New Method For Detection Research Articles

On thermocapillary rings from radioactive particles suspended at the surface of liquids

Thermocapillary motion and its significance with regard the thermal behavior of heat sources and with particular reference to radioactive particles suspended at the surface of fluids is discussed. It is shown that because the radial temperature profile surrounding the hot particle, a thermocapillary flow is induced with the viscous liquid flowing outwards from the particle and then with a drag force propelling the surrounding suspended material away from the hot particle with the formation of a diffusive ring. Utilizing a simplified physical model, it was found a power-law for the concentration of particles surrounding the hot particle. The formation of such a ring may be important as a visual technique to detect or unveil the presence of radioactive particles or as a new method for detection under controlled conditions. Computational Fluid Dynamics (CFD) simulations were performed which agree qualitatively and quantitatively with the analytical model.

Copy-move forgery detection based on multifractals

Digital images and video are the basic media for communication nowadays. They are used as authenticated proofs or corroboratory evidence in different areas like: forensic studies, law enforcement, journalism and others. With development of software for editing digital images, it has become very easy to change image content, add or remove important information or even to make one image combining multiple images. Thus, the development of methods for such change detection has become very important. One of the most common methods is copy-move forgery detection (CMFD). Methods of this type include change detection that occur by copying a part of an image and pasting it to another location within the image. We propose new method for detection of such changes using certain multifractal parameters as characteristic features, as well as common statistical parameters. Before the analysis, images are divided into non-overlapping blocks of fixed dimensions. For each block, the characteristic features are calculated. In order to classify observed blocks, we used metaheuristic method and proposed new semi-metric function for similarity analysis between blocks. Simulation shows that the proposed method provides good results in terms of precision and recall, with low computational complexity.

Automatic detection, localization and segmentation of nano-particles with deep learning in microscopy images

With the growing amount of high resolution microscopy images automatic nano-particle detection, shape analysis and size determination have gained importance for providing quantitative support that gives important information for the evaluation of the material. In this paper, we present a new method for detection of nano-particles and determination of their shapes and sizes simultaneously with deep learning. The proposed method employs multiple output convolutional neural networks (MO-CNN) and has two outputs: first is the detection output that gives the locations of the particles and the other one is the segmentation output for providing the boundaries of the nano-particles. The final sizes of particles are determined with the modified Hough algorithm that runs on the segmentation output. The proposed method is tested and evaluated on a dataset containing 17 TEM images of Fe3O4 and silica coated nano-particles. Also, we compared these results with U-net algorithm which is a popular deep learning method. The experiments showed that the proposed method has 98.23% accuracy for detection and 96.59% accuracy for segmentation of nano-particles.

New method for detection of T4 polynucleotide kinase phosphatase activity through isothermal EXPonential amplification reaction.

As a bifunctional enzyme, T4 polynucleotide kinase phosphatase (T4 PNKP) catalyzes the phosphorylation of 5'-hydroxyl, and also removes the terminal 3'-phosphate group. This is closely related to the restructuring, replication, and damage repair of nucleic acid. In this paper, we describe a new method for the sensitive detection of T4 PNKP activity based on the isothermal EXPonential amplification reaction (EXPAR). T4 PNKP can be linearly assayed in the range from 0.001 to 0.01 U mL-1 with a detection limit of 7.9 × 10-4 U mL-1. Moreover, the method exhibits high specificity and sensitivity and can be applied in the enzyme analysis of complex serum samples. In view of its simplicity and moderate experimental conditions, the method may suitable for use in a commercial kit for the analysis of T4 PNKP activity.

ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATA

Abstract Currently, during the operation in shallow waters, scanning systems, such as multibeam systems, are capable of collecting thousands of points in a short time, promoting a greater coverage of the submerged bottom, with consequent increase in the detection capacity of objects. Although there has been an improvement in the accuracy of the depths collected, traditional processing, that is, manual, is still required. However, mainly due to the increased mass of data collected, manual processing has become extremely time-consuming and subjective, especially in the detection and elimination of spikes. Several algorithms are used to perform this task, but most of them are based on statistical assumptions hardly met and/or verified, such as spatial independence and normality. In this sense, the goal of this study is to present the SODA (Spatial Outlier Detection Algorithm) methodology, a new method for detection of spikes designed to treat bathymetric data collected through swath bathymetry systems. From computational simulation, promising results were obtained. SODA, in some cases, was capable to identify even 90% of spikes inserted on simulation, showing that the methodology is efficient and substantial to the bathymetric data treatment.

Observation of Free Induction Decay Signals of OH Radicals Excited by Terahertz Free-Electron Laser Pulses

The first experimental observation of free induction decay signals of free radicals is reported. The signals were observed on the line of the rotational transition of OH radicals in the terahertz region. OH radicals were generated by the chemical reaction of excited oxygen atoms with water molecules. Radicals were excited by free-electron laser radiation pulses. Free induction decay radiation was detected in real time using ultra fast terahertz radiation detectors. The possibility of using free induction decay signals of radicals as a new method for detection of free radicals in combustion processes is discussed.

Introducing a new method for the fusion of fraud evidence in banking transactions with regards to uncertainty

Detection of fraudulent transactions is a vital factor for financial institutions, and finding more effective and accurate methods is of tremendous importance. The use of supervised data mining techniques is not feasible in many cases due to the lack of access to labeled data. Fraud detection is a complex task, and unsupervised methods like clustering and outlier detection techniques employed alone do not yield satisfactory results. Another issue is epistemic uncertainty due to the absence of sufficient information on the behavioral aspects of different customers, which also leads to poorer results for fraud detection and makes the fraud detection system inapplicable in real world environment. In this paper, using multi criteria decision method, intuitionistic fuzzy set, and evidential reasoning, a new method for detection of fraud was introduced, which infuses several behavioral evidence of a transaction concerning the effect of uncertainty for them. Transactional behavior was modeled by considering the trends of different main and aggregated variables at different periods and the extent of deviation of the new arrived transaction from each of these trends were considered as behavioral evidence. The final belief, which is the result of the combination of much evidence using the proposed method, will determine the originality of a newly arrived transaction. Finally, using a real world dataset, the results of the new method were compared with the results of Dempster–Shafer method in terms of the number of frauds discovered and the number of erroneous alerts they issued. The findings showed that the method introduced in this study has higher accuracy and lower false alarms compared to Dempster–Shafer method while the computational complexity of this method makes its implementation time longer.

A new method for detection of single nucleotide polymorphism in a female reproduction-associated gene, tmigd1, of Anas platyrhynchos using a strip biosensor with gold nanoparticles.

In this study, we first reported a lateral flow assay combined with primer extension (PEXT) and gold nanoparticles for single-nucleotide polymorphism (SNP) genotyping of the tmigd1 gene of the Tsaiya ducks (Anas platyrhynchos), which has the advantages of simplicity of operation, cost-effectiveness, and time-saving. Gold nanoparticles were tailed with thiol-thymine oligodeoxyribonucleotides (thiol-(dT)30) using the salt-aging method at 25°C and used as a label in a lateral flow assay. The lateral flow device was composed of test and control zones on a nitrocellulose membrane containing streptavidin and adenosine oligodeoxyribonucleotides ((dA)30), respectively. When the specific SNP existed, the corresponding primers were extended, and the reaction product was captured by streptavidin at the test zone owing to the introduction of biotin-deoxyuridine triphosphate (biotin-dUTP) into the reaction product during PEXT. Gold nanoparticles hybridized with the reaction product to render it visible. Here, we developed a new system for detection of single nucleotide polymorphism in a female reproduction-associated gene, tmigd1, of Anas platyrhynchos using the strip biosensor, and identified the optimized parameters for the concentration of Mg2+ in the PEXT reaction and the amount of streptavidin used on membranes for signal specificity.

