Dynamical analysis of a diffusive population-toxicant model with toxicant-taxis in polluted aquatic environments.

This paper deals with a diffusive population-toxicant model in polluted aquatic environments, with a toxicant-taxis term describing a toxicant-induced behavior change, that is, the population tends to move away from locations with high-level toxicants. The global existence of solutions is established by the techniques of the semigroup estimation and Moser iteration. Based on a detailed study on the properties of the principal eigenvalue for non-self-adjoint eigenvalue problems, we investigated the local and global stability of the toxin-only steady-state solution and the existence of positive steady state, which yields sufficient conditions that lead to population persistence or extinction. Finally, by numerical simulations, we studied the effects of some key parameters, such as toxicant-taxis coefficient, advection rate, and effect coefficient of the toxicant on population growth, on population persistence. Both numerical and analytical results show that a weak chemotaxis effect, a small advection rate of the population, and a weak effect of the toxicant on population growth are favorable for population persistence.

A nonautonomous model for the interaction between a size-structured consumer and an unstructured resource.

In this paper, we propose and analyze a nonautonomous model that describes the dynamics of a size-structured consumer interacting with an unstructured resource. We prove the existence and uniqueness of the solution of the model using the monotone method based on a comparison principle. We derive conditions on the model parameters that result in persistence and extinction of the population via the upper-lower solution technique. We verify and complement the theoretical results through numerical simulations.

The correlation analysis between organizational justice, knowledge-hiding behaviour and Nurses' innovation ability: A cross-sectional study.

AIM: The aim of the study was to analyse the correlations among organizational justice, knowledge-hiding behaviour and nurses' innovation ability. DESIGN: A descriptive and cross-sectional design and the data were collected using questionnaires. METHODS: Demographic information, professional data, innovation capacity scales, knowledge-hiding scales and organizational justice scales were used in this study. Using descriptive statistics, t-tests, one-way analysis of variance and Pearson's or Spearman's correlation analyses, we compared the differences and examined the correlations between participants' demographic and innovation capacity scales, and knowledge-hiding scales and organizational fairness scales. RESULTS: We received 1486 valid responses, with an effective response rate of 96.68%. We found team role, nursing age, number of training, literature-reading habits, organizational justice, information justice, fair distribution and deaf knowledge-hiding as the influencing factors of nurses' innovation. Nurses' sense of organizational fairness negatively correlated with knowledge concealment and positively correlated with innovation ability. Moreover, knowledge hiding negatively correlated with nurses' innovation ability. Furthermore, knowledge-hiding plays a partial intermediary role between organizational fairness and nurses' innovation ability.

A Stage-Structured Continuous-/Discrete-Time Population Model: Persistence and Spatial Spread.

Population persistence and spatial propagation and their dependence on demography and dispersal are of great importance in spatial ecology. Many species with highly structured life cycles invade new habitats through the dispersal of organisms in their early life stages (e.g., seeds, larvae, etc.). We develop a stage-structured continuous/discrete-time hybrid model to describe the spatiotemporal dynamics of such species, in which a reaction-diffusion equation describes the random movement of dispersing individuals, while two difference equations describe the demography of sedentary individuals. We obtain a formula for the spreading speed of the population in terms of model parameters. We show that the spreading speed can be characterized as the slowest wave speed of a class of traveling wave solutions. We provide an explicit formula for the critical domain size that separates population persistence from extinction. By comparing our stage-structured model with a physically unstructured model, we find that the structured model reduces to the unstructured one in some special cases. Accordingly, the results about the spreading speed and the critical domain size for the unstructured model represent some special cases of those for the structured one. This highlights the significance of including stage structure in studying the spatial dynamics of species with complex life cycles.

Polymers in Lithium-Sulfur Batteries.

