Identification of plasma microRNA-21 as a biomarker for early detection and chemosensitivity of non-small cell lung cancer

Studies have shown cell-free microRNA(miRNA) circulating in the serum and plasma with specific expression in cancer,indicating the potential of using miRNAs as biomarkers for cancer diagnosis and therapy.This study was to investigate whether plasma miRNA-21(miR-21) can be used as a biomarker for the early detection of non-small cell lung cancer(NSCLC) and to explore its association with clinicopathologic features and sensitivity to platinum-based chemotherapy.We used real-time RT-PCR to investigate the expression of miR-21 in the plasma of 63 NSCLC patients and 30 healthy controls and correlated the findings with early diagnosis,pathologic parameters,and treatment.Thirty-five patients(stages IIIB and IV) were evaluable for chemotherapeutic responses:11 had partial response(PR);24 had stable and progressive disease(SD+PD).Plasma miR-21 was significantly higher in NSCLC patients than in age-and sex-matched controls(P<0.001).miR-21 was related to TNM stage(P<0.001),but not related to age,sex,smoking status,histological classification,lymph node status,and metastasis(all P>0.05).This marker yielded a receiver operating characteristic(ROC) curve area of 0.775(95% CI:0.681-0.868) with 76.2% sensitivity and 70.0% specificity.Importantly,miR-21 plasma levels in PR samples were several folds lower than that in SD plus PD samples(P=0.049),and were close to that in healthy controls(P=0.130).Plasma miR-21 can serve as a circulating tumor biomarker for the early diagnosis of NSCLC and is related to the sensitivity to platinum-base chemotherapy.

A Novel Uniplanar Multi-Electrode Capacitive Sensor for In-Situ Weathering Damage Detection of Nonmetallic Materials

A uniplanar capacitive sensor with 5-electrodes on one plane substrate and a large reflector electrode,was designed to get the corresponding capacitance information for weathering damage detection of non-metallic materials exposed to a service environment.A 2-D finite-element method was employed to simulate the electric potential distribution and capacitance measurements for the sensor.2 marble slabs,one was healthy and the other was notched,were experimentally detected.Both the simulation and the preliminary experimental results show that the measured capacitances decrease after weathering damage occurs in nonmetallic material.The reflector can enlarge the sensitive depth.The weathering assessment of nonmetallic materials can be done by processing the measured capacitances.The proposed approach can effectively detect the weathering damage of nonmetallic material and can be practically used for in-situ weathering damage evaluation.

Optical generation,detection and non-destructive testing applications of terahertz waves

Optoelectronic terahertz generation and detection play a key role in the applications of non-destructive testing,which involves different areas such as physics,biological,material science,imaging,explosions detection,astronomy applications,semiconductor technology and superconductiong electronics. In this article,we present a reviewof the principle and performance of typical terahertz sources,detectors and non-destructive testing applications. On this basis,the newdevelopment and trends of terahertz radiation detectors are also discussed.

A Simple and Rapid Method for the Detection of Non-Ionic Surfactants

A spectrophotometric approach for the detection of non-ionic surfactant (Triton X-100) has been proposed in this paper. This method does not involve extraction of the ion-associate with harmful solvents, but employs adhesion of the ion-association of potassium/non-ionic surfactants complex and tetraphenylporphyrin tetrasulfonic acid obtained by vigorous shaking. The adhered ion-associate was dissolved with water and its absorbance was measured. The sensitivity for Triton X-100 was determined to be 0.146 (expressed as absorbance of 1 mg/L solution). The adhesion tendency of ion-associate was found to be dependent on the water contact angle, which in turn was influenced by a high adhesion of the ion-associate and by low blank values. In this respect, a tetrafluo-roethylene vessel was found to be the most suitable for the detection of non-ionic surfactants. This spectrophotometrical method is simply and rapidly performed by a procedure based on mechanical shaking and can be employed to detect non-ionic surfactants containing more than 7 polyethylene oxide units.

Non-coherent sequence detection scheme for satellite-based automatic identification system

The satellite-based automatic identification system (AIS) receiver has to encounter the frequency offset caused by the Doppler effect and the oscillator instability. This paper proposes a non-coherent sequence detection scheme for the satellite-based AIS signal transmitted over the white Gaussian noise channel. Based on the maximum likelihood estimation and a Viterbi decoder, the proposed scheme is capable of tolerating a frequency offset up to 5% of the symbol rate. The complexity of the proposed scheme is reduced by the state-complexity reduction, which is based on per-survivor processing. Simulation results prove that the proposed non-coherent sequence detection scheme has high robustness to frequency offset compared to the relative scheme when messages collision exists.

