Gotowa bibliografia na temat „Encoding Mappings”

Abstract Objective The general equivalence mappings (GEMs) and reimbursement mappings (RMs) facilitate translation between ICD-9-CM and ICD-10-CM. This study compared prospectively dual-encoded diagnoses assigned by professional coders with the GEMs/RMs in a clinical setting. Materials and Methods Professional coders manually encoded diagnoses from 100 primary care notes into both ICD-9-CM and ICD-10-CM. The investigators evaluated whether manual mappings were reproducible using the GEMs/RMs. Reproducible mappings with one ICD-9-CM and one ICD-10-CM code (“one-to-one”) were classified as exact or approximate using GEMs flags. Mismatches were characterized manually. Results Manual encodings were reproducible from the forward GEMs, backward GEMs, and RMs in 85.2%, 90.4%, and 88.1% of diagnoses, respectively. For one-to-one, reproducible mappings, 61% (forward) and 63% (backward) were approximate mappings compared to 85% and 95% in the GEMs as a whole. Mismatches between manual and GEMs encodings were due to differences in coder interpretation (11%–13%), subtle hierarchical differences (52%–55%), or unknown reasons (32%–35%). Discussion This study highlights inconsistencies between manual encoding and using the GEMs/RMs. The number of approximate mappings in our population compared to all one-to-one GEMs entries supports the notion that statistics describing the GEMs as a whole might not represent the most important mappings for each organization. The mismatch characteristics highlight the subtle differences between manual encoding and using the GEMs/RMs. Conclusion These results support the need for organizations to assess the GEMs and RMs in their own environment to avoid changes in reimbursement and longitudinal statistics.

Neural encoding and decoding provide perspectives for understanding neural representations of sensory inputs. Recent functional magnetic resonance imaging (fMRI) studies have succeeded in building prediction models for encoding and decoding numerous stimuli by representing a complex stimulus as a combination of simple elements. While arbitrary visual images were reconstructed using a modular model that combined the outputs of decoder modules for multiscale local image bases (elements), the shapes of the image bases were heuristically determined. In this work, we propose a method to establish mappings between the stimulus and the brain by automatically extracting modules from measured data. We develop a model based on Bayesian canonical correlation analysis, in which each module is modeled by a latent variable that relates a set of pixels in a visual image to a set of voxels in an fMRI activity pattern. The estimated mapping from a latent variable to pixels can be regarded as an image basis. We show that the model estimates a modular representation with spatially localized multiscale image bases. Further, using the estimated mappings, we derive encoding and decoding models that produce accurate predictions for brain activity and stimulus images. Our approach thus provides a novel means of revealing neural representations of stimuli by automatically extracting modules, which can be used to generate effective prediction models for encoding and decoding.

In this work, we consider the zero-delay transmission of bivariate Gaussian sources over a Gaussian broadcast channel with one-bit analog-to-digital converter (ADC) front ends. An outer bound on the conditional distortion region is derived. Focusing on the minimization of the average distortion, two types of methods are proposed to design nonparametric mappings. The first one is based on the joint optimization between the encoder and decoder with the use of an iterative algorithm. In the second method, we derive the necessary conditions to develop the optimal encoder numerically. Using these necessary conditions, an algorithm based on gradient descent search is designed. Subsequently, the characteristics of the optimized encoding mapping structure are discussed, and inspired by which, several parametric mappings are proposed. Numerical results show that the proposed parametric mappings outperform the uncoded scheme and previous parametric mappings for broadcast channels with infinite resolution ADC front ends. The nonparametric mappings succeed in outperforming the parametric mappings. The causes for the differences between the performances of two nonparametric mappings are analyzed. The average distortions of the parametric and nonparametric mappings proposed here are close to the bound for the cases with one-bit ADC front ends in low channel signal-to-noise ratio regions.

In this research, we perform a multiresolution analysis of the mappings used in fractal image compression. We derive the transform-domain structure of the mappings and demonstrate a close connection between fractal image compression and wavelet transform coding using the Haar basis. We show that under certain conditions, the mappings correspond to a hierarchy of affine mappings between the subbands of the transformed image. Our analysis provides new insights into the mechanism underlying fractal image compression, leads to a new non-iterative transform-domain decoding algorithm, and suggests a new transform-domain encoding method with extensions to wavelets other than the Haar transform.

Humans can show striking capacity limitations in sensorimotor processing. Fortunately, these limitations can be attenuated with training. However, less fortunately, training benefits often remain limited to trained tasks. Recent behavioral observations suggest that the extent to which training transfers may depend on the specific stage of information processing that is being executed. Training benefits for a task that taps the consolidation of sensory information (sensory encoding) transfer to new stimulus–response mappings, whereas benefits for selecting an appropriate action (decision-making/response selection) remain specific to the trained mappings. Therefore, training may have dissociable influences on the neural events underlying subsequent sensorimotor processing stages. Here, we used EEG to investigate this possibility. In a pretraining baseline session, participants completed two four-alternative-choice response time tasks, presented both as a single task and as part of a dual task (with another task). The training group completed a further 3,000 training trials on one of the four-alternative-choice tasks. Hence, one task became trained, whereas the other remained untrained. At test, a negative-going component that is sensitive to sensory-encoding demands (N2) showed increased amplitudes and reduced latencies for trained and untrained mappings relative to a no-train control group. In contrast, the onset of the stimulus-locked lateralized readiness potential, a component that reflects the activation of motor plans, was reduced only for tasks that employed trained stimulus–response mappings, relative to untrained stimulus–response mappings and controls. Collectively, these results show that training benefits are dissociable for the brain events that reflect distinct sensorimotor processing stages.

The organization of homologous protein sequences into multiple sequence alignments (MSAs) is a cornerstone of modern analysis of proteins. Recent focus on the importance of alternatively-spliced isoforms in disease and cell biology has highlighted the need for MSA software that can appropriately account for isoforms and the exon-length insertions or deletions that isoforms may have relative to each other. We previously developed Mirage, a software package for generating MSAs for isoforms spanning multiple species. Here, we present Mirage2, which retains the fundamental algorithms of the original Mirage implementation while providing substantially improved translated mapping and improving several aspects of usability. We demonstrate that Mirage2 is highly effective at mapping proteins to their encoding exons, and that these protein-genome mappings lead to extremely accurate intron-aware alignments. Additionally, Mirage2 implements a number of engineering improvements that simplify installation and use.

In this paper I want to explore the systemic-functional notion of ‘grammatical metaphor’ from a cross-linguistic perspective. After a brief introduction to the concept of ‘grammatical metaphor’, I shall discuss the distinction between ‘congruent’ and ‘metaphorical’ encodings of meaning, as well as the distinction between rankshift, transcategorization, and grammatical metaphor as semogenic resources (Section 1). In a second section, I shall then focus on ideational grammatical metaphors in English and German and revisit the notion of direct vs. indirect mapping of experiential and logical semantics onto lexicogrammar (Section 2). It will be argued that ‘directness of encoding’ within one language can be defined with the help of the concept of ‘transparency’ or ‘motivation’ of encoding between levels. Across and between languages, however, the notion of ‘directness’ either has to be seen from the perspective of one of the languages involved, or from the perspective of a generalized semantics and grammar. In Section 3, I shall then explore the question of the experiential vs. logical encoding of semantic categories across languages, and of how this relates to metaphoricity. I shall exemplify and discuss the fact that in cross-linguistic analyses, one cannot consider any one of a given set of experiential or logical encodings of some unit of meaning as ‘congruent’ or ‘direct’, as long as one does not have a cross-linguistic semantics to establish ‘motivation’ and ‘transparentness’ on. It will also be argued that some of the differences in texts across languages as to what counts as ‘congruent’ can be predicted from comparisons between the language-specific grammatical systems involved. Other differences, however, seem to rely heavily on registerial influences and cultural factors. In Section 4, then, I shall inquire into the question of whether and precisely in what sense we can speak of two different types of grammatical metaphor, dependent on whether they involve a relocation in rank or a mere re-arrangement of mappings of semantic and lexicogrammatical functions. These types of metaphor, it will be argued, have different implications for the metaphoricity of the clause as a whole, as well as for the ‘density’ of the packaging of meaning.

