Models of collective cell behaviour with crowding effects : comparing lattice-based and lattice-free approaches

Individual-based models describing the migration and proliferation of a population of cells frequently restrict the cells to a predefined lattice. An implicit assumption of this type of lattice based model is that a proliferative population will always eventually fill the lattice. Here we develop a new lattice-free individual-based model that incorporates cell-to-cell crowding effects. We also derive approximate mean-field descriptions for the lattice-free model in two special cases motivated by commonly used experimental setups. Lattice-free simulation results are compared to these mean-field descriptions and to a corresponding lattice-based model. Data from a proliferation experiment is used to estimate the parameters for the new model, including the cell proliferation rate, showing that the model fits the data well. An important aspect of the lattice-free model is that the confluent cell density is not predefined, as with lattice-based models, but an emergent model property. As a consequence of the more realistic, irregular configuration of cells in the lattice-free model, the population growth rate is much slower at high cell densities and the population cannot reach the same confluent density as an equivalent lattice-based model.

UAS See-and-Avoid using two different approaches of Fuzzy Control

This work presents two UAS See and Avoid approaches using Fuzzy Control. We compare the performance of each controller when a Cross-Entropy method is applied to optimase the parameters for one of the controllers. Each controller receive information from an image processing front-end that detect and track targets in the environment. Visual information is then used under a visual servoing approach to perform autonomous avoidance. Experimental flight trials using a small quadrotor were performed to validate and compare the behaviour of both controllers

Proteomics Approaches in the Identification of Molecular Signatures of Mesenchymal Stem Cells

Mesenchymal stem cells (MSCs) are undifferentiated, multi-potent stem cells with the ability to renew. They can differentiate into many types of terminal cells, such as osteoblasts, chondrocytes, adipocytes, myocytes, and neurons. These cells have been applied in tissue engineering as the main cell type to regenerate new tissues. However, a number of issues remain concerning the use of MSCs, such as cell surface markers, the determining factors responsible for their differentiation to terminal cells, and the mechanisms whereby growth factors stimulate MSCs. In this chapter, we will discuss how proteomic techniques have contributed to our current knowledge and how they can be used to address issues currently facing MSC research. The application of proteomics has led to the identification of a special pattern of cell surface protein expression of MSCs. The technique has also contributed to the study of a regulatory network of MSC differentiation to terminal differentiated cells, including osteocytes, chondrocytes, adipocytes, neurons, cardiomyocytes, hepatocytes, and pancreatic islet cells. It has also helped elucidate mechanisms for growth factor–stimulated differentiation of MSCs. Proteomics can, however, not reveal the accurate role of a special pathway and must therefore be combined with other approaches for this purpose. A new generation of proteomic techniques have recently been developed, which will enable a more comprehensive study of MSCs. Keywords

Practical physical activity measurement in youth : a review of contemporary approaches

Background: The accurate evaluation of physical activity levels amongst youth is critical for quantifying physical activity behaviors and evaluating the effect of physical activity interventions. The purpose of this review is to evaluate contemporary approaches to physical activity evaluation amongst youth. Data sources: The literature from a range of sources was reviewed and synthesized to provide an overview of contemporary approaches for measuring youth physical activity. Results: Five broad categories are described: self-report, instrumental movement detection, biological approaches, direct observation, and combined methods. Emerging technologies and priorities for future research are also identified. Conclusions: There will always be a trade-off between accuracy and available resources when choosing the best approach for measuring physical activity amongst youth. Unfortunately, cost and logistical challenges may prohibit the use of "gold standard" physical activity measurement approaches such as doubly labelled water. Other objective methods such as heart rate monitoring, accelerometry, pedometry, indirect calorimetry, or a combination of measures have the potential to better capture the duration and intensity of physical activity, while self-reported measures are useful for capturing the type and context of activity.

Approaches to learning information literacy : a phenomenographic study

This paper reports on an empirical study that explores the ways students approach learning to find and use information. Based on interviews with 15 education students in an Australian university, this study uses phenomenography as its methodological and theoretical basis. The study reveals that students use three main strategies for learning information literacy: 1) learning by doing; 2) learning by trial and error; and 3) learning by interacting with other people. Understanding the different ways that students approach learning information literacy will assist librarians and faculty to design and provide more effective information literacy education.

