Rapid match-searching for gene silencing assessment

Motivation: Gene silencing, also called RNA interference, requires reliable assessment of silencer impacts. A critical task is to find matches between silencer oligomers and sites in the genome, in accordance with one-to-many matching rules (G-U matching, with provision for mismatches). Fast search algorithms are required to support silencer impact assessments in procedures for designing effective silencer sequences.Results: The article presents a matching algorithm and data structures specialized for matching searches, including a kernel procedure that addresses a Boolean version of the database task called the skyline search. Besides exact matches, the algorithm is extended to allow for the location-specific mismatches applicable in plants. Computational tests show that the algorithm is significantly faster than suffix-tree alternatives. © The Author 2010. Published by Oxford University Press. All rights reserved.

A rapid and simple method of assaying plants transformed with hygromycin or PPT resistance genes

A very simple leaf assay is described that rapidly and reliably identifies transgenic plants expressing the hygromycin resistance gene, hph or the phosphinothricin resistance gene, bar. Leaf tips were cut from plants propagated either in the glasshouse or in tissue culture and the cut surface embedded in solid medium containing the appropriate selective agent. Non-transgenic barley or rice leaf tips had noticeable symptoms of either bleaching or necrosis after three days on the medium and were completely bleached or necrotic after one week. Transgenic leaf tips remained green and healthy over this period. This gave unambiguous discrimination between transgenic and non-transgenic plants. The leaf assay was also effective for dicot plants tested (tobacco and peas).

Influence of kaolinite/carbon black hybridization on combustion and thermal decomposition behaviors of NR composites

A series of NR composites filled with modified kaolinite (MK), carbon black (CB) and the hybrid fillercontained MK and CB, were prepared by melt blending. The microstructure, combustion and thermaldecomposition behaviors of NR composites were characterized by TEM, XRD, infrared spectroscopy, conecalorimeter test (CCT) and thermal-gravimetric analysis (TG). The results show that the filler hybridizationcan improve the dispensability and shape of the kaolinite sheets in the rubber matrix and change theinterface bond between kaolinite particles and rubber molecules. NR-3 filled by 10 phr MK and 40 phr CBhas the lowest heat release rate (HRR), mass loss rate (MLR), total heat release (THR), smoke productionrate (SPR) and the highest char residue among all the NR composites. Therefore, the hybridization ofthe carbon black particles with the kaolinite particles can effectively improve the thermal stability andcombustion properties of NR composites.

Correlating flow induced shear stress and chondrocytes activity in micro-porous scaffold using computational fluid dynamics and rapid prototyping

Flow induced shear stress plays an important role in regulating cell growth and distribution in scaffolds. This study sought to correlate wall shear stress and chondrocytes activity for engineering design of micro-porous osteochondral grafts based on the hypothesis that it is possible to capture and discriminate between the transmitted force and cell response at the inner irregularities. Unlike common tissue engineering therapies with perfusion bioreactors in which flow-mediated stress is the controlling parameter, this work assigned the associated stress as a function of porosity to influence in vitro proliferation of chondrocytes. D-optimality criterion was used to accommodate three pore characteristics for appraisal in a mixed level fractional design of experiment (DOE); namely, pore size (4 levels), distribution pattern (2 levels) and density (3 levels). Micro-porous scaffolds (n=12) were fabricated according to the DOE using rapid prototyping of an acrylic-based bio-photopolymer. Computational fluid dynamics (CFD) models were created correspondingly and used on an idealized boundary condition with a Newtonian fluid domain to simulate the dynamic microenvironment inside the pores. In vitro condition was reproduced for the 3D printed constructs seeded by high pellet densities of human chondrocytes and cultured for 72 hours. The results showed that cell proliferation was significantly different in the constructs (p<0.05). Inlet fluid velocity of 3×10-2mms-1 and average shear stress of 5.65×10-2 Pa corresponded with increased cell proliferation for scaffolds with smaller pores in hexagonal pattern and lower densities. Although the analytical solution of a Poiseuille flow inside the pores was found insufficient for the description of the flow profile probably due to the outside flow induced turbulence, it showed that the shear stress would increase with cell growth and decrease with pore size. This correlation demonstrated the basis for determining the relation between the induced stress and chondrocyte activity to optimize microfabrication of engineered cartilaginous constructs.

Development of the Rapid Assessment, Prioritisation and Referral Tool (RAPaRT) for multidisciplinary teams in emergency care settings

Objective This investigation utilised the expertise of allied members of multidisciplinary teams working in emergency care settings to develop and validate a Rapid Assessment Prioritisation and Referral Tool (RAPaRT). This instrument is intended for use among patients (with non-life threatening acuity) presenting to emergency care settings to indicate when referral to an allied member of the multidisciplinary team is warranted. Method This three stage instrument development and validation study included: a Delphi panel process to determine key criteria to guide instrument development and identify potential items to be carried forward for testing (stage 1); a prospective cohort of consecutive admissions (n=153) to investigate item sensitivity and specificity and retain only the most suitable items (stage 2); then final consultation with the Delphi panel to ensure the final instrument was clinically amenable (stage 3). Results 23 potential items were identified following stage 1. At the completion of item sensitivity and specificity analysis and in consultation with the Delphi panel, seven items were retained in the instrument. Area under the receiver operating characteristic curve was 0.803 for these seven items in predicting when a referral was warranted. Final consultation with the Delphi panel members also resulted in the addition of an open ended (eighth) item to allow description of any infrequent, but important, reason for referral. Conclusions The RAPaRT has demonstrated substantial promise as an efficient clinically amenable instrument to assist multidisciplinary teams in emergency care settings. Further research to investigate the wider implementation of the RAPaRT is warranted.

