Detection Volume Research Articles

A simulation study on the sub-threshold joint gravitational wave-electromagnetic wave observation on binary neutron star mergers

Abstract The coalescence of binary neutron stars (BNS) is a prolific source of gravitational waves (GWs) and electromagnetic (EM) radiation, offering a dual observational window into the Universe. Lowering the signal-to-noise ratio (S/N) threshold is a simple and cost-effective way to enhance the detection probability of GWs from BNS mergers. In this study, we introduce a metric of the purity of joint GW and EM detections Pjoint, which is in analogue to Pastro in GW only observations. By simulating BNS merger GWs jointly detected by the HLV network and EM counterparts (kilonovae and short Gamma-ray bursts, sGRBs) with an assumed merger rate density of BNS, we generate catalogs of GW events and EM counterparts. Through this simulation, we analyze joint detection pairs, both correct and misidentified. We find the following: 1. For kilonovae, requiring Pjoint > 95% instead of $P_{\rm astro}>95~{{\%}}$ reduces the S/N from 9.2 to 8.5-8.8, allowing 5-13 additional joint detections per year and increasing the GW detection volume by 9-17%; 2. For sGRBs, requiring Pjoint > 95% instead of Pastro reduces the S/N from 9.2 to 8.1-8.5; 3. Increasing kilonova or sGRB detection capability does not improve Pjoint due to a higher rate of misidentifications. We also show that sub-threshold GW and kilonova detections can reduce the uncertainty in measuring the Hubble constant to 89-92% of its original value, and sub-threshold GW and sGRB observations can enhance the precision of constraining the speed of GWs to 88% of previously established values.

A vision-based dietary survey and assessment system for college students in China

Understanding the current dietary habits of college students is essential due to the pressing issues of unbalanced diets and insufficient nutrition. However, traditional approaches frequently depend on recollection, which can introduce unconscious bias and make them difficult to implement. Herein, we introduce a new computer vision system to evaluate the dietary habits of college students in China. A specialized food dataset comprising RGB-D images, recipes with ingredient masses, and nutrient composition was created using data collected from college canteens. First, object detection models were utilized to identify food categories and locations. Subsequently, we introduced a method for automatically estimating the food volume of nonstandard portions using position and depth information. The final nutrients were derived directly or indirectly through the database. Experimental results demonstrate the applicability of the YOLOv8 object detection model and volume estimation method to our tasks. To support the development of devices for detecting food intake and diet management, we have made our dataset publicly available. The College Canteen Food-100 dataset is publicly available at https://github.com/zichengzichengzi/CC-FOOD-100.

Photothermal Backscatter Interferometry for Enhanced Detection in Capillary Electrophoresis.

Refractive index (RI) detection using backscatter interferometry (BSI) enables universal detection in capillary electrophoresis (CE). BSI detection is a versatile on-capillary approach that is easily integrated with capillary or microfluidic channels, straightforward to miniaturize, and inexpensive. The focused BSI light source can also double as the excitation source for fluorescence, enabling simultaneous universal (BSI) and specific (fluorescence) signals from the same detection volume. To improve BSI detection and expand orthogonal content, we integrate photothermal absorption with BSI detection. Nonradiative relaxation of an excited analyte releases heat into the surroundings, which modifies both the local RI and conductivity (viscosity) of the analyte zone. We recently showed that the BSI signal is sensitive to both RI and conductivity, which makes photothermal absorption a promising route to signal enhancement. Here, we use coaxially delivered BSI and photothermal absorption beams to characterize BSI, photothermal BSI, and fluorescence detection using the separation of test samples. We show that photothermal absorption leads to 3 orders of magnitude improvement in BSI detection limits at the powers studied and provides new opportunities for studying binding interactions with CE.

Effective lifetime of Ni laser induced fluorescence excited at 336.9 nm during spark plug discharge

In this study, the laser induced fluorescence lifetime of Ni atoms in ambient air with presence of a plasma discharge was measured for the first time. Free Ni atoms were generated in air at a pressure of 1 bar by spark plug discharges driven by an inductive coil. The Ni atoms were excited at the 336.957 nm absorption line by a 336.96 nm, 90 ps laser pulse and the resulting temporally resolved decaying fluorescence signals were captured by a PMT. An effective fluorescence lifetime of about 1.1 ns was observed for the fluorescence signal within a 7.4 nm detection window centered at 345 nm. Further analysis also revealed that the lifetime of the transition showed statistically insignificant change throughout the duration of the discharge. The peak intensity of the fluorescence signal was found to be proportional to the integrated signal intensities. This in turn suggests that the integrated fluorescence signals in the aforementioned spectral region are proportional to the population density of ground state Ni atoms in the detection volume. The number density of free Ni atoms in the spark gap was measured over time during the plasma discharge, showing an accumulating trend in the beginning phase of the discharge followed by a slow decrease until the termination.

