Feasibility assessment of the interactive use of a Monte Carlo algorithm in treatment planning for intraoperative electron radiation therapy

This work analysed the feasibility of using a fast, customized Monte Carlo (MC) method to perform accurate computation of dose distributions during pre- and intraplanning of intraoperative electron radiation therapy (IOERT) procedures. The MC method that was implemented, which has been integrated into a specific innovative simulation and planning tool, is able to simulate the fate of thousands of particles per second, and it was the aim of this work to determine the level of interactivity that could be achieved. The planning workflow enabled calibration of the imaging and treatment equipment, as well as manipulation of the surgical frame and insertion of the protection shields around the organs at risk and other beam modifiers. In this way, the multidisciplinary team involved in IOERT has all the tools necessary to perform complex MC dosage simulations adapted to their equipment in an efficient and transparent way. To assess the accuracy and reliability of this MC technique, dose distributions for a monoenergetic source were compared with those obtained using a general-purpose software package used widely in medical physics applications. Once accuracy of the underlying simulator was confirmed, a clinical accelerator was modelled and experimental measurements in water were conducted. A comparison was made with the output from the simulator to identify the conditions under which accurate dose estimations could be obtained in less than 3 min, which is the threshold imposed to allow for interactive use of the tool in treatment planning. Finally, a clinically relevant scenario, namely early-stage breast cancer treatment, was simulated with pre- and intraoperative volumes to verify that it was feasible to use the MC tool intraoperatively and to adjust dose delivery based on the simulation output, without compromising accuracy. The workflow provided a satisfactory model of the treatment head and the imaging system, enabling proper configuration of the treatment planning system and providing good accuracy in the dosage simulation.

Application of Independent Components Analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration

In recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained

Finite size effects in the specific heat of glass-formers

We report clear finite size effects in the specific heat and in the relaxation times of a model glass former at temperatures considerably smaller than the Mode Coupling transition. A crucial ingredient to reach this result is a new Monte Carlo algorithm which allows us to reduce the relaxation time by two order of magnitudes. These effects signal the existence of a large correlation length in static quantities.

An application of fuzzy logic for hardware/software partitioning in embedded systems

Hardware/Software partitioning (HSP) is a key task for embedded system co-design. The main goal of this task is to decide which components of an application are to be executed in a general purpose processor (software) and which ones, on a specific hardware, taking into account a set of restrictions expressed by metrics. In last years, several approaches have been proposed for solving the HSP problem, directed by metaheuristic algorithms. However, due to diversity of models and metrics used, the choice of the best suited algorithm is an open problem yet. This article presents the results of applying a fuzzy approach to the HSP problem. This approach is more flexible than many others due to the fact that it is possible to accept quite good solutions or to reject other ones which do not seem good. In this work we compare six metaheuristic algorithms: Random Search, Tabu Search, Simulated Annealing, Hill Climbing, Genetic Algorithm and Evolutionary Strategy. The presented model is aimed to simultaneously minimize the hardware area and the execution time. The obtained results show that Restart Hill Climbing is the best performing algorithm in most cases.

Algorithm for the detection of outliers based on the theory of rough sets

Outliers are objects that show abnormal behavior with respect to their context or that have unexpected values in some of their parameters. In decision-making processes, information quality is of the utmost importance. In specific applications, an outlying data element may represent an important deviation in a production process or a damaged sensor. Therefore, the ability to detect these elements could make the difference between making a correct and an incorrect decision. This task is complicated by the large sizes of typical databases. Due to their importance in search processes in large volumes of data, researchers pay special attention to the development of efficient outlier detection techniques. This article presents a computationally efficient algorithm for the detection of outliers in large volumes of information. This proposal is based on an extension of the mathematical framework upon which the basic theory of detection of outliers, founded on Rough Set Theory, has been constructed. From this starting point, current problems are analyzed; a detection method is proposed, along with a computational algorithm that allows the performance of outlier detection tasks with an almost-linear complexity. To illustrate its viability, the results of the application of the outlier-detection algorithm to the concrete example of a large database are presented.

