Multichannel Detection Research Articles

Broadband background-free vibrational spectroscopy using a mode-locked Cr:ZnS laser.

We demonstrate high-sensitivity vibrational absorption spectroscopy in the 2-micron wavelength range by using a mode-locked Cr:ZnS laser. Interferometric subtraction and multichannel detection across the broad laser spectrum realize simultaneous background-free detection of multiple vibrational modes over a spectral span of >380 cm-1. Importantly, we achieve detection of small absorbance on the order of 10-4, which is well below the detection limit of conventional absorption spectroscopy set by the detector dynamic range. The results indicate the promising potential of the background-free method for ultrasensitive and rapid detection of trace gases and chemicals.

The Multi-Channel Maximum-Likelihood (MCML) method for infrasound detection and wave parameter estimation: Evaluation, implementation, and first applications

The detection capability of the International Monitoring System (IMS) infrasound network is a key concern since ubiquitous coherent noise interfere with the identification of explosive events. The need to distinguish between incoherent wind noise and real coherent infrasonic wave signals has motivated the development of a new parametric stochastic model. We establish the expressions of both the Generalized Likelihood Ratio Test (GLRT) and the Maximum Likelihood Estimator (MLE). The major results are the expression of the asymptotic distribution of the GLRT under null hypothesis, leading to the p-value computation, and the expression of the asymptotic covariance. The Multi-Channel Maximum-Likelihood (MCML) detection is implemented in the time-frequency domain in order to discriminate between interfering signals. Extensive simulations with synthetic signals show that MCML outperforms the state-of-the-art multi-channel correlation detector algorithms in poor signal-to-noise ratio scenarios. We illustrate the performance of MCML on real IMS data, highlighting its capability to characterize the coherent ocean ambient infrasound noise in high resolution through comparisons with theoretical state-of-the-art numerical wave models as implemented at the LOPS research unit of IFREMER in the DATARMOR HPC center.

Construction of reversible enol-to-keto-to-enol tautomerization covalent organic polymer for sensitive, selective and multi-channel detection of iron (III)

As an important element in organism, the lack and excess of ferric ions (Fe3+) may lead to an extensive range of diseases presenting with distinct clinical manifestations. In our design, a multi-channel probe with reversible enol-to-keto-to-enol tautomerization for the specific recognition and high sensitivity detection of Fe3+ was prepared. This paper reported a novel Cop-NC probe, Tris (4-formylphenyl) amine bearing 1,4-cyclohexanedione groups, which provides binding site for Fe3+ and also contributes both fluorescent and electrochemical signals. The as-synthesized Cop-NC exhibit intense fluorescence under an excitation wavelength at 378 nm with a quantum yield of 26%. Results of spectroscopic measurement show that Fe3+ can significantly cause a “Switch-off” fluorescence intensity effect. Simultaneously, the addition of Fe3+ can cause a “Switch-on” effect in electrochemical channel. It has realized the detection of Fe3+ with concentration as low as 0.4 μM and 1.0 nM in the fluorescence channel and redox channel, respectively. The development of the joint probe with multi-channel signals provides a more convenient and rapid detection method for food, medical treatment, environmental monitoring and other fields.

The multichannel maximum-likelihood (MCML) method: a new approach for infrasound detection and wave parameter estimation

SUMMARY We are presenting a new and novel approach to the detection and parameter estimation of infrasonic signals. Our approach is based on the likelihood function derived from a multisensor stochastic model expressed in different frequency channels. Using the likelihood function, we determine, for the detection problem, the generalized likelihood ratio (GLR) and for the estimation of the slowness vector, the maximum likelihood estimation (MLE). We establish new asymptotic results (i) for the GLR under the null hypothesis leading to the computation of the corresponding p-value and (ii) for the MLE by focusing on the two wave parameters: backazimuth and horizontal trace velocity. The multichannel maximum-likelihood (MCML) detection and estimation method is implemented in the time–frequency domain in order to avoid the presence of interfering signals. Extensive simulations with synthetic signals show that MCML outperforms the state-of-the-art multichannel correlation detector algorithms like the progressive multichannel correlation in terms of detection probability and false alarm rate in poor signal-to-noise ratio scenarios. We also illustrate the use of the MCML on real data from the International Monitoring System and show how the improved performances of this new method lead to a refined analysis of events in accordance with expert knowledge.

