Subtraction Of Signal Research Articles

Novel CRM cosine similarity mapping strategy for simultaneous in-situ visual profiling lignocellulose in plant cell walls

Confocal Raman microscopy (CRM) is a promising in-situ visual technique that provides detailed insights into multiple lignocellulosic components and structures in plant cell walls at the micro-nano scale. In this study, we propose a novel CRM cosine similarity (CS) mapping strategy for the simultaneous in-situ visual profiling of lignin, cellulose, and hemicellulose in plant cell walls. The main stages of this strategy include: 1) a modified Otsu algorithm for extracting the regions of interest (ROI); 2) a modified subtraction method for cleaning the background signals in the ROI spectra; 3) a lignin signal subtraction method based on the pixel correction factor for eliminating the interference of strong lignin signals with weak cellulose and hemicellulose signals in the Raman full spectra of the cell walls; 4) second-order derivative spectral preprocessing for enhancing the discrimination between the characteristic peaks of cellulose and hemicellulose; 5) a CS mapping algorithm for simultaneous in-situ profiling of lignin, cellulose, and hemicellulose in plant cell walls. The effectiveness of the strategy is verified by characterizing the Brittle Culm1 (BC1) gene-mutant rice stem (IL349-BC1-KO) with known bioinformatics. This approach provides methodological support for in-situ visualization and analysis in fields such as plant or crop science at the micro-nano scale.

Mitigating the Blurring Effect of CryoEM Averaging on a Flexible and Highly Symmetric Protein Complex through Sub-Particle Reconstruction.

Many macromolecules are inherently flexible as a feature of their structure and function. During single-particle CryoEM processing, flexible protein regions can be detrimental to high-resolution reconstruction as signals from thousands of particles are averaged together. This "blurring" effect can be difficult to overcome and is possibly more pronounced when averaging highly symmetric complexes. Approaches to mitigating flexibility during CryoEM processing are becoming increasingly critical as the technique advances and is applied to more dynamic proteins and complexes. Here, we detail the use of sub-particle averaging and signal subtraction techniques to precisely target and resolve flexible DARPin protein attachments on a designed tetrahedrally symmetric protein scaffold called DARP14. Particles are first aligned as full complexes, and then the symmetry is reduced by alignment and focused refinement of the constituent subunits. The final reconstructions we obtained were vastly improved over the fully symmetric reconstructions, with observable secondary structure and side-chain placement. Additionally, we were also able to reconstruct the core region of the scaffold to 2.7 Å. The data processing protocol outlined here is applicable to other dynamic and symmetric protein complexes, and our improved maps could allow for new structure-guided variant designs of DARP14.

Subtraction of liposome signals in cryo-EM structural determination of protein–liposome complexes

Abstract Reconstituting membrane proteins in liposomes and determining their structure is a common method for determining membrane protein structures using single-particle cryo-electron microscopy (cryo-EM). However, the strong signal of liposomes under cryo-EM imaging conditions often interferes with the structural determination of the embedded membrane proteins. Here, we propose a liposome signal subtraction method based on single-particle two-dimensional (2D) classification average images, aimed at enhancing the reconstruction resolution of membrane proteins. We analyzed the signal distribution characteristics of liposomes and proteins within the 2D classification average images of protein–liposome complexes in the frequency domain. Based on this analysis, we designed a method to subtract the liposome signals from the original particle images. After the subtraction, the accuracy of single-particle three-dimensional (3D) alignment was improved, enhancing the resolution of the final 3D reconstruction. We demonstrated this method using a PIEZO1-proteoliposome dataset by improving the resolution of the PIEZO1 protein.

Indirect frequency estimation by time-shifted accelerations subtraction: Generalization of the methodology and numerical application on a Warren truss bridge

