\documentclass[reqno]{amsart}
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\AtBeginDocument{{\noindent\small
\emph{Electronic Journal of Differential Equations},
Vol. 2016 (2016), No. 18, pp. 1--17.\newline
ISSN: 1072-6691. URL: http://ejde.math.txstate.edu or http://ejde.math.unt.edu
\newline ftp ejde.math.txstate.edu}
\thanks{\copyright 2016 Texas State University.}
\vspace{9mm}}

\begin{document}
\title[\hfilneg EJDE-2016/18\hfil Linear and logistic models]
{Linear and logistic models with time dependent coefficients}

\author[Y. Mir,  F. Dubeau \hfil EJDE-2016/18\hfilneg]
{Youness Mir,  Fran\c{c}ois Dubeau}

\address{Youness Mir \newline
 D\'epartement de math\'ematiques,
Universit\'e de Sherbrooke, \newline
2500 Boulevard de l'Universit\'e, 
Sherbrooke (Qc),  J1K 2R1, Canada}
\email{youness.mir@usherbrooke.ca}

\address{Fran\c{c}ois Dubeau \newline
 D\'epartement de math\'ematiques,
Universit\'e de Sherbrooke, \newline
2500 Boulevard de l'Universit\'e,
Sherbrooke (Qc),  J1K 2R1, Canada}
\email{francois.dubeau@usherbrooke.ca}

\thanks{Submitted May 22, 2015. Published January 11, 2016.}
\subjclass[2010]{91B62, 34G10, 34G20, 34K25, 00A71, 92D25}
\keywords{Growth models; linear model; logistic model; carrying capacity;
\hfill\break\indent   product decomposition}

\begin{abstract}
 We sutdy the effects of some properties of the carrying capacity on the
 solution of the linear and logistic differential equations. We present 
 results concerning the behaviour and the asymptotic behaviour of their
 solutions. Special attention  is paid when the carrying capacity is an
 increasing or a decreasing positive  function. For more general carrying
 capacity, we obtain bounds for the  corresponding solution by constructing
 appropriate subsolution and supersolution. We also present a decomposition
 of the solution of the linear, and logistic, differential equation as a 
 product of the carrying capacity and the solution to  the corresponding 
 differential equation with a constant carrying capacity.
\end{abstract}

\maketitle
\numberwithin{equation}{section}
\newtheorem{theorem}{Theorem}[section]
\newtheorem{lemma}[theorem]{Lemma}
\newtheorem{corollary}[theorem]{Corollary}
\newtheorem{example}[theorem]{Example}
\allowdisplaybreaks

\section{Introduction}\label{introduction}

In this article we shall study the solutions of the linear and logistic
differential equations defined respectively by
\begin{equation}\label{eq:intro-linear}
\dot{x}(t)  = \alpha(t)- \beta(t) x(t), \quad  t\geq t_0,
\end{equation}
and
\begin{equation}\label{eq:intro-logistic}
\dot{x} (t) = \beta(t) x(t) - \alpha(t) x^{2}(t), \quad t\geq t_0,
\end{equation}
where $\alpha(t)$ and $\beta(t)$ are strictly positive and continuous
functions on $[t_0, +\infty)$, with $t_0 \in \mathbb{R}$.
More precisely, we will consider the effect of $\alpha(t)$, $\beta(t)$,
and the ratio $k(t) = \alpha(t)/ \beta(t)$
on the behavior of the solutions of these models for any positive
initial value $x(t_0)>0$.

Considering that the mapping $y : x \mapsto y = x^{-1}$ transforms
\eqref{eq:intro-logistic}
into the linear differential equation
$$
 \dot{y} (t) = \alpha(t)  - \beta(t) y(t), \quad  t\geq t_0,
$$
we will focus our study on \eqref{eq:intro-linear}. Indeed, all
results obtained for \eqref{eq:intro-linear} could then be directly
applied to \eqref{eq:intro-logistic}.

Considering the preceding mapping used to rely solutions of
\eqref{eq:intro-logistic} to solutions of \eqref{eq:intro-linear},
we will call the ratio $k(t)=\alpha(t)/ \beta(t)$ the carrying capacity
for the linear model \eqref{eq:intro-linear}
despite the fact that this expression, for the logistic equation
\eqref{eq:intro-logistic},
refer to $ \beta(t)/\alpha(t) = 1/k(t)$.

With a constant carrying capacity $k(t)= k$, these models, and many extensions
of them, have extensively been used to describe and improve the possible
relationship between independent and dependent variables in terms
of mathematical equations. It happended in many fields of applied sciences,
like ecology, sociology, medicine, and other domains
\cite{DuMiAsChMMAC,DuMiAsChIJHST,HuJoMe,Mu,Ra1,Ra2,Tho}.
However, according to Coleman \cite{Col1,Col3,Col2},
and later to  Meyer \cite{Meyer1,Meyer2}, changes in the environment
affect the carrying capacity.
Hence, modeling phenomena with unchanging carrying capacity is often unrealistic.
  Several authors have reformulated these standards models with constant carrying
 capacity to accommodate phenomena with varying \cite{ Saf2,Saf,Shep},
logistically varying \cite{Meyer1,Meyer2}, increasing \cite{DuMi2,DuMi3,MiDu}
or sinusoidally varying \cite{Col2,Col3,Svit} carrying capacity.
In \cite{Bank}, the author has given some examples on real situations in
which the carrying capacity $k$ changes with time continuously. Many other
researchers have been interested in the problem of the existence and
uniqueness solution of the solution of \eqref{eq:intro-logistic}
with bounded time dependent carrying capacity \cite{Geo,Nak}.
In \cite{Thi}, the author argued that it is difficult
to make precise statement about the asymptotic behaviour of the solution
to a non-autonomous differential equation
when the coefficients  $\alpha$ and $\beta$ are time dependent functions.
In \cite{Geo} the authors have proved that a monotone bounded carrying capacity
is an attractor forward in time of all positive solution of
\eqref{eq:intro-logistic} in the sense that the limit at infinity  of the
difference  between  any solution to the differential equation and the carrying
capacity  vanishes.

Despite the intensive examples of real situations involving growth phenomena
 with unbounded time dependent carrying capacity (see  \cite{Bank} for example),
these situations  has  surprisingly received little attention
in the literature compared to the massive literature devoted to the problems
with bounded coefficients.

The main purpose of this paper is to address this knowledge gap through a
qualitative study. We study in a
thorough  way the effect of an unbounded  carrying capacity  on the behaviour
and the asymptotic behaviour of the solution of the linear and logistic
differential equations.  We shall pay particular attention to the
cases when the carrying capacity $k(t)$ is an increasing or decreasing positive
function. Moreover, the asymptotic behaviour of the solutions to these
differential equations is not well described  when the
carrying capacity $k(t)$ is time dependent  and unbounded.
On this basis comes the second aim of this paper which consists of
reformulating the solutions $x(t)$ of \eqref{eq:intro-linear} and
\eqref{eq:intro-logistic}
as a product of a simple function $\tilde{z}(t)$  and a carrying
capacity $\tilde{k}(t)$ such that
$\lim_{t \to +\infty} \tilde{z}(t) = 1$,
and $\lim_{t \to +\infty}  ( x(t) - \tilde{k}(t) ) = 0$.

The present paper is organized as follows.  In Section \ref{sec1}, we start
by giving some properties about the solution of the linear differential equation.
Then, we present some  results on the behaviour and  the
asymptotic behaviour  of its solution when the time dependent coefficients
are not necessary bounded.
We also show  that when the carrying capacity is an increasing and
unbounded function, the limit at infinity
of the difference  between  the solution of the linear differential
equation and the carrying capacity is
not always equal to zero. 
In Section \ref{sec2}, we provide monotonic bounds for the solution of
\eqref{eq:intro-linear} when $k(t)$ is neither an increasing nor a
decreasing function. 
Section \ref{sec6} addresses the problem of decomposing
the solution into a product of a carrying capacity and a simple
analytic function.  Finally, we present a conclusion.