Empirical evaluation of alternative approaches in identifying crash hot spots

This study proposes a framework of a model-based hot spot identification method by applying full Bayes (FB) technique. In comparison with the state-of-the-art approach [i.e., empirical Bayes method (EB)], the advantage of the FB method is the capability to seamlessly integrate prior information and all available data into posterior distributions on which various ranking criteria could be based. With intersection crash data collected in Singapore, an empirical analysis was conducted to evaluate the following six approaches for hot spot identification: (a) naive ranking using raw crash data, (b) standard EB ranking, (c) FB ranking using a Poisson-gamma model, (d) FB ranking using a Poisson-lognormal model, (e) FB ranking using a hierarchical Poisson model, and (f) FB ranking using a hierarchical Poisson (AR-1) model. The results show that (a) when using the expected crash rate-related decision parameters, all model-based approaches perform significantly better in safety ranking than does the naive ranking method, and (b) the FB approach using hierarchical models significantly outperforms the standard EB approach in correctly identifying hazardous sites.

Design and rationale of a Prospective, Observational European Multicenter study on the efficacy of acute surgical decompression after traumatic Spinal Cord Injury: the SCI-POEM study

Objectives:Despite many years of research, there is currently no treatment available that results in major neurological or functional recovery after traumatic spinal cord injury (tSCI). In particular, no conclusive data related to the role of the timing of decompressive surgery, and the impact of injury severity on its benefit, have been published to date. This paper presents a protocol that was designed to examine the hypothesized association between the timing of surgical decompression and the extent of neurological recovery in tSCI patients.Study design: The SCI-POEM study is a Prospective, Observational European Multicenter comparative cohort study. This study compares acute (<12 h) versus non-acute (>12 h, <2 weeks) decompressive surgery in patients with a traumatic spinal column injury and concomitant spinal cord injury. The sample size calculation was based on a representative European patient cohort of 492 tSCI patients. During a 4-year period, 300 patients will need to be enrolled from 10 trauma centers across Europe. The primary endpoint is lower-extremity motor score as assessed according to the 'International standards for neurological classification of SCI' at 12 months after injury. Secondary endpoints include motor, sensory, imaging and functional outcomes at 3, 6 and 12 months after injury.Conclusion:In order to minimize bias and reduce the impact of confounders, special attention is paid to key methodological principles in this study protocol. A significant difference in safety and/or efficacy endpoints will provide meaningful information to clinicians, as this would confirm the hypothesis that rapid referral to and treatment in specialized centers result in important improvements in tSCI patients.Spinal Cord advance online publication, 17 April 2012; doi:10.1038/sc.2012.34.

Teaching and assessing critical thinking : the interaction of student approaches to learning and teaching approaches

This study explored the relationship among student approaches to learning and teaching methods on critical thinking in two business units. Key findings included differences in critical thinking scores between student approaches to learning and some evidence of an interaction between student approaches to learning and critical thinking teach method (immersion vs. infusion). Possible explanations for the results are examined and implications for developing critical thinking skills across a degree discussed. What is apparent is that as Universities move towards program-wide level assessment of critical thinking, further work is required in terms of the design of critical thinking teaching interventions and assessment at the unit, school, and degree level. The session will discuss the challenges in developing critical thinking programs in individual units and at the Faculty level.

A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

SOA approaches

As the service-oriented architecture paradigm has become ever more popular, different standardization efforts have been proposed by various consortia to enable interaction among heterongeneous environments through this paradigm. This chapter will overview the most prevalent of these SOA approaches. It will first show how technical services can be described, how they can interact with each other and be discovered by users. Next, the chapter will present different standards to facilitate service composition and to design service-oriented environments in light of a universal understanding of service orientation. The chapter will conclude with a summary and a discussion on the limitations of the reviewed standards along their ability to describe service properties. This paves the way to the next chapters where the USDL standard will be presented, which aims to lift such limitations.

Experimental comparison of odometry approaches

Odometry is an important input to robot navigation systems, and we are interested in the performance of vision-only techniques. In this paper we experimentally evaluate and compare the performance of wheel odometry, monocular feature-based visual odometry, monocular patch-based visual odometry, and a technique that fuses wheel odometry and visual odometry, on a mobile robot operating in a typical indoor environment.