Differences In Performance Metrics Research Articles

Revolutionizing malaria diagnosis: deep learning-powered detection of parasite-infected red blood cells

Malaria is a significant global health issue, responsible for the highest rates of morbidity and mortality globally. This paper introduces a very effective and precise convolutional neural network (CNN) method that employs advanced deep learning techniques to automate the detection of malaria in images of red blood cells (RBC). Furthermore, we present an emerging and efficient deep learning method for differentiating between cells infected with malaria and those that are not infected. To thoroughly evaluate the efficiency of our approach, we do a meticulous assessment that involves comparing different deep learning models, such as ResNet-50, MobileNet-v2, and Inception-v3, within the domain of malaria detection. Additionally, we conduct a thorough comparison of our proposed approach with current automated methods for malaria identification. An examination of the most current techniques reveals differences in performance metrics, such as accuracy, specificity, sensitivity, and F1 score, for diagnosing malaria. Moreover, compared to existing models for malaria detection, our method is the most successful, achieving an accurate score of 1.00 in all statistical matrices, confirming its promise as a highly efficient tool for automating malaria detection.

Evaluating the Quality of Examination Items From the Pathophysiology, Drug Action, and Therapeutics Course Series

ObjectiveTo determine the impact of item-writing flaws and cognitive level on student performance metrics in 1 course series across 2 semesters at a single institution. MethodsFour investigators reviewed 928 multiple-choice items from an integrated therapeutics course series. Differences in performance metrics were examined between flawed and standard items, flawed stems and flawed answer choices, and cognitive levels. ResultsReviewers found that 80% of the items were flawed, with the most common types being implausible distractors and unfocused stems. Flawed items were generally easier than standard ones, but the type of flaw significantly impacted the difficulty. Items with flawed stems had the same difficulty as standard items; however, those with flawed answer choices were significantly easier. Most items tested lower-level skills and have more flaws than higher-level items. There was no significant difference in difficulty between lower- and higher-level cognitive items, and higher-level items were more likely to have answer flaws than item flaws. ConclusionItem-writing flaws differently impact student performance. Implausible distractors artificially lower the difficulty of questions, even those designed to assess higher-level skills. This effect contributes to a lack of significant difference in difficulty between higher- and lower-level items. Unfocused stems, on the other hand, likely increase confusion and hinder performance, regardless of the question’s cognitive complexity.

A Comparative American Board of Surgery In-Training Examination (ABSITE) Performance Analysis Between International vs. Domestic Graduates and Doctor of Medicine (MD) vs. Doctor of Osteopathic Medicine (DO) Medical Degrees.

Introduction The American Board of Surgery (ABS) plays a pivotal role in certifying surgeons in the United States, with the American Board of Surgery In-Training Examination (ABSITE) serving as a critical assessment tool for general surgery residents aspiring for certification. The aim of this study is to compare the performance of international medical graduates (IMGs) to their domestic counterparts and assess the impact of different medical degrees on ABSITE scores. Notably, ABSITE scores often dictate the trajectory of a surgical career, including opportunities for fellowship placements in specialized fields such as plastic surgery. Methods This study focused on general surgery residents enrolled at Marshall University from 2014 to 2022. Data encompassing ABSITE scores, TrueLearn quiz percentages, and TrueLearn mock exam results were collected for analysis. Descriptive statistics summarized sample characteristics, and linear mixed models were employed to address correlations. Statistical analyses were conducted using the Statistical Analysis System (SAS) (version 9.4; SAS Institute Inc., Cary, NC, USA), with significance defined by a two-sided test with p < 0.05. Results Among the 48 participants, comprising 24 non-international medical graduates (nIMGs) and 24IMGs, IMGs demonstrated superior performance across various metrics. They exhibited higher quiz percentages (67% vs. 61%; p = 0.0029), mock Exam 1 scores (64% vs. 58%; p = 0.0021), mock Exam 2 scores (66% vs. 58%; p = 0.0015), ABSITE scores (560 vs. 505; p = 0.010), and ABSITE percentages (74% vs. 68%; p = 0.0077) compared to nIMGs. Analysis between Doctor of Osteopathic Medicine (DO) and Doctor of Medicine (MD) participants revealed no statistically significant differences in performance metrics, highlighting the comparability of these medical degrees in the context of ABSITE scores and related assessments. Discussion/conclusion This study underscores the superior performance of IMGs over nIMGs in ABSITE examinations, shedding light on the critical role of ABSITE scores in shaping surgical careers. Higher scores correlate with enhanced opportunities for coveted fellowship placements, particularly in specialized fields like plastic surgery. Understanding these dynamics is crucial for resident training and navigating the competitive landscape of surgical sub-specialization. Future research endeavors can delve deeper into the factors influencing ABSITE performance, thereby facilitating the development of targeted interventions to support residents in achieving their career aspirations.

