Relational Persistent Homology for Multispecies Data with Application to the Tumor Microenvironment.

Topological data analysis (TDA) is an active field of mathematics for quantifying shape in complex data. Standard methods in TDA such as persistent homology (PH) are typically focused on the analysis of data consisting of a single entity (e.g., cells or molecular species). However, state-of-the-art data collection techniques now generate exquisitely detailed multispecies data, prompting a need for methods that can examine and quantify the relations among them. Such heterogeneous data types arise in many contexts, ranging from biomedical imaging, geospatial analysis, to species ecology. Here, we propose two methods for encoding spatial relations among different data types that are based on Dowker complexes and Witness complexes. We apply the methods to synthetic multispecies data of a tumor microenvironment and analyze topological features that capture relations between different cell types, e.g., blood vessels, macrophages, tumor cells, and necrotic cells. We demonstrate that relational topological features can extract biological insight, including the dominant immune cell phenotype (an important predictor of patient prognosis) and the parameter regimes of a data-generating model. The methods provide a quantitative perspective on the relational analysis of multispecies spatial data, overcome the limits of traditional PH, and are readily computable.

"A Tale of Two Cities": Cemetery Heterotopia and Spatial Relations in Lagos City.

What does cemetery teach us about the social world? How do spatial configurations of cemetery mirror urban social realities? In what ways can the understanding of spatial order of necropolis contribute to the episteme of spatial relations? In this paper, I juxtapose space practices in the cemetery with spatial relations and practices in the city of Lagos to frame an alternative way of imagining and writing about cityscapes and a new approach of thinking about social taxonomies such as gender, class, race, ethnicity and power. Following Foucault's theory of heterotopia and relational ontology of space this paper frames cemetery as a counter-site to the city. Drawing from oral interviews, participant observation and archival document, the paper argues that cemetery is a container that encloses different sites and sets of social relations as well as lived experiences.

A Decentralized Fuzzy Rule-Based Approach for Computing Topological Relations between Spatial Dynamic Continuous Phenomena with Vague Boundaries Using Sensor Data.

Sensor networks (SN) are increasingly used for the observation and monitoring of spatiotemporal phenomena and their dynamics such as pollution, noise and forest fires. In multisensory systems, a sensor node may be equipped with different sensing units to observe and detect several spatiotemporal phenomena at the same time. Simultaneous detection of different phenomena can be used to infer their spatial interactions over space and time. For this purpose, decentralized spatial computing approaches have shown their potential for effective reasoning on spatial phenomena within a sensor network. However, in most cases, spatial extents of continuous dynamic phenomena are uncertain, and their relations and interactions cannot be inferred by the existing approaches at the sensor node level. To address this limitation, in this paper, we propose and develop a decentralized fuzzy rule-based spatial reasoning approach to depict the spatial relations that hold between two evolving spatial phenomena with fuzzy boundaries. The proposed method benefits from a more adapted fuzzy-crisp representation of dynamic phenomena observed by SN where each vague phenomenon is composed of five distinguished zones including the kernel, conjecture and exterior zone and their boundaries. For each detected phenomenon, a sensor node will report one of these zones based on its location. Aggregation of the information reported from the sensor nodes allows reasoning on spatial relations between the observed phenomena and their evolution. Such spatial information provides users with more valuable near real-time information on the state of different phenomena that can be used for informed decision-making.

The impact of age and familiarity with the environment on categorical and coordinate spatial relation representations.

Retrieving spatial information is a crucial everyday ability that is affected by age-related changes. Previous research has shown that this change is mediated by familiarity with an environment. The present research uses a series of landmark location tasks to extend and deepen our understanding of the role of aging in spatial mental representations of more or less familiar environments, also disentangling the contribution of coordinate and categorical spatial relations. The study tested the following hypotheses: (1) younger adults only have an advantage over the elderly in less familiar environments; (2) the advantage for categorical over coordinate spatial relations is mainly found for less familiar environments; and finally; (3) interactions between age, familiarity, and spatial relations might reveal that the effects of age and familiarity take different trajectories for coordinate and categorical spatial relations. Results confirmed that: (1) young people outperform the elderly only in less familiar environments; (2) there is a reduction in the difference between coordinate and categorical accuracy with increasing familiarity with the environment; while (3) the interaction between age and level of familiarity did not significantly differentiate coordinate from categorical spatial relations. In conclusion, the present study provides new evidence for the role of familiarity with geographical areas and its impact on the representation of categorical and coordinate relations, with practical implications for the assessment of topographical disorientation in aging.

