Extracting Query Interfaces Based on Form Structures and Semantic Similarity

Web databases are now pervasive. Such a database can be accessed via its query interface (usually HTML query form) only. Extracting Web query interfaces is a critical step in data integration across multiple Web databases, which creates a formal representation of a query form by extracting a set of query conditions in it. This paper presents a novel approach to extracting Web query interfaces. In this approach, a generic set of query condition rules are created to define query conditions that are semantically equivalent to SQL search conditions. Query condition rules represent the semantic roles that labels and form elements play in query conditions, and how they are hierarchically grouped into constructs of query conditions. To group labels and form elements in a query form, we explore both their structural proximity in the hierarchy of structures in the query form, which is captured by a tree of nested tags in the HTML codes of the form, and their semantic similarity, which is captured by various short texts used in labels, form elements and their properties. We have implemented the proposed approach and our experimental results show that the approach is highly effective.

Communicating the benefits of wholegrain and functional grain products to European consumers

In order to increase the consumption of wholegrain products or grain products with functional properties, it is important to understand consumer beliefs about such products and the impact of health claims. In a series of consumer studies several differences were found between countries. While consumers in Finland, Italy and the UK saw wholegrain products as having positive attributes, those in Finland had more negative beliefs about refined grain products. Health claims and wholegrain labels increased perceived healthiness but had a less positive impact on likelihood of buying, and in Italy both health claims and wholegrain labels even decreased the likelihood of buying.

Growth of Gold Nanocrystals Incorporated with Magnetic Microbead-based Separation as a Tool for Quantification of Biological Interactions

Au nanoparticles (AuNPs) have been widely used not only as optical labels or ‘weight” labels for the detections of biorecognition events but also an amplifier of surface plasmon resonance biosensors. The intrinsic property of gold nuclei composing of a group of Au atoms to catalyze the reduction of metal ions on the NPs and thereby to enlarge the metallic nanoparticles is employed in different biosensing paths. In a solution containing Au+ ions (e.g. HAuCl4) and the Au clusters, hydrated electrons which are reduced from oxidation of reducers (H2O2, sodium citrate, ascorbic acid, or NaBH4) will be used to reduce the Au+ ion leading to the deposition of Au+ to the Au0 (Au clusters). The reaction will be catalyzed continuously by the Au0 until the Au+ ions and hydrated electrons are exhausted. As a result, the AuNPs will be grown and their optical properties are also changed. If the AuNP nanoclusters are used as probes, the color change will be dependent on amount of analytes, thus give a quantitative monitoring of the analytes.

In this study, we incorporate the use of magnetic beads with the nanocrystalline growth to quantify a target protein based on immunoreactions. Prostate specific antigen (PSA) is chosen as the target analyte because of its values in diagnosis of prostate cancer. A double-sandwiched immunoassay is performed by gold-tagged monoclonal PSA antibody-PSA antigen – magnetic bead-tagged polyclonal PSA antibody interactions. After the immunoreactions, the target analytes are preconcentrated and separated by the magnetic beads while the nanogrowth plays a role of colorimetric signal developer.

The result shows that this is a very sensitive, robust and excellent strategy to detect biological interactions. PSA antigen is detected at femtomolar level with very high specificity under the presence of undesired proteins of crude samples. Furthermore, the method also shows great potential to detect other biological interactions. More details will be described in our presentation.

One-Pot, High-Yield Synthesis of Convex Au Octahedra by H2O2 - Mediated Process In Solution Phase

A simple, non-seeding and high-yield synthesis of convex gold octahedra with size of ca. 50 nm in aqueous solution is described. The octahedral nanoparticles were systematically prepared by reduction of HAuCl4 using ascorbic acid (AA) in the presence of cetyltrimethylammonium bromide (CTAB) as the stabilizing surfactant while concentrations of Au3+ were fixed. The synthesizing process is especially different to other wet synthesis of metallic nanoparticles because it is mediated by H2O2. Mechanism of the H2O2 – mediated process will be described in details. The gold octahedra were shown to be single crystals with all 8 faces belonging to {111} family. Moreover, the single crystalline particles also showed attractive optical properties towards LSPR that should find uses as labels for microscopic imaging, materials for colorimetric biosensings, or nanosensor developments.

