Ultrarapid metabolizers of debrisoquine: characterization and PCR-based detection of alleles with duplication of the CYP2D6 gene

During a six-month period 2,221 haemocultures obtained from patients hospitalized in the Faculty Hospital Olomouc were examined. In all 304 isolated bacteria the sensitivity was assessed by the standard dilution micromethod and moreover all positive haemocultures were examined the "direct" disc method. Agreement between the results of the two methods was proved in 84% of pairs of tests and within a range from 67 to 100%, depending on the type of antimicrobial preparation. Based on these findings it may be stated that assessment of the sensitivity by the "direct" method agrees significantly with assessment of the sensitivity according to minimal inhibitory concentrations (MIC). In patients with septicaemia this procedure makes it possible to change empirical antibiotherapy by 24 hours sooner to aimed therapy.     

Thin film evaporation in microchannels with interfacial slip

We investigate the role of interfacial slip on evaporation of a thin liquid film in a microfluidic channel. The effective slip mechanism is attributed to the formation of a depleted layer adhering to the substrate–fluid interface, either in a continuum or in a rarefied gas regime, as a consequence of intricate hydrophobic interactions in the narrow confinement. We appeal to the fundamental principles of conservation in relating the evaporation mechanisms with fluid flow and heat transfer over interfacial scales. We obtain semi-analytical solutions of the pertinent governing equations, with coupled heat and mass transfer boundary conditions at the liquid–vapor interface. We observe that a general consequence of interfacial slip is to elongate the liquid film, thereby leading to a film thickening effect. Thicker liquid films, in turn, result in lower heat transfer rates from the wall to liquid film, and consequently lower mass transfer rates from the liquid film to the vapor phase. Nevertheless, the total mass of evaporation (or equivalently, the net heat transfer) turns out to be higher in case of interfacial slip due to the longer film length. We also develop significant physical insights on the implications of the relative thickness of the depleted layer with reference to characteristic length scales of the microfluidic channel on the evaporation process, under combined influences of the capillary pressure, disjoining pressure, and the driving temperature differential for the interfacial transport.     

Selection of industrial robots using compromise ranking and outranking methods

Selection of a robot for a specific industrial application is one of the most challenging problems in real time manufacturing environment. It has become more and more complicated due to increase in complexity, advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. At present, different types of industrial robots with diverse capabilities, features, facilities and specifications are available in the market. Manufacturing environment, product design, production system and cost involved are some of the most influencing factors that directly affect the robot selection decision. The decision maker needs to identify and select the best suited robot in order to achieve the desired output with minimum cost and specific application ability. This paper attempts to solve the robot selection problem using two most appropriate multi-criteria decision-making (MCDM) methods and compares their relative performance for a given industrial application. The first MCDM approach is ‘VIsekriterijumsko KOmpromisno Rangiranje’ (VIKOR), a compromise ranking method and the other one is ‘ELimination and Et Choice Translating REality’ (ELECTRE), an outranking method. Two real time examples are cited in order to demonstrate and validate the applicability and potentiality of both these MCDM methods. It is observed that the relative rankings of the alternative robots as obtained using these two MCDM methods match quite well with those as derived by the past researchers.     

GPU-based Acceleration of System-level Design Tasks

Many system-level design tasks (e.g., high-level timing analysis, hardware/software partitioning and design space exploration) involve computational kernels that are intractable (usually NP-hard). As a result, they involve high running times even for mid-sized problems. In this paper we explore the possibility of using commodity graphics processing units (GPUs) to accelerate such tasks that commonly arise in the electronic design automation (EDA) domain. We demonstrate this idea via two detailed case studies. The first explores the possibility of using GPUs to speedup standard schedulability analysis problems. The second proposes a GPU-based engine for a general hardware/software design space exploration problem. Not only do these problems commonly arise in the embedded systems domain, their computational kernels turn out to be variants of a combinatorial optimization problem—viz., the knapsack problem—that lies at the heart of several EDA applications. Experimental results show that our GPU-based implementations offer very attractive speedups for the computational kernels (up to 100×), and speedups of up to 17× for the full problem. In contrast to ASIC/FPGA-based accelerators—given that even low-end desktop and notebook computers are now equipped with GPUs—our solution involves no extra hardware cost. Although recent research has shown the benefits of using GPUs for a variety of non-graphics applications (e.g., in databases and bioinformatics), harnessing the parallelism of GPUs to accelerate problems from the EDA domain has not been sufficiently explored so far. We believe that our results and the generality of the core problem that we address will motivate researchers from this community to explore the possibility of using GPUs for a wider variety of problems from the EDA domain.     

