Number Of Matches Research Articles

Deep Convolutional Network Based on Attention Mechanism for Matching Optical and SAR Images

Abstract. Complex geometric distortions and nonlinear radiation differences between optical and synthetic aperture radar (SAR) images present challenges for the matching of sufficient and evenly distributed corresponding points. To address this problem, this paper proposes a deep convolutional network based on an attention mechanism for matching optical and SAR images. In order to obtain robust feature points, we employ phase consistency instead of image intensity and gradient information for feature detection. A deep convolutional network (DCN) is designed to extract high-level semantic features between optical and SAR images, providing robustness to geometric distortion and nonlinear radiation changes. Notably, incorporating multiple inverted residual structures in the DCN facilitates efficient extraction of local and global features, promoting feature reuse, and reducing the loss of key features. Furthermore, a dense feature fusion module based on coordinate attention is designed, focusing on the spatial positional information of effective features, integrating key features into deep descriptors to enhance the robustness of deep descriptors to nonlinear radiometric differences. A coarse-to-fine strategy is then employed to enhance accuracy by eliminating mismatches. Experimental results demonstrate that the proposed network performs better than the manually designed descriptors-based methods and the stateof- the-art deep learning networks in both matching effectiveness and accuracy. Specifically, the number of matches achieved is approximately 2 times greater than that of other methods, with a 10% improvement in F-measure.

Forecasting vaping health risks through neural network model prediction of flavour pyrolysis reactions

Vaping involves the heating of chemical solutions (e-liquids) to high temperatures prior to lung inhalation. A risk exists that these chemicals undergo thermal decomposition to new chemical entities, the composition and health implications of which are largely unknown. To address this concern, a graph-convolutional neural network (NN) model was used to predict pyrolysis reactivity of 180 e-liquid chemical flavours. The output of this supervised machine learning approach was a dataset of probability ranked pyrolysis transformations and their associated 7307 products. To refine this dataset, the molecular weight of each NN predicted product was automatically correlated with experimental mass spectrometry (MS) fragmentation data for each flavour chemical. This blending of deep learning methods with experimental MS data identified 1169 molecular weight matches that prioritized these compounds for further analysis. The average number of discrete matches per flavour between NN predictions and MS fragmentation was 6.4 with 92.8% of flavours having at least one match. Globally harmonized system classifications for NN/MS matches were extracted from PubChem, revealing that 127 acute toxic, 153 health hazard and 225 irritant classifications were predicted. This approach may reveal the longer-term health risks of vaping in advance of clinical diseases emerging in the general population.

Gated independence in graphs

If G=(V,E) is a (finite and simple) graph, we call an independent set X a gated independent set in G if for each x∈X, there exists a neighbor y of x such that (X∖{x})∪{y} is an independent set in G. We define the gated independence numbergi(G) of G to be the maximum cardinality of a gated independent set in G. We demonstrate that the gated independence number is closely related to both matching and domination parameters of graphs. We prove that the inequalities im(G)⩽gi(G)⩽mur(G) hold for every graph G, where im(G) and mur(G) denote the induced and uniquely restricted matching numbers of G. On the other hand, we show that γi(G)⩽gi(G) and γpr(G)⩽2gi(G) for every graph G without any isolated vertex, where γi(G) and γpr(G) denote the independence and paired domination numbers. Furthermore, we provide bounds on the gated independence number involving the order, size and maximum degree. In particular, we prove that gi(G)⩾n5 for every n-vertex subcubic graph G without any isolated vertex or any component isomorphic to K3,3, and gi(B)⩽3n8 for every n-vertex connected cubic bipartite graph B.

Women in Orthopaedics: 10-Year Trends of Fellowship Match Rate and Subspecialty.

