Large-scale Representations Research Articles

Generation of pore-space images using improved pyramid Wasserstein generative adversarial networks

High-resolution three-dimensional X-ray microscopy can be used to image the pore space of materials. Machine learning algorithms can generate a statistical ensemble of representative images of arbitrary sizes for rock characterization, modeling, and analysis. However, current methods struggle to capture features at different spatial scales observed in many complex rocks which have a wide range of pore size. We use the Improved Pyramid Wasserstein Generative Adversarial Network (IPWGAN) to automatically reproduce multi-scale features in segmented three-dimensional images of porous materials, enabling the reliable generation of large-scale representations of complex porous media. A Laplacian pyramid generator is introduced, which creates pore-space features across a hierarchy of spatial scales. Feature statistics mixing regularization enhances the discriminator’s ability to distinguish between real and generated images by mixing their feature statistics, thereby indirectly enhancing the generator’s ability to capture and reproduce multi-scale pore-space features, leading to increased diversity and realism in the generated images. The method has been tested on five sandstone and carbonate samples. The generated images, which can be of any size – including cm-scale ten-billion-cell images – demonstrate the power of the approach. These images have two-point correlation functions, porosity, permeability, Euler characteristic, curvature, and specific surface area closer to those of the training datasets than existing machine learning techniques. The generated images accurately capture geometric and flow properties, demonstrating a considerable improvement over previously published studies using generative adversarial networks. For instance, the mean relative error in the calculated absolute permeability between the Berea sandstone images generated by IPWGAN and the corresponding real rock images can be reduced by 79%. The work allows representative models of a wide range of porous media to be generated, offering potential benefits in carbon dioxide sequestration, underground hydrogen storage, and enhanced oil recovery.

Cartographic sources of spatial data on the old cities of Torican and Vrbenac

Historical cartography has an important place among historical sources. Many researchers can have the opportunity to use many cartographic sources during their research. An important source in historical cartography is maps created during the reign of the Ottoman Empire on the territory of Bosnia and Herzegovina. However, the existence of cartographic representations of Bosnia and Herzegovina which are the results of the work of cartographers of the world should also be emphasized. Large-scale representations found in the form of cadastral plans of various scales are of particular importance in research. However, small-scale cartographic representations also offer great help to researchers. The first large-scale representations of the territory of Bosnia and Herzegovina were made during the reign of the Austro-Hungarian Monarchy. This short period of rule on the soil of Bosnia and Herzegovina resulted in the surveying and representing of the entire territory of Bosnia and Herzegovina on cadastral plans at the scale 1:6250, 1:3125, 1:1562.5 and 1:781.25. On the basis of these large-scale representations, many small-scale representations of different topics, purposes and scales were created. Small-scale representations were made in different scales, which also dictated the detail of the representation. The maps, i.e. small-scale graphic representations, were produced at the scales of 1:12500, 1:25000, 1:75000, and 1:150000. With the end of the First World War, a new period of cartography of the territory of Bosnia and Herzegovina was born. During this time, topographical maps were made at the scales of 1:25,000, 1:50,000, and smaller scales. Of course, the authors of the maps monitored the situation on the ground and tried to ensure that all the details that could be shown were shown on them in terms of content and according to the possibility of the display. After the end of the Second World War, a completely new period was started in the production of graphic representations of Bosnia and Herzegovina. A special place is occupied by large-scale representations views - cadastral plans that were prepared at the scales of 1:5000, 1:2500, 1:2000, 1:1000 and 1:500. On the basis of cadastral plans, small-scale graphic representations of Bosnia and Herzegovina - maps were created. The map scales were 1:2500, 1:50000 and smaller. Maps with different purposes and themes were created. Topographic maps have a special significance. The completeness of the presentation is an important determinant of all the previously mentioned presentations. The completeness of the cartographic display is reflected in the display of all significant objects, depending on the scale of the display. The area of Bosnia and Herzegovina has many sights. Most of these sights have been measured and shown on large-scale geodetic bases - cadastral plans as well as small-scale geodetic bases - maps. Graphic representations of Bosnia and Herzegovina were created by many cartographers. Taking this as important data, Bosnia and Herzegovina or its individual parts are shown on maps of different scales related to different authors. This is precisely what results in graphic representations on which different signs, display methods, letters, and languages are represented. Cartographic representations in Bosnia and Herzegovina were created in different time periods. The depictions of Bosnia and Herzegovina go back several centuries. Cartographic representations show details that are interesting to many researchers. At the time of the creation of cartographic representations, it was not even imagined how important the representations would be for research in today's time. Historical cartography through cartographic representations offers a lot of information about many objects on the soil of Bosnia and Herzegovina. The depictions of the Travnik's old towns Toričan and Vrbenac, are especially important for the research. In the paper, the depictions of the aforementioned remnants of Travnik's old towns were investigated. They were shown on many cartographic sources of different purposes and different scales, which were made by different authors in different time periods. The paper analyzes the depiction of old cities in historical cartographic sources from the 17th to the 20th centuries.

