scholarly journals Space-Time Covariance Structures and Models

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Wanfang Chen ◽  
Marc G. Genton ◽  
Ying Sun
Keyword(s):  
Climate Models ◽  
Space Time ◽  
Covariance Structures ◽  
Annual Review ◽  
Publication Date ◽  
Monitoring Networks ◽  
Data Set ◽  
Temporal Modeling ◽  
Covariance Models ◽  
Spatio Temporal

In recent years, interest has grown in modeling spatio-temporal data generated from monitoring networks, satellite imaging, and climate models. Under Gaussianity, the covariance function is core to spatio-temporal modeling, inference, and prediction. In this article, we review the various space-time covariance structures in which simplified assumptions, such as separability and full symmetry, are made to facilitate computation, and associated tests intended to validate these structures. We also review recent developments on constructing space-time covariance models, which can be separable or nonseparable, fully symmetric or asymmetric, stationary or nonstationary, univariate or multivariate, and in Euclidean spaces or on the sphere. We visualize some of the structures and models with visuanimations. Finally, we discuss inference for fitting space-time covariance models and describe a case study based on a new wind-speed data set. Expected final online publication date for the Annual Review of Statistics, Volume 8 is March 8, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Simulation and Analysis Methods for Stochastic Compartmental Epidemic Models

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Tapiwa Ganyani ◽  
Christel Faes ◽  
Niel Hens
Keyword(s):  
Stochastic Models ◽  
Online Publication ◽  
Real Life ◽  
Likelihood Estimation ◽  
Annual Review ◽  
Publication Date ◽  
Data Set ◽  
Incidence Data ◽  
Mixed Populations ◽  
Application Volume

This article considers simulation and analysis of incidence data using stochastic compartmental models in well-mixed populations. Several simulation approaches are described and compared. Thereafter, we provide an overview of likelihood estimation for stochastic models. We apply one such method to a real-life outbreak data set and compare models assuming different kinds of stochasticity. We also give references for other publications where detailed information on this topic can be found. Expected final online publication date for the Annual Review of Statistics and Its Application, Volume 8 is March 8, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Re-Arranging Space, Time and Scales in GIS: Alternative Models for Multi-Scale Spatio-Temporal Modeling and Analyses

2019 ◽  
Vol 8 (2) ◽  
pp. 72 ◽  
Author(s):  
Yi Qiang ◽  
Nico Van de Weghe
Keyword(s):  
Spatial Data ◽  
Spatial Scales ◽  
Space Time ◽  
Unified Framework ◽  
Temporal Modeling ◽  
Multi Scale ◽  
Space And Time ◽  
Pyramid Model ◽  
Temporal And Spatial ◽  
Spatio Temporal

The representations of space and time are fundamental issues in GIScience. In prevalent GIS and analytical systems, time is modeled as a linear stream of real numbers and space is represented as flat layers with timestamps. Despite their dominance in GIS and information visualization, these representations are inefficient for visualizing data with complex temporal and spatial extents and the variation of data at multiple temporal and spatial scales. This article presents alternative representations that incorporate the scale dimension into time and space. The article first reviews a series of work about the triangular model (TM), which is a multi-scale temporal model. Then, it introduces the pyramid model (PM), which is the extension of the TM for spatial data, and demonstrates the utility of the PM in visualizing multi-scale spatial patterns of land cover data. Finally, it discusses the potential of integrating the TM and the PM into a unified framework for multi-scale spatio-temporal modeling. This article systematically documents the models with alternative arrangements of space and time and their applications in analyzing different types of data. Additionally, this article aims to inspire the re-thinking of organizations of space, time, and scales in the future development of GIS and analytical tools to handle the increasing quantity and complexity of spatio-temporal data.

Activities, ringmaps and geovisualization of large human movement fields

2008 ◽  
Vol 7 (3-4) ◽  
pp. 198-209 ◽  
Author(s):  
Jinfeng Zhao ◽  
Pip Forer ◽  
Andrew S. Harvey
Keyword(s):  
New Technologies ◽  
Low Cost ◽  
Human Movement ◽  
Space Time ◽  
Data Set ◽  
Fundamental Building Block ◽  
Time Patterns ◽  
Cyclic Time ◽  
Spatio Temporal ◽  
The Individual