Effects of Ramadan intermittent fasting on performance, physiological responses, and bioenergetic pathway contributions during repeated sprint exercise.

This investigation aims to elucidate the impact of Ramadan intermittent fasting on performance, physiological responses, and bioenergetic pathway contributions during repeated sprints. Fourteen active male Muslim athletes (age = 22.4 ± 1.8 years, body weight = 69.5 ± 3.8 kg, height = 176 ± 5.1 cm) executed a repeated sprint protocol, consisting of ten 20-meter sprints with 15-s passive recovery intervals, during both fasting and non-fasting conditions. The fasting session was conducted after a 12-14 h fast following Sahur (the pre-dawn meal during Ramadan). In contrast, the non-fasting session occurred before the Ramadan fasting period began, during the same hours of the day, at a time when fasting was not yet required for the athletes. Bioenergetic pathway contributions during repeated sprints were quantified using the PCr-LA-O2 method. The mean sprint time during fasting sessions was 3.4 ± 0.3 s compared to 3.3 ± 0.2 s in non-fasting sessions, indicating a trend approaching the threshold of significance for slower times in the fasted state (p = 0.052, effect size (ES) = 0.34). In terms of bioenergetic contributions, the total metabolic energy expenditure (TEE) was slightly lower during fasting sessions (236.5 ± 22 kJ) compared to non-fasting sessions (245.2 ± 21.7 kJ), but this difference was not statistically significant (p = 0.102, ES = 0.40). Similarly, metabolic energy expenditure per sprint was 23.7 ± 2.2 kJ in fasting conditions compared to 24.5 ± 2.2 kJ in non-fasting conditions (p = 0.106, ES = 0.35). The oxidative energy contribution did not differ significantly between fasting (34.2 ± 4.1 kJ) and non-fasting conditions (34.2 ± 4.1 vs. 35.5 ± 5.2 kJ; p = 0.238, ES = 0.28). Similarly, lactic (60.4 ± 7.6 vs. 59.2 ± 8.3 kJ; p = 0.484, ES = 0.15); and alactic (149.3 ± 19.9 vs. 143 ± 21.5 kJ; p = 0.137, ES = 0.30) energy contributions showed no significant differences between the fasting and non-fasting sessions. The percentage of performance decrement (Pdec) and the percentage contributions of oxidative, lactic, and alactic pathways to the total energy expenditure did not differ significantly between the fasting and non-fasting conditions, indicating a similar bioenergetic profile across both conditions. The present findings indicate no significant differences in performance metrics and metabolic outcomes between fasted and non-fasted states. Future assessments with longer duration and higher intensity protocols may provide further insights.

Comparative Analysis of Watermarking Methods for DICOM Images: DWT and SVD vs. Traditional Techniques

Digital Imaging and Communications in Medicine (DICOM) images play a critical role in healthcare, necessitating robust methods for ensuring their integrity and authenticity. This research paper evaluates the effectiveness and efficiency of watermarking techniques applied to DICOM images, with a specific emphasis on comparing Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) approaches against traditional methods. The study examines three key criteria-robustness against attacks, imperceptibility to maintain diagnostic integrity, and computational performance-aiming to provide insights into the suitability of these techniques for protecting medical data. Results indicate significant differences in performance metrics, highlighting both strengths and limitations of each approach in the context of medical image watermarking.

Low‐level infection of parasitic copepods on Rainbow Trout does not affect vulnerability to angling or short‐term survival following catch‐and‐release angling