Combining Salmonella Dublin genome information and contact-tracing to substantiate a new approach for improved detection of infectious transmission routes in cattle populations

This study presents a new method for detection of between-herd livestock movements to facilitate disease tracing and more accurately describe network behaviour of relevance for spread of infectious diseases, including within-livestock business risk-carrying contacts that are not necessarily recorded anywhere. The study introduces and substantiates the concept of grouping livestock herds into business-units based on ownership and location in the tracing analysis of animal movement-based contact networks. To test the utility of this approach, whole core genome sequencing of 196 Salmonella Dublin isolates stored from previous surveillance and project activities was combined with information on cattle movements recorded in the Danish Cattle Database between 1997 and 2017. The aim was to investigate alternative explanations for S. Dublin circulation in groups of herds connected by ownership, but without complete records of livestock movements. The EpiContactTrace R-package was used to trace the contact networks between businesses and compare the network characteristics of businesses sharing strains of S. Dublin with different levels of genetic relatedness. The ownership-only definition proved to be an unreliable grouping approach for large businesses, which could have internal distances larger than 250 km and therefore do not represent useful epidemiological units. Therefore, the grouping was refined using spatial analysis. More than 90% of final business units formed were composed of one single cattle property, whereas multi-property businesses could reach up to eight properties in a given year, with up to 15 cattle herds having been part of the same business through the study period. Results showed markedly higher probabilities of introduction of infectious animals between proposed businesses from which the same clone of S. Dublin had been isolated, when compared to businesses with non-related strains, thus substantiating the business-unit as an important epidemiological feature to consider in contact network analysis and tracing of infection routes. However, this approach may overestimate real-life contacts between cattle properties and putatively overestimate the degree of risk-contacts within each business, since it is based solely on information about property ownership and location. This does not consider administrative and individual farmers behaviours that essentially keep two properties separated. Despite this, we conclude that defining epidemiological units based on businesses is a promising approach for future disease tracing tasks.

Gravitational grating

In this work, we study the interaction of the electromagnetic wave (EW) from a distant quasar with the gravitational wave (GW) sourced by the binary stars. While in the regime of geometric optics, the light bending due to this interaction is negligible, we show that the phase shifting on the wavefront of an EW can produce the diffraction pattern on the observer plane. The diffraction of the light (with the wavelength of $\lambda_e$) by the gravitational wave playing the role of {\it gravitational grating} (with the wavelength of $\lambda_g$) has the diffraction angle of $\Delta\beta \sim \lambda_e/\lambda_g$. The relative motion of the observer, the source of gravitational wave and the quasar results in a relative motion of the observer through the interference pattern on the observer plane. The consequence of this fringe crossing is the modulation in the light curve of a quasar with the period of few hours in the microwave wavelength. The optical depth for the observation of this phenomenon for a Quasar with the multiple images strongly lensed by a galaxy where the light trajectory of some of the images crosses the lensing galaxy is $\tau \simeq 0.2$. By shifting the time delay of the light curves of the multiple images in a strong-lensed quasar and removing the intrinsic variations of a quasar, our desired signals, as a new method for detection of GWs, can be detected.

Detection of triacetone triperoxide by thermal decomposition peroxy radical chemical amplification coupled to cavity ring-down spectroscopy.

Triacetone triperoxide (TATP) is frequently used in improvised explosive devices because of its ease of manufacture and tremendous explosive force. In this paper, we describe a new method for detection of TATP, thermal decomposition peroxy radical chemical amplification cavity ring-down spectroscopy (TD-PERCA-CRDS). In this method, air is sampled through a heated inlet to which ~ 1ppmv nitric oxide (NO) is added. To verify the purity of synthetic standards, the mid-infrared spectrum of TATP vapor was recorded. The thermal decomposition of TATP is shown to produce radicals which oxidize NO to nitrogen dioxide (NO2), whose concentration increase is monitored by optical absorption at 405nm using a blue diode laser CRDS. The sensitivity could be improved through addition of ~ 1% ethane (C2H6), which fuels catalytic conversion of NO to NO2. The limit of detection of TD-PERCA-CRDS with respect to TATP is 22pptv (1s data), approximately six orders of magnitude below TATP's saturation vapor pressure. Insights into the mechanism of TATP thermal decomposition, TD-PERCA-CRDS interferences, and the suitability of TD-PERCA-CRDS as a peroxy radical explosive detection method at security check points are discussed.

