Precise Matching Research Articles

EMC+GD_C: circle-based enhanced motion consistency and guided diffusion feature matching for 3D reconstruction

Robust matching, especially the number, precision and distribution of feature point matching, directly affects the effect of 3D reconstruction. However, the existing methods rarely consider these three aspects comprehensively to improve the quality of feature matching, which in turn affects the effect of 3D reconstruction. Therefore, to effectively improve the quality of 3D reconstruction, we propose a circle-based enhanced motion consistency and guided diffusion feature matching algorithm for 3D reconstruction named EMC+GD_C. Firstly, a circle-based neighborhood division method is proposed, which increases the number of initial matching points. Secondly, to improve the precision of feature point matching, on the one hand, we put forward the idea of enhancing motion consistency, reducing the mismatch of high similarity feature points by enhancing the judgment conditions of true and false matching points; on the other hand, we combine the RANSAC optimization method to filter out the outliers and further improve the precision of feature point matching. Finally, a novel guided diffusion idea combining guided matching and motion consistency is proposed, which expands the distribution range of feature point matching and improves the stability of 3D models. Experiments on 8 sets of 908 pairs of images in the public 3D reconstruction datasets demonstrate that our method can achieve better matching performance and show stronger stability in 3D reconstruction. Specifically, EMC+GD_C achieves an average improvement of 24.07% compared to SIFT-based ratio test, 9.18% to GMS and 1.94% to EMC+GD_G in feature matching precision.

Performance improvement of the self-power control valve based on digital twin technology

Providing stable energy for intelligent pipe network systems is a complex problem. Ball valves are widely used in intelligent pipe network systems, and a self-power control valve is designed by integrating a flow-matching wheel in the ball valve. While the spool is throttling the fluid, a part of the energy can be extracted from the fluid and converted into the power. In order to optimize the energy capturing characteristics of the self-power control valve, the shape of the flow-matching wheel must be designed to form a precise match with the valve cavity. In this paper, a lightweight digital twin of the self-power control valve is developed using an agent model. Based on this, an optimized design method for the flow-matching wheel that can dynamically take into account the operating conditions of the valve in real time, is proposed by combining the agent model with the dynamic data from multiple sensor sources. The research results show that after the twin optimization of the flow-matching wheel, the average value of the energy capturing efficiency is improved by 3.21 % compared to the pre-optimization; the average value of the output power is improved by 20.57 % compared to the pre-optimization.

Biomechanical and clinical outcomes of 3D-printed versus modular hemipelvic prostheses for limb-salvage reconstruction following periacetabular tumor resection: a mid-term retrospective cohort study

BackgroundDebates persist over optimal pelvic girdle reconstruction after acetabular tumor resection, with surgeons grappling between modular and 3D-printed hemipelvic endoprostheses. We hypothesize superior outcomes with 3D-printed versions, yet scarce comparative research exists. This study fills the gap, examining biomechanics and clinical results retrospectively.MethodsFrom February 2017 to June 2021, we retrospectively assessed 32 patients undergoing en bloc resection for malignant periacetabular tumors at a single institution. Primary outcome: limb function. Secondary outcomes: implant precision, hip joint rotation center restoration, prosthesis-bone osteointegration, and complications. Biomechanical characteristics were evaluated through finite element analysis on pelvic defect models.ResultsIn the 3D-printed group, stress distribution mirrored a normal pelvis, contrasting the modular group with elevated overall stress, unstable transitions, and higher stress peaks. The 3D-printed group exhibited superior functional scores (MSTS: 24.3 ± 1.8 vs. 21.8 ± 2.0, p < 0.05; HHS: 79.8 ± 5.2 vs. 75.3 ± 3.5, p < 0.05). Prosthetic-bone interface osteointegration, measured by T-SMART, favored 3D-printed prostheses, but surgery time (426.2 ± 67.0 vs. 301.7 ± 48.6 min, p < 0.05) and blood loss (2121.1 ± 686.8 vs. 1600.0 ± 505.0 ml, p < 0.05) were higher.ConclusionsThe 3D-printed hemipelvic endoprosthesis offers precise pelvic ring defect matching, superior stress transmission, and function compared to modular endoprostheses. However, complexity, fabrication expertise, and challenging surgical implantation result in prolonged operation times and increased blood loss. A nuanced consideration of functional outcomes, complexity, and patient conditions is crucial for informed treatment decisions.Level of evidenceLevel III, therapeutic study (Retrospective comparative study).

