A review selection method using product feature taxonomy

As of today, online reviews have become more and more important in decision making process. In recent years, the problem of identifying useful reviews for users has attracted significant attentions. For instance, in order to select reviews that focus on a particular feature, researchers proposed a method which extracts all associated words of this feature as the relevant information to evaluate and find appropriate reviews. However, the extraction of associated words is not that accurate due to the noise in free review text, and this affects the overall performance negatively. In this paper, we propose a method to select reviews according to a given feature by using a review model generated based upon a domain ontology called product feature taxonomy. The proposed review model provides relevant information about the hierarchical relationships of the features in the review which captures the review characteristics accurately. Our experiment results based on real world review dataset show that our approach is able to improve the review selection performance according to the given criteria effectively.

Identification of eusynstyelamide B as a potent cell cycle inhibitor following the generation and screening of an ascidian-derived extract library using a real time cell analyzer

Ascidians are marine invertebrates that have been a source of numerous cytotoxic compounds. Of the first six marine-derived drugs that made anticancer clinical trials, three originated from ascidian specimens. In order to identify new anti-neoplastic compounds, an ascidian extract library (143 samples) was generated and screened in MDA-MB-231 breast cancer cells using a real-time cell analyzer (RTCA). This resulted in 143 time-dependent cell response profiles (TCRP), which are read-outs of changes to the growth rate, morphology, and adhesive characteristics of the cell culture. Twenty-one extracts affected the TCRP of MDA-MB-231 cells and were further investigated regarding toxicity and specificity, as well as their effects on cell morphology and cell cycle. The results of these studies were used to prioritize extracts for bioassay-guided fractionation, which led to the isolation of the previously identified marine natural product, eusynstyelamide B (1). This bis-indole alkaloid was shown to display an IC50 of 5 μM in MDA-MB-231 cells. Moreover, 1 caused a strong cell cycle arrest in G2/M and induced apoptosis after 72 h treatment, making this molecule an attractive candidate for further mechanism of action studies.

Data as an asset : what the upstream oil & gas industry can learn about ‘big data’ from companies like Facebook

The upstream oil & gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data”—that is, the ability to apply more sophisticated types of analytical tools to information in a way that extracts new insights or creates new forms of value—is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil & gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This paper examines existing data management practices in the upstream oil & gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the Big Data revolution. The comparison shows that, in companies that are leading the Big Data revolution, data is regarded as a valuable asset. The presented evidence also shows, however, that this is usually not true within the oil & gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how upstream oil & gas companies could potentially extract more value from data, and concludes with a series of specific technical and management-related recommendations to this end.

Characterization of acyl chain position in unsaturated phosphatidylcholines using differential mobility-mass spectrometry

Glycerophospholipids (GPs) that differ in the relative position of the two fatty acyl chains on the glycerol backbone (i.e., sn-positional isomers) can have distinct physicochemical properties. The unambiguous assignment of acyl chain position to an individual GP represents a significant analytical challenge. Here we describe a workflow where phosphatidylcholines (PCs) are subjected to ESI for characterization by a combination of differential mobility spectrometry and MS (DMS-MS). When infused as a mixture, ions formed from silver adduction of each phospholipid isomer {e.g., [PC (16:0/18:1) + Ag]+ and [PC (18:1/16:0) + Ag]+} are transmitted through the DMS device at discrete compensation voltages. Varying their relative amounts allows facile and unambiguous assignment of the sn-positions of the fatty acyl chains for each isomer. Integration of the well-resolved ion populations provides a rapid method (< 3 min) for relative quantification of these lipid isomers. The DMS-MS results show excellent agreement with established, but time-consuming, enzymatic approaches and also provide superior accuracy to methods that rely on MS alone. The advantages of this DMS-MS method in identification and quantification of GP isomer populations is demonstrated by direct analysis of complex biological extracts without any prior fractionation.

Reliable Fault Diagnosis for Low-Speed Bearings Using Individually Trained Support Vector Machines With Kernel Discriminative Feature Analysis

This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.