Development of empirical equations for irradiance profile of a standard parabolic trough collector using Monte Carlo ray tracing technique

Irradiance profile around the receiver tube (RT) of a parabolic trough collector (PTC) is a key effect of optical performance that affects the overall energy performance of the collector. Thermal performance evaluation of the RT relies on the appropriate determination of the irradiance profile. This article explains a technique in which empirical equations were developed to calculate the local irradiance as a function of angular location of the RT of a standard PTC using a vigorously verified Monte Carlo ray tracing model. A large range of test conditions including daily normal insolation, spectral selective coatings and glass envelop conditions were selected from the published data by Dudley et al. [1] for the job. The R2 values of the equations are excellent that vary in between 0.9857 and 0.9999. Therefore, these equations can be used confidently to produce realistic non-uniform boundary heat flux profile around the RT at normal incidence for conjugate heat transfer analyses of the collector. Required values in the equations are daily normal insolation, and the spectral selective properties of the collector components. Since the equations are polynomial functions, data processing software can be employed to calculate the flux profile very easily and quickly. The ultimate goal of this research is to make the concentrating solar power technology cost competitive with conventional energy technology facilitating its ongoing research.

Modeling bus rapid transit station bus queuing for operational analysis

This paper presents mathematical models for BRT station operation, calibrated using microscopic simulation modelling. Models are presented for station capacity and bus queue length. No reliable model presently exists to estimate bus queue length. The proposed bus queue model is analogous to an unsignalized intersection queuing model.

Optimal camera planning under versatile user constraints in multi-camera image processing systems

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

Modeling Bus Rapid Transit station bus queuing for Bus Rapid Transit station bus operation analysis

Stations on Bus Rapid Transit (BRT) lines ordinarily control line capacity because they act as bottlenecks. At stations with passing lanes, congestion may occur when buses maneuvering into and out of the platform stopping lane interfere with bus flow, or when a queue of buses forms upstream of the station blocking inflow. We contend that, as bus inflow to the station area approaches capacity, queuing will become excessive in a manner similar to operation of a minor movement on an unsignalized intersection. This analogy is used to treat BRT station operation and to analyze the relationship between station queuing and capacity. In the first of three stages, we conducted microscopic simulation modeling to study and analyze operating characteristics of the station under near steady state conditions through output variables of capacity, degree of saturation and queuing. A mathematical model was then developed to estimate the relationship between average queue and degree of saturation and calibrated for a specified range of controlled scenarios of mean and coefficient of variation of dwell time. Finally, simulation results were calibrated and validated.

Development of a new signal processing diagnostic tool for vibration signals acquired in transient conditions

The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

False-colour spectrograms of long duration acoustic recordings

Acoustic recordings of the environment are an important aid to ecologists monitoring biodiversity and environmental health. However, rapid advances in recording technology, storage and computing make it possible to accumulate thousands of hours of recordings, of which, ecologists can only listen to a small fraction. The big-data challenge is to visualize the content of long-duration audio recordings on multiple scales, from hours, days, months to years. The visualization should facilitate navigation and yield ecologically meaningful information. Our approach is to extract (at one minute resolution) acoustic indices which reflect content of ecological interest. An acoustic index is a statistic that summarizes some aspect of the distribution of acoustic energy in a recording. We combine indices to produce false-colour images that reveal acoustic content and facilitate navigation through recordings that are months or even years in duration.

Useful field of view test

A test of the useful field of view was introduced more than two decades ago and was designed to reflect the visual difficulties that older adults experience with everyday tasks. Importantly, the useful field of view is one of the most extensively researched and promising predictor tests for a range of driving outcomes measures, including driving ability and crash risk, as well as other everyday tasks. Currently available commercial versions of the test can be administered using personal computers and measure speed of visual processing speed for rapid detection and localization of targets under conditions of divided visual attention and in the presence and absence of visual clutter. The test is believed to assess higher order cognitive abilities, but performance also relies on visual sensory function since targets must be visible in order to be attended to. The format of the useful field of view test has been modified over the years; the original version estimated the spatial extent of useful field of view, while the latest versions measures visual processing speed. While deficits in the useful field of view are associated with functional impairments in everyday activities in older adults, there is also emerging evidence from several research groups that improvements in visual processing speed can be achieved through training. These improvements have been shown to reduce crash risk, and have a positive impact on health and functional well being, with the potential to increase the mobility and hence independence of older adults.

A cognitive processing framework for learning analytics

Incorporating a learner’s level of cognitive processing into Learning Analytics presents opportunities for obtaining rich data on the learning process. We propose a framework called COPA that provides a basis for mapping levels of cognitive operation into a learning analytics system. We utilise Bloom’s taxonomy, a theoretically respected conceptualisation of cognitive processing, and apply it in a flexible structure that can be implemented incrementally and with varying degree of complexity within an educational organisation. We outline how the framework is applied, and its key benefits and limitations. Finally, we apply COPA to a University undergraduate unit, and demonstrate its utility in identifying key missing elements in the structure of the course.