A New UKF Based Fault Detection Method in Non-linear Systems

To detect the bias fault in stochastic non-linear dynamic systems, a new Unscented Kalman Filtering（UKF） based real-time recursion detection method is brought forward with the consideration of the flaws of traditional Extended Kalman Filtering（ EKF）. It uses the UKF as the residual generation method and the Weighted-Sum Squared Residual （WSSR） as the fault detection strategy. The simulation results are provided which demonstrate better effectiveness and a higher detection ratio of the developed methods.

Non-Detection Probability of a Diffusing Target by a Stationary Searcher in a Large Region

We revisit one of the classical search problems in which a diffusing target encounters a stationary searcher. Under the condition that the searcher’s detection region is much smaller than the search region in which the target roams diffusively, we carry out an asymptotic analysis to derive the decay rate of the non-detection probability. We consider two different geometries of the search region: a disk and a square, respectively. We construct a unified asymptotic expression valid for both of these two cases. The unified asymptotic expression shows that the decay rate of the non-detection probability, to the leading order, is proportional to the diffusion constant, is inversely proportional to the search region, and is inversely proportional to the logarithm of the ratio of the search region to the searcher’s detection region. Furthermore, the second term in the unified asymptotic expansion indicates that the decay rate of the non-detection probability for a square region is slightly smaller than that for a disk region of the same area. We also demonstrate that the asymptotic results are in good agreement with numerical solutions.

Compressed sensing and Otsu's method based binary CT image reconstruction technique in non-destructive detection

This paper tries to address the problem of binary CT image reconstruction in non-destructive detection with an algorithm based on compressed sensing(CS) and Otsu's method, which could reconstruct binary CT image of test object from incomplete detection data. According to binary CT image characteristics, we employ Splitbregman method based on L1/2regularization to solve piecewise constant region reconstruction. To improve the reconstructed image quality from incomplete detection data, we utilize a priori knowledge and Otsu's method as the optimization constraint. In our study, we make numerical simulation to investigate our proposed method,and compare reconstructed results from different reconstruction methods. Finally, the experimental results demonstrate that the proposed method could effectively reduce noise and suppress artifacts, and reconstruct high-quality binary image from incomplete detection data.

Determination of Roxithromycin Tablets by Capillary Electrophoresis Employing Non-aqueous Media with Square-wave Amperometric Detection

A new method of determination for roxithromycin tablets by non-aqueous capillary electrophoresis (NACE) with square-wave amperometric detection was carried out. Several parameters affecting the NACE-AD determination were studied. The data was modified by spline wavelet least square (SWLS). The method is simple, rapid and highly reliable for routine analysis.

Laser-Assisted Generation and Detection of Non-Nuclear Low-Energy Neutrino-Antineutrino Beams

It is argued that conservation of energy, momentum, and spin, and QM transition probabilities, allow the generation and detection of low-energy (eV) neutrinos and antineutrinos in intra-atomic (non-nuclear) laser transitions. Two-quantum transitions between an upper and lower excited state in a lasing medium can support paired emissions of a neutrino and a recoiling counter-propagating anti-neutrino, each carrying half of the lasing transition energy. Their propagations are in opposite directions along the same axis as that of the intracavity laser beam in the lasing medium. Estimates show that the probability of this two-quantum event is on the order of 10&minus;7 compared to a one-quantum stimulated emission of a laser photon. Absorptions or emissions of single antineutrinos or neutrinos by molecular/atomic matter are impossible because they carry spins s = &plusmn;h/2 which violates &Delta;s = &plusmn;nh (n = integer) required for such processes. However, inside a laser, emissions of photons from excited states can be stimulated by neutrinos or anti-neutrinos passing through, provided their undulation frequency is resonant with the transition frequency. This is because in stimulated emissions, neutrinos or antineutrinos are not absorbed, and spin conservation violation is not an issue. Thus, detection of the passage of a laser-generated antineutrino or neutrino beam through a second “receiver” laser is possible provided that the transition energy in the second laser equals half the transition energy of the laser that emits the antineutrino-neutrino beam to be detected.

