Matching Function Research Articles

Optical vortex trajectory of the edge-diffracted single-charged Laguerre-Gaussian beam

The paper deals with the edge diffraction of the single charged Laguerre-Gaussian beam outside the waist. Based on the Kirchhoff-Fresnel integral, the behavior of the optical vortex (OV) migration during sequential beam blocking by the straight edge of the screen is performed analytically. Universal combination of the diffracting-beam parameters determining the shape for the OV spiral trajectories is revealed. Parametric equations describing the OV dislocation dependent on the beam screening degree are derived. In addition, the spiral trajectory, which describes the OV positions in the case of the screen-edge translatory motion across the incident beam under conditions of the weak diffraction perturbation, is obtained. As a result, the equation for a wider region of diffraction perturbation is selected as a best matching function for a certain variation interval of the beam parameters. The work has prepared the basis for solving the inverse diffraction problem: determining parameters of the beam diffractive interaction with obstacles from the migration trajectory of the optical vortex.

Terrain Elevation Map Synthesis Method based on Single Sample and User Sketch

Terrain synthesis has been a hot topic in the field of computer graphics and image processing. However, there are still issues in terrain synthesis where synthesis results are difficult to control and not realistic enough. To address these problems, this paper proposes an interactive terrain elevation map generation method based on the synthesis of a single sample terrain elevation map. First, we propose a method to extract the skeleton from a terrain elevation map and a user sketch. Second, we construct a skeleton sample feature map based on the terrain elevation map and the user sketch. Finally, we propose a matching cost function to match image patches of the terrain sample and the user sketch. The proposed method can obtain a synthesis result containing the features of both the terrain sample and the user sketch, and then generates a synthetic terrain elevation map. The experimental results demonstrate the effectiveness of the proposed method, where the synthesized results can meet the needs of users.

Designing Color Filters That Make Cameras More Colorimetric.

When we place a colored filter in front of a camera the effective camera response functions are equal to the given camera spectral sensitivities multiplied by the filter spectral transmittance. In this article, we solve for the filter which returns the modified sensitivities as close to being a linear transformation from the color matching functions of the human visual system as possible. When this linearity condition - sometimes called the Luther condition- is approximately met, the 'camera+filter' system can be used for accurate color measurement. Then, we reformulate our filter design optimisation for making the sensor responses as close to the CIEXYZ tristimulus values as possible given the knowledge of real measured surfaces and illuminants spectra data. This data-driven method in turn is extended to incorporate constraints on the filter (smoothness and bounded transmission). Also, because how the optimisation is initialised is shown to impact on the performance of the solved-for filters, a multi-initialisation optimisation is developed. Experiments demonstrate that, by taking pictures through our optimised color filters, we can make cameras significantly more colorimetric.

A Mathematical Investigation into the Design of Prefilters That Make Cameras More Colorimetric.

By placing a color filter in front of a camera we make new spectral sensitivities. The Luther-condition optimization solves for a color filter so that the camera’s filtered sensitivities are as close to being linearly related to the XYZ color matching functions (CMFs) as possible, that is, a filter is found that makes the camera more colorimetric. Arguably, the more general Vora-Value approach solves for the filter that best matches all possible target spectral sensitivity sets (e.g., any linear combination of the XYZ CMFs). A concern that we investigate here is that the filters found by the Luther and Vora-Value optimizations are different from one another. In this paper, we unify the Luther and Vora-Value approaches to prefilter design. We prove that if the target of the Luther-condition optimization is an orthonormal basis—a special linear combination of the XYZ CMFs which are orthogonal and are in unit length—the discovered Luther-filter is also the filter that maximizes the Vora-Value. A key advantage of using the Luther-condition formulation to maximize the Vora-Value is that it is both simpler to implement and converges to its optimal answer more quickly. Experiments validate our method.

