 6 most sensitive reagents from Trial 1 were assayed against 10 highly reactive dog sera. The results of Trial 2 showed that 5 antigen combinations detected antibody to a greater degree than the individual lysate antigen. Combinations of northern and southern antigens were able to detect antibody in serum specimens from either of these geographical regions. Comparative studies are continuing to further evaluate various lysate antigen combinations for antibody detection in blastomycosis.

Combination of structure tensor and tilt angle in the edge detection of potential field data

Edge detection is a commonly requested task in the interpretation of potential field data. Different methods have different results for varied depths and shapes of geological bodies. In this paper,we propose using the combination of structure tensor and tilt angle to detect the edges of the sources,which can display the edges of shallow and deep bodies simultaneously. Through tests on synthetic potential field data,it is obvious that the proposed edge detection methods can display the sources edges more clearly and precisely,compared with other commonly used methods. The application on real potential field data shows similar result,obtaining the edges of layers and faults clearly. In addition,another advantage of the new method is its insensitivity to noise.

Combined measurement of thyroid and plasma homocysteic acid for detecting the severity of vascular dementia

BACKGROUND: Recent researches demonstrate that onset of cerebral infarction always accompanies with obvious changes of function of thyroid axis; while, high-homocysteic acidemia has been proved as one of risk factors of vascular dementia and Alzheimer disease. Meanwhile, it is found that level of plasma homocysteic acid is positive correlation with injured degrees of cognitive function and brain damage. OBJECTIVE: To observe the changes of function of thyroid and level of homocysteic acid among patients with vascular dementia and compare with those patients without dementia cerebral infarction. DESIGN: Randomized grouping and contrast observation. SETTING: Department of Neurology, People’s Hospital Affiliated to Yunyang Medical College, South China Hospital of Wuhan University. PARTICIPANTS: A total of 38 patients with vascular dementia were hospitalized in the Department of Neurology, People’s Hospital Affiliated to Yunyang Medical College from February 2004 to December 2005. All patients met the diagnostic criteria of the Fourth Edition of Diagnostic and Statistical Manual of Mental Disorder (DSM-IV) established by American Psychiatric Association. Based on educational degrees, Mini-mental Status Examination (MMSE) was classified into illiteracy (≤ 17 points), education of primary school (educational duration ≤ 6 years, ≤ 24 points) and education of middle school or above (educational duration > 6 years, ≤ 24 points). Forty patients with non-dementia cerebral infarction were regarded as the control group and checked with CT examination. There were no significant differences of sex and age between the two groups. All patients and relatives were provided the consent. METHODS: Within 24 hours after hospitalization, patients with vascular dementia received MMSE scores, and the degrees were classified based on the scoring results: mild (20-24 points), moderate (10-19 points) and severe (below 10 points). Levels of thyroxine were measured with radioimmunodetection and content of homocysteic acid was measured with high performance liquid chromatogram (HPLC) electrochemical detection. MAIN OUTCOME MEASURES: Levels of homocysteic acid and thyroxine among patients with vascular dementia and non-dementia cerebral infarction. RESULTS: A total of 38 patients with vascular dementia and 40 patients with non-dementia cerebral infarction were involved in the final analysis. ① Levels of triiodothyronine (T3), thyroxine (T4) and free T3 (FT3) were (0.9±0.4) μg/L, (92.9±26.4) μg/L and (3.9±1.8) pmol/L in vascular dementia group respectively, which were higher than those in control group [(1.3±0.3) μg/L, (110.2±28.7) μg/L, (7.2±2.1) pmol/L, t =2.766 6-7.433 6, P < 0.01]; while, level of homocysteic acid was (29.57±7.12) μmol/L in vascular dementia group, which was higher than that in control group [(24.53±4.98) μmol/L, t =3.637 7, P < 0.01]. There were no significant differences of free T4 (FT4) and thyrotropic-stimulating hormone (TSH) between the two groups (P > 0.05). ② Levels of FT3 of patients with mild, moderate and severe vascular dementia were (1.0±0.2), (0.9±0.1) and (0.8±0.1) μg/L, respectively; levels of homocysteic acid were (26.52±4.84), (29.59±5.56) and (32.71±6.17) μmol/L, respectively. There were significant differences among patients at the three degrees of vascular dementia (F =3.59-32.4, P < 0.01). However, there were no significant differences of T4, FT4 and TSH among the three kinds of patients (P > 0.05). CONCLUSION: Levels of thyroxine of patients with vascular dementia decrease; however, levels of homocysteic acid increase. Therefore, the results can indirectly reflect severities of vascular dementia.