A new approach for identification of heartbeats in multimodal physiological signals

In this paper, a technique is proposed for detection of heartbeats in multimodal data. Recording of multiple physiological signals from the same subject is common practice nowadays. Multiple physiological signals are generally available but are processed separately without taking into consideration information from other relevant signals. The heartbeats are generally detected from R peaks in electrocardiogram (ECG) signal, however, if ECG is noisy, other signals reflecting the cardiac activity may be used for identifying heartbeats. This paper describes a new method for detection of heartbeats using ECG and arterial blood pressure (ABP) signals. The physiological data are segmented into various fragments and signal quality is determined using the judgment of noise level. If the ECG data fragment is noisy, heartbeats are computed from the ABP fragment. The evaluation was performed on training data set of computing in cardiology challenge 2014. The proposed methodology has resulted in better detection accuracy as compared to the unimodal methods.

Instrument detection and pose estimation with rigid part mixtures model in video-assisted surgeries.

Localizing instrument parts in video-assisted surgeries is an attractive and open computer vision problem. A working algorithm would immediately find applications in computer-aided interventions in the operating theater. Knowing the location of tool parts could help virtually augment visual faculty of surgeons, assess skills of novice surgeons, and increase autonomy of surgical robots. A surgical tool varies in appearance due to articulation, viewpoint changes, and noise. We introduce a new method for detection and pose estimation of multiple non-rigid and robotic tools in surgical videos. The method uses a rigidly structured, bipartite model of end-effector and shaft parts that consistently encode diverse, pose-specific appearance mixtures of the tool. This rigid part mixtures model then jointly explains the evolving tool structure by switching between mixture components. Rigidly capturing end-effector appearance allows explicit transfer of keypoint meta-data of the detected components for full 2D pose estimation. The detector can as well delineate precise skeleton of the end-effector by transferring additional keypoints. To this end, we propose effective procedure for learning such rigid mixtures from videos and for pooling the modeled shaft part that undergoes frequent truncation at the border of the imaged scene. Notably, extensive diagnostic experiments inform that feature regularization is a key to fine-tune the model in the presence of inherent appearance bias in videos. Experiments further illustrate that estimation of end-effector pose improves upon including the shaft part in the model. We then evaluate our approach on publicly available datasets of in-vivo sequences of non-rigid tools and demonstrate state-of-the-art results.

Spectrophotometric, colorimetric and visually detection of Pseudomonas aeruginosa ETA gene based gold nanoparticles DNA probe and endonuclease enzyme

Colorimetric DNA detection is preferred over other methods for clinical molecular diagnosis because it does not require expensive equipment. In the present study, the colorimetric method based on gold nanoparticles (GNPs) and endonuclease enzyme was used for the detection of P. aeruginosa ETA gene. Firstly, the primers and probe for P. aeruginosa exotoxin A (ETA) gene were designed and checked for specificity by the PCR method. Then, GNPs were synthesized using the citrate reduction method and conjugated with the prepared probe to develop the new nano-biosensor. Next, the extracted target DNA of the bacteria was added to GNP-probe complex to check its efficacy for P. aeruginosa ETA gene diagnosis. A decrease in absorbance was seen when GNP-probe-target DNA cleaved into the small fragments of BamHI endonuclease due to the weakened electrostatic interaction between GNPs and the shortened DNA. The right shift of the absorbance peak from 530 to 562nm occurred after adding the endonuclease. It was measured using a UV-VIS absorption spectroscopy that indicates the existence of the P. aeruginosa ETA gene. Sensitivity was determined in the presence of different concentrations of target DNA of P. aeruginosa. The results obtained from the optimized conditions showed that the absorbance value has linear correlation with concentration of target DNA (R: 0.9850) in the range of 10–50ngmL−1 with the limit detection of 9.899ngmL−1. Thus, the specificity of the new method for detection of P. aeruginosa was established in comparison with other bacteria. Additionally, the designed assay was quantitatively applied to detect the P. aeruginosa ETA gene from 103 to 108CFUmL−1 in real samples with a detection limit of 320CFUmL−1.

