Optimal Matching Research Articles

Employment trajectories of workers in low-skilled jobs in Western Germany

According to the segmentation theory, low-skilled jobs belong to the secondary sector of the labour market. Low-skilled jobs do not require vocational training and workers are interchangeable. Therefore, workers in this sector have poor working conditions and are regularly affected by employment interruptions. The current state of research, however, does not provide any longitudinal information about individual employment stability of workers performing low-skilled jobs. Furthermore, most of these workers are employed full-time and have completed professional training. Against this background, this paper deals with employment trajectories of workers in low-skilled jobs and their changes over time with regard to standard employment relationship. The aim of the explorative study is to analyse the assignment of workers in low-skilled jobs within the segmentation theory and to determine how segments have changed over time.We use data from the German Socio-Economic Panel (GSOEP) to analyse the employment trajectories of two cohorts aged 35 to 44 years in Western Germany over a period of ten years. The employment trajectories are compared by means of sequence analysis with optimal matching algorithm as well as cluster analysis applying the “Partitioning Around Medoids” method (PAM) in combination with results from hierarchical ward clusters. The employment trajectories indicate that low-skilled jobs can be assigned to both the secondary and the primary sectors. The cohort comparison of employment trajectories shows change and continuity in the context of segments.

Device‐Level Optimization ofn‐Type Mg3(Sb, Bi)2‐Based Thermoelectric Modules toward Applications: A Perspective

AbstractIn recent decades, improvements in thermoelectric material performance have made it more practical to generate electricity from waste heat and to use solid‐state devices for refrigeration. However, despite the development of successful strategies to enhance the figure‐of‐meritzT, optimizing devices for large‐scale applications remains challenging. HighzTvalues do not guarantee excellent device performance, and maintaining highzTover a wide temperature range is difficult. Thus, device‐level structural optimization is crucial for maximizing overall energy conversion efficiency. Proper interfacial and structure design strategies, including contact layer selection, multi‐stage optimization, and size matching for then‐ andp‐type thermoelectric legs, are necessary for advancing device performance. Additionally, thermal stability issues, device assembly techniques, mechanical properties, and manufacturing costs are crucial considerations for large‐scale applications. To achieve actual applications, the thermoelectric community must look beyond simply aiming for highzTvalues. This article focuses on modules based onn‐type Mg3(Sb, Bi)2, one of the most promising commercially available thermoelectric materials, and discusses the influence of various parameters on the modules and on the corresponding device‐level optimization strategies.

Flexural Behavior of RC Beams with NSM Prestressed Helical Rib Steel Wire

The reinforcement technique of near-surface mounted?NSM?prestressed helical rib steel wire (PHRSW) with wide raw material sources, lower in price and high application value can significantly enhance the flexural behavior of reinforced-concrete (RC) structures. Based on 8 flexural RC beams reinforced with NSM PHRSW, performance of test beams under different groove widths (10 mm, 15 mm and 20 mm) and concrete strengths (C30 and C40) was analyzed, including load-deflection, ductility, flexural capacity, strain of longitudinal steel bar and HRSW, failure mode and crack propagation. The results show that the overall flexural behavior RC beams reinforced with NSM PHRSW was significantly improved. There is a good entirety bearing capacity between the longitudinal reinforcement and PHRSW of reinforced beam with suitable groove size. The comprehensive performance of reinforced beams increases first then decreases, with the increase of groove size. The higher the strength of concrete, the more significant the influence of groove size. There is an optimal match between groove width and concrete strength for RC beams reinforced with NSM PHRSW. Considering comprehensive property of reinforced beams, groove width with 15mmwas best in this research. The results can make the research of RC beams reinforced with NSM PHRSW more comprehensive and in-depth, and provide design basis for its engineering application.

An integrated framework for optimal monitoring and history matching in CO$$_{2}$$ storage projects

An integrated framework for optimal monitoring and history matching in CO$$_{2}$$ storage projects

Energy Level Matching and Band Edge Reconfiguration for Enhanced Charge Transport in Dion-Jacobson 3D/2D Perovskite Heterojunctions.