When a new sensorimotor mapping is learned through practice, learning commonly transfers to unpracticed regions of task space, that is, generalization ensues. Does generalization reflect fixed properties of movement representations in the nervous system and thereby limit what visuomotor mappings can and cannot be learned? Or does what needs to be learned determine the shape of generalization? We used the broad generalization properties of visuomotor gain adaptation to address these questions. Adaptation to a single gain for reaching movements is known to generalize broadly across movement directions. By training subjects on two different gains in two directions, we set up a potential conflict between generalization patterns: if generalization of gain adaptation indicates fixed properties of movement amplitude encoding, then learning two different gains in different directions should not be possible. Conversely, if generalization is flexible, then it should be possible to learn two gains. We found that subjects were able to learn two gains simultaneously, although more slowly than when they adapted to a single gain. Analysis of the resulting double-gain generalization patterns, however, unexpectedly revealed that generalization around each training direction did not arise de novo, but could be explained by a weighted combination of single-gain generalization patterns, in which the weighting takes into account the relative angular separation between training directions. Our findings therefore demonstrate that the mappings to each training target can be fully learned through reweighting of single-gain generalization patterns and not through a categorical alteration of these functions. These results are consistent with a modular decomposition approach to visuomotor adaptation, in which a complex mapping results from a combination of simpler mappings in a “mixture-of-experts” architecture.

A constant demand in engineering design is to couple aesthetics and functionality of design. In this paper, a method is proposed to rapidly update the structural analysis models given the modifications made in the styling/packaging designs, forming a concurrent mechanism for developing the automotive styling and body structure. The seemingly disparate domains are represented by and thus coupled through a pair of wireframes. A joint mapping based on the hard points in packaging and a part mapping encoding local influences between wireframes are established. The deformation transfer from one of the wireframes to the other is solved as an optimization with constraints obtained from the two mappings. Finally, the finite element mesh model is adapted in accordance with the deformed structural wireframe, using a mesh morphing method based on the free-form deformation technique. Numerical results validate the proposed method and demonstrate its effectiveness.

This article asserts that using crossmodal auditory and tactile interaction can aid mobile touchscreen users in accessing data non-visually and, by providing a choice of modalities, can help to overcome problems that occur in different mobile situations where one modality may be less suitable than another (Hoggan, 2010). By encoding data using the crossmodal parameters of audio and vibration, users can learn mappings and translate information between both modalities. In this regard, data may be presented to the most appropriate modality given the situation and surrounding environment.

Data masses on the World Wide Web can hardly be managed by humans or machines. One option is the formal description and linking of data sources using Semantic Web and Linked Data technologies. Ontologies written in standardised languages foster the sharing and linking of data as they provide a means to formally define concepts and relations between these concepts. A second option is visualisation. The visual representation allows humans to perceive information more directly, using the highly developed visual sense. Relatively few efforts have been made on combining both options, although the formality and rich semantics of ontological data make it an ideal candidate for visualisation. Advanced visualisation design systems support the visualisation of tabular, typically statistical data. However, visualisations of ontological data still have to be created manually, since automated solutions are often limited to generic lists or node-link diagrams. Also, the semantics of ontological data are not exploited for guiding users through visualisation tasks. Finally, once a good visualisation setting has been created, it cannot easily be reused and shared. Trying to tackle these problems, we had to answer how to define composable and shareable mappings from ontological data to visual means and how to guide the visual mapping of ontological data. We present an approach that allows for the guided visualisation of ontological data, the creation of effective graphics and the reuse of visualisation settings. Instead of generic graphics, we aim at tailor-made graphics, produced using the whole palette of visual means in a flexible, bottom-up approach. It not only allows for visualising ontologies, but uses ontologies to guide users when visualising data and to drive the visualisation process at various places: First, as a rich source of information on data characteristics, second, as a means to formally describe the vocabulary for building abstract graphics, and third, as a knowledge base of facts on visualisation. This is why we call our approach ontology-driven. We suggest generating an Abstract Visual Model (AVM) to represent and »synthesise« a graphic following a role-based approach, inspired by the one used by J. v. Engelhardt for the analysis of graphics. It consists of graphic objects and relations formalised in the Visualisation Ontology (VISO). A mappings model, based on the declarative RDFS/OWL Visualisation Language (RVL), determines a set of transformations from the domain data to the AVM. RVL allows for composable visual mappings that can be shared and reused across platforms. To guide the user, for example, we discourage the construction of mappings that are suboptimal according to an effectiveness ranking formalised in the fact base and suggest more effective mappings instead. The guidance process is flexible, since it is based on exchangeable rules. VISO, RVL and the AVM are additional contributions of this thesis. Further, we initially analysed the state of the art in visualisation and RDF-presentation comparing 10 approaches by 29 criteria. Our approach is unique because it combines ontology-driven guidance with composable visual mappings. Finally, we compare three prototypes covering the essential parts of our approach to show its feasibility. We show how the mapping process can be supported by tools displaying warning messages for non-optimal visual mappings, e.g., by considering relation characteristics such as »symmetry«. In a constructive evaluation, we challenge both the RVL language and the latest prototype trying to regenerate sketches of graphics we created manually during analysis. We demonstrate how graphics can be varied and complex mappings can be composed from simple ones. Two thirds of the sketches can be almost or completely specified and half of them can be almost or completely implemented
Datenmassen im World Wide Web können kaum von Menschen oder Maschinen erfasst werden. Eine Option ist die formale Beschreibung und Verknüpfung von Datenquellen mit Semantic-Web- und Linked-Data-Technologien. Ontologien, in standardisierten Sprachen geschrieben, befördern das Teilen und Verknüpfen von Daten, da sie ein Mittel zur formalen Definition von Konzepten und Beziehungen zwischen diesen Konzepten darstellen. Eine zweite Option ist die Visualisierung. Die visuelle Repräsentation ermöglicht es dem Menschen, Informationen direkter wahrzunehmen, indem er seinen hochentwickelten Sehsinn verwendet. Relativ wenige Anstrengungen wurden unternommen, um beide Optionen zu kombinieren, obwohl die Formalität und die reichhaltige Semantik ontologische Daten zu einem idealen Kandidaten für die Visualisierung machen. Visualisierungsdesignsysteme unterstützen Nutzer bei der Visualisierung von tabellarischen, typischerweise statistischen Daten. Visualisierungen ontologischer Daten jedoch müssen noch manuell erstellt werden, da automatisierte Lösungen häufig auf generische Listendarstellungen oder Knoten-Kanten-Diagramme beschränkt sind. Auch die Semantik der ontologischen Daten wird nicht ausgenutzt, um Benutzer durch Visualisierungsaufgaben zu führen. Einmal erstellte Visualisierungseinstellungen können nicht einfach wiederverwendet und geteilt werden. Um diese Probleme zu lösen, mussten wir eine Antwort darauf finden, wie die Definition komponierbarer und wiederverwendbarer Abbildungen von ontologischen Daten auf visuelle Mittel geschehen könnte und wie Nutzer bei dieser Abbildung geführt werden könnten. Wir stellen einen Ansatz vor, der die geführte Visualisierung von ontologischen Daten, die Erstellung effektiver Grafiken und die Wiederverwendung von Visualisierungseinstellungen ermöglicht. Statt auf generische Grafiken zielt der Ansatz auf maßgeschneiderte Grafiken ab, die mit der gesamten Palette visueller Mittel in einem flexiblen Bottom-Up-Ansatz erstellt werden. Er erlaubt nicht nur die Visualisierung von Ontologien, sondern verwendet auch Ontologien, um Benutzer bei der Visualisierung von Daten zu führen und den Visualisierungsprozess an verschiedenen Stellen zu steuern: Erstens als eine reichhaltige Informationsquelle zu Datencharakteristiken, zweitens als Mittel zur formalen Beschreibung des Vokabulars für den Aufbau von abstrakten Grafiken und drittens als Wissensbasis von Visualisierungsfakten. Deshalb nennen wir unseren Ansatz ontologie-getrieben. Wir schlagen vor, ein Abstract Visual Model (AVM) zu generieren, um eine Grafik rollenbasiert zu synthetisieren, angelehnt an einen Ansatz der von J. v. Engelhardt verwendet wird, um Grafiken zu analysieren. Das AVM besteht aus grafischen Objekten und Relationen, die in der Visualisation Ontology (VISO) formalisiert sind. Ein Mapping-Modell, das auf der deklarativen RDFS/OWL Visualisation Language (RVL) basiert, bestimmt eine Menge von Transformationen von den Quelldaten zum AVM. RVL ermöglicht zusammensetzbare »Mappings«, visuelle Abbildungen, die über Plattformen hinweg geteilt und wiederverwendet werden können. Um den Benutzer zu führen, bewerten wir Mappings anhand eines in der Faktenbasis formalisierten Effektivitätsrankings und schlagen ggf. effektivere Mappings vor. Der Beratungsprozess ist flexibel, da er auf austauschbaren Regeln basiert. VISO, RVL und das AVM sind weitere Beiträge dieser Arbeit. Darüber hinaus analysieren wir zunächst den Stand der Technik in der Visualisierung und RDF-Präsentation, indem wir 10 Ansätze nach 29 Kriterien vergleichen. Unser Ansatz ist einzigartig, da er eine ontologie-getriebene Nutzerführung mit komponierbaren visuellen Mappings vereint. Schließlich vergleichen wir drei Prototypen, welche die wesentlichen Teile unseres Ansatzes umsetzen, um seine Machbarkeit zu zeigen. Wir zeigen, wie der Mapping-Prozess durch Tools unterstützt werden kann, die Warnmeldungen für nicht optimale visuelle Abbildungen anzeigen, z. B. durch Berücksichtigung von Charakteristiken der Relationen wie »Symmetrie«. In einer konstruktiven Evaluation fordern wir sowohl die RVL-Sprache als auch den neuesten Prototyp heraus, indem wir versuchen Skizzen von Grafiken umzusetzen, die wir während der Analyse manuell erstellt haben. Wir zeigen, wie Grafiken variiert werden können und komplexe Mappings aus einfachen zusammengesetzt werden können. Zwei Drittel der Skizzen können fast vollständig oder vollständig spezifiziert werden und die Hälfte kann fast vollständig oder vollständig umgesetzt werden