Robust and adaptive star identification algorithm based on linear assignment for multiple large field of view visual imaging systems

The integration of the visual imaging system and the self-attitude determination system in on-orbit space projects necessitates robust star identification algorithms. However, disturbances in the on-orbit environment pose a challenge to the accuracy and efficiency of star identification algorithms. This paper introduces a novel star identification algorithm, to the best of our knowledge, designed for multiple large field of view (FOV) visual imaging systems, providing stability in the presence of the noise types, including position noise, lost-star noise, and fake-star noise. We employ the dynamic simulated star images generation method to construct simulated star image libraries suitable for various cameras with different FOV angles. Our algorithm comprises two parts: the star edge matching for coarse matching of interstellar angular distances based on linear assignment, and the star point registration for precise matching of star vectors. This innovative combination of local edge generation and global matching approach achieves an impressive 97.83% identification accuracy, maintaining this performance even with a standard deviation of one pixel in image plane errors and up to five missing stars. A comprehensive approach involving both simulated and empirical experiments was employed to validate the algorithm’s effectiveness. This integration of the visual imaging system and the self-attitude determination system offers potential benefits such as reduced space equipment weight, simplified satellite launch processes, and decreased maintenance costs.

Reconstruction Strategy for Upper Extremity Defects After Bone Tumor Resection Based on 3D Customized Bone Cement Mold.

Reconstructing bone defects in the upper extremities and restoring their functions poses a significant challenge. In this study, we describe a novel workflow for designing and manufacturing customized bone cement molds using 3D printing technology to reconstruct upper extremity defects after bone tumor resection. Computer tomography data was acquired from the unaffected upper extremities to create a detachable mold, which can be customized to fit the joint precisely by shaping the bone cement accordingly. Fourteen patients who underwent reconstructive surgery following bone tumor resection in the proximal humerus (13 cases) or distal radius (1 case) between January 2014 and December 2022 were retrospectively evaluated. The medical records of this case series were reviewed for the demographic, radiological, and operative data. Metastasis, local recurrence, and complication were also reviewed. Additionally, Musculoskeletal Tumor Society Score (MSTS) and Visual Analogue Scale (VAS) were used to assess clinical outcomes. The mean follow-up period was 49.36 ± 15.18 months (range, 27-82 months). At the end of follow-up, there were no cases of metastasis or recurrence, and patients did not experience complications such as infection, dislocation, or implant loosening. Two cases complicated with subluxation (14.3%), and 1 case underwent revision surgery for prosthetic fracture (7.1%). The average MSTS score was 23.2 ± 1.76 (77.4%, range, 66.7%-86.7%), and the postoperative VAS score was 1.86 ± 1.03 (range, 1-4), which was significantly lower than that before surgery (average preoperative VAS score was 5.21 ± 2.00 (range, 2-8)) (P < .001). Customized 3D molds can be utilized to shape bone cement prostheses, which may serve as a potential alternative for reconstructing the proximal humerus and distal radius following en bloc resection of bone tumors. This reconstruction strategy offers apparent advantages, including precise matching of articular surfaces and comparatively reduced costs.

4D-printed dual-responsive bioscaffolds for treating critical-sized irregular bone defects

Currently, treating irregular bone defects with a critical size is still challenging as material implantation in the complex defects with irregular shapes, effective osteogenesis and sufficient vascularization cannot be easily achieved simultaneously via a simple strategy. Herein, a dual-responsive bone tissue engineering scaffold is developed using a 4D printing strategy by intergrating a single type of multifunctional magnetic nanoparticles, Fe3O4@SiO2, with printing inks made of bioceramics and biopolymers. Minimally invasive implantation, fluent navigation of scaffolds as well as the precise boundary matching between scaffolds and the irregular defects are achieved through near-infrared (NIR) irradiation-based temperature responsive shape recovery and static magnetic field (SMF) stimulation. Moreover, improved bone regeneration in critical-sized bone defects is successfully achieved through the activation of PI3K/AKT pathway which significantly promotes osteogenic differentiation and vascularization. Besides, NIR-based photothermal stimulation upregulates the expression of heat shock protein (HSP90) and further promotes the osteogenesis and vascularization. The in vivo study also confirms that our scaffold can precisely fit the bone defect, and induce satisfactory osteogenesis and angiogenesis. This work provides a facile strategy to simultaneously-realize easy scaffold implantation in irregular bone defects and improves osteogenesis and angiogenesis by integrating a single type of multifunctional nanoparticles with scaffold matrices.

