scholarly journals An aptamer-based magnetic flow cytometer using matched filtering

2020 ◽  
Author(s):  
Chih-Cheng Huang ◽  
Partha Ray ◽  
Matthew Chan ◽  
Xiahan Zhou ◽  
Drew A. Hall
Keyword(s):  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Point Of Care ◽  
Spin Valve ◽  
Noncommunicable Diseases ◽  
Matched Filtering ◽  
Detection Accuracy ◽  
Cell Detection ◽  
Magnetic Flow ◽  
Sensor Geometry

AbstractFacing unprecedented population-ageing, the management of noncommunicable diseases (NCDs) urgently needs a point-of-care (PoC) testing infrastructure. Magnetic flow cytometers are one such solution for rapid cancer cellular detection in a PoC setting. In this work, we report a giant magnetoresistive spin-valve (GMR SV) biosensor array with a multi-stripe sensor geometry and matched filtering to improve detection accuracy without compromising throughput. The carefully designed sensor geometry generates a characteristic signature when cells labeled with magnetic nanoparticles (MNPs) pass by thus enabling multi-parametric measurement like optical flow cytometers (FCMs). Enumeration and multi-parametric information were successfully measured across two decades of throughput. 10-µm polymer microspheres were used as a biomimetic model where MNPs and MNP-decorated polymer conjugates were flown over the GMR SV sensor array and detected with a signal-to-noise ratio (SNR) as low as 2.5 dB due to the processing gain afforded by the matched filtering. The performance was compared against optical observation, exhibiting a 92% detection efficiency. The system achieved a 95% counting accuracy for biomimetic models and 98% for aptamer-based pancreatic cancer cell detection. This system demonstrates the ability to perform reliable PoC diagnostics towards the benefit for NCD control plans.

scholarly journals Overcoming detection loss and noise in squeezing-based optical sensing

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Gaetano Frascella ◽  
Sascha Agne ◽  
Farid Ya. Khalili ◽  
Maria V. Chekhova
Keyword(s):  
Shot Noise ◽  
Optical Sensing ◽  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Real Life ◽  
Squeezed States ◽  
Squeezed Light ◽  
Noise Limit ◽  
Imaging And Spectroscopy ◽  
Shot Noise Limit

AbstractAmong the known resources of quantum metrology, one of the most practical and efficient is squeezing. Squeezed states of atoms and light improve the sensing of the phase, magnetic field, polarization, mechanical displacement. They promise to considerably increase signal-to-noise ratio in imaging and spectroscopy, and are already used in real-life gravitational-wave detectors. But despite being more robust than other states, they are still very fragile, which narrows the scope of their application. In particular, squeezed states are useless in measurements where the detection is inefficient or the noise is high. Here, we experimentally demonstrate a remedy against loss and noise: strong noiseless amplification before detection. This way, we achieve loss-tolerant operation of an interferometer fed with squeezed and coherent light. With only 50% detection efficiency and with noise exceeding the level of squeezed light more than 50 times, we overcome the shot-noise limit by 6 dB. Sub-shot-noise phase sensitivity survives up to 87% loss. Application of this technique to other types of optical sensing and imaging promises a full use of quantum resources in these fields.

Weak Transient Electromagnetic Radiation Signal Detection Method Considering the New Watershed Image Segmentation Algorithm

2019 ◽  
Vol 34 (03) ◽  
pp. 2054009
Author(s):  
Wenjun Huo ◽  
Peng Chu ◽  
Kai Wang ◽  
Liangting Fu ◽  
Zhigang Niu ◽  
...  
Keyword(s):  
Electromagnetic Radiation ◽  
Cross Correlation ◽  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Detection Methods ◽  
Signal To Noise ◽  
Long Distance ◽  
Transient Electromagnetic ◽  
Noise Ratio

