An Evaluation of Pay Equity Reports at Five Canadian Universities

This paper reviews five reports measuring discrimination in salaries between males and females at Canadian universities. All find some discrimination (3% to 8%), a result in accord with published research on the same topic. However, the approaches taken are quite different, often reflecting controversial decisions over which variables would be included to explain salary differentials. We examine the strengths and weaknesses of these reports. In particular, the focus on single equation models is a problem since some of the controversial variables, which may be biased by discrimination, also contain some information which explains legitimate differences in salaries. Our review suggests that many of the models are probably misspecified. We conclude with a call for universities to collect the information which is required to complete these studies expeditiously and accurately.Ce article fait l'examen de cinq rapports portant sur l'équité salariale dans les universités canadiennes. Tous les rapports documentent l'existence d'écarts salariaux (entre 3 et 8%) qui reflètent les écarts généralement recensés dans les écrits sur le sujet. Cependant, ces résultats reposent sur des approches méthodologiques très différentes qui témoignent de décisions controversies ayant trait à la sélection des variables pouvant expliquer les écarts salariaux. L'étude analyse les forces et les faiblesses des approches utilisées. En particulier, le choix de modèles à une seule équation pose problème puisque certaines variables sélectionnées peuvent à la fois décrire des différences salariales discriminatoires et contenir de l'information permettant d'expliquer des écarts légitimes de salaires. Notre analyse suggère donc que plusieurs modèles ne permettent pas d'expliquer adéquatement les écarts salariaux et que les universités concernées devraient rapidement faire la collecte d'informations supplémentaires pertinentes pour compléter les études déjà réalisées

Penrose Diagram for a Transient Black Hole

A Penrose diagram is constructed for a spatially coherent black hole that smoothly begins an accretion, then excretes symmetrically as measured by a distant observer, with the initial and final states described by a metric of Minkowski form. Coordinate curves on the diagram are computationally derived. Causal relationships between space-time regions are briefly discussed. The life cycle of the black hole demonstrably leaves asymptotic observers in an unaltered Minkowski space-time of uniform conformal scale.Comment: 14 pages, 9 figures, spelling correction

Epidemiology of Knee Sprains in Youth, High School, and Collegiate American Football Players

Context: Assessment of health-related quality of life (HRQOL) after injury is important. Differences in HRQOL between nonathletes and athletes and between injured and uninjured athletes have been demonstrated; however, the evidence has not been synthesized. Objective: To answer the following questions: (1) Does HRQOL differ among adolescent and collegiate athletes and nonathletes? (2) Does HRQOL differ between injured adolescent and collegiate athletes or between athletes with a history of injury and uninjured athletes or those without a history of injury? Data Sources: We systematically searched CINAHL, MEDLINE, SPORTDiscus, and PubMed. A hand search of references was also conducted. Study Selection: Studies were included if they used generic instruments to compare HRQOL outcomes between athletes and nonathletes and between uninjured and injured athletes. Studies were excluded if they did not use a generic instrument, pertained to instrument development, or included retired athletes or athletes with a chronic disease. Data Extraction: We assessed study quality using the modified Downs and Black Index Tool. Bias-corrected Hedges g effect sizes and 95% confidence intervals (CIs) were calculated. The Strength of Recommendation Taxonomy (SORT) was used to determine the overall strength of the recommendation. A random-effects meta-analysis was performed for all studies using the composite or total score. Data Synthesis: Eight studies with modified Downs and Black scores ranging from 70.6% to 88.4% were included. For question 1, the overall random-effects meta-analysis was weak (effect size = 0.27, 95% confidence interval = 0.14, 0.40; P \u3c .001). For question 2, the overall random-effects meta-analysis was moderate (effect size = 0.68, 95% confidence interval = 0.42, 0.95; P \u3c .001). Conclusions: Grade A evidence indicates that athletes reported better HRQOL than nonathletes and that uninjured athletes reported better HRQOL than injured athletes. However, the overall effect for question 1 was weak, suggesting that the differences between athletes and nonathletes may not be clinically meaningful. Clinicians should monitor HRQOL after injury to ensure that all dimensions of health are appropriately treated

Microwave Components with MEMS Switches

RF MEMS switches with metal-metal contacts are being developed for microwave applications where broadband, high linearity performance is required. These switches provide less than 0.2 dB insertion loss through 40 GHz. This paper describes the integration of these switches into selected microwave components such as reconfigurable antenna elements, tunable filters, switched delay lines, and SPDT switches. Microwave and millimeter wave measured results from these circuits are presented

Normative Functional Performance Values in High School Athletes: The Functional Pre-Participation Evaluation Project

Context: The fourth edition of the Preparticipation Physical Evaluation recommends functional testing for the musculoskeletal portion of the examination; however, normative data across sex and grade level are limited. Establishing normative data can provide clinicians reference points with which to compare their patients, potentially aiding in the development of future injury-risk assessments and injury-mitigation programs. Objective: To establish normative functional performance and limb-symmetry data for high school-aged male and female athletes in the United States. Design: Cross-sectional study. Setting: Athletic training facilities and gymnasiums across the United States. Patients or Other Participants: A total of 3951 male and female athletes who participated on high school-sponsored basketball, football, lacrosse, or soccer teams enrolled in this nationwide study. Main Outcome Measure(s): Functional performance testing consisted of 3 evaluations. Ankle-joint range of motion, balance, and lower extremity muscular power and landing control were assessed via the weight-bearing ankle-dorsiflexion–lunge, single-legged anterior-reach, and anterior single-legged hop-for-distance (SLHOP) tests, respectively. We used 2-way analyses of variance and χ2 analyses to examine the effects of sex and grade level on ankle-dorsiflexion–lunge, single-legged anterior-reach, and SLHOP test performance and symmetry. Results: The SLHOP performance differed between sexes (males = 187.8% ± 33.1% of limb length, females = 157.5% ± 27.8% of limb length; t = 30.3, P \u3c .001). A Cohen d value of 0.97 indicated a large effect of sex on SLHOP performance. We observed differences for SLHOP and ankle-dorsiflexion–lunge performance among grade levels, but these differences were not clinically meaningful. Conclusions: We demonstrated differences in normative data for lower extremity functional performance during preparticipation physical evaluations across sex and grade levels. The results of this study will allow clinicians to compare sex- and grade-specific functional performances and implement approaches for preventing musculoskeletal injuries in high school-aged athletes