In the context of Structural Health Monitoring (SHM) of transportation infrastructures, bridge eigen frequencies are commonly adopted as diagnostic indices. Under this regard, as a cost-effective identification methodology, indirect SHM, which consists in the use of sensors installed on running vehicles, is attracting attention. In particular, methods relying on the use of two or more on-board sensors may suppress the influence of track irregularity, which is a remarkable drawback for indirect SHM, and improve the identification accuracy. However, the combination characteristics of the two on-board sensors is still an open issue to be addressed. Also, in many studies, test bridges consist of simple girders, and there are few verifications on complex structures, such as truss bridges. The first contribution of this study is the analytical and generalized expression of the operational range defining the use of time-shifted signals subtraction operation for indirect frequency estimation. After the outcomes provided by this formulation were confirmed by the results obtained from a 2D explanatory example, the proposed procedure was further validated through three-dimensional train-track-bridge dynamic simulations. For this purpose, 3D FE model of a real existing Warren truss bridge, dynamically validated through experimental tests, and a 3D multi-body rail vehicle were adopted. From an engineering standpoint, a relevant result of this study found is that the coexistence of proper sensors onboard positioning and sufficient target bridge component excitation revealed to be crucial for the success of an indirect frequency identification procedure which is based on time-shifted accelerations subtraction.

Comprehensive software suite for functional analysis and synaptic input mapping of dendritic spines imaged in vivo.

Advances in genetically encoded sensors and two-photon imaging have unlocked functional imaging at the level of single dendritic spines. Synaptic activity can be measured in real time in awake animals. However, tools are needed to facilitate the analysis of the large datasets acquired by the approach. Commonly available software suites for imaging calcium transients in cell bodies are ill-suited for spine imaging as dendritic spines have structural characteristics distinct from those of the cell bodies. We present an automated tuning analysis tool (AUTOTUNE), which provides analysis routines specifically developed for the extraction and analysis of signals from subcellular compartments, including dendritic subregions and spines. Although the acquisition of in vivo functional synaptic imaging data is increasingly accessible, a hurdle remains in the computation-heavy analyses of the acquired data. The aim of this study is to overcome this barrier by offering a comprehensive software suite with a user-friendly interface for easy access to nonprogrammers. We demonstrate the utility and effectiveness of our software with demo analyses of dendritic imaging data acquired from layer 2/3 pyramidal neurons in mouse V1 in vivo. A user manual and demo datasets are also provided. AUTOTUNE provides a robust workflow for analyzing functional imaging data from neuronal dendrites. Features include source image registration, segmentation of regions-of-interest and detection of structural turnover, fluorescence transient extraction and smoothing, subtraction of signals from putative backpropagating action potentials, and stimulus and behavioral parameter response tuning analyses. AUTOTUNE is open-source and extendable for diverse functional synaptic imaging experiments. The ease of functional characterization of dendritic spine activity provided by our software can accelerate new functional studies that complement decades of morphological studies of dendrites, and further expand our understanding of neural circuits in health and in disease.

A Direct Current-Sensing VCO-Based 2nd-Order Continuous-Time Sigma-Delta Modulator for Biosensor Readout Applications.

A second-order voltage-controlled oscillator (VCO)-based continuous-time sigma-delta modulator (CTSDM) for current-sensing readout applications is proposed. Current signals from the sensor can directly be quantized by the proposed VCO-based CTSDM, which does not require any extra trans-impedance amplifiers. With the proportional-integral (PI) structure and a VCO phase integrator, the capability of second-order noise shaping is available to reduce the in-band quantization noise. The PI structure can be simply realized by a resistor in series with the integrating capacitor, which can reduce the architecture complexity and maintain the stability of the system. The current-steering digital-to-analog converter with tail and sink current sources is used on the feedback path for the subtraction of the current-type input signal. All the components of the circuit are scaling friendly and applicable to current-sensing readout applications in the Internet of Things (IoT). The proposed VCO-based CTSDM implemented in a 0.18-μm standard CMOS process has a measured signal-to-noise and distortion ratio (SNDR) of 74.6 dB at 10 kHz bandwidth and consumes 44.8 μw only under a supply voltage of 1.2 V, which can achieve a Figure-of-Merit (FoM) of 160.76 dB.

Extraction of the CDRH3 sequence of the mouse antibody repertoire selected upon influenza virus infection by subtraction of the background antibody repertoire.

As specific interactions between antigens and cell-surface antibodies trigger the proliferation of B-cell clones, the frequency of each antibody sequence in the samples reflects the size of each clonal population. Nevertheless, it is extremely difficult to extract antigen-specific antibody sequences from the comprehensive bulk antibody sequences obtained from blood samples due to repertoire bias influenced by exposure to dietary antigens and other infectious agents. This issue can be addressed by subtracting the background noise from the post-immunization or post-infection repertoire data. In the present study, we propose a method to quantify repertoire data from comprehensive repertoire data. This method allowed subtraction of the background repertoire, resulting in more accurate extraction of expanded antibody repertoires upon influenza virus infection. This accurate extraction of antigen- or infection-specific repertoire information is a useful tool for vaccine evaluation.