Understanding spatial language in radiology: Representation framework, annotation, and spatial relation extraction from chest X-ray reports using deep learning.

Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic findings are mostly described in reference to an anatomical location through spatial prepositions. Such spatial relationships are also linked to various differential diagnoses and often described through uncertainty phrases. Structured representation of this clinically significant spatial information has the potential to be used in a variety of downstream clinical informatics applications. Our focus is to extract these spatial representations from the reports. For this, we first define a representation framework based on the Spatial Role Labeling (SpRL) scheme, which we refer to as Rad-SpRL. In Rad-SpRL, common radiological entities tied to spatial relations are encoded through four spatial roles: Trajector, Landmark, Diagnosis, and Hedge, all identified in relation to a spatial preposition (or Spatial Indicator). We annotated a total of 2,000 chest X-ray reports following Rad-SpRL. We then propose a deep learning-based natural language processing (NLP) method involving word and character-level encodings to first extract the Spatial Indicators followed by identifying the corresponding spatial roles. Specifically, we use a bidirectional long short-term memory (Bi-LSTM) conditional random field (CRF) neural network as the baseline model. Additionally, we incorporate contextualized word representations from pre-trained language models (BERT and XLNet) for extracting the spatial information. We evaluate both gold and predicted Spatial Indicators to extract the four types of spatial roles. The results are promising, with the highest average F1 measure for Spatial Indicator extraction being 91.29 (XLNet); the highest average overall F1 measure considering all the four spatial roles being 92.9 using gold Indicators (XLNet); and 85.6 using predicted Indicators (BERT pre-trained on MIMIC notes). The corpus is available in Mendeley at http://dx.doi.org/10.17632/yhb26hfz8n.1 and https://github.com/krobertslab/datasets/blob/master/Rad-SpRL.xml.

How to separate coordinate and categorical spatial relation components in integrated spatial representations: A new methodology for analysing sketch maps.

Spatial relations between landmarks can be represented by means of categories and coordinates. In the present research, this paradigm was applied to sketch maps based on information acquired in goal-directed behaviour of exploration of a university campus area. The first aim was to investigate whether categorical and coordinate information can be considered conceptually independent in sketch maps. The second aim was to assess which kind of distance measure served better to represent coordinate information in the present case study, and finally to assess the factorial structure of coordinate and categorical data. Analytic methodology as well as statistical analysis were found to confirm that separating coordinate and categorical components was formally as well as empirically appropriate. A series of confirmatory factor analyses showed the best fit for the model with two correlated components, as well as an acceptable reliability of measures emerged. The two components were moderately correlated. Moreover, the adoption of Manhattan distance seemed to be the most effective method to represent coordinate spatial relations in spatial sketch maps of areas acquired through navigation.

Beyond Household Walls: The Spatial Structure of American Extended Kinship Networks.

How far do Americans live from their close and extended kin? The answer is likely to structure the types of social, instrumental, and financial support that they are able to provide to one another. Based on the Panel Study of Income Dynamics, kin pairs vary widely in odds of household co-residence, co-residence in the same administrative units, and inter-tract distances if they do not live in the same census tract. Multivariate regression tests show that family structure, educational attainment, and age are closely associated with kin proximity. Fixed effects models demonstrate that fam ily formation shapes spatial relations between kin.

Positioning Locality Using Cognitive Directions Based on Indoor Landmark Reference System.

