Positioning Localities for Vague Spatial Location Description: A Supervaluation Semantics Approach

In the big data era, spatial positioning based on location description is the foundation to the intelligent transformation of location-based-services. To solve the problem of vagueness in location description in different contexts, this paper proposes a positioning method based on supervaluation semantics. Firstly, through combing the laws of human spatial cognition, the types of elements that people pay attention to in location description are clarified. On this basis, the source of vagueness in the location description and its embodiment in the expression form of each element are analyzed from multiple levels. Secondly, the positioning model is constructed from the following three aspects: spatial object, distance relation and direction relation. The contexts of multiple location description are super-valued, respectively, while the threshold of observations is obtained from the context semantics. Thus, the precisification of location description is realized for positioning. Thirdly, a question-answering system is designed to the collect contexts of location description, and a case study on the method is conducted. The case can verify the transformation of a set of users’ viewpoints on spatial cognition into the real-world spatial scope, to realize the representation of vague location description in the geographic information system. The result shows that the method proposed in the paper breaks through the traditional vagueness modeling, which only focuses on spatial relationship, and enhances the interpretability of semantics of vague location description. Moreover, supervaluation semantics can obtain the precisification results of vague location description in different situations, and the positioning localities are more suitable to individual subjective cognition.

Achieving ‘Active’ 30 Minute Cities: How Feasible Is It to Reach Work within 30 Minutes Using Active Transport Modes?

Confronted with rapid urbanization, population growth, traffic congestion, and climate change, there is growing interest in creating cities that support active transport modes including walking, cycling, or public transport. The ‘30 minute city’, where employment is accessible within 30 min by active transport, is being pursued in some cities to reduce congestion and foster local living. This paper examines the spatial relationship between employment, the skills of residents, and transport opportunities, to answer three questions about Australia’s 21 largest cities: (1) What percentage of workers currently commute to their workplace within 30 min? (2) If workers were to shift to an active transport mode, what percent could reach their current workplace within 30 min? and (3) If it were possible to relocate workers closer to their employment or relocate employment closer to their home, what percentage could reach work within 30 min by each mode? Active transport usage in Australia is low, with public transport, walking, and cycling making up 16.8%, 2.8%, and 1.1% respectively of workers’ commutes. Cycling was found to have the most potential for achieving the 30 min city, with an estimated 29.5% of workers able to reach their current workplace were they to shift to cycling. This increased to 69.1% if workers were also willing and able to find a similar job closer to home, potentially reducing commuting by private motor vehicle from 79.3% to 30.9%.

Hydrochemical and Stable Isotope Analyses Show Limited Interactions Between Groundwater and Lake Water in the Lake Bosomtwi Impact Crater, Ghana.

The relationship between groundwater and surface water in the Lake Bosumtwi impact crater has been assessed using hydrochemical data and stable water isotopes of δ18O and δD. This study aimed to define likely groundwater flow and recharge zones, estimate the rate of evaporation, and examine the relationship between the lake and groundwater in the study area. The results of Q-Mode hierarchical cluster analysis (HCA) clearly differentiate the lake water from the groundwater based on their spatial relationship. These preliminary results indicated that groundwater recharge occurs on the hilltops of the crater, where it is slightly acidic with low levels of dissolved minerals, characterized by short residence time and rapid unrestricted vertical infiltration and recharge. The groundwater becomes more mineralized with longer contact times and deeper circulation with the host rock, while it flows from the recharge areas towards the lake at lower elevations. Analyses of stable water isotopes of δ18O and δD showed a high evaporation rate on the lake surface, of ~90% with a relatively significant evaporative enrichment, whereas groundwater showed a relatively lower evaporation rate ranging between 54-60%. Both reservoirs do not appear to be hydraulically connected, and where such a connection exists, it is expected to favour the lake.