Multiple iterations : mapping the trace

This paper explores the concept that individual dancers leave traces in a choreographer’s body of work and similarly, that dancers carry forward residue of embodied choreographies into other working processes. This presentation will be grounded in a study of the multiple iterations of a programme of solo works commissioned in 2008 from choreographers John Jasperse, Jodi Melnick, Liz Roche and Rosemary Butcher and danced by the author. This includes an exploration of the development by John Jasperse of themes from his solo into the pieces PURE (2008) and Truth, Revised Histories, Wishful Thinking and Flat Out Lies (2009); an adaptation of the solo Business of the Bloom by Jodi Melnick in 2008 and a further adaptation of Business of the Bloom by this author in 2012. It will map some of the developments that occurred through a number of further performances over five years of the solo Shared Material on Dying by Liz Roche and the working process of the (uncompleted) solo Episodes of Flight by Rosemary Butcher. The purpose is to reflect back on authorship in dance, an art form in which lineages of influence can often be clearly observed. Normally, once a choreographic work is created and performed, it is archived through video recording, notation and/or reviews. The dancer is no longer called upon to represent the dance piece within the archive and thus her/his lived presence and experiential perspective disappears. The author will draw on the different traces still inhabiting her body as pathways towards understanding how choreographic movement circulates beyond this moment of performance. This will include the interrogation of ownership of choreographic movement, as once it becomes integrated in the body of the dancer, who owns the dance? Furthermore, certain dancers, through their individual physical characteristics and moving identities, can deeply influence the formation of choreographic signatures, a proposition that challenges the sole authorship role of the choreographer in dance production. This paper will be delivered in a presentation format that will bleed into movement demonstrations alongside video footage of the works and auto-ethnographic accounts of dancing experience. A further source of knowledge will be drawn from extracts of interviews with other dancers including Sara Rudner, Rebecca Hilton and Catherine Bennett.

Template-based circuit understanding

When verifying or reverse-engineering digital circuits, one often wants to identify and understand small components in a larger system. A possible approach is to show that the sub-circuit under investigation is functionally equivalent to a reference implementation. In many cases, this task is difficult as one may not have full information about the mapping between input and output of the two circuits, or because the equivalence depends on settings of control inputs. We propose a template-based approach that automates this process. It extracts a functional description for a low-level combinational circuit by showing it to be equivalent to a reference implementation, while synthesizing an appropriate mapping of input and output signals and setting of control signals. The method relies on solving an exists/forall problem using an SMT solver, and on a pruning technique based on signature computation.

The combination of plant-expressed cellobiohydrolase and low dosages of cellulases for the hydrolysis of sugar cane bagasse

Background The expression of biomass-degrading enzymes (such as cellobiohydrolases) in transgenic plants has the potential to reduce the costs of biomass saccharification by providing a source of enzymes to supplement commercial cellulase mixtures. Cellobiohydrolases are the main enzymes in commercial cellulase mixtures. In the present study, a cellobiohydrolase was expressed in transgenic corn stover leaf and assessed as an additive for two commercial cellulase mixtures for the saccharification of pretreated sugar cane bagasse obtained by different processes. Results Recombinant cellobiohydrolase in the senescent leaves of transgenic corn was extracted using a simple buffer with no concentration step. The extract significantly enhanced the performance of Celluclast 1.5 L (a commercial cellulase mixture) by up to fourfold on sugar cane bagasse pretreated at the pilot scale using a dilute sulfuric acid steam explosion process compared to the commercial cellulase mixture on its own. Also, the extracts were able to enhance the performance of Cellic CTec2 (a commercial cellulase mixture) up to fourfold on a range of residues from sugar cane bagasse pretreated at the laboratory (using acidified ethylene carbonate/ethylene glycol, 1-butyl-3-methylimidazolium chloride, and ball-milling) and pilot (dilute sodium hydroxide and glycerol/hydrochloric acid steam explosion) scales. We have demonstrated using tap water as a solvent (under conditions that mimic an industrial process) extraction of about 90% recombinant cellobiohydrolase from senescent, transgenic corn stover leaf that had minimal tissue disruption. Conclusions The accumulation of recombinant cellobiohydrolase in senescent, transgenic corn stover leaf is a viable strategy to reduce the saccharification cost associated with the production of fermentable sugars from pretreated biomass. We envisage an industrial-scale process in which transgenic plants provide both fibre and biomass-degrading enzymes for pretreatment and enzymatic hydrolysis, respectively.