Application of DNA-based electrochemical biosensor in rapid detection of Escherichia coli exist in licorice decoction

A new method for detection of Escherichia coli exist in licorice decoction was developed by using DNA-based electrochemical biosensor. The thiolated capture probe was immobilized on a gold electrode at first. Then the aptamer for Escherichia coli was combined with the capture probe by hybridization. Due to the stronger interaction between the aptamer and the E. coli, the aptamer can dissociate from the capture probe in the presence of E. coli in licorice decoction. The biotinylated detection probe was hybridized with the single-strand capture probe. As a result, the electrochemical response to Escherichia coli can be measured by using differential pulse voltammetric in the presence of α-naphthyl phosphate. The plot of peak current vs. the logarithm of concentration in the range from 2.7×10² to 2.7×10⁸ CFU·mL⁻¹ displayed a linear relationship with a detection limit of 50 CFU·mL⁻¹. The relative standard deviation of 3 successive scans was 2.5%，2.1%，4.6% for 2×10²，2×10⁴，2×106：⁶ CFU·mL⁻¹ E. coli, respectively. The proposed procedure showed better specificity to E. coli in comparison to Pseudomonas aeruginosa, Staphylococcus aureus and Bacillus subtilis. In the detection of the real extractum glycyrrhizae, the results between the proposed strategy and the GB assay showed high degree of agreement, demonstrating the designed biosensor could be utilized as a powerful tool for microbial examination for traditional Chinese medicine.

Wind turbine fault detection and classification by means of image texture analysis

Abstract The future of the wind energy industry passes through the use of larger and more flexible wind turbines in remote locations, which are increasingly offshore to benefit stronger and more uniform wind conditions. The cost of operation and maintenance of offshore wind turbines is approximately 15–35% of the total cost. Of this, 80% goes towards unplanned maintenance issues due to different faults in the wind turbine components. Thus, an auspicious way to contribute to the increasing demands and challenges is by applying low-cost advanced fault detection schemes. This work proposes a new method for detection and classification of wind turbine actuators and sensors faults in variable-speed wind turbines. For this purpose, time domain signals acquired from the operating wind turbine are represented as two-dimensional matrices to obtain grayscale digital images. Then, the image pattern recognition is processed getting texture features under a multichannel representation. In this work, four types of texture characteristics are used: statistical, wavelet, granulometric and Gabor features. Next, the most significant ones are selected using the conditional mutual criterion. Finally, the faults are detected and distinguished between them (classified) using an automatic classification tool. In particular, a 10-fold cross-validation is used to obtain a more generalized model and evaluates the classification performance. Coupled non-linear aero-hydro-servo-elastic simulations of a 5 MW offshore type wind turbine are carried out in several fault scenarios. The results show a promising methodology able to detect and classify the most common wind turbine faults.

Infrared thermography, a new method for detection of brown adipose tissue activity after a meal in humans

The activation of brown adipose tissue (BAT) after cold exposure leads to heat production. However, the activation of BAT activity after a meal as part of diet induced thermogenesis is still controversial. A possible reason is that measuring BAT activity by positron emission tomography–computed tomography (PET CT) via accumulation of radiotracer fludeoxyglucose (18F-FDG), which competes with an increase in glucose concentration after a meal, fails as the method of choice. In this study, activity of BAT was determined by infrared thermography. Activation of BAT 30 min after a meal increases glucose consumption, decreases plasma glucose concentration, and leads to changes of body temperature (diet-induced thermogenesis). Detecting pathophysiological changes in BAT activity after a meal by infrared thermography, a non-invasive more sensitive method, will be of great importance for people with increased body weight and diabetes mellitus type 2.

