Precise Matching Research Articles

Simultaneous cooling of high-frequency difference resonators through voltage modulation and intracavity-squeezed light

We propose a scheme to achieve simultaneous cooling of the mechanical and radio-frequency resonators in a hybrid optoelectromechanical system. By introducing the voltage modulation switch and intracavity-squeezed light, the high-frequency difference resonators can be successfully cooled to their quantum ground states by eliminating cavity mode dissipation through precise phase and amplitude matching of the squeezed pump field and the cooling optical field. More significantly, ground-state cooling can be achieved even in the highly unresolved sideband regime, and the quantum backaction heating can be effectively suppressed, leading to a significant improvement in cooling performance. Our work provides an alternative approach for quantum coherent manipulation of multiple mechanical systems with different resonant frequencies.

RBD-EVIO: optimized event-based visual-inertial odometry for a large field of view with a rotated binary DART descriptor.

Event-based cameras offer unique advantages over traditional cameras, such as high dynamic range, absence of motion blur, and microsecond-level latency. This paper introduces an innovative approach to visual odometry, to our knowledge, by integrating the newly proposed Rotated Binary DART (RBD) descriptor within a Visual-Inertial Navigation System (VINS)-based event visual odometry framework. Our method leverages event optical flow and RBD for precise feature selection and matching, ensuring robust performance in dynamic environments. We further validate the effectiveness of RBD in scenarios captured by a large field-of-view (FoV) fisheye event camera under high dynamic range and high-speed rotation conditions. Our results demonstrate significant improvements in tracking accuracy and robustness, setting what we believe to be a new benchmark for event-based visual odometry. This work paves the way for advanced applications in high-speed, high dynamic range, and large FoV visual sensing.

Genomic profiling of NSCLC tumors with the TruSight oncology 500 assay provides broad coverage of clinically actionable genomic alterations and detection of known and novel associations between genomic alterations, TMB, and PD-L1

IntroductionMatching patients to an effective targeted therapy or immunotherapy is a challenge for advanced and metastatic non-small cell lung cancer (NSCLC), especially when relying on assays that test one marker at a time. Unlike traditional single marker tests, comprehensive genomic profiling (CGP) can simultaneously assess NSCLC tumors for hundreds of genomic biomarkers and markers for immunotherapy response, leading to quicker and more precise matches to therapeutics.MethodsIn this study, we performed CGP on 7,606 patients with advanced or metastatic NSCLC using the Illumina TruSight Oncology 500 (TSO 500) CGP assay to show its coverage and utility in detecting known and novel features of NSCLC.ResultsTesting revealed distinct genomic profiles of lung adenocarcinoma and squamous cell carcinomas and detected variants with a current targeted therapy or clinical trial in >72% of patient tumors. Known associations between genomic alterations and immunotherapy markers were observed including significantly lower TMB levels in tumors with therapy-associated alterations and significantly higher PD-L1 levels in tumors with ALK, MET, BRAF, or ROS1 driver mutations. Co-occurrence analysis followed by network analysis with gene module detection revealed known and novel co-occurrences between genomic alterations. Further, certain modules of genes with co-occurring genomic alterations had dose-dependent relationships with histology and increasing or decreasing levels of PD-L1 and TMB, suggesting a complex relationship between PD-L1, TMB, and genomic alterations in these gene modules.DiscussionThis study is the largest clinical study to date utilizing the TSO 500. It provides an opportunity to further characterize the landscape of NSCLC using this newer technology and show its clinical utility in detecting known and novel facets of NSCLC to inform treatment decision-making.