Potential prediction in aqueous organic redox-targeting flow batteries: DFT calculation and experimental validation

Aqueous organic redox flow batteries (AORFBs) face challenges of low energy density, which can be addressed by the strategy of redox-targeting (RT) reaction integrating solid materials (SMs) with redox mediators (RMs). However, the potential matching between SM and RM is demanding and complex. In this work, we establish a precise density functional theory (DFT) protocol to predict redox potential in RT-AORFB with anthraquinone-2,7-disulfonic acid (AQDS) derivatives as RM and poly(N-anthraquinoyl pyrrole) (PAQPy) as SM. Theoretical redox potentials are calculated from the Gibbs free energy (GFE) of various molecular models. The results suggest a precise potential match for 1,8-dihydroxyanthraquinone-2,7-disulfonic acid (1,8-DHAQDS) and PAQPy (-1.08 V and -1.09 V vs. SHE). Additionally, hydrogen bonding is involved to make simulation results more realistic, demonstrating a positive potential shift with increased GFE difference for both AQDS derivatives and PAQPy. To further elucidate the influencing mechanism of hydrogen bonding, electrostatic potential (ESP) and HOMO-LUMO gap are integrated together with GFE. The results indicate the introduction of hydrogen bonding results in extended distance for electron tunneling and a larger HOMO-LUMO gap, leading to higher GFE difference and a positive potential shift. Remarkably, results of experimental validations agree well with theoretical potential calculation. Based on predictions results, the RT-AORFB is successfully constructed with the well-matched 1,8-DHAQDS and PAQPy, exhibiting a 3.86-fold capacity enhancement compared to blank AORFB with 1,8-DHAQDS. The integrated DFT approach with GFE, ESP and HOMO-LUMO gap in this work emerges as a promising method for accurately predicting redox potentials in RT systems.

Esthetic Rehabilitation of Congenitally Peg-Shaped Lateral Incisors Using the Injectable Composite Resin Technique: A Clinical Report

ABSTRACT This report details the esthetic dental rehabilitation of a patient with peg-shaped and malformed lateral incisors, conditions that stem from congenital anomalies in tooth formation, using the injectable composite resin technique (ICRT). The ICRT clinical workflow initiates with a smile analysis and precise shade matching, followed by the construction of a diagnostic wax-up crafted according to esthetic and functional guidelines. Subsequently, a mock-up is developed to ensure that the planned restorations fulfill the patient’s functional requirements and esthetic expectations. A transparent silicone index is employed to accurately transfer the patient-approved wax-up into the mouth, utilizing injectable flowable composite resin. This method enhances treatment predictability and ensures that the final direct restoration precisely reflects the approved design within a reasonable chairside timeframe.

Study of fracture monitoring and heat extraction evaluation in geothermal reservoir modified by abandoned well pattern: Numerical models and case studies

The abandoned well pattern for transforming geothermal reservoirs aligns seamlessly with the prevailing shift towards low carbon and enhanced energy efficiency. The effect of anomalous fractures on the effectiveness of heat production is not clear. In this study, we introduce the modified pressure build-up (MPBU) technology tailored for monitoring fracture behavior in geothermal extraction reservoirs. We construct numerical models for geothermal extraction, accounting for dynamic and irregular fractures. Results indicate that the MPBU technology substantially improves the precision of fracture model selection and parameter matching. The interpreted parameters are incorporated into the heat transfer model to assess reservoir heat distribution after 5000 days of extraction. The heat extraction effect of hydraulic fractures is similar to that of irregular fractures. Dynamic fractures have the worst heat extraction effect. Non Sorting Genetic Algorithm II is used to evaluate optimal monitoring and reservoir modification schemes. The innovative technology, numerical models, and optimal solutions will result in an economic improvement of $723,000 per well per year. In conclusion, the integrated monitoring and simulation approach proposed in this paper facilitates efficient and cost-effective differentiation of fracture states, thermal energy extraction evaluation, and optimization of the best extraction strategies to maximize economic benefits for engineers.

An Appearance-Semantic Descriptor with Coarse-to-Fine Matching for Robust VPR.