Effect of moxibustion at sensitized-acupoints on quality of life in patients with chronic superficial gastritis

To compare the efficacy difference between moxibustion at sensitized-acupoints and non-sensitized-acupoints using the same group of acupoints. A total of 139 patients with chronic superficial gastritis were divided into a sensitized acupoint group (102 cases) and a non-sensitized acupoint group (37 cases) based on whether acupoint sensitization occurred. The SPSS version 19.0 statistical software propensity score matching function was used to balance the baseline data between the groups. Finally, 29 pairs of matched patients were included, namely 29 cases in the sensitized acupoint group and 29 cases in the non-sensitized acupoint group. Both groups were treated with moxibustion therapy. The treatment lasted for 30 min per time, and was performed every other day for 8 weeks. Changes in the traditional Chinese medicine (TCM) symptom score and the short-form 36-item health survey (SF-36) score in both groups were observed before and after treatment, as well as the clinical efficacy. The covariates of age, course of disease, TCM symptom score and SF-36 score in the two groups were balanced after matching (all P<0.05). After treatment, the total effective rate was 100.0% in the sensitized acupoint group and 79.3% in the non-sensitized acupoint group. The difference in the total effective rate between the two groups was statistically significant (P<0.01). After treatment and at the 4-week follow-up, the TCM symptom scores in the sensitized acupoint group were significantly lower than those in the non-sensitized acupoint group (all P<0.01); the SF-36 scores in the sensitized acupoint group were significantly higher than those in the non-sensitized acupoint group (all P<0.01). With the same group of acupoints, the sensitized acupoints have a better therapeutic effect and long-term efficacy than the non-sensitized acupoints in the treatment of chronic superficial gastritis.

Hybrid Hole Extraction Layer Enabled High Efficiency in Polymer Solar Cells.

Charge extraction layers with excellent charge extraction capability are essential for achieving high photovoltaic performance in cells. In this work, a hole extraction layer (HEL) is developed by doping conductive polymer TFB into CuSCN (CuSCN:TFB(X)), which exhibits good light transparency and high affinity for the light absorber. Compared to the reference cell, the CuSCN:TFB(X) HEL-based cells show impressive enhancement owing to the increased exciton dissociation and charge extraction processes and weak recombination losses. Furthermore, matched work function, better interface contact, and appropriate domain size also contribute to the enhanced power conversion efficiency. As a consequence, the highest conversion efficiency of 15.28% is observed in a cell based on the PM6:Y6 blend film and CuSCN:TFB(1.0%) HEL, which is >16% higher than the efficiency of 13.13% in a cell with CuSCN HEL.

Thyroid Function Before, During, and After COVID-19.

ContextThe effects of COVID-19 on the thyroid axis remain uncertain. Recent evidence has been conflicting, with both thyrotoxicosis and suppression of thyroid function reported.ObjectiveWe aimed to detail the acute effects of COVID-19 on thyroid function and determine if these effects persisted on recovery from COVID-19.DesignA cohort observational study was conducted.Participants and SettingAdult patients admitted to Imperial College Healthcare National Health Service Trust, London, UK, with suspected COVID-19 between March 9 to April 22, 2020, were included, excluding those with preexisting thyroid disease and those missing either free thyroxine (FT4) or thyrotropin (TSH) measurements. Of 456 patients, 334 had COVID-19 and 122 did not.Main Outcome MeasuresTSH and FT4 measurements were recorded at admission, and where available, in 2019 and at COVID-19 follow-up.ResultsMost patients (86.6%) presenting with COVID-19 were euthyroid, with none presenting with overt thyrotoxicosis. Patients with COVID-19 had a lower admission TSH and FT4 compared to those without COVID-19. In the COVID-19 patients with matching baseline thyroid function tests from 2019 (n = 185 for TSH and 104 for FT4), TSH and FT4 both were reduced at admission compared to baseline. In a complete case analysis of COVID-19 patients with TSH measurements at follow-up, admission, and baseline (n = 55), TSH was seen to recover to baseline at follow-up.ConclusionsMost patients with COVID-19 present with euthyroidism. We observed mild reductions in TSH and FT4 in keeping with a nonthyroidal illness syndrome. Furthermore, in survivors of COVID-19, thyroid function tests at follow-up returned to baseline.