Tyrosine nitration of prostacyclin synthase is associated with enhanced retinal cell apoptosis in diabetes

The risk of diabetic retinopathy is associated with the presence of both oxidative stress and toxic eicosanoids. Whether oxidative stress actually causes diabetic retinopathy via the generation of toxic eicosanoids, however, remains unknown. The aim of the present study was to determine whether tyrosine nitration of prostacyclin synthase (PGIS) contributes to retinal cell death in vitro and in vivo. Exposure of human retinal pericytes to heavily oxidized and glycated LDL (HOG-LDL), but not native forms of LDL (N-LDL), for 24 hours significantly increased pericyte apoptosis, accompanied by increased tyrosine nitration of PGIS and decreased PGIS activity. Inhibition of the thromboxane receptor or cyclooxygenase-2 dramatically attenuated HOG-LDL-induced apoptosis without restoring PGIS activity. Administration of superoxide dismutase (to scavenge superoxide anions) or L-N(G)-nitroarginine methyl ester (L-NAME, a nonselective nitric oxide synthase inhibitor) restored PGIS activity and attenuated pericyte apoptosis. In Akita mouse retinas, diabetes increased intraretinal levels of oxidized LDL and glycated LDL, induced PGIS nitration, enhanced apoptotic cell death, and impaired blood-retinal barrier function. Chronic administration of tempol, a superoxide scavenger, reduced intraretinal oxidized LDL and glycated LDL levels, PGIS nitration, and retina cell apoptosis, thereby preserving the integrity of blood-retinal barriers. In conclusion, oxidized LDL-mediated PGIS nitration and associated thromboxane receptor stimulation might be important in the initiation and progression of diabetic retinopathy.

Nile blue-based nano-sized pH sensors for simultaneous far-red and near-infrared live bioimaging

Diblock copolymer vesicles are tagged with pH-responsive Nile Blue-based labels and used as a new type of pH-responsive colorimetric/fluorescent biosensor for far-red and near-infrared imaging of live cells. The diblock copolymer vesicles described herein are based on poly(2-(methacryloyloxy)ethyl phosphorylcholine-block-2-(diisopropylamino)ethyl methacrylate) [PMPC-PDPA]: the biomimetic PMPC block is known to facilitate rapid cell uptake for a wide range of cell lines, while the PDPA block constitutes the pH-responsive component that enables facile vesicle self-assembly in aqueous solution. These biocompatible vesicles can be utilized to detect interstitial hypoxic/acidic regions in a tumor model via a pH-dependent colorimetric shift. In addition, they are also useful for selective intracellular staining of lysosomes and early endosomes via subtle changes in fluorescence emission. Such nanoparticles combine efficient cellular uptake with a pH-responsive Nile Blue dye label to produce a highly versatile dual capability probe. This is in marked contrast to small molecule dyes, which are usually poorly uptaken by cells, frequently exhibit cytotoxicity, and are characterized by intracellular distributions invariably dictated by their hydrophilic/hydrophobic balance.

Food miles or carbon emissions? Exploring labeling preference for food transport footprint with a stated choice study

The ecological footprint of food transport can be communicated using carbon dioxide emissions (CO2 label) or by providing information about both the length of time and the mileage travelled (food miles label). We use stated choice data to estimate conventional unobserved taste heterogeneity models and extend them to a specification that also addresses attribute nonattendance. The implied posterior distributions of the marginal willingness to pay values are compared graphically and are used in validation regressions. We find strong bimodality of taste distribution as the emerging feature, with different groups of subjects having low and high valuations for these labels. The best fitting model shows that CO2 and food miles valuations are much correlated. CO2 valuations can be high even for those respondents expressing low valuations for food miles. However, the reverse is not true. Taken together, the results suggest that consumers tend to value the CO2 label at least as much and sometimes more than the food miles label.

AGWAN: A Generative Model for Labelled, Weighted Graphs

Real-world graphs or networks tend to exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Much effort has been directed into creating realistic and tractable models for unlabelled graphs, which has yielded insights into graph structure and evolution. Recently, attention has moved to creating models for labelled graphs: many real-world graphs are labelled with both discrete and numeric attributes. In this paper, we present AGWAN (Attribute Graphs: Weighted and Numeric), a generative model for random graphs with discrete labels and weighted edges. The model is easily generalised to edges labelled with an arbitrary number of numeric attributes. We include algorithms for fitting the parameters of the AGWAN model to real-world graphs and for generating random graphs from the model. Using the Enron “who communicates with whom” social graph, we compare our approach to state-of-the-art random labelled graph generators and draw conclusions about the contribution of discrete vertex labels and edge weights to the structure of real-world graphs.

