Halting the hallmarks: a cellular automaton model of early cancer growth inhibition

Cancer treatment is a fragmented and varied process, as “cancer” is really hundreds of different diseases. The “hallmarks of cancer” proposed by Hanahan and Weinberg (Cell 100(1):57–70, 2000) are a framework for viewing cancer within a common set of underlying principles—ten properties that are common to almost all cancers, allowing them to grow uncontrollably and ravage the body. We used a cellular automaton model of tumour growth paired with lattice Boltzmann methods modelling oxygen flow to simulate combination drugs targeted at knocking out pairs of hallmarks. We found that knocking out some pairs of cancer-enabling hallmarks did not prevent tumour formation, while other pairs significantly prevent tumour growth (\(p=0.0004\) using Wilcoxon signed-rank adjusted with the Bonferroni correction for multiple comparisons). This is not what would be expected from models of knocking out the hallmarks individually, as many pairs did not have an additive effect but had either no statistically significant effect or a multiplicative one. We propose that targeting certain pairs of cancer hallmarks, specifically cancers ability to induce blood vessel development paired with another cancer hallmark, could prove an effective cancer treatment option.     

Separation of highly viscous fluid threads in branching microchannels

We experimentally study the transport properties of threads made of high-viscosity fluids flowing in a sheath of miscible, low-viscosity fluids in bifurcating microchannels. A viscous filament is generated using a square hydrodynamic focusing section by injecting a ‘thick’ fluid into the central channel and a ‘thin’ fluid from the side channels. This method allows us to produce miscible fluid threads of various sizes and lateral positions in a straight channel and enables the systematic study of the downstream thread’s response to flow partitioning in branching microfluidic networks at low Reynolds numbers. A phase diagram detailing the various flow patterns observed at the first bifurcation, including thread folding, transport, and fouling, is presented along with transition lines. We also examine the role of viscous buckling instabilities on thread behavior and the formation of complex viscous mixtures and stratifications at the small scale. This work shows the possibility to finely control thread trajectory and stability as well as manipulate the structural arrangement of high-viscosity multiphase flows in complex microfluidic systems.     

Analysis of two authorization protocols using Colored Petri Nets

To prevent unauthorized access to protected trusted platform module (TPM) objects, authorization protocols, such as the object-specific authorization protocol (OSAP), have been introduced by the trusted computing group (TCG). By using OSAP, processes trying to gain access to the protected TPM objects need to prove their knowledge of relevant authorization data before access to the objects can be granted. Chen and Ryan’s 2009 analysis has demonstrated OSAP’s authentication vulnerability in sessions with shared authorization data. They also proposed the Session Key Authorization Protocol (SKAP) with fewer stages as an alternative to OSAP. Chen and Ryan’s analysis of SKAP using ProVerif proves the authentication property. The purpose of this paper was to examine the usefulness of Colored Petri Nets (CPN) and CPN Tools for security analysis. Using OSAP and SKAP as case studies, we construct intruder and authentication property models in CPN. CPN Tools is used to verify the authentication property using a Dolev–Yao-based model. Verification of the authentication property in both models using the state space tool produces results consistent with those of Chen and Ryan.     

Segmentation and recognition of phonetic features in handwritten Pitman shorthand

There is a wish to be able to enter text into mobile computing devices at the speed of speech. Only handwritten shorthand schemes can achieve this data recording rate. A new, overall solution to the segmentation and recognition of phonetic features in Pitman shorthand is proposed in this paper. Approaches to the recognition of consonant outlines, vowel and diphthong symbols and shortforms, which are different components of Pitman shorthand, are presented. A new rule is introduced to solve the issue of smooth junctions in the consonant outlines which was normally the bottleneck for recognition. Experiments with a set of 1127 consonant outlines, 2039 vowels and diphthongs and 841 shortforms from three shorthand writers have demonstrated that the proposed solution is quite promising. The recognition accuracies for consonant outlines, vowels and diphthongs, and shortforms achieved 75.33%, 96.86% and 91.86%, respectively. From the evaluation of 461 outlines with smooth junction, the introduction of the new rule has a great positive effect on the performance of the solution. The recognition accuracy of smooth junction improves from 37.53% to 93.41% given a writing time increase of 14.42%.     

Toward a perceptual theory of flow visualization.

Currently, most researchers in visualization pay very little attention to vision science. The exception is when the effective use of color is the subject. Little research in flow visualization includes a discussion of the related perceptual theory. Nor does it include an evaluation of effectiveness of the display techniques that are generated. This is so, despite Laidlaw's paper showing that such an evaluation is relatively straightforward. Of course, it's not always necessary to relate visualization research to perceptual theory. If the purpose of the research is to increase the efficiency of an algorithm, then the proper test is one of efficiency, not of perceptual validity. But when a new representation of data is the subject of research, addressing how perceptually effective it is - either by means of a straightforward empirical comparison with existing methods or analytically, relating the new mapping to perceptual theory - should be a matter of course. A strong interdisciplinary approach, including the disciplines of perception, design, and computer science will produce better science and better design in that empirically and theoretically validated visual display techniques will result.     

Development of a Weather Forecasting Code: A Case Study

Computational science is increasingly supporting advances in scientific and engineering knowledge. The unique constraints of these types of projects result in a development process that differs from the process more traditional information technology projects use. This article reports the results of the sixth case study conducted under the support of the Darpa High Productivity Computing Systems Program. The case study aimed to investigate the technical challenges of code development in this environment, understand the use of development tools, and document the findings as concrete lessons learned for other developers' benefit. The project studied here is a major component of a weather forecasting system of systems. It includes complex behavior and interaction of several individual physical systems (such as the atmosphere and the ocean). This article describes the development of the code and presents important lessons learned.     

A Numerical Study of Diagonally Split Runge–Kutta Methods for PDEs with Discontinuities

Diagonally split Runge–Kutta (DSRK) time discretization methods are a class of implicit time-stepping schemes which offer both high-order convergence and a form of nonlinear stability known as unconditional contractivity. This combination is not possible within the classes of Runge–Kutta or linear multistep methods and therefore appears promising for the strong stability preserving (SSP) time-stepping community which is generally concerned with computing oscillation-free numerical solutions of PDEs. Using a variety of numerical test problems, we show that although second- and third-order unconditionally contractive DSRK methods do preserve the strong stability property for all time step-sizes, they suffer from order reduction at large step-sizes. Indeed, for time-steps larger than those typically chosen for explicit methods, these DSRK methods behave like first-order implicit methods. This is unfortunate, because it is precisely to allow a large time-step that we choose to use implicit methods. These results suggest that unconditionally contractive DSRK methods are limited in usefulness as they are unable to compete with either the first-order backward Euler method for large step-sizes or with Crank–Nicolson or high-order explicit SSP Runge–Kutta methods for smaller step-sizes. We also present stage order conditions for DSRK methods and show that the observed order reduction is associated with the necessarily low stage order of the unconditionally contractive DSRK methods. The work of C.B. Macdonald was partially supported by an NSERC Canada PGS-D scholarship, a grant from NSERC Canada, and a scholarship from the Pacific Institute for the Mathematical Sciences (PIMS). The work of S. Gottlieb was supported by AFOSR grant number FA9550-06-1-0255. The work of S.J. Ruuth was partially supported by a grant from NSERC Canada.