911 resultados para Filtration and Separation


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The glucose transporter IICB of the Escherichia coli phosphotransferase system (PTS) consists of a polytopic membrane domain (IIC) responsible for substrate transport and a hydrophilic C-terminal domain (IIB) responsible for substrate phosphorylation. We have overexpressed and purified a triple mutant of IIC (mut-IIC), which had recently been shown to be suitable for crystallization purposes. Mut-IIC was homodimeric as determined by blue native-PAGE and gel-filtration, and had an eyeglasses-like structure as shown by negative-stain transmission electron microscopy (TEM) and single particle analysis. Glucose binding and transport by mut-IIC, mut-IICB and wildtype-IICB were compared with scintillation proximity and in vivo transport assays. Binding was reduced and transport was impaired by the triple mutation. The scintillation proximity assay allowed determination of substrate binding, affinity and specificity of wildtype-IICB by a direct method. 2D crystallization of mut-IIC yielded highly-ordered tubular crystals and made possible the calculation of a projection structure at 12Å resolution by negative-stain TEM. Immunogold labeling TEM revealed the sidedness of the tubular crystals, and high-resolution atomic force microscopy the surface structure of mut-IIC. This work presents the structure of a glucose PTS transporter at the highest resolution achieved so far and sets the basis for future structural studies.

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Carnitine is an amino acid derivative that plays a key role in energy metabolism. Endogenous carnitine is found in its free form or esterified with acyl groups of several chain lengths. Quantification of carnitine and acylcarnitines is of particular interest for screening for research and metabolic disorders. We developed a method with online solid-phase extraction coupled to high-performance liquid chromatography and tandem mass spectrometry to quantify carnitine and three acylcarnitines with different polarity (acetylcarnitine, octanoylcarnitine, and palmitoylcarnitine). Plasma samples were deproteinized with methanol, loaded on a cation exchange trapping column and separated on a reversed-phase C8 column using heptafluorobutyric acid as an ion-pairing reagent. Considering the endogenous nature of the analytes, we quantified with the standard addition method and with external deuterated standards. Solid-phase extraction and separation were achieved within 8 min. Recoveries of carnitine and acylcarnitines were between 98 and 105 %. Both quantification methods were equally accurate (all values within 84 to 116 % of target concentrations) and precise (day-to-day variation of less than 18 %) for all carnitine species and concentrations analyzed. The method was used successfully for determination of carnitine and acylcarnitines in different human samples. In conclusion, we present a method for simultaneous quantification of carnitine and acylcarnitines with a rapid sample work-up. This approach requires small sample volumes and a short analysis time, and it can be applied for the determination of other acylcarnitines than the acylcarnitines tested. The method is useful for applications in research and clinical routine.

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Principles and guidelines are presented to ensure a solid scientific standard of papers dealing with the taxonomy of taxa of Pasteurellaceae Pohl 1981. The classification of the Pasteurellaceae is in principle based on a polyphasic approach. DNA sequencing of certain genes is very important for defining the borders of a taxon. However, the characteristics that are common to all members of the taxon and which might be helpful for separating it from related taxa must also be identified. Descriptions have to be based on as many strains as possible (inclusion of at least five strains is highly desirable), representing different sources with respect to geography and ecology, to allow proper characterization both phenotypically and genotypically, to establish the extent of diversity of the cluster to be named. A genus must be monophyletic based on 16S rRNA gene sequence-based phylogenetic analysis. Only in very rare cases is it acceptable that monophyly can not be achieved by 16S rRNA gene sequence comparison. Recently, the monophyly of genera has been confirmed by sequence comparison of housekeeping genes. In principle, a new genus should be recognized by a distinct phenotype, and characters that separate the new genus from its neighbours should be given clearly. Due to the overall importance of accurate classification of species, at least two genotypic methods are needed to show coherence and for separation at the species level. The main criterion for the classification of a novel species is that it forms a monophyletic group based on 16S rRNA gene sequence-based phylogenetic analysis. However, some groups might also include closely related species. In these cases, more sensitive tools for genetic recognition of species should be applied, such as DNA-DNA hybridizations. The comparison of housekeeping gene sequences has recently been used for genotypic definition of species. In order to separate species, phenotypic characters must also be identified to recognize them, and at least two phenotypic differences from existing species should be identified if possible. We recommend the use of the subspecies category only for subgroups associated with disease or similar biological characteristics. At the subspecies level, the genotypic groups must always be nested within the boundaries of an existing species. Phenotypic cohesion must be documented at the subspecies level and separation between subspecies and related species must be fully documented, as well as association with particular disease and host. An overview of methods previously used to characterize isolates of the Pasteurellaceae has been given. Genotypic and phenotypic methods are separated in relation to tests for investigating diversity and cohesion and to separate taxa at the level of genus as well as species and subspecies.