In recent years, semantic segmentation has made significant progress in visual place recognition (VPR) by using semantic information that is relatively invariant to appearance and viewpoint, demonstrating great potential. However, in some extreme scenarios, there may be semantic occlusion and semantic sparsity, which can lead to confusion when relying solely on semantic information for localization. Therefore, this paper proposes a novel VPR framework that employs a coarse-to-fine image matching strategy, combining semantic and appearance information to improve algorithm performance. First, we construct SemLook global descriptors using semantic contours, which can preliminarily screen images to enhance the accuracy and real-time performance of the algorithm. Based on this, we introduce SemLook local descriptors for fine screening, combining robust appearance information extracted by deep learning with semantic information. These local descriptors can address issues such as semantic overlap and sparsity in urban environments, further improving the accuracy of the algorithm. Through this refined screening process, we can effectively handle the challenges of complex image matching in urban environments and obtain more accurate results. The performance of SemLook descriptors is evaluated on three public datasets (Extended-CMU Season, Robot-Car Seasons v2, and SYNTHIA) and compared with six state-of-the-art VPR algorithms (HOG, CoHOG, AlexNet_VPR, Region VLAD, Patch-NetVLAD, Forest). In the experimental comparison, considering both real-time performance and evaluation metrics, the SemLook descriptors are found to outperform the other six algorithms. Evaluation metrics include the area under the curve (AUC) based on the precision-recall curve, Recall@100%Precision, and Precision@100%Recall. On the Extended-CMU Season dataset, SemLook descriptors achieve a 100% AUC value, and on the SYNTHIA dataset, they achieve a 99% AUC value, demonstrating outstanding performance. The experimental results indicate that introducing global descriptors for initial screening and utilizing local descriptors combining both semantic and appearance information for precise matching can effectively address the issue of location recognition in scenarios with semantic ambiguity or sparsity. This algorithm enhances descriptor performance, making it more accurate and robust in scenes with variations in appearance and viewpoint.

A machine-learning method for biobank-scale genetic prediction of blood group antigens.

A key element for successful blood transfusion is compatibility of the patient and donor red blood cell (RBC) antigens. Precise antigen matching reduces the risk for immunization and other adverse transfusion outcomes. RBC antigens are encoded by specific genes, which allows developing computational methods for determining antigens from genomic data. We describe here a classification method for determining RBC antigens from genotyping array data. Random forest models for 39 RBC antigens in 14 blood group systems and for human platelet antigen (HPA)-1 were trained and tested using genotype and RBC antigen and HPA-1 typing data available for 1,192 blood donors in the Finnish Blood Service Biobank. The algorithm and models were further evaluated using a validation cohort of 111,667 Danish blood donors. In the Finnish test data set, the median (interquartile range [IQR]) balanced accuracy for 39 models was 99.9 (98.9-100)%. We were able to replicate 34 out of 39 Finnish models in the Danish cohort and the median (IQR) balanced accuracy for classifications was 97.1 (90.1-99.4)%. When applying models trained with the Danish cohort, the median (IQR) balanced accuracy for the 40 Danish models in the Danish test data set was 99.3 (95.1-99.8)%. The RBC antigen and HPA-1 prediction models demonstrated high overall accuracies suitable for probabilistic determination of blood groups and HPA-1 at biobank-scale. Furthermore, population-specific training cohort increased the accuracies of the models. This stand-alone and freely available method is applicable for research and screening for antigen-negative blood donors.

Literature Survey for In-Vivo Reynolds and Womersley Numbers of Various Arteries and Implications for Compliant In-Vitro Modelling

PurposeIn-vitro modelling can be used to investigate haemodynamics of arterial geometry and stent implants. However, in-vitro model fidelity relies on precise matching of in-vivo conditions. In pulsatile flow, velocity distribution and wall shear stress depend on compliance, and the Reynolds and Womersley numbers. However, matching such values may lead to unachievable tolerances in phantom fabrication.MethodsPublished Reynolds and Womersley numbers for 14 major arteries in the human body were determined via a literature search. Preference was given to in-vivo publications but in-vitro and in-silico values were presented when in-vivo values were not found. Subsequently ascending aorta and carotid artery case studies were presented to highlight the limitations dynamic matching would apply to phantom fabrication.ResultsSeven studies reported the in-vivo Reynolds and Womersley numbers for the aorta and two for the carotid artery. However, only one study each reported in-vivo numbers for the remaining ten arteries. No in-vivo data could be found for the femoral, superior mesenteric and renal arteries. Thus, information derived in-vitro and in-silico were provided instead. The ascending aorta and carotid artery models required scaling to 1.5× and 3× life-scale, respectively, to achieve dimensional tolerance restrictions. Modelling the ascending aorta with the comparatively high viscosity water/glycerine solution will lead to high pump power demands. However, all the working fluids considered could be dynamically matched with low pump demand for the carotid model.ConclusionThis paper compiles available human haemodynamic information, and highlights the paucity of information for some arteries. It also provides a method for optimal in-vitro experimental configuration.

