Matching Process Research Articles

Maternal–fetal medicine fellowship program director perspective on virtual interviews following matriculation of the first virtual interview class

The first class of virtually interviewed maternal-fetal medicine fellows has matriculated into their training programs. This study aimed to evaluate the impact of virtual interviews on the outcomes of the National Resident Matching Program within our subspecialty. We assessed maternal-fetal medicine fellowship program directors' experience with their fellows who interviewed virtually as compared with experience with the previous year's fellows who interviewed in-person. In addition, we evaluated program directors' satisfaction with the virtual interview process and their preferred mode of interviewing for future cycles. A cross-sectional online survey was distributed through the Society for Maternal-Fetal Medicine to all maternal-fetal medicine fellowship program directors on October 26, 2021, approximately 4 months after the first virtually interviewed fellow matriculated into the training program. Program directors were asked to provide information about their National Resident Matching Program rank list between their final in-person and first virtual years. Program directors were asked to evaluate their experience with their fellow 4 months into the first year of fellowship compared with their expectations based on their virtual interview, and their experience at that same point in fellowship of their last fellow who interviewed in-person. For all questions, in programs with >1 fellow per year, program directors were asked to answer the questions for the fellow ranked highest on their National Resident Matching Program rank list for each year. Survey data were collected anonymously and stored securely. Descriptive statistics and bivariate analyses were performed to compare groups, all tests were 2-sided, and the significance level was set at P<.05. A total of 80 of 98 (81.6%) program directors responded. There was no difference in the position of the matched fellow on the program's National Resident Matching Program rank list between candidates interviewed in-person and candidates interviewed virtually. There was also no difference in the number of programs that took an internal or external candidate outside of the National Resident Matching Program match process or that did not fill their fellowship positions. Program directors reported no difference between fellows interviewed virtually and those interviewed in-person in meeting interview-based performance expectations with regard to clinical capabilities (P=.67), technical skills (P=.96), research potential or experience (P=.54), professionalism and ability to be a team player (P=.72), and compatibility with the division and fellowship program (P=.67). Program directors' overall experience with virtual interviews was favorable: 70 (95.8%) program directors reported that the virtual interview experience was better than expected, slightly better than expected, or as expected. In future years, most program directors favored ongoing exclusively virtual interviewing (n=41; 56.2%) or a hybrid of virtual and in-person interviews (n=27; 37.0%). Only 5 (6.9%) reported a desire to return to exclusively in-person interviewing. Maternal-fetal medicine fellowship program directors did not identify a difference in National Resident Matching Program results between fellows interviewed virtually and those interviewed in-person. Furthermore, there was no difference between these fellows in meeting interview-based expectations in the first year of the training program. Most program directors found the virtual interview process to be effective and support ongoing virtual interviews.

Effect of Sarcopenia on Mortality in Type 2 Diabetes: A Long-Term Follow-Up Propensity Score-Matched Diabetes Cohort Study.

Purpose: The effect of sarcopenia on the survival of patients with type 2 diabetes remains unclear. Therefore, we designed a propensity score-matched population-based cohort study to compare the patients with diabetes with or without sarcopenia. Patients and Methods: We included patients with type 2 diabetes and categorized them into two groups according to whether they had sarcopenia and compared their survival; patients in the groups were matched at a ratio of 1:2. Results: The matching process yielded a final cohort of 201,698 patients (132,805 and 68,893 in the sarcopenia and nonsarcopenia diabetes groups, respectively) who were eligible for further analysis. According to both univariate and multivariate Cox regression analyses, the adjusted hazard ratios (aHRs; 95% confidence interval [CI]) of all-cause death for the sarcopenia diabetes group compared with the control group: 1.35 (1.33–1.38; p < 0.001). The aHRs (95% CIs) of all-cause death for those aged 41–50, 51–60, and >60 years (compared with those aged ≤40 years) were 1.53 (1.48–1.60), 2.61 (2.52–2.72), and 6.21 (5.99–6.45), respectively. The aHR (95% CI) of all-cause death for the male patients compared with the female patients was 1.56 (1.54–1.60). The aHRs (95% CIs) of all-cause death for those with adapted Diabetes Complications Severity Index (aDCSI) scores of 1, 2, 3, 4, and ≥5 (compared with an aDCSI score of 0) were 1.01 (1.00–1.14), 1.38 (1.35–1.42), 1.58 (1.54–1.63), and 2.23 (2.14–2.33), respectively. Conclusion: Patients with type 2 diabetes and sarcopenia had higher mortality than did those without sarcopenia.