Locality descriptions are generally communicated using reference objects and spatial relations that reflect human spatial cognition. However, uncertainty is inevitable in locality descriptions. Positioning locality with locality description, with a mapping mechanism between the qualitative and quantitative data, is one of the important research issues in next-generation geographic information sciences. Spatial relations play an important role in the uncertainty of positioning locality. In indoor landmark reference systems, the nearest landmarks can be selected when describing localities by using direction relations indoors. By using probability operation, we combine a set of uncertainties, that is, near and direction relations to positioning locality. Some definitions are proposed from cognitive and computational perspectives. We evaluate the performance of our method through indoor cognitive experiments. Test results demonstrate that a positioning accuracy of 3.55 m can be achieved with the semantically derived direction relationships in indoor landmark reference systems.

Lateralized pointing does not cause a cognitive bias.

Lateralized pointing has been shown to cause not only a shift in visuo-motor midline, but also a shift in non-lateralized spatial attention. Non-lateralized cognitive consequences of lateralized pointing have been reported for local and global visuospatial processing. Here, we evaluate these findings and examine this effect for categorical and coordinate spatial relation processing, for which the attentional processes are thought to be highly similar to local and global visuospatial processing, respectively. Participants performed a commonly used working memory task to assess categorical and coordinate spatial relation processing. Lateralized pointing with either the left or the right hand, to either the left or the right side was introduced as a manipulation, as well as a new control condition without any pointing. Performance on the spatial relation task was measured before and after pointing. The results suggest that non-lateralized consequences of lateralized pointing cannot be generalized to other cognitive tasks relying on attentional processing. Further examination of lateralized pointing is recommended before drawing further conclusions concerning its impact on non-lateralized cognition.

When Far Becomes Near.

On many occasions, people spontaneously or deliberately take the perspective of a person facing them rather than their own perspective. How is this done? Using a spatial perspective task in which participants were asked to identify objects at specific locations, we found that self-perspective judgments were faster for objects presented to the right, rather than the left, and for objects presented closer to the participants' own bodies. Strikingly, taking the opposing perspective of another person led to a reversal (i.e., remapping) of these effects, with reference to the other person's position (Experiment 1). A remapping of spatial relations was also observed when an empty chair replaced the other person (Experiment 2), but not when access to the other viewpoint was blocked (Experiment 3). Thus, when the spatial scene allows a physically feasible but opposing point of view, people respond as if their own bodies were in that place. Imagination can thus overcome perception.

Topological Relations Between Objects Are Categorically Coded.

How do individuals compare images-for example, two graphs or diagrams-to identify differences between them? We argue that categorical relations between objects play a critical role. These relations divide continuous space into discrete categories, such as "above" and "below," or "containing" and "overlapping," which are remembered and compared more easily than precise metric values. These relations should lead to categorical perception, such that viewers find it easier to notice a change that crosses a category boundary (one object is now above, rather than below, another, or now contains, rather than overlaps with, another) than a change of equal magnitude that does not cross a boundary. We tested the influence of a set of topological categorical relations from the cognitive-modeling literature. In a visual same/different comparison task, viewers more accurately noticed changes that crossed relational category boundaries, compared with changes that did not cross these boundaries. The results highlight the potential of systematic exploration of the boundaries of between-object relational categories.

Frames of reference and categorical/coordinate spatial relations in a "what was where" task.

The aim of this study was to explore how people use egocentric (i.e., with respect to their body) and allocentric (i.e., with respect to another element in the environment) references in combination with coordinate (metric) or categorical (abstract) spatial information to identify a target element. Participants were asked to memorize triads of 3D objects or 2D figures, and immediately or after a delay of 5 s, they had to verbally indicate what was the object/figure: (1) closest/farthest to them (egocentric coordinate task); (2) on their right/left (egocentric categorical task); (3) closest/farthest to another object/figure (allocentric coordinate task); (4) on the right/left of another object/figure (allocentric categorical task). Results showed that the use of 2D figures favored categorical judgments over the coordinate ones with either an egocentric or an allocentric reference frame, whereas the use of 3D objects specifically favored egocentric coordinate judgments rather than the allocentric ones. Furthermore, egocentric judgments were more accurate than allocentric judgments when the response was Immediate rather than delayed and 3D objects rather than 2D figures were used. This pattern of results is discussed in the light of the functional roles attributed to the frames of reference and spatial relations by relevant theories of visuospatial processing.

