A Goal-Directed Decision Procedure for Hybrid PDL

We present the first goal-directed decision procedure for hybrid PDL. The procedure is based on a modular approach that scales from basic modal logic with eventualities to hybrid PDL. The approach is designed so that nominals and eventualities are treated orthogonally. To deal with the complex programs of PDL, the approach employs a novel disjunctive program decomposition. In arguing the correctness of our approach, we employ the novel notion of support generalizing the standard notion of Hintikka sets

Matrix Recruitment and Calcium Sequestration for Spatial Specific Otoconia Development

Otoconia are bio-crystals anchored to the macular sensory epithelium of the utricle and saccule in the inner ear for motion sensing and bodily balance. Otoconia dislocation, degeneration and ectopic calcification can have detrimental effects on balance and vertigo/dizziness, yet the mechanism underlying otoconia formation is not fully understood. In this study, we show that selected matrix components are recruited to form the crystal matrix and sequester Ca2+ for spatial specific formation of otoconia. Specifically, otoconin-90 (Oc90) binds otolin through both domains (TH and C1q) of otolin, but full-length otolin shows the strongest interaction. These proteins have much higher expression levels in the utricle and saccule than other inner ear epithelial tissues in mice. In vivo, the presence of Oc90 in wildtype (wt) mice leads to an enrichment of Ca2+ in the luminal matrices of the utricle and saccule, whereas absence of Oc90 in the null mice leads to drastically reduced matrix-Ca2+. In vitro, either Oc90 or otolin can increase the propensity of extracellular matrix to calcify in cell culture, and co-expression has a synergistic effect on calcification. Molecular modeling and sequence analysis predict structural features that may underlie the interaction and Ca2+-sequestering ability of these proteins. Together, the data provide a mechanism for the otoconial matrix assembly and the role of this matrix in accumulating micro-environmental Ca2+ for efficient CaCO3 crystallization, thus uncover a critical process governing spatial specific otoconia formation

Thermo-Mixed Hydrodynamics of Piston Compression Ring Conjunction

The final publication is available at http://link.springer.com.A new method, comprising Navier-Stokes equations, Rayleigh-Plesset volume fraction equation, an analytical control-volume thermal mixed approach and asperity interactions is reported. The method is employed for prediction of lubricant flow and assessment of friction in the compression ring-cylinder liner conjunction. The results are compared with Reynolds-based laminar flow with Elrod cavitation algorithm. Good conformance is observed for medium load intensity part of the engine cycle. At lighter loads and higher sliding velocity, the new method shows more complex fluid flow, possessing layered flow characteristics on account of pressure and temperature gradient into the depth of the lubricant film, which leads to a cavitation region with vapour content at varied volume fractions. Predictions also conform well to experimental measurements reported by other authors

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases