Precise Matching Research Articles

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.

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.

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.

Efficiency and Privacy in Record Linkage: Evaluating a Novel Blocking Technique Implemented on Cryptographic Longterm Keys

Efficient privacy-preserving record linkage (PPRL) is essential for integrating data from different providers without exposing personally identifiable information (PII). This study investigates the effectiveness of a novel blocking technique, implemented on Bloom filters (a space-efficient probabilistic data structure), to enhance efficiency and maintain privacy in a real-world evaluation. This methodology involves the utilization of Anonlink, an open-source Python-based PPRL system which generates a type of Bloom filter, Cryptographic Longterm Keys (CLK), for secure record linkage. Initially, the relevant PII fields of the two datasets undergo anonymization into CLKs. Utilizing the CLK’s property of similarity preservation, we create manageable blocks of records based on bits in common within the Bloom filters. This allows us to reduce the number of comparisons of non-matching records to improve linkage efficiency. Finally, record linkage is performed to identify potential matches within the blocked datasets. This blocking technique for CLKs is evaluated in terms of efficiency and record matching precision, aiming to determine the optimal balance between the two factors. Preliminary results indicate a significant reduction in computational burden, with recall minimally affected. Moreover, the implemented blocking technique poses no additional risks of privacy breaches. Preliminary evaluation of the blocking technique shows a promising avenue for secure and efficient data integration, especially in datasets with PII, warranting further investigation for validation and wider application.

Gravitational index of the heterotic string

The fundamental heterotic string has a tower of BPS states whose supersymmetric index has an exponential growth in the charges. We construct the saddle-point of the gravitational path integral corresponding to this index. The saddle-point configuration is a supersymmetric rotating non-extremal Euclidean black hole. This configuration is singular in the two-derivative theory. We show that the addition of higher-derivative terms in four-dimensional N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 2 supergravity resolves the singularity. In doing so, we extend the recently-developed “new attractor mechanism” to include the effect of higher-derivative terms. Remarkably, the one-loop, four-derivative F-term contribution to the prepotential leads to a precise match of the gravitational and microscopic index. We also comment, using the effective theory near the horizon, on the possibility of a string-size near-extremal black hole. Our results clarify the meaning of different descriptions of this system in the literature. The thermal state transitions to a winding condensate and a gas of strings without ever reaching a small black hole, while the index is captured by the rotating Euclidean black hole solution and is constant and thus smoothly connected to the microscopic ensemble.

Multi-layer resource scheduling architecture and algorithm for a service-oriented optical network based on a fine grain OTN

With the development of service, there are demands for flexible connection scheduling based on customer-side services, fast connection response, and efficient scheduling of line-side resources in an optical transport network (OTN). This article proposes a service-oriented multi-layer resource scheduling architecture and algorithm based on the introduction of OTN fine grain technology. Specifically, we propose a service awareness scheme that enables OTNs to better match service requirements. Based on a centralized distributed collaborative architecture, we extend a path computation element communication protocol (PCEP) to achieve more efficient connection distribution. We further design a resource scheduling strategy and an algorithm based on multi-layer collaboration to perform differentiated scheduling for services with different priorities. Through the mechanisms and algorithms proposed, it is technically feasible to achieve precise matching of customer-side services, flexible scheduling of connections and resources, and efficient service response, and promote the evolution of the OTN service supply from traditional fixed point-to-point connections to flexible service-oriented optical network (SOON) connections.

Acoustic Processing and the Origin of Human Vocal Communication

Humans have inherited from their remotest mammalian ancestors an integration of the sensory and motor systems that permits the exchange of signals and information, led by an instinctive response to harmonicity. The transition, from capacity for animal communication involving calls, facial expression and gestures, to modern human culture that embraces language, music, and dance, has resulted from anatomical adaptations such as upright posture, a distinct oro-facial and respiratory tract arrangement, and important changes in neural architecture, connectivity and plasticity. A key development on which modern human vocal abilities depend was the achievement of a feedback loop between the perception and production of voiced sound that allows precise matching, imitation, and meaningful variation, of the acoustic properties: fundamental frequency, duration, amplitude, and timbre; all contributing to the capacity to coordinate simultaneous participation. These are the four specific properties that influence our sensations of sound. They play parallel and complementary roles in both language and vocal music, represented in blended synchrony such as unison song and collective speech as well as temporally organised and coordinated sequences such as call-and-response and polyphony. In turn, responding especially to the properties of the Harmonic Series, such features inform the musical employment of tools – musical instruments – that make use of materials available in the local environment (skin, bone, stone, bamboo, wood, etc.) to provide increased range and loudness as well as alternative timbres to those produced by the voice. We propose a framework by which the adaptations essential to such universal behaviours may have arisen, drawing on an extensive and varied literature to explore the potential of this position for illuminating the nature of human musicality and its relationship to language development.

Which is better? Taxonomy induction with learning the optimal structure via contrastive learning

A taxonomy represents a hierarchically structured knowledge graph that forms the infrastructure for various downstream applications, including recommender systems, web search, and question answering. The exploration of automated induction from text corpora has yielded notable taxonomies such as CN-probase, CN-DBpedia, and Zhishi.schema. Despite these efforts, existing taxonomies still face two critical issues that result in sub-optimal hierarchical structures. On the one hand, commonly observed taxonomies exhibit a coarse-grained and “flat” structure, stemming from a noticeable lack of diversity in both nodes and edges. This limitation primarily originates from the biased and homogeneous data distribution. On the other hand, the semantic granularity among “siblings” within these taxonomies remains inconsistent, presenting a challenge in accurately and comprehensively identifying hierarchical relations. To address these issues, this study introduces a novel taxonomy induction framework composed of three meticulously designed components. Initially, we established a seed schema by leveraging statistical information from external data sources as distant supervision to append nodes and edges containing “generic semantics”, thereby rectifying biased data distributions. Subsequently, a clustering algorithm is employed to group the nodes based on their similarities, followed by a refinement operation of the hierarchical relations among these nodes. Building on this seed schema, we propose a fine-grained contrastive learning method in the expansion module to strengthen the utilization of taxonomic structures, consequently boosting the precision of query-anchor matching. Finally, we meticulously scrutinized the hierarchical relations between each query and its siblings to ensure the integrity of the constructed taxonomy. Extensive experiments on real-world datasets validated the efficacy of our proposed framework for constructing well-structured taxonomies.

A “poor-man’s” deformation plasticity based approach to topology optimization of elastoplastic structures

This paper presents a topology optimization framework utilizing a deformation plasticity model to approximate the isotropic hardening von-Mises incremental elastoplasticity model under monotone proportional loading. One advantage of the model is that it is based on a yield surface allowing for precise matching to uniaxial elastoplastic isotropic hardening response. The deformation plasticity model and the incremental plasticity model coincides for proportional loading and since the deformation plasticity model is path-independent, the computational cost and implementation complexity reduce significantly compared to the conventional incremental elastoplasticity. To investigate the deformation plasticity model combined with topology optimization, we compare three common elastoplastic optimization objectives: stiffness, strain energy and plastic work. The possibility to limit the peak local plastic work while maximizing the strain energy is also investigated. The consistent analytical sensitivity analysis which only requires the terminal state is derived using adjoint method. Numerical examples demonstrate that the proportionality assumption is reasonable and the deformation plasticity model combined with topology optimization is a competitive alternative to cumbersome incremental elastoplasticity.