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As water quality interventions are scaled up to meet the Millennium Development Goal of halving the proportion of the population without access to safe drinking water by 2015 there has been much discussion on the merits of household- and source-level interventions. This study furthers the discussion by examining specific interventions through the use of embodied human and material energy. Embodied energy quantifies the total energy required to produce and use an intervention, including all upstream energy transactions. This model uses material quantities and prices to calculate embodied energy using national economic input/output-based models from China, the United States and Mali. Embodied energy is a measure of aggregate environmental impacts of the interventions. Human energy quantifies the caloric expenditure associated with the installation and operation of an intervention is calculated using the physical activity ratios (PARs) and basal metabolic rates (BMRs). Human energy is a measure of aggregate social impacts of an intervention. A total of four household treatment interventions – biosand filtration, chlorination, ceramic filtration and boiling – and four water source-level interventions – an improved well, a rope pump, a hand pump and a solar pump – are evaluated in the context of Mali, West Africa. Source-level interventions slightly out-perform household-level interventions in terms of having less total embodied energy. Human energy, typically assumed to be a negligible portion of total embodied energy, is shown to be significant to all eight interventions, and contributing over half of total embodied energy in four of the interventions. Traditional gender roles in Mali dictate the types of work performed by men and women. When the human energy is disaggregated by gender, it is seen that women perform over 99% of the work associated with seven of the eight interventions. This has profound implications for gender equality in the context of water quality interventions, and may justify investment in interventions that reduce human energy burdens.

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In recent years there has been a tremendous amount of research in the area of nanotechnology. History tells us that the commercialization of technologies will always be accompanied by both positive and negative effects for society and the environment. Products containing nanomaterials are already available in the market, and yet there is still not much information regarding the potential negative effects that these products may cause. The work presented in this dissertation describes a holistic approach to address different dimensions of nanotechnology sustainability. Life cycle analysis (LCA) was used to study the potential usage of polyethylene filled with nanomaterials to manufacture automobile body panels. Results showed that the nanocomposite does not provide an environmental benefit over traditional steel panels. A new methodology based on design of experiments (DOE) techniques, coupled with LCA, was implemented to investigate the impact of inventory uncertainties. Results showed that data variability does not have a significant effect on the prediction of the environmental impacts. Material profiles for input materials did have a highly significant effect on the overall impact. Energy consumption and material characterization were identified as two mainstreams where additional research is needed in order to predict the overall impact of nanomaterials more effectively. A study was undertaken to gain insights into the behavior of small particles in contact with a surface exposed to air flow to determine particle lift-off from the surface. A mapping strategy was implemented that allows for the identification of conditions for particle liftoff based on particle size and separation distance from the wall. Main results showed that particles smaller than 0:1mm will not become airborne under shear flow unless the separation distance is greater than 15 nm. Results may be used to minimize exposure to airborne materials. Societal implications that may occur in the workplace were researched. This research task explored different topics including health, ethics, and worker perception with the aim of identifying the base knowledge available in the literature. Recommendations are given for different scenarios to describe how workers and employers could minimize the unwanted effects of nanotechnology production.

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Information Centric Networking (ICN) as an emerging paradigm for the Future Internet has initially been rather focusing on bandwidth savings in wired networks, but there might also be some significant potential to support communication in mobile wireless networks as well as opportunistic network scenarios, where end systems have spontaneous but time-limited contact to exchange data. This chapter addresses the reasoning why ICN has an important role in mobile and opportunistic networks by identifying several challenges in mobile and opportunistic Information-Centric Networks and discussing appropriate solutions for them. In particular, it discusses the issues of receiver and source mobility. Source mobility needs special attention. Solutions based on routing protocol extensions, indirection, and separation of name resolution and data transfer are discussed. Moreover, the chapter presents solutions for problems in opportunistic Information-Centric Networks. Among those are mechanisms for efficient content discovery in neighbour nodes, resume mechanisms to recover from intermittent connectivity disruptions, a novel agent delegation mechanisms to offload content discovery and delivery to mobile agent nodes, and the exploitation of overhearing to populate routing tables of mobile nodes. Some preliminary performance evaluation results of these developed mechanisms are provided.