Development of a low-cost multi-channel nucleic acid detection PCR instrument and clinical detection application of COVID-19

Since the COVID-19 outbreak at the end of December 2019, a variety of novel Coronavirus nucleic acid detection methods have been proposed at home and abroad. Because of the disadvantages of most existing PCR instruments on the market such as long reaction time and high cost, this study developed a more timesaving and cheaper two-channel real-time quantitative PCR instrument. In this instrument, a PCR system combining a thermal cycle system and real-time fluorescence quantitative technology was designed. The software system and data processing, optical system, thermal cycle module, and hardware module of the PCR instrument were studied. The low-cost, portable real-time quantitative PCR system has been validated with consistent results compared to Bio-rad CFX Connect. At the same time, the same samples were used for the contract experiment with the hospital instrument, and the amplification result was better than the existing instrument in the hospital.

Multi-channel non-destructive testing of steel strip stress based on magneto-elastic effect

ABSTRACT Internal stress is an important factor that affects the quality of strip products. Most online detection methods for internal strip stress have been realised by contact sensors. However, contact sensors are expensive to manufacture and tend to scratch the strip surface. The purpose of this study was to develop a multi-channel non-contact stress detection system that can reflect the longitudinal stress inhomogeneity of the strip in the width direction. First, a finite element model of residual stress detection based on the magneto-elastic effect was established in COMSOL, and it was calculated that the detection sensitivity was optimal when the sensor was arranged at 45°. Magnetic shielding technology effectively reduces the minimum interference-free distance of the sensor. A prototype of the detection system was built, the accuracy of the simulation model and the feasibility of the online detection of common steel grades are proved by experiments. The simulation model can directly solve issues related to the sensor’s induced voltage and the minimum interference-free distance, thereby reducing the design cycle and trial production cost of the sensor and providing new ideas for the development of magnetic shielding technology. The experimental results demonstrated that the detection method was feasible, reliable, and displayed high detection precision.

Nanoscopic distribution of VAChT and VGLUT3 in striatal cholinergic varicosities suggests colocalization and segregation of the two transporters in synaptic vesicles.

Striatal cholinergic interneurons (CINs) use acetylcholine (ACh) and glutamate (Glut) to regulate the striatal network since they express vesicular transporters for ACh (VAChT) and Glut (VGLUT3). However, whether ACh and Glut are released simultaneously and/or independently from cholinergic varicosities is an open question. The answer to that question requires the multichannel detection of vesicular transporters at the level of single synaptic vesicle (SV). Here, we used super-resolution STimulated Emission Depletion microscopy (STED) to characterize and quantify the distribution of VAChT and VGLUT3 in CINs SVs. Nearest-neighbor distances analysis between VAChT and VGLUT3-immunofluorescent spots revealed that 34% of CINs SVs contain both VAChT and VGLUT3. In addition, 40% of SVs expressed only VAChT while 26% of SVs contain only VGLUT3. These results suggest that SVs from CINs have the potential to store simultaneously or independently ACh and/or Glut. Overall, these morphological findings support the notion that CINs varicosities can signal with either ACh or Glut or both with an unexpected level of complexity.

Light-addressable photoelectrochemical sensors for multichannel detections of GPC1, CEA and GSH and its applications in early diagnosis of pancreatic cancer

Glypican-1 (GPC1) has been demonstrated to be a potential biomarker of pancreatic cancer, so ultrasensitive detection of GPC1 was important for the diagnosis of pancreatic cancer. In this paper, a photoelectrochemical (PEC) immunosensor based on gold nanoclusters (AuNCs) was developed for the first time for the ultrasensitive detection of GPC1. Then graphene oxide (GO) was introduced into AuNCs as a hybrid nanomaterial to improve the sensitivity. The results confirmed that GO increased the sensitivity by enhancing both the photoelectric properties and antibody loading properties. Finally, the PEC immunosensors for GPC1 detection achieved an optimal sensitivity (7.265 nA/decade) and an excellent limit of detection (LOD) of 15 pg/mL (S/N = 3). To provide more information for the early diagnosis of pancreatic cancer, multichannel light-addressable PEC sensors that achieved the simultaneous detection of biomacromolecules and biomicromolecules was further developed by AuNCs/GO based PEC immunosensors and carbon dots@mesoporous silica beads (CDs@MSB) based PEC sensor. The simultaneous ultrasensitive detection of GPC1, carcinoembryonic antigen (CEA) and glutathione (GSH) were achieved by using this light-addressable PEC sensor. Finally, samples from pancreatic cancer models were detected, which verified the practicality and accuracy of the light-addressable PEC sensor in the evaluation and early diagnosis of pancreatic cancer.