The timeline or track of any individual, mobile, sentient organism, whether animal or human being, represents a fundamental building block in understanding the interactions of such entities with their environment and with each other. New technologies have emerged to capture the (x, y, t) dimension of such timelines in large volumes and at relatively low cost, with various degrees of precision and with different sampling properties. This has proved a catalyst to research on data mining and visualizing such movement fields. However, a good proportion of this research can only infer, implicitly or explicitly, the activity of the individual at any point in time. This paper in contrast focuses on a data set in which activity is known. It uses this to explore ways to visualize large movement fields of individuals, using activity as the prime referential dimension for investigating space—time patterns. Visually central to the paper is the ringmap, a representation of cyclic time and activity, that is itself quasi spatial and is directly linked to a variety of visualizations of other dimensions and representations of spatio-temporal activity. Conceptually central is the ability to explore different levels of generalization in each of the space, time and activity dimensions, and to do this in any combination of the (s, t, a) phenomena. The fundamental tenet for this approach is that activity drives movement, and logically it is the key to comprehending pattern. The paper discusses these issues, illustrates the approach with specific example visualizations and invites critiques of the progress to date.

scholarly journals Implications of New Physics Models for the Couplings of the Higgs Boson

2021 ◽  
Vol 71 (1) ◽  
Author(s):  
Matthew McCullough
Keyword(s):  
Higgs Boson ◽  
Online Publication ◽  
New Physics ◽  
Space Time ◽  
Science Volume ◽  
Annual Review ◽  
Publication Date ◽  
Broad Audience ◽  
New Space

It has been almost a decade since the first hints of the Higgs boson discovery began to emerge from CERN, making a review of our updated expectations for the Higgs boson properties, in light of New Physics models, timely. In this review I attempt to draw connections between modified Higgs boson couplings and the big questions that broad classes of New Physics models aim to answer. Questions considered include whether the Higgs boson is composite and whether a new space-time supersymmetry exists. The goal is to present these topics, framed in reference to the Higgs boson, in a conceptually driven manner and, to make them accessible to a relatively broad audience, without a great deal of technicality. Expected final online publication date for the Annual Review of Nuclear and Particle Science, Volume 71 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Neurocomputational Models of Language Processing

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
John T. Hale ◽  
Luca Campanelli ◽  
Jixing Li ◽  
Shohini Bhattasali ◽  
Christophe Pallier ◽  
...  
Keyword(s):  
Language Processing ◽  
Computational Models ◽  
Annual Review ◽  
Publication Date ◽  
Data Sets ◽  
Linguistic Features ◽  
Neural Signals ◽  
Data Set ◽  
Interpretable Models ◽  
Compare And Contrast

Efforts to understand the brain bases of language face the Mapping Problem: At what level do linguistic computations and representations connect to human neurobiology? We review one approach to this problem that relies on rigorously defined computational models to specify the links between linguistic features and neural signals. Such tools can be used to estimate linguistic predictions, model linguistic features, and specify a sequence of processing steps that may be quantitatively fit to neural signals collected while participants use language. Progress has been helped by advances in machine learning, attention to linguistically interpretable models, and openly shared data sets that allow researchers to compare and contrast a variety of models. We describe one such data set in detail in the Supplementary Appendix. Expected final online publication date for the Annual Review of Linguistics, Volume 8 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Statistical Evaluation of Medical Tests

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Vanda Inácio ◽  
María Xosé Rodríguez-Álvarez ◽  
Pilar Gayoso-Diz
Keyword(s):  
Statistical Evaluation ◽  
Roc Curves ◽  
Annual Review ◽  
Publication Date ◽  
Special Focus ◽  
Model Assessment ◽  
Data Set ◽  
Predictive Values ◽  
Prognostic Accuracy ◽  
Medical Tests

In this review, we present an overview of the main aspects related to the statistical evaluation of medical tests for diagnosis and prognosis. Measures of diagnostic performance for binary tests, such as sensitivity, specificity, and predictive values, are introduced, and extensions to the case of continuous-outcome tests are detailed. Special focus is placed on the receiver operating characteristic (ROC) curve and its estimation, with emphasis on the topic of covariate adjustment. The extension to the case of time-dependent ROC curves for evaluating prognostic accuracy is also touched upon. We apply several of the approaches described to a data set derived from a study aimed to evaluate the ability of homeostasis model assessment of insulin resistance (HOMA-IR) levels to identify individuals at high cardio-metabolic risk and how such discriminatory ability might be influenced by age and gender. We also outline software available for the implementation of the methods. Expected final online publication date for the Annual Review of Statistics, Volume 8 is March 8, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A Framework for the Study of Persuasion

2021 ◽  
Vol 25 (1) ◽  
Author(s):  
James N. Druckman
Keyword(s):  
Political Science ◽  
Online Publication ◽  
Space Time ◽  
Science Volume ◽  
Annual Review ◽  
Publication Date ◽  
Time Process ◽  
Vital Part ◽  
Enormous Number ◽  
Normative Implications