An encyclopædia of plants; comprising the description, specific character, culture, history, application in the arts, and every other desirable particular respecting all the plants indigenous, cultivated in, or introduced to Britain, combining all the advantages of a Linnean and Jussieuean species plantarum, an historia plantarum, a grammar of botany, and a dictionary of botany and vegetable culture. The whole in English; with the synonymes of the commoner plants in the different European and other languages ...

"Names of books referred to": p. [vii]-xiii.

A dictionary of chemistry, exhibiting the present state of the theory and practice of that science, its application to natural philosophy, the processes of manufactures, metallurgy, and numerous other arts dependant on the properties and habitudes of bodies, in the mineral, vegetable, and animal kingdoms. With a considerable number of tables, expressing the elective attractions, specific gravities, comparative heats, component parts, combinations, and other affections of the objects of chemical research. Illustrated with engravings.

Paged continuously.

The field book of manures; or The American muck book; treating of the nature, properties, sources, history, and operations of all the principal fertilizers and manures in common use, with specific directions for their preparation, preservation, and application to the soil and to crops; as combined with the leading principles of practical and scientific agriculture; drawn from authentic sources, actual experience, and personal observation ...

Mode of access: Internet.

First additional supplement to Loudon's encyclopaedia of plants : comprising the specific character, description, culture, history, application in the arts, and every other desirable particular respecting all the plants originated in, or introduced into Britain, between the first publication of the work in 1829, and January, 1840 /

Includes bibliographical references and a new general index to the whole work.

An encyclopædia of plants : comprising the specific character, description, culture, history, application in the arts, and every other desirable particular respecting all the plants indigenous, cultivated in, or introduced to Britain /

Includes bibliographical references (p. [vii]-xiv).

The application of silviculture in controlling the specific gravity of wood /

"Supersedes U.S. Department of Agriculture Tech. Bull. No. 168 of same title."

Loudon's encyclopaedia of plants; comprising the specific character, description, culture, history, application in the arts, and every other desirable particular respecting all the plants indigenous to, cultivated in, or introduced into Britain.

"Names of books referred to": p. [vii]-xiv.

Finite mixture regression model with random effects: application to neonatal hospital length of stay

A two-component mixture regression model that allows simultaneously for heterogeneity and dependency among observations is proposed. By specifying random effects explicitly in the linear predictor of the mixture probability and the mixture components, parameter estimation is achieved by maximising the corresponding best linear unbiased prediction type log-likelihood. Approximate residual maximum likelihood estimates are obtained via an EM algorithm in the manner of generalised linear mixed model (GLMM). The method can be extended to a g-component mixture regression model with the component density from the exponential family, leading to the development of the class of finite mixture GLMM. For illustration, the method is applied to analyse neonatal length of stay (LOS). It is shown that identification of pertinent factors that influence hospital LOS can provide important information for health care planning and resource allocation. (C) 2002 Elsevier Science B.V. All rights reserved.

Specific modulation of airway epithelial tight junctions by apical application of an occludin peptide

Tight junctions are directly involved in regulating the passage of ions and macromolecules (gate functions) in epithelial and endothelial cells. The modulation of these gate functions to transiently regulate the paracellular permeability of large solutes and ions could increase the delivery of pharmacological agents or gene transfer vectors. To reduce the inflammatory responses caused by tight junction-regulating agents, alternative strategies directly targeting specific tight junction proteins could prove to be less toxic to airway epithelia. The apical delivery of peptides corresponding to the first extracellular loop of occludin to transiently modulate apical paracellular flux has been demonstrated in intestinal epithelia. We hypothesized that apical application of these occludin peptides could similarly modulate tight junction permeability in airway epithelia. Thus, we investigated the effects of apically applied occludin peptide on the paracellular permeability of molecular tracers and viral vectors in well differentiated human airway epithelial cells. The effects of occludin peptide on cellular toxicity, tight junction protein expression and localization, and membrane integrity were also assessed. Our data showed that apically applied occludin peptide significantly reduced transepithelial resistance in airway epithelia and altered tight junction permeability in a concentration-dependent manner. These alterations enhanced the paracellular flux of dextrans as well as gene transfer vectors. The occludin peptide redistributed occludin but did not alter the expression or distribution of ZO-1, claudin-1, or claudin-4. These data suggest that specific targeting of occludin could be a better-suited alternative strategy for tight junction modulation in airway epithelial cells compared with current agents that modulate tight junctions.