A Thermal Infrared Pedestrian-Detection Method for Edge Computing Devices.

The thermal imaging pedestrian-detection system has excellent performance in different lighting scenarios, but there are problems regarding weak texture, object occlusion, and small objects. Meanwhile, large high-performance models have higher latency on edge devices with limited computing power. To solve the above problems, in this paper, we propose a real-time thermal imaging pedestrian-detection method for edge computing devices. Firstly, we utilize multi-scale mosaic data augmentation to enhance the diversity and texture of objects, which alleviates the impact of complex environments. Then, the parameter-free attention mechanism is introduced into the network to enhance features, which barely increases the computing cost of the network. Finally, we accelerate multi-channel video detection through quantization and multi-threading techniques on edge computing devices. Additionally, we create a high-quality thermal infrared dataset to facilitate the research. The comparative experiments on the self-built dataset, YDTIP, and three public datasets, with other methods show that our method also has certain advantages.

Multi-channel parallel ultrasound detection based on a photothermal tunable fiber optic sensor array.

A multi-channel parallel ultrasound detection system based on a photothermal tunable fiber optic sensor array is proposed. The resonant wavelength of the ultrasound sensor has a quadratic relationship with the power of a 980-nm heating laser. The maximum tuning range is larger than 15 nm. Through photothermal tuning, the inconsistent operating wavelengths of the Fabry-Perot (FP) sensor array can be solved, and then a multiplexing capacity of up to 53 can be theoretically realized, which could greatly reduce the time required for data acquisition. Then, a fixed wavelength laser with ultra-narrow linewidth is used to interrogate the sensor array. The interrogation system demonstrates a noise equivalent pressure (NEP) as low as 0.12 kPa, which is 5.5-times lower than the commercial hydrophone. Furthermore, a prototype of a four-channel ultrasound detection system is built to demonstrate the parallel detection capability. Compared with the independent detection, the SNR of parallel detection does not deteriorate, proving that the parallel detection system and the sensor array own very low cross talk characteristics. The parallel detection technique paves a way for real-time photoacoustic/ultrasound imaging.

Broadband stimulated Raman imaging based on multi-channel lock-in detection for spectral histopathology

Spontaneous Raman microscopy reveals the chemical composition of a sample in a label-free and non-invasive fashion by directly measuring the vibrational spectra of molecules. However, its extremely low cross section prevents its application to fast imaging. Stimulated Raman scattering (SRS) amplifies the signal by several orders of magnitude thanks to the coherent nature of the nonlinear process, thus unlocking high-speed microscopy applications that provide analytical information to elucidate biochemical mechanisms with subcellular resolution. Nevertheless, in its standard implementation, narrowband SRS provides images at only one frequency at a time, which is not sufficient to distinguish constituents with overlapping Raman bands. Here, we report a broadband SRS microscope equipped with a home-built multichannel lock-in amplifier simultaneously measuring the SRS signal at 32 frequencies with integration time down to 44 µs, allowing for detailed, high spatial resolution mapping of spectrally congested samples. We demonstrate the capability of our microscope to differentiate the chemical constituents of heterogeneous samples by measuring the relative concentrations of different fatty acids in cultured hepatocytes at the single lipid droplet level and by differentiating tumor from peritumoral tissue in a preclinical mouse model of fibrosarcoma.

Design considerations for a cycloidal mass analyzer using a focal plane array detector.