An effective inliers selection strategy for high-precision image feature matching

ABSTRACT Seeking a reliable inliers selection method to image feature matching is a fundamental and important task in image processing and robotic vision. To improve the precision of feature matching on putative matches with heavy outliers, we propose a new strategy to select the inliers from the rough feature correspondence-set. Firstly, we construct the inliers selection problem as a concise mathematical model with linear time complexity based on the local K-nearest neighbour structure preserving (KNNSP). Then, to improve the robustness of this model, we design a threshold decrease strategy for this model to iteratively solve the optimal inliers set. Extensive experiments on various image pairs demonstrate that the proposed method does not need prior information and can be directly used for rigid or non-rigid image matching problems. In addition, compared with other typical image matching algorithms, our method ensures competitive performance in precision and recall.

Simplified Composite Restorations for Fractured Young Incisors: A Clinical Review.

Tooth fractures are a common consequence of dental trauma in young patients, requiring prompt and effective restorative interventions that ensure both functional integrity and esthetic appeal. Although resin stratification (layering) is the gold standard for achieving life-like restoration of fractured teeth, many clinicians find it technically challenging due to the time and effort required for precise shade matching, concealing the fracture line, and accurate placement of resin composite layers with different levels of opacity. The more recent generation of monoshade composites, with their ability to adapt to various tooth shades, reduce the complexity of multi-layer restorations, and improve chairside efficiency. Additionally, the composite cutback technique has gained attention as an effective method for restoring fractured teeth in young patients. This method combines the benefits of monoshade composites and the precision of simple additional layering to enhance both the esthetic and functional outcomes of the restorations. This mini-review provides a comprehensive analysis of the composite cutback technique, the role of monoshade composites, and their clinical application in the restoration of fractured young teeth.

Enhanced Chirality Transfer in Self-Assembled Nanocomposites Powered by A Trace Amount of Chiral Dimeric Molecules.

Chiral-selective self-assembly has markedly advanced the development of chiral materials. While the Sergeant and Soldiers principle allows for chirality amplification, it necessitates precise shape-matching between chiral and achiral molecules, leading to a low chirality transfer efficiency-where one chiral molecule influences the chirality of a limited number of achiral molecules. Here, we show that this efficiency can be markedly enhanced by introducing chiral dimeric molecules. In this work, a single chiral molecule can control the chirality of up to 200 achiral molecules and even direct the assembly of inorganic nanoparticles into chiral nanocomposites through a sequential chirality transfer process. Moreover, this approach exhibits remarkable robustness, operating effectively without necessitating a precise match between chiral and achiral molecules. Consequently, using the same chiral molecules at an exceptionally low molar fraction (0.5 mol %) allows for the chiral-selective assembly of achiral molecules over a broad spectrum, regardless of their packing habits, thus facilitating the creation of otherwise inaccessible chiral materials with modulated chiroptical properties. Last but not least, even a trace amount of chiral molecules can enhance the elastic modulus of the self-assembled nanocomposites by a factor of eight.

Enhanced Chirality Transfer in Self‐Assembled Nanocomposites Powered by A Trace Amount of Chiral Dimeric Molecules

Chiral‐selective self‐assembly has markedly advanced the development of chiral materials. While the Sergeant and Soldiers principle allows for chirality amplification, it necessitates precise shape‐matching between chiral and achiral molecules, leading to a low chirality transfer efficiency—where one chiral molecule influences the chirality of a limited number of achiral molecules. Here, we show that this efficiency can be markedly enhanced by introducing chiral dimeric molecules. In this work, a single chiral molecule can control the chirality of up to 200 achiral molecules and even direct the assembly of inorganic nanoparticles into chiral nanocomposites through a sequential chirality transfer process. Moreover, this approach exhibits remarkable robustness, operating effectively without necessitating a precise match between chiral and achiral molecules. Consequently, using the same chiral molecules at an exceptionally low molar fraction (0.5 mol%) allows for the chiral‐selective assembly of achiral molecules over a broad spectrum, regardless of their packing habits, thus facilitating the creation of otherwise inaccessible chiral materials with modulated chiroptical properties. Last but not least, even a trace amount of chiral molecules can enhance the elastic modulus of the self‐assembled nanocomposites by a factor of eight.