\section{The linear differential equation} \label{sec1}

Let $I=[t_0, +\infty)$ be an interval such that $t_0 \in \mathbb{R}$
and consider the linear differential equation
\begin{equation}\label{eq:1}
 \dot{x}(t)  =  \alpha(t)- \beta(t) x(t) =  \beta(t)(k(t) - x(t))\quad
 t\geq t_0,
\end{equation}
where $\alpha(t), \beta(t) : I \to (0,+\infty)$ are two continuous functions,
and $k(t)=\alpha(t)/ \beta(t)$. Subject to the initial condition
$x(t_0) = x_0$, \eqref{eq:1} has the unique solution given by
\begin{equation}\label{eq:2}
 x(t)  =  e^{ - \int^{t}_{t_0} \beta(u) du   }
\Big( x_0  +  \int^{t}_{t_0} \alpha(\tau) e^{ \int^{\tau}_{t_0} \beta(u) du   }
  d \tau \Big).
\end{equation}
Under the assumptions $k(t_0) = k_0$, and
\begin{equation}\label{eq:assump1}
\begin{aligned}
 k \in AC^{1}_{\rm loc}(I)
=\Big\{&k \in C(I) : \dot{k} \in L^{1}_{\rm loc}(I),\;
 k(t_2)=k(t_1) + \int^{t_2}_{t_1}\dot{k}(\tau) d\tau,\\
& \text{for all  } t_1, t_2 \in I\Big\},
 \end{aligned}
\end{equation}
Equation \eqref{eq:2} takes the form
\begin{equation}\label{eq:3}
 x(t) = k(t) + \Big( (x_0 - k_0)e^{ -  \int^{t}_{t_0} \beta(u) du   }
 - e^{ - \int^{t}_{t_0} \beta(u) du   } \int^{t}_{t_0} \dot{k}(u)
e^{ \int^{u}_{t_0} \beta(\tau) d \tau   } du  \Big).
\end{equation}

In the case where $\alpha (t) / \beta (t) = k$ does not depend on time,
\eqref{eq:3} reduces to
\begin{equation}\label{eq:4}
 x(t)  =  k +   ( x_0  - k )e^{ - \int^{t}_{t_0} \beta(u) du }.
\end{equation}
Regarding  $x_0$ and $k$ we have the following situations:
\begin{itemize}
\item if $x_0 = k$, from \eqref{eq:4} we have  $x(t) = k$ for all $t \in I$;

\item  if $x_0 \neq k$, we have
$$
\lim_{t \to +\infty} x(t)  = k +   ( x_0  - k )e^{ - \int^{+\infty}_{t_0} \beta(u)
 du   } = x_{\infty},
$$
and
\begin{itemize}
\item[*] if $x_0 < k$, then $x(t)< x_{\infty}$ for all $t \in I$, and
 the solution $x(t)$ grows up to $x_{\infty}$,
\item[*] if $x_0 > k$, then $x(t)> x_{\infty}$ for all $t \in I$,
and the solution $x(t)$ decreases to $x_{\infty}$.
 \end{itemize}
\end{itemize}

When $\alpha (t) / \beta (t) = k(t)$ depends on time, \eqref{eq:1} has no
constant solution and the solution \eqref{eq:2} may crosses  $k(t)$.
It happens when $\dot{x}(t) = 0$. For $t_* \in I$, let us consider the
closed interval
$$
 J_{t_*} = \{ t \in I : t  \geq t_*, \text{  and  }
x(\tau) = x(t_*) \text{ for all } t_* \leq \tau \leq t \}=[t_{*},t_{**}],
$$
where $t_{**}= \sup_{\tau \in I} J_{t_*} $. Moreover,
if $t_*<t_{**}$, then $\dot{x}(t) = 0$ for all $t \in J_{t_*}$
and consequently, from \eqref{eq:1} and \eqref{eq:3} we have
\begin{equation}\label{eq:5}
 x(t)  =  k(t), \quad\text{and}\quad    \dot{k}(t) = 0   \text{    for all   }
 t \in J_{t_*}.
\end{equation}

\subsection{Increasing case}

In this section, we suppose that $k(t)$ is a non-decreasing function
\begin{equation}\label{eq:assump2}
 k(t_1) \leq k(t_2)  \quad \text{for all  } t_1, t_2 \in I \text{  such that   }
t_1 < t_2.
\end{equation}
We have the following result.

\begin{lemma}\label{lem1}
Let $k(t)= \alpha(t)/ \beta(t) : I \to \mathbb{R} $  be defined such
that $\beta(t) > 0 $ for all $t$.
Suppose that $k$ satisfies the assumptions \eqref{eq:assump1} and \eqref{eq:assump2},
 and let  $x(t)$ be the solution of \eqref{eq:1} passing through the point
 $(t_0,x_0)$. If for some $s \in I$ we have  $x(s) = k(s)$,
then  $x(t) \leq k(t)$ for all $t \geq s$. More precisely,
\begin{itemize}
 \item $x(t) = k(t)$, and $\dot{x}(t) =0$, for all $t \in J_{s} $, and
 \item $x(t) < k(t)$, and $\dot{x}(t) >0$, for all $t > t_s = \sup J_{s} $.
 \end{itemize}
\end{lemma}

\begin{proof}
Let $x(t)$ be the solution of \eqref{eq:1} passing through the point $(t_0,x_0)$,
and let $s \in I$ such that $x(s) = k(s)$. From \eqref{eq:5},
we have $x(t) = k(t)$ for all $t \in J_{s} $. Let $t_s = \sup J_{s} \in J_{s}$,
it follows that $x(t_s) = k(t_s) = k(s)$ and  $k(t) > k(t_s)$ for all $t > t_s  $.
Thus, by considering the solution
passing through the point $(t_s,x(t_s))$, we have
\begin{align*}
 x(t) &=  k(t)+\Big((x(t_s)-k(t_s))e^{-\int^{t}_{t_s}\beta(u)du }
 -e^{-\int^{t}_{t_s}\beta(u)du}\int^{t}_{t_s}\dot{k}(u)
 e^{\int^{u}_{t_s}\beta(\tau)d\tau}du\Big) \\
      &=  k(t) - \int^{t}_{t_s} \dot{k}(u) e^{ \int^{u}_{t} \beta(\tau) d \tau } du.
\end{align*}
As $k(t) > k(t_s)$ for all $t > t_s  $, it follows that $k(t_s)<x(t)<k(t)$
for all $t > t_s $.
\end{proof}

The following result characterizes the behaviour of any solution of
\eqref{eq:1} in the case where $k(t)$ is non decreasing.

\begin{theorem} \label{thm2}
Let $k(t)$  and  $x(t)$ be defined as in Lemma \ref{lem1}. Also let 
$k_{\infty}=\lim_{t \to +\infty} k(t)$. Then
\begin{itemize}
\item[(a)] if $x_0 < k_0$, then  $x(t) < k(t)   $, and $\dot{x}(t) >0$,
for all  $t \in I$;

\item[(b)] if $x_0 = k_0$, then  $x(t) \leq k(t)$, and $\dot{x}(t) \geq 0$,
for all  $t \in I$;

\item[(c)] if $x_0 > k_0$, we have two cases to consider
\begin{itemize}
\item[(i)] if $x_0 \leq k_{\infty}$, then it will exists some
 $s>t_0$ where $s = \arg\!\min x(t) $ such that $x(s)= k(s)$, and in this
case  $x(t)$ decreases if $t<s$ and increases if $t>s$;

\item[(ii)] if $x_0 > k_{\infty}$, then either $x(t)$ has the same behaviour
as in  $(i)$, or $x(t) > k(t)   $, and $\dot{x}(t) <0$, for all  $t \in I$.
\end{itemize}
\end{itemize}
\end{theorem}

\begin{proof}
The proofs of assertions (a) and (b) follow immediately from
\eqref{eq:3} and Lemma~\ref{lem1}. Let us prove (c).