With the advent of technologies such as ion array detectors and high energy permanent magnet materials, there is renewed interest in the unique focusing properties of the cycloidal mass analyzer and its ability to enable small, high-resolution, and high-sensitivity instruments. However, most literature dealing with the design of cycloidal mass analyzers assumes a single channel detector because at the time of those publications, compatible multichannel detectors were not available. This manuscript introduces and discusses considerations and a procedure for designing cycloidal mass analyzers coupled with focal plane ion array detectors. To arrive at a set of relevant design considerations, we first review the unique focusing properties of the cycloidal mass analyzer and then present calculations detailing how the dimensions and position of the focal plane array detector relative to the ion source determine the possible mass ranges and resolutions of a cycloidal mass analyzer. We present derivations and calculations used to determine the volume of homogeneous electric and magnetic fields needed to contain the ion trajectories and explore the relationship between electric and magnetic field homogeneity on resolving power using finite element analysis (FEA) simulations. A set of equations relating the electric field homogeneity to the geometry of the electric sector electrodes was developed by fitting homogeneity values from 78 different FEA models. Finally, a sequence of steps is suggested for designing a cycloidal mass analyzer employing an array detector.

DXYW: a depth-guided multi-channel edge detection model

DXYW: a depth-guided multi-channel edge detection model

Non-Cooperative UAV Detection with Semi-Adaptive Sampling of Control Signal and SNR Estimation

This paper proposes a non-cooperative unmanned aerial vehicle (UAV) signal detection strategy based on a multichannel control signal with an energy detector (ED), wherein the sampling point of the control signal on each subchannel is adjusted with environmental signal-to-noise (SNR) in a semi-adaptive manner. In order to estimate the SNR in the environment, not only is a convolutional neural network (CNN) applied in the proposed signal detection strategy, but a long shor-term memory network (LSTM) network is also included; in terms of features, it combines deep features and time-dimension features. The numbers of layers of the CNN and LSTM impact the performance of the algorithm. The decision on the presence or absence of a control signal is made at the fusion center (FC) based on the majority voting rule. This paper shows that the network with a two-layer CNN and a two-layer LSTM can achieve high estimation accuracy of environmental SNR. Simultaneously, the detection accuracy is improved by about 1 dB compared with the classical multichannel detection schemes.

Multi‐channel attack detection based on lightweight message authentication code access control using Internet of Things design

AbstractThe Internet of Things (IoT) is a network of interconnected, Internet‐connected items that can gather and transmit data without the need for human interaction through a wireless network. Cryptography is a way of using codes to safeguard information and communications so that only those who are supposed to read and process it may do so. Existing system shows privacy and replication issues caused during cipher text attribute set based encryption. The technical issues in achieving secured authentication is removed by using multi‐channel attack detection based on lightweight message authentication code (LMAC) access control using IoT design in which collision attack can be removed by using secure hash algorithm based Merkle tree and to control sinkhole attacks agent navigation algorithm is proposed and long short‐term memory (LSTM) recurrent neural network (RNN) is proposed to provide the conformity of the user login password. Moreover, to identify attackers on the transmitter side by ensuring authentication, multichannel detection method is proposed. Finally, the security and privacy is improved by using LMAC and user revocation. Thus the multi‐channel attack detection based on LMAC using IoT design can be outperforming the other existing model with higher throughput and low execution time.

Global fitting for high-accuracy multi-channel single-molecule localization

Multi-channel detection in single-molecule localization microscopy greatly increases information content for various biological applications. Here, we present globLoc, a graphics processing unit based global fitting algorithm with flexible PSF modeling and parameter sharing, to extract maximum information from multi-channel single molecule data. As signals in multi-channel data are highly correlated, globLoc links parameters such as 3D coordinates or photon counts across channels, improving localization precision and robustness. We show, both in simulations and experiments, that global fitting can substantially improve the 3D localization precision for biplane and 4Pi single-molecule localization microscopy and color assignment for ratiometric multicolor imaging.

Electron energy spectroscopic mapping of surface plasmon by parallel scanning method

In this work, electron energy spectroscopic mapping of surface plasmon of Ag nanostructures on highly oriented pyrolytic graphite is reported. Benefitting from the angular dispersive feature of the present scanning probe electron energy spectrometer, a multi-channel detection mode is developed. By scanning along one direction, the two-dimensional intensity distribution of Ag surface plasmon excitation due to the collision of electron emitted from the tip can be obtained in parallel. The spectroscopic spatial resolution is determined to be around 80 nm.