Categorization of dynamic realistic motion events: Infants form categories of path before manner.

Acquiring verbs and prepositions requires categorization of spatial relations. This study examined whether a ground object differentially influences 13- to 15-month-old English-learning infants' categorization of a figure's path (e.g., around; Experiment 1) and manner (e.g., hopping; Experiment 2) of motion in non-linguistic dynamic realistic events. Furthermore, we tested whether categorizing path is "easier" than categorizing manner. Results revealed that infants categorized path only in the presence of a ground object, validating Talmy's definition of path. In contrast, infants categorized manner only in the absence of a ground object. Finally, infants categorizing path showed stronger novelty preferences than those categorizing manner, supporting a primacy of path. Infants showed sensitivity to event components lexicalized in relational terms.

Children's limited tooling ability in a novel concurrent tool use task supports the innovation gap.

School-aged children have consistently shown a surprising developmental lag when attempting to innovate solutions to tool use tasks, despite being capable of learning to solve these problems from a demonstrator. We suggest that this "innovation gap" arises from tool tasks with more complex spatial relations. Following Fragaszy and Mangalam's new tooling theory, we predicted that innovating a new "sticker slide" task should be more challenging when two tools need to be used at the same time (concurrently) rather than one at a time (sequentially), despite the similarity of the other task elements. In line with previous work, both versions of the task were challenging for all ages of children (4-9 years) that we tested. However, the youngest group showed particularly extreme difficulties, which was marked by not a single child innovating the concurrent version. Although success significantly increased with age, even the oldest group failed to reach 50% success on the concurrent version of the task, whereas the majority of the two older groups could solve the sequential version. Thus, in this first study of concurrent tool use in children, we found support for the prediction that increasing the complexity of spatial relations in tooling exacerbates the innovation gap.

Perceptual specialization and configural face processing in infancy.

Adults' face processing expertise includes sensitivity to second-order configural information (spatial relations among features such as distance between eyes). Prior research indicates that infants process this information in female faces. In the current experiments, 9-month-olds discriminated spacing changes in upright human male and monkey faces but not in inverted faces. However, they failed to process matching changes in upright house stimuli. A similar pattern of performance was exhibited by 5-month-olds. Thus, 5- and 9-month-olds exhibited specialization by processing configural information in upright primate faces but not in houses or inverted faces. This finding suggests that, even early in life, infants treat faces in a special manner by responding to changes in configural information more readily in faces than in non-face stimuli. However, previously reported differences in infants' processing of human versus monkey faces at 9 months of age (but not at younger ages), which have been associated with perceptual narrowing, were not evident in the current study. Thus, perceptual narrowing is not absolute in the sense of loss of the ability to process information from other species' faces at older ages.

Concepts in Space: Enhancing Lexical Search With a Spatial Diversity Prime.

Informed by theories of embodied cognition, in the present study, we designed a novel priming technique to investigate the impact of spatial diversity and script direction on searching through concepts in both English and Persian (i.e., two languages with opposite script directions). First, participants connected a target dot either to one other dot (linear condition) or to multiple other dots (diverse condition) and either from left to right (rightward condition) or from right to left (leftward condition) on a computer touchscreen using their dominant hand's forefinger. Following the spatial prime, they were asked to generate as many words as possible using two-letter cues (e.g., "lo" → "love," "lobster") in 20 s. We hypothesized that greater spatial diversity, and consistency with script direction, should facilitate conceptual search and result in a higher number of word productions. In both languages, word production performance was superior for the diverse prime relative to the linear prime, suggesting that searching through lexical memory is facilitated by spatial diversity. Although some effects were observed for the directionality of the spatial prime, they were not consistent across experiments and did not correlate with script direction. This pattern of results suggests that a spatial prime that promotes diverse paths can improve word retrieval from lexical memory and lends empirical support to the embodied cognition framework, in which spatial relations play a crucial role in the conceptual system.

Dissociation of categorical and coordinate spatial relations on dynamic network organization states.