AbstractObjectiveParasitic copepods, or “gill lice,” can harm fish hosts, resulting in reductions in fitness and increased probability of mortality. The purpose of our study was to determine the effect of Salmincola californiensis on the vulnerability of Rainbow Trout Oncorhynchus mykiss to recreational angling and short‐term survival after being caught and released.MethodsWe compared the prevalence and intensity of infection of S. californiensis on Rainbow Trout that were caught while angling and with a backpack electrofisher in May and October 2020 in Birch Creek, Idaho. In October, we also conducted a stress test (air‐exposure treatment) on trout that were caught by angling to determine the effects of parasitic copepods on the short‐term survival of Rainbow Trout in a catch‐and‐release fishery.ResultInfection with S. californiensis did not influence the vulnerability of Rainbow Trout to angling. After adjusting for sample size and size distribution, the prevalence of infection in May was 48.3% for Rainbow Trout that were caught while electrofishing and 49.3% for Rainbow Trout that were caught while angling. In October, the prevalence of infection was 41.2% for Rainbow Trout that were caught while electrofishing and 41.8% for Rainbow Trout that were caught while angling. We did not find a difference in short‐term survival rates for infected and uninfected Rainbow Trout after the stress test (4–7 days after the test).ConclusionWe did not observe consequences of infection by parasitic copepods on vulnerability to angling or short‐term survival of Rainbow Trout in Birch Creek. However, the conditions (low‐level of infection and relatively small fish) may not have been conducive to detecting differences in the performance metrics; further testing at higher intensity of infection and with larger fish may uncover the negative effects of parasitic copepods on Rainbow Trout.

Are Differences in Research Performance Creating a Glass Ceiling for Women Faculty in Business Schools?

Despite prevailing discourses around equal opportunity and inclusivity, gender disparity still exists in academic ranks and leadership positions. The authors reviewed 3290 faculty members within the thirty top-ranked business schools around the world, using the Scopus database to retrieve the h-index, number of publications, and citations for each faculty member. They examined the distribution of male and female faculty members across geographical regions, academic ranks, and subspecialties while comparing academic performance. The authors found evident disparities between male and female faculty across all domains, with women occupying a disproportionately lower number of academic ranks and leadership positions despite no significant differences in performance metrics. The greatest disparity was among the professor rank; less than one-fifth of all business professors were female.

Stratified assessment of an FDA-cleared deep learning algorithm for automated detection and contouring of metastatic brain tumors in stereotactic radiosurgery

PurposeArtificial intelligence-based tools can be leveraged to improve detection and segmentation of brain metastases for stereotactic radiosurgery (SRS). VBrain by Vysioneer Inc. is a deep learning algorithm with recent FDA clearance to assist in brain tumor contouring. We aimed to assess the performance of this tool by various demographic and clinical characteristics among patients with brain metastases treated with SRS.Materials and methodsWe randomly selected 100 patients with brain metastases who underwent initial SRS on the CyberKnife from 2017 to 2020 at a single institution. Cases with resection cavities were excluded from the analysis. Computed tomography (CT) and axial T1-weighted post-contrast magnetic resonance (MR) image data were extracted for each patient and uploaded to VBrain. A brain metastasis was considered “detected” when the VBrain- “predicted” contours overlapped with the corresponding physician contours (“ground-truth” contours). We evaluated performance of VBrain against ground-truth contours using the following metrics: lesion-wise Dice similarity coefficient (DSC), lesion-wise average Hausdorff distance (AVD), false positive count (FP), and lesion-wise sensitivity (%). Kruskal–Wallis tests were performed to assess the relationships between patient characteristics including sex, race, primary histology, age, and size and number of brain metastases, and performance metrics such as DSC, AVD, FP, and sensitivity.ResultsWe analyzed 100 patients with 435 intact brain metastases treated with SRS. Our cohort consisted of patients with a median number of 2 brain metastases (range: 1 to 52), median age of 69 (range: 19 to 91), and 50% male and 50% female patients. The primary site breakdown was 56% lung, 10% melanoma, 9% breast, 8% gynecological, 5% renal, 4% gastrointestinal, 2% sarcoma, and 6% other, while the race breakdown was 60% White, 18% Asian, 3% Black/African American, 2% Native Hawaiian or other Pacific Islander, and 17% other/unknown/not reported. The median tumor size was 0.112 c.c. (range: 0.010–26.475 c.c.). We found mean lesion-wise DSC to be 0.723, mean lesion-wise AVD to be 7.34% of lesion size (0.704 mm), mean FP count to be 0.72 tumors per case, and lesion-wise sensitivity to be 89.30% for all lesions. Moreover, mean sensitivity was found to be 99.07%, 97.59%, and 96.23% for lesions with diameter equal to and greater than 10 mm, 7.5 mm, and 5 mm, respectively. No other significant differences in performance metrics were observed across demographic or clinical characteristic groups.ConclusionIn this study, a commercial deep learning algorithm showed promising results in segmenting brain metastases, with 96.23% sensitivity for metastases with diameters of 5 mm or higher. As the software is an assistive AI, future work of VBrain integration into the clinical workflow can provide further clinical and research insights.