What’s in a (Party) Name?: Examining preferences, discipline, and social identity in a parliamentary free vote

In trying to understand the effects of political parties on shaping the voting behaviour of legislators, research has attempted the difficult task of separating the effects of preferences from rules used by party leaders to enforce discipline. However, little research has explored the prospect that party labels also reflect a social identity that is independent of legislators’ preferences and the rules used by party leaders to enforce discipline. In this study we examine that possibility, employing a data set that permits us to control both for leadership-based effects and legislator preferences on a 2000 free vote dealing with stem cell research. Using the British Representation Studies 1997 – which interviewed Members of Parliament regarding their preferences on several key issues related to the bill – we find significant evidence that party-as-identification plays a role in shaping how legislators vote, even after preferences and discipline are accounted for.

AGWAN: A Generative Model for Labelled, Weighted Graphs

Real-world graphs or networks tend to exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Much effort has been directed into creating realistic and tractable models for unlabelled graphs, which has yielded insights into graph structure and evolution. Recently, attention has moved to creating models for labelled graphs: many real-world graphs are labelled with both discrete and numeric attributes. In this paper, we presentAgwan (Attribute Graphs: Weighted and Numeric), a generative model for random graphs with discrete labels and weighted edges. The model is easily generalised to edges labelled with an arbitrary number of numeric attributes. We include algorithms for fitting the parameters of the Agwanmodel to real-world graphs and for generating random graphs from the model. Using real-world directed and undirected graphs as input, we compare our approach to state-of-the-art random labelled graph generators and draw conclusions about the contribution of discrete vertex labels and edge weights to graph structure.

Evaluation of information extraction techniques to label extracted data from e-commerce web page

Automatically determining and assigning shared and meaningful text labels to data extracted from an e-Commerce web page is a challenging problem. An e-Commerce web page can display a list of data records, each of which can contain a combination of data items (e.g. product name and price) and explicit labels, which describe some of these data items. Recent advances in extraction techniques have made it much easier to precisely extract individual data items and labels from a web page, however, there are two open problems: 1. assigning an explicit label to a data item, and 2. determining labels for the remaining data items. Furthermore, improvements in the availability and coverage of vocabularies, especially in the context of e-Commerce web sites, means that we now have access to a bank of relevant, meaningful and shared labels which can be assigned to extracted data items. However, there is a need for a technique which will take as input a set of extracted data items and assign automatically to them the most relevant and meaningful labels from a shared vocabulary. We observe that the Information Extraction (IE) community has developed a great number of techniques which solve problems similar to our own. In this work-in-progress paper we propose our intention to theoretically and experimentally evaluate different IE techniques to ascertain which is most suitable to solve this problem.

Automatically Annotating Structured Web Data Using a SVM-Based Multiclass Classifier

In this paper, we propose a new learning approach to Web data annotation, where a support vector machine-based multiclass classifier is trained to assign labels to data items. For data record extraction, a data section re-segmentation algorithm based on visual and content features is introduced to improve the performance of Web data record extraction. We have implemented the proposed approach and tested it with a large set of Web query result pages in different domains. Our experimental results show that our proposed approach is highly effective and efficient.

Carbon distribution within the plant and rhizosphere in laboratory and field-grown Lolium perenne at different stages of development

Carbon distribution within perennial ryegrass was determined at different stages of plant development, by pulse-labelling laboratory and field-grown plants with ¹⁴C-CO₂. During the early stages of growth (23-51 days), C distribution of laboratory grown plants was not markedly affected by plant age, with 12.4-24% of net assimilated label lost into the soil as root-soil respiration. The percentage of net assimilate translocated below ground was 20-28% during this stage of growth. At 65 days, the percentage of the label translocated below ground decreased to 8.1% of the net assimilate, with a subsequent decrease in root-soil respiration to 3.9%. The ability of the plant to fix the label (expressed in MBq g^-1 oven dry total plant weight) decreased steadily as the plants aged. When the 30 day old plants were subjected to water stress (soil water potential -1.5 MPa) for 2 days before pulse-labelling, root-soil respiration of the pulse-label decreased compared with plants grown at field capacity. The distribution of a ¹⁴C pulse-label within perennial ryegrass grown under field conditions was found to be dependent on the age of the plants. For 4 week old plants, 67% of net assimilated label was translocated below ground, with 64.8% of this respired by the roots and soil. Less label was translocated below ground at subsequent pulse-labels from weeks 8 to 24. The proportion of label translocated below ground respired by the roots and soil also decreased. The investment of label in the plant shoots was found to be greater in field grown plants as compared to plants of the same age grown in a controlled, laboratory environment. © 1990.

