Spatial Description Research Articles

Cr-Precipitates Growth Kinetics and Microstructure Evolution of Fe-Cr Binary Alloys from Kinetic Monte-Carlo Simulation Combined with Spatial Coarse-Grained Mass Density Field Description

Cr-Precipitates Growth Kinetics and Microstructure Evolution of Fe-Cr Binary Alloys from Kinetic Monte-Carlo Simulation Combined with Spatial Coarse-Grained Mass Density Field Description

Proxy modeling pf reservoir hydrodynamics with graph neural networks

The primary goal of hydrodynamic reservoir modeling is to predict the production wells performance, or more precisely, the dependence of this performance on the choice of the reservoir development plan. The achievement of this goal is hampered by the lack of accurate information about the properties of the reservoir. These properties have to be inferred from indirect data, first of all from the historical indicators of already functioning wells. This information is used to perform the adaptation of the numerical reservoir model or proxy models, which are less informative but have the advantage of speed and flexibility. The article proposes a reservoir proxy modeling method based on the use of a specific artificial neural network (ANN). The novel graph convolutional architecture of the ANN takes in the graph data describing the reservoir. The edges and vertices of the graph contain a spatial description of the reservoir along with the history of the well performance. Such architecture makes it possible to train the neural network for a whole class of situations instead of only one case. In accordance with the principles of the Physics-Informed Neural Networks (PINN), the task of the ANN is to derive a kind of formulation of a physical law guiding the system, rather than just a correlation between time series. The advantages of this approach over most ANN-based proxy models used today are, firstly, speed: adjustment to historical data and forecast output are made in seconds even for hundreds of wells; secondly, a certain degree of physical meaningfulness.

A Binned Triple Collocation for Estimating Regime-Dependent Uncertainties of Precipitation

Triple collocation (TC)-based methods have become popular to estimate the uncertainty of many geophysical variables retrieved from satellite observations. The true advantage of these methods is that no ground-based truth is required and they can thus be applied on a global scale. So far, the TC-based methods have been limited to estimate the STandard Deviation (STD) at grid scale. These estimates represent an overall STD error for the precipitation products over each grid. Such information is useful to investigate sources of errors such as topography or surface properties, but as “static” information, it is limited and cannot represent precipitation error for a particular time step. Regime-dependent uncertainties of the satellite products are mandatory to better assess their quality and combine them <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a posteriori</i> . In this letter, a simple and easy-to-implement method is introduced to estimate regime-dependent STD error of precipitation with the TC framework. Instead of considering collocation at grid scale, the method relies on clustering to distinguish various precipitation regimes. The method then estimates the corresponding STD errors of the three precipitation datasets for each one of the bins (i.e., clusters). These regime-dependent STDs offer a temporal as well as a spatial description of the error statistics. Tests are conducted for multisource precipitation estimates over Europe.

Improve the Efficiency of the Yaskawa Motoman MH5 Robot for Utilization in Robot-Assisted Orthopedic Surgery

Introduction: Despite a wide range of applications of robotics in medical sciences, the role of medical robotics in orthopedic surgeries is of great importance. Methods: In the present study, the transformation, spatial description, and movement of the Yaskawa Motoman MH5 robot were compared with two improved types of this robot. In type A, a rotational joint is replaced with the prismatic joint, and in type B, beside a rotational joint, a prismatic joint is added to the mechanism of the original robot. Results: The results demonstrated that despite the fact that type A used less distance, it had a stronger possibility than type B for workspaces feasibility spatial movement. The results also indicated that the first, second, and third joints must be involved to create a static balance in type A robot, and for type B, in the same conditions, the first, second, third, and fourth joints must be involved. This means that the type A robot needs a higher power to make the balance, and the error potential in the type B robot is higher than that of type A. Discussion: The internal loading that the joints of type A robot must tolerate maintaining a static balance is greater than that of type B, which causes more wear out of type A robot. From workspaces and movements points of view, the efficiency of the type B MH5 robot is greater than in other cases.