Lithium-sulfur batteries (LSBs) hold great promise as one of the next-generation power supplies for portable electronics and electric vehicles due to their ultrahigh energy density, cost effectiveness, and environmental benignity. However, their practical application has been impeded owing to the electronic insulation of sulfur and its intermediates, serious shuttle effect, large volume variation, and uncontrollable formation of lithium dendrites. Over the past decades, many pioneering strategies have been developed to address these issues via improving electrodes, electrolytes, separators and binders. Remarkably, polymers can be readily applied to all these aspects due to their structural designability, functional versatility, superior chemical stability and processability. Moreover, their lightweight and rich resource characteristics enable the production of LSBs with high-volume energy density at low cost. Surprisingly, there have been few reviews on development of polymers in LSBs. Herein, breakthroughs and future perspectives of emerging polymers in LSBs are scrutinized. Significant attention is centered on recent implementation of polymers in each component of LSBs with an emphasis on intrinsic mechanisms underlying their specific functions. The review offers a comprehensive overview of state-of-the-art polymers for LSBs, provides in-depth insights into addressing key challenges, and affords important resources for researchers working on electrochemical energy systems.

Forecast of the COVID-19 trend in India: A simple modelling approach.

By February 2021, the overall impact of the COVID-19 pandemic in India had been relatively mild in terms of total reported cases and deaths. Surprisingly, the second wave in early April becomes devastating and attracts worldwide attention. Multiple factors (e.g., Delta variants with increased transmissibility) could have driven the rapid growth of the epidemic in India and led to a large number of deaths within a short period. We aim to reconstruct the transmission rate, estimate the infection fatality rate and forecast the epidemic size. We download the reported COVID-19 mortality data in India and formulate a simple mathematical model with a flexible transmission rate. We use iterated filtering to fit our model to deaths data. We forecast the infection attack rate in a month ahead. Our model simulation matched the reported deaths well and is reasonably close to the results of the serological study. We forecast that the infection attack rate (IAR) could have reached 43% by July 24, 2021, under the current trend. Our estimated infection fatality rate is about 0.07%. Under the current trend, the IAR will likely reach a level of 43% by July 24, 2021. Our estimated infection fatality rate appears unusually low, which could be due to a low case to infection ratio reported in previous study. Our approach is readily applicable in other countries and with other types of data (e.g., excess deaths).

Direct and indirect effects of toxins on competition dynamics of species in an aquatic environment.

When two competing species are simultaneously exposed in a polluted environment, one species may be more vulnerable to toxins than the other. To study the impact of environmental toxins on competition dynamics of two species, we develop a toxin-dependent competition model that incorporates both direct and indirect toxic effects on the species. The direct effects of toxins typically reduce population abundance by increasing mortality and reducing reproduction. However, the indirect effects, which are mediated through competitive interactions, may lead to counterintuitive effects. We investigate the toxin-dependent competition model and explore the impact of the interplay between environmental toxins and distinct toxic tolerance of two species on the competition outcomes. The results of theoretical analysis and numerical studies reveal that while high level of toxins is harmful to both species, possibly leading to extirpation of both species, intermediate level of toxins, plus different vulnerabilities of two species to toxins, affect competition outcomes in many counterintuitive ways. It turns out that sublethal toxins may boost coexistence of two species (hence keep species diversity in ecosystems) by reducing the abundance of the predominant species; sublethal toxins may overturn and exchange roles of winner and loser in competition; sublethal toxins may also induce different types of bistability of the competition dynamics, where the competition outcome is doomed to exclusion or coexistence, depending on initial population densities. The theory developed here provides a sound foundation for understanding competitive interactions between two species in a polluted aquatic environment.

PPARα Regulates the Proliferation of Human Glioma Cells through miR-214 and E2F2.