Bibliography: leaves 127-166. This study describes the isolation, sequencing and characterization of two cDNAs encoding barley (1-4)-B-xylanase isoenzymes X-I and X-II and the gene corresponding to isoenzyme X. The results of genomic Southern blot analyses indicate that the barley (1-4)-B-xylanase gene family consists of at least 3 genes which are mapped to a single locus on the long arm of chromosome 7(5H). The cDNA is used to monitor tissue-specific expression, developmental regulation and hormonal control of the (1-4)-B-xylanase genes.

Thesis (M.S.)--University of Kentucky, 2005.
Title from document title page (viewed on November 8, 2005). Document formatted into pages; contains vii, 34 p. : ill. Includes abstract and vita. Includes bibliographical references (p. 31-33).

Learning new object-name associations (i.e., word learning) is an ability crucial to normal development starting in early childhood and continuing through the lifespan. To learn a new word, an object must be associated with an arbitrary phonological (or orthographic) string representing a word. The declarative memory system formulates and encodes associations between two arbitrary stimuli and has been well established as playing a critical role for adult word learning. Research investigating the neural substrates of the declarative memory system and word learning has implicated the hippocampus and the surrounding medial temporal lobe (MTL) as crucial structures. A substantial literature on populations with damage to these particular structures (e.g., hippocampal amnesia, temporal lobectomy) has supports the view that without these structures, declarative learning, and word learning by extension, is grossly impaired. However, a recent study Sharon and colleagues (2011) suggested that non-MTL structures may be sufficient to support word learning under special study conditions ("fast mapping") (Sharon, Moscovitch, & Gilboa, 2011). Fast mapping is a word-learning phenomenon described as the ability to acquire the name for a new word in a single exposure to an unknown word and unfamiliar referent alongside a known word with its referent (e.g., Carey & Bartlett, 1978; Carey, 2010). This study evaluated the ability of patients with unilateral temporal lobectomy (TL) following early-onset temporal lobe epilepsy to learn new object-name associations in two different word learning conditions: fast mapping (FM) and explicit encoding (EE). The word learning performance was evaluated relative to a group of healthy normal comparison participants (NC). The goal of this study was to examine the role of the hippocampus in word learning to answer the question: does a FM condition promote word learning in participants with temporal lobe epilepsy who have had a left temporal lobectomy? NC participants were able to acquire a rich representation of novel items (as evidenced by improved familiarity ratings and generalization of items) while TL participants had severely impaired performance on free recall, recognition testing, and generalization tasks. TL participants did not learn novel object-name associations despite a FM paradigm while the NC group performed significantly above chance on recognition testing. These findings in conjunction with broadly similar results obtained from hippocampal amnesic patients tested using the same paradigm (Warren & Duff, 2012), support the necessity of the hippocampus for rapid and flexible associations to be obtained via the declarative memory system.