Stratified Assessment of a Commercial Deep Learning Algorithm for Automated Detection and Contouring of Metastatic Brain Tumors in Stereotactic Radiosurgery

<h3>Purpose/Objective(s)</h3> Artificial intelligence-based tools can be leveraged to improve detection and segmentation of brain metastases for stereotactic radiosurgery (SRS). This study explores a deep learning algorithm with recent FDA clearance to assist in brain tumor contouring. In this study, we aimed to assess the performance of this tool by various demographic and clinical characteristics among patients with brain metastases treated with SRS. <h3>Materials/Methods</h3> We randomly selected 100 patients with brain metastases who underwent initial SRS on a frameless robotic radiosurgery system from 2017 to 2020 at a single institution. Cases with resection cavities were excluded from the analysis. Computed tomography (CT) and axial T1-weighted post-contrast magnetic resonance (MR) image data were extracted for each patient and uploaded to VBrain. A brain metastasis was considered "detected" when the VBrain "predicted" contours overlapped with the corresponding physician contours ("ground-truth" contours). We evaluated performance of VBrain against ground-truth contours using the following metrics: lesion-wise Dice similarity coefficient (DSC), lesion-wise average Hausdorff distance (AVD), false positive count (FP), and lesion-wise sensitivity (%). Wilcoxon rank-sum tests were performed to assess the relationships between patient characteristics including sex, race, primary histology, age, and size and number of brain metastases, and performance metrics such as DSC, AVD, FP, and sensitivity. <h3>Results</h3> We analyzed 100 patients with 422 intact brain metastases treated with SRS. Our cohort consisted of patients with a median number of 2 brain metastases (range: 1 to 47), median age of 79 (range: 19 to 91), and 50% male and 50% female patients. The primary site breakdown was 56% lung, 10% melanoma, 9% breast, 8% gynecological, 5% gastrointestinal, 2% prostate, and 5% other, while the race breakdown was 60% White, 18% Asian, 3% Black/African American, 2% Native Hawaiian or other Pacific Islander, and 17% other/unknown/not reported. The median tumor size was 0.118 c.c. (range: 0.003-28.838 c.c.). We found mean lesion-wise DSC to be 0.714, mean lesion-wise AVD to be 8.44% of lesion size (0.796 mm), mean FP count to be 0.17 tumors per case, and lesion-wise sensitivity to be 83.65% for all lesions. Moreover, mean sensitivity was found to be 98%, 91.93%, and 79.87% for lesions with diameter equal to and greater than 10 mm, 5 mm, and 3 mm, respectively. No other significant differences in performance metrics were observed across demographic or clinical characteristic groups. <h3>Conclusion</h3> A commercial deep learning algorithm showed promising results in segmenting brain metastases, with 98% sensitivity for metastases with diameters of 1 cm or higher. Performance declined for smaller lesions. As advances in imaging and radiosurgery enable the detection and treatment of smaller brain metastases, future work is ongoing to develop and improve these tools to assist in radiosurgical treatment planning.

Association Between Parental Leave and Ophthalmology Resident Physician Performance

Although parental leave is essential in enhancing resident wellness and fostering inclusive workplace environments, residents may often feel discouraged from using parental leave owing to perceived stigma and concerns about possible negative effects on their training. To examine parental leave usage across multiple institutions and compare residency performance metrics between residents who took parental leave vs their peers who did not take leave. This was a retrospective cross-sectional analysis conducted from April 1, 2020, to July 28, 2022, of educational records. Multicenter data were obtained from 10 Accreditation Council for Graduate Medical Education (ACGME)-accredited ophthalmology programs across the US. Included ophthalmology residents graduated between 2015 and 2019. Data were analyzed from August 15, 2021, to July 25, 2022. Performance metrics of residents who used parental leave during residency were compared with those of residents who did not take parental leave. Measures of performance included the Ophthalmic Knowledge Assessment Program (OKAP) scores, ACGME milestones scores, board examination pass rates, research activity, and surgical volumes. Of the 283 ophthalmology residents (149 male [52.7%]) included in the study, 44 (15.5%) took a median (IQR) parental leave of 4.5 (2-6) weeks. There were no differences in average OKAP percentiles, research activity, average ACGME milestones scores, or surgical volume between residents who took parental leave and those who did not. Residents who pursued fellowship were less likely to have taken parental leave (odds ratio [OR], 0.43; 95% CI, 0.27-0.68; P < .001), and residents who practiced in private settings after residency were more likely to have taken parental leave (OR, 3.56; 95% CI, 1.79-7.08; P < .001). When stratified by sex, no differences were identified in performance between female residents who took parental leave compared with residents who did not take leave, except a mild surgical number difference in 1 subspecialty category of keratorefractive procedures (difference in median values, -2; 95% CI, -3.7 to -0.3; P = .03). In this multicenter cross-sectional study, no differences in performance metrics were identified between residents taking parental leave compared with their peers. These findings may provide reassurance to trainees and program directors regarding the unlikelihood, on average, that taking adequate parental leave will affect performance metrics adversely.