Peroxisome proliferator-activated receptor α (PPARα) is a member of the nuclear hormone receptor superfamily and functions as a transcription factor. Previous work showed that PPARα plays multiple roles in lipid metabolism in tissues such as cardiac and skeletal muscle, liver, and adipose tissue. Recent studies have discovered additional roles for PPARα in cell proliferation and metabolism, as well as tumor progression. PPARα is aberrantly expressed in various cancers, and activated PPARα inhibits the proliferation of some tumor cells. However, there have been no studies of PPARα in human gliomas. Here, we show that PPARα is expressed at lower levels in anaplastic gliomas and glioblastoma multiforme (GBM) tissue compared with low-grade gliomas tissue, and low expression is associated with poor patient prognosis. PPARα activates transcription of dynamin-3 opposite strand (DNMO3os), which encodes a cluster of miR-214, miR-199a-3p, and miR-199a-5p microRNAs. Of these, miR-214 is transcribed at particularly high levels. PPARα-induced miR-214 expression causes downregulation of its target E2F2. Finally, miR-214 overexpression inhibits glioma cell growth in vitro and in vivo by inducing cell cycle arrest in G0/G1. Collectively, these data uncover a novel role for a PPARα-miR-214-E2F2 pathway in controlling glioma cell proliferation.

Bifurcations and global dynamics in a toxin-dependent aquatic population model.

The study of effects of environmental toxins on ecosystems is of great interest from both environmental and conservation points of view. In this paper, we present a global stability and bifurcation analysis of a toxin-dependent aquatic population model. Our analytical and numerical results show that both the environmental toxin level and the depuration capability of the population significantly affect the population persistence. The model exhibits a multifarious array of dynamics. While low levels of external toxin allow population persistence and high levels of toxin lead to an extirpation, intermediate toxin concentrations can produce very rich dynamics, such as transient oscillations, hysteresis, heteroclinic orbits, and a codimension-two bifurcation. In particular, a regime of bistability exists where the population is doomed to extinction or survival, depending on initial state of the system. As a practical implication of our study, the toxic effects of methylmercury on rainbow trout are scrutinized. The theory developed here provides a sound theoretical foundation for understanding the population effects of toxicity.

Simultaneous removal of cadmium, zinc and manganese using electrocoagulation: Influence of operating parameters and electrolyte nature.

In the present study, the influence of operating parameters and electrolyte nature on the simultaneous removal of toxic metals (cadmium, zinc and manganese) from synthetic smelting wastewater by batch electrocoagulation was investigated. This wastewater contained high concentrations of anion-cation electrolytes. Results indicated that the efficiency of heavy metals removal can be enhanced by increasing the solution pH and current density. The Fe-Fe electrode combination is more effective than the other combinations (Al-Al, Al-Fe and Fe-Al). The interaction of heavy metal ions showed that the increase of initial Zn2+ concentration adversely affects on Cd2+ removal. In addition, the single chloride system exhibits the optimum removal efficiency on Mn2+. Single sulfate and binary anion systems exert a more positive effect on Cd2+ and Zn2+ removal because of the stronger charge neutralization and destabilization of iron hydroxide flocs. Increases of Ca2+ and Mg2+ ions exert a significant negative effect on metal removal. However, the addition of a small amount of sodium chloride into a high sulfate and hardness solution can accelerate the removal of heavy metals. Finally, the sludge samples generated from electrocoagulation were characterized by XRD and SEM-EDS analyses.

A toxin-mediated size-structured population model: Finite difference approximation and well-posedness.

The question of the effects of environmental toxins on ecological communities is of great interest from both environmental and conservational points of view. Mathematical models have been applied increasingly to predict the effects of toxins on a variety of ecological processes. Motivated by the fact that individuals with different sizes may have different sensitivities to toxins, we develop a toxin-mediated size-structured model which is given by a system of first order fully nonlinear partial differential equations (PDEs). It is very possible that this work represents the first derivation of a PDE model in the area of ecotoxicology. To solve the model, an explicit finite difference approximation to this PDE system is developed. Existence-uniqueness of the weak solution to the model is established and convergence of the finite difference approximation to this unique solution is proved. Numerical examples are provided by numerically solving the PDE model using the finite difference scheme.

Temperature- and Turbidity-Dependent Competitive Interactions Between Invasive Freshwater Mussels.