A rapid method for phosphocreatine-weighted imaging in muscle using double saturation power-chemical exchange saturation transfer.

Monitoring the variation in phosphocreatine (PCr) levels following exercise provides valuable insights into muscle function. Chemical exchange saturation transfer (CEST) has emerged as a sensitive method with which to measure PCr levels in muscle, surpassing conventional MR spectroscopy. However, existing approaches for quantifying PCr CEST signals rely on time-consuming fitting methods that require the acquisition of the entire or a section of the CEST Z-spectrum. Additionally, traditional fitting methods often necessitate clear CEST peaks, which may be challenging to obtain at low magnetic fields. This paper evaluated the application of a new model-free method using double saturation power (DSP), termed DSP-CEST, to estimate the PCr CEST signal in muscle. The DSP-CEST method requires the acquisition of only two or a few CEST signals at the PCr frequency offset with two different saturation powers, enabling rapid dynamic imaging. Additionally, the DSP-CEST approach inherently eliminates confounding signals, offering enhanced robustness compared with fitting methods. Furthermore, DSP-CEST does not demand clear CEST peaks, making it suitable for low-field applications. We evaluated the capability of DSP-CEST to enhance the specificity of PCr CEST imaging through simulations and experiments on muscle tissue phantoms at 4.7 T. Furthermore, we applied DSP-CEST to animal leg muscle both before and after euthanasia and observed successful reduction of confounding signals. The DSP-CEST signal still has contaminations from a residual magnetization transfer (MT) effect and an aromatic nuclear Overhauser enhancement effect, and thus only provides a PCr-weighted imaging. The residual MT effect can be reduced by a subtraction of DSP-CEST signals at 2.6 and 5 ppm. Results show that the residual MT-corrected DSP-CEST signal at 2.6 ppm has significant variation in postmortem tissues. By contrast, both the CEST signal at 2.6 ppm and a conventional Lorentzian difference analysis of CEST signal at 2.6 ppm demonstrate no significant variation in postmortem tissues.

A high precision indoor positioning system of BLE AOA based on ISSS algorithm

This paper investigates the Bluetooth direction finding technique and combines it with the improved signal subtraction subspace (ISSS) algorithm for precise indoor positioning. First, the phase offset caused by the electronic switch is solved by the phase compensation algorithm. Then, the ISSS algorithm is proposed by combining the spatial smoothing techniques algorithm, the density-based spatial clustering of applications with noise (DBSCON) techniques and the signal subtraction subspace (SSS), which reduces the interference of coherent signals and caused by moving between people in the room. Finally, different placement methods for receivers in different spatial shapes are proposed. In this paper, the positioning accuracy of the algorithm is tested using Silicon Labs' Bluetooth device. The results show that the average positioning errors are 0.92 m for single receivers and 0.30 m for dual receivers in a room size of 3 m * 3 m. Therefore, the method has a promising application in achieving accurate indoor positioning.

A robust normalized local filter to estimate compositional heterogeneity directly from cryo-EM maps

Cryo electron microscopy (cryo-EM) is used by biological research to visualize biomolecular complexes in 3D, but the heterogeneity of cryo-EM reconstructions is not easily estimated. Current processing paradigms nevertheless exert great effort to reduce flexibility and heterogeneity to improve the quality of the reconstruction. Clustering algorithms are typically employed to identify populations of data with reduced variability, but lack assessment of remaining heterogeneity. Here we develope a fast and simple algorithm based on spatial filtering to estimate the heterogeneity of a reconstruction. In the absence of flexibility, this estimate approximates macromolecular component occupancy. We show that our implementation can derive reasonable input parameters, that composition heterogeneity can be estimated based on contrast loss, and that the reconstruction can be modified accordingly to emulate altered constituent occupancy. This stands to benefit conventionally employed maximum-likelihood classification methods, whereas we here limit considerations to cryo-EM map interpretation, quantification, and particle-image signal subtraction.

The use of double-integral of experimental EPR spectra for tooth enamel EPR dosimetry.