(i) If $k_0 < x_0 < k_{\infty}$, from \eqref{eq:1}, it follows that
$\dot{x}(t_0)<0$. By continuity, we also have
$\dot{x}(t)<0$ for all $t$ provided that  $x(t) > k(t)$ which is satisfied
at least locally near $t_0$. We will prove
that, there exists some $s>t_0$ such that $ x(s) = k(s)$ and $x(t)$
increases for $t>s$ with $x(t) < k(t)$. Indeed,
suppose that $ x(t) > k(t)$ for all $t>t_0$. Thus, from \eqref{eq:1},
we have that $\dot{x}(t)<0$ for all $t \geq t_0$
and hence, $k(t) < x(t) < x(t_0) = x_0$. By taking the limit at infinity we obtain
 $k_{\infty} \leq x_0$ which contradicts our assumption on $x_0$.
If $x_0 = k_{\infty}<\infty$, by arguing as in the proof above  and by taking
the limit at infinity we obtain $x_{\infty} = x_0$
which contradict the fact that  $ x(t) > k(t)$, i.e. $\dot{x}(t) <0$,
for all $t>t_0$.

(ii) if $x_0 > k_{\infty}> k_0$, i.e. $k_{\infty}<\infty$, we must have
$x_{\infty}=\lim_{t \to +\infty} x(t) < \infty $.
In addition, if we set $\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du = l$,
from \eqref{eq:3}, we have
\begin{equation}\label{eq:7}
 (x_0 - k_0)e^{-l} - (k_{\infty}-k_0) \leq x_{\infty} - k_{\infty}
\leq (x_0 - k_{\infty})e^{-l}.
\end{equation}
If $l= +\infty$, from \eqref{eq:7}, it follows that $x_{\infty}  \leq k_{\infty}$
and hence, $x(t)$ has the same asymptotic
behaviour as in  $(i)$. If $l < +\infty$, from \eqref{eq:7}, it follows that
$x_{\infty}  \geq k_{\infty}$ if $x_0 \geq  k_0 + (k_{\infty}-k_0)e^{l} $,
and the solution $x(t)$ is always decreasing.
If $x_0 \leq  k_0 + (k_{\infty}-k_0)e^{l} $, the solution decreases or has
the same asymptotic behaviour as in (i).
\end{proof}

 The following result gives us some information about the asymptotic behaviour
of the solution to the linear  problem \eqref{eq:1}
when the time dependent coefficients $\alpha(t)$ and  $\beta(t)$ are not
necessary bounded.

\begin{theorem}\label{thm1}
Let $k(t)$  and  $x(t)$ be defined as in Lemma \ref{lem1} and set
\[
k_{\infty}=\lim_{t \to +\infty} k(t), \quad 
x_{\infty}=\lim_{t \to +\infty} x(t).
\]
Then
\begin{itemize}
\item[(a)] If $\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du < + \infty$,
 then $x_{\infty} < + \infty$.

\item[(b)] If $\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du = + \infty$, then
\begin{itemize}
  \item[(I)] if $\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du = l< +\infty $,
 then $x_{\infty} = +\infty$;

  \item[(II)] if $\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du = +\infty$,
then $x_{\infty} = k_{\infty}$, and
  \begin{itemize}
  \item[(i)] if $k_{\infty} <+\infty $, then $\lim_{t \to +\infty} (x(t) - k(t)) = 0$;

  \item[(ii)] if $k_{\infty} =+\infty$, then $\lim_{t \to +\infty} (x(t) - k(t))
= - \lim_{t \to +\infty} \frac{\dot{k}(t)}{\beta(t)}$
  if this limit exists.
\end{itemize}
\end{itemize}
\end{itemize}
\end{theorem}

\begin{proof}
(a) If $\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du < + \infty$,
then from the fact that $\alpha(t)=k(t) \beta(t)$,
and $k(t)>k_0>0$ for all $t \in I$, it follows that
$\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du < + \infty$. Hence,
$$
 \lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) e^{\int^{u}_{t_0} \beta(\tau) d \tau}du
 \leq \lim_{t \to +\infty} e^{\int^{t}_{t_0} \beta(u) d u} \int^{t}_{t_0}\alpha(u)du < +\infty.
$$
Thus, from \eqref{eq:2} it follows that $x_{\infty}< +\infty$. 

(b) Let us suppose that
$\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du = + \infty$. As
\[
\int^{t}_{t_0} \alpha(u) du \leq  \int^{t}_{t_0}  \alpha(u)
e^{  \int^{u}_{t_0} \beta(\tau) d \tau   } du ,
\]
 it follows that
\begin{equation}\label{eq:8}
 \lim_{t \to +\infty}  \int^{t}_{t_0}  \alpha(u)
 e^{  \int^{u}_{t_0} \beta(\tau) d \tau} du =+\infty.
\end{equation}

(I) If $\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du = l< +\infty $,
then from \eqref{eq:2}, and \eqref{eq:8},
it follows that $\lim_{t \to +\infty} x(t) =  \infty $.

(II) If $\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du = +\infty $,
then  from \eqref{eq:2} and \eqref{eq:8},
and by using the L'H\^opital's rule we obtain
\begin{align*}
 x_{\infty} = \lim_{t \to +\infty} x(t)
&=  \lim_{t\to +\infty}
 \frac{\int^{t}_{t_0} \alpha(\tau) e^{ \int^{\tau}_{t_0} \beta(u) du}d \tau}
 {  e^{\int^{t}_{t_0} \beta(u) du}} \\
 &=  \lim_{t \to +\infty} \frac{\alpha(t) e^{\int^{t}_{t_0} \beta(u) du}}
 {\beta(t) e^{\int^{t}_{t_0} \beta(u) du}} \\
 &=  \lim_{t \to +\infty} \frac{\alpha(t)}{\beta(t)} \\
 &=  \lim_{t \to +\infty} k(t) = k_{\infty}.
\end{align*}

(i) If $ k_{\infty} <\infty $, we have that
$ \lim_{t \to +\infty}(x(t) - k(t)) = x_{\infty} - k_{\infty} = 0$.

(ii) If $ \lim_{t \to +\infty} k(t) =\infty $, as
$\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du = +\infty $ it follows that
\begin{align*}
& \lim_{t \to +\infty} (x(t) -k(t))\\
&=  \lim_{t \to +\infty} \Big( (x_0 - \frac{\alpha_0}{\beta_0})
 e^{ -  \int^{t}_{t_0} \beta(u) du   }
 - e^{ - \int^{t}_{t_0} \beta(u) du   } \int^{t}_{t_0} \dot{k}(u)
 e^{ \int^{u}_{t_0} \beta(\tau) d \tau } \Big) \\
  &=  - \lim_{t \to +\infty}  \frac{ \int^{t}_{t_0} \dot{k}(u)
e^{ \int^{u}_{t_0} \beta(\tau) d \tau   }}{e^{ \int^{t}_{t_0} \beta(u) du   }}.
\end{align*}
In addition,  as $k(t)$ is an non decreasing function, we have for all $t > t_0$,
$$
 \dot{k}(u) \leq  \dot{k}(u) e^{  \int^{u}_{t_0} \beta(\tau) d \tau   } du
\leq \dot{k}(u) e^{  \int^{t}_{t_0} \beta(\tau) d \tau   },
$$
thus
$$
 k(t)- k(t_0) \leq \int^{t}_{t_0}  \dot{k}(u)
e^{  \int^{u}_{t_0} \beta(\tau) d \tau   } du \leq  (k(t)- k(t_0))
 e^{  \int^{t}_{t_0} \beta(\tau) d \tau   },
$$
and  $\lim_{t \to +\infty} \int^{t}_{t_0} \dot{k}(u)
e^{ \int^{u}_{t_0} \beta(\tau) d \tau} du = + \infty$.
Thus
$$
\lim_{t \to +\infty} x(t) -k(t) =  - \lim_{t \to +\infty}
\frac{ \int^{t}_{t_0} \dot{k}(u) e^{ \int^{u}_{t_0} \beta(\tau)
d \tau   }}{e^{ \int^{t}_{t_0} \beta(u) du   }}
 = - \lim_{t \to +\infty} \frac{\dot{k}(t)}{\beta(t)},
$$
if this limit exists.
\end{proof}

\begin{example}[\cite{Bank}, Linear asymptote] \label{exemple:1} \rm
Let $\beta(t) = a$, and $k(t) = pt +q$, where $a > 0$, $p>0$, and $q \geq 0$.
From \eqref{eq:3} we have
\begin{align*}
 x(t) &=  e^{ - a (t-t_0)   }
\Big( x_0  +  \int^{t}_{t_0} a e^{a (x-t_0)   } (px +q)  dx \Big),  \\
      &=  k(t) - p/a +  (    x_0 - ( k_0 - p/a)       ) e^{ -  a(t-t_0) },
\end{align*}
where $x_0=x(t_0)$ and $k_{0} =k(t_0)$. From Lemma \ref{thm2} we have
\begin{itemize}
\item[(1)] If $x_0 < k_{0}$, then $x(t)$ is increasing and $x(t)< k(t)$ for all $t$.
 In this case $x(t)$ is convex if $x_0> k_{0} - p/a$ and concave if not.