Fast Edge Detection Based on the Combination of Fuzzy Subsets

A fast edge detection method basing on the combination of fuzzy subsets is developed, in which the detection of an edge as a classification problem will be considered, partitioning the image into two portions: the edge portion and the non-edge portion. The latter one, as the main constituent of an image, consists of the object and its background. Removing the non-edge portion from an image, the remainder is nothing but the edge of this image. As far as the fuzziness of the edge of an image is concerned, some fuzzy operations can be made. In this paper, the gray level histogram is partitioned into several sub-regions, and some operations are performed with the associated fuzzy subsets corresponding to those sub-edges in the sub-regions on the gray-level-square-difference histogram, and the edge of this image is finally obtained. Practical examples in this paper illustrate that, the described method is simple and effective to achieve an ideal edge image.

RVP Fast与Seeplex PneumoBacter ACE Detection assay联合诊断呼吸道感染病原体

目的采用RVP Fast与Seeplex PneumoBacter ACE Detection assay两种方法,联合诊断呼吸道感染病原体。方法收集南京市呼吸道感染患者咽拭子标本67份,提取RNA及DNA,呼吸道病毒群快速检测(Respiratory Virus Panel Fast Array,RVP Fast)技术检测呼吸道病毒,Seeplex PneumoBacter ACE Detection assay检测呼吸道六重病原体。结果 67份标本中,呼吸道病毒阳性仅4例,主要为肠鼻病毒。呼吸道六重病原体检测中,阳性标本为26例,其中肺炎链球菌、流感嗜血杆菌、肺炎衣原体阳性较多。结论 RVP Fast与Seeplex PneumoBacter ACE Detection assay联合使用,有利于明确呼吸道感染病原体。

Combining TDLAS and multi-fusion algorithms for methane gas concentration detection

High-precision methane gas detection is of great importance in industrial safety, energy production and environmental protection, etc. However, in the existing measurement techniques, the methane gas concentration information is susceptible to noise, which leads to its useful signal being drowned by noise. A fusion algorithm of variational modal decomposition(VMD) and improved wavelet threshold filtering is proposed, which is used in combination with tunable diode laser absorption spectroscopy(TDLAS) to implement a non-contact, high-resolution methane gas concentration detection. The fusion algorithm can perform noise reduction and further segmentation of the methane gas detection signal. And the simulation and experiment verify the effectiveness of the fusion algorithm, and the experimental results show that for the detection of air containing 10 ppm, 30 ppm, 60 ppm, 80 ppm, and 99 ppm methane, the errors are 12.75%, 8.18%, 3.37%, 2.46%, and 1.78%, respectively.

A Generalized Wind Turbine Anomaly Detection Method Based on Combined Probability Estimation Model

Anomaly detection based on the data collected from the supervisory control and data acquisition(SCADA)system is crucial to reduce the failure rate of wind turbines(WTs).The difficulty of this kind of methods is to dynamically identify the threshold for anomaly detection under changing operating conditions.In this paper,a generalized WT anomaly detection method based on the combined probability estimation model(CPEM)is proposed.The CPEM can estimate the conditional probability density function(PDF)of the target variable given changing conditions.Its generalization and accuracy are better than those of the independent probability estimation model because it combines the advantages of various kinds of probability estimation models through linear combination.By using the CPEM,the normal operating bounds under different operating conditions can be obtained,which dynamically form the thresholds for anomaly detection.Meanwhile,with respect to the thresholds,hypothesis testing(HT)is adopted to identify the anomaly by inspecting whether the observations exceed the thresholds at a given significance level,providing sound mathematical support for anomaly detection and making the detection results more reliable.The effectiveness of the proposed method is tested by using the actual data of WTs with known faults.The results illustrate that the proposed method can detect the abnormal operating state of the gearbox and generator much more early than the system fault alarm.

ANALYSES ON STRUCTURAL DAMAGE IDENTIFICATION BASED ON COMBINED PARAMETERS

The relative sensitivities of structural dynamical parameters were analyzed using a directive derivation method. The neural network is able to approximate arbitrary nonlinear mapping relationship, so it is a powerful damage identification tool for unknown systems. A neural network-based approach was presented for the structural damage detection. The combined parameters were presented as the input vector of the neural network, which computed with the change rates of the several former natural frequencies ( C), the change ratios of the frequencies ( R), and the assurance criterions of flexibilities (A). Some numerical simulation examples, such as, cantilever and truss with different damage extends and different damage locations were analyzed. The results indicate that the combined parameters are more suitable for the input patterns of neural networks than the other parameters alone.

Pautomatic Sea Target Detection Based on Wavelet Transform

An effective automatic target detection algorithm based on wavelet transform,which takes advantage of the localization and the orientation of wavelet analysis,is proposed.The algorithm detects the target in the vertical component of the wavelet transformation of the image.After mutual energy combination and sea clutter suppression through spatial weighting and thresholding,the target is located through maximum energy determination and its size is indicated through similarity measurement function of two overlapping windows.Experiment results show that the target can be detected by the algorithm in a single image frame and the better efficiency can be obtained also under the complicated backgrounds of existing the disturbances of cloud layer and fish scale light.