Novel biochemical, structural, and systems insights into inflammatory signaling revealed by contextual interaction proteomics

Protein-protein interactions (PPIs) represent the main mode of the proteome organization in the cell. In the last decade, several large-scale representations of PPI networks have captured generic aspects of the functional organization of network components but mostly lack the context of cellular states. However, the generation of context-dependent PPI networks is essential for structural and systems-level modeling of biological processes-a goal that remains an unsolved challenge. Here we describe an experimental/computational strategy to achieve a modeling of PPIs that considers contextual information. This strategy defines the composition, stoichiometry, temporal organization, and cellular requirements for the formation of target assemblies. We used this approach to generate an integrated model of the formation principles and architecture of a large signalosome, the TNF-receptor signaling complex (TNF-RSC). Overall, we show that the integration of systems- and structure-level information provides a generic, largely unexplored link between the modular proteome and cellular function.

Impact of Climate Change on Forests in Cambodia

Cambodia is rich in forest resources, which play critical roles in local rural livelihoods, as well as providing valuable ecological and economic resources for the country’s economic development. Managing forests sustainably and equitably will be essential for maintaining the ecological integrity of the country, maintaining freshwater supplies and protecting biodiversity. Approximately 80% of the Cambodians live in rural areas depend upon the forests to support many people’s lives as a source of food, medicine and building products, and as a source of materials and goods for small business ventures. Forest degradation globally contributes around 17 % to Green House Gases (GHG) emissions, but in Cambodia represents the main factor in the country becoming a net emitter of GHGs. Climate change is one of the most environmental issues facing to the government. The study aimed at i) assessing the impact of climate change on NPP, Vegetation Carbon and Soil Organic Carbon using LPJ model; ii) projecting the spatial representation of Impact of climate change on NPP, Vegetation Carbon stocks, and Soil Organic Carbon. The Lund Potsdam Jena (LPJ) model combines process-based, large-scale representations of terrestrial vegetation dynamics and land-atmosphere carbon and water exchanges in a modular framework. The model climate data requirements are benign as it requires only Temperature, Rainfall and Cloudiness as climatology inputs. Model validation is used for Net Primary Productivity (NPP), Vegetation Carbon (VegC), and Soil Organic Carbon (SoC). Obtaining observation of NPP, VegC, and SoC data for the region from the published literature or from the international databases and compare these with the LPJ projections (Spatially or non- spatially). As results, LPJ Simulated distribution on NPP in Cambodia using different scenarios including Baseline, RCP 8.5, and RCP 8.5 with control CO2 generated based on NPP, VegC, and SoC. Also, LPJ simulated Soil carbon change (%) projections for Cambodia under the RCP 8.5 under the two scenarios of CO2 fertilization and no-CO2 fertilization.