The presence of background signal in tooth enamel EPR dosimetry is the most challenging situation to overcome. This becomes even more important because it obscures the radiation-induced signal, especially at radiation doses below 1Gy. In order to overcome this problem, subtraction of the unirradiated sample signal from the irradiated one and the simulation methods are the most widely used methods in the literature. These methods have their own difficulties. Obtaining the double integral of the experimental EPR spectra (first derivative) of tooth enamel and its advantages are presented in the present work. This method offers the opportunity to handle the whole experimental spectrum, both background, and radiation-induced signals, without performing any subtraction or simulation operations, and to overcome the signal-to-noise effects.

Application of 3D U-Net-based neutral hydrogen foreground reduction method

Deep learning techniques are gradually making their way into the field of cosmology, bringing new ideas to the foreground subtraction of cosmological signals. This study aims to separate neutral hydrogen signals from the foreground. Traditional methods include principal component analysis (PCA) and singular value decomposition (SVD), but it is not realistic to use these methods alone to completely separate the foreground from the 21 centimeter signal in the universe, Therefore, we use a deep learning method, namely the 3D U-Net network to facilitate separation. We add residual modules to 3D U-Net to avoid network degradation issues, and also considered system effects in the foreground of 3D U-Net subtraction. We use a Gaussian beam model and use power spectrum analysis to compare the results. The analysis of the simulated data training results is shown in Fig. 8. It has been proven that using PCA processing followed by 3D U-Net for foreground subtraction has better consistency than using PCA alone. Therefore, the use of deep learning methods provides a new and effective method for observing neutral hydrogen (HI) to eliminate HI foreground and reveal physical phenomena in the universe.

Toward the rapid diagnosis of sepsis: dendritic copper nanostructure functionalized diazonium salt modified screen-printed graphene electrode for IL-6 detection.

Sepsis, an infectious disease affecting millions of people's health worldwide each year, calls for urgent attention to an improvement of analytical devices. Chemiluminescence immunoassay is a typical diagnostic method utilized to assess the risk development of sepsis. However, due to its high-cost, delayed, and complicated procedure, the practical utilization is therefore undoubtedly limited, especially for point-of-care test. Herein, we fabricated for the first time an immunosensor based on dendritic copper nanostructures (CuNSs) combined with 4-aminobenzoic acid (4-AB, the diazonium salt) as antibody linker modified on a screen-printed graphene electrode for the early detection of the sepsis biomarker interleukin-6 (IL-6). The electrode fabrication is madeby electrodeposition, thus eliminating the multistep of nanomaterial synthesis and time wasting. The resulting dendritic CuNSs significantly increase theeffective surface area (1.2 times) and the sensor's performance. The morphology of this combination was characterized using CV, EIS, SEM, EDX, and FTIR techniques. In the detection process, the appearance of IL-6 suppresses the current response of the redox probe indicator measured by differential pulse voltammetry due to the antibody-antigen complex. The subtraction of signal (ΔI) was interpreted as IL-6 concentration. This sensor exhibited a linear range from 0.05 to 500pgmL-1 with low detection limit of 0.02pgmL-1, proving a possibility for early sepsis screening. In addition, the established immunosensor can successfully quantify IL-6 in human serum sample, in which the results agreed wellwith those achieved using the standard approach, further showing highpractical applicability of this developed immunosensor.

Mock data study for next-generation ground-based detectors: The performance loss of matched filtering due to correlated confusion noise

The next-generation (3G/XG) ground-based gravitational-wave (GW) detectors such as Einstein Telescope (ET) and Cosmic Explorer (CE) will begin observing in the next decade. Due to the extremely high sensitivity of these detectors, the majority of stellar-mass compact-binary mergers in the entire Universe will be observed. It is also expected that 3G detectors will have significant sensitivity down to 2-7 Hz; the observed duration of binary neutron star signals could increase to several hours or days. The abundance and duration of signals will cause them to overlap in time, which may form a confusion noise that could affect the detection of individual GW sources when using naive matched filtering; matched filtering is only optimal for stationary Gaussian noise. We create mock data for CE and ET using the latest population models informed by the GWTC-3 catalog and investigate the performance loss of matched filtering due to overlapping signals. We find the performance loss mainly comes from a deviation in the noise's measured amplitude spectral density. The redshift reach of CE (ET) can be reduced by 15%-38% (8%-21%) depending on the merger rate estimate. The direct contribution of confusion noise to the total signal-to-noise ratio (SNR) is generally negligible compared to the contribution from instrumental noise. We also find that correlated confusion noise has a negligible effect on the quadrature summation rule of network SNR for ET, but might reduce the network SNR of high detector-frame mass signals for detector networks including CE if no mitigation is applied. For ET, the null stream can mitigate the astrophysical foreground. For CE, we demonstrate that a computationally efficient, straightforward single-detector signal subtraction method suppresses the total noise to almost the instrument noise level; this will allow for near-optimal searches.