Harder Than You Think – Immigrant Labor Market Integration in Agricultural Sector

The recent forced migration to Europe has created more challenges for the labor market integration. However, the Swedish government encourages unemployed immigrants to seek employment in the farming, gardening, and forestry industries. Thus, this article focuses on the matching process in the Swedish agricultural sector by using an exploratory, qualitative, in-depth interview with representatives involved in the matching process. Immigrants experience challenges of Swedish language proficiency, lacking a driving license and adapting to new cultures in the workplace, while employers attribute challenges of effective hiring process and the absence of evidence of immigrants’ work experience. Furthermore, the employment service offices struggle with scant knowledge of agricultural employment that needs to be combined with limited contact with employers and the bureaucratic delays caused by requirements of qualifications validation. The paper concludes with a Labour Market Matching Model, which focuses on critical aspects before, during, and after the matching process.

OG-SLAM: A real-time and high-accurate monocular visual SLAM framework

The challenge of improving the accuracy of monocular Simultaneous Localization and Mapping (SLAM) is considered, which widely appears in computer vision, autonomous robotics, and remote sensing. A new framework (ORB-GMS-SLAM (or OG-SLAM)) is proposed, which introduces the region-based motion smoothness into a typical Visual SLAM (V-SLAM) system. The region-based motion smoothness is implemented by integrating the Oriented Fast and Rotated Brief (ORB) features and the Grid-based Motion Statistics (GMS) algorithm into the feature matching process. The OG-SLAM significantly reduces the absolute trajectory error (ATE) on the key-frame trajectory estimation without compromising the real-time performance. This study compares the proposed OG-SLAM to an advanced V-SLAM system (ORB-SLAM2). The results indicate the highest accuracy improvement of almost 75% on a typical RGB-D SLAM benchmark. Compared with other ORB-SLAM2 settings (1800 key points), the OG-SLAM improves the accuracy by around 20% without losing performance in real-time. The OG-SLAM framework has a significant advantage over the ORB-SLAM2 system in that it is more robust for rotation, loop-free, and long ground-truth length scenarios. Furthermore, as far as the authors are aware, this framework is the first attempt to integrate the GMS algorithm into the V-SLAM.

Resting-state functional MRI for motor cortex mapping in childhood-onset focal epilepsy.

Task-based functional MRI (fMRI) mapping of the motor function prior to epilepsy surgery has limitations in children with epilepsy. We present a data-driven method to automatically delineate the motor cortex using task-free, resting-state fMRI (rsfMRI) data. We used whole-brain rsfMRI for independent component analysis (ICA). A template matching process with Discriminability Index-based Component Identification score was used for each participant to select and combine motor ICA components in their native brain space, resulting in a whole-brain ICA Motor Map (wIMM). We validated wIMM by comparing individual results with bilateral finger-tapping motor task fMRI activation, and evaluated its reproducibility in controls. Data from 64 patients and 12 controls were used to generate group wIMM maps. The hit rate between wIMM and motor task activation ranged from 60% to 79% across all participants. Sensitivity of wIMM for capturing the task activation peak was 87.5% among 32 patients and 100% in 12 controls with available motor task results. We also showed high similarity in repeated runs in controls. Our results show the sensitivity and reproducibility of an automated motor mapping method based on ICA analysis of rsfMRI in children with epilepsy. The ICA maps may provide different, but useful, information than task fMRI. Future studies will expand our method to mapping other brain functions, and may lead to a surgical planning tool for patients who cannot perform task fMRI and help predict their postsurgical function.

