Models which define fitness in terms of per capita rate of increase of phenotypes are used to analyse patterns of individual growth. It is shown that sigmoid growth curves are an optimal strategy (i.e. maximize fitness) if (Assumption 1a) mortality decreases with body size; (2a) mortality is a convex function of specific growth rate, viewed from above; (3) there is a constraint on growth rate, which is attained in the first phase of growth. If the constraint is not attained then size should increase at a progressively reducing rate. These predictions are biologically plausible. Catch-up growth, for retarded individuals, is generally not an optimal strategy though in special cases (e.g. seasonal breeding) it might be. Growth may be advantageous after first breeding if birth rate is a convex function of G (the fraction of production devoted to growth) viewed from above (Assumption 5a), or if mortality rate is a convex function of G, viewed from above (Assumption 6c). If assumptions 5a and 6c are both false, growth should cease at the age of first reproduction. These predictions could be used to evaluate the incidence of indeterminate versus determinate growth in the animal kingdom though the data currently available do not allow quantitative tests. In animals with invariant adult size a method is given which allows one to calculate whether an increase in body size is favoured given that fecundity and developmental time are thereby increased.
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http://dx.doi.org/10.1016/s0022-5193(85)80022-9 | DOI Listing |
Arq Gastroenterol
January 2025
Escola Bahiana de Medicina e Saúde Pública, Salvador, BA, Brasil.
Background: To investigate the association between metabolic dysfunction-associated steatotic pancreas disease (MASPD) and insulin resistance (IR).
Methods: This cross-sectional study involved 157 participants diagnosed with MASPD based on ultrasonography criteria. Baseline demographic data were collected, including age, gender, and body mass index.
PLoS One
January 2025
Department of Basic Sciences, Preparatory Year, King Faisal University, Al-Ahsa, Saudi Arabia.
Our study presents a novel orbit with s-convexity, for illustration of the behavior shift in the fractals. We provide a theorem to demonstrate the escape criterion for transcendental cosine functions of the type Tα,β(u) = cos(um)+αu + β, for [Formula: see text] and m ≥ 2. We also demonstrate the impact of the parameters on the formatted fractals with numerical examples and graphical illustrations using the MATHEMATICA software, algorithm, and colormap.
View Article and Find Full Text PDFInsects
December 2024
Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 11/a, 43124 Parma, Italy.
Human-driven changes in land cover and use can significantly impact species ants community structures, often leading to a decline in taxonomic diversity or species homogenization. Ant morphology, used as a proxy for ecological function, offers a valuable framework for understanding the effects of anthropogenic disturbances on ant diversity. This study explored the morphological diversity of ant assemblages in agricultural ecosystems and secondary forests in Italy and the Brazilian Amazon, analyzing how these communities are structured and adapted to different environments.
View Article and Find Full Text PDFFluids Barriers CNS
December 2024
Department of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.
Background: Disproportionately enlarged subarachnoid space hydrocephalus (DESH) is one of the neuroradiological characteristics of idiopathic normal pressure hydrocephalus (iNPH), which makes statistical analyses of brain images difficult. This study aimed to develop and validate methods of accurate brain segmentation and spatial normalisation in patients with DESH by using the Computational Anatomy Toolbox (CAT12).
Methods: Two hundred ninety-eight iNPH patients with DESH and 25 healthy controls (HCs) who underwent cranial MRI were enrolled in this study.
Neural Netw
December 2024
School of Mathematics and Statistics, Yili Normal University, Yining 835000, China.
In this paper, a recurrent neural network is proposed for distributed nonconvex optimization subject to globally coupled (in)equality constraints and local bound constraints. Two distributed optimization models, including a resource allocation problem and a consensus-constrained optimization problem, are established, where the objective functions are not necessarily convex, or the constraints do not guarantee a convex feasible set. To handle the nonconvexity, an augmented Lagrangian function is designed, based on which a recurrent neural network is developed for solving the optimization models in a distributed manner, and the convergence to a local optimal solution is proven.
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