Frequency modulation stimulated Raman scattering scheme for real-time background correction with a single light source.

A frequency modulation (FM) scheme for stimulated Raman scattering (SRS) is presented with a single fiber-based light source. Pulse-to-pulse wavelength-switching allows real-time subtraction of parasitic signals leaving only the resonant SRS signal with a noise reduction of up to 30 % compared to digital subtraction schemes, leading effectively to a contrast improvement by a factor of up to 8.3. The wide tuning range of the light source from 1500 cm-1 to 3000 cm-1 and the possibility to separately adjust the resonant and the nonresonant wavenumber for every specimen allow to investigate a variety of samples with high contrast and high signal-to-noise ratio, e. g., for medical diagnostics.

Grating Lobe Reduction in Plane-Wave Imaging With Angular Compounding Using Subtraction of Coherent Signals.

Plane-wave imaging (PWI) with angular compounding has gained in popularity over recent years, because it provides high frame rates and good image properties. However, most linear arrays used in clinical practice have a pitch that is equal to than the wavelength of ultrasound. Hence, the presence of grating lobes is a concern for PWI using multiple transmit angles. The presence of grating lobes produces clutter in images and reduces the ability to observe tissue contrast. Techniques to reduce or eliminate the presence of grating lobes for PWI using multiple angles will result in improved image quality. Null subtraction imaging (NSI) is a nonlinear beamforming technique that has been explored for improving the lateral resolution of ultrasonic imaging. However, the apodization scheme used in NSI also eliminates or greatly reduces the presence of grating lobes. Imaging tasks using NSI were evaluated in simulations and physical experiments involving tissue-mimicking phantoms and rat tumors in vivo. Images created with NSI were compared with images created using traditional delay and sum (DAS) with Hann apodization and images created using a generalized coherence factor (GCF). NSI was observed to greatly reduce the presence of grating lobes in ultrasonic images, compared to DAS with Hann and GCF, while maintaining spatial resolution and contrast in the images. Therefore, NSI can provide a novel means of creating images using PWI with multiple steering angles on clinically available linear arrays while reducing the adverse effects associated with grating lobes.

Constraining the stochastic gravitational wave background with photometric surveys

The detection of the Stochastic Gravitational Wave Background (SGWB) is essential for understanding black hole populations, especially for supermassive black hole binaries. The recent promising results from various Pulsar Timing Array (PTA) collaborations allude to an imminent detection. In this paper, we investigate the relative astrometric gravitational wave detection method, which can contribute to SGWB studies in the microhertz range. We consider the Roman Space Telescope and Gaia as candidates and quantitatively discuss the survey sensitivity in both the frequency and spatial domains. We emphasize the importance of survey specific constraints on performance estimates by considering mean field of view (FoV) signal subtraction and angular power spectrum binning. We conclude that if the SGWB is at a similar level as in PTA estimates, both Roman and Gaia have the potential to detect this frequency-domain power excess. However, both Roman and Gaia are subject to FoV limitations, and are unlikely to be sensitive to the spatial pattern of the SGWB.

Interleaved NQR detection using atomic magnetometers

Interleaved Nuclear Quadrupole Resonance (NQR) detection was conducted on ammonium nitrate and potassium chlorate using two 87Rb magnetometers, where potassium chlorate is measured during the T1 limited recovery time of ammonium nitrate. The multi-pass magnetometers are rapidly matched to the NQR frequencies, 531 kHz and 423 kHz, with the use of a single tuning field. For ease of implementation, a double resonant tank circuit was used for excitation, but could be replaced by a broad-band transmitter. All work was done in an unshielded environment and compared to conventional coil detection. The two magnetometers were sensitive, base noise as low as 2 fT/Hz, and were shown to reduce ambient noise through signal subtraction. When an excitation pulse was introduced, however, residual ringing increased the noise floor; mitigation techniques are discussed. The two detection techniques resulted in comparable Signal-to-Noise Ratio (SNR). Interleaved detection using the atomic magnetometers took half the time of conventional detection and provided localization of the explosives.