Persuasion is a vital part of politics—who wins elections and policy disputes often depends on which side can persuade more people. Given this centrality, the study of persuasion has a long history with an enormous number of theories and empirical inquiries. However, the literature is fragmented, with few generalizable findings. I unify previously disparate dimensions of this topic by presenting a framework focusing on actors (speakers and receivers), treatments (topics, content, media), outcomes (attitudes, behaviors, emotions, identities), and settings (competition, space, time, process, culture). This Generalizing Persuasion (GP) Framework organizes distinct findings and offers researchers a structure in which to situate their work. I conclude with a discussion of the normative implications of persuasion. Expected final online publication date for the Annual Review of Political Science, Volume 25 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Pyramidal Framework: Guidance for the Next Generation of GIS Spatial-Temporal Models

2021 ◽  
Vol 10 (3) ◽  
pp. 188
Author(s):  
Cyril Carré ◽  
Younes Hamdani
Keyword(s):  
Conceptual Models ◽  
Future Generations ◽  
Temporal Data ◽  
Temporal Modeling ◽  
Temporal Models ◽  
Gis Data ◽  
Spatio Temporal ◽  
New Interpretation ◽  
Conventional Literature

Over the last decade, innovative computer technologies and the multiplication of geospatial data acquisition solutions have transformed the geographic information systems (GIS) landscape and opened up new opportunities to close the gap between GIS and the dynamics of geographic phenomena. There is a demand to further develop spatio-temporal conceptual models to comprehensively represent the nature of the evolution of geographic objects. The latter involves a set of considerations like those related to managing changes and object identities, modeling possible causal relations, and integrating multiple interpretations. While conventional literature generally presents these concepts separately and rarely approaches them from a holistic perspective, they are in fact interrelated. Therefore, we believe that the semantics of modeling would be improved by considering these concepts jointly. In this work, we propose to represent these interrelationships in the form of a hierarchical pyramidal framework and to further explore this set of concepts. The objective of this framework is to provide a guideline to orient the design of future generations of GIS data models, enabling them to achieve a better representation of available spatio-temporal data. In addition, this framework aims at providing keys for a new interpretation and classification of spatio-temporal conceptual models. This work can be beneficial for researchers, students, and developers interested in advanced spatio-temporal modeling.

scholarly journals A data acquisition setup for data driven acoustic design

2021 ◽  
pp. 1351010X2098690
Author(s):  
Romana Rust ◽  
Achilleas Xydis ◽  
Kurt Heutschi ◽  
Nathanael Perraudin ◽  
Gonzalo Casas ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Interdisciplinary Approach ◽  
Computational Design ◽  
Surface Structures ◽  
Future Research ◽  
Data Set ◽  
Process Measures ◽  
First Results ◽  
Spatio Temporal ◽  
Automated Data Acquisition

In this paper, we present a novel interdisciplinary approach to study the relationship between diffusive surface structures and their acoustic performance. Using computational design, surface structures are iteratively generated and 3D printed at 1:10 model scale. They originate from different fabrication typologies and are designed to have acoustic diffusion and absorption effects. An automated robotic process measures the impulse responses of these surfaces by positioning a microphone and a speaker at multiple locations. The collected data serves two purposes: first, as an exploratory catalogue of different spatio-temporal-acoustic scenarios and second, as data set for predicting the acoustic response of digitally designed surface geometries using machine learning. In this paper, we present the automated data acquisition setup, the data processing and the computational generation of diffusive surface structures. We describe first results of comparative studies of measured surface panels and conclude with steps of future research.

Endogenous Retroviruses Drive Resistance and Promotion of Exogenous Retroviral Homologs

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Elliott S. Chiu ◽  
Sue VandeWoude
Keyword(s):  
Immune Modulation ◽  
Viral Infections ◽  
Viral Evolution ◽  
Endogenous Retroviruses ◽  
Annual Review ◽  
Publication Date ◽  
Biological Functions ◽  
Self Tolerance ◽  
Vertebrate Hosts ◽  
Insight Into

Endogenous retroviruses (ERVs) serve as markers of ancient viral infections and provide invaluable insight into host and viral evolution. ERVs have been exapted to assist in performing basic biological functions, including placentation, immune modulation, and oncogenesis. A subset of ERVs share high nucleotide similarity to circulating horizontally transmitted exogenous retrovirus (XRV) progenitors. In these cases, ERV–XRV interactions have been documented and include ( a) recombination to result in ERV–XRV chimeras, ( b) ERV induction of immune self-tolerance to XRV antigens, ( c) ERV antigen interference with XRV receptor binding, and ( d) interactions resulting in both enhancement and restriction of XRV infections. Whereas the mechanisms governing recombination and immune self-tolerance have been partially determined, enhancement and restriction of XRV infection are virus specific and only partially understood. This review summarizes interactions between six unique ERV–XRV pairs, highlighting important ERV biological functions and potential evolutionary histories in vertebrate hosts. Expected final online publication date for the Annual Review of Animal Biosciences, Volume 9 is February 16, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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