\item[(2)] If $x_0 \geq k_{0}$, then $x(t) $ is convex and intersects $k(t) $
at $t_* = t_0 + \ln(  1+ \frac{a}{p} (x_0 - k_{0} ) )/ a$,
with $t_* = \arg\!\min x(t)$. In this case, $x(t)$ increases if $t>t_*$ and
decreases if not.
\end{itemize}
Moreover we have
$$
\lim_{t \to +\infty}  (x(t) - k(t))
=  - \lim_{t \to +\infty} \frac{\dot{k}(t)}{\beta(t)}=   - \frac{b}{a}.
$$
\end{example}

In the next example, we give some hypothesis on $\beta(t)$ which ensure that
the limit at infinity between the solution
to the differential equation \eqref{eq:1} and a curvilinear carrying
capacity $k(t)$ vanishes.

\begin{example}[Curvilinear asymptote]\label{cor1} \rm
Let $\alpha(t) $, and $\beta(t)$ be two continuous functions such that
$$
 k(t) = \frac{\alpha(t)}{\beta(t)} = pt^{\lambda} + q,
$$
with $t>0$, $p>0$, $q \geq 0$,  and suppose that
$$
 \frac{\beta (t)}{t^{\gamma}} \geq c>0,  \quad \text{for all  } t >0,
$$
with $0<\lambda < \gamma+1$. The unique solution to the initial value problem
 \begin{gather*}
   \dot{x} (t) = \alpha(t)    - \beta(t) x(t), \quad t \geq t_0, \\
        x(t_0) = x_0,
 \end{gather*}
has the following asymptotic property,
$$
 \lim_{t \to +\infty} (x(t) - k(t)) = 0.
$$
Indeed, as $\beta(t) \geq c t^{\gamma}$, and $k(t) \beta(t) = \alpha(t)$
it follows that
\[
\int^{+\infty}_{t_0} \beta(\tau) d \tau
= \int^{+\infty}_{t_0} \alpha(\tau) d \tau = +\infty.
\]
From Theorem \ref{thm1},
and  $\lim_{t \to +\infty} k(t) = +\infty $,  it follows that
$\lim_{t \to +\infty} (x(t) - k(t))
= - \lim_{t \to +\infty} \frac{\dot{k}(t)}{\beta(t)}$.
In addition, we have
$$
 0 \leq \frac{\dot{k}(t)}{\beta(t)}  \leq \frac{\dot{k}(t)}{c t^{\gamma}}
 = \frac{\lambda p }{c} t^{\lambda-(\gamma+1)}.
$$
As $0<\lambda < \gamma+1$, it follows that
$\lim_{t \to +\infty} \frac{\dot{k}(t)}{\beta(t)} =0$. Thus,
$$
 \lim_{t \to +\infty} (x(t) - k(t))
 = - \lim_{t \to +\infty}\frac{\dot{k}(t)}{\beta(t)} = 0.
$$
\end{example}

\subsection{Decreasing case}

In this section, we suppose that  $k(t)$ is a non increasing function
\begin{equation}\label{eq:assump3}
 k(t_1) \geq k(t_2) \quad  \text{for all  } t_1, t_2 \in I \text{  such that   }
t_1 < t_2.
\end{equation}
We have the following result.

\begin{lemma}\label{lem11}
Let $k(t)= \alpha(t)/ \beta(t) : I \to \mathbb{R}^+ $
 be defined such that $\alpha(t) > 0 $,
and $\beta(t) > 0 $ for all $t$. Suppose that $k(t)$ satisfies the
assumptions \eqref{eq:assump1}
and \eqref{eq:assump3}, and let  $x(t)$ be the solution of \eqref{eq:1}
passing through the point $(t_0,x_0)$.
If for some $s \in I$ we have  $x(s) = k(s)$, then  $x(t) \geq k(t)$
for all $t \geq s$.
More precisely,
\begin{itemize}
 \item $x(t) = k(t)$, and $\dot{x}(t) =0$, for all $t \in J_{s} $, and
 \item $x(t) > k(t)$, and $\dot{x}(t) <0$, for all $t > t_s = \sup J_{s} $.
\end{itemize}
\end{lemma}

\begin{proof}
Let $x(t)$ be the solution of \eqref{eq:1} passing through the point
$(t_0,x_0)$, and let $s \in I$ such that $x(s) = k(s)$.
From \eqref{eq:5}, we have $x(t) = k(t)$ for all $t \in J_{s} $.
Let $t_s = \sup J_{s} \in J_{s}$, it follows that $x(t_s) = k(t_s) = k(s)$
and  $k(t) < k(t_s)$ for all $t > t_s  $.
Thus, by considering the solution passing through the point $(t_s,x(t_s))$,
we have
\begin{align*}
 x(t) &=  k(t) +   \Big( (x(t_s) - k(t_s))e^{ -  \int^{t}_{t_s} \beta(u) du   }
- e^{ - \int^{t}_{t_s} \beta(u) du   } \int^{t}_{t_s} \dot{k}(u)
e^{ \int^{u}_{t_s} \beta(\tau) d \tau   } du    \Big), \\
&=  k(t) -  \int^{t}_{t_s} \dot{k}(u) e^{ \int^{u}_{t} \beta(\tau) d \tau   } du
> k(t).
\end{align*}
\end{proof}

 The following result characterizes the behaviour of any solution
 of \eqref{eq:1} in the case where $k(t)$ is decreasing.

\begin{theorem}\label{thm22}
Let $k(t)$  and  $x(t)$ be defined as in Lemma \ref{lem11}. Also let
 $k_{\infty}=\lim_{t \to +\infty} k(t)$
and $x_{\infty}=\lim_{t \to +\infty} x(t)$. Then
\begin{itemize}
\item[(a)] if $x_0 > k_0$, then  $x(t) > k(t)   $, and
$\dot{x}(t) <0$, for all  $t \in I$;

\item[(b)] if $x_0 = k_0$, then  $x(t) \geq k(t)$, and $\dot{x}(t) \leq 0$,
for all  $t \in I$;

\item[(c)] if $0 \leq x_0 < k_0$, we have two cases to consider

\begin{itemize}
\item[(i)] if $x_0 \geq k_{\infty}$, then it will exists some  $s>t_0$ where
$s = \arg\!\max x(t) $ such
that $x(s)= k(s)$, and in this case  $x(t)$ increases if $t<s$ and decreases
if $t>s$;

\item[(ii)] if $x_0 < k_{\infty}$, then either $x(t)$ has the same behaviour
as in  $(i)$, or $x(t) < k(t)   $,
and $\dot{x}(t) >0$, for all  $t \in I$.
\end{itemize}
\end{itemize}
\end{theorem}

\begin{proof}
The proofs of the assertions (a) and (b) follow immediately from \eqref{eq:3}
 and Lemma \ref{lem11}.
Let us prove (c).