Designing a Color Filter via Optimization of Vora-Value for Making a Camera more Colorimetric

Previous work has proposed to solve for a filter which, when placed in front of a camera, improves the colorimetric property by best satisfying the Luther condition. That is, the filtered spectral sensitivities of a camera - after a linear transform - are as close to the color matching functions of the human visual system as possible. By construction, the prior art solves for a filter for a given set of human visual sensitivities, e.g.the XYZ color matching functions or the cone response functions. However, depending on the target spectral sensitivity set, a different optimal filter is found. In this paper, we set out a method to solve for a filter that works equally well for all possible target sensitivity sets of the human visual system. We observe that the cone fundamentals, the CIE XYZ color matching functions or any linear combination thereof, span the same vector space. Thus, we solve for a filter that makes the vector space spanned by the filtered camera sensitivities as similar as possible to the space spanned by human vision sensors. We argue that the Vora-Value is a suitable way to measure subspace similarity and we develop an optimization method for finding a filter that maximizes the Vora-Value measure. Experiments demonstrate that our new optimization leads to the filtered camera sensitivities which have a significantly higher Vora-Value and improved colorimetric performance compared with antecedent methods.

Observer metamerism to display white point between LCD and OLED displays

Displays with different primary sets were found to introduce perceived color mismatch between pairs that are computationally metameric and to affect the degree of observer metamerism. OLED display is becoming more and more popular than LCD display in different imaging systems. In this study, human observers used an LCD and eight OLED displays to match the color appearance of a D 70 white stimulus produced by a spectrally tunable LED device. It was found the chromaticities of the LCD display were significantly different from those of the OLED displays to achieve a match. When the colors were adjusted to have matched appearance, the chromaticities of the OLED displays were always shifted towards closer to the blackbody locus using the CIE 1931 Color Matching Functions (CMFs). The results also suggested that the CIE 2006 2° Color Matching Functions had the best performance.

Labor mobility within Japanese regional labor markets and spillover effects

This paper re-estimates the regional job-matching function using annual panel data covering 47 Japanese prefectures from 1987 to 2013, controlling for spillovers and agglomeration effects across prefectures, in addition to prefecture-level labor market determinants and prefecture and time fixed effects. The estimates reveal that the number of job matches rises together with rising stocks of unemployed and vacancies within and across prefectures suggesting significant spillover effects. A model comparison shows that the spatial spillovers are best captured using a contiguity weight matrix and are restricted to the local labor markets. Finally, the estimates of the matching function in different periods indicate that job seekers have substantially shifted their job-search behavior over time.

AligNet: alignment of protein-protein interaction networks

BackgroundAll molecular functions and biological processes are carried out by groups of proteins that interact with each other. Metaproteomic data continuously generates new proteins whose molecular functions and relations must be discovered. A widely accepted structure to model functional relations between proteins are protein-protein interaction networks (PPIN), and their analysis and alignment has become a key ingredient in the study and prediction of protein-protein interactions, protein function, and evolutionary conserved assembly pathways of protein complexes. Several PPIN aligners have been proposed, but attaining the right balance between network topology and biological information is one of the most difficult and key points in the design of any PPIN alignment algorithm.ResultsMotivated by the challenge of well-balanced and efficient algorithms, we have designed and implemented AligNet, a parameter-free pairwise PPIN alignment algorithm aimed at bridging the gap between topologically efficient and biologically meaningful matchings. A comparison of the results obtained with AligNet and with the best aligners shows that AligNet achieves indeed a good balance between topological and biological matching.ConclusionIn this paper we present AligNet, a new pairwise global PPIN aligner that produces biologically meaningful alignments, by achieving a good balance between structural matching and protein function conservation, and more efficient computations than state-of-the-art tools.

Binaural Pitch Fusion in Children With Normal Hearing, Hearing Aids, and Cochlear Implants.