GSEA-SDBE: A gene selection method for breast cancer classification based on GSEA and analyzing differences in performance metrics.

Selecting the most relevant genes for sample classification is a common process in gene expression studies. Moreover, determining the smallest set of relevant genes that can achieve the required classification performance is particularly important in diagnosing cancer and improving treatment. In this study, I propose a novel method to eliminate irrelevant and redundant genes, and thus determine the smallest set of relevant genes for breast cancer diagnosis. The method is based on random forest models, gene set enrichment analysis (GSEA), and my developed Sort Difference Backward Elimination (SDBE) algorithm; hence, the method is named GSEA-SDBE. Using this method, genes are filtered according to their importance following random forest training and GSEA is used to select genes by core enrichment of Kyoto Encyclopedia of Genes and Genomes pathways that are strongly related to breast cancer. Subsequently, the SDBE algorithm is applied to eliminate redundant genes and identify the most relevant genes for breast cancer diagnosis. In the SDBE algorithm, the differences in the Matthews correlation coefficients (MCCs) of performing random forest models are computed before and after the deletion of each gene to indicate the degree of redundancy of the corresponding deleted gene on the remaining genes during backward elimination. Next, the obtained MCC difference list is divided into two parts from a set position and each part is respectively sorted. By continuously iterating and changing the set position, the most relevant genes are stably assembled on the left side of the gene list, facilitating their identification, and the redundant genes are gathered on the right side of the gene list for easy elimination. A cross-comparison of the SDBE algorithm was performed by respectively computing differences between MCCs and ROC_AUC_score and then respectively using 10-fold classification models, e.g., random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), extreme gradient boosting (XGBoost), and extremely randomized trees (ExtraTrees). Finally, the classification performance of the proposed method was compared with that of three advanced algorithms for five cancer datasets. Results showed that analyzing MCC differences and using random forest models was the optimal solution for the SDBE algorithm. Accordingly, three consistently relevant genes (i.e., VEGFD, TSLP, and PKMYT1) were selected for the diagnosis of breast cancer. The performance metrics (MCC and ROC_AUC_score, respectively) of the random forest models based on 10-fold verification reached 95.28% and 98.75%. In addition, survival analysis showed that VEGFD and TSLP could be used to predict the prognosis of patients with breast cancer. Moreover, the proposed method significantly outperformed the other methods tested as it allowed selecting a smaller number of genes while maintaining the required classification accuracy.

Thoracic Outlet Syndrome in Major League Baseball Pitchers: Return to Sport and Performance Metrics After Rib Resection.

Background:Thoracic outlet syndrome (TOS) is a rare injury that affects Major League Baseball (MLB) pitchers and is often corrected with surgical resection of the first rib. There are limited return-to-play (RTP) data for this surgery in MLB pitchers.Hypothesis:It was hypothesized that MLB pitchers who undergo first rib resection for TOS will show (1) a high rate of RTP, (2) no difference in postoperative career length compared with controls, (3) no difference in pre- and postoperative performance, and (4) no difference in postoperative performance compared with controls.Study Design:Cohort study; Level of evidence, 3.Methods:This retrospective cohort study evaluated MLB pitchers with neurogenic or vascular TOS who underwent rib resection surgery between January 1, 2001, and December 31, 2019. Players were identified through public injury reports from press releases, the MLB website, MLB team injury reports, and blogs. A demographics- and performance-matched control group was generated for comparison. Each player in the control group was given an index year that corresponded to the surgery year of the case group. Performance data included innings pitched (IP), games played (GP), earned run average (ERA), complete GP, shutouts, saves, hits, runs, home runs (HR), walks, strikeouts (K), walks plus hits per IP (WHIP), and earned runs (ER).Results:We identified 26 MLB pitchers who underwent rib resection for neurogenic or vascular TOS; 21 players (81%) had a successful RTP. Pitchers were 30 ± 3.6 years old at the time of surgery and had played 6.2 ± 3.5 seasons before undergoing surgery. Average postoperative career length was 3.1 ± 2.0 seasons, with an average time from surgery to RTP being 10 ± 4.7 months. Pitchers who RTP showed no significant differences in performance metrics compared with controls. Players pitch 0.94 (P < .05) more IP/GP in the season directly following RTP compared with the season before surgical intervention.Conclusion:MLB pitchers undergoing rib resection for TOS demonstrated (1) high RTP rates following rib resection, (2) no difference in postoperative career length compared with controls, (3) improvement in postoperative performance, and (4) no difference in postoperative performance compared with controls.

