Monte Carlo Algorithms for Linear Problems

MSC Subject Classification: 65C05, 65U05.Monte Carlo methods are a powerful tool in many fields of mathematics, physics and engineering. It is known, that these methods give statistical estimates for the functional of the solution by performing random sampling of a certain chance variable whose mathematical expectation is the desired functional. Monte Carlo methods are methods for solving problems using random variables. In the book [16] edited by Yu. A. Shreider one can find the following definition of the Monte Carlo method

A comprehensive survey of Rhinonyssid mites (Mesostigmata: Rhinonyssidae) in Northwest Russia: New mite-host associations and prevalence data

Background: Rhinonyssid mites are permanent parasites of birds that inhabit their respiratory tract. There are around 600 species described worldwide and almost all species of birds are found to have embedded rhinonyssid mites. Despite their presumed relevance, these mites are largely unstudied due to the difficulty in sampling them and, therefore, the majority of mite-host associations and species-prevalence data are unknown. New information: In this study, 179 mite specimens belonging to 27 species and eight genera were identified. Notably, 18 new mite-bird associations were documented for the first time, thus increasing the known host range for these mite species. In addition, mite-host associations found in this study were compared with known associations from these species of birds in the European part of Russia and in Europe. Overall, this study represents the largest survey to date carried out on rhinonyssid mites in Russia and one of the most comprehensive datasets on rhinonyssid host-rang

Configurable and Up-Scalable Microfluidic Life Science Platform for Cell Based Assays by Gravity Driven Sequential Perfusion and Diffusion

Microfluidics has the potential to significantly change the way modern biology is performed, but for this potential to be realized several on-chip integration and operation challenges have to be addressed. Critical issues are addressed in this work by first demonstrating an integrated microfluidic tmRNA purification and real time nucleic acid sequence based amplification (NASBA) device. The device is manufactured using soft lithography and a unique silica bead immobilization method for the nucleic acid micro purification column. The integrated device produced a pathogen-specific response in < 3 min from the chip-purified RNA. Further enhancements in the device design and operation that allow the on-chip integration of mammalian cell handling and culturing produced a novel integrated NASBA array. This system demonstrated for the first time that it is possible to combine on a single micro-device cell culture and real time NASBA. In order to expand the cell based assay capabilities of the integrated NASBA array and simplify the device operation novel hydrodynamics and cell sedimentation within trench structures and gravity driven sequential perfusion and diffusion mechanisms were developed. These mechanisms were characterized and implemented within an iCell array device. iCell array can completely integrate cell based assays with bio-analytical read-out. The device is highly scalable and can enable the configurable on-chip integration of procedures such as adherent and non-adherent cell-culture, cellstimulation, cell-lysis, cell-fixing, protein-immunoassays, bright field and fluorescent microscopic monitoring, and real time detection of nucleic acid amplification. The device uses on-board gravity driven flow control which makes it simple and economical to operate with dilute samples (down to 5 cells per reaction), low reagent volumes (50 nL per reaction), highly efficient cell capture (100% capture rates) and single cell protein and gene expression sensitivity. The key results from this work demonstrate a novel technology for versatile, fully integrated microfluidic array platforms. By multiplexing this integrated functionality, the device can be used from routine applications in a biology laboratory to high content screenings

Monte Carlo Algorithm for Solving Integral Equations with Polynomial Non-Linearity. Parallel Implementation

An iterative Monte Carlo algorithm for evaluating linear functionals of the solution of integral equations with polynomial non-linearity is proposed and studied. The method uses a simulation of branching stochastic processes. It is proved that the mathematical expectation of the introduced random variable is equal to a linear functional of the solution. The algorithm uses the so-called almost optimal density function. Numerical examples are considered. Parallel implementation of the algorithm is also realized using the package ATHAPASCAN as an environment for parallel realization.The computational results demonstrate high parallel efficiency of the presented algorithm and give a good solution when almost optimal density function is used as a transition density.Supported by the Ministry of Education, Science and Technology of Bulgaria under Grants # MM 449/94 and # I 501/95 as well as by EC under INCO-Copernicus Project #960237 - STABLE

Statistical Numerical Methods for Eigenvalue Problem. Parallel Implementation

MSC subject classification: 65C05, 65U05.The problem of evaluating the smallest eigenvalue of real symmetric matrices using statistical numerical methods is considered

Hybrid integrated platform of PDMS microfluidics and silica capillary for effective CE and ESI-MS coupling

We present an effective hybrid integration of PDMS microfluidic devices and fused silica capillaries. These hybrid microfluidic integrated PDMS and silica capillary (iPSC) modules exhibit a novel architecture and method for leakage free CE sample injection requiring only a single high voltage source. Use of the iPSC devices is based on a modular approach which allows the capillary to be reused over 1,000 times whilst replacing the fluidics below it for different experiments. Integrating fused silica capillaries with PDMS microfluidics allows the direct application of a wide variety of well established conventional CE protocols for complex analyte separations and ESI-MS coupling, allowing users to focus on the sample analysis rather than the development of new separation protocols. The iPSC fabrication method is simple (3 steps) and quick (7 min)

Could early visual processes be sufficient to label motions?

Biological motion recognition refers to our ability to recognize a scene (motion or movement) based on the evolution of a limited number of points acquired for instance with a motion capture tool. Much work has been done in this direction showing how it is possible to recognize actions based on these points. Following the reference work of Giese and Poggio (giese-poggio:03), we propose an approach to extract such points from a video based on spiking neural networks with rank order coding. Using this estimated set of points, we verify that correct biological motion classification can be perfomed. We use some recent results of Thorpe et al. (rullen-thorpe:01,thorpe-fabre-thorpe:01,delorme-perrinet-etal:01) who claim that the neural information is coded by the relative order in which these neurons fire. This allows to select a limited set of relevant points to be used in the motion classification. Several experiments and comparisons with previous neurological work and models are proposed. The result of these simulations show that information from early visual processes appears to be sufficient to classify biological motion

Monte Carlo algorithms: performance analysis for some computer architectures

AbstractThe paper deals with the performance analysis of three Monte Carlo algorithms for some models of computer architectures. To estimate the performance and the speedup of these algorithms, we introduce a special modification of the criterion for the time required to achieve a preset probable error and consider a serial (von Neumann) architecture, a pipeline architecture, and two MIMD (Multiple Instruction stream, Multiple Data stream) parallel architectures. An approach to constructing Monte Carlo vector algorithms to be efficiently run on pipeline computers has also been considered

Incidence of epulides in the dog: A retrospective histopathological study

The retrospective histopathological study of 468 samples of tumour material obtained from dogs, referred to the Faculty of Veterinary Medicine, Trakia University, Stara Zagora during the period 1991-2000 showed that 29 specimens (6.19%) were epulides. According to their histogenesis, the lesions were classified in two primary groups: reactive lesions – 37.94% and peripheral odontogenic tumours – 62.06%. Epulides were most commonly encountered in males (68.96%) compared to females (31.04%). The average age of affected dogs was 4 years for both genders. In 18 cases (62.06%), the lesions were mandibular whereas in 11 (37.94%) – maxillar. The highest predilection to epulides was observed in German Shepherds – 27.58%