Binaural pitch fusion is the perceptual integration of stimuli that evoke different pitches between the ears into a single auditory image. Adults who use hearing aids (HAs) or cochlear implants (CIs) often experience abnormally broad binaural pitch fusion, such that sounds differing in pitch by as much as 3 to 4 octaves are fused across ears, leading to spectral averaging and speech perception interference. The main goal of this study was to measure binaural pitch fusion in children with different hearing device combinations and compare results across groups and with adults. A second goal was to examine the relationship of binaural pitch fusion to interaural pitch differences or pitch match range, a measure of sequential pitch discriminability. Binaural pitch fusion was measured in children between the ages of 6.1 and 11.1 years with bilateral HAs (n = 9), bimodal CI (n = 10), bilateral CIs (n = 17), as well as normal-hearing (NH) children (n = 21). Depending on device combination, stimuli were pure tones or electric pulse trains delivered to individual electrodes. Fusion ranges were measured using simultaneous, dichotic presentation of reference and comparison stimuli in opposite ears, and varying the comparison stimulus to find the range that fused with the reference stimulus. Interaural pitch match functions were measured using sequential presentation of reference and comparison stimuli, and varying the comparison stimulus to find the pitch match center and range. Children with bilateral HAs had significantly broader binaural pitch fusion than children with NH, bimodal CI, or bilateral CIs. Children with NH and bilateral HAs, but not children with bimodal or bilateral CIs, had significantly broader fusion than adults with the same hearing status and device configuration. In children with bilateral CIs, fusion range was correlated with several variables that were also correlated with each other: pure-tone average in the second implanted ear before CI, and duration of prior bilateral HA, bimodal CI, or bilateral CI experience. No relationship was observed between fusion range and pitch match differences or range. The findings suggest that binaural pitch fusion is still developing in this age range and depends on hearing device combination but not on interaural pitch differences or discriminability.

Numerical Investigation of Consolidation Induced by Prefabricated Horizontal Drains (PHD) in Clayey Deposits

In this work, the process of prefabricated horizontal drains (PHD) induced consolidation in clayey embankment fills is investigated by a numerical approach. Based on spacing parameters, the suitability of axisymmetric and plane strain conditions for modeling the drain has been studied, and the suitability zones and matching functions have been proposed. The implications of the use of elastoplastic models to simulate the behavior of in situ soil on the suitability zones and matching functions have also been studied. The numerical results were compared with the analytical unit cell solutions for axisymmetric and plane strain conditions. Further, the effect of PHD in improving the consolidation behavior of various soil types has been analyzed in terms of pore pressure dissipation and settlement. The studies showed that the drain improved ground is best modeled under axisymmetric conditions at lower spacing ratios, and plane strain conditions simulate the more distantly spaced cases. PHD was found to accelerate the consolidation process in soft soils significantly, and the effect was found to be most prominent in highly plastic soils.

Optimal planning and investment benefit analysis of shared energy storage for electricity retailers

With the rapid development of energy storage (ES) technology, it has gradually become a vital facility to cope with the intermittent renewable generation and reduce the users’ electricity purchase cost. However, the limited application of the ES has suffered from its high capital cost. This paper proposes an approach of optimal planning the shared energy storage based on cost-benefit analysis to minimize the electricity procurement cost of electricity retailers. First, the multi-time scale electricity purchase model is established. Then the retailers are screened and classified based on the proposed matching degree function to select the collective of retailers, which maximizes the profits of planning the shared ES. The life cycle cost model and the equivalent cycle life method are used to evaluate the benefit of investing the shared ES. The benefit distribution among the collective is conducted based on the contribution degree of each retailer. In the case study, the optimization results of the shared ES for high-matching and low-matching groups are compared in detail. The simulation results illustrate that the costs are reduced by 8.83% and 8.03% respectively for the two groups of electricity retailers by the proposed approach. Results also verify that ES can effectively reduce the cost of retailers, and high matching degree can be used as the selection criterion to obtain a greater benefit of the shared ES.