Data masses on the World Wide Web can hardly be managed by humans or machines. One option is the formal description and linking of data sources using Semantic Web and Linked Data technologies. Ontologies written in standardised languages foster the sharing and linking of data as they provide a means to formally define concepts and relations between these concepts. A second option is visualisation. The visual representation allows humans to perceive information more directly, using the highly developed visual sense. Relatively few efforts have been made on combining both options, although the formality and rich semantics of ontological data make it an ideal candidate for visualisation. Advanced visualisation design systems support the visualisation of tabular, typically statistical data. However, visualisations of ontological data still have to be created manually, since automated solutions are often limited to generic lists or node-link diagrams. Also, the semantics of ontological data are not exploited for guiding users through visualisation tasks. Finally, once a good visualisation setting has been created, it cannot easily be reused and shared. Trying to tackle these problems, we had to answer how to define composable and shareable mappings from ontological data to visual means and how to guide the visual mapping of ontological data. We present an approach that allows for the guided visualisation of ontological data, the creation of effective graphics and the reuse of visualisation settings. Instead of generic graphics, we aim at tailor-made graphics, produced using the whole palette of visual means in a flexible, bottom-up approach. It not only allows for visualising ontologies, but uses ontologies to guide users when visualising data and to drive the visualisation process at various places: First, as a rich source of information on data characteristics, second, as a means to formally describe the vocabulary for building abstract graphics, and third, as a knowledge base of facts on visualisation. This is why we call our approach ontology-driven. We suggest generating an Abstract Visual Model (AVM) to represent and »synthesise« a graphic following a role-based approach, inspired by the one used by J. v. Engelhardt for the analysis of graphics. It consists of graphic objects and relations formalised in the Visualisation Ontology (VISO). A mappings model, based on the declarative RDFS/OWL Visualisation Language (RVL), determines a set of transformations from the domain data to the AVM. RVL allows for composable visual mappings that can be shared and reused across platforms. To guide the user, for example, we discourage the construction of mappings that are suboptimal according to an effectiveness ranking formalised in the fact base and suggest more effective mappings instead. The guidance process is flexible, since it is based on exchangeable rules. VISO, RVL and the AVM are additional contributions of this thesis. Further, we initially analysed the state of the art in visualisation and RDF-presentation comparing 10 approaches by 29 criteria. Our approach is unique because it combines ontology-driven guidance with composable visual mappings. Finally, we compare three prototypes covering the essential parts of our approach to show its feasibility. We show how the mapping process can be supported by tools displaying warning messages for non-optimal visual mappings, e.g., by considering relation characteristics such as »symmetry«. In a constructive evaluation, we challenge both the RVL language and the latest prototype trying to regenerate sketches of graphics we created manually during analysis. We demonstrate how graphics can be varied and complex mappings can be composed from simple ones. Two thirds of the sketches can be almost or completely specified and half of them can be almost or completely implemented.:Legend and Overview of Prefixes xiii 1 Introduction 1 2 Background 11 2.1 Visualisation 11 2.1.1 What is Visualisation? 11 2.1.2 What are the Benefits of Visualisation? 12 2.1.3 Visualisation Related Terms Used in this Thesis 12 2.1.4 Visualisation Models and Architectural Patterns 12 2.1.5 Visualisation Design Systems 14 2.1.6 What is the Difference between Visual Mapping and Styling? 14 2.1.7 Lessons Learned from Style Sheet Languages 15 2.2 Data 16 2.2.1 Data – Information – Knowledge 17 2.2.2 Structured Data 17 2.2.3 Ontologies in Computer Science 19 2.2.4 The Semantic Web and its Languages 19 2.2.5 Linked Data and Open Data 20 2.2.6 The Metamodelling Technological Space 21 2.2.7 SPIN 21 2.3 Guidance 22 2.3.1 Guidance in Visualisation 22 3 Problem Analysis 23 3.1 Problems of Ontology Visualisation Approaches 24 3.2 Research Questions 25 3.3 Set up of the Case Studies 25 3.3.1 Case Studies in the Life Sciences Domain 26 3.3.2 Case Studies in the Publishing Domain 26 3.3.3 Case Studies in the Software Technology Domain 27 3.4 Analysis of the Case Studies’ Ontologies 27 3.5 Manual Sketching of Graphics 29 3.6 Analysis of the Graphics for Typical Visualisation Cases 29 3.7 Requirements 33 3.7.1 Requirements for Visualisation and Interaction 34 3.7.2 Requirements for Data Awareness 34 3.7.3 Requirements for Reuse and Composition 34 3.7.4 Requirements for Variability 35 3.7.5 Requirements for Tooling Support and Guidance 35 3.7.6 Optional Features and Limitations 36 4 Analysis of the State of the Art 37 4.1 Related Visualisation Approaches 38 4.1.1 Short Overview of the Approaches 38 4.1.2 Detailed Comparison by Criteria 46 4.1.3 Conclusion – What Is Still Missing? 60 4.2 Visualisation Languages 62 4.2.1 Short Overview of the Compared Languages 62 4.2.2 Detailed Comparison by Language Criteria 66 4.2.3 Conclusion – What Is Still Missing? 71 4.3 RDF Presentation Languages 72 4.3.1 Short Overview of the Compared Languages 72 4.3.2 Detailed Comparison by Language Criteria 76 4.3.3 Additional Criteria for RDF Display Languages 87 4.3.4 Conclusion – What Is Still Missing? 89 4.4 Model-Driven Interfaces 90 4.4.1 Metamodel-Driven Interfaces 90 4.4.2 Ontology-Driven Interfaces 92 4.4.3 Combined Usage of the Metamodelling and Ontology Technological Space 94 5 A Visualisation Ontology – VISO 97 5.1 Methodology Used for Ontology Creation 100 5.2 Requirements for a Visualisation Ontology 100 5.3 Existing Approaches to Modelling in the Field of Visualisation 101 5.3.1 Terminologies and Taxonomies 101 5.3.2 Existing Visualisation Ontologies 102 5.3.3 Other Visualisation Models and Approaches to Formalisation 103 5.3.4 Summary 103 5.4 Technical Aspects of VISO 103 5.5 VISO/graphic Module – Graphic Vocabulary 104 5.5.1 Graphic Representations and Graphic Objects 105 5.5.2 Graphic Relations and Syntactic Structures 107 5.6 VISO/data Module – Characterising Data 110 5.6.1 Data Structure and Characteristics of Relations 110 5.6.2 The Scale of Measurement and Units 112 5.6.3 Properties for Characterising Data Variables in Statistical Data 113 5.7 VISO/facts Module – Facts for Vis. Constraints and Rules 115 5.7.1 Expressiveness of Graphic Relations 116 5.7.2 Effectiveness Ranking of Graphic Relations 118 5.7.3 Rules for Composing Graphics 119 5.7.4 Other Rules to Consider for Visual Mapping 124 5.7.5 Providing Named Value Collections 124 5.7.6 Existing Approaches to the Formalisation of Visualisation Knowledge . . 126 5.7.7 The VISO/facts/empiric Example Knowledge Base 126 5.8 Other VISO Modules 126 5.9 Conclusions and Future Work 127 5.10 Further Use Cases for VISO 127 5.11 VISO on the Web – Sharing the Vocabulary to Build a Community 128 6 A VISO-Based Abstract Visual Model – AVM 129 6.1 Graphical Notation Used in this Chapter 129 6.2 Elementary Graphic Objects and Graphic Attributes 131 6.3 N-Ary Relations 131 6.4 Binary Relations 131 6.5 Composition of Graphic Objects Using Roles 132 6.6 Composition of Graphic Relations Using Roles 132 6.7 Composition of Visual Mappings Using the AVM 135 6.8 Tracing 135 6.9 Is it Worth Having an Abstract Visual Model? 135 6.10 Discussion of Fresnel as a Related Language 137 6.11 Related Work 139 6.12 Limitations 139 6.13 Conclusions 140 7 A Language for RDFS/OWL Visualisation – RVL 141 7.1 Language Requirements 142 7.2 Main RVL Constructs 145 7.2.1 Mapping 145 7.2.2 Property Mapping 146 7.2.3 Identity Mapping 146 7.2.4 Value Mapping 147 7.2.5 Inheriting RVL Settings 147 7.2.6 Resource Mapping 148 7.2.7 Simplifications 149 7.3 Calculating Value Mappings 150 7.4 Defining Scale of Measurement 153 7.4.1 Determining the Scale of Measurement 154 7.5 Addressing Values in Value Mappings 156 7.5.1 Determining the Set of Addressed Source Values 156 7.5.2 Determining the Set of Addressed Target Values 157 7.6 Overlapping Value Mappings 158 7.7 Default Value Mapping 158 7.8 Default Labelling 159 7.9 Defining Interaction 159 7.10 Mapping Composition and Submappings 160 7.11 A Schema Language for RVL 160 7.11.1 Concrete Examples of the RVL Schema 163 7.12 Conclusions and Future Work 166 8 The OGVIC Approach 169 8.1 Ontology-Driven, Guided Editing of Visual Mappings 172 8.1.1 Classification of Constraints 172 8.1.2 Levels of Guidance 173 8.1.3 Implementing Constraint-Based Guidance 173 8.2 Support of Explicit and Composable Visual Mappings 177 8.2.1 Mapping Composition Cases 178 8.2.2 Selecting a Context 180 8.2.3 Using the Same Graphic Relation Multiple Times 181 8.3 Prototype P1 (TopBraid-Composer-based) 182 8.4 Prototype P2 (OntoWiki-based) 184 8.5 Prototype P3 (Java Implementation of RVL) 187 8.6 Lessons Learned from Prototypes & Future Work 190 8.6.1 Checking RVL Constraints and Visualisation Rules 190 8.6.2 A User Interface for Editing RVL Mappings 190 8.6.3 Graph Transformations with SPIN and SPARQL 1.1 Update 192 8.6.4 Selection and Filtering of Data 193 8.6.5 Interactivity and Incremental Processing 193 8.6.6 Rendering the Final Platform-Specific Code 196 9 Application 197 9.1 Coverage of Case Study Sketches and Necessary Features 198 9.2 Coverage of Visualisation Cases 201 9.3 Coverage of Requirements 205 9.4 Full Example 206 10 Conclusions 211 10.1 Contributions 211 10.2 Constructive Evaluation 212 10.3 Research Questions 213 10.4 Transfer to Other Models and Constraint Languages 213 10.5 Limitations 214 10.6 Future Work 214 Appendices 217 A Case Study Sketches 219 B VISO – Comparison of Visualisation Literature 229 C RVL 231 D RVL Example Mappings and Application 233 D.1 Listings of RVL Example Mappings as Required by Prototype P3 233 D.2 Features Required for Implementing all Sketches 235 D.3 JSON Format for Processing the AVM with D3 – Hierarchical Variant 238 Bibliography 238 List of Figures 251 List of Tables 254 List of Listings 257