Malware visual resemblance analysis with minimum losses using Siamese neural networks

With the rapid development of information technology, malware has grown exponentially to become the main threat to network security. Malware generally refers to all malicious program codes, which can cause information leakage or resource abuse of the target system, devastate the integrity and availability of the system, and violate the security policy of the target system. During this technology revolution, outstanding new things transpire from time to time, leading to the development of broad, diverse data. Thereupon the happening of eminent things in the technology, the invaders increasingly penetrated in designing and development of dangerous new data often referred to as malware. In view of uncovering of these vulnerable invaders, a deepen detection mechanisms and discussion forums are to be evolved with advanced anti malware penetration inventions in the data world. The on-going ways take superfluous cycles and computational resources.This paper depicts the concealment of matching malevolent inside insignificant processing cycles and resources. The progression of on-going way is to endorse the Siamese Networks (SN) to develop the model for calculating and reducing the similarities. The idea of resemblance of malevolent visuals is incorporated as it address the code designed in the two fold malevolent source and cipher record architecture and impression generated from the data processing file. Exploration on exemplary data files using high-end computational resources in research COLAB with numerous python libraries torch vision. For terrific outcomes, the template is formed with different learning rates and range values. The seeking advise that making use of SN to know similitude of malware aids in the advancement of more precise designs even when are actually less samples per training class as well as unequal training class dissemination. The made a proposal design goes beyond top-level methods through obtaining 99.67 per-cent precision along with a learning of 0.0005 as well as a scope of 1.0.

Extraction of surface-wave phase velocities from ambient noise in the presence of local noise sources based on matched-field processing

Passive surface wave methods have gained much attention from geophysics and civil engineering communities with the advantage of lower costs and deeper penetration depths compared to active seismic methods. The successful extraction of surface waves from ambient noise relies on the assumption of a homogeneous random distribution of noise sources. In urban environments, there are many strong noise sources located in localized areas (i.e., local sources) that violate the ideal noise distribution conditions, which causes errors in surface-wave dispersion extraction. To solve this problem, we propose a new passive surface wave analysis method in the presence of strong local noise sources (local-source passive surface wave analysis, LSPSW). We use the matched field processing (MFP) algorithm to capture noise source distributions and then extract reliable surface wave phase velocities. The MFP algorithm can accurately estimate the distribution of noise sources located either close to or far from the receiver array. Synthetic and field examples demonstrate the feasibility of using LSPSW to estimate phase velocities in complicated noise environments with a pseudo-linear array. Comparisons with other passive surface wave methods (seismic interferometry, the spatial autocorrelation method, pseudo-linear array analysis of passive surface waves based on beamforming) further illustrate the superiority of the MFP-based LSPSW method.

Outcomes of ultra-old vs old patients after hip fracture surgery: a matched cohort analysis of 1524 patients.

Surgical management of geriatric hip fractures yields improved functional outcomes with decreased morbidity and mortality. Cohort studies have suggested that the older patients within the geriatric age group have worse outcomes with surgery, However, these studies inherently report inflated risks due to poor handling of confounders and have inadequately age-stratified their geriatric population. This study aims to investigate the effect of age alone on the 1-year mortality and functional status of geriatric patients after hip fracture surgery. This is a retrospective single institution cohort study based on the prospectively-maintained registry of hip fracture patients. 2603 patients aged 60years and above were treated surgically under a geriatric-orthopaedic hip fracture pathway from January 2014 to December 2018. Patients were split into two age groups: ultra-old (≥ 85years) vs old (< 85years). Baseline demographics and the ASA (American Society of Anaesthesiologists) status and the Modified Barthel's Index (MBI) were obtained at admission and 1year after the fracture. Adverse outcomes from the fracture and surgery were recorded during a follow-up period of minimally 2years. A 2:1 matching process based on the gender, fracture type, ASA status, CCI and MBI categories was conducted. There were 1009 and 515 patients in the old and ultra-old age groups, respectively. 1-year mortality was similar for both age groups (4.0% ultra-old vs 3.6% old, p = 0.703). 30-day morbidity was similar except for higher rates of postoperative pneumonia in the ultra-old (14.0 vs 6.3%, p < 0.001). MBI scores at 1-year were lower in the ultra-old (severe dependence: 16.4 vs 10.0%; p = 0.001). Ultra-old patients were less likely to be community ambulant at 12months (21.2 vs 36.0%) with the deterioration in ambulatory status significant after correction for baseline status (p < 0.001). The 1-year mortality of surgically-managed geriatric hip fracture patients older than 85years of age is not determined by age alone. Patients aged 85years and above are at higher risk for pneumonia postoperatively. Ultra-old hip fracture patients with an intertrochanteric fracture are more likely to have poorer function at 1year after hip fracture surgery.

