Assemble geo-analytical questions through a Blockly-based natural language interface

Natural language Interfaces (NLIs) have the ability to make Geographic Information Systems more accessible for interdisciplinary researchers or any inexperienced users. However, the majority of research on NLIs for GIS explored NLIs for visualization or spatial data retrieval. Research on NLIs for geo-analytical questions is still lacking. Google Blockly, an open-source JavaScript library, is frequently used for developing visual programming editors for young students learning programming languages. Students set up program functions by selecting and assembling the programming blocks and the Blockly system automatically translates the block stacks into different programming languages. Similarly, we present a Blockly-based interface that generates a question depending on the blocks the user has assembled. It can be seen that a Blockly-based interface not only naturally represents syntactic structures in geo-analytical questions but also well assists users in familiarizing the blocks and generating clear and complete questions. A comprehensive usability study is still necessary to better evaluate the interface’s performance

A grammar for interpreting geo-analytical questions as concept transformations

Geographic Question Answering (GeoQA) systems can automatically answer questions phrased in natural language. Potentially this may enable data analysts to make use of geographic information without requiring any GIS skills. However, going beyond the retrieval of existing geographic facts on particular places remains a challenge. Current systems usually cannot handle geo-analytical questions that require GIS analysis procedures to arrive at answers. To enable geo-analytical QA, GeoQA systems need to interpret questions in terms of a transformation that can be implemented in a GIS workflow. To this end, we propose a novel approach to question parsing that interprets questions in terms of core concepts of spatial information and their functional roles in context-free grammar. The core concepts help model spatial information in questions independently from implementation formats, and their functional roles indicate how concepts are transformed and used in a workflow. Using our parser, geo-analytical questions can be converted into expressions of concept transformations corresponding to abstract GIS workflows. We developed our approach on a corpus of 309 GIS-related questions and tested it on an independent source of 134 test questions including workflows. The evaluation results show high precision and recall on a gold standard of concept transformations

Association of immune cell traits with Parkinson’s disease: a Mendelian randomization study

BackgroundImmunity and neuroinflammation play crucial roles in the pathogenesis of Parkinson’s disease (PD). Nonetheless, prior investigations into the correlation between immune inflammation and PD have produced varying results. Identifying specific immune cell phenotypes that are truly associated with PD is challenging, and the causal relationship between immune cells and PD remains elusive.MethodsThis study conducted a comprehensive two-sample Mendelian randomization (MR) analysis, employing five distinct analytical approaches, to clarify the causal connection between immune cell characteristics and the risk of PD. Utilizing GWAS data, we investigated the causal relationship between 731 immune cell traits and PD. These immune cell phenotypes encompass absolute cell (AC) counts, median fluorescence intensity (MFI), and relative cell (RC) counts for B cells, cDCs, mature stage T cells, monocytes, myeloid cells, TBNK (T cells, B cells, and natural killer cells), and Tregs, as well as the logistic parameter (MP) for cDCs and TBNK.ResultsThe inverse variance weighted (IVW) analysis indicated that Myeloid DCs (p = 0.004), HVEM expression on CD45RA− CD4+ T cells (p = 0.007), CD62L− CD86+ Myeloid DCs (p = 0.015), and HLA DR expression on monocytes (p = 0.019) were associated with a reduced risk of PD. CD14+ CD16+ monocytes (p = 0.005), HLA DR+ NK cells within CD3− lymphocytes (p = 0.023), and CD28 expression on activated & secreting Tregs (p = 0.032) were associated with an increased risk of PD.ConclusionThis study establishes a causal link between immune cell phenotype and the pathogenesis of PD, identifying several specific immune cell characteristics associated with PD. This could inspire researchers to delve into the pathogenesis of PD at the cellular subtype level, and aid in the identification of potential pharmacological protein targets for PD

The Semantics of Extensive Quantities within Geographic Information

The next generation of Geographic Information Systems (GIS) is anticipated to automate some of the reasoning required for spatial analysis. An important step in the development of such systems is to gain a better understanding and corresponding modeling practice of when to apply arithmetic operations to quantities. The concept of extensivity plays an essential role in determining when quantities can be aggregated by summing them, and when this is not possible. This is of particular importance to geographic information systems, which serve to quantify phenomena across space and time. However, currently, multiple contrasting definitions of extensivity exist, and none of these suffice for handling the different practical cases occurring in geographic information. As a result, analysts predominantly rely on intuition and ad hoc reasoning to determine whether two quantities are additive. In this paper, we present a novel approach to formalizing the concept of extensivity. Though our notion as such is not restricted to quantifications occurring within geographic information, it is particularly useful for this purpose. Following the idea of spatio-temporal controls by Sinton, we define extensivity as a property of measurements of quantities with respect to a controlling quantity, such that a sum of the latter implies a sum of the former. In our algebraic definition of amounts and other quantities, we do away with some of the constraints that limit the usability of older approaches. By treating extensivity as a relation between amounts and other types of quantities, our definition offers the flexibility to relate a quantity to many domains of interest. We show how this new notion of extensivity can be used to classify the kinds of amounts in various examples of geographic information