Generally, the 2D CsPbI3 layer capping on 3D counterparts has been considered as an effective strategy for both enhancing photovoltaic efficiency and stability. However, the intrinsically poor out-of-plane charge transport through the 2D layer remarkably hinders the overall performance of solar devices. To overcome such a challenge, we report the rationally designed 3D-CsPbI3/2D-(PYn)PbI4 (n = 1-4) heterojunctions with desirable energy level matching. It is evidenced that the valence band (VB) edge reconfiguration would occur with the increase of n, accompanied by the VB maximum (VBM) of the 2D component moving down from the higher level above that of the 3D component to the underneath. Consequently, the as-constructed 3D/2D-(PYn)PbI4 (n = 1, 2) heterojunctions exhibit optimal energy level matching, with accelerated transport of holes from 3D to 2D component and limited backflow of electrons. These findings might provide some meaningful insights on the energy level matching in 3D/2D perovskite heterojunctions.

Lateral nonlinear vibration of the camshaft considering the structural clearance and load force

To reveal the influence of variations in dynamic characteristics on the working performance of the camshaft, the lateral nonlinear vibration of the camshaft considering the structural clearance and load force is studied. By using the Magnus series expansion method, the response of lateral nonlinear vibration is solved, and the numerical computation scheme applied to the global evolution characteristics of attractors and their basins is developed, which solves the problems of inadequate accuracy and long-term numerical unreliability in numerical solutions and simulations. By analyzing the attractors and basins, single-parameter bifurcation, and bi-parameter dynamic characteristics, the influence of different parameters on the nonlinear dynamic characteristics of the camshaft system is revealed. The results show that as the structural clearance increases, the attraction basins of both periodic and chaotic attractors exhibit tongue-shaped fractal features, and the camshaft system changes from the coexistence of two types of period-3 attractors to chaotic attractors, which reveals the mechanism of global vibration instability of the camshaft system. In addition, when the camshaft system evolves from the flutter to forced vibration conditions, the period-doubling bifurcation behavior occurs, and the parameter ranges for stable operation of the system increase. More importantly, the bi-parameter dynamic characteristics confirm that the parameter ranges for the periodic motion of the system are enlarged when the load force increases, and there exist multi-parameter optimal matching solutions for the stable motion of the camshaft system. The research results reveal the evolution mechanism of the lateral nonlinear vibration of the camshaft, which can provide a theoretical reference for suppressing the vibration and improving the working performance.

Feature tracking and matching for wide-baseline images with closed-loop sequence

Variations in wide-baseline images occur depending on the viewing angle in a three-dimensional reconstruction of oblique photography, leading to instability in interest-point extraction. Traditional methods, however, invalidate wide-baseline images. In this study, a feature-tracking and matching algorithm based on the analysis of closed-loop images is proposed for wide-baseline images. First, the points of interest in each image were extracted using the SuperPoint algorithm. Continuous pairwise matching was then performed using the SuperGlue algorithm. The matching results were used for feature tracking in both the forward and backward directions, and the feature tracking results were combined. Finally, the algorithm filters the points to obtain an optimal matching result. Comparative experiments demonstrated that this method significantly outperforms the existing conventional methods. The proposed method is robust, obtains matching points more uniformly, and performs better than traditional methods for wide-baseline images.

Rerandomization and optimal matching

AbstractOn average, randomization achieves balance in covariate distributions between treatment groups; yet in practice, chance imbalance exists post randomization, which increases the error in estimating treatment effects. This is an important issue, especially in cluster randomized trials, where the experimental units (the clusters) are highly heterogeneous and relatively few in number. To address this, several restricted randomization designs have been proposed to balance on a few covariates of particular interest. More recently, approaches involving rerandomization have been proposed that aim to achieve simultaneous balance on several important prognostic factors. In this article, we comment on some properties of rerandomized designs and propose a new design for comparing two or more treatments. This design combines optimal nonbipartite matching of the subjects together with rerandomization, both aimed at minimizing a measure of distance between elements in blocks to achieve reductions in the mean squared error of estimated treatment effects. Compared with the existing alternatives, the proposed design can substantially reduce the mean squared error of the estimated treatment effect. This enhanced efficiency is evaluated both theoretically and empirically, and robustness properties are also noted. The design is generalized to three or more treatment arms.