Product stability and sequestration mechanisms in Solanum tuberosum engineered to biosynthesize high value ketocarotenoids

To produce commercially valuable ketocarotenoids in Solanum tuberosum, the 4, 4′ β-oxygenase (crtW) and 3, 3′ β-hydroxylase (crtZ) genes from Brevundimonas spp. have been expressed in the plant host under constitutive transcriptional control. The CRTW and CRTZ enzymes are capable of modifying endogenous plant carotenoids to form a range of hydroxylated and ketolated derivatives. The host (cv. Désirée) produced significant levels of nonendogenous carotenoid products in all tissues, but at the apparent expense of the economically critical metabolite, starch. Carotenoid levels increased in both wild-type and transgenic tubers following cold storage; however, stability during heat processing varied between compounds. Subcellular fractionation of leaf tissues revealed the presence of ketocarotenoids in thylakoid membranes, but not predominantly in the photosynthetic complexes. A dramatic increase in the carotenoid content of plastoglobuli was determined. These findings were corroborated by microscopic analysis of chloroplasts. In tuber tissues, esterified carotenoids, representing 13% of the total pigment found in wild-type extracts, were sequestered in plastoglobuli. In the transgenic tubers, this proportion increased to 45%, with esterified nonendogenous carotenoids in place of endogenous compounds. Conversely, nonesterified carotenoids in both wild-type and transgenic tuber tissues were associated with amyloplast membranes and starch granules.

Discrete families of Saffman–Taylor fingers with exotic shapes

The mathematical problem of determining the shape of a steadily propagating Saffman–Taylor finger in a rectangular Hele-Shaw cell is known to have a countably infinite number of solutions for each fixed surface tension value. For sufficiently large surface tension values, we find that fingers on higher solution branches are non-convex. The tips of the fingers have increasingly exotic shapes as the branch number increases.

Wound healing from the outback: novel wound healing therapeutics from native Australian plants

Introduction Chronic wounds are an area of major concern. The on-going and in-direct costs are substantial, reaching far beyond the costs of the hospitalization and associated care. As a result, pharmacological therapies have been developed to address treatment insufficiencies, however, the availability of drugs capable of promoting the wound repair process still remain limited. The wound healing properties of various herbal plants is well recognised amongst indigenous Australians. Hence, based on traditional accounts, we evaluated the wound healing potential of two Australian native plants. Methods Bioactive compounds were methanol extracted from dried plant leaves that were commercially sourced. Primary keratinocyte (Kc) and fibroblast (Fib) cells (denoted as Kc269, Kc274, Kc275, Kc276 and Fib274) obtained from surgical discarded tissue were cultured in 48-well plates and incubated (37⁰C, 5% CO2) overnight. The growth media was discarded and replaced with fresh growth media plus various concentrations (15.12 µg/mL, 31.25 µg/mL, 62.5 µg/mL, 125 µg/mL, 250 µg/mL and 500 µg/mL) of the plant extracts. Cellular responses were measured using the alamarBlue® assay and the CyQUANT® assay. Plant extracts in the aqueous phase were prepared by boiling whole leaves in water and taking aqueous phase samples at various (1, 2 , 5 minutes boiling) time points. Plant leaves were either added before the water was boiled (cold boiled) or after the water was boiled (hot boiled). The final concentrations of the aqueous plant extracts were 3.3 ng/mL (± 0.3 ng/mL) per sample. The antimicrobial properties of the plant extracts were tested using the well diffusion assay method against Staphylococcus aureus, Klebsiella pnuemoniae and methicillin resistant S. aureus and Bacillus cereus. Results Assay results from the almarBlue® and CYQUANT® assays indicated that extracts from both native plants at various time points (0, 24 and 48 hours) and concentrations (31.25 mg/mL, 62.5 mg/mL, and 125 mg/mL) were significantly higher (n=3, p=0.03 for Kc269, p=0.04 for Kc274, p=0.02 for Fib274, p=0.04 for Kc275 and p=0.001 for Kc276) compared with the untreated controls. Neither plant extract demonstrated cytotoxic effects. Significant antimicrobial activity against methicillin resistant Staphylococcus aureus (p=0.0009 for hot boiled plant A, n=2, p=0.034 for cold boiled plant A, n=2) K. pnuemoniae (p=0.0009 for hot boiled plant A, n=2, p=0.002 for cold boiled plant A, n=2) and B. cereus (p=0.0009 for hot boiled plant A, n=2, p=0.003 for cold boiled plant A, n=2) was observed at concentrations of 3.2 ng/mL for plant A and 3.4 ng/mL for plant B. Conclusion Both native plants contain bioactive compounds that increase cellular metabolic rates and total nucleic acid content. Neither plant was shown to be cytotoxic. Furthermore, both exhibited significant antimicrobial activity.