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Background. Increasing rates of maternal employment highlight the need for non-maternal child care for infants at an earlier age. Several studies have shown that employment induced maternal depression or psychological distress is associated with the child's socio-emotional and cognitive development. However, separation anxiety, a common phenomenon observed among employed mothers during early years, has seldom been studied. Therefore, the purpose of this study was to evaluate the role of maternal separation anxiety in the child's cognitive development.^ Methods. Data were obtained from Phase I (birth to 36 months) of the National Institute of Child Health and Human Development, Study of Early Child Care and Youth Development (NICHD SECCYD). Bivariate and multivariate analyses were performed to determine the association between separation anxiety groups and child outcomes. Multivariate analysis was also used to examine the mediating and/or moderating effect of sensitivity and moderating effect of difficult temperament.^ Results. Separation anxiety showed a negative association with the Bracken, attachment security, maternal sensitivity and psychological state. Children whose mothers never reported high levels of separation anxiety showed higher levels of school readiness and attachment security compared to those whose mothers experienced high levels of separation anxiety at least once. There was a significant interaction between separation anxiety and maternal sensitivity for the Bracken and attachment security indicating the moderating effect of sensitivity. Maternal sensitivity was also found to partially mediate the association between high levels of separation anxiety and school readiness or attachment security. However, the interaction between difficult temperament and separation anxiety was not significant for any of the child outcomes. ^ Conclusions. High levels of separation anxiety have a negative impact on school readiness, attachment security, maternal sensitivity and psychological state. In addition, mothers who experience high levels of separation anxiety but are sensitive during the mother-child interaction have children with high school readiness and attachment security compared to those who are less sensitive.^ Keywords. Maternal separation anxiety, School readiness. ^

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Developing countries are heavily burdened by limited access to safe drinking water and subsequent water-related diseases. Numerous water treatment interventions combat this public health crisis, encompassing both traditional and less-common methods. Of these, water disinfection serves as an important means to provide safe drinking water. Existing literature discusses a wide range of traditional treatment options and encourages the use of multi-barrier approaches including coagulation-flocculation, filtration, and disinfection. Most sources do not delve into approaches specifically appropriate for developing countries, nor do they exclusively examine water disinfection methods.^ The objective of this review is to focus on an extensive range of chemical, physio-chemical, and physical water disinfection techniques to provide a compilation, description and evaluation of options available. Such an objective provides further understanding and knowledge to better inform water treatment interventions and explores alternate means of water disinfection appropriate for developing countries. Appropriateness for developing countries corresponds to the effectiveness of an available, easy to use disinfection technique at providing safe drinking water at a low cost.^ Among chemical disinfectants, SWS sodium hypochlorite solution is preferred over sodium hypochlorite bleach due to consistent concentrations. Tablet forms are highly recommended chemical disinfectants because they are effective and very easy to use, but also because they are stable. Examples include sodium dichloroisocyanurate, calcium hypochlorite, and chlorine dioxide, which vary in cost depending on location and availability. Among physio-chemical disinfection options, electrolysis which produces mixed oxidants (MIOX) provides a highly effective disinfection option with a higher upfront cost but very low cost over the long term. Among physical disinfection options, solar disinfection (SODIS) applications are effective, but they treat only a fixed volume of water at a time. They come with higher initial costs but very low on-going costs. Additional effective disinfection techniques may be suitable depending on the location, availability and cost.^

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Chromosome segregation is a critical step during cell division to avoid aneuploidy and promote proper organismal development. Correct sister chromatid positioning and separation during mitosis helps to achieve faithful transmission of genetic material to daughter cells. This prevents improper chromosome partitioning that can potentially result in extrachromosomal fragments, increasing the tumorigenic potential of the cells. The kinetochore is a protenaicious structure responsible for the initiation and orchestration of chromosome movement during mitosis. This highly conserved structure among eukaryotes is required for chromosome attachment to the mitotic spindle and failure to assemble the kinetochore results in aberrant chromosome segregation. Thus elucidating the mechanism of kinetochore assembly is important to have a better understanding of the regulation that controls chromosome segregation. Our previous work identified the C. elegans Tousled-like kinase (TLK-1) as a mitotic kinase and depletion of TLK-1 results in embryonic lethality, characterized by nuclei displaying poor mitotic chromosome alignment, lagging chromosome, and chromosome bridges during anaphase. Additionally, previous studies from our group revealed that TLK-1 is phosphorylated independently by Aurora B at serine 634, and by CHK-1 at threonine T610. The research presented herein reveals that both phosphorylated forms of TLK-1 associate with the kinetochore during mitosis. Moreover, by systematic depletion of kinetochore proteins, I uncovered that pTLK-1 is bona fide kinetochore component that is located at the outer kinetochore layer, influencing the microtubule-binding interface. I also demonstrated that TLK-1 is necessary for the kinetochore localization of the microtubule interacting proteins CLS-2 and LIS-1 and I show that embryos depleted of TLK-1 presented an aberrant twisted kinetochore pattern. Furthermore, I established that the inner kinetochore protein KNL-2 is an in vitro substrate of TLK-1 indicating a possible role of TLK-1 in regulating centromeric assembly. Collectively, these results suggest a novel role for the Tousled-like kinase in regulation of kinetochore assembly and microtubule dynamics and demonstrate the necessity of TLK-1 for proper chromosome segregation in C. elegans.