Characterization of the BOLDPET optical prototype, an innovative Cherenkov detector for 511 keV γ radiation

In the present work we describe the design, construction, and testing of the optical prototype developed for the BOLDPET project, with the objective of creating a PET detection module with high spatial and time resolution. The BOLDPET technology uses an innovative detection liquid, trimethylbismuth, for detecting 511 keV γ-quanta resulting from positron annihilation. The optical signal is exclusively produced through the Cherenkov mechanism, and the produced photons are detected using Planacon microchannel-plate photomultiplier. We achieve an excellent time resolution of 150 ps (FWHM) within a sizable detection volume measuring 55 mm× 55 mm× 25 mm. Through detailed Geant4 simulations, we examine the limiting factors affecting time resolution and explore potential avenues for improvement. Furthermore, we demonstrate the feasibility of coarse 2D localization of interactions using the optical signal alone, achieving a precision of about 5–8 mm (FWHM) within the homogeneous detection volume.

Detection and validation of common noctule bats (Nyctalus noctula) with a pulse radar and acoustic monitoring in the proximity of an onshore wind turbine.

This paper presents the results of bats detected with marine radar and their validation with acoustic detectors in the vicinity of a wind turbine with a hub height of 120 m. Bat detectors are widely used by researchers, even though the common acoustic detectors can cover only a relatively small volume. In contrast, radar technology can overcome this shortcoming by offering a large detection volume, fully covering the rotor-swept areas of modern wind turbines. Our study focused on the common noctule bats (Nyctalus noctula). The measurement setup consisted of a portable X-band pulse radar with a modified radar antenna, a clutter shielding fence, and an acoustic bat detector installed in the wind turbine's nacelle. The radar's detection range was evaluated using an analytical simulation model. We developed a methodology based on a strict set of criteria for selecting suitable radar data, acoustic data and identified bat tracks. By applying this methodology, the study data was limited to time intervals with an average duration of 48 s, which is equal to approximately 20 radar images. For these time intervals, 323 bat tracks were identified. The most common bat speed was extracted to be between 9 and 10 m/s, matching the values found in the literature. Of the 323 identified bat tracks passed within 80 m of the acoustic detector, 32% had the potential to be associated with bat calls due to their timing, directionality, and distance to the acoustic bat detector. The remaining 68% passed within the studied radar detection volume but out of the detection volume of the acoustic bat detector. A comparison of recorded radar echoes with the expected simulated values indicated that the in-flight radar cross-section of recorded common noctule bats was mostly between 1.0 and 5.0 cm2, which is consistent with the values found in the literature for similar sized wildlife.

Forecasting the volume of defect detection works on a river fleet vessel hull

Forecasting the volume of defect detection works on a river fleet vessel hull

AI-Driven Spectral Decomposition: Predicting the Most Probable Protein Compositions from Surface Enhanced Raman Spectroscopy Spectra of Amino Acids.

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for elucidating the molecular makeup of materials. It possesses the unique characteristics of single-molecule sensitivity and extremely high specificity. However, the true potential of SERS, particularly in capturing the biochemical content of particles, remains underexplored. In this study, we harnessed transformer neural networks to interpret SERS spectra, aiming to discern the amino acid profiles within proteins. By training the network on the SERS profiles of 20 amino acids of human proteins, we explore the feasibility of predicting the predominant proteins within the µL-scale detection volume of SERS. Our results highlight a consistent alignment between the model's predictions and the protein's known amino acid compositions, deepening our understanding of the inherent information contained within SERS spectra. For instance, the model achieved low root mean square error (RMSE) scores and minimal deviation in the prediction of amino acid compositions for proteins such as Bovine Serum Albumin (BSA), ACE2 protein, and CD63 antigen. This novel methodology offers a robust avenue not only for protein analytics but also sets a precedent for the broader realm of spectral analyses across diverse material categories. It represents a solid step forward to establishing SERS-based proteomics.