Two-sided matching decision-making model for complex product system based on life-cycle sustainability assessment

Since the different matching schemes between manufacturing tasks and services have a great influence on the life cycle sustainability of complex product system (CoPS), the strategy used to find cost-effective, environmentally friendly, and socially acceptable matching results is essential for sustainable development. This paper proposed a novel two-sided matching model for CoPS based on life-cycle sustainability assessment (TSMM-CoPS-LCSA). First, the two-sided matching model based on the life-cycle sustainability assessment of manufacturing tasks and services for CoPS is presented. Then, a bi-level decision-making method is proposed, where learning and synergy effect are considered to ensure stability in the matching process. Sequentially, to facilitate the optimization solution, the Karush-Kuhn-Tucker (KKT) conditions are adopted to convert the bi-level model to a single model which aims to minimize the total cost, environmental impact, and social impact. Subsequently, for solving this nonlinear and complex multi-objective decision-making model, an improved hybrid algorithm that integrated Tabu Search and non-dominated sorting genetic algorithm II (TS-NSGA-II) is applied to solve the above model. Finally, a case study of CoPS manufacturing project is illustrated to demonstrate the effectiveness and superiority of the proposed TSMM-CoPS-LCSA model. The results indicate that the proposed method can find a better services scheme in line with actual demand, which provides a guiding significance for promoting the sustainable development of the manufacturing industry.

Microstructures, Corrosion Resistance and Wear Resistance of High-Entropy Alloys Coatings with Various Compositions Prepared by Laser Cladding: A Review

Nowadays, high-entropy alloys (HEAs) have become a hot research topic in the field of coating materials. However, HEAs have a large wide range of compositional systems, and the differences in their composition inevitably lead to the significant variations in the matching process parameters of laser cladding and post-treatment methods, which in turn give the coatings a broad range of microstructures and protective properties. Therefore, it is crucial to review and summarize the research progresses on laser cladding HEA coatings to provide a reference for obtaining high-performance HEA coatings and further expand the application of HEA coatings. This work describes the working mechanism of laser cladding and illustrates the advantages and drawbacks of laser cladding in detail. The effects of the addition of alloying elements, process parameters and post-treatment techniques on the microstructures and properties of the coatings are thoroughly reviewed and analyzed. In addition, the correlations between the chemical compositions of HEAs, process parameters of laser cladding, post-treatment techniques and the microstructure and protective properties of the coatings are investigated and summarized. On this basis, the future development direction of HEA coatings is outlined.

Construction of Data Resource Sharing Platform in College Students’ Ideological and Political Education Based on Deep Learning

At present, the irrational allocation of IPE (ideological and political education) resources in universities reflects the dilemma of university’s control of university students’ IPE system. In order to make educational big data really useful to us and really promote the sharing of educational resources and improve the utilization rate of resources, this paper discusses the construction of data resource sharing platform for college students in IPE field based on DL (Deep learning) based on the characteristics and existing problems of educational big data. Based on DL, the collected data are parameterized, the matching algorithm parameters are determined, the dynamic data sample subset is incrementally reduced, the discernibility matrix and logical analytic formula are established, the conjunctive normal form is obtained through calculation, and the kernel attribute is introduced into each conjunctions to realize incremental mining of dynamic data. The results show that the model in this paper achieves the best classification effect on six samples, with an average classification accuracy of 88.81%. The results show that the comprehensive shared data matching algorithm based on DL can realize the matching in a short time, and the matching process has high stability.

Application of Sparse-Channel Lidar Sensors on Viewpoint-Invariant Loop Closing Task

Loop closing is an essential task for SLAM system, which can reduce the pose drifts and map distortion. However, challenges from viewpoint changes and sparse-channel lidar are still open problems. In this paper, a novel efficient and viewpoint-invariant loop closing method is presented, which well fits sparse-channel lidars. To keep the metric information of 3D point clouds, elevation maps are explored to represent sparse point clouds, based on which a novel and viewpoint-invariant key point feature detection method is proposed. To improve efficiency, Bag of Words technique is applied to accelerate the process of scene description and matching. In addition, a strict geometric consistency check of matched key point pairs is proposed to reject false positive detections, which makes our method robust to scenes with similar layouts in urban environments. Extensive experiments on challenging public datasets verify the validity and superiority of the proposed method.