Orthopaedic surgery has consistently remained one of the least diverse specialties in medicine. There are limited data on the match rate by sex into orthopaedic fellowships. The goals of this study were to determine (1) how the percentage of women applying to orthopaedic fellowships has changed from 2011 to 2021, (2) whether there was a correlation between sex and the likelihood of a successful fellowship match, and (3) which subspecialties tend to have a greater proportion of female applicants and fellows. The San Francisco (SF) Match service was used to obtain US orthopaedic fellowship applicant data from 2010 to 2021. San Francisco Match has run the match for the orthopaedic fellowship match since 2010. International medical graduates' applications, incomplete applications, or withdrawn applications were excluded. The following variables were collected and assessed: sex, subspecialty choice (except for hand because they do not use SF Match services), and match outcome. The number of female applicants and matches was recorded by year and compared with the number of male applicants and matches. Chi-square analysis was used to analyze categorical variables. A total of 6969 applicants to all orthopaedic specialties within SF Match were included during the study period. Overall, 859 were female (12.3%), and 6110 were male (87.7%). The number of female applicants had an increasing trend over the 10-year period from 65 applicants in 2011 to 111 in 2021. The overall proportion of female applicants was between 10.1% and 14.4%. The annual match rate for female applicants was 90.7% to 100% during the study period while the match rate for male applicants was 93.7% to 97.3%. Regarding successful matches, pediatrics had the highest proportion of women (range: 30.2% to 46.2%), followed by foot and ankle (range: 9.8% to 26.4%). Spine (range: 3.2 to 10.9%) and adult reconstruction (range: 3.9% to 9%) had the least number of women among matched applicants. This study found that the number of female applicants to orthopaedic fellowships has increased over the past 10 years. The difference in fellowship match rates among male versus female applicants did not statistically differ during this 10-year period; however, the proportion of female fellows is not equally distributed among subspecialties, with a higher proportion of women matching into pediatrics and foot and ankle and lower proportion in reconstruction and spine. These data can provide a benchmark for department chairs and society leadership to ensure they are recruiting, interviewing, and selecting candidates who are representative of the current sex demographics of orthopaedic fellowship graduates.

EFFECTS OF PRE-MATCH TRAVEL AND TRAINING ON PHYSICAL AND TECHNICAL PERFORMANCE IN INTERNATIONAL FOOTBALL MATCHES

INTRODUCTION & AIMS International footballers (soccer) are regularly required to travel directly from club to national team with only a few days to recover and prepare for matches. The combined stress of travel and training loads may therefore influence match performance. This research aims to examine the relationship of pre-match travel and in-camp training on ensuing physical and technical match performance of footballers competing for a national team. METHODS Match running and technical performance data were obtained from 68 national team footballers competing in international matches (n=108). Match performance data was aligned with confirmed travel durations, time zone change, travel direction, and the time between arrival and kick-off for travel into the match. Additionally, in-camp training loads for GPS for the 3 days prior to national team matches were also collated. Linear mixed models assessed relationships between travel and training measures with physical and technical match performance outcomes. RESULTS Travel variables explained little variance in outcomes (R2=0.02-0.16). Travelling eastward was associated with an increase in total (p=0.042) and very high-speed distance (p=0.030) in matches and a 5% decrease in pass accuracy (p=0.012). Greater time zone difference was associated with increased match decelerations (p=0.027), while arriving earlier for matches was associated with decreased total tackles (p=0.041). Increases in training high-speed distance were associated with increases in match high-speed distance (p=0.004) and number of decelerations (p<0.001). An increase in training total distance was associated with a decrease in match decelerations (p=0.002). CONCLUSIONS Pre-match travel appeared to have minimal effects on physical and technical performance in this national team, especially given most players arrived at least 40h prior to matches. Training loads prior to matches may have some relationship with match running performance and thus readiness to train should be a priority for athletes arriving in national team camps.

Optimal vector phase-matching conditions in biaxial crystalline materials determined by the extreme surfaces method: the case of orthorhombic crystals

The optimal geometries of vector phase matching are determined for the cases of second harmonic generation, sum frequency generation, and difference frequency generation in a number of orthorhombic nonlinear optical crystals: KTP, KTA, KB5, KNbO3, LBO, CBO, and LRB4. The extreme surface method was used to define the wave vector directions of highest possible generation efficiency. As shown, in a significant number of cases vector phase matching ensures higher efficiencies than the scalar one.

Team Performance Indicators That Predict Match Outcome in Rugby Union

The aim of the study is to identify the most significant indicators of the national team's performance at the European Rugby Championships 15 and to design a model for predicting the outcomes of matches. Data was collected from teams’ performance at the European Rugby 15 Championships 2021, 2022 and 2023 for the analysis. The total number of matches was 41. All indicators presented in the official reports were taken: 22 for the home and away teams. The analysis of the team results was carried out according to all indicators: mean value, standard deviation, and test were used to compare the performance indicators of the winning and losing teams. Machine learning techniques were utilized to develop a predictive model for match outcomes. On one hand, 15 indicators (68.2%) are higher for teams that won (winning teams). On the other hand, 7 (31.8%) indicators are higher for teams that lost. The difference between the teams' means varies from -56.46% (the minus indicates that this indicator is higher for the teams that lost) to 273.68%. Based on the results, the Random Forest Classifier and Extra Trees Classifier algorithms have the best prediction accuracy (0.92). The most significant indicators of team performance that affect the final result of the match are tries (196.3% – the difference between the average values of winning and losing teams), conversions (176.7%), missed tackles (- 56.46%), offload (126.3%). Based on the data obtained, refining the team training process in Rugby 15 is possible.

Counting deranged matchings

Let pm(G) denote the number of perfect matchings of a graph G, and let Kr×2n/r denote the complete r-partite graph where each part has size 2n/r. Johnson, Kayll, and Palmer conjectured that for any perfect matching M of Kr×2n/r, we have for 2n divisible by rpm(Kr×2n/r−M)pm(Kr×2n/r)∼e−r/(2r−2).This conjecture can be viewed as a common generalization of counting the number of derangements on n letters, and of counting the number of deranged matchings of K2n. We prove this conjecture. In fact, we prove the stronger result that if R is a uniformly random perfect matching of Kr×2n/r, then the number of edges that R has in common with M converges to a Poisson distribution with parameter r2r−2.

Thematic Learning in the Independent Curriculum in Elementary Schools Based on the Islamic Montessori Method for Multiple Intelligence

Recently, the practice of categorizing intelligent students and unintelligent students is a deeply ingrained phenomenon within the realm of education in Indonesia. Indeed, multiple specialists have verified that the attributes of intelligence vary among individual students. Hence, this study aims to revolutionize theme education in primary schools by implementing an autonomous curriculum that is rooted in the Islamic Montessori for Multiple Intelligence approach. This study employs the library research methodology, utilizing primary and secondary data derived from printed or digital sources such as books, journals, and magazines. The outcome of this discussion is to generate a set of activities for different domains of learning. These activities include folding clothes or buttoning clothes for the Islamic Studies domain, hand washing for the practical life domain, matching pictures with zones for the sensorial domain, matching words for the language domain, matching numbers for the mathematical domain, matching fruit with pictures for the cultural realm, and drawing or creating ecobricks for the arts & crafts realm. These diverse educational approaches involve the creation of a curriculum centered around the Islamic Montessori for Multiple Intelligence method, with the aim of promoting a healthy and virtuous lifestyle. These methods can be effectively utilized by teachers during classroom instruction. Through the development of diverse learning activities, education will be conducted in a more comprehensive manner, tailored to the individual traits and capabilities of each student. This approach to designing educational activities can thereafter be implemented in the instruction of young children in primary schools.

Effects of saturated and monounsaturated fatty acids on cognitive impairment: evidence from Mendelian randomization study.

Prior observational studies have suggested correlations between saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs) with cognitive function. However, causal relationships remains unclear. We assessed the causal impact of two SFAs (palmitic acid [PA] and stearic acid [SA]) and two MUFAs (oleic acid [OA] and palmitoleic acid [POA]) on cognitive function-related traits, and dementia-related traits by univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) analyses. UVMR indicated β of 0.060 (P = 4.05E-06) for cognitive performance score and 0.066 (P = 4.21E-04) for fluid intelligence per standard deviation (SD) increase in OA level. MVMR indicated: (i) β of -0.608 (P = 8.37E-05) for fluid intelligence score per SD increase in POA; (ii) β of 0.074 (P = 0.018) for fluid intelligence score per SD increase in OA; (iii) β of 0.029 (P = 0.033) for number of incorrect matches in round per SD increase in PA; and (iv) β of 0.039 (P = 0.032) for number of incorrect matches in round per SD increase in SA. In addition, a secondary MVMR analysis after excluding the effect of polyunsaturated fatty acids suggested that: (i) β of -0.043 (P = 1.97E-02) for cognitive performance score per SD increase in PA and (ii) β of -0.079 (P = 1.79E-03) for cognitive performance score per SD increase in SA. Overall, UVMR and MVMR suggest that OA may be beneficial for cognitive function, while POA, PA, and SA may have detrimental effects on cognitive function.