Scale Sequence Joint Deep Learning (SS-JDL) for land use and land cover classification

Choosing appropriate scales for remotely sensed image classification is extremely important yet still an open question in relation to deep convolutional neural networks (CNN), due to the impact of spatial scale (i.e., input patch size) on the recognition of ground objects. Currently, the optimal scale selection processes are extremely cumbersome and time-consuming requiring repetitive experiments involving trial-and-error procedures, which significantly reduce the practical utility of the corresponding classification methods. This issue is crucial when trying to classify large-scale land use (LU) and land cover (LC) jointly (Zhang et al., 2019). In this paper, a simple and parsimonious Scale Sequence Joint Deep Learning (SS-JDL) method is proposed for joint LU and LC classification, in which a sequence of scales is embedded in the iterative process of fitting the joint distribution implicit in the joint deep learning (JDL) method, thus, replacing the previous paradigm of scale selection. The sequence of scales, derived autonomously and used to define the CNN input patch sizes, provides consecutive information transmission from small-scale features to large-scale representations, and from simple LC states to complex LU characterisations. The effectiveness of the novel SS-JDL method was tested on aerial digital photography of three complex and heterogeneous landscapes, two in Southern England (Bournemouth and Southampton) and one in North West England (Manchester). Benchmark comparisons were provided in the form of a range of LU and LC methods, including the state-of-the-art joint deep learning (JDL) method. The experimental results demonstrated that the SS-JDL consistently outperformed all of the state-of-the-art baselines in terms of both LU and LC classification accuracies, as well as computational efficiency. The proposed SS-JDL method, therefore, represents a fast and effective implementation of the state-of-the-art JDL method. By creating a single, unifying joint distribution framework for classifying higher order feature representations, including LU, the SS-JDL method has the potential to transform the classification paradigm in remote sensing, and in machine learning more generally.

Dual Portraits of the Deceased in Yangqiaopan M1, Jingbian, Shaanxi

Murals decorating an Eastern Han tomb excavated in Jingbian, Shaanxi include two large-scale representations of the deceased who appears in a processional scene on the left front wall of the tomb wearing typical Han elite dress, and then again on the rear wall in a regional version of a spirit seat (lingwei) composition, clean-shaven and donning a hairstyle uncommon in Han mortuary art. This paper considers these depictions in terms of Han pictorial conventions and argues that they are dual portraits of the deceased in which different attributes of his political, social, and cultural identity are stressed.

Audiovisual Cartography: Established and New Multimedia Approaches to Represent Soundscapes

Since the mid-1990s, sound has been discussed and used in multimedia cartography. There are four main variants of auditory map elements that have been established in the theory and practice of audiovisual cartography, i.e. abstract sounds/abstract sound sequences, speech, music and, especially, audiorealistic sequences representing so-called “soundscapes”. In cartography, soundscapes are often addressed in large-scale representations. The term originates in multidisciplinary landscape research. Empirical findings of landscape research, and especially those of social constructivist landscape research, have shown the relevance of non-visual stimuli for people’s individual impressions and meanings of the experienced landscape. Amongst the non-visual landscape dimensions, the auditory dimension is the most prominent one. As 3D cartography offers new methods and techniques of designing and experiencing highly realistic, incl. photo- and audiorealistic landscape representation, this discipline becomes more and more interesting for simulating and presenting multisensory landscapes and for presenting the results of empirical findings in landscape research. After an introduction to traditional means of audiovisual cartography and the relevance of auditory stimuli for social constructivist approaches of landscape research, a modern software-based method is presented which highlights the opportunity to imbed 3D sound data representing a location’s soundscape into audiovisual 3D environments in Virtual Reality (VR). It is technically based on the cross-platform game engine Unity3D.