Spatial analysis of COVID-19 in North Minahasa Regency of North Sulawesi Province

Background: COVID-19 is an infectious disease that is currently a concern and has become a global problem. The trend in the number of confirmed cases and deaths due to COVID-19 every day is still increasing significantly. North Sulawesi Province currently has 7 regencies/cities which are declared as local transmission areas including North Minahasa Regency. The population density factor can affect the process of transmission of this disease. This study aims to determine the spatial description of the distribution of COVID-19 events in North Minahasa Regency.Methods: This quantitative research with descriptive observational design using a geographic information system approach. The location is in 10 sub-districts of North Minahasa Regency. Study population was all patients who were confirmed positive for COVID-19 based on data from the North Minahasa District Health Office as of 13 February 2021, as many as 1,273 cases. Simple random sampling was used and obtained 300 samples.Results: Results showed that the highest number of cases was for the age group 30-49 years (40%), female gender (54.7%), symptom onset date interval 4 days (26.7%), confirmation date grouped by month, namely October in 2020 (23%), the status of the patient recovered (86%), and there were no comorbidities (82%).Conclusions: Most of the cases of COVID-19 were found in densely populated areas and passenger transit areas between districts/cities. Policies on prevention and supervision of health protocols that are implemented must synergize across sectors and need to be improved.

Language and Cognition: The Exploration of Spatial Description in English and Pashto Languages

This article explores the relation between language and cognition by examining the spatial description in English and Pashto. The study is descriptive and exploratory in nature. It identifies how Pashto and English speakers respond when they are asked to guide a stranger to some location, and which systems of reference they use to indicate directions and locations. For this purpose, firstly, the conversation of four speakers was recorded in Pashto and English and then transcribed and analysed by applying the rules of conversational analysis. After analysing the data, it has been found that all four speakers predominantly used the egocentric and intrinsic codes of spatial reference whereas absolute system of reference was rarely used. These findings strengthen the view that speakers are inclined to use objects in the environment as well as egocentric system associated with the speakers’ point of view. Moreover, the speakers’ responses are depended on the physical and situational context and independent of the languages they use. The study concludes with the understanding that there may be universal features demonstrable in the spatial domain.

Analisis Spasial pada Model Perekonomian Sumatera Bagian Selatan

This study tries to use the Spatial concept by analyzing the observed spatial patterns and spatial autocorrelation, as well as evaluating the spatial modeling of each region in 60 districts/cities in five Southern Sumatra Provinces. This research used Geoda. Geoda will then provide a spatial description of the condition of the percentage of GRDP presented in the Moran I statistics, LISA and LISA Clusterd Map in 2015-2019.&#x0D; The results of this study are expected to show the spatial relationship of GRDP between 60 regencies/cities in five provinces in Sumbagsel and be able to indicate how the spatial relationship is in the clustered pattern of regions with the same characteristics. Furthermore, the LISA Cluster map is expected to describe the grouping of GRDP in 11 regions. The SAR model was chosen to analyze cases of spatial linkage. This study will further provide an economic analysis of how the percentage of the population and GRDP influence, In addition, this study will examine how the influence of the Development Index and poverty on GRDP. Therefore, this research will be one of the studies that has the latest updates because it uses two approaches; spatial approach and economic approach presented in the results of the discussion and discussion.

Learning-based classification of multispectral images for deterioration mapping of historic structures

The conservation of historic structures requires detailed knowledge of their state of preservation. Documentation of deterioration makes it possible to identify risk factors and interpret weathering mechanisms. It is usually performed using non-destructive methods such as mapping of surface features. The automated mapping of deterioration is a direction not often explored, especially when the investigated architectural surfaces present a multitude of deterioration forms and consist of heterogeneous materials, which significantly complicates the generation of thematic decay maps. This work combines reflectance imaging and supervised segmentation, based on machine learning methods, to automatically segment deterioration patterns on multispectral image composites, using a weathered historic fortification as a case study. Several spectral band combinations and image classification techniques (regression, decision tree, and ensemble learning algorithmic implementations) are evaluated to propose an accurate approach. The automated thematic mapping facilitates the spatial and semantic description of the deterioration patterns. Furthermore, the utilization of low-cost photographic equipment and easily operable digital image processing software adds to the practicality and agility of the presented methodology.

Locative phrase and descriptive discourse in L2 Chinese

AbstractThis study examines the way in which French-speaking learners of L2 Chinese construct a type of discourse calledstatic spatial description. It involves the analysis of an oral corpus collected from two groups of native speakers of Chinese and French, and two groups of learners of L2 Chinese at two proficiency levels (low and intermediate). The data collected consist of the description of a poster. The results show that linguistic devices used in Chinese and French to encode the locative phrase and its syntactic functions have an impact on the presence and placement of the locative in utterances encoding spatial localization. These properties in turn influence the way in which the informational content develops across the utterances in the discourse. There is a clear development of proficiency between the two L2 groups. However, intermediate learners are not yet able to organize information on the discourse level like native Chinese speakers do.

