Rice ragged stunt oryzavirus genome segment S4 could encode an RNA dependent RNA polymerase and a second protein of unknown function

The complete nucleotide sequence of genome segment S4 of rice ragged stunt oryzavirus (RRSV, Thai-isolate) was determined. The 3823 bp sequence contains two large open reading frames (ORFs). ORF1, spanning nucleotides 12 to 3776, is capable of encoding a protein of M(r) 141,380 (P4a). The P4a amino acid sequence predicted from the nucleotide sequence contains sequence motifs conserved in RNA-dependent RNA polymerases (RDRPs). When compared for evolutionary relationships with RDRPs of other reoviruses using the amino acid sequences around the conserved GDD motif, P4a was shown to be more related to Nilaparvata lugens reovirus and reovirus serotype 3 than to rice dwarf phytoreovirus, bovine rotavirus or bluetongue virus. The ORF2, spanning nucleotides 491 to 1468, is out of frame with ORF1 and is capable of encoding a protein of 36, 920 (P4b). Coupled in vitro transcription-translation from cloned ORF2 in wheat germ extract confirmed the existence of ORF2 but in vivo production and possible function of P4b is yet to be determined.

Odometry-driven inference to link multiple exemplars of a location

A major challenge for robot localization and mapping systems is maintaining reliable operation in a changing environment. Vision-based systems in particular are susceptible to changes in illumination and weather, and the same location at another time of day may appear radically different to a system using a feature-based visual localization system. One approach for mapping changing environments is to create and maintain maps that contain multiple representations of each physical location in a topological framework or manifold. However, this requires the system to be able to correctly link two or more appearance representations to the same spatial location, even though the representations may appear quite dissimilar. This paper proposes a method of linking visual representations from the same location without requiring a visual match, thereby allowing vision-based localization systems to create multiple appearance representations of physical locations. The most likely position on the robot path is determined using particle filter methods based on dead reckoning data and recent visual loop closures. In order to avoid erroneous loop closures, the odometry-based inferences are only accepted when the inferred path's end point is confirmed as correct by the visual matching system. Algorithm performance is demonstrated using an indoor robot dataset and a large outdoor camera dataset.

Predicting shot locations in tennis using spatiotemporal data

Over the past decade, vision-based tracking systems have been successfully deployed in professional sports such as tennis and cricket for enhanced broadcast visualizations as well as aiding umpiring decisions. Despite the high-level of accuracy of the tracking systems and the sheer volume of spatiotemporal data they generate, the use of this high quality data for quantitative player performance and prediction has been lacking. In this paper, we present a method which predicts the location of a future shot based on the spatiotemporal parameters of the incoming shots (i.e. shot speed, location, angle and feet location) from such a vision system. Having the ability to accurately predict future short-term events has enormous implications in the area of automatic sports broadcasting in addition to coaching and commentary domains. Using Hawk-Eye data from the 2012 Australian Open Men's draw, we utilize a Dynamic Bayesian Network to model player behaviors and use an online model adaptation method to match the player's behavior to enhance shot predictability. To show the utility of our approach, we analyze the shot predictability of the top 3 players seeds in the tournament (Djokovic, Federer and Nadal) as they played the most amounts of games.

Enhanced geoproof : improved geographic assurance for data in the cloud

The geographic location of cloud data storage centres is an important issue for many organisations and individuals due to various regulations that require data and operations to reside in specific geographic locations. Thus, cloud users may want to be sure that their stored data have not been relocated into unknown geographic regions that may compromise the security of their stored data. Albeshri et al. (2012) combined proof of storage (POS) protocols with distance-bounding protocols to address this problem. However, their scheme involves unnecessary delay when utilising typical POS schemes due to computational overhead at the server side. The aim of this paper is to improve the basic GeoProof protocol by reducing the computation overhead at the server side. We show how this can maintain the same level of security while achieving more accurate geographic assurance.

A web-based approach to data imputation

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Moreover, several optimization techniques are also proposed to reduce the cost of estimating the confidence of imputation queries at both the tuple-level and the database-level. Experiments based on several real-world data collections demonstrate not only the effectiveness of WebPut compared to existing approaches, but also the efficiency of our proposed algorithms and optimization techniques.