Maximum size of a triangle-free graph with bounded maximum degree and matching number

Maximum size of a triangle-free graph with bounded maximum degree and matching number

Commitment on Volunteer Crowdsourcing Platforms: Implications for Growth and Engagement

Problem definition: Volunteer crowdsourcing platforms match volunteers with tasks that are often recurring. To ensure completion of such tasks, platforms frequently use a lever known as “adoption,” which amounts to a commitment by the volunteer to repeatedly perform the task. Despite reducing match uncertainty, high levels of adoption can decrease the probability of forming new matches, which in turn can suppress growth. We study how platforms should manage this trade-off. Our research is motivated by a collaboration with Food Rescue U.S. (FRUS), a volunteer-based food recovery organization active in more than 30 locations. For platforms such as FRUS, effectively using nonmonetary levers, such as adoption, is critical. Methodology/results: Motivated by the volunteer management literature and our analysis of FRUS data, we develop a model for two-sided markets that repeatedly match volunteers with tasks. We study the platform’s optimal policy for setting the adoption level to maximize the total discounted number of matches. When market participants are homogeneous, we fully characterize the optimal myopic policy and show that it takes a simple extreme form: depending on volunteer characteristics and market thickness, either allow for full adoption or disallow adoption. In the long run, we show that such a policy is either optimal or achieves a constant-factor approximation. We further extend our analysis to settings with heterogeneity and find that the structure of the optimal myopic policy remains the same if volunteers are heterogeneous. However, if tasks are heterogeneous, it can be optimal to only allow adoption for the harder-to-match tasks. Managerial implications: Our work sheds light on how two-sided platforms need to carefully control the double-edged impacts that commitment levers have on growth and engagement. Setting a misguided adoption level may result in marketplace decay. At the same time, a one-size-fits-all solution may not be effective, as the optimal design crucially depends on the characteristics of the volunteer population. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2020.0426 .

On 5- and 6-Leaved Trees with the Largest Number of Matchings

On 5- and 6-Leaved Trees with the Largest Number of Matchings

Indicators of Spectacle in Wrestling at the 2021 Olympic Games

Background and Study: Spectacle plays a key role in sports wrestling in attracting viewers' attention, creating emotional involvement, and making the sport an integral part of culture. Aim: To identify the most significant indicators of wrestlers' competitive activity based on the analysis of the 2021 Olympic Games, which influence the spectacle in sports wrestling. Material and Methods: The study involved 289 wrestlers. An analysis of protocols and video recordings of 340 matches at the 2021 Olympic Games in three types of sports wrestling was conducted: in women's wrestling – 113 matches (n=96 female wrestlers), in Greco-Roman wrestling – 113 matches (n=97 wrestlers), and in freestyle wrestling – 114 matches (n=96 wrestlers). Expert assessment method was used to evaluate the indicators of competitive activity. Statistical analysis of the data was conducted using licensed Excel spreadsheet packages. Results: For Greco-Roman wrestling and women's wrestling, the ratio of actions performed in par terre and standing is about 70 to 30. Whereas, for freestyle wrestlers, almost 80% of actions are performed in standing. The efficiency coefficient of wrestling in standing for Greco-Roman style wrestlers averaged 1.43 points per action; for freestyle wrestlers, it was 1.78 points per action, and for female wrestlers – 2.01 points per action. The highest number of one-point actions was performed in Greco-Roman wrestling, which significantly and statistically significantly (p<0.05) exceeds the indicators in freestyle and women's wrestling. Meanwhile, female wrestlers and freestyle wrestlers statistically significantly (p<0.05) executed more two-point actions. The average number of actions per match does not significantly differ (p>0.05): 4.23 actions for Greco-Roman wrestling; 4.47 actions for freestyle wrestling, and 4.08 actions for women's wrestling. However, when considering the average number of points scored per match, statistically significant differences were found. Thus, Greco-Roman style wrestlers score an average of 6.95 points, this indicator is statistically significantly lower (p<0.05) than in freestyle (8.12 points) and in women's wrestling (8.07 points). Conclusions: The analysis of matches at the 2021 Olympic Games made it possible to identify competitive activity indicators that influence the spectacle in sports wrestling. Positive indicators include: a large number of technical-tactical actions performed in standing; execution of throws in par terre by Greco-Roman style wrestlers; a high percentage of early victories in matches. Negative indicators: execution of simple one-point and two-point technical-tactical actions; in Greco-Roman wrestling, a large number of matches that ended with a score of 1:1; interruptions in matches (Challenge, Negative Wrestling, Caution), lack of dynamism in the match, and the inability to score too many points. The obtained results will help provide recommendations for changing competition rules and enhancing the spectacle of sports wrestling.