Intercomparison of OH radical measurement in a complex atmosphere in Chengdu, China.

Atmospheric oxidation is a driving force of complex air pollution, and accurate hydroxyl radical (OH) measurement is helpful in investigating the radical-cored photooxidation mechanism in the troposphere. A self-developed laser-induced fluorescence instrument by the Anhui Institute of Optics Fine Mechanics, Chinese Academy of Sciences (AIOFM-LIF), was able to measure OH concentration with high sensitivity and good time resolution, and a detection limit of 1.7 × 105 cm-3 (1σ, 30 s). A long-period, multi-level intercomparison of hydroxyl radical (OH) measurements between AIOFM-LIF and PKU-LIF (the Peking University laser-induced fluorescence system) was conducted in Chengdu, China. The measurement between two instruments was in excellent agreement in the 5-min time resolution. Linear regression analysis reported a linear slope of 0.96 with a 0.68 × 106 cm-3 offset, and the correlation coefficient R2 was 0.85. The overall linearity with only a slight offset indicated a negligible influence on OH measurement. No noticeable artifacts from ozonolysis were observed under the condition of high ozone and ozonolysis-related compound concentrations. In addition to the subtraction of background signal through wavelength modulation, the dynamic correction on ozone photolysis interference ensured high intercomparison quality in both relatively constant and rapidly varying periods. Based on the reliability of OHAIOFM and OHPKU, comparisons under different oxidation-related species (NOx, VOCs, O3, PM2.5) levels and typical scenarios (rich-BVOC and high-reactivity) were carried out to evaluate the performance under complex atmospheres. A slightly higher drift was observed in a certain scenario, but the general data variability due to environmental changes did not affect the measurement accuracy. The intercomparison demonstrated that both systems are able to achieve reliable OH data under typical conditions of complex atmospheric pollution in China. Additional improvements are necessary for future intercomparisons in order to enhance the confidence in OH detection accuracy.

On the use of polychromatic cameras for high spatial resolution spectral dose measurements

Objective. Despite the demonstrated benefits of hyperspectral formalism for stem effect corrections in the context of fiber dose measurements, this approach has not been yet translated into volumetric measurements where cameras are typically used for their distinguishing spatial resolution. This work investigates demosaicing algorithms for polychromatic cameras based spectral imaging. Approach. The scintillation and Cherenkov signals produced in a radioluminescent phantom are imaged by a polychromatic camera and isolated using the spectral formalism. To do so, five demosaicing algorithms are investigated from calibration to measurements: a clustering method and four interpolation algorithms. The resulting accuracy of scintillation and Cherenkov images is evaluated with measurements of the differences (mean ± standard deviation) between the obtained and expected signals from profiles drawn across a scintillation spot. Signal-to-noise ratio and signal-to-background ratio are further measured and compared in the resulting scintillation images. Finally, the resulting differences on the scintillation signal from a 0.2 × 0.2 cm2 region-of-interest (ROI) were reported. Main results. Clustering, OpenCV, bilinear, Malvar and Menon demosaicing algorithms respectively yielded differences of 3 ± 5%, 1 ± 3%, 1 ± 3%, 1 ± 2% and 2 ± 4% in the resulting scintillation images. For the Cherenkov images, all algorithms provided differences below 1%. All methods enabled measurements over the detectability (SBR > 2) and sensitivity (SNR > 5) thresholds with the bilinear algorithm providing the best SNR value. Clustering, OpenCV, bilinear, Malvar and Menon demosaicing algorithms respectively provided differences on the ROI analysis of 7 ± 5%, 3 ± 2%, 3 ± 2%, 4 ± 2%, 7 ± 3%. Significance. Radioluminescent signals can accurately be isolated using a single polychromatic camera. Moreover, demosaicing using a bilinear kernel provided the best results and enabled Cherenkov signal subtraction while preserving the full spatial resolution of the camera.