Identification Dockless Bike-Sharing and Metro Transfer Travelers through Mobility Chain

The burgeoning dockless bike-sharing system presents a promising solution to the first- and last-mile transportation challenge by connecting trip origins/destinations to metro stations. However, the differentiation between metro passengers and DBS riders, as they belong to distinct systems, hinders the precise identification of DBS-metro transfers. This study introduces an innovative method employing mobility chains to establish spatiotemporal relationships, including spatiotemporal conflicts and similarities, among potential users from both systems. This significantly enhances the precision of user matching. An empirical study in Chengdu validates the method’s increased accuracy and examines travel patterns, yielding the following insights: (1) Introduction of the mobility chain reduces average matched pairs by 28.27% and improves accuracy by 18.36%. The addition of spatial-temporal similarity further boosts accuracy by 19.32%. (2) Median distances for DBS-metro access and egress transfers are approximately 950 meters. Short trips of 650–750 meters are prevalent, while trips exceeding 1.5 kilometers lead passengers to opt for alternative modes. (3) Temporal patterns reveal weekday peaks at 8:00, 9:00, and 17:00. On weekends, transfers are uniformly distributed, mainly within urban areas. Suburban stations exhibit reduced weekend activity. These findings can provide valuable insights for enhancing DBS bicycle redistribution, promoting transportation mode integration, and fostering urban transportation’s sustainable development.

The One-Point-One-Line geometry for robust and efficient line segment correspondence

Three-dimensional (3D) lines are common elements in artificial scenes and serve as basic, yet essential features for structural 3D reconstruction. The crucial step of 3D line reconstruction, namely two-view line segment matching, still faces challenges in terms of both accuracy and efficiency improvements. Therefore, robust and efficient constraints are needed to establish valid line candidates. This paper introduces a novel geometry constraint called “one-point-one-line geometry” (OPOL) to enhance the precision of line matching and reduce computational complexity. OPOL offers two remarkable advantages: (1) It takes point orientations as the constraint, which is not only invariant to projective transformations, but also alleviates computational requirements. (2) It needs only one point match to construct the geometry constraint, thus both the grouping and validation are greatly reduced. Additionally, we incorporate the line sweep strategy into OPOL, leveraging depth and space constraints derived from existing 3D points to further enhance efficiency. Extensive experiments conducted on large-coverage and high-resolution images (as large as 10336 × 7788 pixels) demonstrated that OPOL matched lines within a second for an image pair. Both quantitative and qualitative results also demonstrated the superior accuracy and efficiency performance of OPOL. We integrated OPOL into multiple view line reconstruction frameworks, and the promising experimental results reveal the performance of OPOL for robust line reconstruction. The OPOL code is publicly available at https://github.com/JoeAlexxxxx/OPOL.

A stable numerical framework for long-time dynamic crack analysis

This paper introduces a stable numerical framework designed to address dynamic crack problems over long-time intervals. The initial step involves the temporal discretization of the governing dynamic equilibrium equations using the arbitrary order Krylov deferred correction method. To ensure precise boundary condition matching, a novel numerical implementation is incorporated into the Krylov deferred correction technique. Subsequently, the resulting system of spatial partial differential equations at each time node is solved using the meshless generalized finite difference method with 4th-order expansions in regions close to the crack-tips and 2nd-order expansions in areas far from the crack-tips. This combined approach capitalizes on the strengths of both the Krylov deferred correction technique and the generalized finite difference method, enabling stable simulations of dynamic cracks with the large time step and without the need for mesh generation. Notably, we refine the collocation nodes near crack tips to attain accurate numerical results for displacement and stress field. Several numerical experiments involving diverse impact loadings are conducted to validate the developed framework. Furthermore, a comparison is made between the dynamic stress intensity factors obtained using our approach and those from existing methods.

Linking shape conspicuous asymmetry with shape covariation patterns and performance in the insect head and mandibles.