Geotagging of natural history collections for reuse in environmental research

The availability of archival spatial datasets, which are crucial means of obtaining valuable information in biological and ecological research, is often limited due to the analog form of the data. Therefore, digitization projects of natural history collections (NHCs) currently show a rising trend. Increasingly, these projects include geotagging, which means assigning geographical coordinates and spatial attributes to specimens discovered in the field. Although numerous studies have examined the process of digitizing NHCs, there is still a need to develop good practice guides and a unified database or list of geographical information resources. Moreover, the accuracy of the spatial assignment of specimen locations in many online databases is unacceptable for environmental research. Therefore, it is important to develop a methodology to standardize geotagging methods.The first goal of this paper was to create and verify a list of available online sources of geotagged spatial information. The second goal was to develop a good practice guide for geotagging NHCs based on the limitations resulting from the specificity of archival data. These aims were achieved owing to participation in the AMU Nature Collections project – digitization and sharing of natural data resources of the Faculty of Biology of Adam Mickiewicz University in Poznań (AMUNATCOLL). The results of the proposed methodology indicate that natural history data are so heterogeneous in terms of spatial description quality that it is not always possible to unambiguously and precisely geotag them. Therefore, it is important to implement the spatial quality assessment and commenting system proposed by the authors.

Curvature effects and radial homoclinic snaking

Abstract In this work, we revisit some general results on the dynamics of circular fronts between homogeneous states and the formation of localized structures in two dimensions (2D). We show how the bifurcation diagram of axisymmetric structures localized in radius fits within the framework of collapsed homoclinic snaking. In 2D, owing to curvature effects, the collapse of the snaking structure follows a different scaling that is determined by the so-called nucleation radius. Moreover, in the case of fronts between two symmetry-related states, the precise point in parameter space to which radial snaking collapses is not a ‘Maxwell’ point but is determined by the curvature-driven dynamics only. In this case, the snaking collapses to a ‘zero surface tension’ point. Near this point, the breaking of symmetry between the homogeneous states tilts the snaking diagram. A different scaling law is found for the collapse of the snaking curve in each case. Curvature effects on axisymmetric localized states with internal structure are also discussed, as are cellular structures separated from a homogeneous state by a circular front. While some of these results are well understood in terms of curvature-driven dynamics and front interactions, a proper mathematical description in terms of homoclinic trajectories in a radial spatial dynamics description is lacking.

Analisis Spasial Breeding Places Potensial Aedes sp di Desa Bangunharjo, Sewon, Bantul, DIY

DHF is an endemic disease that spreads massively throughout the year, especially in the rainy season. It needs a method that can depict the spread of dengue cases based on the map of Ae-des sp. distribution. The aim of the study is to find out the spatial description of potential breeding places of Aedes sp. at Bangunharjo village, in Sewon, Bantul, DIY, by conducting a descriptive study with survey method. The study was held between January-April 2020. As the study popula-tion was 39 houses of DHF cases in 2019, meanwhile as the sample were 16 houses of dengue cases during two trimesters (May-December) in 2019 that met the criteria. The examination used visual larvae survey method, and to record the houses’ coordinates was by using GPS based on the presence of larvae. The study results show that the distribution of dengue cases in Bangun-harjo Village were occuring in all dukuh and tends to spread throughout the villages. This DHF mapping become a guide to see the presence of larvae at 50 m and 100 m distance from the cases’ houses based on possible breeding sites Aedes sp. The results also exhibit that the distri-bution of larvae in Bangunharjo Village as many as 40 houses (37,03 %) out of the observed 108 houses. The distribution of larvae using buffer method based on the type of containers, reveal that larvae distribution is found mostly in containers that used for daily purposes. The buffer ana-lyses find that DFH transmission at 50 m radius zone from cases’ point is more at risk to occur because more larvae are found

Randomized study comparing 3D virtual reality and conventional 2D on-screen teaching of cerebrovascular anatomy.

