The Problems and Techniques section features two papers: one on differential equations, and one on sums containing binomial coefficients and their logarithms. The deflection u(x) of a beam at point x can be described by an ordinary differential equation (ODE) of fourth order, such as, for instance, $$ \hspace*{58pt}\frac{ \mbox{ \textit{d}$^{\mbox{\fontsize{6pt}{6pt}\selectfont 4}}$\textit{u}(\textit{x})}} {\mbox{ \textit{dx}$^{\mbox{\fontsize{6pt}{6pt}\selectfont 4}}$}} \mbox{ = – 100,\qquad 0 $\leq$ \textit{x} $\leq$ 1.} $$ In this specific example the vertical load on the beam is uniform, as is the bending stiffness, and the beam has length 1. A unique solution u(x) exists if appropriate boundary conditions are prescribed, e.g., u(0) = u(1) = u$^{\prime}$(0) = u$^{\prime}$(1) = 0, which means that the beam is fixed at both ends. But what if the beam isn't fixed and we don't know the boundary conditions precisely? What if we have only bounds on the deflection and rotation at the endpoints, that is, inequalities of the form –1 $\leq$ u(x) $\leq$ 1 and –1 $\leq$ u$^{\prime}$(x) $\leq$ 1 for x = 0 and x = 1? Does a solution still exist? Enrique Castillo, Antonio Conejo, Carmen Castillo, and Roberto Mínguez, in “Solving Ordinary Differential Equations with Range Conditions,” show that it does indeed. The authors present a method to determine all solutions for linear ODEs whose boundary conditions are linear and are prescribed within intervals (or ranges) rather than at single points. Based on the inequalities in the boundary conditions, they formulate a system of linear inequalities. The solutions to this system represent coefficients in a linear combination that describes all solutions of the ODE. The authors also discuss tests for existence and uniqueness of solutions. The second paper, “Difference of Sums Containing Products of Binomial Coefficients and Their Logarithms,” is concerned with the expression $$ \hspace*{59pt}\displaystyle\frac{\mbox{1}} {\mbox{2$^{\mbox{\fontsize{6pt}{6pt}\selectfont \textit{n}}}$}} \mbox{$\displaystyle\sum_{\mbox{\fontsize{6pt}{6pt}\selectfont \textit{k} = 0}} ^{\mbox{\fontsize{6pt}{6pt}\selectfont \textit{n}}}$} \left(\displaystyle\frac{\mbox{1}}{\mbox{2}} \mbox{$\alpha_{\mbox{\fontsize{6pt}{6pt}\selectfont \textit{k}}}$} \mbox{ ln } \alpha_{\mbox{\fontsize{6pt}{6pt}\selectfont \textit{k}}}-\beta_{\mbox{\fontsize{6pt}{6pt}\selectfont \textit{k}}} \mbox{ ln } \beta_{\mbox{\fontsize{6pt}{6pt}\selectfont \textit{k}}} \right)\mbox{,} \qquad \mbox{$\alpha_{\mbox{\fontsize{6pt}{6pt}\selectfont \textit{k}}}$} \equiv {\mbox{\textit{n} + 1}\choose \mbox{\textit{k}}}\mbox{,}\quad \mbox{$\beta_{\mbox{\fontsize{6pt}{6pt}\selectfont \textit{k}}}$} \equiv {\mbox{\textit{n}}\choose \mbox{\textit{k}}}\mbox{,} $$ which occurs in an analysis of covert communication channels and is related to the capacity of the covert channel. Authors Allen Miller and Ira Moskowitz use binomial identities to simplify the expression, show that it increases monotonically with n, and prove that it converges to ln 2 as n $\rightarrow \infty$.
Read full abstract