Calculating the Fickian diffusivity for a lattice-based random walk with agents and obstacles of different shapes and sizes

Random walk models are often used to interpret experimental observations of the motion of biological cells and molecules. A key aim in applying a random walk model to mimic an in vitro experiment is to estimate the Fickian diffusivity (or Fickian diffusion coefficient),D. However, many in vivo experiments are complicated by the fact that the motion of cells and molecules is hindered by the presence of obstacles. Crowded transport processes have been modeled using repeated stochastic simulations in which a motile agent undergoes a random walk on a lattice that is populated by immobile obstacles. Early studies considered the most straightforward case in which the motile agent and the obstacles are the same size. More recent studies considered stochastic random walk simulations describing the motion of an agent through an environment populated by obstacles of different shapes and sizes. Here, we build on previous simulation studies by analyzing a general class of lattice-based random walk models with agents and obstacles of various shapes and sizes. Our analysis provides exact calculations of the Fickian diffusivity, allowing us to draw conclusions about the role of the size, shape and density of the obstacles, as well as examining the role of the size and shape of the motile agent. Since our analysis is exact, we calculateDdirectly without the need for random walk simulations. In summary, we find that the shape, size and density of obstacles has a major influence on the exact Fickian diffusivity. Furthermore, our results indicate that the difference in diffusivity for symmetric and asymmetric obstacles is significant.

Achieving a national sample of nursing homes: Balancing probability techniques and practicalities

Sampling design is critical to the quality of quantitative research, yet it does not always receive appropriate attention in nursing research. The current article details how balancing probability techniques with practical considerations produced a representative sample of Australian nursing homes (NHs). Budgetary, logistical, and statistical constraints were managed by excluding some NHs (e.g., those too difficult to access) from the sampling frame; a stratified, random sampling methodology yielded a final sample of 53 NHs from a population of 2,774. In testing the adequacy of representation of the study population, chi-square tests for goodness of fit generated nonsignificant results for distribution by distance from major city and type of organization. A significant result for state/territory was expected and was easily corrected for by the application of weights. The current article provides recommendations for conducting high-quality, probability-based samples and stresses the importance of testing the representativeness of achieved samples.

Web crippling tests of hollow flange channel beams with flanges fastened to supports under two flange load cases

Thin-walled steel hollow flange channel beams known as LiteSteel beam (LSB) sections were developed for use as joists and bearers in various flooring systems. However, they are subjected to specific buckling and failure modes, one of them being web crippling. Despite considerable research in this area, much of the current design predictions for cold-formed steel sections are not directly applicable to LSBs. This is due to the geometry of the LSB, which consists of two closed rectangular hollow flanges, and its unique residual stress characteristics and initial geometric imperfections. Hence an experimental study was conducted to investigate the web crippling behaviour and capacities of LSBs with their flanges fastened to supports. Thirty nine web crippling tests were conducted under two flange load cases (End Two Flange (ETF) and Interior Two Flange (ITF)). Test results showed that for ETF load case the web crippling capacities increased by 50% on average while they increased by 97% for ITF load case when flanges were fastened to supports. Comparison of the ultimate web crippling capacities from tests showed that AS/NZS 4600 and AISI S100 web crippling design equations are conservative for LSB sections with flanges fastened to supports under ETF and ITF load cases. Hence new equations were proposed to determine the web crippling capacities of LSBs with flanges fastened to supports. This paper presents the details of the experimental study into the web crippling behaviour of LSB sections with their flanges fastened under ETF and ITF load cases, and the results.