Bilateral symmetry is widespread across animals, yet, among bilaterians, many cases of conspicuous asymmetries evolved. This means that bilaterally homologous structures on the left and right sides display divergent phenotypes. The evolution of such divergent phenotypes between otherwise similarly shaped structures can be thought to be favored by modularity, but this has rarely been studied in the context of left-right differences. Here, we provide an empirical example, using geometric morphometrics to assess patterns of asymmetry and covariation between landmark partitions in a grasshopper with conspicuously asymmetric mandibles. Our morphometric data confirm the presence of strictly directional conspicuous asymmetry in the mandibles and surrounding structures. Covariance patterns and tests hint at a strong integration between mandibles despite their divergent morphologies, and variational modularity with the head capsule. While mandibles have been selected to achieve a key-and-lock morphology by having interlocking shapes, the developmental modularity required to achieve this seems to be overwritten by developmental and/or functional integration, allowing the precise matching required for feeding. The consequent conflicting covariation patterns are reminiscent of the palimpsest model. Finally, the degree of directional asymmetry appears to be under selection, although we find no relationship between bite force and mandible shape or asymmetry.

Synchronizing crowdsourced co-modality between passenger and freight transportation services

This study introduces a synchronized passenger and freight co-modality problem (SPFCP), exploring a crowdsourced co-modality transportation mode where passengers, viewed as an external crowd, volunteer to participate in logistics activities in exchange for compensation. In SPFCP, decision-makers have the option to utilize both crowdsourced passengers (CPs) and self-operated professional couriers (PCs) for deliveries. We formalize the problem and employ a population-based variable neighborhood search to solve it. Our findings indicate that the availability of CPs crucially enhances delivery capacity and efficiency, with the system benefiting from a larger pool of CPs and a higher variability in their travel distances. However, challenges arise from extreme average parcel distances, necessitating precise matching for short distances and extensive crowdsourced resources for long distances. The study underscores the viability of integrating crowdsourced logistics into urban transport systems, suggesting a strategic balance between leveraging crowdsourced solutions and managing logistical complexities.

Manipulating the processing window of directed self-assembly in contact hole shrinking with binary block copolymer/homopolymer blending

Manipulating the processing window of directed self-assembly in contact hole shrinking with binary block copolymer/homopolymer blending

Smart match: revolutionizing organ allocation through artificial intelligence.

In this transformative era of organ transplantation, integrating Smart Match and artificial intelligence (AI) emerges as a pivotal advancement, revolutionizing organ allocation processes. Smart Match employs AI algorithms, enhancing organ matching precision and optimizing transplantation outcomes. Leveraging machine learning addresses complexities in donor-recipient pairing, immunosuppression management, and post-operative care, promising to minimize waitlist mortality and improve patient wellbeing. The multifaceted potential of Smart Match lies in its ability to not only streamline current practices but also pave the way for future innovations in solid organ transplantation. As technology continues to evolve, the collaboration between Smart Match and AI exemplifies a beacon of progress, promising increased efficiency, equitable organ distribution, and improved patient care. This article delves into the paradigm shift facilitated by Smart Match and AI, emphasizing their transformative impact on the landscape of organ allocation and patient outcomes.

Graph-Based Method for Calibration of High-Resolution Mass Spectra of Natural Organic Matter.

Inaccuracies in ion detection and signal processing can undermine confidence in the molecular formula assignment of high-resolution mass spectrometry, which relies on precise matching of the mass-to-charge ratio (m/z). This study proposes a novel graph-based spectra calibration method, MSCMcalib, which implements coordinate transformation and pattern detection. MSCMcalib maps uncalibrated m/z data onto a modified 2D mass defect plot, facilitating the automatic calibration of detected lines, i.e., the calibration of uncalibrated peaks aligned with these lines. The "propagation" method is subsequently employed to accurately and automatically calibrate 605 m/z values across multiple lines, encompassing 98% of the m/z range. The calibrated m/z values divide the m/z range of the spectrum into multiple subintervals, with each subinterval undergoing a process of "scaling" calibration. The utilization of narrower partitions effectively mitigates divergence issues at both ends that arise from the polynomial fitting of errors against m/z. The effectiveness of MSCMcalib is validated through the calibration of SRFA data with m/z error ranges spanning from -10 to -6 ppm, resulting in an additional assignment of 11%-30% more molecular formulas compared to the quadratic fitting calibration.