Migration of breast cancer cells : understanding the roles of volume exclusion and cell-to-cell adhesion

We study MCF-7 breast cancer cell movement in a transwell apparatus. Various experimental conditions lead to a variety of monotone and nonmonotone responses which are difficult to interpret. We anticipate that the experimental results could be caused by cell-to-cell adhesion or volume exclusion. Without any modeling, it is impossible to understand the relative roles played by these two mechanisms. A lattice-based exclusion process random-walk model incorporating agent-to-agent adhesion is applied to the experimental system. Our combined experimental and modeling approach shows that a low value of cell-to-cell adhesion strength provides the best explanation of the experimental data suggesting that volume exclusion plays a more important role than cell-to-cell adhesion. This combined experimental and modeling study gives insight into the cell-level details and design of transwell assays.

Efficient querying of large process model repositories

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective and less error-prone than developing them from scratch. Since process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. To make our approach more applicable, we consider the semantic similarity between labels. Experiments are conducted to demonstrate that our approach is efficient.

Volcanic stratigraphy, alteration zoning, and vein paragenesis of the Sascha-Pelligrini low-sulphidation epithermal system, Santa Cruz, Argentina

The Sascha-Pelligrini low-sulphidation epithermal system is located on the western edge of the Deseado Massif, Santa Cruz Province, Argentina. Outcrop sampling has returned values of up to 160g/t gold and 796g/t silver, with Mirasol Resources and Coeur D.Alene Mines currently exploring the property. Detailed mapping of the volcanic stratigraphy has defined three units that comprise the middle Jurassic Chon Aike Formation and two units that comprise the upper Jurassic La Matilde Formation. The Chon Aike Formation consists of rhyodacite ignimbrites and tuffs, with the La Matilde Formation including rhyolite ash and lithic tuffs. The volcanic sequence is intruded by a large flow-banded rhyolite dome, with small, spatially restricted granodiorite dykes and sills cropping out across the study area. ASTER multispectral mineral mapping, combined with PIMA (Portable Infrared Mineral Analyser) and XRD (X-ray diffraction) analysis defines an alteration pattern that zones from laumontite-montmorillonite, to illite-pyritechlorite, followed by a quartz-illite-smectite-pyrite-adularia vein selvage. Supergene kaolinite and steam-heated acid-sulphate kaolinite-alunite-opal alteration horizons crop out along the Sascha Vein trend and Pelligrini respectively. Paragenetically, epithermal veining varies from chalcedonic to saccharoidal with minor bladed textures, colloform/crustiform-banded with visible electrum and acanthite, crustiform-banded grey chalcedonic to jasperoidal with fine pyrite, and crystalline comb quartz. Geothermometry of mineralised veins constrains formation temperatures from 174.8 to 205.1¡ÆC and correlates with the stability field for the interstratified illite-smectite vein selvage. Vein morphology, mineralogy and associated alteration are controlled by host rock rheology, permeability, and depth of the palaeo-water table. Mineralisation within ginguro banded veins resulted from fluctuating fluid pH associated with selenide-rich magmatic pulses, pressure release boiling and wall-rock silicate buffering. The study of the Sascha-Pelligrini epithermal system will form the basis for a deposit-specific model helping to clarify the current understanding of epithermal deposits, and may serve as a template for exploration of similar epithermal deposits throughout Santa Cruz.

Effects of opening in the cross girders of the flat bottom rail wagons to the load transferring mechanisms when used as road bridge deck

A Flat Bed Rail Wagon (FBRW) has been proposed as an alternative solution for replacing bridges on low traffic volume roads. The subject matter for this paper is to investigate the impediment to load transfer from cross girders to main girder, through visually identifiable structural flaws. Namely, the effect of having large openings at close proximity to the connection of the main girder to the cross girder of a FBRW was examined. It was clear that openings locally reduce the section modulus of the secondary members; however it was unclear how these reductions would affect the load transfer to the main girder. The results are presented through modeling grillage action for which the loads applied onto the FBRW were distributed through cross girders to the main girder.

A Two-stage information filtering based on rough decision rule and pattern mining

Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.

Blast atlas: a virtual observatory for genomes

Following the completion of the draft Human Genome in 2001, genomic sequence data is becoming available at an accelerating rate, fueled by advances in sequencing and computational technology. Meanwhile, large collections of astronomical and geospatial data have allowed the creation of virtual observatories, accessible throughout the world and requiring only commodity hardware. Through a combination of advances in data management, data mining and visualization, this infrastructure enables the development of new scientific and educational applications as diverse as galaxy classification and real-time tracking of earthquakes and volcanic plumes. In the present paper, we describe steps taken along a similar path towards a virtual observatory for genomes – an immersive three-dimensional visual navigation and query system for comparative genomic data.

