Numerical investigation of aerosol particle transport and deposition in realistic lung airway

Different human activities like combustion of fossil fuels, biomass burning, industrial and agricultural activities, emit a large amount of particulates into the atmosphere. As a consequence, the air we inhale contains significant amount of suspended particles, including organic and inorganic solids and liquids, as well as various microorganism, which are solely responsible for a number of pulmonary diseases. Developing a numerical model for transport and deposition of foreign particles in realistic lung geometry is very challenging due to the complex geometrical structure of the human lung. In this study, we have numerically investigated the airborne particle transport and its deposition in human lung surface. In order to obtain the appropriate results of particle transport and deposition in human lung, we have generated realistic lung geometry from the CT scan obtained from a local hospital. For a more accurate approach, we have also created a mucus layer inside the geometry, adjacent to the lung surface and added all apposite mucus layer properties to the wall surface. The Lagrangian particle tracking technique is employed by using ANSYS FLUENT solver to simulate the steady-state inspiratory flow. Various injection techniques have been introduced to release the foreign particles through the inlet of the geometry. In order to investigate the effects of particle size on deposition, numerical calculations are carried out for different sizes of particles ranging from 1 micron to 10 micron. The numerical results show that particle deposition pattern is completely dependent on its initial position and in case of realistic geometry; most of the particles are deposited on the rough wall surface of the lung geometry instead of carinal region.

Agent-based simulation as a component of mixed methods in entrepreneurship research

As a new research method supplementing the existing qualitative and quantitative approaches, agent-based modelling and simulation (ABMS) may fit well within the entrepreneurship field because the core concepts and basic premises of entrepreneurship coincide with the characteristics of ABMS (McKelvey, 2004; Yang & Chandra, 2013). Agent-based simulation is a simulation method based on agent-based models. The agentbased models are composed of heterogeneous agents and their behavioural rules. By repeatedly carrying out agent-based simulations on a computer, the simulations reproduce each agent’s behaviour, their interactive process, and the emerging macroscopic phenomenon according to the flow of time. Using agent-based simulations, researchers may investigate temporal or dynamic effects of each agent’s behaviours.

Wrapped optoelectronic devices and methods for making same

In various embodiments, optoelectronic devices are described herein. The optoelectronic device may include an optoelectronic cell arranged so as to wrap around a central axis wherein the cell includes a first conductive layer, a semi-conductive layer disposed over and in electrical communication with the first conductive layer, and a second conductive layer disposed over and in electrical communication with the semi-conductive layer. In various embodiments, methods for making optoelectronic devices are described herein. The methods may include forming an optoelectronic cell while flat and wrapping the optoelectronic cell around a central axis. The optoelectronic devices may be photovoltaic devices. Alternatively, the optoelectronic devices may be organic light emitting diodes.

Public Health Psychology: A Conceptual and Practical Framework

Introduction For many years concern for public health has transcended the boundaries of the medical sciences and epidemiology. For the last 50 years or so psychologists have been increasingly active in this field. Recently, psychologists have not only begun to see the need to take action to mould health promoting behaviours in individuals, but have also pointed out the need to join in an effort to develop appropriate social, political, economic and institutional conditions which would help to improve the state of public health. Psychologists have postulated the need to distinguish a new subdiscipline of psychology called public health psychology which, together with other disciplines, would further the realization of this goal. In the following article the historical and international context of health psychology and the changing nature of public health are put forward as having important implications for the establishment of a ‘public health psychology’. These implications are addressed in later sections of the article through the description of conceptual and practical framework of public health psychology in which theory, methods and practice are considered. Many aspects of the conceptual and practical framework of public health psychology have relevance to the health social sciences more generally and forming a basis for interdisciplinary work. The framework of public health psychology, together with the obstacles that need to be overcome, are critically examined within an overall approach that contends it is necessary to increase and improve the contribution of health psychology to public health.

Anatomy of a trending topic : Methods for the visualisation of retweet chains [Anatomie eines Trending Topics: Methoden zur Visualisierung von Retweet-Ketten]

Twitter and other social networking sites play an ever more present role in the spread of current events. The dynamics of information dissemination through digital network structures are still relatively unexplored, however. At what time an issue is taken up by whom? Who forwards a message when to whom else? What role do individual communication participants, existing digital communities or the technical foundations of each network platform play in the spread of news? In this chapter we discuss, using the example of a video on a current sociopolitical issue in Australia that was shared on Twitter, a number of new methods for the dynamic visualisation and analysis of communication processes. Our method combines temporal and spatial analytical approaches and provides new insights into the spread of news in digital networks. [Social media dienen immer häufger als Disseminationsmechanismen für Medieninhalte. Auf Twitter ermöglicht besonders die Retweet-Funktion den schnellen und weitläufgen Transfer von Nachrichten. In diesem Beitrag etablieren neue methodische Ansätze zur Erfassung, Visualisierung und Analyse von Retweet-Ketten. Insbesondere heben wir hervor, wie bestehende Netzwerkanalysemethoden ergänzt werden können, um den Ablauf der Weiterleitung sowohl temporal als auch spatial zu erfassen. Unsere Fallstudie demonstriert die verbreitung des videoclips einer am 9. Oktober 2012 spontan gehaltenen Wutrede der australischen Premierministerin Julia Gillard, in der sie Oppositionsführer Tony Abbott als Frauenhasser brandmarkte. Durch die Erfassung von Hintergrunddaten zu den jeweiligen NutzerInnen, die sich an der Weiterleitung des Videoclips beteiligten, erstellen wir ein detailliertes Bild des Disseminationsablaufs im vorliegenden Fall. So lassen sich die wichtigsten AkteurInnen und der Ablauf der Weiterleitung darstellen und analysieren. Daraus entstehen Einblicke in die allgemeinen verbreitungsmuster von Nachrichten auf Twitter].