(i) If $k_0 > x_0 > k_{\infty}$, from \eqref{eq:1}, it follows that
$\dot{x}(t_0)>0$. By continuity, we
also have $\dot{x}(t)>0$ for all $t$ provided that  $x(t) < k(t)$.
We will prove that, there exists some
$s>t_0$ such that $ x(s) = k(s)$ and $x(t)$ decreases for $t>s$ with $x(t) > k(t)$.
Indeed, suppose that
$ x(t) < k(t)$ for all $t>t_0$. Thus, from \eqref{eq:1}, we have that
 $\dot{x}(t)>0$ for all $t \geq t_0$
and hence, $k(t) > x(t) > x(t_0) = x_0$. By taking the limit at infinity
 we obtain $k_{\infty} \geq x_0$ which
contradicts our assumption on $x_0$.

If $x_0 = k_{\infty}$, by arguing as in the proof above  and by taking the limit
at infinity we obtain $x_{\infty} = x_0$
which contradict the fact that  $ x(t) < k(t)$, i.e. $\dot{x}(t) >0$, for
all $t>t_0$.

(ii) Suppose that $0 \leq x_0 < k_{\infty}< k_0$. If we set
$\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du = l$,
from \eqref{eq:3}, we have
\begin{equation}\label{eq:16}
 (x_0 - k_{\infty})e^{-l}  \leq x_{\infty} - k_{\infty} \leq (x_0 - k_0)e^{-l}
- (k_{\infty}-k_0).
\end{equation}
If $l= +\infty$, from \eqref{eq:16}, it follows that
$x_{\infty}  \geq k_{\infty}$ and hence, $x(t)$ has the
same asymptotic behaviour as in  $(i)$. If $l < +\infty$, from \eqref{eq:16},
it follows that
$x_{\infty}  \leq k_{\infty}$ if $x_0 \leq  k_0 + (k_{\infty}-k_0)e^{l} $,
and the solution $x(t)$ is always
increasing. If $x_0 \geq  k_0 + (k_{\infty}-k_0)e^{l} $, the solution
increases or has the same asymptotic
behaviour as in (i).
\end{proof}

 The following result gives us some information about the asymptotic behaviour
of the solution to the linear problem \eqref{eq:1} when the time dependent
coefficients $\alpha(t)$ and  $\beta(t)$ are not necessary bounded.

\begin{theorem}\label{thm15}
Let $k(t)$  and  $x(t)$ be defined as in Lemma \ref{lem11}. Also let 
$k_{\infty}=\lim_{t \to +\infty} k(t)$,
and $x_{\infty}=\lim_{t \to +\infty} x(t)$. Then
\begin{itemize}
\item[(a)] If $\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du = + \infty$,
then $ x_{\infty} = k_{\infty} \geq 0$.

\item[(b)] If $\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du < + \infty$, then
\begin{itemize}
  \item[(I)] if $\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du =  +\infty $,
  then $x_{\infty} = k_{\infty} = 0$;
  \item[(II)] if $\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du =l< +\infty$,
 then
$$
 k_{\infty} + (x_0 - k_{\infty})e^{-l}  \leq x_{\infty}
\leq  k_0 + (x_0 - k_0)e^{-l}.
$$
\end{itemize}
\end{itemize}
\end{theorem}

\begin{proof}
(a) If $\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du = + \infty$, as
$\alpha(t)=k(t) \beta(t)$, and $ k(t) \leq k_0$ for all $t \in I$,
it follows that $\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du = + \infty$.
In addition, $\int^{t}_{t_0} \alpha(u) du
\leq  \int^{t}_{t_0}  \alpha(u) e^{  \int^{u}_{t_0} \beta(\tau) d \tau   } du  $,
hence
$$
 \lim_{t \to +\infty}  \int^{t}_{t_0}  \alpha(u)
e^{  \int^{u}_{t_0} \beta(\tau) d \tau   } du =+\infty.
$$
Thus, by using  L'H\^opital's rule we have
\begin{align*}
 x_{\infty} = \lim_{t \to +\infty} x(t) &=
     \lim_{t \to +\infty} \frac{\int^{t}_{t_0} \alpha(\tau)
e^{ \int^{\tau}_{t_0} \beta(u) du } d \tau}{e^{\int^{t}_{t_0} \beta(u) du}} \\
 &=  \lim_{t \to +\infty} \frac{\alpha(t) e^{\int^{t}_{t_0}
 \beta(u) du}}{\beta(t) e^{\int^{t}_{t_0} \beta(u) du}} \\
 &=  \lim_{t \to +\infty} \frac{\alpha(t)}{\beta(t)} \\
 &=  \lim_{t \to +\infty} k(t) = k_{\infty} \geq 0.
\end{align*}

(b) Let us suppose that
$\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du < + \infty$.

(I) If $\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du = +\infty $,
then from \eqref{eq:2} and
the dominated convergence Theorem, it follows that
$$
\lim_{t \to +\infty} x(t) = \lim_{t \to +\infty} \int^{t}_{t_0} \alpha(\tau)
e^{- \int^{t}_{\tau} \beta(u) du} d \tau= 0.
$$
As $x_{\infty} \geq k_{\infty} \geq 0 $ it follows that  $k_{\infty} = 0 $.

(II) If $\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du = l < +\infty $,
then from \eqref{eq:3}
the result follows.
\end{proof}

\begin{example}[Hyperbolic asymptote, first case] \rm
Let  $k(t) = 1/(pt+q)$, and $\alpha(t) = 1/(t+1)^{\gamma} $  where $p>0$,
$q > 0$, and $x(t)$ be the solution
of \eqref{eq:1} passing through the point $(t_0,x_0)$ where $t_0 = 0$.
From Theorem \ref{thm15} we have

If $\gamma \leq 1$ then $\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du = + \infty$
and hence $ x_{\infty} = k_{\infty} = 0$.

If $\gamma > 1$, then $\alpha(t)$ is decreasing with $\alpha(0)=1$ and
 $\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du =  \frac{1}{\gamma - 1}$.
Moreover, $\beta(t) = (pt+q)/(t+1)^{\gamma}$,  $\beta(0)=q$, and we have
$$
\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du  =
 \begin{cases}
 l=\frac{p}{\gamma - 2} +\frac{q-p}{\gamma - 1} & \text{if }  \gamma>2, \\
 +\infty                                        & \text{if } 1 < \gamma \leq 2.
\end{cases}
$$
Hence,
\begin{itemize}
\item If $1 < \gamma \leq 2$, then  $ x_{\infty} = k_{\infty} = 0$.
\item If  $\gamma>2$, then
$$
 x_0 e^{-l} \leq x_{\infty} \leq x_0 e^{-l} + \frac{1}{q}(1- e^{-l}).
$$
\end{itemize}
\end{example}

\begin{example}[Hyperbolic asymptote, second case] \rm
Let  $k(t) = 1/(pt^{\lambda}+q)$, and $\alpha(t) = 1/t^{\gamma} $
 where $\lambda>0$, $p>0$, $q > 0$,
and $x(t)$ be the solution of \eqref{eq:1} passing through the point
$(t_0,x_0)$ where $t_0 = 1$. From Theorem \ref{thm15} we have
\begin{itemize}
\item  If $\gamma \leq 1$ then $\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du
 = + \infty$ and hence $ x_{\infty} = k_{\infty} = 0$.