RESEARCH ON THE REGULATION OF MULTI-AGENT'S EMOTION BASED ON MULTI-AGENT'S HETEROGENEOUS GAME PREFERENCE AND BILATERAL PARTNER'S PREFERENCE

Abstract Background The development of virtual enterprise is inseparable from the support of partners. Due to information asymmetry, the choice of virtual enterprise partners is blind, and simple matching formula is difficult to meet. At the same time, the psychology of the matching subject is based on the maximization of its own interests rather than the maximization of collective interests. There are interest contradictions and conflicts between subjects, and they may eventually fall into a “prisoner's dilemma”. Therefore, how to carry out the research on emotion regulation based on multi-agent heterogeneous game preference and bilateral partner preference is very important. Research Objects and Methods Aiming at the contradictions and interest conflicts between subjects in the process of virtual enterprise partner matching, combined with the basic characteristics of subject language preference evaluation, the game idea is introduced into the process of virtual enterprise partner bilateral matching analysis, a bilateral matching game model of heterogeneous multi-attribute preference and subjects' psychological behavior is proposed, and the influence of the changes of subjects' psychological behavior on the evolution law of bilateral matching game system is analyzed, The Nash equilibrium strategy of bilateral matching is discussed. In order to verify the impact of the algorithm on emotion, this study uses relevant scales to investigate. (1) Positive emotion scale. The Panas emotion scale developed by Watson et al. Is widely used to measure emotion. The scale includes two dimensions: positive emotion and negative emotion. There are 6 questions in this dimension, and Likert scores 5 points (1 means “very inconsistent”, 5 means “very consistent”, the same below). The Cronbach coefficient of this questionnaire is 0.90. (2) Motivation. The problem of measuring motivation is mainly the motivation scale compiled by Phan, which has 8 questions and is scored with Likert 5 points. (3) Social support scale. The scale is adapted from the social support scale compiled by Ye Yuemei et al. It has eight questions, using Likert's five points scoring method. Clonbach α the coefficient of the scale is 0.87. (4) Behavioral propensity scale. Propensity dimension in intention measurement. The scale has 6 questions, and Likert scores 5 points. The clonbach coefficient of the scale is 0.95. Results The results of case analysis show that the model can make full use of the multi-attribute preference information of heterogeneous subjects, describe the mechanism of psychological behavior affecting the evolution of game system, and help virtual enterprises match business partners; This has important value and significance for the establishment of virtual enterprises and their industrial agglomeration effect. In the influence process of cooperative anxiety, emotional response plays an intermediary role, psychological elasticity plays a regulatory role, and emotional response to life events plays an intermediary role. That is, the higher the psychological elasticity, the higher the excessive coping style of the game, and vice versa. Conclusion Various stable matching solutions can be obtained by solving the model, and the conclusion is more suitable for the matching decision-making process of both parties in the actual process, which makes the model can be applied to various scenarios, such as the selection of battery suppliers of new energy vehicles and smart phone screen suppliers, which has greater practical value and significance. It should be pointed out that there are some deficiencies in the setting conditions of the model method, mainly because some individuals in the group cooperate to form an alliance, so as to form a community of interests. In the process of game, the individual experience in the group is constrained by more conditions, which makes the results of the model deviate. Acknowledgements Zhejiang Provincial Natural Science Foundation (No. LQ20G010005), Zhejiang Provincial Statistical Science Research Project (NO. 21TJQN15) and Natural Science Fund Project of Huzhou City (No. 2018YZ13)

Optimally filtering and matching processing for regional upstrokes to improve ultrasound transit time-based local PWV estimation