Improving PLDA speaker verification using WMFD and linear-weighted approaches in limited microphone data conditions

This paper proposes the addition of a weighted median Fisher discriminator (WMFD) projection prior to length-normalised Gaussian probabilistic linear discriminant analysis (GPLDA) modelling in order to compensate the additional session variation. In limited microphone data conditions, a linear-weighted approach is introduced to increase the influence of microphone speech dataset. The linear-weighted WMFD-projected GPLDA system shows improvements in EER and DCF values over the pooled LDA- and WMFD-projected GPLDA systems in inter-view-interview condition as WMFD projection extracts more speaker discriminant information with limited number of sessions/ speaker data, and linear-weighted GPLDA approach estimates reliable model parameters with limited microphone data.

Automatic clustering of white matter fibers in brain diffusion mri with an application to genetics

To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

Grass pollen allergens

Pollens from diverse grass plants are main contributors to seasonal inhalant allergies worldwide. Grass group 1 and 5 allergens represent highly cross-reactive and potent major allergens, group 5 present only in temperate climate grasses (Pooideae). Depending on climate and region, global sensitization rates to grass pollen vary between 1% to 30% of the general population,. Strong evidence supports specific immunotherapy with grass pollen extracts.

Specific IgE recognition of pollen allergens from subtropic grasses in patients from the subtropics

Background Pollens of subtropical grasses, Bahia (Paspalum notatum), Johnson (Sorghum halepense), and Bermuda (Cynodon dactylon), are common causes of respiratory allergies in subtropical regions worldwide. Objective To evaluate IgE cross-reactivity of grass pollen (GP) found in subtropical and temperate areas. Methods Case and control serum samples from 83 individuals from the subtropical region of Queensland were tested for IgE reactivity with GP extracts by enzyme-linked immunosorbent assay. A randomly sampled subset of 21 serum samples from patients with subtropical GP allergy were examined by ImmunoCAP and cross-inhibition assays. Results Fifty-four patients with allergic rhinitis and GP allergy had higher IgE reactivity with P notatum and C dactylon than with a mixture of 5 temperate GPs. For 90% of 21 GP allergic serum samples, P notatum, S halepense, or C dactylon specific IgE concentrations were higher than temperate GP specific IgE, and GP specific IgE had higher correlations of subtropical GP (r = 0.771-0.950) than temperate GP (r = 0.317-0.677). In most patients (71%-100%), IgE with P notatum, S halepense, or C dactylon GPs was inhibited better by subtropical GP than temperate GP. When the temperate GP mixture achieved 50% inhibition of IgE with subtropical GP, there was a 39- to 67-fold difference in concentrations giving 50% inhibition and significant differences in maximum inhibition for S halepense and P notatum GP relative to temperate GP. Conclusion Patients living in a subtropical region had species specific IgE recognition of subtropical GP. Most GP allergic patients in Queensland would benefit from allergen specific immunotherapy with a standardized content of subtropical GP allergens.