Оценка эффективности ПЦР тест-систем для контроля деконтаминации объектов окружающей среды, потенциально инфицированных коронавирусом SARS-CoV-2

In the context of the coronavirus pandemic, one of the priority tasks is the disinfection of environmental objects in order to comply with the anti-epidemic regime. In this regard, questions arise regarding the laboratory control of the effectiveness of disinfection measures. The use of virological approaches is hardly acceptable for solving this problem, and the use of fast and affordable methods of molecular genetic analysis comes to the fore, which are certainly of signal value, but sufficient to evaluate the effectiveness of these measures. In this work, studies were carried out on the detection of SARS-CoV-2 coronavirus RNA by several test systems using the real-time polymerase chain reaction method in swabs from various surfaces after they were treated with a disinfectant. The study showed that to control the decontamination of environmental objects potentially infected with the SARS-CoV-2 coronavirus, test systems can be used to detect the RNA of the SARS-CoV-2 virus in clinical samples. The greatest sensitivity is shown for PCR kits in which multichannel detection of individual RNA sites is carried out. Keywords: disinfectants, decontamination control, novel coronavirus infection COVID-19.

Metal foreign body detection based on double/multiple differential coils pair magnetic module

The DDP/MDP (Dual Differential coil Pair/ Multiple Differential coil Pair) module are designed, and a multi-channel detection method for metal foreign bodies is defined based on DDP/MDP module. The DDP/MDP module structure is optimized and designed by loose mathematical modeling and multi-physics electromagnetic simulation according to the BX/Y/Z. A multi-channel detection platform is built based on the 16-bit MDP module composed of 4-bit UQV-DDP modules. Given the standard metal foreign body detection test, the system reaches the optimal metal foreign body detection state, in which the detection area is reduced by 3/4, and the parameter uncertainty is reduced to 0.5%-1.5%, responding to overall the module width range of 60–100 mm, the radius of 150 mm, and the diagonal distance of 200 mm, respectively. By comparative analysis, the accuracy of the multi-channel detection method is 3.0%, and the initial detection value is 5.0 V based on the MDP module. In comparison, the detection accuracy of the multi-channel detection method is 5.0%, and the initial detection value is 3.5 V based on the DDP module. Taking use of 16-bit MDP/DDP module detection platform, the detection accuracy of 3.0% and the initial detection value of 3.5 V can be achieved by the multi-channel detection method based on DDP/MDP module.

Nanoscale Imaging of Interstitial-Dependent Optical Confinement through Near-Field Scanning Optical Microscopy.

Exploitation of optical confinement in nanoscale unveils a wealth of information about the structure, optical, electronic, and chemical properties of the materials. However, realizing such confinement by optical microscopy and spectroscopic techniques have remained challenging due to fundamental formulation that is related to the diffraction theory of light. A state-of-art technique, known as near-field scanning optical microscopy (NSOM) has the ability to break such diffraction limitation, as the spatial resolution depends on the near-field probe diameter and the distance between the probe and the surface. A home-built apertured NSOM (a-NSOM) developed in the beginning of NSOM discovery facilitated to investigate N-particles nano-assemblies, where N is two or more. Through surface-sensitive spectroscopy such as surface-enhanced Raman scattering (SERS) and surface-enhanced two-photon-induced photoluminescence (TPI-PL), a correlated optometrology was revealed by taking snapshots of shear-force topography, SERS and TPI-PL simultaneously in single-channel and multi-channel detection system. Here in this "Personal Account" we have decorated near-field optical confinement observed by a-NSOM in three constructs; archetype dimer, nano-assembly of few nanoparticles and long-range two-dimensional (2D) nano-assembly. In the case of dimer, optical confinement was localized and interstitial-dependent whereas coalescence of nearby confinements was reported in few particles nanoaggregate. In the case of 2D nano-assembly, optical confinements were more complex because a nanoparticle was surrounded by six or more adjacent nanoparticles. FDTD simulation were carried out to support and validate the experimental observations. Such observations in nanoscale taking snapshots of nanometric topography and surface-sensitive spectroscopic signal not only inspire us to understand optical confinements in near-field, but also implement the concept in designing miniaturized and efficient system.