DMRT1 regulates human germline commitment

Germline commitment following primordial germ cell (PGC) specification during early human development establishes an epigenetic programme and competence for gametogenesis. Here we follow the progression of nascent PGC-like cells derived from human embryonic stem cells in vitro. We show that switching from BMP signalling for PGC specification to Activin A and retinoic acid resulted in DMRT1 and CDH5 expression, the indicators of migratory PGCs in vivo. Moreover, the induction of DMRT1 and SOX17 in PGC-like cells promoted epigenetic resetting with striking global enrichment of 5-hydroxymethylcytosine and locus-specific loss of 5-methylcytosine at DMRT1 binding sites and the expression of DAZL representing DNA methylation-sensitive genes, a hallmark of the germline commitment programme. We provide insight into the unique role of DMRT1 in germline development for advances in human germ cell biology and in vitro gametogenesis

Empirical Evidence for Concepts of Spatial Information as Cognitive Means for interpreting and using Maps

Due to the increasing prevalence and relevance of geo-spatial data in the age of data science, Geographic Information Systems are enjoying wider interdisciplinary adoption by communities outside of GIScience. However, properly interpreting and analysing geo-spatial information is not a trivial task due to knowledge barriers. There is a need for a trans-disciplinary framework for sharing specialized geographical knowledge and expertise to overcome these barriers. The core concepts of spatial information were proposed as such a conceptual framework. These concepts, such as object and field, were proposed as cognitive lenses that can simplify understanding of and guide the processing of spatial information. However, there is a distinct lack of empirical evidence for the existence of such concepts in the human mind or whether such concepts can be indeed useful. In this study, we have explored for such empirical evidence using behavioral experiments with human participants. The experiment adopted a contrast model to investigate whether the participants can semantically distinguish between the object and field core concepts visualized as maps. The statistically significant positive results offer evidence supporting the existence of the two concepts or cognitive concepts closely resembling them. This gives credibility to the core concepts of spatial information as tools for sharing, teaching, or even automating the process of geographical information processing

Development of a digitalization tool for linking thematic data to a background map

Cartographic mashups present geographic data from various sources. A typical example is adding thematic data on top of a multi-scales background map. Currently, thematic data and multi-scales background data are not linked together in cartographic mashups which may have potential problems such as inconsistency of scale ranges. However, in some cases, thematic data and background data have some identical geometries. By creating linkage via these common parts, thematic data can be linked to background map. The Sematic Web is a Web 3.0 technology through standards by the World Wide Web Consortium (W3C). It provides techniques that enable people to create and link data in standard data formats by semantically describing interrelations of datasets. The linked data can be shared and reused across application, enterprise, and community boundaries. This study develops a digitalization tool to create and link thematic data to background data in a cartographic mashup. The tool provides two ways to create geometries of thematic data: (1) using common geometries from background map and (2) generating new geometries. Then, thematic data are linked to background data by applying the Semantic Web technologies in the tool. After implementation of the digitalization tool, it is used to create and link thematic data to background map in a use case. Finally, the tool is evaluated against some predefined requirement specifications. It turns out that the digitalization tool manages to create and link thematic data with a background map. With the digitalization tool developed in this study, thematic data are linked to background map which contributes to synchronize scale ranges between two datasets. It also benefits the real-time data integration of multi-scale data in cartographic mashups.A cartographic mashup presents geographic data from multiple sources, an example is adding thematic data (e.g. natural hazard data, city crime data, etc.) on top of a background map (e.g. topographic map, Google map, etc.) In the current cartographic mashups, thematic data do not link with background map. Sometimes, there might be displacements between two datasets. Moreover, thematic data only have one or few scales while background maps always have more. As a result, it could cause inconsistencies when adding thematic data above a background map in cartographic mashups. However, in some cases, thematic data and background data have some identical geometries. By creating linkage via these common parts, thematic data can be linked to background map. And thus, the displacement problems and scales ranges between two datasets can be solved. The Semantic Web provides techniques that enable people to create and link data in standard data formats by explicitly describing interrelations of datasets. This study develops a digitalization tool to create and link thematic data to a background map. The tool provides two ways to create geometries of thematic data: (1) using common geometries from a background map and (2) generating new geometries. Then, thematic data are linked to background data by applying the Semantic Web technologies in the tool. After implementation of the digitalization tool, it is used to create and link thematic data to background map in a use case. Finally, the tool is evaluated against some predefined requirement specifications. It turns out that the digitalization tool manages to create and link thematic data with a background map