Evaluating the predictive performance of empirical estimators of natural mortality rate using information on over 200 fish species

Many methods have been developed in the last 70 years to predict the natural mortality rate, M, of a stock based on empirical evidence from comparative life history studies. These indirect or empirical methods are used in most stock assessments to (i) obtain estimates of M in the absence of direct information, (ii) check on the reasonableness of a direct estimate of M, (iii) examine the range of plausible M estimates for the stock under consideration, and (iv) define prior distributions for Bayesian analyses. The two most cited empirical methods have appeared in the literature over 2500 times to date. Despite the importance of these methods, there is no consensus in the literature on how well these methods work in terms of prediction error or how their performance may be ranked. We evaluate estimators based on various combinations of maximum age (t(max)), growth parameters, and water temperature by seeing how well they reproduce \u3e200 independent, direct estimates of M. We use tenfold cross-validation to estimate the prediction error of the estimators and to rank their performance. With updated and carefully reviewed data, we conclude that a t(max)-based estimator performs the best among all estimators evaluated. The t(max)-based estimators in turn perform better than the Alverson-Carney method based on t(max) and the von Bertalanffy K coefficient, Pauly\u27s method based on growth parameters and water temperature and methods based just on K. It is possible to combine two independent methods by computing a weighted mean but the improvement over the t(max)-based methods is slight. Based on cross-validation prediction error, model residual patterns, model parsimony, and biological considerations, we recommend the use of a t(max)-based estimator (M = 4.899t(max)(-0.916), prediction error = 0.32) when possible and a growth-based method (M = 4.118K(0.73)L(infinity)(-0.33), prediction error = 0.6) otherwise

The logic of comparative life history studies for estimating key parameters, with a focus on natural mortality rate

There are a number of key parameters in population dynamics that are difficult to estimate, such as natural mortality rate, intrinsic rate of population growth, and stock-recruitment relationships. Often, these parameters of a stock are, or can be, estimated indirectly on the basis of comparative life history studies. That is, the relationship between a difficult to estimate parameter and life history correlates is examined over a wide variety of species in order to develop predictive equations. The form of these equations may be derived from life history theory or simply be suggested by exploratory data analysis. Similarly, population characteristics such as potential yield can be estimated by making use of a relationship between the population parameter and bio-chemico-physical characteristics of the ecosystem. Surprisingly, little work has been done to evaluate how well these indirect estimators work and, in fact, there is little guidance on how to conduct comparative life history studies and how to evaluate them. We consider five issues arising in such studies: (i) the parameters of interest may be ill-defined idealizations of the real world, (ii) true values of the parameters are not known for any species, (iii) selecting data based on the quality of the estimates can introduce a host of problems, (iv) the estimates that are available for comparison constitute a non-random sample of species from an ill-defined population of species of interest, and (v) the hierarchical nature of the data (e.g. stocks within species within genera within families, etc., with multiple observations at each level) warrants consideration. We discuss how these issues can be handled and how they shape the kinds of questions that can be asked of a database of life history studies

Current state and future prospects of artificial intelligence in ophthalmology: a review

Artificial intelligence (AI) has emerged as a major frontier in computer science research. Although AI has broad application across many medical fields, it will have particular utility in ophthalmology and will dramatically change the diagnostic and treatment pathways for many eye conditions such as corneal ectasias, glaucoma, age-related macular degeneration and diabetic retinopathy. However, given that AI has primarily been driven as a computer science, its concepts and terminology are unfamiliar to many medical professionals. Important key terms such as machine learning and deep learning are often misunderstood and incorrectly used interchangeably. This article presents an overview of AI and new developments relevant to ophthalmology

Perfectionism and eating disorder symptoms in female university students: The central role of perfectionistic self-presentation

Purpose: Numerous studies have found perfectionism to show positive relations with eating disorder symptoms, but so far no study has examined whether perfectionistic self-presentation can explain these relations or whether the relations are the same for different eating disorder symptom groups. Methods: A sample of 393 female university students completed self-report measures of perfectionism (self-oriented perfectionism, socially prescribed perfectionism), perfectionistic self-presentation (perfectionistic self-promotion, nondisplay of imperfection, nondisclosure of imperfection), and three eating disorder symptom groups (dieting, bulimia, oral control). In addition, students reported their weight and height so their body mass index (BMI) could be computed. Results: Results of multiple regression analyses controlling for BMI indicated that socially prescribed perfectionism positively predicted all three symptom groups, whereas self-oriented perfectionism positively predicted dieting only. Moreover, perfectionistic self-presentation explained the positive relations that perfectionism showed with dieting and oral control, but not with bulimia. Further analyses indicated that all three aspects of perfectionistic self-presentation positively predicted dieting, whereas only nondisclosure of imperfection positively predicted bulimia and oral control. Overall, perfectionistic self-presentation explained 10.4-23.5% of variance in eating disorder symptoms, whereas perfectionism explained 7.9-12.1%. Conclusions: The findings suggest that perfectionistic self-presentation explains why perfectionistic women show higher levels of eating disorder symptoms, particularly dieting. Thus perfectionistic self-presentation appears to play a central role in the relations of perfectionism and disordered eating and may warrant closer attention in theory, research, and treatment of eating and weight disorders