Synchronous decomposition match-reassigning transform and its application in planetary gearbox fault diagnosis

Abstract Under time-varying operating conditions, the instantaneous frequency (IF) of the vibration signal of the planetary gearbox exhibits non-stationary time-varying closely spaced characteristics as well as non-proportional and non-synchronous characteristics, making it difficult for traditional time-frequency analysis (TFA) methods to accurately identify its fault features and obtain accurate time-frequency representations (TFR). To address this challenge, this paper proposes a TFA method based on Synchronous Decomposition Match-Reassigning Transform (SDMRT). Firstly, the successive variational mode decomposition (SVMD) is used to adaptively separate non-synchronous frequency components in the original vibration signal. Then, the chirp rate (CR) describing the signal harmonic structure is used to synchronously match each frequency component, obtaining the TFR corresponding to each component. Next, all TFRs are merged to obtain a complete TFA result. Finally, Finally, the energy spread is re-aggregated to the ridge of the IF using the reassignment principle, resulting in a new frequency estimation operator called the Synchronous Decomposition Match-Reassigning Operator (SDMRO). SDMRT can adaptively separate non-proportional and non-synchronous IFs and achieve precise matching of time-varying closely spaced IFs, thereby completing the TFR of the vibration signal generated by the planetary gearbox. By analyzing simulated signals and measured vibration signals from planetary gearboxes, the method proposed in this paper is significantly superior to other TFA methods, thereby validating the effectiveness and superiority of SDMRT.

Abstract 4136705: Complexity and Inconsistency of Echocardiogram Prices at Top-Rated Hospitals in the United States

Background: Recent U.S. policies require hospitals and health insurers to post payer-specific negotiated prices for services. Few studies, if any, have thoroughly investigated the accuracy of these payer-specific prices for individual hospitals. Hypothesis: Top-rated medical centers charge consistent prices for echocardiograms, which are reflected in price transparency files. Aim: To evaluate the concordance of prices of echocardiograms using three datasets: 1) hospital price transparency, 2) payer price transparency data, and 3) Electronic Remittance Advice (ERA) claims data, reflecting actual payments. Methods: We extracted prices for transthoracic echocardiograms (CPT 93306) at 22 top-rated hospitals by US News&World Report from 1/1/2022 to 12/31/2022. We used price transparency data aggregated by Turquoise Health and compared with ERA claims data. This analysis included 9,171 insurance claims, matched to either payer or hospital-reported prices. For each claim, concordance between datasets was determined by evaluating whether each claim payment fell within a $10 margin of a publicly reported payer-specific price. Findings: In the payer and hospital price transparency files, reported prices ranged from $1.3 to $34,424. In the ERA claims data, the median payment for the professional fee was $203 (Q1 = $116, Q3 = $245), and the median payment for the facility fee was $2682 (Q1 = 1829, Q3 = $4531). There was a ten-fold difference in median price between the cheapest and most expensive facility. Only 27.4% of claim payments had a concordant price in the payer price transparency dataset, and 11.9% in the hospital dataset. Conclusion: Deriving accurate price estimates for patients requires precise matching of the insurance plan, place of service, and fee type. This process highlights the complexity of insurance contracting, and it is not surprising that there is some disagreement in prices. Regardless, we are hopeful that highlighting variation and complexity in prices is a step towards a better system of healthcare payments in the United States.

High-sensitivity and high-resolution triboelectric acoustic sensor for mechanical equipment monitoring

