Investigation of autoclaved cement systems with reactive MgO and Al <inf>2</inf>O<inf>3</inf>-SiO<inf>2</inf> rich fired clay brick

Portland cement (PC) is one of the world's most important building materials, as it is a fundamental component of concrete. However, the manufacture of PC is highly energy intensive and leads to the emission of carbon dioxide (CO2). One promising control measure is the use of industrial wastes and by-products as supplementary cementing materials (SCMs) in order to minimise PC consumption, thereby producing greener cement-based products. This study investigates mechanical properties and phase development of hydrothermally treated cement-ground quartz sand blends with the incorporation of fired clay-brick (CB) waste and reactive magnesia (MgO). The addition of CB waste in autoclaved PC-quartz mortar mixes showed that the alumina-silica rich CB waste was pozzolanic when the Al2O3 accelerated formation and increased crystallinity of Al substituted 1.1 nm tobermorite, resulting in the observed strength gain. Autoclaved mortar specimens incorporating reactive MgO showed a reduction in strength with increasing MgO addition. This was a result of dilution when the relative proportion of PC available for the formation of the strength contributing hydration products including tobermorite is decreased

Transgenic Overexpression of LARGE Induces alpha-Dystroglycan Hyperglycosylation in Skeletal and Cardiac Muscle

Background: LARGE is one of seven putative or demonstrated glycosyltransferase enzymes defective in a common group of muscular dystrophies with reduced glycosylation of alpha-dystroglycan. Overexpression of LARGE induces hyperglycosylation of alpha-dystroglycan in both wild type and in cells from dystroglycanopathy patients, irrespective of their primary gene defect, restoring functional glycosylation. Viral delivery of LARGE to skeletal muscle in animal models of dystroglycanopathy has identical effects in vivo, suggesting that the restoration of functional glycosylation could have therapeutic applications in these disorders. Pharmacological strategies to upregulate Large expression are also being explored.Methodology/Principal Findings: In order to asses the safety and efficacy of long term LARGE over-expression in vivo, we have generated four mouse lines expressing a human LARGE transgene. On observation, LARGE transgenic mice were indistinguishable from the wild type littermates. Tissue analysis from young mice of all four lines showed a variable pattern of transgene expression: highest in skeletal and cardiac muscles, and lower in brain, kidney and liver. Transgene expression in striated muscles correlated with alpha-dystroglycan hyperglycosylation, as determined by immunoreactivity to antibody IIH6 and increased laminin binding on an overlay assay. Other components of the dystroglycan complex and extracellular matrix ligands were normally expressed, and general muscle histology was indistinguishable from wild type controls. Further detailed muscle physiological analysis demonstrated a loss of force in response to eccentric exercise in the older, but not in the younger mice, suggesting this deficit developed over time. However this remained a subclinical feature as no pathology was observed in older mice in any muscles including the diaphragm, which is sensitive to mechanical load-induced damage.Conclusions/Significance: This work shows that potential therapies in the dystroglycanopathies based on LARGE upregulation and alpha-dystroglycan hyperglycosylation in muscle should be safe

Robust textual data streams mining based on continuous transfer learning

Copyright © SIAM. In textual data stream environment, concept drift can occur at any time, existing approaches partitioning streams into chunks can have problem if the chunk boundary does not coincide with the change point which is impossible to predict. Since concept drift can occur at any point of the streams, it will certainly occur within chunks, which is called random concept drift. The paper proposed an approach, which is called chunk level-based concept drift method (CLCD), that can overcome this chunking problem by continuously monitoring chunk characteristics to revise the classifier based on transfer learning in positive and unlabeled (PU) textual data stream environment. Our proposed approach works in three steps. In the first step, we propose core vocabulary-based criteria to justify and identify random concept drift. In the second step, we put forward the extension of LELC (PU learning by extracting likely positive and negative microclusters)[ 1], called soft-LELC, to extract representative examples from unlabeled data, and assign a confidence score to each extracted example. The assigned confidence score represents the degree of belongingness of an example towards its corresponding class. In the third step, we set up a transfer learning-based SVM to build an accurate classifier for the chunks where concept drift is identified in the first step. Extensive experiments have shown that CLCD can capture random concept drift, and outperforms state-of-the-art methods in positive and unlabeled textual data stream environments