Datenmassen im World Wide Web können kaum von Menschen oder Maschinen erfasst werden. Eine Option ist die formale Beschreibung und Verknüpfung von Datenquellen mit Semantic-Web- und Linked-Data-Technologien. Ontologien, in standardisierten Sprachen geschrieben, befördern das Teilen und Verknüpfen von Daten, da sie ein Mittel zur formalen Definition von Konzepten und Beziehungen zwischen diesen Konzepten darstellen. Eine zweite Option ist die Visualisierung. Die visuelle Repräsentation ermöglicht es dem Menschen, Informationen direkter wahrzunehmen, indem er seinen hochentwickelten Sehsinn verwendet. Relativ wenige Anstrengungen wurden unternommen, um beide Optionen zu kombinieren, obwohl die Formalität und die reichhaltige Semantik ontologische Daten zu einem idealen Kandidaten für die Visualisierung machen. Visualisierungsdesignsysteme unterstützen Nutzer bei der Visualisierung von tabellarischen, typischerweise statistischen Daten. Visualisierungen ontologischer Daten jedoch müssen noch manuell erstellt werden, da automatisierte Lösungen häufig auf generische Listendarstellungen oder Knoten-Kanten-Diagramme beschränkt sind. Auch die Semantik der ontologischen Daten wird nicht ausgenutzt, um Benutzer durch Visualisierungsaufgaben zu führen. Einmal erstellte Visualisierungseinstellungen können nicht einfach wiederverwendet und geteilt werden. Um diese Probleme zu lösen, mussten wir eine Antwort darauf finden, wie die Definition komponierbarer und wiederverwendbarer Abbildungen von ontologischen Daten auf visuelle Mittel geschehen könnte und wie Nutzer bei dieser Abbildung geführt werden könnten. Wir stellen einen Ansatz vor, der die geführte Visualisierung von ontologischen Daten, die Erstellung effektiver Grafiken und die Wiederverwendung von Visualisierungseinstellungen ermöglicht. Statt auf generische Grafiken zielt der Ansatz auf maßgeschneiderte Grafiken ab, die mit der gesamten Palette visueller Mittel in einem flexiblen Bottom-Up-Ansatz erstellt werden. Er erlaubt nicht nur die Visualisierung von Ontologien, sondern verwendet auch Ontologien, um Benutzer bei der Visualisierung von Daten zu führen und den Visualisierungsprozess an verschiedenen Stellen zu steuern: Erstens als eine reichhaltige Informationsquelle zu Datencharakteristiken, zweitens als Mittel zur formalen Beschreibung des Vokabulars für den Aufbau von abstrakten Grafiken und drittens als Wissensbasis von Visualisierungsfakten. Deshalb nennen wir unseren Ansatz ontologie-getrieben. Wir schlagen vor, ein Abstract Visual Model (AVM) zu generieren, um eine Grafik rollenbasiert zu synthetisieren, angelehnt an einen Ansatz der von J. v. Engelhardt verwendet wird, um Grafiken zu analysieren. Das AVM besteht aus grafischen Objekten und Relationen, die in der Visualisation Ontology (VISO) formalisiert sind. Ein Mapping-Modell, das auf der deklarativen RDFS/OWL Visualisation Language (RVL) basiert, bestimmt eine Menge von Transformationen von den Quelldaten zum AVM. RVL ermöglicht zusammensetzbare »Mappings«, visuelle Abbildungen, die über Plattformen hinweg geteilt und wiederverwendet werden können. Um den Benutzer zu führen, bewerten wir Mappings anhand eines in der Faktenbasis formalisierten Effektivitätsrankings und schlagen ggf. effektivere Mappings vor. Der Beratungsprozess ist flexibel, da er auf austauschbaren Regeln basiert. VISO, RVL und das AVM sind weitere Beiträge dieser Arbeit. Darüber hinaus analysieren wir zunächst den Stand der Technik in der Visualisierung und RDF-Präsentation, indem wir 10 Ansätze nach 29 Kriterien vergleichen. Unser Ansatz ist einzigartig, da er eine ontologie-getriebene Nutzerführung mit komponierbaren visuellen Mappings vereint. Schließlich vergleichen wir drei Prototypen, welche die wesentlichen Teile unseres Ansatzes umsetzen, um seine Machbarkeit zu zeigen. Wir zeigen, wie der Mapping-Prozess durch Tools unterstützt werden kann, die Warnmeldungen für nicht optimale visuelle Abbildungen anzeigen, z. B. durch Berücksichtigung von Charakteristiken der Relationen wie »Symmetrie«. In einer konstruktiven Evaluation fordern wir sowohl die RVL-Sprache als auch den neuesten Prototyp heraus, indem wir versuchen Skizzen von Grafiken umzusetzen, die wir während der Analyse manuell erstellt haben. Wir zeigen, wie Grafiken variiert werden können und komplexe Mappings aus einfachen zusammengesetzt werden können. Zwei Drittel der Skizzen können fast vollständig oder vollständig spezifiziert werden und die Hälfte kann fast vollständig oder vollständig umgesetzt werden.:Legend and Overview of Prefixes xiii 1 Introduction 1 2 Background 11 2.1 Visualisation 11 2.1.1 What is Visualisation? 11 2.1.2 What are the Benefits of Visualisation? 12 2.1.3 Visualisation Related Terms Used in this Thesis 12 2.1.4 Visualisation Models and Architectural Patterns 12 2.1.5 Visualisation Design Systems 14 2.1.6 What is the Difference between Visual Mapping and Styling? 14 2.1.7 Lessons Learned from Style Sheet Languages 15 2.2 Data 16 2.2.1 Data – Information – Knowledge 17 2.2.2 Structured Data 17 2.2.3 Ontologies in Computer Science 19 2.2.4 The Semantic Web and its Languages 19 2.2.5 Linked Data and Open Data 20 2.2.6 The Metamodelling Technological Space 21 2.2.7 SPIN 21 2.3 Guidance 22 2.3.1 Guidance in Visualisation 22 3 Problem Analysis 23 3.1 Problems of Ontology Visualisation Approaches 24 3.2 Research Questions 25 3.3 Set up of the Case Studies 25 3.3.1 Case Studies in the Life Sciences Domain 26 3.3.2 Case Studies in the Publishing Domain 26 3.3.3 Case Studies in the Software Technology Domain 27 3.4 Analysis of the Case Studies’ Ontologies 27 3.5 Manual Sketching of Graphics 29 3.6 Analysis of the Graphics for Typical Visualisation Cases 29 3.7 Requirements 33 3.7.1 Requirements for Visualisation and Interaction 34 3.7.2 Requirements for Data Awareness 34 3.7.3 Requirements for Reuse and Composition 34 3.7.4 Requirements for Variability 35 3.7.5 Requirements for Tooling Support and Guidance 35 3.7.6 Optional Features and Limitations 36 4 Analysis of the State of the Art 37 4.1 Related Visualisation Approaches 38 4.1.1 Short Overview of the Approaches 38 4.1.2 Detailed Comparison by Criteria 46 4.1.3 Conclusion – What Is Still Missing? 60 4.2 Visualisation Languages 62 4.2.1 Short Overview of the Compared Languages 62 4.2.2 Detailed Comparison by Language Criteria 66 4.2.3 Conclusion – What Is Still Missing? 71 4.3 RDF Presentation Languages 72 4.3.1 Short Overview of the Compared Languages 72 4.3.2 Detailed Comparison by Language Criteria 76 4.3.3 Additional Criteria for RDF Display Languages 87 4.3.4 Conclusion – What Is Still Missing? 89 4.4 Model-Driven Interfaces 90 4.4.1 Metamodel-Driven Interfaces 90 4.4.2 Ontology-Driven Interfaces 92 4.4.3 Combined Usage of the Metamodelling and Ontology Technological Space 94 5 A Visualisation Ontology – VISO 97 5.1 Methodology Used for Ontology Creation 100 5.2 Requirements for a Visualisation Ontology 100 5.3 Existing Approaches to Modelling in the Field of Visualisation 101 5.3.1 Terminologies and Taxonomies 101 5.3.2 Existing Visualisation Ontologies 102 5.3.3 Other Visualisation Models and Approaches to Formalisation 103 5.3.4 Summary 103 5.4 Technical Aspects of VISO 103 5.5 VISO/graphic Module – Graphic Vocabulary 104 5.5.1 Graphic Representations and Graphic Objects 105 5.5.2 Graphic Relations and Syntactic Structures 107 5.6 VISO/data Module – Characterising Data 110 5.6.1 Data Structure and Characteristics of Relations 110 5.6.2 The Scale of Measurement and Units 112 5.6.3 Properties for Characterising Data Variables in Statistical Data 113 5.7 VISO/facts Module – Facts for Vis. Constraints and Rules 115 5.7.1 Expressiveness of Graphic Relations 116 5.7.2 Effectiveness Ranking of Graphic Relations 118 5.7.3 Rules for Composing Graphics 119 5.7.4 Other Rules to Consider for Visual Mapping 124 5.7.5 Providing Named Value Collections 124 5.7.6 Existing Approaches to the Formalisation of Visualisation Knowledge . . 126 5.7.7 The VISO/facts/empiric Example Knowledge Base 126 5.8 Other VISO Modules 126 5.9 Conclusions and Future Work 127 5.10 Further Use Cases for VISO 127 5.11 VISO on the Web – Sharing the Vocabulary to Build a Community 128 6 A VISO-Based Abstract Visual Model – AVM 129 6.1 Graphical Notation Used in this Chapter 129 6.2 Elementary Graphic Objects and Graphic Attributes 131 6.3 N-Ary Relations 131 6.4 Binary Relations 131 6.5 Composition of Graphic Objects Using Roles 132 6.6 Composition of Graphic Relations Using Roles 132 6.7 Composition of Visual Mappings Using the AVM 135 6.8 Tracing 135 6.9 Is it Worth Having an Abstract Visual Model? 135 6.10 Discussion of Fresnel as a Related Language 137 6.11 Related Work 139 6.12 Limitations 139 6.13 Conclusions 140 7 A Language for RDFS/OWL Visualisation – RVL 141 7.1 Language Requirements 142 7.2 Main RVL Constructs 145 7.2.1 Mapping 145 7.2.2 Property Mapping 146 7.2.3 Identity Mapping 146 7.2.4 Value Mapping 147 7.2.5 Inheriting RVL Settings 147 7.2.6 Resource Mapping 148 7.2.7 Simplifications 149 7.3 Calculating Value Mappings 150 7.4 Defining Scale of Measurement 153 7.4.1 Determining the Scale of Measurement 154 7.5 Addressing Values in Value Mappings 156 7.5.1 Determining the Set of Addressed Source Values 156 7.5.2 Determining the Set of Addressed Target Values 157 7.6 Overlapping Value Mappings 158 7.7 Default Value Mapping 158 7.8 Default Labelling 159 7.9 Defining Interaction 159 7.10 Mapping Composition and Submappings 160 7.11 A Schema Language for RVL 160 7.11.1 Concrete Examples of the RVL Schema 163 7.12 Conclusions and Future Work 166 8 The OGVIC Approach 169 8.1 Ontology-Driven, Guided Editing of Visual Mappings 172 8.1.1 Classification of Constraints 172 8.1.2 Levels of Guidance 173 8.1.3 Implementing Constraint-Based Guidance 173 8.2 Support of Explicit and Composable Visual Mappings 177 8.2.1 Mapping Composition Cases 178 8.2.2 Selecting a Context 180 8.2.3 Using the Same Graphic Relation Multiple Times 181 8.3 Prototype P1 (TopBraid-Composer-based) 182 8.4 Prototype P2 (OntoWiki-based) 184 8.5 Prototype P3 (Java Implementation of RVL) 187 8.6 Lessons Learned from Prototypes & Future Work 190 8.6.1 Checking RVL Constraints and Visualisation Rules 190 8.6.2 A User Interface for Editing RVL Mappings 190 8.6.3 Graph Transformations with SPIN and SPARQL 1.1 Update 192 8.6.4 Selection and Filtering of Data 193 8.6.5 Interactivity and Incremental Processing 193 8.6.6 Rendering the Final Platform-Specific Code 196 9 Application 197 9.1 Coverage of Case Study Sketches and Necessary Features 198 9.2 Coverage of Visualisation Cases 201 9.3 Coverage of Requirements 205 9.4 Full Example 206 10 Conclusions 211 10.1 Contributions 211 10.2 Constructive Evaluation 212 10.3 Research Questions 213 10.4 Transfer to Other Models and Constraint Languages 213 10.5 Limitations 214 10.6 Future Work 214 Appendices 217 A Case Study Sketches 219 B VISO – Comparison of Visualisation Literature 229 C RVL 231 D RVL Example Mappings and Application 233 D.1 Listings of RVL Example Mappings as Required by Prototype P3 233 D.2 Features Required for Implementing all Sketches 235 D.3 JSON Format for Processing the AVM with D3 – Hierarchical Variant 238 Bibliography 238 List of Figures 251 List of Tables 254 List of Listings 257