High accuracy mapping with cartographic assessment for a fixed-wing remotely piloted aircraft system

The lack of updated maps on large scale representations has encouraged the use of remotely piloted aircraft systems (RPAS) to generate maps for a wide range of professionals. However, some questions arise: do the orthomosaics generated by these systems have the cartographic precision required to use them? Which problems can be identified in stitching orthophotos to generate orthomosaics? To answer these questions, an aerophotogrammetric survey was conducted in an environmental conservation unit in the city of Goiânia. The flight plan was set up using the E-motion software, provided by Sensefly—a Swiss manufacturer of the RPAS Swinglet CAM used in this work. The camera installed in the RPAS was the Canon IXUS 220 HS, with the number of pixels in the sensor array of 12.1 megapixel, complementary metal oxide semiconductor 1 ∶ 2.3 ? (4000 × 3000 pixel), horizontal and vertical pixel sizes of 1.54 μm. Using the orthophotos, four orthomosaics were generated in the Pix4D mapper software. The first orthomosaic was generated without using the control points. The other three mosaics were generated using 4, 8, and 16 premarked ground control points. To check the precision and accuracy of the orthomosaics, 46 premarked targets were uniformly distributed in the block. The three-dimensional (3-D) coordinates of the premarked targets were read on the orthomosaic and compared with the coordinates obtained by the geodetic survey real-time kinematic positioning method using the global navigation satellite system receiver signals. The cartographic accuracy standard was evaluated by discrepancies between these coordinates. The bias was analyzed by the Student’s t test and the accuracy by the chi-square probability considering the orthomosaic on a scale of 1 ∶ 250, in which 90% of the points tested must have a planimetric error of <0.13 m with a standard deviation of 0.08 m and altimetric errors of <0.30 m with a standard deviation of 0.20 m. It was observed that some buildings in the orthomosaics were not properly orthorectified. The orthomosaics generated with 8 or more points reached the scale of 1 ∶ 250, whereas without control points the scale was 10-fold smaller (1 ∶ 3000).

IDSS: A Novel Representation for Woven Fabrics

The appearance of woven fabrics is intrinsically determined by the geometric details of their meso/micro scale structure. In this paper, we propose a multiscale representation and tessellation approach for woven fabrics. We extend the Displaced Subdivision Surface (DSS) to a representation named Interlaced/Intertwisted Displacement Subdivision Surface (IDSS). IDSS maps the geometric detail, scale by scale, onto a ternary interpolatory subdivision surface that is approximated by Bezier patches. This approach is designed for woven fabric rendering on DX11 GPUs. We introduce the Woven Patch, a structure based on DirectX’s new primitive, patch, to describe an area of a woven fabric so that it can be easily implemented in the graphics pipeline using a hull shader, a tessellator and a domain shader. We can render a woven piece of fabric at 25 frames per second on a low-performance NVIDIA 8400 MG mobile GPU. This allows for large-scale representations of woven fabrics that maintain the geometric variances of real yarn and fiber.

A RANGE BASED METHOD FOR COMPLEX FACADE MODELING

Abstract. 3d modelling of Architectural Heritage does not follow a very well-defined way, but it goes through different algorithms and digital form according to the shape complexity of the object, to the main goal of the representation and to the starting data. Even if the process starts from the same data, such as a pointcloud acquired by laser scanner, there are different possibilities to realize a digital model. In particular we can choose between two different attitudes: the mesh and the solid model. In the first case the complexity of architecture is represented by a dense net of triangular surfaces which approximates the real surface of the object. In the other -opposite- case the 3d digital model can be realized by the use of simple geometrical shapes, by the use of sweeping algorithm and the Boolean operations. Obviously these two models are not the same and each one is characterized by some peculiarities concerning the way of modelling (the choice of a particular triangulation algorithm or the quasi-automatic modelling by known shapes) and the final results (a more detailed and complex mesh versus an approximate and more simple solid model). Usually the expected final representation and the possibility of publishing lead to one way or the other. In this paper we want to suggest a semiautomatic process to build 3d digital models of the facades of complex architecture to be used for example in city models or in other large scale representations. This way of modelling guarantees also to obtain small files to be published on the web or to be transmitted. The modelling procedure starts from laser scanner data which can be processed in the well known way. Usually more than one scan is necessary to describe a complex architecture and to avoid some shadows on the facades. These have to be registered in a single reference system by the use of targets which are surveyed by topography and then to be filtered in order to obtain a well controlled and homogeneous point cloud of the complex architecture. From the point cloud we can extract a false colour map depending on the distance of each point from the average plane. In this way we can represent each point of the facades by a height map in grayscale. In this operation it is important to define the scale of the final result in order to set the correct pixel size in the map. The following step is concerning the use of a modifier which is well-known in computer graphics. In fact the modifier Displacement allows to simulate on a planar surface the original roughness of the object according to a grayscale map. The value of gray is read by the modifier as the distance from the reference plane and it represents the displacement of the corresponding element of the virtual plane. Similar to the bump map, the displacement modifier does not only simulate the effect, but it really deforms the planar surface. In this way the 3d model can be use not only in a static representation, but also in dynamic animation or interactive application. The setting of the plane to be deformed is the most important step in this process. In 3d Max the planar surface has to be characterized by the real dimension of the façade and also by a correct number of quadrangular faces which are the smallest part of the whole surface. In this way we can consider the modified surface as a 3d raster representation where each quadrangular face (corresponding to traditional pixel) is displaced according the value of gray (= distance from the plane). This method can be applied in different context, above all when the object to be represented can be considered as a 2,5 dimension such as facades of architecture in city model or large scale representation. But also it can be used to represent particular effect such as deformation of walls in a complete 3d way.