In order to study the detection methods of weak transient electromagnetic radiation signals, a detection algorithm integrating generalized cross-correlation and chaotic sequence prediction is proposed in this paper. Based on the dual-antenna test and cross-correlation information estimation method, the detection of aperiodic weak discharge signals under low signal-to-noise ratio is transformed into the estimation of periodic delay parameters, and the noise is reduced at the same time. The feasibility of this method is verified by simulation and experimental analysis. The results show that under the condition of low signal-to-noise ratio, the integrated method can effectively suppress the influence of 10 noise disturbances. It has a high detection probability for weak transient electromagnetic radiation signals, and needs fewer pulse accumulation times, which improves the detection efficiency and is more suitable for long-distance detection of weak electromagnetic radiation sources.

scholarly journals Cellulose and Vanadium Plasmonic Sensor to Measure Ni2+ Ions

2021 ◽  
Vol 11 (7) ◽  
pp. 2963
Author(s):  
Nur Alia Sheh Omar ◽  
Yap Wing Fen ◽  
Irmawati Ramli ◽  
Umi Zulaikha Mohd Azmi ◽  
Hazwani Suhaila Hashim ◽  
...  
Keyword(s):  
Thin Film ◽  
Surface Plasmon Resonance ◽  
Surface Plasmon ◽  
Plasmon Resonance ◽  
Signal To Noise Ratio ◽  
Affinity Constant ◽  
Detection Accuracy ◽  
Plasmonic Sensor ◽  
Spr Sensor ◽  
Resonance Sensor

A novel vanadium–cellulose composite thin film-based on angular interrogation surface plasmon resonance (SPR) sensor for ppb-level detection of Ni(II) ion was developed. Experimental results show that the sensor has a linear response to the Ni(II) ion concentrations in the range of 2–50 ppb with a determination coefficient (R2) of 0.9910. This SPR sensor can attain a maximum sensitivity (0.068° ppb−1), binding affinity constant (1.819 × 106 M−1), detection accuracy (0.3034 degree−1), and signal-to-noise-ratio (0.0276) for Ni(II) ion detection. The optical properties of thin-film targeting Ni(II) ions in different concentrations were obtained by fitting the SPR reflectance curves using the WinSpall program. All in all, the proposed Au/MPA/V–CNCs–CTA thin-film-based surface plasmon resonance sensor exhibits better sensing performance than the previous film-based sensor and demonstrates a wide and promising technology candidate for environmental monitoring applications in the future.

scholarly journals A large area diamond-based beam tagging hodoscope for ion therapy monitoring

2018 ◽  
Vol 170 ◽  
pp. 09005 ◽  
Author(s):  
M.-L. Gallin-Martel ◽  
L. Abbassi ◽  
A. Bes ◽  
G. Bosson ◽  
J. Collot ◽  
...  
Keyword(s):  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Therapy Monitoring ◽  
Chemical Vapor ◽  
X Rays ◽  
Reaction Products ◽  
Large Area ◽  
Position Measurement ◽  
Set Up ◽  
Good Signal

The MoniDiam project is part of the French national collaboration CLaRyS (Contrôle en Ligne de l’hAdronthérapie par RaYonnements Secondaires) for on-line monitoring of hadron therapy. It relies on the imaging of nuclear reaction products that is related to the ion range. The goal here is to provide large area beam detectors with a high detection efficiency for carbon or proton beams giving time and position measurement at 100 MHz count rates (beam tagging hodoscope). High radiation hardness and intrinsic electronic properties make diamonds reliable and very fast detectors with a good signal to noise ratio. Commercial Chemical Vapor Deposited (CVD) poly-crystalline, heteroepitaxial and monocrystalline diamonds were studied. Their applicability as a particle detector was investigated using α and β radioactive sources, 95 MeV/u carbon ion beams at GANIL and 8.5 keV X-ray photon bunches from ESRF. This facility offers the unique capability of providing a focused (~1 μm) beam in bunches of 100 ps duration, with an almost uniform energy deposition in the irradiated detector volume, therefore mimicking the interaction of single ions. A signal rise time resolution ranging from 20 to 90 ps rms and an energy resolution of 7 to 9% were measured using diamonds with aluminum disk shaped surface metallization. This enabled us to conclude that polycrystalline CVD diamond detectors are good candidates for our beam tagging hodoscope development. Recently, double-side stripped metallized diamonds were tested using the XBIC (X Rays Beam Induced Current) set-up of the ID21 beamline at ESRF which permits us to evaluate the capability of diamond to be used as position sensitive detector. The final detector will consist in a mosaic arrangement of double-side stripped diamond sensors read out by a dedicated fast-integrated electronics of several hundreds of channels.