Fermions and Type IIB Supergravity On Squashed Sasaki-Einstein Manifolds

We discuss the dimensional reduction of fermionic modes in a recently found class of consistent truncations of type IIB supergravity compactified on squashed five-dimensional Sasaki-Einstein manifolds. We derive the lower dimensional equations of motion and effective action, and comment on the supersymmetry of the resulting theory, which is consistent with N=4 gauged supergravity in $d=5$, coupled to two vector multiplets. We compute fermion masses by linearizing around two $AdS_{5}$ vacua of the theory: one that breaks N=4 down to N=2 spontaneously, and a second one which preserves no supersymmetries. The truncations under consideration are noteworthy in that they retain massive modes which are charged under a U(1) subgroup of the $R$-symmetry, a feature that makes them interesting for applications to condensed matter phenomena via gauge/gravity duality. In this light, as an application of our general results we exhibit the coupling of the fermions to the type IIB holographic superconductor, and find a consistent further truncation of the fermion sector that retains a single spin-1/2 mode.Comment: 43 pages, 2 figures, PDFLaTeX; v2: added references, typos corrected, minor change

Comparison of embedded and added motor imagery training in patients after stroke: Results of a randomised controlled pilot trial

Copyright @ 2012 Schuster et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Motor imagery (MI) when combined with physiotherapy can offer functional benefits after stroke. Two MI integration strategies exist: added and embedded MI. Both approaches were compared when learning a complex motor task (MT): ‘Going down, laying on the floor, and getting up again’. Methods: Outpatients after first stroke participated in a single-blinded, randomised controlled trial with MI embedded into physiotherapy (EG1), MI added to physiotherapy (EG2), and a control group (CG). All groups participated in six physiotherapy sessions. Primary study outcome was time (sec) to perform the motor task at pre and post-intervention. Secondary outcomes: level of help needed, stages of MT-completion, independence, balance, fear of falling (FOF), MI ability. Data were collected four times: twice during one week baseline phase (BL, T0), following the two week intervention (T1), after a two week follow-up (FU). Analysis of variance was performed. Results: Thirty nine outpatients were included (12 females, age: 63.4 ± 10 years; time since stroke: 3.5 ± 2 years; 29 with an ischemic event). All were able to complete the motor task using the standardised 7-step procedure and reduced FOF at T0, T1, and FU. Times to perform the MT at baseline were 44.2 ± 22s, 64.6 ± 50s, and 118.3 ± 93s for EG1 (N = 13), EG2 (N = 12), and CG (N = 14). All groups showed significant improvement in time to complete the MT (p < 0.001) and degree of help needed to perform the task: minimal assistance to supervision (CG) and independent performance (EG1+2). No between group differences were found. Only EG1 demonstrated changes in MI ability over time with the visual indicator increasing from T0 to T1 and decreasing from T1 to FU. The kinaesthetic indicator increased from T1 to FU. Patients indicated to value the MI training and continued using MI for other difficult-to-perform tasks. Conclusions: Embedded or added MI training combined with physiotherapy seem to be feasible and benefi-cial to learn the MT with emphasis on getting up independently. Based on their baseline level CG had the highest potential to improve outcomes. A patient study with 35 patients per group could give a conclusive answer of a superior MI integration strategy.The research project was partially funded by the Gottfried und Julia Bangerter-Rhyner Foundation

High-mass X-ray binaries and OB-runaway stars

High-mass X-ray binaries (HMXBs) represent an important phase in the evolution of massive binary systems. HMXBs provide unique diagnostics to test massive-star evolution, to probe the physics of radiation-driven winds, to study the process of mass accretion, and to measure fundamental parameters of compact objects. As a consequence of the supernova explosion that produced the neutron star (or black hole) in these systems, HMXBs have high space velocities and thus are runaways. Alternatively, OB-runaway stars can be ejected from a cluster through dynamical interactions. Observations obtained with the Hipparcos satellite indicate that both scenarios are at work. Only for a minority of the OB runaways (and HMXBs) a wind bow shock has been detected. This might be explained by the varying local conditions of the interstellar medium.Comment: 15 pages, latex (sty file included) with 5 embedded figures (one in jpg format), to appear in Proc. "Influence of binaries on stellar population studies", Eds. Vanbeveren, Van Rensberge

Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes

Controlled release from zein matrices: Interplay of drug hydrophobicity and pH

Purpose: In earlier studies, the corn protein zein is found to be suitable as a sustained release agent, yet the range of drugs for which zein has been studied remains small. Here, zein is used as a sole excipient for drugs differing in hydrophobicity and isoelectric point: indomethacin, paracetamol and ranitidine. Methods: Caplets were prepared by hot-melt extrusion (HME) and injection moulding (IM). Each of the three model drugs were tested on two drug loadings in various dissolution media. The physical state of the drug, microstructure and hydration behaviour were investigated to build up understanding for the release behaviour from zein based matrix for drug delivery. Results: Drug crystallinity of the caplets increases with drug hydrophobicity. For ranitidine and indomethacin, swelling rates, swelling capacity and release rates were pH dependent as a consequence of the presence of charged groups on the drug molecules. Both hydration rates and release rates could be approached by existing models. Conclusion: Both the drug state as pH dependant electrostatic interactions are hypothesised to influence release kinetics. Both factors can potentially be used factors influencing release kinetics release, thereby broadening the horizon for zein as a tuneable release agent

SentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methods

In the last few years thousands of scientific papers have investigated sentiment analysis, several startups that measure opinions on real data have emerged and a number of innovative products related to this theme have been developed. There are multiple methods for measuring sentiments, including lexical-based and supervised machine learning methods. Despite the vast interest on the theme and wide popularity of some methods, it is unclear which one is better for identifying the polarity (i.e., positive or negative) of a message. Accordingly, there is a strong need to conduct a thorough apple-to-apple comparison of sentiment analysis methods, \textit{as they are used in practice}, across multiple datasets originated from different data sources. Such a comparison is key for understanding the potential limitations, advantages, and disadvantages of popular methods. This article aims at filling this gap by presenting a benchmark comparison of twenty-four popular sentiment analysis methods (which we call the state-of-the-practice methods). Our evaluation is based on a benchmark of eighteen labeled datasets, covering messages posted on social networks, movie and product reviews, as well as opinions and comments in news articles. Our results highlight the extent to which the prediction performance of these methods varies considerably across datasets. Aiming at boosting the development of this research area, we open the methods' codes and datasets used in this article, deploying them in a benchmark system, which provides an open API for accessing and comparing sentence-level sentiment analysis methods

Moisture transport by Atlantic tropical cyclones onto the North American continent

Tropical Cyclones (TCs) are an important source of freshwater for the North American continent. Many studies have tried to estimate this contribution by identifying TC-induced precipitation events, but few have explicitly diagnosed the moisture fluxes across continental boundaries. We design a set of attribution schemes to isolate the column-integrated moisture fluxes that are directly associated with TCs and to quantify the flux onto the North American Continent due to TCs. Averaged over the 2004–2012 hurricane seasons and integrated over the western, southern and eastern coasts of North America, the seven schemes attribute 7 to 18 % (mean 14 %) of total net onshore flux to Atlantic TCs. A reduced contribution of 10 % (range 9 to 11 %) was found for the 1980–2003 period, though only two schemes could be applied to this earlier period. Over the whole 1980–2012 period, a further 8 % (range 6 to 9 % from two schemes) was attributed to East Pacific TCs, resulting in a total TC contribution of 19 % (range 17 to 22 %) to the ocean-to-land moisture transport onto the North American continent between May and November. Analysis of the attribution uncertainties suggests that incorporating details of individual TC size and shape adds limited value to a fixed radius approach and TC positional errors in the ERA-Interim reanalysis do not affect the results significantly, but biases in peak wind speeds and TC sizes may lead to underestimates of moisture transport. The interannual variability does not appear to be strongly related to the El Nino-Southern Oscillation phenomenon