Poster 130: Accuracy of Distal Femoral Condyle Osteochondral Allograft Transplantation Using Patient Specific Instrumentation

Objectives: As a surgical treatment option for cartilage defects in the knee, osteochondral allograft (OCA) transplantation reconstructs the damaged area with a fully formed articular hyaline cartilage/osseous unit. For patients undergoing this procedure, topography matching between the donor and recipient sites is essential to limit premature wear of the OCA. To help prevent graft failure, the surgeon must precisely reconstruct the original anatomic curvature of the articular surface. For this to be successful, the graft needs to be chosen and harvested from the correct location on the donor femoral condyle, and then placed correctly on the recipient condyle during surgery to minimize step-off relative to the surrounding cartilage. Currently, the process of donor and recipient graft matching as well as intra-operative techniques to match these surfaces are fairly rudimentary and require significant experience from the treating surgeon. The purpose of this study is to evaluate a novel topography matching technique for distal femoral condyle OCA transplantation using three-dimensional (3D) laser scanning to create 3D printed patient-specific instrumentation in a human cadaveric model. Methods: Twelve cadaveric knees were dissected to isolate the distal femoral condyles (DFC) with cartilage intact and then 3D laser scanned. An 18-mm circular osteochondral recipient defect was virtually created on the medial femoral condyle (MFC) and the position and orientation of the best topography matched osteochondral graft from a paired donor lateral femoral condyle (LFC) was determined using an in-silico analysis algorithm minimizing articular step-off (Figure 1). Donor (LFC) and recipient (MFC) 3D-printed patient-specific guides were created based on 3D reconstructions of the scanned condyles. Using the guides, OCAs were harvested from the previously defined best-match position on the LFC and transplanted to the reamed recipient defect site (MFC) (Figure 2). The post-OCA recipient condyles were laser scanned. The 360-degree articular step-off and cartilage mismatch topography were calculated by a point-to-surface distance calculation algorithm and compared to the in-silico result. Results: The in-silico cartilage step-off and graft perimeter mismatch for the virtual OCA transplant was 0.073 ± 0.029 mm (range: 0.005-0.113 mm) and 0.166 ± 0.039 mm (range: 0.120-0.243 mm), respectively. Comparatively, our cadaveric specimens post-implant had significantly larger step-off differences (0.173 ± 0.085 mm, range: 0.082-0.399 mm, P = 0.001) but equivalent surface topography matching (0.181 ± 0.080 mm, range: 0.087-0.396 mm, P = 0.678). Conclusions: This novel technique for OCA articular step-off and topography matching demonstrated the ability to optimize cartilage topography matching for LFC to MFC transplantation. Despite a larger mean step-off in the cadaveric specimens compared to the ideal in-silico model, our study demonstrated substantially lower mismatch values compared to previous orthopedic literature evaluating LFC to MFC transplantation that reported means of 0.48 mm for articular step-off (range: 0.335-0.738 mm) and 0.63 mm for surface area mismatch (range: 0.349-1.461 mm). It should be noted that clinically, surgeons performing OCA for the femoral condyles will preferentially select the ipsilateral condyle from the donor to take a plug for the recipient, as this will generally allow for optimal surface matching. Our results show better mismatch values than prior work using this contralateral technique, and even the maximum step-off distance in our cadaveric model fell well below the 0.5 cm –1.0 cm maximum step-off values assigned to be clinically significant by prior studies evaluating ipsilateral OCA transplantations. Using this novel technique in a model performing MFC to MFC transplantation would likely yield further enhanced results due to improved radii of curvature matching. Improving upon topography matched graft implantation for focal chondral defects of the knee in young patients will improve surface matching and associated long-term outcomes. Additionally, efficient selection of the allograft using patient-specific guides would also improve availability of the limited allograft sources and reduce surgical time.

Research on user requirements preprocessing of imaging reconnaissance satellites

Aiming at how to solve the problem of optimal matching between imaging reconnaissance user requirements and satellite resources, this paper conducts research on the preprocessing of imaging reconnaissance satellite requirements. First, considering the remote sensor type and resolution of imaging satellites, a requirement-resource matching matrix is constructed to realize the preliminary matching between user requirements and imaging reconnaissance satellite resources. Secondly, starting from the time constraints, by calculating the observation time window of requirement and resources, the time requirements of satellite resources and user requirements are matched. Finally, in order to solve the problem that the same observation task can be completed by multiple imaging satellites, a conflict resolution method based on resource consumption is proposed, which effectively improves the preprocessing ability of user requirements.