Performing aneurysmal clipping requires years of training to successfully understand the 3D neurovascular anatomy. This training has traditionally been obtained by learning through observation. Currently, with fewer operative aneurysm clippings, stricter work-hour regulations, and increased patient safety concerns, novel teaching methods are required for young neurosurgeons. Virtual-reality (VR) models offer the opportunity to either train a specific surgical skill or prepare for an individual surgery. With this study, the authors aimed to compare the spatial orientation between traditional 2D images and 3D VR models in neurosurgical residents or medical students. Residents and students were each randomly assigned to describe 4 aneurysm cases, which could be either 2D images or 3D VR models. The time to aneurysm detection as well as a spatial anatomical description was assessed via an online questionnaire and compared between the groups. The aneurysm cases were 10 selected patient cases treated at the authors' institution. Overall, the time to aneurysm detection was shorter in the 3D VR model compared to 2D images, with a trend toward statistical significance (25.77 ± 37.26 vs 45.70 ± 51.94 seconds, p = 0.052). No significant difference was observed for residents (3D VR 24.47 ± 40.16 vs 2D 33.52 ± 56.06 seconds, p = 0.564), while in students a significantly shorter time to aneurysm detection was measured using 3D VR models (26.95 ± 35.39 vs 59.16 ± 44.60 seconds, p = 0.015). No significant differences between the modalities for anatomical and descriptive spatial mistakes were observed. Most participants (90%) preferred the 3D VR models for aneurysm detection and description, and only 1 participant (5%) described VR-related side effects such as dizziness or nausea. VR platforms facilitate aneurysm recognition and understanding of its spatial anatomy, which could make them the preferred method compared to 2D images in the years to come.

Optimal Trajectory Generation for Intelligent Vehicles in Complex Traffic Based on Iteration Convex Optimization

Intelligent vehicles face considerable challenges in the complex traffic environment since they need to deal with various constraints and elements. This dissertation puts forward a novel trajectory planning framework for intelligent vehicles to generate safe and optimal driving trajectories. First, we design a spatiotemporal occupancy framework to deal with all kinds of elements in the complex driving environment based on the Frenét frame. This framework unifies various constraints on the road in the three-dimensional spatiotemporal representation and clearly describes the collision-free configuration space. Then we use the convex approximation method to construct a time-varying convex feasible region based on the above accurate temporal and spatial description. We formulate the trajectory planning problem as a standard quadratic programming formulation with collision-free and dynamics constraints. Finally, we apply the iterative convex optimization algorithm to solve the quadratic programming problem in the time-varying convex feasible region. Moreover, we design several typical experimental scenarios and have verified that the proposed method has good effectiveness and real-time.

Combining Multiband Imaging, Photogrammetric Techniques, and FOSS GIS for Affordable Degradation Mapping of Stone Monuments

The detailed documentation of degradation constitutes a fundamental step for weathering diagnosis and, consequently, for successful planning and implementation of conservation measures for stone heritage. Mapping the surface patterns of stone is a non-destructive procedure critical for the qualitative and quantitative rating of the preservation state. Furthermore, mapping is employed for the annotation of weathering categories and the calculation of damage indexes. However, it is often a time-consuming task, which is conducted manually. Thus, practical methods need to be developed to automatize degradation mapping without significantly increasing the diagnostic process’s cost for conservation specialists. This work aims to develop and evaluate a methodology based on affordable close-range sensing techniques, image processing, and free and open source software for the spatial description, annotation, qualitative analysis, and rating of stone weathering-induced damage. Low-cost cameras were used to record images in the visible, near-infrared, and thermal-infrared spectra. The application of photogrammetric techniques allowed for the generation of the necessary background, that was elaborated to extract thematic information. Digital image processing of the spatially and radiometrically corrected images and image mosaics enabled the straightforward transition to a spatial information environment simplifying the development of degradation maps. The digital thematic maps facilitated the rating of stone damage and the extraction of useful statistical data.