Maternal behavior is the complex array of caregiving behaviors females display towards offspring. In rats, the transition to motherhood depends on the action of various hormones, especially estradiol near parturition, which primes the maternal circuitry to respond to pups upon first encounter at parturition with appropriate maternal behavior. Although virgin rats avoid pups, new mothers are highly motivated to interact with pups, and their maternal behavior depends on the functional interaction between the medial preoptic area (mPOA) and the ventral tegmental area (VTA). However, a precise mapping of the VTA-projecting mPOA neurons remains to be elucidated. To determine whether pup-responsive neurons in the mPOA project to the VTA, we injected the retrograde tracer Fluorogold (FG) into the VTA of new mother and virgin female rats. Six days later, females were exposed to 3 pups for 5 minutes, and their brains processed to visualize FG and c-Fos immunostaining. In addition, we further characterized the molecular phenotype of these neurons by performing immunohistochemistry against estrogen receptor alpha (Esr1). As expected, the behavior of postpartum and virgin females toward pups was different. Mothers readily approached pups and displayed maternal behavior, whereas virgins avoided interaction with pups. Despite these disparate responses to pups, no differences were found in the number and distribution of mPOAc-Fos→VTA neurons. In addition, in both postpartum and virgin females, a significant proportion of these pup-responsive mPOA→VTA projecting neurons also express Esr1. Further functional interrogation of these c-Fos+/Esr1+ mPOA→VTA neurons in virgins and mothers might elucidate distinct circuit dynamics potentially underlying their behavioral differences towards pups.