Computational methods to extract meaning from text and advance theories of human cognition.

Over the past two decades, researchers have made great advances in the area of computational methods for extracting meaning from text. This research has to a large extent been spurred by the development of latent semantic analysis (LSA), a method for extracting and representing the meaning of words using statistical computations applied to large corpora of text. Since the advent of LSA, researchers have developed and tested alternative statistical methods designed to detect and analyze meaning in text corpora. This research exemplifies how statistical models of semantics play an important role in our understanding of cognition and contribute to the field of cognitive science. Importantly, these models afford large-scale representations of human knowledge and allow researchers to explore various questions regarding knowledge, discourse processing, text comprehension, and language. This topic includes the latest progress by the leading researchers in the endeavor to go beyond LSA.

Collado-Vides J, Hofestädt R, (editors): Gene Regulation and Metabolism: Postgenomic Computational Approaches

The inference, analysis and integration of networks of genes and products are fundamental goals of post-genomic research. Over the past few years several data- and knowledge-driven computational approaches have been proposed, which have provided relevant insights into the informational complexity and function of some of such networks in different organisms. Gene Regulation and Metabolism probably represents one of the first books attempting to discuss essential computational concepts, methods and applications in this area. Although its editors did not aim to offer a comprehensive review of advances available at the time of its publication, this book may still be seen as a useful introduction for computer scientists to key problems, solutions and questions relevant to the study of regulatory and metabolic networks. Collado-Vides and Hofestadt edited a collection of contributions by internationally-recognised authors, which were motivated by a summer school following a series of Dagstuhl seminars in Germany. The book is divided into three main parts addressing information and knowledge representation problems, gene regulation and post-genomic approaches. Each chapter also provides lists of suggested readings and relevant websites, which include some of the databases and tools discussed in the book. The book also offers a glossary of terms and acronyms. Overall, the chapters are well-written and organised. Readers would have benefited from an introductory chapter to overview fundamental biological concepts and problems. However, this is partially compensated by some chapters, which adequately present basic concepts and motivation necessary to approach specific applications such as DNA regulatory motif discovery. In the first chapter, Ahouse discusses the concept of homology and its inference within the context of regulatory networks, which represents an important source for predicting potential interactions. The second chapter, by Apweiler et al., describes several techniques for automated protein sequence characterisation and its applications in whole proteome analysis. Chapter 3, by Freier et al., overviews approaches to database integration, which are relevant to the prediction and analysis of metabolic networks. They also put emphasis on the application of a rule-based simulation tool (MetabSim). In Chapter 4, Stormo introduces quantitative indicators required to support the prediction of regulatory binding sites from sets of co-regulated genes. This is followed by Collado-Vides et al.'s review of methods for identifying regulatory elements, e.g. promoters and regulatory binding sites. Chapter 6, by Manson McGuire and Church, focuses on the discovery of DNA regulatory motifs. It introduces different techniques for regulon prediction and an algorithm for detecting motifs (AlignACE). In Chapter 7, Kolchanov et al. discusses the representation and modelling of gene networks using the GeneNet database. This system encodes different types of networks, e.g. networks relating to cell growth and differentiation. This chapter concludes with an introduction to the mathematical simulation of gene network dynamics. Chapter 8, by Huang, emphasises Boolean networks approaches to modelling cellular regulatory systems. In Chapter 9, Marcotte discusses important questions and challenges for the large-scale prediction of protein function and networks. Chapter 10, by Schmidt and Dandekar, concentrates on metabolic pathways. It introduces fundamental concepts and problems, such as enzymatic reactions and pathway alignment. The final chapter, by Tomita, introduces the E-CELL project, which has been applied to simulate several cellular processes, e.g. signal transduction and gene regulation. The ultimate goal of this project is to model the cell based on large-scale representations of thousands of functionally-diverse processes. Even when it does not provide a comprehensive, up-to-date review of techniques and tools for supporting the inference and analysis of gene regulation and metabolism networks, this book represents a useful reference to reflect on recent advances and challenges ahead. Moreover, some of its chapters highlight crucial open questions and computational opportunities in the systems biology era.