EDENet: Elaborate density estimation network for crowd counting

For the CNN-based density estimation approaches in the field of crowd counting, how to generate a high-quality density map with accurate counting performance and detailed spatial description is still an open question. In this paper, to tackle the aforementioned contradiction, we propose an end-to-end trainable architecture called Elaborate Density Estimation Network for Crowd Counting (EDENet), which can gradually generate high-quality density estimation maps based on distributed supervision. Specifically, EDENet is composed of Feature Extraction Network (FEN), Feature Fusion Network (FFN), Double-Head Network (DHN) and Adaptive Density Fusion Network (ADFN). The FEN adopts VGG as the backbone network and employs Spatial Adaptive Pooling (SAP) to extract coarse-grained features. The FFN can effectively fuse contextual information and localization information for enhancing the spatial description ability of fine-grained features. In the DHN, the Density Attention Module (DAM) can provide attention masks of foreground-background, thereby urging the Density Regression Module (DRM) to focus on the pixels around the head annotations to regress density maps with different resolutions. The ADFN constructed on the basis of the adaptive weighting mechanism can directly introduce coarse-grained density representation into high-resolution density maps to strengthen the commonality and dependency among density maps. Extensive experiments on four benchmark crowd datasets (the ShanghaiTech, the UCF-QNRF, the JHU-CRWORD++ and the NWPU-Crowd) indicate that EDENet can achieve state-of-the-art recognition performance and high robustness. Not only that, the density map with the highest Peak Signal to Noise Ratio (PSNR) can be considered to be of high quality.

Text-Guided Human Image Manipulation via Image-Text Shared Space.

Text is a new way to guide human image manipulation. Albeit natural and flexible, text usually suffers from inaccuracy in spatial description, ambiguity in the description of appearance, and incompleteness. We in this paper address these issues. To overcome inaccuracy, we use structured information (e.g., poses) to help identify correct location to manipulate, by disentangling the control of appearance and spatial structure. Moreover, we learn the image-text shared space with derived disentanglement to improve accuracy and quality of manipulation, by separating relevant and irrelevant editing directions for the textual instructions in this space. Our model generates a series of manipulation results by moving source images in this space with different degrees of editing strength. Thus, to reduce the ambiguity in text, our model generates sequential output for manual selection. In addition, we propose an efficient pseudo-label loss to enhance editing performance when the text is incomplete. We evaluate our method on various datasets and show its precision and interactiveness to manipulate human images.

‘I Must Also See Rome’ (Acts 19:21)

This article discusses eyewitnessing as a literary motif in Luke and Acts. Both writings position themselves within a scientific-historiographical tradition which conceives of eyewitness testimony as the most reliable source of knowledge. Hence, both Luke and Acts bolster the trustworthiness of their contents by presenting it as going back to eyewitness testimonies by e.g. the shepherds in Luke 2 and the women and disciples in Luke 24. Aside from this inclusio of eyewitnesses, the repeated expression ‘what we/you/they have seen and heard’ embodies the centrality of eyewitnessing in Luke’s and Acts’s accounts. The second section of the article connects the development of an eyewitness perspective in Acts with notions of space and memory. In that section I argue that the combination of spatial description and autopsy language in Acts serves to create literary memories of David’s tomb, the Areopagus, and the city of Rome.

Spatial description theory of narrow-band single-carrier avalanche photodetectors.

The avalanche is the foundation of the understanding and vast applications of the breakdown of semiconductors and insulators. Present numerical theories analyzing the avalanche photodetectors are mainly split into two categories: the macroscopic empirical model with fitting parameters and the microscopic process simulation with statistical estimations. Here, we present a parameter-free analytic theory of the avalanche for a narrow-band material, HgCdTe, originated from quantum mechanics, avoiding any fitting parameter or any statistical estimation while taking advantage of both categories. Distinct from classical theory, we propose a full spatial description of an avalanche with basic concepts such as transition rate and equation of motion modified. As a stochastic process, the probability density function (PDF) of impact ionization is utilized in a generalized history-dependent theory. On account of different carrier generation character of light and leakage current, we suggest that carrier generated at different positions should be considered separately, which is done by generalized history-dependent theory in our work. Further, in our calculation, the reason for the abnormal rise of excess noise factor (ENF) observed in the experiment in single-carrier avalanche photodetectors is clarified.

A new approach to solving the solid mechanics problems with matter supply

We discuss some aspects of using the spatial description and the finite volume method as applied to the solid mechanics problems. The main objective is to study the differential equation relating the strain measure to the velocity gradient. We show that this equation can be reduced to an integral form and the obtained equation has the structure of the balance equation without a source term. On the one hand, such form of equation for the strain measure is convenient when dynamical problems of solid mechanics are solved by using the finite volume method. On the other hand, the balance equation allows us to look at the strain measure as a parameter of state in a broader sense, not as the purely geometrical characteristic. We believe that this interpretation of the strain measure may open up new prospects for describing the processes connected with the substance supply into solids. In order to solve such problems, we suggest to add a source term into the balance equation for the strain measure. We discuss this idea from different points of view. We also solve some problems where the stress–strain state of solids is caused by the source terms in the balance equation for the strain measure.