Dynamical Detection of Magnetic Nanoparticles in Paper Microfluidics With Spin Valve Sensors for Point-of-Care Applications

2014 ◽  
Vol 50 (11) ◽  
pp. 1-4 ◽  
Author(s):  
Alexandre Chicharo ◽  
Filipe Cardoso ◽  
Susana Cardoso ◽  
Paulo P. Freitas
Keyword(s):  
Magnetic Nanoparticles ◽  
Point Of Care ◽  
Spin Valve ◽  
Paper Microfluidics

scholarly journals Artificial Neural Networks for Automated Cell Quantification in Lensless LED Imaging Systems

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 989 ◽  
Author(s):  
Agus Budi Dharmawan ◽  
Gregor Scholz ◽  
Shinta Mariana ◽  
Philipp Hörmann ◽  
Igi Ardiyanto ◽  
...  
Keyword(s):  
Neural Networks ◽  
Principal Component Analysis ◽  
Artificial Neural Networks ◽  
Light Emitting Diode ◽  
Principal Component ◽  
Component Analysis ◽  
Detection Accuracy ◽  
Cell Detection ◽  
Artificial Neural ◽  
Feature Values

Cell registration by artificial neural networks (ANNs) in combination with principal component analysis (PCA) has been demonstrated for cell images acquired by light emitting diode (LED)-based compact holographic microscopy. In this approach, principal component analysis was used to find the feature values from cells and background, which would be subsequently employed as neural inputs into the artificial neural networks. Image datasets were acquired from multiple cell cultures using a lensless microscope, where the reference data was generated by a manually analyzed recording. To evaluate the developed automatic cell counter, the trained system was assessed on different data sets to detect immortalized mouse astrocytes, exhibiting a detection accuracy of ~81% compared with manual analysis. The results show that the feature values from principal component analysis and feature learning by artificial neural networks are able to provide an automatic approach on the cell detection and registration in lensless holographic imaging.

scholarly journals The theory and application of the random dislocation directional seismic wave technique in a tunnel environment

2019 ◽  
Vol 16 (5) ◽  
pp. 939-949
Author(s):  
Yonggao Yue ◽  
Tao Jiang ◽  
Jingye Wang ◽  
Yunfeng Chao ◽  
Qi Zhou ◽  
...  
Keyword(s):  
Seismic Wave ◽  
Signal To Noise Ratio ◽  
Random Noise ◽  
Geological Structure ◽  
Detection Accuracy ◽  
Detection Distance ◽  
Geological Structures ◽  
Multiple Wave ◽  
Geological Conditions ◽  
Wave Technique