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Abundance of microzooplankton was studied from August to October 1970 in a ship laboratory using the method of concentration of water samples by filtration and then counting living organisms under a microscope. The main groups (in order of decreasing abundance) were as follows: infusorians, nauplii, copepodids, radiolarians, appendicularians, and some others (rotifers, worm and mollusk larvae). Concentration of infusorians rarely exceeded 100 #/l, possibly an underestimate. Nauplii often numbered 20 to 30 #/l. Study of vertical distribution of microzooplankton showed that peak concentrations in the Mediterranean Sea were at depth of 20-30 m regardless of day time. There were 2 peaks in the Atlantic Ocean, one in the 10- to 20-m layer, the other in the 50- to 75-m layer.

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Two modal size groups of sexually mature Arctic charr (Salvelinus alpinus) differing in shape and found at different depths in Lake Aigneau in the Canadian sub-Arctic are described and tested for genetic and ecological differentiation. Forms consisted of a small littoral resident, mean size 21.7 cm, and a large profundal resident, mean size 53.9 cm. Mitochondrial DNA analysis indicated that seven of eight haplotypes were diagnostic for either the littoral or profundal fish, with 66.6% of the variation being found within form groupings. Pairwise tests of microsatellite data indicated significant differences in nine of 12 loci and a significant difference between the forms across all tested loci. Molecular variation was partitioned to 84.1% within and 15.9% between forms and suggestive of either restricted interbreeding over time or different allopatric origins. Stable isotope signatures were also significantly different, with the profundal fish having higher d13C and d15N values than the littoral fish. Overlap and separation, respectively, in the range of form d13C and d15N signatures indicated that carbon was obtained from similar sources, but that forms fed at different trophic levels. Littoral fish relied on aquatic insects, predominantly chironomids. Profundal fish were largely piscivorous, including cannibalism. Predominantly empty stomachs and low per cent nitrogen muscle-tissue composition among profundal fish further indicated that the feeding activity was limited to the winter when ice-cover increases the density of available prey at depth. Results provide evidence of significant differences between the modal groups, with origins in both genetics and ecology.

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Organisms inhabiting coastal waters naturally experience diel and seasonal physico-chemical variations. According to various assumptions, coastal species are either considered to be highly tolerant to environmental changes or, conversely, living at the thresholds of their physiological performance. Therefore, these species are either more resistant or more sensitive, respectively, to ocean acidification and warming. Here, we focused on Crepidula fornicata, an invasive gastropod that colonized bays and estuaries on northwestern European coasts during the 20th century. Small (<3 cm in length) and large (>4.5 cm in length), sexually mature individuals of C. fornicata were raised for 6 months in three different pCO2 conditions (390 µatm, 750 µatm, and 1400 µatm) at four successive temperature levels (10°C, 13°C, 16°C, and 19°C). At each temperature level and in each pCO2 condition, we assessed the physiological rates of respiration, ammonia excretion, filtration and calcification on small and large individuals. Results show that, in general, temperature positively influenced respiration, excretion and filtration rates in both small and large individuals. Conversely, increasing pCO2 negatively affected calcification rates, leading to net dissolution in the most drastic pCO2 condition (1400 µatm) but did not affect the other physiological rates. Overall, our results indicate that C. fornicata can tolerate ocean acidification, particularly in the intermediate pCO2 scenario. Moreover, in this eurythermal species, moderate warming may play a buffering role in the future responses of organisms to ocean acidification.

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OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web 1. INTRODUCTION. LINGUISTIC TOOLS AND ANNOTATIONS: THEIR LIGHTS AND SHADOWS Computational Linguistics is already a consolidated research area. It builds upon the results of other two major ones, namely Linguistics and Computer Science and Engineering, and it aims at developing computational models of human language (or natural language, as it is termed in this area). Possibly, its most well-known applications are the different tools developed so far for processing human language, such as machine translation systems and speech recognizers or dictation programs. These tools for processing human language are commonly referred to as linguistic tools. Apart from the examples mentioned above, there are also other types of linguistic tools that perhaps are not so well-known, but on which most of the other applications of Computational Linguistics are built. These other types of linguistic tools comprise POS taggers, natural language parsers and semantic taggers, amongst others. All of them can be termed linguistic annotation tools. Linguistic annotation tools are important assets. In fact, POS and semantic taggers (and, to a lesser extent, also natural language parsers) have become critical resources for the computer applications that process natural language. Hence, any computer application that has to analyse a text automatically and ‘intelligently’ will include at least a module for POS tagging. The more an application needs to ‘understand’ the meaning of the text it processes, the more linguistic tools and/or modules it will incorporate and integrate. However, linguistic annotation tools have still some limitations, which can be summarised as follows: 1. Normally, they perform annotations only at a certain linguistic level (that is, Morphology, Syntax, Semantics, etc.). 