Traditional sensors for mechanical equipment monitoring often face challenges such as high cost, difficult installation and removal, and reliance on power sources. Herein, we introduced a polyvinylidene fluoride (PVDF) nanofiber membrane doped with BaTiO3 for constructing a triboelectric acoustic sensor (PB-TAS), innovatively designed for monitoring and recognizing the working conditions of mechanical equipment. This represents the first application of a triboelectric acoustic sensor for mechanical equipment monitoring. The PB-TAS demonstrates an ultra-broad frequency response range of 20–20,000 Hz, effectively covering the characteristic frequency spectrum (within 2000 Hz) during piston pump operation. It also exhibits extraordinarily sensitivity of 4.40 V Pa−1 at 85 dB, and ultra-high frequency resolution down to 0.1 Hz, enabling precise matching of the piston pump's acoustic characteristic frequencies. Integrated with deep learning techniques, the PB-TAS achieves real-time recognition of 15 distinct working conditions of a piston pump, with an impressive accuracy of 95.2 %. The PB-TAS, boasting exceptional sensitivity and frequency resolution, offers a cost-effective, miniaturized, self-powered, non-contact, and highly accurate solution for intelligent monitoring of hydraulic piston pumps.

First demonstration of a combined light and charge pixel readout on the anode plane of a LArTPC

The novel SoLAr concept aims to extend sensitivities of liquid-argon neutrino detectors down to the MeV scale for next-generation detectors. SoLAr plans to accomplish this with a liquid-argon time projection chamber that employs an anode plane with dual charge and light readout, which enables precision matching of light and charge signals for data acquisition and reconstruction purposes. We present the results of a first demonstration of the SoLAr detector concept with a small-scale prototype detector integrating a pixel-based charge readout and silicon photomultipliers on a shared printed circuit board. We discuss the design of the prototype, and its operation and performance, highlighting the capability of such a detector design.

Research on efficient matching method of coal gangue recognition image and sorting image

When the coal gangue sorting robot sorts coal gangue, the position of the target coal gangue will change due to belt slippage, deviation, and speed fluctuations of the belt conveyor. This will cause the robotic to fail in grasping or miss grasping. We have developed a solution to this problem: the IMSSP-Net two-stage network gangue image fast matching method. This method will reacquire the target gangue position information and improve the robot’s grasping precision and efficiency. In the first stage, we use SuperPoint to guarantee the scene adaptability and credibility of feature point extraction. We have enhanced Superpoint’s ability to detect feature points further by using the improved Multi-scale Retinex with Color Restoration enhancement algorithm. In the second stage, we introduce SuperGlue for feature matching to improve the robustness of the matching network. We eliminated erroneous feature matching point pairs and improved the accuracy of image matching by adopting the PROSAC algorithm. We conducted image matching comparison experiments under different object distances, scales, rotation angles, and complex conditions. The experimental platform adopts the double-manipulator truss-type coal gangue sorting robot independently developed by the team. The matching precision, recall, and matching time of the method are 98.2%, 98.3%, and 84.6ms, respectively. The method can meet the requirements of efficient and accurate matching between coal gangue recognition images and sorting images.

Effectiveness of an HIV peer support precision matching platform: a randomized controlled trial protocol

BackgroundPeer support is a promising and significant way for people living with HIV (PLWH) to improve their health outcomes. Matching PLWH with HIV peer volunteers can effectively stimulate and mobilize the function of peer support in health management. We develop the online platform Aspark, which features a precision matching function for PLWH and volunteers. This protocol provides a comprehensive overview of the randomized controlled trial design based on Aspark.MethodA parallel randomized controlled trial using block randomization will be conducted at the Beijing YouAn Home of Loving Care. The intervention group (n = 70) will have access to all 12 features of Aspark, including precise volunteer matching, health management tools, drug interaction queries, and medication reminders. The control group (n = 70) will have access to two features of informational support on Aspark. The outcomes of both groups will be evaluated at baseline and at 3, 6, 9, and 12 months after platform registration. The primary outcome is perceived social support. The secondary outcomes include mental symptoms, quality of life, self-efficacy, medication adherence, and health behaviors. Linear mixed models or generalized linear mixed models will be applied to test the intervention effects.DiscussionThe Aspark trial is a randomized controlled trial designed to examine the influence of a mobile health (mHealth) application that integrates peer support and precision matching to strengthen social support for PLWH in China. This trial has the potential to significantly enhance social support for PLWH while also optimizing the delivery of peer support services and fully mobilizing the role of peer support in the overall health management of PLWH.Trial registrationClinical registration number: ChiCTR2300077454.