Miner pose detection algorithm based on improved YOLOv7 in the coal mine

The unsafe behavior of workers in underground mines is a major cause of accidents. Recently, deep learning technology has become more and more widely used in the computer field and has achieved remarkable results, providing new opportunities for the research of miner behavior recognition algorithms. To address the current problem of large computation volume and low detection efficiency of multi-person posture detection in underground mines, we propose an improved algorithm that introduces the GSConv convolution module into the YOLOv7-Pose model and replaces the ELEN-W module with the GSELEN module to accelerate model convergence. We also introduce a group-convolution reconstruction SPPCSPC module to reduce parameter load and calculation amount and reduce the original 17 joint points to 14 joints to further realize a lightweight model. The experimental results showed that the improved YOLOv7-Pose model in this study decreased to 135.7 MB, by about 18.8%, while maintaining model accuracy. Therefore, this improvement can achieve a lightweight algorithm and improve real-time posture detection of construction workers in underground mines while ensuring model accuracy.

Accurate Identification of Motoneuron Discharges From Ultrasound Images Across the Full Muscle Cross-Section.

Non-invasive identification of motoneuron (MN) activity commonly uses electromyography (EMG). However, surface EMG (sEMG) detects only superficial sources, at less than approximately 10-mm depth. Intramuscular EMG can detect deep sources, but it is limited to sources within a few mm of the detection site. Conversely, ultrasound (US) images have high spatial resolution across the whole muscle cross-section. The activity of MNs can be extracted from US images due to the movements that MN activation generates in the innervated muscle fibers. Current US-based decomposition methods can accurately identify the location and average twitch induced by MN activity. However, they cannot accurately detect MN discharge times. Here, we present a method based on the convolutive blind source separation of US images to estimate MN discharge times with high accuracy. The method was validated across Ten participants using concomitant sEMG decomposition as the ground truth. 140 unique MN spike trains were identified from US images, with a rate of agreement (RoA) with sEMG decomposition of 87.4 ± 10.3%. Over 50% of these MN spike trains had a RoA greater than 90%. Furthermore, with US, we identified additional MUs well beyond the sEMG detection volume, at up to >30 mm below the skin. The proposed method can identify discharges of MNs innervating muscle fibers in a large range of depths within the muscle from US images. The proposed methodology can non-invasively interface with the outer layers of the central nervous system innervating muscles across the full cross-section.

Achievement of Sub‐Diffractive Detection Depth in Absorption Spectroscopy Using Excitation from an Upconverting Particle

Conventionally, a collimated visible laser beam can only be focused to a transverse region volume with a waist of about 200 nm and an axial waist of about 1200 nm due to the wave nature of light. Several techniques have been used to bypass the diffraction limit, including a recently developed one using the emission from an optically trapped upconverting nanoparticle. This nanoparticle has a diameter smaller than 200 nm, such that it emits like a dipole into a 45° cone. Thus, not only is the emission coming from a particle smaller in size than the waist of the diffraction‐limited spot but also the cone is smaller than that of the volume of a very tightly focused beam. Here, the technique is developed even further where the emission coming from a specific region of the cone is selected by an optical fiber‐based pinhole in the detection path. Using this technique, a confocal depth of about 200 nm is achieved as the overlap between the emission cone and the detection volume. This would correspond to a volume of about 250 attoliters for a 1.5 μm diameter particle which can be reduced to 40 attoliters by using a 500 nm diameter particle.

Identifying Exchangeable Protons in a 1D NMR Spectrum by Spatially Selective Exchange-Editing.

Signals undergoing chemical or conformational exchange in one-dimensional NMR spectra are often identified by deuterium exchange. In order to obtain quantitative information about the dynamic processes involved, one frequently used method is EXchange SpectroscopY (EXSY). To detect all exchange processes, the EXSY experiment requires the acquisition of time-consuming two-dimensional spectra. Here we report a faster alternative, an experiment which uses spatial encoding to extract similar information in a 1D exchange-edited experiment. Thereby, all protons are observed at once, but in different slices of the detection volume. The experiment can be carried out in a single scan to identify exchanging sites in a 1D spectrum by changes in signal intensity indicating exchange processes. If the exchanging partner, for example water is in molar excess the exchange-editing method easily identifies mobile protons by negative signals in the 1D 1H NMR spectrum.

Critical evaluation of artificial intelligence as a digital twin of pathologists for prostate cancer pathology