\item  If $\gamma > 1$, then $\alpha(t)$ is  decreasing  with
$\alpha(1)=1$ and  $\lim_{t \to +\infty} \int^{t}_{t_0} \alpha(u) du
=  \frac{1}{\gamma - 1}<+\infty$.
Moreover,
$\beta(t) = (pt^{\lambda}+q)/t^{\gamma}$,  and we have
$$
\lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du  =
 \begin{cases}
 l=\frac{p}{\gamma - \lambda - 1} +\frac{q}{\gamma - 1} &\text{if }
  \gamma>\lambda +1, \\
 +\infty & \text{if }  1 < \gamma \leq \lambda +1.
\end{cases}
$$
\end{itemize}
Hence,
\begin{itemize}
\item If $1 < \gamma \leq \lambda +1$, then  $ x_{\infty} = k_{\infty} = 0$.
\item If  $\gamma>\lambda +1$, then
$$
 x_0 e^{-l} \leq x_{\infty} \leq x_0 e^{-l} + \frac{1}{q}(1- e^{-l}).
$$
\end{itemize}
\end{example}

\section{Subsolution and supersolution} \label{sec2}

The following theorem gives us some information on the boundedness of the solution
$x(t)$ of \eqref{eq:1} passing through a point $(t_0,x_0)$ when the carrying
capacity $k(t)= \alpha(t)/ \beta(t)$ is bounded above
and below by given positive functions.

\begin{theorem}\label{theorem11}
Let $k: I \to (0,+\infty)$  be defined such that $\alpha(t) > 0 $, and
$\beta(t) > 0 $ for all $t$,
and let  $x(t)$ be the solution of \eqref{eq:1} passing through the point 
$(t_0,x_0)$. Suppose that there
exist two functions $\underline{k}, \overline{k} : I \to (0,+\infty)$ such that
\begin{equation}\label{eq:19}
 \underline{k}(t) \leq k(t) \leq \overline{k}(t), \quad \text{for all  }  
t\geq t_0.
\end{equation}
In addition, let $ \underline{x}(t)$  and $\overline{x}(t)$ be respectively 
the solutions of the auxiliary problems
\begin{equation} \label{eq:20}
 \begin{gathered}
 \dot{\underline{x}} (t) = \beta(t)(\underline{k}(t) - \underline{x}(t)), 
\\
  \dot{\overline{x}} (t) = \beta(t)(\overline{k}(t) - \overline{x}(t)), \\
 \end{gathered} 
\end{equation}
with $\underline{x}(t_0) = \overline{x}(t_0) = x(t_0)$. Then, we have
\begin{equation}\label{eq:21}
 \underline{x}(t) \leq x(t) \leq \overline{x}(t), \quad \text{for all  }  
t\geq t_0.
\end{equation}
\end{theorem}

\begin{proof}
The solutions ${\underline{\epsilon}} (t) = {x(t) - \underline{x}(t)} $, and 
${\overline{\epsilon}} (t) = { \overline{x}(t) - x(t)} $ of the auxiliary problems
 \begin{gather*}
 \dot{\underline{\epsilon}} (t) 
=  \beta(t)((k(t) - \underline{k}(t)) - (x(t) - \underline{x}(t)))), \\
 \dot{\overline{\epsilon}} (t) 
= \beta(t)((\overline{k}(t) - k(t)) - (\overline{x}(t)-x(t))),
 \end{gather*}
with ${\underline{\epsilon}} (t_0) = {\overline{\epsilon}} (t_0) = 0 $ 
are respectively
\begin{gather*}
 \underline{\epsilon}(t)= e^{-\int^{t}_{t_0} \beta(u) du } 
\int^{t}_{t_0} \beta(\tau)(k(\tau)
-\underline{k} (\tau) ) e^{\int^{\tau}_{t_0} \beta(u)du d \tau},
\\
 {\overline{\epsilon}} (t)= e^{-\int^{t}_{t_0}\beta(u) du} \int^{t}_{t_0} 
\beta(\tau)(\overline{k}(\tau) - k(\tau))  e^{\int^{\tau}_{t_0} \beta(u) du d \tau}.
\end{gather*}
From \eqref{eq:19} it follows that $\underline{\epsilon} (t) \geq 0 $, 
$\overline{\epsilon} (t) \geq 0 $,
and hence the inequalities \eqref{eq:21} follow.
\end{proof}

The following corollary is an immediate consequence of Theorem \ref{theorem11}.

\begin{corollary}[Increasing case] \label{corolary11}
Let  $\overline{k}, \underline{k} : I \to (0,+\infty)$ be defined by
$$
 \overline{k} (t) =  \max \{k(\tau) : t_0 \leq \tau \leq t  \}, \quad \text{and}\quad
\underline{k} (t) =  \min \{k(\tau): \tau \geq t \},
$$
and let $ \underline{x}(t)$  and $\overline{x}(t)$ be respectively the solutions 
of the auxiliary  problems \eqref{eq:20},
with $\underline{x}(t_0) = \overline{x}(t_0) = x(t_0)$. Then,
\begin{equation}\label{eq:25}
\underline{x}(t) \leq x(t) \leq \overline{x}(t), \quad \text{for all  }  t\geq t_0.
\end{equation}
\end{corollary}

\begin{proof}
It will be noted that $\overline{k} (t)$ and $\underline{k} (t)$ are respectively 
the least upper and the greatest lower bounds  of the sets of all increasing 
function $f(t)$, such that $k(t) \leq f(t)$, respectively $k(t) \geq f(t)$.
Hence, $\overline{k} (t)$ and $\underline{k} (t)$ are  positive and increasing 
functions with $ \underline{k}(t) \leq k(t) \leq \overline{k}(t)$ for all 
$t\geq t_0$.  From Theorem \ref{theorem11}
the inequalities \eqref{eq:25} follow immediately.
\end{proof}

\begin{example}
Let  $k(t) = p t +q(1 + r \sin (\omega t))$ and $\beta(t) = a$, where $p \geq 0$, 
$q \geq 0$,  $ 0 <r \leq 1$, $\omega>0$, and $a>0$.
From \eqref{eq:3}, and Example $\ref{exemple:1}$  we have
$$
 x(t)= k(t)- p/a + ( x_0 - ( k_0 - p/a )) e^{ -a(t-t_0) } 
- \frac{r q \omega }{a^2 + \omega^2} [ \phi (t) - \phi (t_0) e^{- a( t-t_0) }],
$$
where $x_0=x(t_0)$, $k_{0} =k(t_0)$, and 
$\phi(t) = ( \omega \sin (\omega t) + a \cos (\omega t) ) $.
It will be noted that, for a large values of $t$, we have
$$
  x(t) - k (t) \approx  -p/a - \frac{r q \omega }{a^2 + \omega^2} \phi (t).
$$
On the other hand, let $\vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t) $ and $\widetilde{k} (t)$  be defined by
$$
 \vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t)=  p t + q(1-r), \quad\text{and}\quad
  \widetilde{k} (t) =  p t + q(1+r).
$$
Obviously, $\vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}}$ and $\widetilde{k}$ are non decreasing functions and 
satisfy the inequalities
$$
 \vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t) \leq \underline{k}(t) \leq k(t) \leq \overline{k}(t) 
\leq \widetilde{k} (t), \; \; \text{  for all  }  t\geq t_0.
$$
It follows from Corollary~$\ref{corolary11}$, that
$$
 \vtop{\hbox{$x$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t)   \leq x(t) \leq \widetilde{x} (t), \quad \text{for all}  
t\geq t_0,
$$
where
\begin{gather*}
\vtop{\hbox{$x$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t)=  \vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}}(t) - p/a 
+  (    \vtop{\hbox{$x$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}}_0 - ( \vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}}_0 - p/a )) e^{ -  a(t-t_0) }, \\
 \widetilde{x} (t) = \widetilde{k}(t) - p/a 
 + (\widetilde{x}_0 - ( \widetilde{k}_0 - p/a ) ) e^{ -  a(t-t_0) },
\end{gather*}
are respectively the solutions of \eqref{eq:1} with carrying capacities  
$\vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t)$ and $\widetilde{k} (t)$ respectively.
Figures $\ref{fig1}$ and $\ref{fig2}$ illustrates respectively
the cases $p>0$ and $p=0$.
\end{example}

\begin{figure}[htbp]
  \begin{center}
  \includegraphics[width=0.48\textwidth]{fig1a} % Figure_1_increase
  \includegraphics[width=0.48\textwidth]{fig1b} \\ % Figure_2_increase
(a) $x_0<k_0$ \hfil (b) $x_0>k_0$
  \end{center} 
  \caption{Representation of the solution $x(t)$ (solid line) with its lower 
and upper bound solutions $\vtop{\hbox{$x$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}}(t)$
  and $\widetilde{x}(t)$ (long dashed line), and the carrying capacity $k(t)$ 
(black line) when $p>0$.}
  \label{fig1}
\end{figure}

\begin{figure}[htbp]
  \begin{center}
 \includegraphics[width=0.48\textwidth]{fig2a} % Figure_1_sinus
 \includegraphics[width=0.48\textwidth]{fig2b} \\ % Figure_2_sinus
(a) $x_0<k_0$ \hfil (b)  $x_0>k_0$
  \end{center} 
  \caption{Representation of the solution $x(t)$ (solid line) with its 
lower and upper bound solutions $\vtop{\hbox{$x$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}}(t)$
  and $\widetilde{x}(t)$ (long dashed line), and the carrying capacity 
$k(t)$ (black line) when $p=0$.}
  \label{fig2}
\end{figure}