Panning for Gold: The Standardizing Work of Filling “Autistic” Shells – Using institutional ethnography to explore textually mediated health relations in the diagnostic process of autism.

Health reform practices in Canada and elsewhere have restructured the purpose and use of diagnostic labels and the processes of naming such labels. Diagnoses are no longer only a means to tell doctors and patients what may be wrong and indicate potential courses of treatment; some diagnoses activate specialized services and supports for persons with a disability and those who provide care for them. In British Columbia, a standardized process of diagnosis with the outcome of an autism spectrum disorder gives access to government provided health care and educational services and supports. Such processes enter individuals into a complex of text mediated relations, regulated by the principles of evidence-based medicine. However, the diagnosis of autism in children is notoriously uncertain. Because of this ambiguity, standardizing the diagnostic process creates a hurdle in gaining help and support for parents who have children with problems that could lead to a diagnosis on the autism spectrum. Such processes and their organizing relations are problematized, explored and explicated below. Grounded in the epistemological and ontological shift offered by Dorothy E. Smith (1987; 1990a; 1999; 2005), this article reports on the findings of an institutional ethnographic study that explored the diagnostic process of autism in British Columbia. More specifically, this article focuses on the processes involved in going from mothers talking from their experience about their childrens problems to the formalized and standardized, and thus “virtually” produced, diagnoses that may or may not give access to services and supports in different systems of care. Two psychologists, a developmental pediatrician, a social worker – members of a specialized multidisciplinary assessment team – and several mothers of children with a diagnosis on the autism spectrum were interviewed. The implications of standardizing the diagnosis process of a disability that is not clear-cut and has funding attached are discussed. This ethnography also provides a glimpse of the implications of current and ongoing reforms in the state-supported health care system in British Columbia, and more generally in Canada, for people’s everyday doings.

Organo-mineral complexation alters carbon and nitrogen cycling in stream microbial assemblages

Inland waters are of global biogeochemical importance receiving carbon inputs of ~ 4.8 Pg C y^-1. Of this 12 % is buried, 18 % transported to the oceans, and 70 % supports aquatic secondary production. However, the mechanisms that determine the fate of organic matter (OM) in these systems are poorly defined. One important aspect is the formation of organo-mineral complexes in aquatic systems and their potential as a route for OM transport and burial vs. their use potential as organic carbon (C) and nitrogen (N) sources. Organo-mineral particles form by sorption of dissolved OM to freshly eroded mineral surfaces and may contribute to ecosystem-scale particulate OM fluxes. We tested the availability of mineral-sorbed OM as a C & N source for streamwater microbial assemblages and streambed biofilms. Organo-mineral particles were constructed in vitro by sorption of ¹³C:¹⁵N-labelled amino acids to hydrated kaolin particles, and microbial degradation of these particles compared with equivalent doses of ¹³C:¹⁵N-labelled free amino acids. Experiments were conducted in 120 ml mesocosms over 7 days using biofilms and streamwater sampled from the Oberer Seebach stream (Austria), tracing assimilation and mineralization of ¹³C and ¹⁵N labels from mineral-sorbed and dissolved amino acids.Here we present data on the effects of organo-mineral sorption upon amino acid mineralization and its C:N stoichiometry. Organo-mineral sorption had a significant effect upon microbial activity, restricting C and N mineralization by both the biofilm and streamwater treatments. Distinct differences in community response were observed, with both dissolved and mineral-stabilized amino acids playing an enhanced role in the metabolism of the streamwater microbial community. Mineral-sorption of amino acids differentially affected C & N mineralization and reduced the C:N ratio of the dissolved amino acid pool. The present study demonstrates that organo-mineral complexes restrict microbial degradation of OM and may, consequently, alter the carbon and nitrogen cycling dynamics within aquatic ecosystems.