2. They usually introduce a certain rate of errors and ambiguities when tagging. This error rate ranges from 10 percent up to 50 percent of the units annotated for unrestricted, general texts. 3. Their annotations are most frequently formulated in terms of an annotation schema designed and implemented ad hoc. A priori, it seems that the interoperation and the integration of several linguistic tools into an appropriate software architecture could most likely solve the limitations stated in (1). Besides, integrating several linguistic annotation tools and making them interoperate could also minimise the limitation stated in (2). Nevertheless, in the latter case, all these tools should produce annotations for a common level, which would have to be combined in order to correct their corresponding errors and inaccuracies. Yet, the limitation stated in (3) prevents both types of integration and interoperation from being easily achieved. In addition, most high-level annotation tools rely on other lower-level annotation tools and their outputs to generate their own ones. For example, sense-tagging tools (operating at the semantic level) often use POS taggers (operating at a lower level, i.e., the morphosyntactic) to identify the grammatical category of the word or lexical unit they are annotating. Accordingly, if a faulty or inaccurate low-level annotation tool is to be used by other higher-level one in its process, the errors and inaccuracies of the former should be minimised in advance. Otherwise, these errors and inaccuracies would be transferred to (and even magnified in) the annotations of the high-level annotation tool. Therefore, it would be quite useful to find a way to (i) correct or, at least, reduce the errors and the inaccuracies of lower-level linguistic tools; (ii) unify the annotation schemas of different linguistic annotation tools or, more generally speaking, make these tools (as well as their annotations) interoperate. Clearly, solving (i) and (ii) should ease the automatic annotation of web pages by means of linguistic tools, and their transformation into Semantic Web pages (Berners-Lee, Hendler and Lassila, 2001). Yet, as stated above, (ii) is a type of interoperability problem. There again, ontologies (Gruber, 1993; Borst, 1997) have been successfully applied thus far to solve several interoperability problems. Hence, ontologies should help solve also the problems and limitations of linguistic annotation tools aforementioned. Thus, to summarise, the main aim of the present work was to combine somehow these separated approaches, mechanisms and tools for annotation from Linguistics and Ontological Engineering (and the Semantic Web) in a sort of hybrid (linguistic and ontological) annotation model, suitable for both areas. This hybrid (semantic) annotation model should (a) benefit from the advances, models, techniques, mechanisms and tools of these two areas; (b) minimise (and even solve, when possible) some of the problems found in each of them; and (c) be suitable for the Semantic Web. The concrete goals that helped attain this aim are presented in the following section. 2. GOALS OF THE PRESENT WORK As mentioned above, the main goal of this work was to specify a hybrid (that is, linguistically-motivated and ontology-based) model of annotation suitable for the Semantic Web (i.e. it had to produce a semantic annotation of web page contents). This entailed that the tags included in the annotations of the model had to (1) represent linguistic concepts (or linguistic categories, as they are termed in ISO/DCR (2008)), in order for this model to be linguistically-motivated; (2) be ontological terms (i.e., use an ontological vocabulary), in order for the model to be ontology-based; and (3) be structured (linked) as a collection of ontology-based triples, as in the usual Semantic Web languages (namely RDF(S) and OWL), in order for the model to be considered suitable for the Semantic Web. Besides, to be useful for the Semantic Web, this model should provide a way to automate the annotation of web pages. As for the present work, this requirement involved reusing the linguistic annotation tools purchased by the OEG research group (http://www.oeg-upm.net), but solving beforehand (or, at least, minimising) some of their limitations. Therefore, this model had to minimise these limitations by means of the integration of several linguistic annotation tools into a common architecture. Since this integration required the interoperation of tools and their annotations, ontologies were proposed as the main technological component to make them effectively interoperate. From the very beginning, it seemed that the formalisation of the elements and the knowledge underlying linguistic annotations within an appropriate set of ontologies would be a great step forward towards the formulation of such a model (henceforth referred to as OntoTag). Obviously, first, to combine the results of the linguistic annotation tools that operated at the same level, their annotation schemas had to be unified (or, preferably, standardised) in advance. This entailed the unification (id. standardisation) of their tags (both their representation and their meaning), and their format or syntax. Second, to merge the results of the linguistic annotation tools operating at different levels, their respective annotation schemas had to be (a) made interoperable and (b) integrated. And third, in order for the resulting annotations to suit the Semantic Web, they had to be specified by means of an ontology-based vocabulary, and structured by means of ontology-based triples, as hinted above. Therefore, a new annotation scheme had to be devised, based both on ontologies and on this type of triples, which allowed for the combination and the integration of the annotations of any set of linguistic annotation tools. This annotation scheme was considered a fundamental part of the model proposed here, and its development was, accordingly, another major objective