Prostate cancer pathology plays a crucial role in clinical management but is time-consuming. Artificial intelligence (AI) shows promise in detecting prostate cancer and grading patterns. We tested an AI-based digital twin of a pathologist, vPatho, on 2603 histological images of prostate tissue stained with hematoxylin and eosin. We analyzed various factors influencing tumor grade discordance between the vPatho system and six human pathologists. Our results demonstrated that vPatho achieved comparable performance in prostate cancer detection and tumor volume estimation, as reported in the literature. The concordance levels between vPatho and human pathologists were examined. Notably, moderate to substantial agreement was observed in identifying complementary histological features such as ductal, cribriform, nerve, blood vessel, and lymphocyte infiltration. However, concordance in tumor grading decreased when applied to prostatectomy specimens (κ = 0.44) compared to biopsy cores (κ = 0.70). Adjusting the decision threshold for the secondary Gleason pattern from 5 to 10% improved the concordance level between pathologists and vPatho for tumor grading on prostatectomy specimens (κ from 0.44 to 0.64). Potential causes of grade discordance included the vertical extent of tumors toward the prostate boundary and the proportions of slides with prostate cancer. Gleason pattern 4 was particularly associated with this population. Notably, the grade according to vPatho was not specific to any of the six pathologists involved in routine clinical grading. In conclusion, our study highlights the potential utility of AI in developing a digital twin for a pathologist. This approach can help uncover limitations in AI adoption and the practical application of the current grading system for prostate cancer pathology.

Vox-Surf: Voxel-Based Implicit Surface Representation.

Virtual content creation and interaction play an important role in modern 3D applications. Recovering detailed 3D models from real scenes can significantly expand the scope of its applications and has been studied for decades in the computer vision and computer graphics community. In this work, we propose Vox-Surf, a voxel-based implicit surface representation. Our Vox-Surf divides the space into finite sparse voxels, where each voxel is a basic geometry unit that stores geometry and appearance information on its corner vertices. Due to the sparsity inherited from the voxel representation, Vox-Surf is suitable for almost any scene and can be easily trained end-to-end from multiple view images. We utilize a progressive training process to gradually cull out empty voxels and keep only valid voxels for further optimization, which greatly reduces the number of sample points and improves inference speed. Experiments show that our Vox-Surf representation can learn fine surface details and accurate colors with less memory and faster rendering than previous methods. The resulting fine voxels can also be considered as the bounding volumes for collision detection, which is useful in 3D interactions. We also show the potential application of Vox-Surf in scene editing and augmented reality. The source code is publicly available at https://github.com/zju3dv/Vox-Surf.

The concentration estimation for ensemble of NV– color centers with spin coherent manipulation

The concentration and distribution of negatively charged nitrogen-vacancy color centers (NV−) directly affect the sensitivity and resolution of quantum sensing. In this paper, a simple method is proposed to estimate the concentration of the ensemble of NV− centers with spin coherent manipulation. The stray fluorescence is eliminated by separating the fluorescence near the NV− zero-phonon line. By introducing a single NV− fluorescence quantitative model, the number of NV− centers in the diamond under test can be obtained. The average concentration of the ensemble of NV− centers in the sample can be obtained by combining the detection volume. Compared with the results measured by electron spin resonance, the concentration of NV− centers measured by our method can be verified, and the maximum error between the two methods is less than 4.3%. The results show that the method provides an effective reference for accurately characterizing the concentration distribution characteristics of the NV− ensemble.

Development of axion haloscopes for high-mass search at CAPP

The axion offers a well-motivated solution to two fundamental questions in modern physics: the strong CP problem and the dark matter mystery. Cavity haloscopes, exploiting resonant enhancement of photon signals, provide the most sensitive searches for axion dark matter in the microwave region. However, current experimental sensitivities are limited to the O(100)μeV range, while recent theoretical predictions for the axion mass favor up to O(102)μeV, suggesting the need of new experimental approaches that are suitable for higher mass regions. CAPP has developed/proposed several haloscopes effective for high-mass axion searches based on new cavity concepts and practical tuning mechanisms. They are characterized by large detection volumes and/or high quality factors at high frequencies, achieved by partitioning a single cavity into multiple cells, exploiting higher-order resonant modes, and constructing dielectric photonic crystal structures. Improving on the dish antenna haloscope scheme, a horn antenna array has also been proposed for volume-efficient broadband search in the THz region. We review these haloscope designs for sensitive search in the high-mass regions and discuss their impacts on future experiments.

Nonlinear spatio-temporal filter to reduce crosstalk in bipolar electromyogram

Objective. The wide detection volume of surface electromyogram (EMG) makes it prone to crosstalk, i.e. the signal from other muscles than the target one. Removing this perturbation from bipolar recordings is an important open problem for many applications. Approach. An innovative nonlinear spatio-temporal filter is developed to estimate the EMG generated by the target muscle by processing noisy signals from two bipolar channels, placed over the target and the crosstalk muscle, respectively. The filter is trained on some calibration data and then can be applied on new signals. Tests are provided in simulations (considering different thicknesses of the subcutaneous tissue, inter-electrode distances, locations of the EMG channels, force levels) and experiments (from pronator teres and flexor carpi radialis of 8 healthy subjects). Main results. The proposed filter allows to reduce the effect of crosstalk in all investigated conditions, with a statistically significant reduction of its root mean squared of about 20%, both in simulated and experimental data. Its performances are also superior to those of a blind source separation method applied to the same data. Significance. The proposed filter is simple to be applied and feasible in applications in which single bipolar channels are placed over the muscles of interest. It can be useful in many fields, such as in gait analysis, tests of myoelectric fatigue, rehabilitation with EMG biofeedback, clinical studies, prosthesis control.