Building-Specific Recognition Algorithms Based on Image Sequence

Building extraction, recognition and corresponding three-dimensional modeling in image is an active research field, which is mainly applied to map feature extraction, urban population survey and so on. It has important significance in military and civil areas. Aiming at the shortcoming of the classical invariant feature extraction algorithm, a building recognition algorithm based on local feature and shape contour matching is proposed. Firstly, according to the fact that the whole building is susceptible to rotation and inclination, the local feature points of known buildings are extracted, and their orientation, position and angle are determined. At the same time, the similarity criterion and mapping function of arbitrary shape contour matching are formulated according to the scale change information of buildings in different states, and the building recognition under different illumination and scales is realized. The simulation results show that the method can quickly and accurately adapt to the construction in different environments. The accuracy of this method fluctuates around 97%, while the average accuracy of 20 experiments is 96.56%. The average accuracy of the SFBR method is 94.66%. Compared with the SFBR and SIFT methods, the average accuracy of the method is improved by nearly 2%.

HLA Matching in Cardiac Transplantation - Impact on Cardiac Allograft Vasculopathy, Rejection and Donor Specific Antibodies

Introduction HLA matching is not current practice in heart transplant (HT) donor allocation due to scarcity of donor organs and ischemic time. However HLA mismatch might adversely affect transplant outcomes. Even if HLA matching is not possible the degree of HLA mismatch might help inform clinicians on a patients risk for long term transplant complications. Hypothesis We hypothesize that the degree of HLA mismatch affects long-term complications in a stable HT cohort. Methods 65 clinically stable HT recipients (no cellular (ACR) or antibody mediated rejection (AMR) in the preceding 6 months) ≥ 2 years post transplant were enrolled. Serologic HLA typing was obtained for donor and recipients (D/R) pairs and the number of matches was analyzed combined for HLA class I and HLA II. Study endpoints were donor specific antibody (DSA) formation and significant cardiac allograft vasculopathy (CAV). Results HLA-A,-B,-C, -DR and-DQ (ABCDRQ) typing were available for 37 D/R pairs and were analyzed for matches. Additionally, 53 D/R pairs had HLA-A,-B, -DR (ABDR) typing. Meantime post HT was 8.5±5.4 years. A total of 28 patients had CAV and 9 patients had DSA. Among the ABCDRDQ cohort the number of matches was 1.54 ± 1.17 and 1.00 (0.00-1.00) in the ABDR cohort. There were no differences in the number of HLA matches for both cohorts among those with and without DSA and those with and without CAV (Table).However among the ABCDRDQ cohort there was a trend towards higher number of HLA matches in those without DSA 1.63 ± 1.19 versus 1.14 ± 1.07 in the DSA group (p 0.32), this was likely limited by the small sample size.There was no significant relationship between total HLA matches and number of ACR episodes (p 0.89). The incidence of AMR was too low for analysis. Conclusion In this highly selected cohort of clinically stable long time transplant survivors the degree of serological HLA matching was not associated with the development of CAV or ACR. However, there was a trend towards less DSA formation in those with more D/R HLA matches. Future longitudinal studies should evaluate the development of long-term complications as a function of HLA matching and potentially incorporate HLA mismatch as an indicator for the need of enhanced clinical surveillance.

Designing a physically-feasible colour filter to make a camera more colorimetric

Previously, a method has been developed to find the best colour filter for a given camera which results in the new effective camera sensitivities that best meet the Luther condition. That is, the new sensitivities are approximately linearly related to the XYZ colour matching functions. However, with no constraint, the filter derived from this Luther-condition based optimisation can be rather non-smooth and transmit very little light which are impractical for fabrication. In this paper, we extend the Luther-condition filter optimisation method to allow us to incorporate both the smoothness and transmittance bounds of the recovered filter which are key practical concerns. Experiments demonstrate that we can find physically realisable filters which are smooth and reasonably transmissive with which the effective 'camera+filter' becomes significantly more colorimetric.

A Framework of Matching Algorithm for Influencer Marketing

Modern lifestyles have been altered significantly by recent developments in information and communications technology. In the marketing field, enterprises often use video advertising because of its effectiveness. The number of content producers is increasing, and YouTube is an effective medium for advertising. This advertising method is called ‘influencer marketing.’ Therefore, both the demand and the supply are increasing in the field of video advertising. In the present study, this trend was analysed from the viewpoints of an enterprise and a content producer. Then, a new business model was developed for increasing the demand and supply. The business model includes a matching function between enterprises and content producers for video advertising to achieve such increases. Second, a matching algorithm based on the calculation of the relativity between enterprises and content producers was proposed. Because the inputs of an enterprise and content producer include both numerical and textual data, a relativity-value calculation algorithm using these inputs was developed. Moreover, the feasibility of the proposed algorithm was evaluated.

Physics and Geometry of Knots-Quivers Correspondence

The recently conjectured knots-quivers correspondence (Kucharski et al. in Phys Rev D 96(12):121902, 2017. arXiv:1707.02991 , Adv Theor Math Phys 23(7):1849–1902, 2019. arXiv:1707.04017 ) relates gauge theoretic invariants of a knot K in the 3-sphere to the representation theory of a quiver $$Q_{K}$$ associated to the knot. In this paper we provide geometric and physical contexts for this conjecture within the framework of Ooguri-Vafa large N duality (Ooguri and Vafa in Nucl Phys B 577:419–438, 2000), that relates knot invariants to counts of holomorphic curves with boundary on $$L_{K}$$ , the conormal Lagrangian of the knot in the resolved conifold, and corresponding M-theory considerations. From the physics side, we show that the quiver encodes a 3d $${\mathcal {N}}=2$$ theory $$T[Q_{K}]$$ whose low energy dynamics arises on the worldvolume of an M5 brane wrapping the knot conormal and we match the (K-theoretic) vortex partition function of this theory with the motivic generating series of $$Q_{K}$$ . From the geometry side, we argue that the spectrum of (generalized) holomorphic curves on $$L_{K}$$ is generated by a finite set of basic disks. These disks correspond to the nodes of the quiver $$Q_{K}$$ and the linking of their boundaries to the quiver arrows. We extend this basic dictionary further and propose a detailed map between quiver data and topological and geometric properties of the basic disks that again leads to matching partition functions. We also study generalizations of A-polynomials associated to $$Q_{K}$$ and (doubly) refined version of LMOV invariants (Ooguri and Vafa 2000; Labastida and Marino in Commun Math Phys 217(2):423–449, 2001. arXiv:hep-th/0004196 ; Labastida et al. in JHEP 11:007, 2000. arXiv:hep-th/0010102 ; Aganagic and Vafa in Large N duality, mirror symmetry, and a Q-deformed A-polynomial for knots. arXiv:1204.4709 ; Fuji et al. in Nucl Phys B 867:506–546, 2013. arXiv:1205.1515 ).

Semi-supervised self-growing generative adversarial networks for image recognition

Image recognition is an important topic in computer vision and image processing, and has been mainly addressed by supervised deep learning methods, which need a large set of labeled images to achieve promising performance. However, in most cases, labeled data are expensive or even impossible to obtain, while unlabeled data are readily available from numerous free on-line resources and have been exploited to improve the performance of deep neural networks. To better exploit the power of unlabeled data for image recognition, in this paper, we propose a semi-supervised and self-generative approach, namely the semi-supervised self-growing generative adversarial network (SGGAN). Label inference is a key step for the success of semi-supervised learning approaches. There are two main problems in label inference: how to measure the confidence of the unlabeled data and how to generalize the classifier. We address these two problems via the generative framework and a novel convolution-block-transformation technique, respectively. To stabilize and speed up the training process of SGGAN, we employ the metric Maximum Mean Discrepancy as the feature matching objective function and achieve larger gain than the standard semi-supervised GANs (SSGANs), narrowing the gap to the supervised methods. Experiments on several benchmark datasets show the effectiveness of the proposed SGGAN on image recognition and facial attribute recognition tasks. By using the training data with only 4% labeled facial attributes, the SGGAN approach can achieve comparable accuracy with leading supervised deep learning methods with all labeled facial attributes.