Building Tilt Scanning Measurement Based on Binary Linear Regression Analysis

Abstract With the development of modern surveying and mapping technology, 3D laser scanners are increasingly used for building dip scanning. Building inclination characteristics are analyzed using three-dimensional point cloud data and binary linear regression. It can easily and intuitively obtain the inclination of the building. This method extracted the building inclination Angle from the point, line, plane, surface, and other angles. Then, a matching method based on two dimensions and surfaces is proposed, with a strong anti-noise ability. An optimal matching algorithm of structural plane and surface based on quadratic linear regression is proposed. Experiments prove the anti-interference ability and accuracy of this method. It is found that the binary linear regression fitting method can effectively identify the noise signal when there is a lot of noise interference in the point cloud data. It has good anti-interference ability.

Optimizing Patient Record Linkage in a Master Patient Index Using Machine Learning: Algorithm Development and Validation

Background To provide quality care, modern health care systems must match and link data about the same patient from multiple sources, a function often served by master patient index (MPI) software. Record linkage in the MPI is typically performed manually by health care providers, guided by automated matching algorithms. These matching algorithms must be configured in advance, such as by setting the weights of patient attributes, usually by someone with knowledge of both the matching algorithm and the patient population being served. Objective We aimed to develop and evaluate a machine learning–based software tool, which automatically configures a patient matching algorithm by learning from pairs of patient records previously linked by humans already present in the database. Methods We built a free and open-source software tool to optimize record linkage algorithm parameters based on historical record linkages. The tool uses Bayesian optimization to identify the set of configuration parameters that lead to optimal matching performance in a given patient population, by learning from prior record linkages by humans. The tool is written assuming only the existence of a minimal HTTP application programming interface (API), and so is agnostic to the choice of MPI software, record linkage algorithm, and patient population. As a proof of concept, we integrated our tool with SantéMPI, an open-source MPI. We validated the tool using several synthetic patient populations in SantéMPI by comparing the performance of the optimized configuration in held-out data to SantéMPI’s default matching configuration using sensitivity and specificity. Results The machine learning–optimized configurations correctly detect over 90% of true record linkages as definite matches in all data sets, with 100% specificity and positive predictive value in all data sets, whereas the baseline detects none. In the largest data set examined, the baseline matching configuration detects possible record linkages with a sensitivity of 90.2% (95% CI 88.4%-92.0%) and specificity of 100%. By comparison, the machine learning–optimized matching configuration attains a sensitivity of 100%, with a decreased specificity of 95.9% (95% CI 95.9%-96.0%). We report significant gains in sensitivity in all data sets examined, at the cost of only marginally decreased specificity. The configuration optimization tool, data, and data set generator have been made freely available. Conclusions Our machine learning software tool can be used to significantly improve the performance of existing record linkage algorithms, without knowledge of the algorithm being used or specific details of the patient population being served.

Towards a luminescent solar concentrator with ultra-broadband absorption and spectral conversion for optimizing photovoltaic solar cell response: “The photonic cannon shot”

Solar energy harvesting is largely limited by the spectral sensitivity of the employed photovoltaic solar cell, since typically the full potential of each photon of the whole solar spectrum is not efficiently used in the generation of electricity. Therefore, increasing the overall solar spectrum utilization is of crucial interest and stands up as a frontier-of-research approach in the photovoltaic sector. Here we present an innovative ultra-broadband absorption and multiple spectral conversion approach, by means of rare-earth doped materials together with organic dyes embedded in a luminescent solar concentrator. The combination of different luminescent materials is a key factor for improving energy harvesting over the whole solar spectrum. At the same time, a simultaneously combined effect of up-conversion and down-shifting of light is aimed to optimal spectral matching with amorphous silicon solar cells response. Thus, UV–visible photons coming from the incoming sunlight, together with UV–visible up-converted photons coming from near-infrared radiation, can be all shifted to the yellow-orange-red part of the spectrum. To the best of our knowledge, this represents the first reported proof-of-concept using LSCs with up-conversion and down-shifting photonic processes working together and sequentially.