Climbing Performance in U23 and Professional Cyclists during a Multi-stage Race.

The aim of this study was to analyze climbing performance across two editions of a professional multistage race, and assess the influence of climb category, prior workload, and intensity measures on climbing performance in U23 and professional cyclists. Nine U23 cyclists (age 20.8±0.9 years) and 8 professional cyclists (28.1±3.2 years) participated in this study. Data were divided into four types: overall race performance, climb category, climbing performance metrics (power output, ascent velocity, speed), and workload and intensity measures. Differences in performance metrics and workload and intensity measures between groups were investigated. Power output, ascent velocity, speed were higher in professionals than U23 cyclists for Cat 1 and Cat 2 (p≤0.001-0.016). Workload and intensity measures (Worktotal, Worktotal∙km-1, Elevationgain, eTRIMP and eTRIMP∙km-1) were higher in U23 compared to professionals (p=0.002-0.014). Climbing performance metrics were significantly predicted by prior workload and intensity measures for Cat 1 and 2 (R2=0.27-0.89, p≤0.001-0.030) but not Cat 3. These findings reveal that climbing performance in professional road cycling is influenced by climb categorization as well as prior workload and intensity measures. Combined, these findings suggest that Cat 1 and 2 climbing performance could be predicted from workload and intensity measures.

Improving predictive performance on survival in dairy cattle using an ensemble learning approach

Cow survival is a complex trait that combines traits like milk production, fertility, health and environmental factors such as farm management. This complexity makes survival difficult to predict accurately. This is probably the reason why few studies attempted to address this problem and no studies are published that use ensemble methods for this purpose. We explored if we could improve prediction of cow survival to second lactation, when predicted at five different moments in a cow’s life, by combining the predictions of multiple (weak) methods in an ensemble method. We tested four ensemble methods: majority voting rule, multiple logistic regression, random forest and naive Bayes. Precision, recall, balanced accuracy, area under the curve (AUC) and gains in proportion of surviving cows in a scenario where the best 50% were selected were used to evaluate the ensemble model performance. We also calculated correlations between the ensemble models and obtained McNemar’s test statistics. We compared the performance of the ensemble methods against those of the individual methods. We also tested if there was a difference in performance metrics when continuous (from 0 to 1) and binary (0 or 1) prediction outcomes were used. In general, using continuous prediction output resulted in higher performance metrics than binary ones. AUCs for models ranged from 0.561 to 0.731, with generally increasing performance at moments later in life. Precision, AUC and balanced accuracy values improved significantly for the naive Bayes and multiple logistic regression ensembles in at least one data set, although performance metrics did remain low overall. The multiple logistic regression ensemble method resulted in equal or better precision, AUC, balanced accuracy and proportion of animals surviving on all datasets and was significantly different from the other ensembles in three out of five moments. The random forest ensemble method resulted in the least significant improvement over the individual methods.

Performance and Return to Sport After Anterior Cruciate Ligament Reconstruction in Professional Baseball Players.

Background:Anterior cruciate ligament reconstruction (ACLR) is the gold standard treatment for ACL tears to allow baseball players to return to sport (RTS). The optimal graft type and femoral tunnel drilling technique are currently unknown.Hypothesis:There is a high rate of RTS in professional baseball players after ACLR, with no significant difference in RTS rates or performance between cases and controls or between graft types or femoral drilling techniques.Study Design:Cohort study; Level of evidence, 3.Methods:All professional baseball players who underwent ACLR between 2010 and 2015 were included. Demographic and performance data (pre- and postoperative) for each player were recorded. Performance metrics were then compared between cases and matched controls.Results:A total of 124 players (mean age, 23.7 ± 4.1 years; 83% minor league players) underwent ACLR. Of these, 80% returned to sport (73% to the same or higher level) at a mean 310 ± 109 days overall and 333 ± 126 days at the same or higher level. The most common graft type was an ipsilateral bone–patellar tendon–bone (BTB) autograft (n = 87; 70%). A total of 91 players underwent concomitant meniscal debridement or repair. No significant difference in any of the primary performance metrics existed from before to after ACLR. Compared with matched controls, no significant difference existed in RTS rates or any performance metrics after ACLR. No significant difference existed in RTS rates or primary performance outcome measures between graft types or femoral drilling techniques.Conclusion:The RTS rate for professional baseball players after ACLR was 80%. No significant difference in performance metrics existed between BTB and hamstring autografts or between femoral drilling techniques. Furthermore, no significant difference in performance or RTS rates existed between cases and matched controls. Femoral drilling technique and graft type did not affect performance and RTS rates in professional baseball players after ACLR.