Burn healing is dependent on burn site : a quantitative analysis from a porcine burn model

This retrospective review examines healing in different sites on a porcine burn model; 24 pairs of burns on 18 pigs from other animal trials were selected for analysis. Each pair of burns was located on the either the cranial or the caudal part of the thoracic ribs region, on the same side of the animal. The burns were 40-50 cm(2) in size and of uniform deep-dermal partial thickness. Caudal burns healed significantly better than cranial burns, demonstrated by earlier closure of wounds, less scar formation and better cosmesis. To our knowledge, this is the first detailed study reporting that burn healing is affected by location on a porcine burn model. We recommend that similar symmetrical burns should be used for future comparative assessments of burn healing.

Anthropogenic-based regional-scale factors most consistently explain plot-level exotic diversity in grasslands

Aim Evidence linking the accumulation of exotic species to the suppression of native diversity is equivocal, often relying on data from studies that have used different methods. Plot-level studies often attribute inverse relationships between native and exotic diversity to competition, but regional abiotic filters, including anthropogenic influences, can produce similar patterns.We seek to test these alternatives using identical scale-dependent sampling protocols in multiple grasslands on two continents. Location Thirty-two grassland sites in North America and Australia. Methods We use multiscale observational data, collected identically in grain and extent at each site, to test the association of local and regional factors with the plot-level richness and abundance of native and exotic plants. Sites captured environmental and anthropogenic gradients including land-use intensity, human population density, light and soil resources, climate and elevation. Site selection occurred independently of exotic diversity, meaning that the numbers of exotic species varied randomly thereby reducing potential biases if only highly invaded sites were chosen. Results Regional factors associated directly or indirectly with human activity had the strongest associations with plot-level diversity. These regional drivers had divergent effects: urban-based economic activity was associated with high exotic : native diversity ratios; climate- and landscape-based indicators of lower human population density were associated with low exotic : native ratios. Negative correlations between plot-level native and exotic diversity, a potential signature of competitive interactions, were not prevalent; this result did not change along gradients of productivity or heterogeneity. Main conclusion We show that plot-level diversity of native and exotic plants are more consistently associatedwith regional-scale factors relating to urbanization and climate suitability than measures indicative of competition. These findings clarify the long-standing difficulty in resolving drivers of exotic diversity using single-factor mechanisms, suggesting that multiple interacting anthropogenic-based processes best explain the accumulation of exotic diversity in modern landscapes.

Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. 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Location of hydrogen atoms in hydronium jarosite

Various models for the crystal structure of hydronium jarosite were determined from Rietveld refinements against neutron powder diffraction patterns collected at ambient temperature and also single-crystal X-ray diffraction data. The possibility of a lower symmetry space group for hydronium jarosite that has been suggested by the literature was investigated. It was found the space group is best described as R3¯m, the same for other jarosite minerals. The hydronium oxygen atom was found to occupy the 3¯m site (3a Wyckoff site). Inadequately refined hydronium bond angles and bond distances without the use of restraints are due to thermal motion and disorder of the hydronium hydrogen atoms across numerous orientations. However, the acquired data do not permit a precise determination of these orientations; the main feature up/down disorder of hydronium is clear. Thus, the highest symmetry model with the least disorder necessary to explain all data was chosen: The hydronium hydrogen atoms were modeled to occupy an m (18 h Wyckoff site) with 50 % fractional occupancy, leading to disorder across two orientations. A rigid body description of the hydronium ion rotated by 60° with H–O–H bond angles of 112° and O–H distances of 0.96 Å was optimal. This rigid body refinement suggests that hydrogen bonds between hydronium hydrogen atoms and basal sulfate oxygen atoms are not predominant. Instead, hydrogen bonds are formed between hydronium hydrogen atoms and hydroxyl oxygen atoms. The structure of hydronium alunite is expected to be similar given that alunite supergroup minerals are isostructural.