Improving heat supply of ammonia-water absorption heat transformer by enlarging heat source utilization temperature span

Compared with the LiBr–H2O absorption heat transformers, the NH3–H2O ones show greater application potential without the risk of crystallization and corrosion at high operating temperatures, while with the main drawback of lower COP. However, the heating capacity of systems at given heat source conditions attracts more attention for users than COP. Therefore, this work aims to increase the heating capacity of the NH3–H2O system by enlarging the temperature utilization span of the heat source. To achieve this, a temperature-changing generation process is introduced and generator configurations are modified. The comparison results with the literature indicate that the heating capacity of the proposed NH3–H2O system at given heat source conditions is equal to and even higher than the LiBr–H2O systems. In addition, it is found that the temperature matching with the heat source influences the system exergy efficiency. The maximum system exergy efficiency of 49.7% is realized when the optimum temperature matching is achieved. It is hoped that this work has eliminated influences of low COP drawbacks on NH3–H2O absorption heat transformers and promotes its practical application of low-grade heat recovery and low-carbon heating.

The Uncertainty of SNO Cross-Calibration for Satellite Infrared Channels

The on-orbit radiometric calibration is a fundamental task in quantitative remote sensing applications. A widely used calibration method is the cross-calibration based on Simultaneous Nadir Observation (SNO), which involves using high-precision reference instruments to calibrate lower-precision onboard instruments. However, despite efforts to match the observation time, spatial location, field geometry, and instrument spectra, errors can still be introduced during the matching processes and linear regression analysis. This paper focuses on the error generated by sample matching and the error fitting method generated by the sample fitting method. An error propagation analysis is performed to develop a generic model for assessing the uncertainty of the SNO cross-calibration method itself in meteorological satellite infrared channels. The model is validated using the payload parameters of the Hyperspectral Infrared Atmospheric Sounder (HIRAS) and the Medium Resolution Spectral Imager (MERSI) instruments aboard the FengYun-3D (FY-3D). Simulation experiments are performed considering typical bright temperatures, different background fields, and varying matching threshold conditions. The results demonstrate the effectiveness of the proposed model in capturing the error propagation chain in the SNO cross-calibration process. The model provides valuable insight into error analysis in the SNO cross-calibration method and can assist in determining the optimal sample matching threshold for achieving radiometric calibration accuracy.

Explainable human‐in‐the‐loop healthcare image information quality assessment and selection

AbstractSmart healthcare applications cannot be separated from healthcare data analysis and the interactive interpretability between data and model. A human‐in‐the‐loop active learning approach is introduced to reduce the cost of healthcare data labelling by evaluating the information quality of unlabelled medical data and then screening the high informative samples. Specifically, focused on the extracted feature tensor of medical images, a new evaluation metric was proposed, called local feature information distance. Then, the whole feature information distance between two images can be obtained by seeking optimal matching of local feature information correlation based on the feature spatial traversal. Further, the feature information distance entropy (FIDE) method was proposed from the perspective of feature spatial distribution, which outperformed other related works. Many comparison and ablation experiments were carried out; the results showed that the proposed method can well distinguish the information quality of the unlabelled samples even facing different datasets. The stability, robustness, and generalisation of the proposed method were verified. Thus, this study provides some inspirations for healthcare data analysis and efficient management, such as eliminating redundancy and selective annotation.

Enhancing emission in a QD–nanodisk system via the alignment of the orientation of excitons with the polarization of Mie modes

A Ge quantum dot (QD)–resonator system is an attractive solution for the Si-based emitter applied in monolithic optical–electronic integrated circuits, in which efficient coupling of QDs and cavity modes is crucial for achieving significant emission enhancement. Here, we present unique emission characteristics of a Ge QD–nanodisk array system based on the spatial matching of the two components. In this system, the two-order-of-magnitude emission enhancement is derived from self-assembled QDs, which is related to the orientation of excitons in QDs coinciding with a vertical-polarized Mie mode. In addition, the emission efficiency is also strongly dependent on the position of the QDs in nanodisks. As the orientation of the emitter is matched with the polarized mode, and the QD is located at the maximum of the field, optimal spatial matching can be achieved. These experimental and simulated results demonstrate the importance of spatial matching between emitters with proper polarization and cavity modes, which promises the realization of efficient on-chip light sources.