Effectiveness of tolvaptan on renal replacement therapy in patients with autosomal dominant polycystic kidney disease: a retrospective cohort study from the TriNetX global collaborative network

Background and hypothesis Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a major genetic contributor to end-stage kidney disease (ESKD). Current evidence on tolvaptan primarily focuses on slowing estimated glomerular filtration rate (eGFR) decline and kidney volume growth. However, direct confirmation of its effectiveness in reducing the need for hemodialysis in ESKD remains limited. Methods We included ADPKD patients aged ≥18 years using TriNetx data from Sep 2, 2018, to Sep 3, 2023. Propensity score matching (PSM) ensured baseline comparability (standardized mean difference (SMD) <0.1). Hazard ratios (HRs) with 95% confidence intervals (CIs) evaluated outcomes, and subgroup analyses were performed. Results After 1:1 PSM, both groups comprised 673 patients. The average age was 45, with generally good health (3–5% diabetes, 2-3% ischemic heart disease). Baseline eGFR averaged ∼55 ml/min/1.732m2. Post-matching, all SMDs were <0.1, indicating successful matching. Tolvaptan users exhibited lower eGFR (51.45 ± 30.09 vs. 57.37 ± 33.65, p < 0.001) and higher risk of stage 4-CKD (HR: 2.436, 95% CI:1.649, 3.599) compared to non-users. However, tolvaptan users showed significantly reduced chances of initiating hemodialysis (HR:0.362, 95%CI:0.176, 0.745), experiencing urinary tract infections (HR:0.581, 95%CI:0.354, 0.956), and all-cause mortality (HR:0.355, 95% CI:0.180, 0.700). Kaplan-Meier curves for hemodialysis initiation indicated higher survival rates among tolvaptan users across age and number of medication refill subgroups. Conclusions This real-world study, employing precise matching, reveals tolvaptan’s role in reducing hemodialysis initiation risk in ADPKD, despite initial hemodynamic-induced lower eGFR.

YPR-SLAM: A SLAM System Combining Object Detection and Geometric Constraints for Dynamic Scenes

Traditional SLAM systems assume a static environment, but moving objects break this ideal assumption. In the real world, moving objects can greatly influence the precision of image matching and camera pose estimation. In order to solve these problems, the YPR-SLAM system is proposed. First of all, the system includes a lightweight YOLOv5 detection network for detecting both dynamic and static objects, which provides pre-dynamic object information to the SLAM system. Secondly, utilizing the prior information of dynamic targets and the depth image, a method of geometric constraint for removing motion feature points from the depth image is proposed. The Depth-PROSAC algorithm is used to differentiate the dynamic and static feature points so that dynamic feature points can be removed. At last, the dense cloud map is constructed by the static feature points. The YPR-SLAM system is an efficient combination of object detection and geometry constraint in a tightly coupled way, eliminating motion feature points and minimizing their adverse effects on SLAM systems. The performance of the YPR-SLAM was assessed on the public TUM RGB-D dataset, and it was found that YPR-SLAM was suitable for dynamic situations.

Particle tracking-aided digital volume correlation for clay–sand soil mixtures

In this study, a novel, interdisciplinary method is introduced that merges fundamental geomechanics with computer vision to develop an advanced hybrid feature-aided digital volume correlation (DVC) technique. This technique is specifically engineered to measure and compute the full-field strain distribution in fine-grained soil mixtures. A clay–sand mixture specimen composed of quartz sand particles and kaolinite was created. Its mechanical properties and deformation behaviour were then tested using a mini-triaxial apparatus, combined with micro-focus X-ray computed tomography (μCT). The CT slices underwent image processing for denoising, segmentation of distinct phases, reconstruction of sand particles and feature extraction within the soil specimen. The proposed approach incorporated a two-step particle tracking method, which initially uses particle volume and surface area features to establish a preliminary matching list for a reference particle and then use the iterative closest point method for precise target particle matching. The soil specimen's initial displacement field was then mapped onto the DVC method's grid, and further refined through sub-voxel registration by way of a three-dimensional inverse compositional Gauss–Newton algorithm. The proposed method's effectiveness and efficiency were validated by accurately calculating the displacement and strain fields of the soil mixture sample, and comparing the results with those from a traditional DVC method. Given the soil's compositional and microstructural characteristics, these image-matching techniques can be integrated to create a versatile, efficient, and robust DVC system, suitable for a variety of soil mixture types.