of the present work. All these goals, aims and objectives could be re-stated more clearly as follows: Goal 1: Development of a set of ontologies for the formalisation of the linguistic knowledge relating linguistic annotation. Sub-goal 1.1: Ontological formalisation of the EAGLES (1996a; 1996b) de facto standards for morphosyntactic and syntactic annotation, in a way that helps respect the triple structure recommended for annotations in these works (which is isomorphic to the triple structures used in the context of the Semantic Web). Sub-goal 1.2: Incorporation into this preliminary ontological formalisation of other existing standards and standard proposals relating the levels mentioned above, such as those currently under development within ISO/TC 37 (the ISO Technical Committee dealing with Terminology, which deals also with linguistic resources and annotations). Sub-goal 1.3: Generalisation and extension of the recommendations in EAGLES (1996a; 1996b) and ISO/TC 37 to the semantic level, for which no ISO/TC 37 standards have been developed yet. Sub-goal 1.4: Ontological formalisation of the generalisations and/or extensions obtained in the previous sub-goal as generalisations and/or extensions of the corresponding ontology (or ontologies). Sub-goal 1.5: Ontological formalisation of the knowledge required to link, combine and unite the knowledge represented in the previously developed ontology (or ontologies). Goal 2: Development of OntoTag’s annotation scheme, a standard-based abstract scheme for the hybrid (linguistically-motivated and ontological-based) annotation of texts. Sub-goal 2.1: Development of the standard-based morphosyntactic annotation level of OntoTag’s scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996a) and also the recommendations included in the ISO/MAF (2008) standard draft. Sub-goal 2.2: Development of the standard-based syntactic annotation level of the hybrid abstract scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996b) and the ISO/SynAF (2010) standard draft. Sub-goal 2.3: Development of the standard-based semantic annotation level of OntoTag’s (abstract) scheme. Sub-goal 2.4: Development of the mechanisms for a convenient integration of the three annotation levels already mentioned. These mechanisms should take into account the recommendations included in the ISO/LAF (2009) standard draft. Goal 3: Design of OntoTag’s (abstract) annotation architecture, an abstract architecture for the hybrid (semantic) annotation of texts (i) that facilitates the integration and interoperation of different linguistic annotation tools, and (ii) whose results comply with OntoTag’s annotation scheme. Sub-goal 3.1: Specification of the decanting processes that allow for the classification and separation, according to their corresponding levels, of the results of the linguistic tools annotating at several different levels. Sub-goal 3.2: Specification of the standardisation processes that allow (a) complying with the standardisation requirements of OntoTag’s annotation scheme, as well as (b) combining the results of those linguistic tools that share some level of annotation. Sub-goal 3.3: Specification of the merging processes that allow for the combination of the output annotations and the interoperation of those linguistic tools that share some level of annotation. Sub-goal 3.4: Specification of the merge processes that allow for the integration of the results and the interoperation of those tools performing their annotations at different levels. Goal 4: Generation of OntoTagger’s schema, a concrete instance of OntoTag’s abstract scheme for a concrete set of linguistic annotations. These linguistic annotations result from the tools and the resources available in the research group, namely • Bitext’s DataLexica (http://www.bitext.com/EN/datalexica.asp), • LACELL’s (POS) tagger (http://www.um.es/grupos/grupo-lacell/quees.php), • Connexor’s FDG (http://www.connexor.eu/technology/machinese/glossary/fdg/), and • EuroWordNet (Vossen et al., 1998). This schema should help evaluate OntoTag’s underlying hypotheses, stated below. Consequently, it should implement, at least, those levels of the abstract scheme dealing with the annotations of the set of tools considered in this implementation. This includes the morphosyntactic, the syntactic and the semantic levels. Goal 5: Implementation of OntoTagger’s configuration, a concrete instance of OntoTag’s abstract architecture for this set of linguistic tools and annotations. This configuration (1) had to use the schema generated in the previous goal; and (2) should help support or refute the hypotheses of this work as well (see the next section). Sub-goal 5.1: Implementation of the decanting processes that facilitate the classification and separation of the results of those linguistic resources that provide annotations at several different levels (on the one hand, LACELL’s tagger operates at the morphosyntactic level and, minimally, also at the semantic level; on the other hand, FDG operates at the morphosyntactic and the syntactic levels and, minimally, at the semantic level as well). Sub-goal 5.2: Implementation of the standardisation processes that allow (i) specifying the results of those linguistic tools that share some level of annotation according to the requirements of OntoTagger’s schema, as well as (ii) combining these shared level results. In particular, all the tools selected perform morphosyntactic annotations and they had to be conveniently combined by means of these processes. Sub-goal 5.3: Implementation of the merging processes that allow for the combination (and possibly the improvement) of the annotations and the interoperation of the tools that share some level of annotation (in particular, those relating the morphosyntactic level, as in the previous sub-goal). Sub-goal 5.4: Implementation of the merging processes that allow for the integration of the different standardised and combined annotations aforementioned, relating all the levels considered. Sub-goal 5.5: Improvement of the semantic level of this configuration by adding a named entity recognition, (sub-)classification and annotation subsystem, which also uses the named entities annotated to populate a domain ontology, in order to provide a concrete application of the present work in the two areas involved (the Semantic Web and Corpus Linguistics). 