Optimization of Subthreshold Swing and Hysteresis in Hf0.5Zr0.5O2-Based MoS2 Negative Capacitance Field-Effect Transistors by Modulating Capacitance Matching.

Negative capacitance field effect transistors made of Hf0.5Zr0.5O2 (HZO) are one of the most promising candidates for low-power-density devices because of the extremely steep subthreshold swing and high open-state currents resulting from the addition of ferroelectric materials in the gate dielectric layer. In this paper, HZO thin films were prepared by magnetron sputtering combined with rapid thermal annealing. Their ferroelectric properties were adjusted by changing the annealing temperature and the thickness of HZO. Two-dimensional MoS2 back-gate negative capacitance field-effect transistors (NCFETs) based on HZO were prepared as well. Different annealing temperatures, thicknesses of HZO thin films, and Al2O3 thicknesses were studied to achieve optimal capacitance matching, aiming to reduce both the subthreshold swing of the transistor and the hysteresis of the NCFET. The NCFET exhibits a minimum subthreshold swing as low as 27.9 mV/decade, negligible hysteresis (∼20 mV), and the ION/IOFF of up to 1.58 × 107. Moreover, a negative drain-induced barrier lowering effect and a negative differential resistance effect have been observed. This steep-slope transistor is compatible with standard CMOS manufacturing processes and attractive for 2D logic and sensor applications as well as future energy-efficient nanoelectronic devices with scaled power supplies.

In-situ measurement of anisotropic Young’s modulus in fused deposition modeling printed cantilevers

In this study, we investigate the effect of fused deposition modeling printing direction on the effective Young’s modulus value of cantilevers. Through finite-element simulations and experiments with seven different dimensions and totaling over 100 cantilevers, we have observed the impact of printing direction on cantilever resonance. Unlike the conventional compressive and tensile stress—strain characterization, observation of the resonance allows for in-situ testing on the final device under test during operation. Initially, we observed the bulk filament modulus to be 4.5 GPa based on the optimal match between experiments and realistic finite element models expressing the internal structures of the longitudinal and transverse printed cantilevers. Then, the effective Young’s modulus of the cantilevers is inferred through sweeping the Young’s modulus that provides the best fit between the experiments, conventional cantilever formulations and finite-element simulations with solid, homogeneous, and isotropic cantilever model. Overall, we observed an average effective Young’s modulus of 3.35 GPa for the cantilevers with longitudinal (along the cantilever axis) deposited filaments and an average effective Young’s Modulus of 2.50 GPa for the transverse (perpendicular to the cantilever axis, along the width dimension) deposited Polylactic acid cantilevers. Eventually, simplified shape outline and effective Young’s modulus for the corresponding printing direction eases the subsequent theoretical and simulation analyses. The presented methodology is also applicable to micrometric and sub-micrometric scale serial manufacturing techniques (i.e. two-photon polymerization) where the laser beams steering direction causes anisotropy in the mechanical properties of the device under test.

Binding of different hyaluronan to CD44 mediates distinct cell adhesion dynamics under shear flow.

As a known receptor-ligand pair for mediating cell-cell or cell-extracellular matrix adhesions, cluster of differentiation 44 (CD44)-hyaluronan (HA) interactions are not only determined by molecular weight (MW) diversity of HA, but also are regulated by external physical or mechanical factors. However, the coupling effects of HA MW and shear flow are still unclear. Here, we compared the differences between high molecular weight HA (HHA) and low molecular weight HA (LHA) binding to CD44 under varied shear stresses. The results demonstrated that HHA dominated the binding phase but LHA was in favour of the shear resistance phase, respectively, under shear stress range ≤ 1.0 dyne·cm-2 . This difference was attributed to the high binding strength of the CD44-HHA interaction, as well as the optimal distribution matching between both CD44 and HA sides. Activation of the intracellular signal pathway was sensitive to both HA MW and shear flow. Our findings also indicate that only CD44-HHA interaction under shear stress of 0.2 dyne·cm-2 could significantly enhance the clustering of CD44, as well as induce the increase in both CD44 and CD18 expression. The present study offers the basis for further quantification of the features of CD44-HA interactions and their biological functions.