Mine yOur owN Anatomy: Revisiting Medical Image Segmentation with Extremely Limited Labels

Recent studies on contrastive learning have achieved remarkable performance solely by leveraging few labels in the context of medical image segmentation. Existing methods mainly focus on instance discrimination and invariant mapping. However, they face three common pitfalls: (1) tailness: medical image data usually follows an implicit long-tail class distribution. Blindly leveraging all pixels in training hence can lead to the data imbalance issues, and cause deteriorated performance; (2) consistency: it remains unclear whether a segmentation model has learned meaningful and yet consistent anatomical features due to the intra-class variations between different anatomical features; and (3) diversity: the intra-slice correlations within the entire dataset have received significantly less attention. This motivates us to seek a principled approach for strategically making use of the dataset itself to discover similar yet distinct samples from different anatomical views. In this paper, we introduce a novel semi-supervised 2D medical image segmentation framework termed Mine yOur owN Anatomy (MONA), and make three contributions. First, prior work argues that every pixel equally matters to the model training; we observe empirically that this alone is unlikely to define meaningful anatomical features, mainly due to lacking the supervision signal. We show two simple solutions towards learning invariances - through the use of stronger data augmentations and nearest neighbors. Second, we construct a set of objectives that encourage the model to be capable of decomposing medical images into a collection of anatomical features in an unsupervised manner. Lastly, our extensive results on three benchmark datasets with different labeled settings validate the effectiveness of our proposed MONA which achieves new state-of-the-art under different labeled settings

Microbial Aerosols from Food Processing Waste Spray Fields

Federal legislation restricts the discharge of waste from various industrial processes into rivers, lakes, or other waters. For this reason disposal of wastewater by spraying onto cultivated, grassed, or forested lands has come into use. These waste disposal spray systems produce droplets of water containing suspended material that may become aerosolized as particles less than about 20 µ in diameter. Particles of this size will remain suspended in the atmosphere and will travel long distances downwind. The generation of such particles by commercial spray or sprinkler equipment may be presumed because regardless of the size distribution for water droplets leaving the sprinkler nozzle a number of particles of aerosol size will develop through rapid evaporation. Solid materials, including microorganisms, suspended in the water become the nuclei of the aerosol particles. Recent reviews have been published regarding the aerosolization of microorganisms in sprays resulting from the treatment and disposal of wastewater from domestic waste. Microbial aerosol particles were sampled up to 1.2 km downwind of the spray source. Katzenelson and Teltch reported aerosolized coliforms short distances downwind of spray fields for disposal of wastewater containing raw domestic waste and for disposal of effluent from a wastewater settling pond. In this report, studies were made of microbial aerosols downwind from spray fields for the disposal of potato processing wastewater

Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective

For medical image segmentation, contrastive learning is the dominant practice to improve the quality of visual representations by contrasting semantically similar and dissimilar pairs of samples. This is enabled by the observation that without accessing ground truth label, negative examples with truly dissimilar anatomical features, if sampled, can significantly improve the performance. In reality, however, these samples may come from similar anatomical features and the models may struggle to distinguish the minority tail-class samples, making the tail classes more prone to misclassification, both of which typically lead to model collapse. In this paper, we propose ARCO, a semi-supervised contrastive learning (CL) framework with stratified group sampling theory in medical image segmentation. In particular, we first propose building ARCO through the concept of variance-reduced estimation, and show that certain variance-reduction techniques are particularly beneficial in medical image segmentation tasks with extremely limited labels. Furthermore, we theoretically prove these sampling techniques are universal in variance reduction. Finally, we experimentally validate our approaches on three benchmark datasets with different label settings, and our methods consistently outperform state-of-the-art semi-supervised methods. Additionally, we augment the CL frameworks with these sampling techniques and demonstrate significant gains over previous methods. We believe our work is an important step towards semi-supervised medical image segmentation by quantifying the limitation of current self-supervision objectives for accomplishing medical image analysis tasks

The partially alternating ternary sum in an associative dialgebra

The alternating ternary sum in an associative algebra, $abc - acb - bac + bca + cab - cba$, gives rise to the partially alternating ternary sum in an associative dialgebra with products $\dashv$ and $\vdash$ by making the argument $a$ the center of each term: $a \dashv b \dashv c - a \dashv c \dashv b - b \vdash a \dashv c + c \vdash a \dashv b + b \vdash c \vdash a - c \vdash b \vdash a$. We use computer algebra to determine the polynomial identities in degree $\le 9$ satisfied by this new trilinear operation. In degrees 3 and 5 we obtain $[a,b,c] + [a,c,b] \equiv 0$ and $[a,[b,c,d],e] + [a,[c,b,d],e] \equiv 0$; these identities define a new variety of partially alternating ternary algebras. We show that there is a 49-dimensional space of multilinear identities in degree 7, and we find equivalent nonlinear identities. We use the representation theory of the symmetric group to show that there are no new identities in degree 9.Comment: 14 page