An experimental analysis of electrostatically vibrated array of polysilicon cantilevers

Micromechanical cantilevers are one of the most fundamental and widely studied structures in micro-electromechanical systems. Dynamic response of such cantilevers has long been an interesting subject to researchers and different analytical and experimental approaches have been reported to determine it. Theoretical estimation of different damping mechanisms have been reported over years which are relevant particularly in studying the dynamics of the micro-mechanical structures. Most properties and functionalities of the MEMS devices are invariably dependant on the dynamic response of the devices, which in turn depends on the quality factor of the devices or in other words the overall damping present in the system. This paper presents a thorough experimental analysis of vibration characteristics of micro-mechanical cantilevers of different dimensions. Arrays of polysilicon micro-cantilevers of different dimensions have been designed and fabricated using surface micromachining process. The beams are resonated by electrostatic actuation and their vibration characteristics have been observed using Laser Doppler Vibrometer. Also a thorough analysis of modal behaviour of the beams is presented using analytical approach and finite element method based simulation. Different damping mechanisms have been critically reviewed and a semi-analytical estimation of the overall damping is presented. The results are compared with experimental values.     

Bayesian binary kernel probit model for microarray based cancer classification and gene selection

With the arrival of gene expression microarrays a new challenge has opened up for identification or classification of cancer tissues. Due to the large number of genes providing valuable information simultaneously compared to very few available tissue samples the cancer staging or classification becomes very tricky.In this paper we introduce a hierarchical Bayesian probit model for two class cancer classification. Instead of assuming a linear structure for the function that relates the gene expressions with the cancer types we only assume that the relationship is explained by an unknown function which belongs to an abstract functional space like the reproducing kernel Hilbert space. Our formulation automatically reduces the dimension of the problem from the large number of covariates or genes to a small sample size. We incorporate a Bayesian gene selection scheme with the automatic dimension reduction to adaptively select important genes and classify cancer types under an unified model. Our model is highly flexible in terms of explaining the relationship between the cancer types and gene expression measurements and picking up the differentially expressed genes. The proposed model is successfully tested on three simulated data sets and three publicly available leukemia cancer, colon cancer, and prostate cancer real life data sets.     

A layered algorithm for quantifier elimination from linear modular constraints

Linear equalities, disequalities and inequalities on fixed-width bit-vectors, collectively called linear modular constraints, form an important fragment of the theory of fixed-width bit-vectors. We present a practically efficient and bit-precise algorithm for quantifier elimination from conjunctions of linear modular constraints. Our algorithm uses a layered approach, whereby sound but incomplete and cheaper layers are invoked first, and expensive but complete layers are called only when required. We then extend this algorithm to work with arbitrary Boolean combinations of linear modular constraints as well. Experiments on an extensive set of benchmarks demonstrate that our techniques significantly outperform alternative quantifier elimination techniques based on bit-blasting and linear integer arithmetic.     

In vitro growth and drug sensitivity of tumor colony-forming units from human tumor xenografts

To investigate the feasibility of using tissue obtained from human tumor xenografts for in vitro screening of antineoplastic agents, we grew human tumor colony-forming units (CFU) in semisold agar from xenografts serially passaged in nude mice. Growth of human tumor CFU was accomplished from nine xenografts representing five different histological tumor types (ovarian carcinoma, adenocarcinoma of the colon, malignant melanoma, epidermoid carcinoma of the lung, and malignant astrocytoma). Cloning efficiency ranged from 0.04 to 0.1% and showed significant variability both between tumor types and between individual animals bearing the same type of xenograft. A high percentage of tumor CFU was in S phase [47 +/- 20% (S.D.)] as determined by the thymidine "suicide" technique. The number of tumor CFU observed increased linearly with increasing numbers of cells plated. In vitro drug sensitivity of the tumor CFU was assessed to Adriamycin, cis-platinum, and melphalan. The patterns of drug sensitivity were found to be reproducible and stable over a period of 9 months. Drug sensitivity curves to Adriamycin for five xenografts representing four tumor types showed complex patterns with plateau portions similar to those described for tumor CFU from primary tumors. The rank order of sensitivity of the tumors was compared to that of normal granulocyte-macrophage progenitors and, with the exception of the melanomas, was found to correlate well with clinical experience (order of sensitivity = colon less than ovary less than bone marrow). Growth of human tumor CFU from xenografts represents a reproducible and stable means for the study of the biology of tumor CFU and has potential applications as a means for screening new anticancer agents.