Anti-Ramsey number for perfect matchings in 3-regular bipartite graphs

The anti-Ramsey number AR(G,H) is the maximum number of colors in an edge-coloring of a graph in the family G without any rainbow copy of H. The anti-Ramsey number for matchings has been studied extensively in several graph families, while the problem for perfect matchings was only solved in complete graphs. The anti-Ramsey number of matchings in the family of regular bipartite graphs of order large enough was determined by Li and Xu. Jin improved their bounds on the order of 3-regular bipartite graphs. In this paper, we consider the problem for perfect matchings in 3-regular bipartite graphs. Let G be the family of 3-regular bipartite graphs with m vertices in each partite set. First, we characterize the structure of extremal graphs for the Turán number of perfect matchings in graphs with maximum degree three. Using this characterization, we show that AR(G,mK2)=3m−3. Moreover, we show that AR(F,mK2)=3m−5, where F is the subfamily of 3-edge-connected graphs in G. In order to prove this result, we characterize the structure of bipartite graphs, which contains no perfect matchings, with maximum degree three and size Turán number minus one.

Determining the impact of current Canadian stem cell registry policy on donor availability via dynamic registry simulation.

When a haematopoietic stem cell registry size is constrained by limits on recruiting, as in Canada, identifying the right person to recruit is a critical determinant of effectiveness. The aim of this study was to evaluate the impact of changes to donor recruitment effort, within ethnic groups, on the matching effectiveness of the Canadian registry as it evolves over time. Simulation methods are applied to create a cohort of donor recruits and patients over a 10-year time horizon. New recruits are added to the registry each year, while some existing donors 'age-out' upon reaching their 36th birthday. In a similar fashion, simulated patient lists are created. At the end of each simulated year, simulated patients are matched against the simulated registry. There are increased matches in non-White populations when diverse registrants are preferentially recruited, but there are larger decreases in the number of matches for Caucasian patients. Additionally, ethnic communities that have limited registrants in the Canadian registry in 2021 do not benefit from increased recruiting efforts as much as communities with a larger initial number of registrants. Preferentially recruiting from non-Caucasian populations reduces the number of matches from Canadian sources because increases in non-Caucasian populations will not fully counterbalance decreases to Caucasian patient matches. Nevertheless, more than 80% of all matches are for Caucasian patients, regardless of the donor recruiting effort within ethnic groups.

Abstract 5378: Spatially resolved human leukocyte antigen (HLA) expression correlates with motif neoepitope expression and durable response to immune checkpoint blockade (ICB) in non-small cell lung cancer (NSCLC)