Do Outcomes or Subsequent Injuries Differ After Ulnar Collateral Ligament Reconstruction With Palmaris Versus Hamstring Autograft?

Background: Ulnar collateral ligament reconstruction (UCLR) is a successful procedure in professional baseball players. It is unclear whether graft choice affects results. Purpose: Determine performance and rate of return to sport (RTS) in professional baseball players after UCLR and compare performance and RTS rate, as well as injury rates, between players who underwent UCLR with hamstring versus palmaris autograft. Hypothesis: A high RTS rate exists in professional baseball players after UCLR, with no significant difference in injury rates, RTS rates, or performance specifically related to primary outcome performance variables—WHIP ([walks + hits]/innings pitched), fielding independent pitching (FIP), and wins above replacement (WAR)—between those who undergo UCLR with palmaris versus hamstring autograft. Study Design: Cohort study; Level of evidence, 3. Methods: All professional baseball players who underwent UCLR with hamstring autograft between 2010 and 2015 were included. Surgical details were gathered from operative reports. Players with hamstring UCLR were compared with a matched control group of players who underwent UCLR with palmaris autograft. Results: Overall, 195 players underwent UCLR with hamstring autograft. No differences in RTS rates or timing to RTS were found between the hamstring and palmaris groups. Significantly more subsequent injuries to the contralateral lower extremity were seen in the hamstring group versus the palmaris group (25 vs 13, respectively) (P = .040). More subsequent injuries to the upper extremity were found in the palmaris group versus the hamstring group (73 vs 55, respectively), although this difference was not significant (P = .052). No consistent differences in performance metrics upon RTS existed between hamstring and palmaris groups, although both groups significantly declined in many performance metrics after surgery. Both hamstring and palmaris groups showed a decline postoperatively in WAR (0.86 vs 0.35 and 1.23 vs 0.34, respectively) and WHIP (1.33 vs 1.44 and 1.36 vs 1.51, respectively); FIP did not decline (4.56 vs 5.27 and 4.51 vs 4.53, respectively). No significant difference in WAR, WHIP, or FIP existed between groups postoperatively. Conclusion: Baseball players who underwent UCLR with hamstring autograft were more likely to sustain a subsequent lower extremity injury, whereas those who underwent UCLR with palmaris autograft had a trend toward sustaining more upper extremity injuries. No difference in performance or RTS rates existed between groups. Both groups significantly declined in WAR and WHIP after UCLR.

How Much Practice Is Required to Reduce Performance Variability in a Virtual Reality Mining Simulator?

Virtual reality allows researchers to explore training scenarios that are not feasible or are potentially risky to recreate in the real world. The aim of this research was to examine whether using a tutorial session prior to using the mining simulator could adequately reduce the performance variability and increase the consistency of participant performance metrics. Eighteen participants were randomly assigned to a tutorial or a non-tutorial group. The tutorial group completed a five-minute tutorial that introduced them to the basics of the machine and virtual reality environment. All participants then completed five sessions in the simulator lasting five minutes each. Personality scores were recorded and participants answered questions to test their situational awareness after each session. Performance metrics such as number of collisions and perception response time were recorded by the simulator. A Wilcoxon signed rank test was used to determine at what point a significant difference in performance metrics was apparent across the five sessions. A mixed effects multilevel regression was done to evaluate the change in variability across time. There were no significant correlations between the personality questionnaire scores and the number of collisions or the perception response time. Both groups demonstrated high standard deviation scores for collisions and perception response time, but the tutorial group had decreasing variability across time. Both groups began to exhibit more consistent scores in the simulator after 10 min of use. Situational awareness questions require some refinement prior to further testing.