3. MAIN RESULTS: ASSESSMENT OF ONTOTAG’S UNDERLYING HYPOTHESES The model developed in the present thesis tries to shed some light on (i) whether linguistic annotation tools can effectively interoperate; (ii) whether their results can be combined and integrated; and, if they can, (iii) how they can, respectively, interoperate and be combined and integrated. Accordingly, several hypotheses had to be supported (or rejected) by the development of the OntoTag model and OntoTagger (its implementation). The hypotheses underlying OntoTag are surveyed below. Only one of the hypotheses (H.6) was rejected; the other five could be confirmed. H.1 The annotations of different levels (or layers) can be integrated into a sort of overall, comprehensive, multilayer and multilevel annotation, so that their elements can complement and refer to each other. • CONFIRMED by the development of: o OntoTag’s annotation scheme, o OntoTag’s annotation architecture, o OntoTagger’s (XML, RDF, OWL) annotation schemas, o OntoTagger’s configuration. H.2 Tool-dependent annotations can be mapped onto a sort of tool-independent annotations and, thus, can be standardised. • CONFIRMED by means of the standardisation phase incorporated into OntoTag and OntoTagger for the annotations yielded by the tools. H.3 Standardisation should ease: H.3.1: The interoperation of linguistic tools. H.3.2: The comparison, combination (at the same level and layer) and integration (at different levels or layers) of annotations. • H.3 was CONFIRMED by means of the development of OntoTagger’s ontology-based configuration: o Interoperation, comparison, combination and integration of the annotations of three different linguistic tools (Connexor’s FDG, Bitext’s DataLexica and LACELL’s tagger); o Integration of EuroWordNet-based, domain-ontology-based and named entity annotations at the semantic level. o Integration of morphosyntactic, syntactic and semantic annotations. H.4 Ontologies and Semantic Web technologies (can) play a crucial role in the standardisation of linguistic annotations, by providing consensual vocabularies and standardised formats for annotation (e.g., RDF triples). • CONFIRMED by means of the development of OntoTagger’s RDF-triple-based annotation schemas. H.5 The rate of errors introduced by a linguistic tool at a given level, when annotating, can be reduced automatically by contrasting and combining its results with the ones coming from other tools, operating at the same level. However, these other tools might be built following a different technological (stochastic vs. rule-based, for example) or theoretical (dependency vs. HPS-grammar-based, for instance) approach. • CONFIRMED by the results yielded by the evaluation of OntoTagger. H.6 Each linguistic level can be managed and annotated independently. • REJECTED: OntoTagger’s experiments and the dependencies observed among the morphosyntactic annotations, and between them and the syntactic annotations. In fact, Hypothesis H.6 was already rejected when OntoTag’s ontologies were developed. We observed then that several linguistic units stand on an interface between levels, belonging thereby to both of them (such as morphosyntactic units, which belong to both the morphological level and the syntactic level). Therefore, the annotations of these levels overlap and cannot be handled independently when merged into a unique multileveled annotation. 4. OTHER MAIN RESULTS AND CONTRIBUTIONS First, interoperability is a hot topic for both the linguistic annotation community and the whole Computer Science field. The specification (and implementation) of OntoTag’s architecture for the combination and integration of linguistic (annotation) tools and annotations by means of ontologies shows a way to make these different linguistic annotation tools and annotations interoperate in practice. Second, as mentioned above, the elements involved in linguistic annotation were formalised in a set (or network) of ontologies (OntoTag’s linguistic ontologies). • On the one hand, OntoTag’s network of ontologies consists of − The Linguistic Unit Ontology (LUO), which includes a mostly hierarchical formalisation of the different types of linguistic elements (i.e., units) identifiable in a written text; − The Linguistic Attribute Ontology (LAO), which includes also a mostly hierarchical formalisation of the different types of features that characterise the linguistic units included in the LUO; − The Linguistic Value Ontology (LVO), which includes the corresponding formalisation of the different values that the attributes in the LAO can take; − The OIO (OntoTag’s Integration Ontology), which  Includes the knowledge required to link, combine and unite the knowledge represented in the LUO, the LAO and the LVO;  Can be viewed as a knowledge representation ontology that describes the most elementary vocabulary used in the area of annotation. • On the other hand, OntoTag’s ontologies incorporate the knowledge included in the different standards and recommendations for linguistic annotation released so far, such as those developed within the EAGLES and the SIMPLE European projects or by the ISO/TC 37 committee: − As far as morphosyntactic annotations are concerned, OntoTag’s ontologies formalise the terms in the EAGLES (1996a) recommendations and their corresponding terms within the ISO Morphosyntactic Annotation Framework (ISO/MAF, 2008) standard; − As for syntactic annotations, OntoTag’s ontologies incorporate the terms in the EAGLES (1996b) recommendations and their corresponding terms within the ISO Syntactic Annotation Framework (ISO/SynAF, 2010) standard draft; − Regarding semantic annotations, OntoTag’s ontologies generalise and extend the recommendations in EAGLES (1996a; 1996b) and, since no stable standards or