Efficient Accurate Context-Sensitive Anomaly Detection

For program behavior-based anomaly detection, the only way to ensure accurate monitoring is to construct an efficient and precise program behavior model. A new program behavior-based anomaly detection model, called combined pushdown automaton (CPDA) model was proposed, which is based on static binary executable analysis. The CPDA model incorporates the optimized call stack walk and code instrumentation technique to gain complete context information. Thereby the proposed method can detect more attacks, while retaining good performance.

A combined moving mechanism with independent movement in longitudinal direction and transverse direction

To make the detecting robot move on the surface of the finned tubes, a novel combined moving mechanism is developed. The combined moving mechanism is composed of sprocket wheel and drum-like small wheel installed on the chain. It can make the robot move independently in the direction parallel to the tubes and in the direction perpendicular to the tubes. This paper made a detailed discussion on the composition of the combined moving mechanism, the design method of the conjugate outline curve and the circular-arc outline curve of the drum-like small wheel that meshes with the tubes. The error of the circular-arc outline curve is also analyzed.

PCT、CRP、IL-6、SAA在恶性肿瘤患者血流感染中的诊断效能分析

目的探讨降钙素原(procalcitonin,PCT)、C反应蛋白(C-reactive protein,CRP)、白细胞介素-6(interleukin-6,IL-6)、血清淀粉样蛋白A(serum amyloid A,SAA)4种血清学感染指标对恶性肿瘤患者血流感染的诊断效能。方法选择120例临床确诊血流感染且血培养阳性恶性肿瘤患者作为观察组,100例同期血培养阴性恶性肿瘤患者作为对照组。记录并比较2组血清PCT、CRP、IL-6、SAA水平,绘制受试者工作特征曲线(receiver operator characteristic curve,ROC curve)对4种感染指标进行诊断效能分析,计算单项检测与多项目联合检测水平的灵敏度、特异度及约登指数。结果观察组血清PCT、CRP、IL-6、SAA浓度水平均显著高于对照组,差异有统计学意义(P<0.01);ROC曲线显示PCT的曲线下面积较大(0.935),最佳截断值0.594 ng·mL-1,此时的特异性和敏感度分别是96%、83%,具有一定的诊断价值,但不具备足够的敏感度;PCT、CRP、SAA、IL6联合检测曲线下面积最大(0.981),敏感度达到了92%,诊断效能最佳,对恶性肿瘤患者血流感染具有较高的诊断价值。结论恶性肿瘤患者普遍年龄较大并伴有基础疾病,机体抵御病原菌侵袭的能力下降,更容易发生血流感染。PCT、CRP、SAA、IL6联合检测在早期诊断血流感染方面具有较高的应用价值,可以在一定程度上提高临床诊断准确度,改善患者的预后、降低病死率。

钻孔瞬变电磁法扫描探测RCQPSO-LMO组合算法2.5D反演

利用钻孔进行超前探测地质构造及含水体是地下开挖工程中的常规手段,如何利用这些钻孔进行钻孔瞬变电磁法扫描探测,从而实现钻孔孔壁外围地质异常体的精细探测,对实现地下工程地质透明化具有重要的指导意义.本文提出钻孔瞬变电磁法扫描探测2.5D反演的数据解译方法,首先针对随机性反演算法时效性低,易陷入局部最优解,而确定性反演算法依赖初始模型的问题,提出了组合策略的量子粒子群优化算法用来随机搜索最优初始模型.在此基础上,利用Levenberg-Marquarat方法求解Occam反演的目标函数,形成了RCQPSO-LMO组合算法进行2.5D反演,通过对比组合算法和单一算法,验证了组合算法具有更精确的反演结果.其次结合屏蔽条件下扫描探测,对比分析了有无屏蔽的2.5D反演结果,通过设定屏蔽系数对非探测方向信号进行部分压制,可以较好地解决钻孔径向扫描探测中对非探测方向信号部分屏蔽下的反演及成像.最后建立三组理论模型进行组合算法2.5D反演,结果表明:组合算法反演结果与理论模型的一致性较好,对低阻异常体的反演精度较高,验证了组合算法对钻孔孔壁外围低阻异常体具有较高的反演精度和分辨能力.

基于立体视觉下联合收获机边缘检测技术的研究

智能联合收割机是目前作物收获的发展热点与研究重点技术之一,而确定田间地块边缘、未收割作物边缘、联合收获机直线行驶和在作物地头转向是实现全田间自动收获的基础。为此,设计了一种基于立体视觉下多种作物收获边缘快速检测方法,保持作物收获边缘在检测目标区域内,并提出了一种基于HSV(色调、饱和度和值)空间扫描的动态感兴趣区域提取算法,利用Ostu算法获得作物未收获面积,实现未收获作物边缘和作物末端边缘的同时检测,并根据作物收获末端边缘自动转向到下一个收割路径。田间验证试验表明:水稻检测准确率高于98%,玉米的检测准确率高于94%,平均处理速度为49frame/ms。研究结果表明:提出的基于立体视觉下联合收获机边缘检测及精准转向系统具有较高的工作精度和效率,可为提高作物收获性能提供技术参考与借鉴。