Abstract Performing exact predictions of geological conditions for tunnel construction is important for ensuring safe and quick tunnel engineering. Weak effective signals and strong random noise are the main factors that affect the distance and precision of tunnel seismic detection. Considering that directional seismic wave (DSW) technology has the ability to enhance target signals and suppress random noise, we attempt to apply this method to solve the problems of low detection accuracy and short detection distance. However, the process of data processing with the DSW technique generates false multiple wave interference (FMWI), which can lead to the misinterpretation of geological structures. This study analyses the origins of FMWI and presents the random dislocation directional seismic wave (RDDSW) method to suppress this interference. The results of a numerical simulation indicate that the FMWI is effectively suppressed and that the signal-to-noise ratio of the data is increased by approximately N times through use of the N-element RDDSW technique. In the ideal case, only spherical diffusion attenuation is considered, and the detection distance increases by approximately $\scriptstyle\sqrt N $ times. In addition, this method is also effective for signals from curved events, thereby improving the precision of the analysis of the geological structure of the tunnel. Furthermore, the field data results further verify that the RDDSW technique can significantly suppress interference and thus improve the quality of the data at little cost. Hence, the RDDSW technique has great significance for accurately predicting the geological structures of tunnels and increasing the detection distance in tunnels.

scholarly journals Hemolysis detection based on SVM of Adaboost classification algorithm

2018 ◽  
Vol 173 ◽  
pp. 03006
Author(s):  
xiaonan Shi ◽  
Zitong Wang ◽  
Zhenmin Zhao
Keyword(s):  
Detection Efficiency ◽  
Test Sample ◽  
Cell Counting ◽  
Detection Accuracy ◽  
Target Area ◽  
Gray Level ◽  
Adaboost Algorithm ◽  
Weak Learner ◽  
Basic Features ◽  
Blood Cell Counting

Aiming at the problem that clinical hemolysis is difficult to be observed and judged, a method of Adaboost learning classification based on SVM is proposed. The method firstly extracts the basic features of the target area of the blood sample, such as the average of the gray level, the standard deviation of the gray level and the appearance frequency of the particles, as the input eigenvectors of the learning, and carries out SVM weak learner learning. Subsequently, Adaboost algorithm is used to measure the weak learner Set linear weighting, so as to enhance the strong learning device; Finally, online testing, calculation of test sample hemolytic degree and classification. The Adaboost learning classification test based on SVM is compared with the macroscopic and red blood cell counting methods. The experimental results show that the learning-based classification testing method achieves higher detection accuracy without subjective factors and has the highest detection efficiency.

scholarly journals Performance Validation of a Planar Hall Resistance Biosensor through Beta-Amyloid Biomarker

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 434 ◽  
Author(s):  
SungJoon Kim ◽  
Sri Ramulu Torati ◽  
Artem Talantsev ◽  
ChangYeop Jeon ◽  
SungBae Lee ◽  
...  
Keyword(s):  
Magnetic Field ◽  
External Magnetic Field ◽  
Second Harmonic ◽  
Signal To Noise Ratio ◽  
Point Of Care ◽  
Magnetic Sensors ◽  
Hall Resistance ◽  
Field Mode ◽  
Mode Method ◽  
Performance Validation

Magnetic sensors have great potential for biomedical applications, particularly, detection of magnetically-labeled biomolecules and cells. On the basis of the advantage of the planar Hall effect sensor, which consists of improved thermal stability as compared with other magnetic sensors, we have designed a portable biosensor platform that can detect magnetic labels without applying any external magnetic field. The trilayer sensor, with a composition of Ta (5 nm)/NiFe (10 nm)/Cu (x = 0 nm~1.2 nm)/IrMn (10 nm)/Ta (5 nm), was deposited on a silicon wafer using photolithography and a sputtering system, where the optimized sensor sensitivity was 6 μV/(Oe∙mA). The detection of the magnetic label was done by comparing the signals obtained in first harmonic AC mode (1f mode) using an external magnetic field and in the second harmonic AC mode (2f mode) with a self-field generated by current passing through the sensor. In addition, a technique for the β-amyloid biomarker-based antibody-antigen sandwich model was demonstrated for the detection of a series of concentrations of magnetic labels using the self-field mode method, where the signal-to-noise ratio (SNR) was high. The generated self-field was enough to detect an immobilized magnetic tag without an additional external magnetic field. Hence, it could be possible to reduce the device size to use the point-of-care testing using a portable circuit system.

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