Detection and Characterization of β-Lactamase Encoding Genes in Carbapenem Non-Susceptible Gram-Negative Bacteria and Susceptibility of Isolates to Ceftazidime-Avibactam at a New York City Community Hospital

A surveillance study was undertaken to identify prominent β-lactamase encoding genes in 131 carbapenem non-susceptible gram-negative clinical isolates at a New York City community hospital. KPC carbapenemases were detected in 89% of Enterobacteriaceae as well as additional TEM, SHV, and CTX-M class A enzymes. OXA-23 and OXA-24 were the prevalent class D carbapenemases identified in Acinetobacter species. One OXA-23 in M. morganii and one OXA-48 in K. pneumoniae were also identified. Among class C β-lactamases CMY, ACT/MIR, DHA, and FOX were detected. The in vitro activity of ceftazidime-avibactam by E-test methodology was tested with minimal inhibitory concentrations (MIC) of ≤3 μg/ml for 97.8% of all Enterobacteriaceae, MIC50/90 of 16/>256 μg/ml for carbapenem non-susceptible Acinetobacter, and 3/6 μg/ml for carbapenem non-susceptible Pseudomonas aeruginosa. Periodic surveillance of isolates to characterize current and emerging β-lactamase genotypes present in local isolates may help identify outbreak situations, provide assistance to infection control and antibiotic stewardship programs, and potentially improve patient outcomes.

Multi-Energy Gamma-Ray Attenuations for Non-Destructive Detection of Hazardous Materials

We present a non-destructive method (NDM) to identify minute quantities of high atomic number (Z) elements in containers such as passenger baggage, goods carrying transport trucks, and environmental samples. This method relies on the fact that photon attenuation varies with its energy and properties of the absorbing medium. Low-energy gamma-ray intensity loss is sensitive to the atomic number of the absorbing medium, while that of higher-energies vary with the density of the medium. To verify the usefulness of this feature for NDM, we carried out simultaneous measurements of intensities of multiple gamma rays of energies 81 to 1408 keV emitted by sources 133Ba (half-life = 10.55 y) and 152Eu (half-life = 13.52 y). By this arrangement, we could detect minute quantities of lead and copper in a bulk medium from energy dependent gamma-ray attenuations. It seems that this method will offer a reliable, low-cost, low-maintenance alternative to X-ray or accelerator-based techniques for the NDM of high-Z materials such as mercury, lead, uranium, and transuranic elements etc.

CFAR DETECTORS FOR HIGH RESOLUTION RADAR IN NON-GAUSSIAN CLUTTER

For high resolution radar, the echoes of target come from several points rather than one point as in low resolution radar. In this case the target is called an extended target. This paper presents two CFAR detectors for such a target in non Gaussian clutter, which are CA CFAR and OS CFAR detectors. The detection performances of the two detectors are evaluated.

Statistical moment-based structural damage detection method in time domain

A novel structural damage detection method with a new damage index,i.e.,the statistical moment-based damage detection（SMBDD） method in the frequency domain,has been recently proposed.The aim of this study is to extend the SMBDD method in the frequency domain to the time domain for building structures subjected to non-Gaussian and non-stationary excitations.The applicability and effectiveness of the SMBDD method in the time domainis verified both numerically and experimentally.Shear buildings with various damage scenarios are first numerically investigated in the time domain taking into account the effect of measurement noise.The applicability of the proposed method in the time domain to building structures subjected to non-Gaussian and non-stationary excitations is then experimentally investigated through a series of shaking table tests,in which two three-story shear building models with four damage scenarios aretested.The identified damage locations and severities are then compared with the preset values.The comparative results are found to be satisfactory,and the SMBDD method is shown to be feasible and effective for building structures subjected to non-Gaussian and non-stationary excitations.

Diagnostic aids for detection of oral precancerous conditions

Oral cancer has a tendency to be detected at late stage which is detrimental to the patients because of its high mortality and morbidity rates. Early detection of oral cancer is therefore important to reduce the burden of this devastating disease. In this review article, the most common oral precancerous lesions are discussed and the importance of early diagnosis is emphasized. In addition, the most common non-invasive oral cancer devices that can aid the general practitioners in early diagnosis are also discussed.

