PLIT: An alignment-free computational tool for identification of long non-coding RNAs in plant transcriptomic datasets

Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs which play a significant role in several biological processes. RNA-seq based transcriptome sequencing has been extensively used for identification of lncRNAs. However, accurate identification of lncRNAs in RNA-seq datasets is crucial for exploring their characteristic functions in the genome as most coding potential computation (CPC) tools fail to accurately identify them in transcriptomic data. Well-known CPC tools such as CPC2, lncScore, CPAT are primarily designed for prediction of lncRNAs based on the GENCODE, NONCODE and CANTATAdb databases. The prediction accuracy of these tools often drops when tested on transcriptomic datasets. This leads to higher false positive results and inaccuracy in the function annotation process. In this study, we present a novel tool, PLIT, for the identification of lncRNAs in plants RNA-seq datasets. PLIT implements a feature selection method based on L1 regularization and iterative Random Forests (iRF) classification for selection of optimal features. Based on sequence and codon-bias features, it classifies the RNA-seq derived FASTA sequences into coding or long non-coding transcripts. Using L1 regularization, 31 optimal features were obtained based on lncRNA and protein-coding transcripts from 8 plant species. The performance of the tool was evaluated on 7 plant RNA-seq datasets using 10-fold cross-validation. The analysis exhibited superior accuracy when evaluated against currently available state-of-the-art CPC tools

A department of methodology can coordinate transdisciplinary sport science support

In the current sporting landscape, it is not uncommon for professional sport teams and organizations to employ multidisciplinary sport science support teams. In these teams and organizations, a “head of performance” may manage a number of sub-discipline specialists with the aim of enhancing athlete performance. Despite the best intentions of multidisciplinary sport science support teams, difficulties associated with integrating sub-disciplines to enhance performance preparation have become apparent. It has been suggested that the problem of integration is embedded in the traditional reductionist method of applied sport science, leading to the eagerness of individual specialists to quantify progress in isolated components. This can lead to “silo” working and decontextualized learning environments that can hinder athlete preparation. To address this challenge, we suggest that ecological dynamics is one theoretical framework that can inform common principles and language to guide the integration of sport science sub-disciplines in a Department of Methodology. The aim of a Department of Methodology would be for group members to work within a unified conceptual framework to (1) coordinate activity through shared principles and language, (2) communicate coherent ideas, and (3) collaboratively design practice landscapes rich in information (i.e., visual, acoustic, proprioceptive and haptic) and guide emergence of multi-dimensional behaviors in athlete performance

A generalized approach for computation of near field radiation pattern of an antenna

A generalized procedure in the form of an analytical formulation for the determination of radiation pattern of an antenna at any arbitrary distance which covers the near field as well as far field is presented in this paper. With the prior knowledge of either the current or field distribution on the radiating aperture, the proposed near field analysis is generic and can be applied for wide variety of antenna elements. The underlying principle of the generalized procedure is tantamount to considering the radiating aperture as an array of point electric and magnetic dipoles. The validity and novelty of the proposed new approach have been substantiated considering an open ended circular cylindrical waveguide and a conical horn as case studies and treating the far field as a special case of near field with pertinent distance criterion. The effect of change in the distance of observation ranging from reactive near field to far field on the radiation patterns of these antennas has also been discussed. The simulation studies reveal that the depicted normalized phase patterns of both the circular waveguide and conical horn follow the changes in the profile of the corresponding amplitude patterns

Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing

Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases is necessary in order to identify the group at risk of visual impairment. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images by employing fuzzy image processing techniques. The paper first introduces the existing systems for diabetic retinopathy screening, with an emphasis on the maculopathy detection methods. The proposed medical decision support system consists of four parts, namely: image acquisition, image preprocessing including four retinal structures localisation, feature extraction and the classification of diabetic retinopathy and maculopathy. A combination of fuzzy image processing techniques, the Circular Hough Transform and several feature extraction methods are implemented in the proposed system. The paper also presents a novel technique for the macula region localisation in order to detect the maculopathy. In addition to the proposed detection system, the paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of our online database compared to other public eye fundus image databases for diabetic retinopathy purposes

Assessing the perceived realism of agent grouping dynamics for adaptation and simulation

Virtual crowds are a prominent feature for a range of applications; from simulations for cultural heritage, to interactive elements in video games. A body of existing research seeks to develop and improve algorithms for crowd simulation, typically with a goal of achieving more realistic behaviours. For applications targeting human interaction however, what is judged as realistic crowd behaviour can be subjective, leading to situations where actual crowd data is not always perceived to be more real than simulation, making it difficult to identify a ground truth. We present a novel method using psychophysics to assess the perceived realism of behavioural features with respect to virtual crowds. In this instance, a focus is given to the grouping dynamics feature, whereby crowd composition in terms of group frequency and density is evaluated through thirty-six conditions based on crowd data captured from three pedestrianised real-world locations. The study, conducted with seventy-eight healthy participants, allowed for the calculation of perceptual thresholds, with configurations identified that appear most real to human viewers. The majority of these configurations correlate with the values extracted from the crowd data, with results suggesting that viewers have more perceptual flexibility when group frequency and density are increased, rather than decreased.</p

Automatic detection of microaneurysms in colour fundus images for diabetic retinopathy screening.

Regular eye screening is essential for the early detection and treatment of the diabetic retinopathy. This paper presents a novel automatic screening system for diabetic retinopathy that focuses on the detection of the earliest visible signs of retinopathy, which are microaneurysms. Microaneurysms are small dots on the retina, formed by ballooning out of a weak part of the capillary wall. The detection of the microaneurysms at an early stage is vital, and it is the first step in preventing the diabetic retinopathy. The paper first explores the existing systems and applications related to diabetic retinopathy screening, with a focus on the microaneurysm detection methods. The proposed decision support system consists of an automatic acquisition, screening and classification of diabetic retinopathy colour fundus images, which could assist in the detection and management of the diabetic retinopathy. Several feature extraction methods and the circular Hough transform have been employed in the proposed microaneurysm detection system, alongside the fuzzy histogram equalisation method. The latter method has been applied in the preprocessing stage of the diabetic retinopathy eye fundus images and provided improved results for detecting the microaneurysms