Mass spectral analysis and imaging of tissue by ToF-SIMS—The role of buckminsterfullerene, C60, primary ions

Recent developments in desorption/ionisation mass spectrometry techniques have made their application to biological analysis a realistic and successful proposition. Developments in primary ion source technology, mainly through the advent of polyatomic ion beams, have meant that the technique of secondary ion mass spectrometry (SIMS) can now access the depths of information required to allow biological imaging to be a viable option.Here the role of the primary ion C₆₀⁺ is assessed with regard to molecular imaging of lipids and pharmaceuticals within tissue sections. High secondary ion yields and low surface damage accumulation are demonstrated on both model and real biological samples, indicating the high secondary ion efficiency afforded to the analyst by this primary ion when compared to other cluster ion beams used in imaging. The newly developed 40 keV C₆₀⁺ ion source allows the beam to be focused such that high resolution imaging is demonstrated on a tissue sample, and the greater yields allow the molecular signal from the drug raclopride to be imaged within tissue section following in vivo dosing.The localisation shown for this drug alludes to issues regarding the chemical environment affecting the ionisation probability of the molecule; the importance of this effect is demonstrated with model systems and the possibility of using laser post-ionisation as a method for reducing this consequence of bio-sample complexity is demonstrated and discussed.     

New efficient numerical procedures for solving stochastic variational problems with a priori maximum pointwise error estimates

In a previous paper we gave a new formulation and derived the Euler equations and other necessary conditions to solve strong, pathwise, stochastic variational problems with trajectories driven by Brownian motion. Thus, unlike current methods which minimize the control over deterministic functionals (the expected value), we find the control which gives the critical point solution of random functionals of a Brownian path and then, if we choose, find the expected value.This increase in information is balanced by the fact that our methods are anticipative while current methods are not. However, our methods are more directly connected to the theory and meaningful examples of deterministic variational theory and provide better means of solution for free and constrained problems. In addition, examples indicate that there are methods to obtain nonanticipative solutions from our equations although the anticipative optimal cost function has smaller expected value.In this paper we give new, efficient numerical methods to find the solution of these problems in the quadratic case. Of interest is that our numerical solution has a maximal, a priori, pointwise error of O(h3/2) where h is the node size. We believe our results are unique for any theory of stochastic control and that our methods of proof involve new and sophisticated ideas for strong solutions which extend previous deterministic results by the first author where the error was O(h²).We note that, although our solutions are given in terms of stochastic differential equations, we are not using the now standard numerical methods for stochastic differential equations. Instead we find an approximation to the critical point solution of the variational problem using relations derived from setting to zero the directional derivative of the cost functional in the direction of simple test functions.Our results are even more significant than they first appear because we can reformulate stochastic control problems or constrained calculus of variations problems in the unconstrained, stochastic calculus of variations formulation of this paper. This will allow us to find efficient and accurate numerical solutions for general constrained, stochastic optimization problems. This is not yet being done, even in the deterministic case, except by the first author.     

The Laplace transform on time scales revisited

In this work, we reexamine the time scale Laplace transform as defined by Bohner and Peterson [M. Bohner, A. Peterson, Dynamic Equations on Time Scales: An Introduction with Applications, Birkhäuser, Boston, 2001; M. Bohner, A. Peterson, Laplace transform and Z-transform: Unification and extension, Methods Appl. Anal. 9 (1) (2002) 155-162]. In particular, we give conditions on the class of functions which have a transform, develop an inversion formula for the transform, and further, we provide a convolution for the transform. The notion of convolution leads to considering its algebraic structure—in particular the existence of an identity element—motivating the development of the Dirac delta functional on time scales. Applications and examples of these concepts are given.     

Generalized optical logic elements - GOLEs

A Generalized Optical Logic Element or GOLE is device that performs any of the 16 Boolean logic operations on signals in an optical beam with very fast switching among functions. The advantages of a generalized or universal gate in manufacturing are obvious. Extremely flexible functioning becomes possible if the GOLE functionality is switched in response to earlier computations. Likewise Field Programmable Gate Arrays or FPGAs can be used to fix the GOLE functions, making one of the most powerful and flexible processor units ever designed - called a Field GOLE. Such systems can be made in bulk optics to utilize Spatial Light Modulator or SLM capabilities, but integrated optics on silicon will be the choice for most applications. GOLEs can be generalized in several ways to become Fredkin gates and generalized Fredkin gates. They can also be cascaded similarly to electronic gates.     

The probability of generating a soluble subgroup of a finite group

It is proved that for finite groups G, the probability thattwo randomly chosen elements of G generate a soluble subgrouptends to zero as the index of the largest soluble normal subgroupof G tends to infinity.     

Generalized KKM Type Theorems in FC-Spaces with Applications (I)

The class KKM(X,Y) (resp., s-KKM(X,Y,Z)) of set-valued mappings with KKM (resp., s-KKM) property is introduced in FC-spaces without any convexity structure. Some generalized KKM (resp., s-KKM) type theorems are proved in FC-spaces under much weak assumptions. As applications, some new section theorems and coincidence theorems are established in FC-spaces. These theorems generalize many known results in literature. The further applications of these results will be given in a follow-up paper.