The following corollary is an immediate consequence of Theorem~\ref{theorem11}.

\begin{corollary}[Decreasing case]\label{corolary111}
Let  $\overline{k}, \underline{k} : I \to (0,+\infty)$ be defined by
$$
 \overline{k}(t) = \max \{k(\tau):\tau \geq t\} \quad \text{and }\quad
 \underline{k} (t) = \min \{k(\tau) : t_0 \leq \tau \leq t \},
$$
and let $ \underline{x}(t)$  and $\overline{x}(t)$ be respectively the solutions 
of the auxiliary problems \eqref{eq:20}, with 
$\underline{x}(t_0) = \overline{x}(t_0) = x(t_0)$. Then
$$
 \underline{x}(t) \leq x(t) \leq \overline{x}(t), \quad \text{for all  } 
 t\geq t_0.
$$
\end{corollary}

The proof can be done in a  similar way as done in the proof of
 Corollary \ref{corolary11}. Hence it is omitted.

\begin{example} \rm
Let  $k(t) = p e^{-\sigma (t - t_0)} (1 + r \sin (\omega t) )$ and 
$\beta(t) = a$, where $p > 0$,
$\sigma \geq 0$,  $ 0 <r \leq 1$, $\omega>0$, and $a>0$. 
Two cases would be considered. If $a \neq \sigma$,
the solution of the problem \eqref{eq:1} is 
\begin{align*}
x(t) &=  e^{- a(t-t_0)} \big[ \frac{ap}{a-\sigma}( e^{(a-\sigma) (t-t_0)} -1 )
 +  \frac{rap}{(a-\sigma)^2 + \omega^2}(e^{(a-\sigma) (t-t_0)} \varphi (t) 
- \varphi(t_0) ) \big] \\
&\quad + x_0 e^{- a(t - t_0)},
%\label{eq:31}
\end{align*}
where $\varphi(t) = (a-\sigma) \sin (\omega t)  - \omega \cos(\omega t)  $.
 Otherwise, the solution is 
$$
 x(t) = e^{- a(t-t_0)} \big[ ap ( t - \frac{r}{\omega} \cos (\omega t) ) 
- ap ( t_0 - \frac{r}{\omega} \cos (\omega t_0) ) + x_0  \big].
$$
In both cases, let $\vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t) $ and $\widetilde{k} (t)$  be defined by
$$
 \vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t)=  p e^{-\sigma (t - t_0)}(1-r), \quad
  \widetilde{k} (t) =  p e^{-\sigma (t - t_0)}(1+r).
$$
Obviously, $\vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}}$ and $\widetilde{k}$ are non increasing functions 
and satisfy the inequalities
$$
 \vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t) \leq \underline{k}(t) \leq k(t) \leq \overline{k}(t) 
\leq \widetilde{k} (t), \quad \text{for all  }  t\geq t_0.
$$
It follows from Corollary $\ref{corolary111}$, that
$$
 \vtop{\hbox{$x$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t)   \leq x(t) \leq \widetilde{x} (t), \quad \text{for all  }  
t\geq t_0,
$$
where
\begin{gather*}
 \vtop{\hbox{$x$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t)=  \frac{(1 - r)ap}{a-\sigma}\big( e^{- \sigma(t-t_0)} 
- e^{- a(t-t_0)}   \big) + x_0 e^{- a(t-t_0)},
\\
 \widetilde{x} (t) = \frac{(1 + r)ap}{a-\sigma}\big( e^{- \sigma(t-t_0)} 
- e^{- a(t-t_0)} \big) + x_0 e^{- a(t-t_0)},
\end{gather*}
are respectively the solutions of \eqref{eq:1} with carrying capacities
 $\vtop{\hbox{$k$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t)$ and $\widetilde{k} (t)$
respectively for the case $a \neq \sigma$. In the case $a = \sigma$, 
$\vtop{\hbox{$x$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t)$ and $\widetilde{x} (t)$ are given by
$$
 \vtop{\hbox{$x$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}} (t)= e^{- a(t-t_0)} ( ap (1-r)(t-t_0) + x_0   ), \quad 
 \widetilde{x} (t) = e^{- a(t-t_0)} ( ap (1 + r)(t-t_0) + x_0   ).
$$
An illustration is given in Figure \ref{fig3}.
\end{example}

\begin{figure}[htbp]
  \begin{center}
 \includegraphics[width=0.48\textwidth]{fig3a} % Figure_decroit1
 \includegraphics[width=0.48\textwidth]{fig3b} \\ % Figure_decroit2
 (a) $x_0<k_0$ \hfil (b) $x_0>k_0$ 
 \end{center}
  \caption{Representation of the solution  $x(t)$ (solid line) with its lower 
and upper bound solutions $\vtop{\hbox{$x$}\hbox{$\widetilde{\vrule height 0pt depth 0pt width 5pt}$}}(t)$   and $\widetilde{x}(t)$ 
(long dashed line), and the carrying capacity $k(t)$ (black line) when 
$a \neq \sigma$.}
  \label{fig3}
\end{figure}


\section{A product decomposition of the solution} \label{sec6}

In this section, we present a decomposition for the solution of
\eqref{eq:intro-linear} and \eqref{eq:intro-logistic} as the product of the
carrying capacity and the solution to
a corresponding differential equation with a constant carrying capacity. 
The next two theorems present these results.

\begin{theorem}[Linear equation]\label{thm3}
Let $\alpha, \beta \in C^{1}(I;(0,+\infty))$, $k(t)=\alpha(t)/\beta(t) > 0 $ 
for all $t\geq t_0$, and $k(t) \in AC^{1}_{\rm loc}(I)$.
We have the following product decomposition of the solution.

(i)  The unique solution to
\begin{equation}\label{eq:40}
 \begin{gathered}
 \dot{\tilde{x}} (t) = \alpha(t) - \big(\beta(t) - \frac{\dot{k}(t)}{k(t)} \big) 
{\tilde{x}} (t), \quad t \geq t_0, \\
 \tilde{x}(t_0) = \tilde{x}_0, 
 \end{gathered} 
\end{equation}
is 
\begin{equation}\label{eq:41}
 \tilde{x}(t)  = k(t)  \omega(t),
\end{equation}
where $\omega(t)$ is the solution of
\begin{equation}\label{eq:42}
 \begin{gathered}
 \dot{\omega} (t) = \beta(t)(1 - {\omega}(t)), \quad t \geq t_0, \\
 \omega(t_0)= \tilde{x}_{0} / k_0.  
 \end{gathered} 
\end{equation}