Wives and Patrons: Uygur Political and Artistic Influence in Tenth-Century Dunhuang

This article studies the intercultural links between the Uygurs and Dunhuang in the tenth-eleventh centuries. Some of the biggest caves at Dunhuang show large-scale representations of Ganzhou Uygur brides as donors. It is argued that the marriage of a Chinese ruler of Dunhuang with the daughter of the Ganzhou Uygur kaghan acted as a catalyst for the formation of a new Sino-Uygur ruling class. A sketch and a painting from Dunhuang are examined in detail. Emphasis is on the appearance of new colours and decorative technologies such as applied gold leaf, iconography including the clothing of the figures and style, including facial features and mannerisms. It is concluded that Ganzhou Uygur brides as patrons played an important role in the formation of tenth-century Dunhuang art, and Uygur influence continued to grow in the eleventh century.

Response and risk in rural ecosystems: from models and plots to defined universes

This essay was prepared as an invited closure of a thematic session on “Scaling and Extrapolation” at the CGTE Conference on “Food and Forestry: Global Change and Global Challenges”. It is addressed to those who prognosticate at the global or other large levels about food and forestry systems, and who naturally confront several problems, and inevitably also some risk. The problems range from conceptual and practical to measuremental and statistical. For other than simplistic models, many constraints apply to procedures used to aggregate from small-scale to large-scale representations of agricultural systems, whether they be biophysical or socioeconomic, especially when uncertainty is explicitly recognized. Model-linking procedures work well in some cases but by no means all. The risks encountered in such work are similarly wide-ranging, depending on the intrinsic uncertainties, context, analyst and audience. These spectrums of problems and risks, along with some suggestions for what practically can be done about them (largely involving ad hoc simulation modeling), are examined from a response-analysis perspective across a range of biophysical and social phenomena pertinent to terrestrial ecosystems. Attention is given to policy applications of scaled-up models.

A high signal-to-noise ratio composite quasar spectrum

A very high signal-to-noise ratio (S/N of about 400) composite spectrum of the rest-frame ultraviolet and optical region of high luminosity quasars is presented. The spectrum is derived from 718 individual spectra obtained as part of the Large Bright Quasar Survey. The moderate resolution, 4A or less, and high signal-to-noise ratio allow numerous weak emission features to be identified. Of particular note is the large equivalent-width of the Fe II emission in the rest-frame ultraviolet and the blue continuum slope of the composite. The primary aim of this paper is to provide a reference spectrum for use in line identifications, and a series of large-scale representations of the composite spectrum are shown. A measure of the standard deviation of the individual quasar spectra from the composite spectrum is also presented. 12 refs.