Background and objectivePulse wave velocity (PWV) is an important index for quantifying the elasticity of artery. Local PWV estimates based on ultrasonic transit time (TT) methods, however, are affected by the reflected waves and ultrasonic noise, biasing the spatiotemporal propagation of the time fiduciary point (TFP) positioning in the distension waveforms. In this study, an optimally filtering and matching processing for regional upstrokes is proposed to improve the ultrasound TT-based local PWV estimation. Method(i) Smooth the pulse waves (PWs) using the Savitzky–Golay filter with one set of randomly combined parameters. (ii) An arbitrary region at the first beam upstroke of the smoothed PWs is selected as the curve template, and then matched with the upstrokes of other PWs by calculating the sum of square differences (SSD) between the template and matching regions to find its similar regions. (iii) Update the filter parameters and the template using the moth-flame optimization (MFO) feedback for computing the new SSD value. When the new SSD value is smaller than the historical one, the later will be replaced. (iv) Repeat the above steps until the MFO algorithm converges to the minimum SSD value. (v) Output the optimal filter parameters and the locations of regional curves corresponding to the minimum SSD value. Then the time delay of the PWs propagation can be detected by using the starting points of the regional curves as the TFPs. ResultsWe conducted performance comparison with the advanced TT method through both simulation and clinical experiments. The results demonstrate that the proposed work observes considerable reductions on both the normalized root mean square error ± the standard deviation (from 6.73 ± 2.27% to 1.57 ± 0.72%) and the coefficient of variation (from 13.39% to 8.87%). ConclusionsThe results of this study support that the proposed method may facilitate the early diagnosis and prevention of local arterial stiffness .

Detection of Room Cleanliness Based on Digital Image Processing using SVM and NN Algorithm

A clean environment can prevent us from disease and can increase productivity. A neat and clean room arrangement can affect health, avoiding the possibility of stress, lethargy, and depression. The room recognition process based on its neatness is carried out through a process of matching and comparing the images that are used as training and testing sets. Technological developments make it possible to detect room conditions through image. Detection uses image processing by classifying images into 2 categories, clean and messy. It has been widely used in various fields, one of which is hospitality. In determining the clean room and messy room has problems due to image quality, different lighting, and image similarity. This study aims to detect clean and messy spaces by comparing the Support Vector Machine and Neural Network methods on a dataset of 199 images. Based on the test, the highest accuracy classification value was 98.0% for the Neural Network method with an AUC of 0.999

Relative Importance of Applicant Characteristics in Ophthalmology Residency Interview Selection: A Survey of Program Directors.

Introduction Ophthalmology residency positions remain competitive. A lack of clarity regarding which residency selection criteria are prioritized by program directors can heighten the stress associated with the match process. While surveys of program directors in several other medical specialties have been conducted to identify the most important residency selection criteria, there is limited data on selection criteria used by ophthalmology residency program directors. The purpose of our study was to survey ophthalmology residency program directors to identify the current state of interview selection decisions-the factors currently considered most important in determining whether to extend an interview invitation to residency applicants. Methods We developed and distributed a Web-based questionnaire to all U.S. ophthalmology residency program directors. Questions evaluated program demographics and the relative importance of 23 different selection criteria used by ophthalmology residency program directors when evaluating applicants for residency interviews (Likert scale 1-5, with 1 being "not important" and 5 being "very important"). Program directors were also asked to identify the one factor they felt was most important. Results The overall residency program director response rate was 56.5% (70/124). The selection criteria with the highest average importance scores were core clinical clerkship grades (4.26/5) followed by letters of recommendation (4.06/5), and United States Medical Licensing Examination (USMLE) Step 1 score (4.03/5). The most frequently cited single most important factor for interview selection was core clinical clerkship grades (18/70, 25.7%), with USMLE Step 1 score (9/70, 12.9%) and rotations at the program director's department (6/70, 8.6%) also commonly reported. Conclusion Our results suggest that core clinical clerkship grades, letters of recommendation, and USMLE Step 1 scores are deemed the most important selection criteria by ophthalmology residency program directors as of a 2021 survey. With changes in clerkship grading for many medical schools and changes in national USMLE Step 1 score reporting, programs will face challenges in evaluating applicants and the relative importance of other selection criteria will likely increase.

Are Orthopedic Fellowship Programs Giving Out Too Many Interviews? A Retrospective Analysis Suggests They Are.