Controlled synthesis of polydopamine: A new strategy for highly sensitive fluorescence turn-on detection of acetylcholinesterase activity.

A new water soluble fluorescent coronene probe (CTCA) was synthesized and is shown to display strong fluorescence (with excitation/emission maxima at 313/450nm) in aqueous solution. Dopamine was oxidized under air to form polydopamine (PDA) which quenches the fluorescence of CTCA. The enzyme acetylcholinesterase (AChE) is known catalyze the hydrolysis of acetylthiocholine to produce thiocholine. Thiocholine inhibits the polymerization of DA, and this leads to recovery in CTCA fluorescence. These findings form the basis for a new method for detection of AChE activity. The assay has a detection limit as low as 0.05mU·mL-1 of AChE. It is highly selective, and other enzymes do no noticeably interfere. It was applied to the determination of AChE activity in (spiked) human serum, and of AChE inhibitors in (spiked) lake water samples. Graphical abstract Controlled synthesis of polydopamine for the highly sensitive and selective sensing of AChE activity is reported for the first time.

Quantitative method for analysis of six anticoagulant rodenticides in faeces, applied in a case with repeated samples from a dog

BackgroundAccidental poisoning with anticoagulant rodenticides is not uncommon in dogs, but few reports of the elimination kinetics and half-lives in this species have been published. Our objectives were to develop and validate a new method for the quantification of anticoagulant rodenticides in canine blood and faeces using reversed phase ultra-high performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS) and apply the method on a case of anticoagulant rodenticide intoxication.ResultsSample preparation was liquid–liquid extraction. Six anticoagulant rodenticides were separated using a UPLC® BEH C18-column with a mobile phase consisting of 5 mM ammonium formate buffer pH 10.2 and methanol. MS/MS detection was performed with positive electrospray ionization and two multiple reaction monitoring transitions. The limits of quantification were set at the levels of the lowest calibrator (1.5–2.7 ng/mL or ng/g). The method was successfully applied to a case from a dog accidentally poisoned with anticoagulant rodenticide. Coumatetralyl and brodifacoum concentrations were determined from serial blood and faecal samples. A terminal half-life of at least 81 days for coumatetralyl in blood was estimated, which is longer than previous reported in other species. A slow elimination of brodifacoum from the faeces was found, with traces still detectable in the faeces at day 513.ConclusionsThis study offers a new method of detection and quantification of six frequently used anticoagulant rodenticides in canine faeces. Such drugs might cause serious health effects and it is important to be able to detect these drugs, to initiate proper treatment. The very long elimination half-lives detected in our study is important to be aware of in assessment of anticoagulant rodenticide burden to the environment.

Detection and identification of furan fatty acids from fish lipids by high-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry

Using high-performance liquid chromatography coupled to high-resolution electrospray ionization quadrupole time-of-flight mass spectrometry (HPLC/ESI-Q-TOF-MS), we have developed a new method for detection and identification of furan fatty acids (F-acids), which are widely distributed in living organisms and foods as minor lipid components and are known to have antioxidant and anti-inflammatory effects. For this purpose, total fatty acids prepared from the testis lipids of Japanese chum salmon (Oncorhynchus keta) were examined without any concentration or isolation of F-acids. In negative ESI mode, F-acids gave a prominent [M−H]− ion, by which individual F-acids could be detected and identified. High-resolution extracted ion chromatograms clearly showed the occurrence of five major F-acid homologs as already reported by GC/MS. The method was successfully applied to several fish samples and revealed the occurrence of F-acids for the first time in the two New Zealand fish, hoki (Macruronus novaezelandiae) and school shark (Galeorhinus galeus).