We develop a staged-structured population model that describes the competitive dynamics of two functionally similar, congeneric invasive species: zebra mussels and quagga mussels. The model assumes that the population survival rates are functions of temperature and turbidity, and that the two species compete for food. The stability analysis of the model yields conditions on net reproductive rates and intrinsic growth rates that lead to competitive exclusion. The model predicts quagga mussel dominance leading to potential exclusion of zebra mussels at mean water temperatures below [Formula: see text] and over a broad range of turbidities, and a much narrower set of conditions that favor zebra mussel dominance and potential exclusion of quagga mussels at temperatures above [Formula: see text] and turbidities below 35 NTU. We then construct a two-patch dispersal model to examine how the dispersal rates and the environmental factors affect competitive exclusion and coexistence.

The impact of environmental toxins on predator-prey dynamics.

Predators and prey may be simultaneously exposed to environmental toxins, but one may be more susceptible than the other. To study the effects of environmental toxins on food web dynamics, we develop a toxin-dependent predator-prey model that combines both direct and indirect toxic effects on two trophic levels. The direct effects of toxins typically reduce organism abundance by increasing mortality or reducing fecundity. Such direct effects, therefore, alter both bottom-up food availability and top-down predatory ability. However, the indirect effects, when mediated through predator-prey interactions, may lead to counterintuitive effects. This study investigates how the balance of the classical predator-prey dynamics changes as a function of environmental toxin levels. While high toxin concentrations are shown to be harmful to both species, possibly leading to extirpation of both species, intermediate toxin concentrations may affect predators disproportionately through biomagnification, leading to reduced abundance of predators and increased abundance of the prey. This counterintuitive effect significantly increases biomass at the lower trophic level. Environmental toxins may also reduce population variability by preventing populations from fluctuating around a coexistence equilibrium. Finally, environmental toxins may induce bistable dynamics, in which different initial population levels produce different long-term outcomes. Since our toxin-dependent predator-prey model is general, the theory developed here not only provides a sound foundation for population or community effects of toxicity, but also could be used to help develop management strategies to preserve and restore the integrity of contaminated habitats.

A model for the impact of contaminants on fish population dynamics.

Mathematical models have been widely applied to perform chemical risk assessments on biological populations for a variety of ecotoxicological processes. In this paper, by introducing a dose-dependent mortality rate function, we formulate a toxin-dependent aquatic population model that integrates mortality as toxin effect in addition to considering the effects of toxin on growth and recruitment. The model describes the direct effect of toxin on population by treating the concentration of toxin in the environment as a parameter. The model is more convenient to connect with data than traditional differential equation models that describe the interaction between toxin and population. We analyze the positive invariant region and the stability of boundary and interior steady states. The model is connected to experimental data via model parametrization. In particular, we consider the toxic effects of mercury on rainbow trout (Oncorhynchus mykiss) and obtain an appropriate range for each model parameter. The parameter estimates are then used to illustrate the long-time behavior of the population under investigation. The numerical results provide threshold values of toxin concentration in the environment to keep the population from extirpation. The findings are consistent with surface water quality guidelines. It may be appropriate to apply our model to other species and other chemicals of interest to consider guideline development.

Fitting a structured juvenile-adult model for green tree frogs to population estimates from capture-mark-recapture field data.

We derive point and interval estimates for an urban population of green tree frogs (Hyla cinerea) from capture-mark-recapture field data obtained during the years 2006-2009. We present an infinite-dimensional least-squares approach which compares a mathematical population model to the statistical population estimates obtained from the field data. The model is composed of nonlinear first-order hyperbolic equations describing the dynamics of the amphibian population where individuals are divided into juveniles (tadpoles) and adults (frogs). To solve the least-squares problem, an explicit finite difference approximation is developed. Convergence results for the computed parameters are presented. Parameter estimates for the vital rates of juveniles and adults are obtained, and standard deviations for these estimates are computed. Numerical results for the model sensitivity with respect to these parameters are given. Finally, the above-mentioned parameter estimates are used to illustrate the long-time behavior of the population under investigation.

Stochastic juvenile--adult models with application to a green tree frog population.

We derive several stochastic models from a deterministic population model that describes the dynamics of age-structured juveniles coupled with size-structured adults. Numerical simulation results of the stochastic models are compared with the solution of the deterministic model. These models are then used to understand the effect of demographic stochasticity on the dynamics of an urban green tree frog (Hyla cinerea) population.