Multi-point calorimeter using distributed fiber Bragg gratings for small field dosimetry in radiotherapy.

The interest of using fiber Bragg gratings (FBGs) dosimeters in radiotherapy (RT) lies in their (i) microliter detection volume, (ii) customizable spatial resolution, (iii) multi-point dose measurement, (iv) real-time data acquisition and (v) insensitivity to Cherenkov light. These characteristics could prove very useful for characterizing dose distributions of small and nonstandard fields with high spatialresolution. We developed a multi-point FBGs dosimeter customized for small field RT dosimetry with a spatial resolution of 1mm. The 3cm-long multi-point dosimeter is made by embedding a 80 silica fiber containing an array of thirty (30) co-located 1mm-long fs-written FBGs inside a plastic cylinder with an UV curing optical adhesive. With its higher thermal expansion coefficient, the plastic cylinder increases the sensitivity of the dosimeter by stretching the fiber containing the FBGs when the temperature rises slightly due to radiation energy deposition. Irradiations (2000MU at 600MU/min) were performed with a Varian TrueBeam linearaccelerator. The dose profile of a 2 2cm 6MV beam was measured with a mean relative difference of 1.8% (excluding the penumbra region). The measured output factors for a 6MV beam are in general agreement with the expected values within the experimental uncertainty (except for the 2 2cm field). The detector response to different energy of photon and electron beams is within 5% of the mean response ( pm/Gy). The calorimeter's post-irradiation thermal decay is in agreement with thetheory. An energy-independent small field calorimeter that allows dose profile and output factor measurements for RT using FBGs was developed, which, to our knowledge, has never been done before. This type of detector could prove really useful for small field dosimetry, but also potentially for MRI-LINAC since FBGs are insensitive to magnetic fields and for FLASH since FBGs have been used to measure doses up to100kGy.

Pacific Ocean Neutrino Experiment

Following the breakthrough discoveries of very-high-energy neutrinos of astrophysical origin by IceCube, a new field of research, neutrino astronomy, was established in the previous decade. Even though two extragalactic point sources of such neutrinos have been identified by now, TXS 0506+056 and NGC 1068, the origin and processes of the creation of astrophysical neutrinos are still mostly unexplored. To advance quickly in this new field, more neutrino telescopes are needed. This article describes the current status and plans for the development of the Pacific Ocean Neutrino Experiment (P-ONE), which is under construction in the Pacific Ocean near Vancouver Island. The deployment of P-ONE is expected to start in 2025, exploiting the already available deep-sea infrastructure provided by Ocean Networks Canada. P-ONE will complement the existing IceCube, Baikal-GVD, and KM3NeT neutrino telescopes not only with its large detection volume, but also by providing insight into the southern celestial hemisphere, where the central region of the Galactic Plane is located.

Luminescent Properties of β-(hydroxyaryl)-butenolides and Fluorescence Quenching in Water.

This work describes the luminescent properties of the new compound β-(hydroxyaryl)-butenolides recently discovered. The compounds were subjected to UV-Vis absorption and fluorescence analyzes when diluted in different solvents. Through the results, it was possible to observe that the β-hydroxyarylutenolides have two absorption bands, one at 289-291nm and the other with higher intensity at 328-354nm. The emission band between 385-422nm is observed under excitation at 324-327nm. The compounds showed solvatochromism as a function of the analyzed solvent. In water, fluorescence quenching of all compounds occurs. Therefore, studies with compound containing the methylenedioxy group attached in phenyl ring were carried at different concentrations of water in DMSO. The decrease in the fluorescence intensity of this compound is linearly proportional to the increase in the amount of water in the DMSO, with a minimum detection volume of 0.028%. Quantum yields of three compounds were evaluated in different solvents, showing that the relationship between the structure of the compound and the solvent is essential for a high value. The fluorescence quantum yield was also measured by Thermal Lens Spectroscopy (TLS) using DMSO as the solvent, confirming the high value for the analyzed samples. Despite being preliminary, the studies revealed that these compounds have luminescent properties that could be applied in the development of chemical sensors for detecting water in DMSO.