Abstract Background: We previously showed electrostatic interactions enhance binding between “motif” neoepitopes and HLA and predict advanced NSCLC ICB benefit, suggesting optimal neoantigen presentation drives effective anti-tumor immune response (Cummings 2020). However, not all cases with motif neoepitopes exhibit favorable ICB outcomes. Methods: As proof-of-concept, participants from our published NSCLC ICB cohort with available pre-treatment archival tissue were selected based on HLA supertype B44, predicted motif neoepitopes, and best response of progressive disease (PD) vs partial/complete response (PR/CR). Whole exome sequencing, HLA typing and neoepitope prediction were previously performed (Cummings 2020). GeoMx slides were prepared, hybridized with RNA probes and stained with antibodies to cytokeratin (CK), nuclear material and CD45 per manufacture instructions (Geiss 2008). Antibody to CD8 (Novus) was optimized at 1:50 dilution. Twelve regions of interest (ROI) were selected per sample including the following compartments: CK+CD8+, CK+CD8-, CK-CD8+ and CK-CD8- (negative control). Each ROI included ~150 nuclei selected using GeoMx Digital Spatial Profiler. Sequencing was performed on Illumina Novaseq 6000 (50bpx2) demultiplexed using Illumina Bcl2fastq v2.19.1.403. Raw reads were normalized and compared using paired student’s T-tests with Tukey’s correction via R v4.1. Neoepitope (non/motif) comparisons used matched numbers per sample selected by highest expression. Results: Seven participants (3 PD, 3 PR, 1 CR) were included, each exhibiting 1-7 motif neoepitopes without HLA loss of heterozygosity. 84 ROI included 24 CK+CD8+, 24 CK+CD8-, 24 CK-CD8+ and 12 CK-CD8- with at least one ROI per category per participant. PD samples had fewer CD8+ ROI (12 vs 36) and lower CXCL9 (p=0.011) and CD274 (p=0.014). HLA-A/B/C expression followed a gradient with highest expression in CK+CD8+ ROI with limited detection in CK-CD8- ROI. Among HLA, HLA-B had highest median expression (A: 226, B: 650, C: 202; p<0.001). In CK+ ROI, motif neoepitope expression was detectable for all participants but not statistically different from non-motif expression (p=0.23). HLA-A/B/C all exhibited lower expression in PD CK+ ROI (p<0.001). Conclusion: HLA expression may modify prediction of clinically meaningful neoepitopes and response to ICB. Validation in a larger, prospective cohort is planned. Citation Format: Lucas Goldman, Sarah Gorbatov, Collin Shen, Alexa Berezowitz, Edward Garon, Amy Lauren Cummings. Spatially resolved human leukocyte antigen (HLA) expression correlates with motif neoepitope expression and durable response to immune checkpoint blockade (ICB) in non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5378.

Snapshot-Optimal Real-Time Ride Sharing

Ridesharing effectively tackles urban mobility challenges by providing a service comparable to private vehicles while minimising resource usage. Our research primarily concentrates on dynamic ridesharing, which conventionally involves connecting drivers with passengers in need of transportation. The process of one-to-one matching presents a complex challenge, particularly when addressing it on a large scale, as the substantial number of potential matches make the attainment of a global optimum a challenging endeavour. This paper aims to address the absence of an optimal approach for dynamic ridesharing by refraining from the conventional heuristic-based methods commonly used to achieve timely solutions in large-scale ride-matching. Instead, we propose a novel approach that provides snapshot-optimal solutions for various forms of one-to-one matching while ensuring they are generated within an acceptable timeframe for service providers. Additionally, we introduce and solve a new variant in which the system itself provides the vehicles. The efficacy of our methodology is substantiated through experiments carried out with real-world data extracted from the openly available New York City taxicab dataset.

Integer k-matching preclusion of graphs

As a generalization of matching preclusion number of a graph, we provide the (strong) integer $k$-matching preclusion number, abbreviated as $MP^{k}$ number ($SMP^{k}$ number), which is the minimum number of edges (vertices and edges) whose deletion results in a graph that has neither perfect integer $k$-matching nor almost perfect integer $k$-matching. In this paper, we obtain a necessary condition of graphs with an almost-perfect integer $k$-matching and a relational expression between the matching number and the integer $k$-matching number of bipartite graphs. And then the $MP^{k}$ number and the $SMP^{k}$ number of complete graphs, bipartite graphs and arrangement graphs are obtained, respectively.

Sharp lower bounds for the number of maximum matchings in bipartite multigraphs

AbstractWe study the minimum number of maximum matchings in a bipartite multigraph with parts and under various conditions, refining the well‐known lower bound due to M. Hall. When , every vertex in has degree at least , and every vertex in has at least distinct neighbors, the minimum is when and is when . When every vertex has at least two neighbors and , the minimum is , where . We also determine the minimum number of maximum matchings in several other situations. We provide a variety of sharpness constructions.