Stochastic linear multistep methods for the simulation of chemical kinetics

In this paper, we introduce the Stochastic Adams-Bashforth (SAB) and Stochastic Adams-Moulton (SAM) methods as an extension of the tau-leaping framework to past information. Using the theta-trapezoidal tau-leap method of weak order two as a starting procedure, we show that the k-step SAB method with k >= 3 is order three in the mean and correlation, while a predictor-corrector implementation of the SAM method is weak order three in the mean but only order one in the correlation. These convergence results have been derived analytically for linear problems and successfully tested numerically for both linear and non-linear systems. A series of additional examples have been implemented in order to demonstrate the efficacy of this approach.

Narrating the law: Possibilities, pitfalls and prospects

This article explores the possibilities and limits of using narrative analysis as a socio-legal method to illuminate issues of law and justice. It defines narrative analysis, explores the different ways the method has been used in the social sciences, and critically evaluates its use in interdisciplinary research on sexual harassment.

Kits and methods for diagnosis, screening, treatment and disease monitoring [WO 2015048852 A1]

Disclosed are methods for detecting the presence of a carcinoma or an increased likelihood that a carcinoma is present in a subject. More particularly, the present invention discloses methods for diagnosis, screening, treatment and monitoring of carcinomas associated with aberrant DNA methylation of the MED15 promoter region

Using Bourdieu in education research: Theory and methods

This workshop will snapshot Bourdieu's sociology. In recognition of Bourdieu's work as a powerful theoretical instrument to speculate the reproduction of social orders and cultural values, the workshop will firstly discuss the core concepts of habitus, capital, and field – the foundational triad of Bourdieu's sociology. Although Bourdieu's original work was built on some quantitative studies, his sociology has been largely qualitatively used in education research. Different from the bulk of extant research, the workshop will secondly showcase some quantitative and mixed methods research that uses a Bourdieusian framework. Mindful of such a framework helping understand social practice at a macro level, the workshop will then make an attempt to think through the macro and the micro by weaving together Bourdieu's sociology with Garfinkel's ethnomethodology. The workshop will conclude with some reflections and communications in terms of how to better realise the full value of Bourdieu in education research.

Fourier spectral methods for fractional-in-space reaction-diffusion equations

Fractional differential equations are becoming increasingly used as a powerful modelling approach for understanding the many aspects of nonlocality and spatial heterogeneity. However, the numerical approximation of these models is demanding and imposes a number of computational constraints. In this paper, we introduce Fourier spectral methods as an attractive and easy-to-code alternative for the integration of fractional-in-space reaction-diffusion equations described by the fractional Laplacian in bounded rectangular domains ofRn. The main advantages of the proposed schemes is that they yield a fully diagonal representation of the fractional operator, with increased accuracy and efficiency when compared to low-order counterparts, and a completely straightforward extension to two and three spatial dimensions. Our approach is illustrated by solving several problems of practical interest, including the fractional Allen–Cahn, FitzHugh–Nagumo and Gray–Scott models, together with an analysis of the properties of these systems in terms of the fractional power of the underlying Laplacian operator.

Dissimilarities in alignment-free methods for phylogenetic analysis based on genomes

Whole genome sequences are generally accepted as excellent tools for studying evolutionary relationships. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignments could not be directly applied to the whole-genome comparison and phylogenomic studies. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. The “distances” used in these alignment-free methods are not proper distance metrics in the strict mathematical sense. In this study, we first review them in a more general frame — dissimilarity. Then we propose some new dissimilarities for phylogenetic analysis. Last three genome datasets are employed to evaluate these dissimilarities from a biological point of view.

Methods for constructing uncertainty intervals for queries of Bayesian nets

In this paper the issue of finding uncertainty intervals for queries in a Bayesian Network is reconsidered. The investigation focuses on Bayesian Nets with discrete nodes and finite populations. An earlier asymptotic approach is compared with a simulation-based approach, together with further alternatives, one based on a single sample of the Bayesian Net of a particular finite population size, and another which uses expected population sizes together with exact probabilities. We conclude that a query of a Bayesian Net should be expressed as a probability embedded in an uncertainty interval. Based on an investigation of two Bayesian Net structures, the preferred method is the simulation method. However, both the single sample method and the expected sample size methods may be useful and are simpler to compute. Any method at all is more useful than none, when assessing a Bayesian Net under development, or when drawing conclusions from an ‘expert’ system.

Missing in space: An evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes

Background Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. Methods We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Results Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Conclusions Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.

Impacts of tillage and application methods on atrazine and alachlor losses from upland fields: Research paper

The effects of tillage practises and the methods of chemical application on atrazine and alachlor losses through run-off were evaluated for five treatments: conservation (untilled) and surface (US), disk and surface, plow and surface, disk and preplant-incorporated, and plow and preplant-incorporated treatments. A rainfall simulator was used to create 63.5 mm h^-1 of rainfall for 60 min and 127 mm h^-1 for 15 min. Rainfall simulation occurred 24-36 h after chemical application. There was no significant difference in the run-off volume among the treatments but the untilled treatment significantly reduced erosion loss. The untilled treatments had the highest herbicide concentration and the disk treatments were higher than the plow treatments. The surface treatments showed a higher concentration than the incorporated treatments. The concentration of herbicides in the water decreased with time. Among the experimental sites, the one with sandy loam soil produced the greatest losses, both in terms of the run-off volume and herbicide loss. The US treatments had the highest loss and the herbicide incorporation treatments had smaller losses through run-off as the residue cover was effective in preventing herbicide losses. Incorporation might be a favorable method of herbicide application to reduce the herbicide losses by run-off.