Fault detection and diagnosis for data incomplete industrial systems with new Bayesian network approach

For the fault detection and diagnosis problem in largescale industrial systems, there are two important issues： the missing data samples and the non-Gaussian property of the data. However, most of the existing data-driven methods cannot be able to handle both of them. Thus, a new Bayesian network classifier based fault detection and diagnosis method is proposed. At first, a non-imputation method is presented to handle the data incomplete samples, with the property of the proposed Bayesian network classifier, and the missing values can be marginalized in an elegant manner. Furthermore, the Gaussian mixture model is used to approximate the non-Gaussian data with a linear combination of finite Gaussian mixtures, so that the Bayesian network can process the non-Gaussian data in an effective way. Therefore, the entire fault detection and diagnosis method can deal with the high-dimensional incomplete process samples in an efficient and robust way. The diagnosis results are expressed in the manner of probability with the reliability scores. The proposed approach is evaluated with a benchmark problem called the Tennessee Eastman process. The simulation results show the effectiveness and robustness of the proposed method in fault detection and diagnosis for large-scale systems with missing measurements.

A fast and adaptive method for automatic weld defect detection in various real-time X-ray imaging systems

A first and effective method is proposed to detect weld deject adaptively in various Dypes of real-time X-ray images obtained in different conditions. After weld extraction and noise reduction, a proper template of median filter is used to estimate the weld background. After the weld background is subtracted from the original image, an adaptite threshold segmentation algorithm is proposed to obtain the binary image, and then the morphological close and open operation, labeling algorithm and fids＇e alarm eliminating algorithm are applied to pracess the binary image to obtain the defect, ct detection result. At last, a fast realization procedure jbr proposed method is developed. The proposed method is tested in real-time X-ray image,s obtairted in different X-ray imaging sutems. Experiment results show that the proposed method is effective to detect low contrast weld dejects with few .false alarms and is adaptive to various types of real-time X-ray imaging systems.

Higher-Order Statistics for Automatic Weld Defect Detection

Image processing and image analysis are the main aspects for obtaining information from digital image owing to the fact that this techniques give the desired details in most of the applications generally and Non-Destructive testing specifically. This paper presents a proposed method for the automatic detection of weld defects in radiographic images. Firstly, the radiographic images were enhanced using adaptive histogram equalization and are filtered using mean and wiener filters. Secondly, the welding area is selected from the radiography image. Thirdly, the Cepstral features are extracted from the Higher-Order Spectra (Bispectrum and Trispectrum). Finally, neural networks are used for feature matching. The proposed method is tested using 100 radiographic images in the presence of noise and image blurring. Results show that in spite of time consumption, the proposed method yields best results for the automatic detection of weld defects in radiography images when the features were extracted from the Trispectrum of the image.

A Novel Island Detection Methodology for the Realization of Smart Grid

Responding to the problem of increased load demand, progress has been made to develop a new smarter infrastructure, which employs a decentralised approach. This smart decentralised system, termed smart grid, is composed of micro grids which utilise a combination of distributed energy resources (DER). The DERs can either be operated in parallel with the grid or in autonomous condition (intentional-islanding). Operating the DER under intentional islanding condition is seen as the next stage in smart grid’s future development which requires intelligent control implementation. In order to utilise this intelligent control, immediate detection of islanding is essential. This paper proposes a new smarter islanding detection method, which implements the forecast capability of smart grid by detecting the fluctuations before islanding occurs. The proposed method has been tested in simulation and compared against the current islanding detection methods. The simulation results have successfully proven the benefits of the new proposed method over the current methodologies in island detection.

Performance Assessment of Islanding Detection for Mul-ti-inverter Grid-connected Photovoltaic Systems

Islanding detection is an essential function for safety and reliability in grid-connected Distributed Generation Systems (DGS). Passive and active islanding detection methods have been analyzed in literature considering DGS with only one inverter connected to the utility. With the big scale application of photovoltaic (PV) power systems, islanding detection technology of multi-inverter DGS has been paid more attention. This paper analyzes the performance of diverse islanding detection methods in multiple inverters grid-connected PV systems. Non-Detection Zones (NDZ) of multi-inverter systems in a load parameter space are used as analytical tool. The paper provides guidance for the islanding detection design in multiple grid-connected inverters.