This book presents theoretical and empirical research on the syntax of events within the broader framework of generative grammar. A central theoretical concern is how conceptual meaning interacts with narrow syntactic computation in the derivation of the information of an event. A set of Integration Conditions are proposed. Building on the Conceptual-Intentional Interface Conditions proposed in Chomsky’s (1995, 2000, 2001) Minimalist Programme, the Integration Conditions require that the content of the predicate be licensed by theta-role information generated by narrow syntax. Another theoretical component concerns the functional structure of events, which is related to such issues as the parallel between the event and nominal domains, the mapping of a predicate onto an entity, as well as the grammatical foundation of verb classification. The theoretical framework is applied in three areas: (1) the syntax of resultatives in English and Chinese, which exhibits how a theory of the syntax of events can address the thematic relationship between core arguments and predicates; (2) variation of resultatives at cross-linguistic and diachronic levels, which shows how the universal functional structure of events can be compatible with, and even contribute to, the theory of parametric variation in the generative tradition; and (3) applicative constructions, which extend the analysis of core arguments to non-core arguments, and shed light on the typology of verb/satellite-framed languages (Talmy 1991, 2000) and the analyticity parameter proposed in Huang (2015).

The main clinical application of functional neuroimaging is mapping cortical regions containing part of the circuitry necessary for somatosensory, motor, and language functions and assessing hemispheric dominance for both language and encoding operations of memory prior to several types of brain surgery. Presently, it is used in conjunction with the classical invasive methods of brain mapping. This chapter presents the case for replacing invasive methods with noninvasive ones given the limitations of the invasive methods that render them unjustifiable as “gold standards.” Evidence is presented that the efficacy of the two types of methods in reducing morbidity, facilitating surgical planning, and enhancing surgical outcome is comparable. Additional advantages of noninvasive presurgical brain mapping are also discussed. The chapter concludes that there are no compelling reasons for invasive mapping in most patients whenever noninvasive methods are available.

A large part of the contemporary literature involves functional neuroimaging. Yet few readers are sufficiently familiar with the various imaging methods, their capabilities and limitations, to appraise it correctly. To fulfill that need is the purpose of this Handbook, which consists of an accessible description of the methods and their clinical and research applications. The Handbook begins with an overview of basic concepts of functional brain imaging, magnetoencephalography and the use of magnetic source imaging (MSI), positron emission tomography (PET), diffusion tensor imaging (DTI), and transcranial magnetic stimulation (TMS). The authors then discuss the various research applications of imaging, such as white matter connectivity; the function of the default mode network; the possibility and the utility of imaging of consciousness; the search for mnemonic traces of concepts the mechanisms of the encoding, consolidation, and retrieval of memories; executive functions and their neuroanatomical mechanisms; voluntary actions, human will and decision-making; motor cognition; language and the mechanisms of affective states and pain. The final chapter discusses the uses of functional neuroimaging in the presurgical mapping of the brain.

This chapter shows that multiple sensory information sources can generally be integrated in a similar fashion. However, seeing that different modalities are grounded in different frames of reference, integrations will focus on space or on identities. Body-relative spaces integrate information about the body and the surrounding space in body-relative frames of reference, integrating the available information across modalities in an approximately optimal manner. Simple topological neural population encodings are well-suited to generate estimates about stimulus locations and to map several frames of reference onto each other. Self-organizing neural networks are introduced as the basic computation mechanism that enables the learning of such mappings. Multisensory object recognition, on the other hand, is realized most effectively in an object-specific frame of reference – essentially abstracting away from body-relative frames of reference. Cognitive maps, that is, maps of the environment are learned by connecting locations over space and time. The hippocampus strongly supports the learning of cognitive maps, as it supports the generation of new episodic memories, suggesting a strong relation between these two computational tasks. In conclusion, multisensory integration yields internal predictive structures about spaces and object identities, which are well-suited to plan, decide on, and control environmental interactions.

AbstractThe reference indexing problem for $$k$$-mers is to pre-process a collection of reference genomic sequences $$\mathcal {R}$$ so that the position of all occurrences of any queried $$k$$-mer can be rapidly identified. An efficient and scalable solution to this problem is fundamental for many tasks in bioinformatics.In this work, we introduce the spectrum preserving tiling (SPT), a general representation of $$\mathcal {R}$$ that specifies how a set of tiles repeatedly occur to spell out the constituent reference sequences in $$\mathcal {R}$$. By encoding the order and positions where tiles occur, SPTs enable the implementation and analysis of a general class of modular indexes. An index over an SPT decomposes the reference indexing problem for $$k$$-mers into: (1) a $$k$$-mer-to-tile mapping; and (2) a tile-to-occurrence mapping. Recently introduced work to construct and compactly index $$k$$-mer sets can be used to efficiently implement the $$k$$-mer-to-tile mapping. However, implementing the tile-to-occurrence mapping remains prohibitively costly in terms of space. As reference collections become large, the space requirements of the tile-to-occurrence mapping dominates that of the $$k$$-mer-to-tile mapping since the former depends on the amount of total sequence while the latter depends on the number of unique $$k$$-mers in $$\mathcal {R}$$.To address this, we introduce a class of sampling schemes for SPTs that trade off speed to reduce the size of the tile-to-reference mapping. We implement a practical index with these sampling schemes in the tool . When indexing over 30,000 bacterial genomes, reduces the size of the tile-to-occurrence mapping from 86.3 GB to 34.6 GB while incurring only a 3.6$$\times $$ slowdown when querying $$k$$-mers from a sequenced readset.Availability: is implemented in Rust and available at https://github.com/COMBINE-lab/pufferfish2.