Bluetooth and Wi-Fi MAC address based crowd data collection and monitoring : benefits, challenges and enhancement

This paper firstly presents the benefits and critical challenges on the use of Bluetooth and Wi-Fi for crowd data collection and monitoring. The major challenges include antenna characteristics, environment’s complexity and scanning features. Wi-Fi and Bluetooth are compared in this paper in terms of architecture, discovery time, popularity of use and signal strength. Type of antennas used and the environment’s complexity such as trees for outdoor and partitions for indoor spaces highly affect the scanning range. The aforementioned challenges are empirically evaluated by “real” experiments using Bluetooth and Wi-Fi Scanners. The issues related to the antenna characteristics are also highlighted by experimenting with different antenna types. Novel scanning approaches including Overlapped Zones and Single Point Multi-Range detection methods will be then presented and verified by real-world tests. These novel techniques will be applied for location identification of the MAC IDs captured that can extract more information about people movement dynamics.

Top-k retrieval using facility location analysis

The top-k retrieval problem aims to find the optimal set of k documents from a number of relevant documents given the user’s query. The key issue is to balance the relevance and diversity of the top-k search results. In this paper, we address this problem using Facility Location Analysis taken from Operations Research, where the locations of facilities are optimally chosen according to some criteria. We show how this analysis technique is a generalization of state-of-the-art retrieval models for diversification (such as the Modern Portfolio Theory for Information Retrieval), which treat the top-k search results like “obnoxious facilities” that should be dispersed as far as possible from each other. However, Facility Location Analysis suggests that the top-k search results could be treated like “desirable facilities” to be placed as close as possible to their customers. This leads to a new top-k retrieval model where the best representatives of the relevant documents are selected. In a series of experiments conducted on two TREC diversity collections, we show that significant improvements can be made over the current state-of-the-art through this alternative treatment of the top-k retrieval problem.

The location patterns of artistic clusters : a metro- and neighborhood-level analysis

Analysing census and industry data at the metro and neighbourhood levels, this paper seeks to identify the location characteristics associated with artistic clusters and determine how these characteristics vary across different places. We find that the arts cannot be taken overall as an urban panacea, but rather that their impact is place-specific and policy ought to reflect these nuances. However, our work also finds that, paradoxically, the arts’ role in developing metro economies is as highly underestimated as it is overgeneralised. While arts clusters exhibit unique industry, scale and place-specific attributes, we also find evidence that they cluster in ‘innovation districts’, suggesting they can play a larger role in economic development. To this end, our results raise important questions and point toward new approaches for arts-based urban development policy that look beyond a focus on the arts as amenities to consider the localised dynamics between the arts and other industries.

BDNF SNPs are implicated in comorbid alcohol dependence in schizophrenia but not in alcohol-dependent patients without schizophrenia

Aims The functional BDNF single nucleotide polymorphism (SNP) rs6265 has been associated with many disorders including schizophrenia and alcohol dependence. However, studies have been inconsistent, reporting both positive and negative associations. Comorbid alcohol dependence has a high prevalence in schizophrenia so we investigated the role of rs6265 in alcohol dependence in Australian populations of schizophrenia and alcohol dependent patients. Methods Two BDNF SNPs rs6265 and a nearby SNP rs7103411 were genotyped in a total of 848 individuals. These included a schizophrenia group (n = 157) and a second schizophrenia replication group (n = 235), an alcohol dependent group (n = 231) that had no schizophrenia diagnosis and a group of healthy controls (n = 225). Results Allelic association between rs7103411 and comorbid alcohol dependence was identified (P = 0.044) in the primary schizophrenia sample. In the replication study, we were able to detect allelic associations between both BDNF SNPs and comorbid alcohol dependence (rs6265, P = 0.006; rs7103411, P = 0.014). Moreover, we detected association between both SNPs and risk-taking behaviour after drinking (rs6265, P = 0.005; rs7103411, P = 0.009) and we detected strong association between both SNPs and alcohol dependence in males (rs6265, P = 0.009; rs7103411, P = 0.013) while females showed association with multiple behavioural measures reflecting repetitive alcohol consumption. Haplotype analysis revealed the rs6265-rs7103411 A/C haplotype is associated with comorbid alcohol dependence (P = 0.002). When these SNPs were tested in the non-schizophrenia alcohol dependent group we were unable to detect association. Conclusion We conclude that these BDNF SNPs play a role in development of comorbid alcohol dependence in schizophrenia while our data does not indicate that they play a role in alcohol dependent patients who do not have schizophrenia.

miRPlant : an integrated tool for identification of plant miRNA from RNA sequencing data

Background Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction. Result We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram. Conclusions We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2’–deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.