Velocity quantization approach of the one-dimensional dissipative harmonic oscillator

Given a constant of motion for the one-dimensional harmonic oscillator with linear dissipation in the velocity, the problem to get the Hamiltonian for this system is pointed out, and the quantization up to second order in the perturbation approach is used to determine the modification on the eigenvalues when dissipation is taken into consideration. This quantization is realized using the constant of motion instead of the Hamiltonian.Comment: 10 pages, 2 figure

A qualitative study of unmet needs and interactions with primary care among cancer survivors

INTRODUCTION: Despite increasing numbers, there is little research investigating the long-term needs of cancer survivors. The aim of this study is to explore the experiences of individuals who have survived at least 5 years following a cancer diagnosis, and to describe perceived unmet needs and interactions with primary care. METHODS: Forty long-term survivors of breast, colorectal and prostate cancer were purposively selected for an in-depth qualitative study. We aimed for a maximum variation sample according to cancer site, gender, time since diagnosis, cancer needs, anxiety and depression. Interviews were audio recorded and transcribed verbatim. Transcripts were coded thematically using a grounded theory approach. RESULTS: Analysis of the interview data is presented in four subthemes: the role they perceived for the general practitioner (GP), unmet needs, reasons for not using primary care for needs they perceived as cancer related, and ongoing care for cancer-related issues. The majority of cancer survivors did not see a role for their GP in their long-term care related to their cancer diagnosis as most considered that they did not need active follow-up, but some expressed a need for psychological services and information on possible long-term effects. Cancer survivors cited three main reasons for not using GP services in relation to their cancer diagnosis: GPs were seen as non-experts in cancer; they were perceived as too busy; and a lack of continuity within primary care made it difficult to talk about long-term issues. There was a wide variation in schedules and notification of PSA tests among the prostate cancer survivors. DISCUSSION: The results from this project suggest that some cancer survivors have specific emotional and physical needs that could benefit from input from their primary care team, but not all cancer survivors look to their GP for their long-term cancer-related care. Better information care planning is required from specialists in order to identify those who would benefit mos

Biallelic CPAMD8 variants are a frequent cause of childhood and juvenile open-angle glaucoma

Purpose: Developmental abnormalities of the ocular anterior segment in some cases can lead to ocular hypertension and glaucoma. CPAMD8 is a gene of unknown function recently associated with ocular anterior segment dysgenesis, myopia, and ectopia lentis. We sought to assess the contribution of biallelic CPAMD8 variants to childhood and juvenile open-angle glaucoma. Design: Retrospective, multicenter case series. Participants: A total of 268 probands and their relatives with a diagnosis of childhood or juvenile open-angle glaucoma. Methods: Patients underwent a comprehensive ophthalmic assessment, with DNA from patients and their relatives subjected to genome, exome, or capillary sequencing. CPAMD8 RNA expression analysis was performed on tissues dissected from cadaveric human eyes. Main outcome measures: Diagnostic yield within a cohort of childhood and juvenile open-angle glaucoma, prevalence and risk of ophthalmic phenotypes, and relative expression of CPAMD8 in the human eye. Results: We identified rare (allele frequency -5) biallelic CPAMD8 variants in 5.7% (5/88) of probands with childhood glaucoma and 2.1% (2/96) of probands with juvenile open-angle glaucoma. When including family members, we identified 11 individuals with biallelic variants in CPAMD8 from 7 unrelated families. Nine of these individuals were diagnosed with glaucoma (9/11, 81.8%), with a mean age at diagnosis of 9.22±14.89 years, and all individuals with glaucoma required 1 or more incisional procedures to control high intraocular pressure. Iris abnormalities were observed in 9 of 11 individuals, cataract was observed in 8 of 11 individuals (72.7%), and retinal detachment was observed in 3 of 11 individuals (27.3%). CPAMD8 expression was highest in neural crest-derived tissues of the adult anterior segment, suggesting that CPAMD8 variation may cause malformation or obstruction of key drainage structures. Conclusions: Biallelic CPAMD8 variation was associated with a highly heterogeneous phenotype and in our cohorts was the second most common inherited cause of childhood glaucoma after CYP1B1 and juvenile open-angle glaucoma after MYOC. CPAMD8 sequencing should be considered in the investigation of both childhood and juvenile open-angle glaucoma, particularly when associated with iris abnormalities, cataract, or retinal detachment

The role of motion analysis in elite soccer

The optimal physical preparation of elite soccer (association football) players has become an indispensable part of the professional game especially due to the increased physical demands of match-play. The monitoring of players’ work-rate profiles during competition is now feasible through computer-aided motion analysis. Traditional methods of motion analysis were extremely labour intensive and were largely restricted to university- based research projects. Recent technological developments have meant that sophisticated systems, capable of quickly recording and processing the data of all players’ physical contributions throughout an entire match, are now being used in elite club environments. In recognition of the important role motion analysis now plays as a tool for measuring the physical performance of soccer players, this review critically appraises various motion analysis methods currently employed in elite soccer and explores research conducted using these methods. This review therefore aims to increase the awareness of both practitioners and researchers of the various motion analysis systems available, identify practical implications of the established body of knowledge, while highlighting areas that require further exploration