Shear tests of rivet fastened rectangular hollow flange channel beams

The intermittently rivet fastened Rectangular Hollow Flange Channel Beam (RHFCB) is a new cold-formed hollow section proposed as an alternative to welded hollow flange channel beams. It is a monosymmetric channel section made by intermittently rivet fastening two torsionally rigid rectangular hollow flanges to a web plate. This process enables the end users to choose an effective combination of different web and flange plate sizes to achieve optimum design capacities. Recent research studies focused mainly on the shear behaviour of the most commonly used lipped channel beam and welded hollow flange beam sections. However, the shear behaviour of rivet fastened RHFCB has not been investigated. Therefore a detailed experimental study involving 24 shear tests was undertaken to investigate the shear behaviour and capacities of rivet fastened RHFCBs. Simply supported test specimens of RHFCB with aspect ratios of 1.0 and 1.5 were loaded at mid-span until failure. Comparison of experimental shear capacities with corresponding predictions from the current Australian cold-formed steel design rules showed that the current design rules are very conservative for the shear design of rivet fastened RHFCBs. Significant improvements to web shear buckling occurred due to the presence of rectangular hollow flanges while considerable post-buckling strength was also observed. Such enhancements to the shear behaviour and capacity were achieved with a rivet spacing of 100 mm. Improved design rules were proposed for rivet fastened RHFCBs based on the current shear design equations in AISI S100 and the direct strength method. This paper presents the details of this experimental investigation and the results.

Shear tests of rivet fastened rectangular hollow flange channel beams with web openings

The rivet-fastened rectangular hollow flange channel beam (RHFCB) is a new cold-formed hollow section proposed as an alternative to welded hollow flange steel beams. No research has been undertaken on the shear behaviour and strength of rivet fastened RHFCBs with web openings. Hence a detailed experimental study involving 30 shear tests was undertaken to investigate the shear behaviour and strength of rivet fastened RHFCBs with web openings. Experimental results showed that the current design rules are inadequate for the shear design of Rivet fastened RHFCBs with web openings. Improved design equations have been proposed for the shear strength of rivet fastened RHFCBs with web openings.

Web crippling tests of rivet fastened rectangular hollow flange channel beams under two-flange load cases

The rivet-fastened rectangular hollow flange channel beam (RHFCB) is a new cold-formed hollow section proposed as an alternative to welded hollow flange steel beams. To date, no investigation has been conducted on their web crippling behaviour and strengths. Hence an experimental study was conducted to investigate the web crippling behaviour and capacities of rivet fastened RHFCBs under End Two Flange (ETF) and Interior Two Flange (ITF) load cases. Experimental results showed that the current design rules are unconservative for rivet fastened RHFCB sections under ETF and ITF load cases. Hence new equations were proposed to determine the web crippling capacities of rivet fastened RHFCBs.

Deeper and wider fully convolutional network coupled with conditional random fields for scene labeling

Deep convolutional neural networks (DCNNs) have been employed in many computer vision tasks with great success due to their robustness in feature learning. One of the advantages of DCNNs is their representation robustness to object locations, which is useful for object recognition tasks. However, this also discards spatial information, which is useful when dealing with topological information of the image (e.g. scene labeling, face recognition). In this paper, we propose a deeper and wider network architecture to tackle the scene labeling task. The depth is achieved by incorporating predictions from multiple early layers of the DCNN. The width is achieved by combining multiple outputs of the network. We then further refine the parsing task by adopting graphical models (GMs) as a post-processing step to incorporate spatial and contextual information into the network. The new strategy for a deeper, wider convolutional network coupled with graphical models has shown promising results on the PASCAL-Context dataset.

Repeated random sampling in year 5

As an extension to an activity introducing Year 5 students to the practice of statistics, the software TinkerPlots made it possible to collect repeated random samples from a finite population to informally explore students’ capacity to begin reasoning with a distribution of sample statistics. This article provides background for the sampling process and reports on the success of students in making predictions for the population from the collection of simulated samples and in explaining their strategies. The activity provided an application of the numeracy skill of using percentages, the numerical summary of the data, rather than graphing data in the analysis of samples to make decisions on a statistical question. About 70% of students made what were considered at least moderately good predictions of the population percentages for five yes–no questions, and the correlation between predictions and explanations was 0.78.