Abstract In this work, we study the Wigner phase-space representation of qubit states encoded in continuous variables (CV) by using the Gottesman–Kitaev–Preskill (GKP) mapping. We explore a possible connection between resources for universal quantum computation in discrete-variable (DV) systems, i.e. non-stabilizer states, and negativity of the Wigner function in CV architectures, which is a necessary requirement for quantum advantage. In particular, we show that the lowest Wigner logarithmic negativity corresponds to encoded stabilizer states, while the maximum negativity is associated with the most non-stabilizer states, H-type and T-type quantum states.

This chapter defines the coastal web atlases interoperability problem, introduces interoperability standards, and describes the development of a semantic mediator prototype to provide a common access point to coastal data, maps and information from distributed coastal web atlases. The prototype showcases how ontologies and ontology mappings can be used to integrate different heterogeneous and autonomous atlases (or information systems), using international standards such as ISO-19139 for metadata encoding and the Open Geospatial Consortium’s Catalogue Service for the Web specification. Lessons learned from this prototype will help build regional atlases and improve decision support systems as part of a new International Coastal Atlas Network (ICAN).

Auditory-display research has had a largely unsolved challenge of balancing functional and aesthetic considerations. While functional designs tend to reduce musical expressivity for the fidelity of data, aesthetic or musical sound organization arguably has a potential for representing multi-dimensional or hierarchical data structure with enhanced perceptibility. Existing musical designs, however, generally employ nonlinear or interpretive mappings that hinder the assessment of functionality. The authors propose a framework for designing expressive and complex sonification using small timescale musical hierarchies, such as the harmony and timbral structures, while maintaining data integrity by ensuring a close-to-the-original recovery of the encoded data utilizing descriptive analysis by a machine listener.

One of the key purposes of eXplainable AI (XAI) is to develop techniques for understanding predictions made by Machine Learning (ML) models and for assessing how much reliable they are. Several encoding schemas have recently been pointed out, showing how ML classifiers of various types can be mapped to Boolean circuits exhibiting the same input-output behaviours. Thanks to such mappings, XAI queries about classifiers can be delegated to the corresponding circuits. In this paper, we define new explanation and/or verification queries about classifiers. We show how they can be addressed by combining queries and transformations about the associated Boolean circuits. Taking advantage of previous results from the knowledge compilation map, this allows us to identify a number of XAI queries that are tractable provided that the circuit has been first turned into a compiled representation.

Multilayer perceptrons (MLPs) have been successfully used to represent 3D shapes implicitly and compactly, by mapping 3D coordinates to the corresponding signed distance values or occupancy values. In this paper, we propose a novel positional encoding scheme, called Spline Positional Encoding, to map the input coordinates to a high dimensional space before passing them to MLPs, which help recover 3D signed distance fields with fine-scale geometric details from unorganized 3D point clouds. We verified the superiority of our approach over other positional encoding schemes on tasks of 3D shape reconstruction and 3D shape space learning from input point clouds. The efficacy of our approach extended to image reconstruction is also demonstrated and evaluated.

We present results from a Lidar-based high definition 3D mapping system designed and built through optimization of a large software-controllable parameter space combining high throughput multi-channel optics with noise resistant digital encoding and processing.

This paper presents a new and practical method for mapping and annotating indoor environments for mobile robot use. The method makes use of 2D occupancy grid maps for metric representation, and topology maps to indicate the connectivity of the ‘places-of-interests’ in the environment. Novel use of 2D visual tags allows encoding information physically at places-of-interest. Moreover, using physical characteristics of the visual tags (i.e. paper size) is exploited to recover relative poses of the tags in the environment using a simple camera. This method extends tag encoding to simultaneous localization and mapping in topology space, and fuses camera and robot pose estimations to build an automatically annotated global topo-metric map. It is developed as a framework for a hospital service robot and tested in a real hospital. Experiments show that the method is capable of producing globally consistent, automatically annotated hybrid metric-topological maps that is needed by mobile service robots.

Oroginal Objectives: (i) identify DNA markers linked to the avirulence (Avr) locus and locate the Avr locus through genetic mapping with an inter-race Orobanche cumana population; (ii) develop high-throughput fingerprint DNA markers for genotypingO. cumana races; (iii) identify nucleotide binding domain leucine rich repeat (NB-LRR) genes encoding R proteins conferring resistance to O. cumana in sunflower; (iv) increase the resolution of the chromosomal segment harboring Or₅ and related R genes through genetic and physical mapping in previously and newly developed mapping populations of sunflower; and (v) develop high-throughput DNA markers for rapidly and efficiently identifying and transferring sunflower R genes through marker-assisted selection. Revisions made during the course of project: Following changes in O. cumana race distribution in Israel, the newly arrived virulent race H was chosen for further analysis. HA412-HO, which was primarily chosen as a susceptible sunflower cultivar, was more resistant to the new parasite populations than var. Shemesh, thus we shifted sunflower research into analyzing the resistance of HA412-HO. We exceeded the deliverables for Objectives #3-5 by securing funding for complete physical and high-density genetic mapping of the sunflower genome, in addition to producing a complete draft sequence of the sunflower genome. We discovered limited diversity between the parents of the O. cumana population developed for the mapping study. Hence, the developed DNA marker resources were insufficient to support genetic map construction. This objective was beyond the scale and scope of the funding. This objective is challenging enough to be the entire focus of follow up studies. Background to the topic: O. cumana, an obligate parasitic weed, is one of the most economically important and damaging diseases of sunflower, causes significant yield losses in susceptible genotypes, and threatens production in Israel and many other countries. Breeding for resistance has been crucial for protecting sunflower from O. cumana, and problematic because new races of the pathogen continually emerge, necessitating discovery and deployment of new R genes. The process is challenging because of the uncertainty in identifying races in a genetically diverse parasite. Major conclusions, solutions, achievements: We developed a small collection of SSR markers for genetic mapping in O. cumana and completed a diversity study to lay the ground for objective #1. Because DNA sequencing and SNPgenotyping technology dramatically advanced during the course of the study, we recommend shifting future work to SNP discovery and mapping using array-based approaches, instead of SSR markers. We completed a pilot study using a 96-SNP array, but it was not large enough to support genetic mapping in O.cumana. The development of further SNPs was beyond the scope of the grant. However, the collection of SSR markers was ideal for genetic diversity analysis, which indicated that O. cumanapopulations in Israel considerably differ frompopulations in other Mediterranean countries. We supplied physical and genetic mapping resources for identifying R-genes in sunflower responsible for resistance to O. cumana. Several thousand mapped SNP markers and a complete draft of the sunflower genome sequence are powerful tools for identifying additional candidate genes and understanding the genomic architecture of O. cumana-resistanceanddisease-resistance genes. Implications: The OrobancheSSR markers have utility in sunflower breeding and genetics programs, as well as a tool for understanding the heterogeneity of races in the field and for geographically mapping of pathotypes.The segregating populations of both Orobanche and sunflower hybrids are now available for QTL analyses.