Background: The orthopedic surgery fellowship match process is associated with substantial stress and expense, yet the optimal number of interviews for fellowships to offer has not been evaluated. Purpose: We sought to evaluate the number of orthopedic surgery fellowship interviews given and construct a model to determine the appropriate number of interviews to offer based on specialty and program size. Methods: We conducted a retrospective study of 6 orthopedic fellowship specialties; data were obtained from San Francisco Match and covered the 5-year period from 2014 to 2018. The orthopedic fellowship subspecialties included adult reconstruction/oncology, foot and ankle, pediatrics, spine, sports medicine, and trauma. We excluded shoulder and elbow (less than 5 years of data) and hand and upper extremity (alternative matching process). Parameters included number of programs, number of spots per program, number of ranked applicants per program (mean ± SD), and difference in number of interviews offered and ranked applicants per program (mean ± SD). Multiple regression analysis was used to create an equation for determining the optimal number of interviews for the programs. Results: Of 1377 orthopedic fellowship programs analyzed, 1370 (99.50%) conducted interviews beyond the number of ranked applicants. Programs ranked an overall mean of 20.10 ± 10.17 applicants with an overall mean of 11.60 ± 8.62 additional interviews offered. Sports medicine had the highest mean ranked applicants (23.21 ± 9.77) and pediatrics had the lowest mean ranked applicants (15.74 ± 7.76). The most additional interviews were given in adult reconstruction (14.80 ± 9.92) and the least were given in pediatrics (8.32 ± 7.17). The predictive equation was reported as Y = β1x1 + β2x2 (Y = ranked applicants, x1 = spots open, and x2 = last rank). Conclusion: Programs in 6 orthopedic subspecialties in the fellowship match process appear to consistently offer more interviews than necessary. We have developed a model to help programs predict the optimal number of fellowship applicants to interview. Future studies need to validate the model, especially with anticipated increases of the virtual interview format.

RapidFlow

Continuous subgraph matching (CSM) is an important building block in many real-time graph processing applications. Given a subgraph query Q and a data graph stream, a CSM algorithm reports the occurrences of Q in the stream. Specifically, when a new edge e arrives in the stream, existing CSM algorithms start from the inserted e in the current data graph G to search Q. However, this rigid matching order of always starting from e can lead to a massive number of partial results that will turn out futile. Also, if Q contains automorphisms, there will be a lot of redundant computation in the matching process. To address these two problems, we propose RapidFlow, an effective approach to CSM. First, we design a query reduction technique, which reduces CSM to batch subgraph matching (BSM) where we enumerate all results in a region of G that will be affected by the update. The well-established BSM techniques can determine effective matching orders, not necessarily starting from the newly inserted edge. Second, to eliminate redundant computation caused by automorphisms in Q , we propose dual matching, which leverages the duality of Q and G in the matching process. Extensive experiment results show that RapidFlow outperforms state-of-the-art algorithms, including TurboFlux and SymBi, by up to two orders of magnitude on various workloads.

Permitting the Compensation of Birth Mothers for Adoption Expenses and its Impact on Adoptions

Abstract For seven decades, states have passed legislation to regulate the exchange of funds in the adoption process by either enabling or prohibiting prospective adoptive parents from compensating a matched birth mother for adoption-related expenses. In 1940, no state codes contained provisions for adoption compensation. By the mid-1980s, nearly half of states had passed such legislation, and today, 45 states have such laws. Leveraging this variation in state adoption laws governing compensation, I estimate how the allowance of monetary transfers affects the number of infant adoptions in a two-stage difference-in-differences framework. Results indicate that the number of private infant adoptions is not affected by the passage of such laws, and estimates are robust across multiple specifications. The findings suggesting that non-fiscal concerns or uncertainty in the matching process may overshadow potential compensation of medical, legal, or living expenses.

Research on Rule Matching Model Based on Spark

Rule engines are widely used in engineering and academic fields because they can flexibly separate facts and rules from the rule matching process. Since the rule matching process is very time-consuming, and the traditional rule matching uses single-computer operation when many facts and rules exceed the computer’s memory and computational capacity limit, it will cause the application to crash and paralyze. To solve the above problems, this paper investigates the Spark framework and Rete algorithm to take advantage of Spark’s in-memory computation to alleviate the time-consuming problem of the traditional rule matching process. A high-performance distributed rule matching model is designed by combining the actual rule matching scenario and the development process. In addition, according to the form of rules and facts in the actual scenario, this paper effectively divides the matching process and improves the scalability of the rule matching model.