standard drafts have been released for semantic annotation by ISO/TC 37 yet, they incorporate the terms in SIMPLE (2000) instead; − The terms coming from all these recommendations and standards were supplemented by those within the ISO Data Category Registry (ISO/DCR, 2008) and also of the ISO Linguistic Annotation Framework (ISO/LAF, 2009) standard draft when developing OntoTag’s ontologies. Third, we showed that the combination of the results of tools annotating at the same level can yield better results (both in precision and in recall) than each tool separately. In particular, 1. OntoTagger clearly outperformed two of the tools integrated into its configuration, namely DataLexica and FDG in all the combination sub-phases in which they overlapped (i.e. POS tagging, lemma annotation and morphological feature annotation). As far as the remaining tool is concerned, i.e. LACELL’s tagger, it was also outperformed by OntoTagger in POS tagging and lemma annotation, and it did not behave better than OntoTagger in the morphological feature annotation layer. 2. As an immediate result, this implies that a) This type of combination architecture configurations can be applied in order to improve significantly the accuracy of linguistic annotations; and b) Concerning the morphosyntactic level, this could be regarded as a way of constructing more robust and more accurate POS tagging systems. Fourth, Semantic Web annotations are usually performed by humans or else by machine learning systems. Both of them leave much to be desired: the former, with respect to their annotation rate; the latter, with respect to their (average) precision and recall. In this work, we showed how linguistic tools can be wrapped in order to annotate automatically Semantic Web pages using ontologies. This entails their fast, robust and accurate semantic annotation. As a way of example, as mentioned in Sub-goal 5.5, we developed a particular OntoTagger module for the recognition, classification and labelling of named entities, according to the MUC and ACE tagsets (Chinchor, 1997; Doddington et al., 2004). These tagsets were further specified by means of a domain ontology, namely the Cinema Named Entities Ontology (CNEO). This module was applied to the automatic annotation of ten different web pages containing cinema reviews (that is, around 5000 words). In addition, the named entities annotated with this module were also labelled as instances (or individuals) of the classes included in the CNEO and, then, were used to populate this domain ontology. • The statistical results obtained from the evaluation of this particular module of OntoTagger can be summarised as follows. On the one hand, as far as recall (R) is concerned, (R.1) the lowest value was 76,40% (for file 7); (R.2) the highest value was 97, 50% (for file 3); and (R.3) the average value was 88,73%. On the other hand, as far as the precision rate (P) is concerned, (P.1) its minimum was 93,75% (for file 4); (R.2) its maximum was 100% (for files 1, 5, 7, 8, 9, and 10); and (R.3) its average value was 98,99%. • These results, which apply to the tasks of named entity annotation and ontology population, are extraordinary good for both of them. They can be explained on the basis of the high accuracy of the annotations provided by OntoTagger at the lower levels (mainly at the morphosyntactic level). However, they should be conveniently qualified, since they might be too domain- and/or language-dependent. It should be further experimented how our approach works in a different domain or a different language, such as French, English, or German. • In any case, the results of this application of Human Language Technologies to Ontology Population (and, accordingly, to Ontological Engineering) seem very promising and encouraging in order for these two areas to collaborate and complement each other in the area of semantic annotation. Fifth, as shown in the State of the Art of this work, there are different approaches and models for the semantic annotation of texts, but all of them focus on a particular view of the semantic level. Clearly, all these approaches and models should be integrated in order to bear a coherent and joint semantic annotation level. OntoTag shows how (i) these semantic annotation layers could be integrated together; and (ii) they could be integrated with the annotations associated to other annotation levels. Sixth, we identified some recommendations, best practices and lessons learned for annotation standardisation, interoperation and merge. They show how standardisation (via ontologies, in this case) enables the combination, integration and interoperation of different linguistic tools and their annotations into a multilayered (or multileveled) linguistic annotation, which is one of the hot topics in the area of Linguistic Annotation. And last but not least, OntoTag’s annotation scheme and OntoTagger’s annotation schemas show a way to formalise and annotate coherently and uniformly the different units and features associated to the different levels and layers of linguistic annotation. This is a great scientific step ahead towards the global standardisation of this area, which is the aim of ISO/TC 37 (in particular, Subcommittee 4, dealing with the standardisation of linguistic annotations and resources).

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This paper presents the complete development of the Simbiosis Smart Walker. The device is equipped with a set of sensor subsystems to acquire user-machine interaction forces and the temporal evolution of user's feet during gait. The authors present an adaptive filtering technique used for the identification and separation of different components found on the human-machine interaction forces. This technique allowed isolating the components related with the navigational commands and developing a Fuzzy logic controller to guide the device. The Smart Walker was clinically validated at the Spinal Cord Injury Hospital of Toledo - Spain, presenting great acceptability by spinal chord injury patients and clinical staff