Side of Hamstring Harvest Does Not Affect Performance, Return-to-Sport Rate, or Future Hamstring Injuries After Ulnar Collateral Ligament Reconstruction Among Professional Baseball Pitchers

Background: Ulnar collateral ligament reconstruction (UCLR) is a successful procedure among professional baseball pitchers. It is unclear if hamstring tendon harvest side for UCLR affects the outcome or alters the risk for subsequent hamstring injury. Hypothesis: Players with prior UCLR with ipsilateral (drive leg) hamstring autograft will have the same return-to-sport (RTS) rate and performance upon RTS but a higher number of subsequent lower extremity injuries than those with contralateral (landing leg) hamstring autograft. Study Design: Cohort study; Level of evidence, 3. Methods: All players between 2010 and 2015 who underwent UCLR with hamstring autograft were included. Surgical details of their procedures were recorded from operative reports. Outcomes for UCLR with hamstring autograft harvested from the drive leg were compared with UCLR with the graft harvested from the landing leg. Results: Overall, 191 players underwent UCLR with hamstring autograft (drive leg, n = 58, 30%; landing leg, n = 133, 70%). The docking technique was more common in the drive leg group, while the figure-of-8 technique was more common in the landing leg group (P > .001). More patients in the landing leg group underwent concomitant treatment of the ulnar nerve than the drive leg group (P < .001). No difference existed in RTS rates or timing of RTS between groups. No differences in subsequent ipsilateral or contralateral hamstring injuries occurred between players who underwent UCLR with hamstring autograft from the drive leg or the landing leg (P≥ .999 and P = .460, respectively). No difference in overall upper or lower extremity injury rates existed between groups (all P > .05), and no difference in performance metrics existed between groups upon RTS. Conclusion: No difference in RTS rate, performance upon RTS, or subsequent injury rates (hamstring, lower extremity, or upper extremity) existed between players who underwent UCLR with hamstring autograft whether the graft came from the drive or the landing leg.

Comparison of attraction, entrance and passage of downstream migrant American eels (Anguilla rostrata) through airlift and siphon deep entrance bypass systems

Downstream migrating anguillid eels face many barriers including turbines and pumps at impoundments for water abstraction, power generation and water level control, when attempting to exit the freshwater catchment to reach spawning grounds. Multiple eel species worldwide are facing different levels of endangerment and alleviating the impacts of barriers to migration is essential to allow completion of the life cycle. Deep bypass systems with entrances located near the riverbed hold some promise for increased effectiveness compared to traditional downstream guidance and bypass facilities with entrances near the surface, as eels typically occupy the bottom of the water column. Here we evaluate two deep entrance bypass designs; an airlift (the Conte Airlift) and a conventional gravity siphon of the same entrance dimensions. Tests were performed using migratory silver-phase American eels (Anguilla rostrata), at night, in a simulated forebay environment. Passage performance was monitored over a 3 h test period using both PIT (passive integrated transponder) tag and video recording equipment. Entrance velocity was fixed at 1.2 m s−1 in each of 8 test runs with cohort size fixed in six runs at 14 and in two runs at 42. Test eels readily located, entered and passed both bypass designs. Differences in performance metrics between the airlift and siphon were not statistically significant (P > 0.05) with linked mean values of 74.5%, 90.5% and 100%, respectively. Eel length did not affect passage speed (P > 0.05) or slip ratio, i.e., the measured eel velocity relative to fluid velocity. The slip ratio was, however, greater in the siphon than in the airlift (P < 0.01) within identical vertical upflow sections of the test equipment. Siphon slip ratios in the upflow vertical section were comparable to those established for the horizontal and downflow sections. Fish density did not affect attraction and passage through the airlift or siphon. No mortality or signs of injury were observed on any of the test eels through a 48 h post-test observation period. Both airlift and siphon downstream bypass systems show promise as effective technologies for protection of downstream migrating eels at a variety of water diversion or hydroelectric sites that pose threats of impingement, entrainment, and turbine mortality.

Assessment of public charging infrastructure push and pull rollout strategies: The case of the Netherlands

Over recent years, numbers of electric vehicles (EVs) have shown a strong growth and sales are projected to continue to grow. For facilitating charging possibilities for EVs typically two rollout strategies have been applied; demand-driven and strategic rollout. This study focuses on determining the differences in performance metrics of the two rollout strategies by first defining key performance metrics. Thereafter, the root causes of performance differences between the two rollout strategies are investigated. This study analyzes charging data of 1,007,137 transactions on 1742 different CPs by use of 53,850 unique charging cards. This research concludes that demand-driven CPs outperform strategic CPs on weekly energy transfer and connection duration, while strategic CPs outperform their demand-driven counterparts on charging time ratio. Regarding users facilitated, there is a significant change in performance after massive EV-uptake. The root cause analysis shows effects of EV uptake and user type composition on the differences in performance metrics. This research concludes with implications for policy makers regarding an optimal portfolio of rollout strategies.