Strategies to facilitate grading consistency in large classes

First year undergraduate university classes can be very large, and big student numbers often creates a challenge for instructors to ensure assignments are graded consistently across the cohort. This session describes and demonstrates the use of interactive audience response technology (ART) with assessors (rather than students) to moderate assignment grading. Results from preliminary research indicate this method of moderating the grading of assignments is effective, and achieves more consistent outcomes for students.

Meshless TL and UL approaches for large deformation analysis

To accurately and effectively simulate large deformation is one of the major challenges in numerical modeling of metal forming. In this paper, an adaptive local meshless formulation based on the meshless shape functions and the local weak-form is developed for the large deformation analysis. Total Lagrangian (TL) and the Updated Lagrangian (UL) approaches are used and thoroughly compared each other in computational efficiency and accuracy. It has been found that the developed meshless technique provides a superior performance to the conventional FEM in dealing with large deformation problems for metal forming. In addition, the TL has better computational efficiency than the UL. However, the adaptive analysis is much more efficient using the UL approach than using in the TL approach.

An evidence-based approach to professional development planning in large state educational systems

This paper presents a systems-level approach for adjudicating the prioritization, selection, and planning of inservcie professional development (PD) for teachers. We present a step-by-step model for documenting and assessing system-wide 'bids' for professional development programs

Lean project management in large scale industrial project via standardization

Lean project management is the comprehensive adaption of other lean concept like lean construction, lean manufacturing and lean thinking into project management context. Execution of many similar industrial projects creates the idea of lean project management in companies and rapidly growing in industries. This paper offers the standardization method in order to achieve Lean project management in large scale industrial project. Standardization refers to all activity which makes two projects most identical and unify to each other like standardization of design, reducing output variability, value analysis and strategic management. Although standard project may have minor effi ciency decrease, compare to custom built project; but great advantage of standard project like cost saving, time reduction and quality improvement justify standardization methodology. This paper based on empirical experience in industrial project and theoretical analysis of benefi ts of project standardization.

Psychiatric and substance abuse comorbidity among a large sample of DUI Texas offenders

Research is indicating that individuals who present for DUI treatment may have competing substance abuse and mental health needs. This study aimed to examine the extent of such comorbidity issues among a sample of Texas DUI offenders. Method: Records of 36,372 DUI clients and 308,695 non-DUI clients admitted to Texas treatment programs between 2005 and 2008 were obtained from the State's administrative dataset. The data were analysed to identify the relationship between substance use, psychiatric problems, program completion and recidivism rates. Results: Analysis indicated that while non-DUI clients were more likely to present with more severe illicit substance use problems, DUI clients were more likely to have a primary problem with alcohol. Additionally, a cannabis use problem was also found to be significantly associated with DUI recidivism in the last year. In regards to mental health needs, a major finding was that depression was the most common psychiatric condition reported by DUI clients, including those with more than one DUI offence in the past year. This group were also more at risk of being diagnosed with Bipolar Disorder compared to the general population, and such a diagnosis was also associated with an increased likelihood of not completing treatment. Interestingly, female DUI and non-DUI clients were also more likely to be diagnosed with mental health problems compared to males, as well as more likely to be placed on medications at admission and have problems with methamphetamine, cocaine, and opiates. Conclusion: The findings highlight the complex competing needs of some DUI offenders who enter treatment. The results also suggest that there is a need to utilise mental health and substance abuse screening methods to ensure DUI offenders are directed towards appropriate treatment pathways as well as ensure that such interventions adequately cater for complex substance abuse and psychiatric needs.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

Automatic in-bucket volume estimation for dragline operations

This paper presents a method for calculating the in-bucket payload volume on a dragline for the purpose of estimating the material’s bulk density in real-time. Knowledge of the bulk density can provide instant feedback to mine planning and scheduling to improve blasting and in turn provide a more uniform bulk density across the excavation site. Furthermore costs and emissions in dragline operation, maintenance and downstream material processing can be reduced. The main challenge is to determine an accurate position and orientation of the bucket with the constraint of real-time performance. The proposed solution uses a range bearing and tilt sensor to locate and scan the bucket between the lift and dump stages of the dragline cycle. Various scanning strategies are investigated for their benefits in this real-time application. The bucket is segmented from the scene using cluster analysis while the pose of the bucket is calculated using the iterative closest point (ICP) algorithm. Payload points are segmented from the bucket by a fixed distance neighbour clustering method to preserve boundary points and exclude low density clusters introduced by overhead chains and the spreader bar. A height grid is then used to represent the payload from which the volume can be calculated by summing over the grid cells. We show volume calculated on a scaled system with an accuracy of greater than 95 per cent.