Optimise web browsing on heterogeneous mobile platforms:a machine learning based approach

Web browsing is an activity that billions of mobile users perform on a daily basis. Battery life is a primary concern to many mobile users who often find their phone has died at most inconvenient times. The heterogeneous mobile architecture is a solution for energy-efficient mobile web browsing. However, the current mobile web browsers rely on the operating system to exploit the underlying architecture, which has no knowledge of the individual web workload and often leads to poor energy efficiency. This paper describes an automatic approach to render mobile web workloads for performance and energy efficiency. It achieves this by developing a machine learning based approach to predict which processor to use to run the web browser rendering engine and at what frequencies the processor cores of the system should operate. Our predictor learns offline from a set of training web workloads. The built predictor is then integrated into the browser to predict the optimal processor configuration at runtime, taking into account the web workload characteristics and the optimisation goal: whether it is load time, energy consumption or a trade-off between them. We evaluate our approach on a representative ARM big.LITTLE mobile architecture using the hottest 500 webpages. Our approach achieves 80% of the performance delivered by an ideal predictor. We obtain, on average, 45%, 63.5% and 81% improvement respectively for load time, energy consumption and the energy delay product, when compared to the Linux governo

Prediction of trans-antisense transcripts in Arabidopsis thaliana

BACKGROUND: Natural antisense transcripts (NATs) are coding or non-coding RNAs with sequence complementarity to other transcripts (sense transcripts). These RNAs could potentially regulate the expression of their sense partner(s) at either the transcriptional or post-transcriptional level. Experimental and computational methods have demonstrated the widespread occurrence of NATs in eukaryotes. However, most previous studies only focused on cis-NATs with little attention being paid to NATs that originate in trans. RESULTS: We have performed a genome-wide screen of trans-NATs in Arabidopsis thaliana and identified 1,320 putative trans-NAT pairs. An RNA annealing program predicted that most trans-NATs could form extended double-stranded RNA duplexes with their sense partners. Among trans-NATs with available expression data, more than 85% were found in the same tissue as their sense partners; of these, 67% were found in the same cell as their sense partners at comparable expression levels. For about 60% of Arabidopsis trans-NATs, orthologs of at least one transcript of the pair also had trans-NAT partners in either Populus trichocarpa or Oryza sativa. The observation that 430 transcripts had both putative cis- and trans-NATs implicates multiple regulations by antisense transcripts. The potential roles of trans-NATs in inducing post-transcriptional gene silencing and in regulating alternative splicing were also examined. CONCLUSION: The Arabidopsis transcriptome contains a fairly large number of trans-NATs, whose possible functions include silencing of the corresponding sense transcripts or altering their splicing patterns. The interlaced relationships observed in some cis- and trans-NAT pairs suggest that antisense transcripts could be involved in complex regulatory networks in eukaryotes

Universal Dependencies Parsing for Colloquial Singaporean English

Singlish can be interesting to the ACL community both linguistically as a major creole based on English, and computationally for information extraction and sentiment analysis of regional social media. We investigate dependency parsing of Singlish by constructing a dependency treebank under the Universal Dependencies scheme, and then training a neural network model by integrating English syntactic knowledge into a state-of-the-art parser trained on the Singlish treebank. Results show that English knowledge can lead to 25% relative error reduction, resulting in a parser of 84.47% accuracies. To the best of our knowledge, we are the first to use neural stacking to improve cross-lingual dependency parsing on low-resource languages. We make both our annotation and parser available for further research.Comment: Accepted by ACL 201

The Age-Redshift Relationship of Old Passive Galaxies

We use 32 age measurements of passively evolving galaxies as a function of redshift to test and compare the standard model ($\Lambda$CDM) with the $R_{\rm h}=ct$ Universe. We show that the latter fits the data with a reduced $\chi^2_{\rm dof}=0.435$ for a Hubble constant $H_{0}= 67.2_{-4.0}^{+4.5}$ km $\rm s^{-1}$ $\rm Mpc^{-1}$. By comparison, the optimal flat $\Lambda$CDM model, with two free parameters (including $\Omega_{\rm m}=0.12_{-0.11}^{+0.54}$ and $H_{0}=94.3_{-35.8}^{+32.7}$ km $\rm s^{-1}$ $\rm Mpc^{-1}$), fits the age-\emph{z} data with a reduced $\chi^2_{\rm dof}=0.428$. Based solely on their $\chi^2_{\rm dof}$ values, both models appear to account for the data very well, though the optimized $\Lambda$CDM parameters are only marginally consistent with those of the concordance model ($\Omega_{\rm m}=0.27$ and $H_{0}= 70$ km $\rm s^{-1}$ $\rm Mpc^{-1}$). Fitting the age-$z$ data with the latter results in a reduced $\chi^2_{\rm dof}=0.523$. However, because of the different number of free parameters in these models, selection tools, such as the Akaike, Kullback and Bayes Information Criteria, favour $R_{\rm h}=ct$ over $\Lambda$CDM with a likelihood of $\sim 66.5\%-80.5\%$ versus $\sim 19.5\%-33.5\%$. These results are suggestive, though not yet compelling, given the current limited galaxy age-$z$ sample. We carry out Monte Carlo simulations based on these current age measurements to estimate how large the sample would have to be in order to rule out either model at a $\sim 99.7\%$ confidence level. We find that if the real cosmology is $\Lambda$CDM, a sample of $\sim 45$ galaxy ages would be sufficient to rule out $R_{\rm h}=ct$ at this level of accuracy, while $\sim 350$ galaxy ages would be required to rule out $\Lambda$CDM if the real Universe were instead $R_{\rm h}=ct$.Comment: 36 pages, 13 figures, 1 table; accepted for publication in The Astronomical Journal. arXiv admin note: text overlap with arXiv:1405.238

Ethyl 2-(4-chloro­phenyl)-3-(2,4-di­fluoro­phenoxy)acrylate

In the mol­ecule of the title compound, C17H13ClF2O3, the dihedral angles formed by the aromatic rings of the chloro­benzene and difluoro­benzene groups with the plane of the acrylate unit are 48.85 (12) and 9.07 (14)°, respectively. In the crystal structure, mol­ecules are linked by weak inter­molecular C—H⋯O hydrogen-bond inter­actions, forming chains along the c axis