Humans can flexibly represent both categorical and coordinate spatial relations. Previous research has mainly focused on hemisphere lateralization in representing these two types of spatial relations, but little is known about how distinct network organization states support representations of the two. Here we used dynamic resting-state functional connectivity (FC) to explore this question. To do this, we separated a meta-identified navigation network into a ventral and two other subnetworks. We revealed a Weak State and a Strong State within the ventral subnetwork and a Negative State and a Positive State between the ventral and other subnetworks. Further, we found the Weak State (i.e., weak but positive FC) within the ventral subnetwork was related to the ability of categorical relation recognition, suggesting that the representation of categorical spatial relations was related to weak integration among focal regions in the navigation network. In contrast, the Negative State (i.e., negative FC) between the ventral and other subnetworks was associated with the ability of coordinate relation processing, suggesting that the representation of coordinate spatial relations may require competitive interactions among widely distributed regions. In sum, our study provides the first empirical evidence revealing different focal and distributed organizations of the navigation network in representing different types of spatial information.

Study on Spatial Geometric Similarity Based on Conformal Geometric Algebra.

The study of spatial geometric similarity plays a significant role in spatial data retrieval. Many researchers have examined spatial geometric similarity, which is useful for spatial analysis and data retrieval. However, the majority of them focused on objects of the same type. Methods to support the spatial geometric similarity computation for different types of objects are rare, a systematic theory index has not been developed yet, and there has not been a comprehensive computational model of spatial geometric similarity. In this study, we conducted an analysis of the spatial geometric similarity computation based on conformal geometric algebra (CGA), which has certain advantages in the quantitative computation of the measurement information of spatial objects and the qualitative judgment of the topological relations of spatial objects. First, we developed a unified expression model for spatial geometric scenes, integrating shapes of objects and spatial relations between them. Then, we established a model for the spatial geometric similarity computation under various geographical circumstances to provide a novel approach for spatial geometric similarity research. Finally, the computation model was verified through a case study. The study of spatial geometric similarity sheds light on spatial data retrieval, which has scientific significance and practical value.

Geographically weighted regression model for physical, social, and economic factors affecting the COVID-19 pandemic spreading.

This study aims to analyze the spatial distribution of the epidemic spread and the role of the physical, social, and economic characteristics in this spreading. A geographically weighted regression (GWR) model was built within a GIS environment using infection data monitored by the Iraqi Ministry of Health records for 10 months from March to December 2020. The factors adopted in this model are the size of urban interaction areas and human gatherings, movement level and accessibility, and the volume of public services and facilities that attract people. The results show that it would be possible to deal with each administrative unit in proportion to its circumstances in light of the factors that appear in it. So, there will not be a single treatment for all areas with different urban characteristics, which sometimes helps not to stop social and economic life due to the imposition of a comprehensive ban on movement and activities. Therefore, there will be other supportive policies other than the ban, depending on the urban indicators for each region, such as reducing external movement from it or relying on preventing public activities only.

Identifying spatial relations of industrial carbon emissions among provinces of China: evidence from unsupervised clustering algorithms.

Reducing the total carbon emissions of modern industry is of great significance for China to achieve the carbon peak mission. The MD-SNA spatial correlation measure methodology was innovatively proposed in this paper, which was based on the clustering algorithm of similarity measure. Furthermore, the social network analysis (SNA) method was incorporated to explore the spatial relationship of provincial industrial carbon emissions. The GINI coefficient, Theil index (GE0), and mean of logarithmic deviation (GE1) were used to measure the regional differences of China's industrial carbon emissions. More specifically, we adopted a combined tactic of spatial difference and spatial correlation frameworks. The primary objective of the proposed methodology is to empirically investigate the structural characteristics and spatial relations of different provinces. The results of the case study are as follows. First, the regional industrial carbon emission intensity was unbalanced, among which energy-rich provinces and eastern developed provinces were relatively strong. Second, Beijing, Shandong, Shaanxi, Henan, Sichuan, and Xinjiang were located at the center of the spatial network of industrial carbon emissions. Third, our work clarified the node attributes and different functions of provinces. More than half of the core provinces belonged to the primary beneficial block, which was in the central position of spatial correlation network. The conclusion can help policymakers clarify the overall industrial sector spatial pattern and provinces' roles and functions.