Design of a polarization-insensitive broadband achromatic metalens for mid-wave infrared detector.

Metalenses, boasting outstanding focusing efficiency and high-resolution imaging capabilities, have generated widespread usage in fields such as integrated optics, achromatic imaging, and optical holography. In this study, we have developed a broadband achromatic metalens within the detection range from 3 to 5 µm, and it has a numerical aperture (NA) of 0.71 with a remarkable maximum focusing efficiency of 63.8% at the focal plane within the specified bandwidth. We have further delved into the dispersion control mechanism that combines the geometric and transmission phases and optimized the constructed phase response simulation database using the particle swarm optimization (PSO) algorithm, ensuring a precise phase matching between the actual wavefront and the ideal focusing wavefront. This metalens with its ability to expand the array size has the potential to create a compact infrared imager, which holds significant importance in achieving efficient detection and integration within infrared detectors.

Solving AdS3 string theory at minimal tension: tree-level correlators

We revisit the minimal tension (k = 1) string theory on AdS3 × S3 × \U0001d54b4. We propose a new free-field description of the worldsheet theory and show how localization of string amplitudes emerges from the path integral. We exemplify our proposal by reproducing the worldsheet partition function of the psu\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathfrak{psu} $$\\end{document}(1, 1|2)1 WZW model and providing explicit expressions for spectrally-flowed vertex operators and DDF operators. We compute string correlators in the path integral formalism and obtain a precise tree-level match with correlation functions of the boundary symmetric orbifold.

Synthesis of nano tungsten carbide via loose yellow tungsten oxide rod processing

Nano tungsten carbide (WC) was synthesized using loose yellow tungsten oxide (WO3) rods, which were derived from violet tungsten oxide (WO2.72) through calcination in dry oxygen. The WO3 rods were then subjected to ball milling with carbon black, followed by carbothermal reduction and carbonization. Unlike conventional methods such as hydrogen reduction or carbothermal reduction, this technique avoids the formation of hydrated tungsten oxides and addresses challenges related to precise carbon control and matching. This streamlined procedure produces nanoscale tungsten carbide particles approximately 150 nm in size, showing great potential for future industrial applications.

UAV image object detection based on self-attention guidance and global feature fusion

Unmanned aerial vehicle (UAV) image object detection has garnered considerable attentions in fields such as Intelligent transportation, urban management and agricultural monitoring. However, it suffers from key challenges of the deficiency in multi-scale feature extraction and the inaccuracy when processing complex scenes and small-sized targets in practical applications. To address this challenge, we propose a novel UAV image object detection network based on self-attention guidance and global feature fusion, named SGGF-Net. First, in order to optimizing feature extraction in global perspective and enhancing target localization precision, the global feature extraction module (GFEM) is introduced by exploiting the self-attention mechanism to capture and integrate long-range dependencies within images. Second, a normal distribution-based prior assigner (NDPA) is developed by measuring the resemblance between ground truth and the priors, which improves the precision of target position matching and thus handle the problem of inaccurate localization of small targets. Furthermore, we design an attention-guided ROI pooling module (ARPM) via a deep fusion strategy of multilevel features for optimizing the integration of multi-scale features and improving the quality of feature representation. Finally, experimental results demonstrate the effectiveness of the proposed SGGF-Net approach.