 (ii) Let $\tilde{\beta}(t)$ be the solution of
\begin{equation}\label{eq:43}
\begin{gathered}
  \dot{\tilde{\beta}}(t)  = 1 - \big(\frac{\dot{\alpha}(t) }{{\alpha}(t)} 
+ \beta(t)\big) \tilde{\beta}(t),  \quad t \geq t_0, \\
 \tilde{\beta}(t_0) > 0. 
 \end{gathered}
\end{equation}
Let us set
\begin{equation}\label{eq:45}
 \tilde{k}(t) = \alpha(t) \tilde{\beta}(t),
\end{equation}
and let $\tilde{\omega}(t)$ be the solution of
\begin{equation}\label{eq:46}
 \begin{gathered}
 \dot{\tilde{\omega}} (t) = \frac{1}{\tilde{\beta}(t)}(1 - \tilde{\omega}(t)), \quad
 t \geq t_0, \\
 \tilde{\omega}(t_0)=\tilde{\omega}_0 = x_{0} / \tilde{k}_0.  
 \end{gathered}
\end{equation}
Then the solution of \eqref{eq:1} passing through the point $(t_0,{x}_0)$ 
is 
\begin{equation}\label{eq:44}
 x(t)  =  {\tilde{k}(t)} \tilde{\omega}(t),
\end{equation}
where $\tilde{k}(t)$ is a solution of \eqref{eq:1} passing through 
the point $(t_0,\tilde{k}_0 )$.
Moreover, 
\begin{equation}\label{eq:limite}
 \lim_{t \to +\infty}  ({x}(t) - \tilde{k}(t) )
 =  \begin{cases}
 0 & if \lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du =+\infty , \\
 ( {x}_0  - \tilde{k}_0   ) e^{-l} 
& if \lim_{t \to +\infty} \int^{t}_{t_0} \beta(u) du =l.
 \end{cases} 
\end{equation}
\end{theorem}

\begin{proof}
(i) From \eqref{eq:2}, the unique solution of \eqref{eq:40} is 
\begin{equation}
\begin{aligned}
 \tilde{x}(t)  
&=   e^{ - \int^{t}_{t_0} (\beta(u) - \frac{\dot{k}(u)}{k(u)})du   } 
\Big( \tilde{x}_0  +  \int^{t}_{t_0} \alpha(\tau) e^{ \int^{\tau}_{t_0} (\beta(u) 
-  \frac{\dot{k}(u)}{k(u)}) du   }    d \tau \Big)  \\
&=   e^{ - \int^{t}_{t_0} \beta(u) du   } e^{  \ln \frac{k(t)}{k_0}    } 
\Big( \tilde{x}_0  +  \int^{t}_{t_0} \alpha(\tau) e^{ \int^{\tau}_{t_0} \beta(u)  du} 
  e^{ - \ln \frac{k(\tau)}{k_0}   }   d \tau \Big)  \\
&=  \frac{k(t)}{k_0} e^{ - \int^{t}_{t_0} \beta(u) du   } 
\Big( \tilde{x}_0  +  k_0 \int^{t}_{t_0}  \frac{\alpha(\tau)}{k(\tau)} 
 e^{ \int^{\tau}_{t_0} \beta(u)  du}   d \tau \Big)  \\
&=  \frac{k(t)}{k_0} e^{ - \int^{t}_{t_0} \beta(u) du   }  
\Big( \tilde{x}_0  +  k_0 (e^{ \int^{t}_{t_0} \beta(u)  du}  - 1   )  \Big)  \\
&=  k(t)  \Big( 1  +   \big( \frac{\tilde{x}_0}{k_0}  - 1   \big) 
e^{ -\int^{t}_{t_0} \beta(u)  du}  \Big)  \\
&=  k(t) \omega(t),
\end{aligned}
	\end{equation}
where $\omega(t)$ is the solution of the initial value problem \eqref{eq:42}.

(ii) From \eqref{eq:45} and \eqref{eq:43}, we show that $\tilde{k}(t)$ 
is the solution of \eqref{eq:1} because 
\begin{equation}\label{eq:47}
 \dot{\tilde{k}}(t) = \dot{\alpha}(t) \tilde{\beta}(t) 
+ \alpha(t) \dot{\tilde{\beta}}(t) = \alpha(t) - \beta(t)\tilde{k}(t).
\end{equation}
Then using \eqref{eq:44}, \eqref{eq:47} and \eqref{eq:46}, we have
\begin{align*}
 \dot{{x}}(t) 
&=   \dot{\tilde{k}}(t) \tilde{\omega}(t) +  \tilde{k}(t) \dot{\tilde{\omega}}(t) \\
&=  \big(\alpha(t) - \beta(t)  \tilde{k}(t)\big) \tilde{\omega}(t) 
 + \frac{\tilde{k}(t)}{ \tilde{\beta}(t)}(1 - \tilde{\omega}(t)) \\
	&=   \alpha(t) \tilde{\omega}(t) - \beta(t)  \tilde{k}(t)\tilde{\omega}(t)  
 + \alpha(t) - \alpha(t) \tilde{\omega}(t)\\
	&=   \alpha(t) - \beta(t)  \tilde{k}(t)\tilde{\omega}(t) \\
	&=   \alpha(t) - \beta(t)  {x}(t).
\end{align*}
Thus, ${x}(t)$ is the solution of \eqref{eq:1} passing through the point 
$(t_0,{x}_0)$. 

In addition, since both $x(t)$ and $\tilde{k}(t)$ are solution of \eqref{eq:1},
 from \eqref{eq:2} we have
$$
 {x}(t) - \tilde{k} (t)
 = ( {x}_0 - \tilde{k}_0 )  e^{ - \int^{t}_{t_0} \beta(u) du }
$$
and \eqref{eq:limite} follows directly.
\end{proof}

The results presented in Theorem~\ref{thm3} can then be applied to the logistic
equation \eqref{eq:intro-logistic}
and we have the following theorem.

\begin{theorem}[Logistic equation]\label{thm3log}
Let $\alpha, \beta \in C^{1}(I;(0,+\infty))$, $k(t)=\alpha(t)/\beta(t) > 0 $ 
for all $t\geq t_0$, and suppose $k(t) \in AC^{1}_{\rm loc}(I)$.
We have the following product decomposition of the solution.

(i)  The unique solution to
\begin{equation} \label{eq:48}
 \begin{gathered}
 \dot{\tilde{x}} (t) = \big(\beta(t) - \frac{\dot{k}(t)}{k(t)}  \big) \tilde{x} (t) 
- \alpha(t) \tilde{x}^2 (t), \quad  t \geq t_0, \\
 \tilde{x}(t_0)= \tilde{x}_0,  
 \end{gathered}
\end{equation}
is 
\begin{equation}\label{eq:49}
 \tilde{x}(t)  = \frac{w(t)}{k(t)},
\end{equation}
where $w(t)$ is the solution of
\begin{equation}\label{eq:50}
\begin{gathered}
 \dot{w} (t) = \beta(t){w}(t)(1 - {w}(t)), \quad t \geq t_0, \\
 w(t_0) = k_0 \tilde{x}_{0} . 
\end{gathered}
\end{equation}

(ii) Let $\tilde{\beta}(t)$ be the solution of
\begin{equation}\label{eq:51}
\begin{gathered}
  \dot{\tilde{\beta}}(t)  = (\frac{\dot{\alpha}(t) }{\alpha(t)} 
+ \beta(t)) \tilde{\beta}(t) - \tilde{\beta}^{2}(t),  \quad t \geq t_0, \\
  \tilde{\beta}(t_0) > 0. 
 \end{gathered}
\end{equation}
Let us set
$$
 \tilde{k}(t) = \frac{\tilde{\beta}(t)}{\alpha(t)},
$$
and let $\tilde{w}(t)$ be the solution of the initial value problem
\begin{equation}\label{eq:54}
\begin{gathered}
 \dot{\tilde{w}} (t) = \tilde{\beta}(t) \tilde{w}(t) (1 - \tilde{w}(t)), \quad
 t \geq t_0, \\
 \tilde{w}(t_0) = \tilde{k}_0 \tilde{x}_{0}. 
 \end{gathered}
\end{equation}
Then the solution of \eqref{eq:intro-logistic} passing through the point
$(t_0,{x}_0)$ is 
\begin{equation}\label{eq:52}
 x(t)  =  \tilde{k}(t) \tilde{w}(t),
\end{equation}
where $\tilde{k}(t)$ is the solution of \eqref{eq:intro-logistic}
 passing through the point $(t_0,\tilde{k}_0)$.
\end{theorem}

\begin{proof} (i) and (ii) are directly obtained from Theorem~\ref{thm3} 
using the application $x \mapsto y = x^{-1}$.
\end{proof}

\subsection*{Conclusion} 
The goal of this study has been to make a qualitative study of the solutions 
of the linear and logistic differential equations.
We have obtained new results on the behaviour and the asymptotic behaviour 
of any solution to these
differential equations in the case where the coefficients are time dependent.
We have studied the monotone case and also the non monotone case when it is 
possible to construct subsolution and supersolution.
Finally we obtain a product decomposition of the solution for some special 
form of these models.


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\end{document}