Is It Possible to Perform Fifth Carpometacarpal Joint Arthroscopy? Cadaveric Study on Its Feasibility, Safety, and Potential Hazards in Portal Creation

Background Fifth carpometacarpal joint (CMCJ) fracture dislocation is a relatively rare injury and most will require operative treatment because of its unstable nature. Improper reduction and fixation lead to joint surface destruction, pain, and reduced grasping power. Intra-articular fragment reduction is often obscured by dorsally displaced ulnar fragment. Therefore, fifth CMCJ arthroscopy can be advantageous in assisting intra-articular fragment reduction. However, there is no detailed description of the portal landmarks or portals' relationship with adjacent important structures in the literature. Purposes To explore the feasibility and safety of fifth CMCJ arthroscopy, locations of the portals are examined in cadaveric hand specimens. Their proximity to important anatomical structures such as dorsal cutaneous branch of ulnar nerve (DCBUN), ring finger and little finger extensor digitorum communis (EDC), and extensor digiti minimi (EDM) is measured. Methods Fifth CMCJ arthroscopy is performed on 11 cadaveric hand specimens by specialist-level surgeon. The portals are marked and portal positions are further confirmed under the fluoroscopy. Then the cadaveric specimens were undergone anatomical dissection by specialist-level surgeon. During dissection, the spatial relationship between the portal positions and DCBUN, EDC to ring finger and little finger, and EDM is identified. The distance between the portals and the above important structures was measured in millimeters. Results DCBUN was consistently found between fourth metacarpohamate (4-MH) and fifth metacarpohamate (5-MH) portals, with it being closer to the latter (mean distance, 2.03 mm; range, 0–4.43 mm; standard deviation [SD], 1.09 mm). The closest tendon for 4-MH portal is ring finger EDC (mean distance, 2.65 mm; range, 0–5.89 mm; SD, 1.78 mm), while 5-MH portal and accessory portal were closest to EDC (mean distance, 1.88 mm; range, 0–3.69 mm; SD, 1.25 mm) and EDM (mean distance, 7.79 mm; range, 6.63–10.72 mm; SD, 1.49 mm), respectively. During the process of specimen dissection, we found no damage to the above structures after portal introduction. Conclusion The above findings support the use of fifth CMCJ arthroscopy, which can be used for assisted reduction in fifth metacarpal base fracture dislocation and hamate body fracture. Gentle soft tissue spreading technique during portal creation prevents injury to the important structure surrounding the portals. Level of evidence This is a Level V study.

Small but visible: Predicting rare bryophyte distribution and richness patterns using remote sensing-based ensembles of small models

In Canadian boreal forests, bryophytes represent an essential component of biodiversity and play a significant role in ecosystem functioning. Despite their ecological importance and sensitivity to disturbances, bryophytes are overlooked in conservation strategies due to knowledge gaps on their distribution, which is known as the Wallacean shortfall. Rare species deserve priority attention in conservation as they are at a high risk of extinction. This study aims to elaborate predictive models of rare bryophyte species in Canadian boreal forests using remote sensing-derived predictors in an Ensemble of Small Models (ESMs) framework. We hypothesize that high ESMs-based prediction accuracy can be achieved for rare bryophyte species despite their low number of occurrences. We also assess if there is a spatial correspondence between rare and overall bryophyte richness patterns. The study area is located in western Quebec and covers 72,292 km2. We selected 52 bryophyte species with <30 occurrences from a presence-only database (214 species, 389 plots in total). ESMs were built from Random Forest and Maxent techniques using remote sensing-derived predictors related to topography and vegetation. Lee’s L statistic was used to assess and map the spatial relationship between rare and overall bryophyte richness patterns. ESMs yielded poor to excellent prediction accuracy (AUC > 0.5) for 73% of the modeled species, with AUC values > 0.8 for 19 species, which confirmed our hypothesis. In fact, ESMs provided better predictions for the rarest bryophytes. Likewise, our study revealed a spatial concordance between rare and overall bryophyte richness patterns in different regions of the study area, which have important implications for conservation planning. This study demonstrates the potential of remote sensing for assessing and making predictions on inconspicuous and rare species across the landscape and lays the basis for the eventual inclusion of bryophytes into sustainable development planning.

Unveiling the Experience of IZTECH

Izmir Institute of Technology (IZTECH), a university campus located in a rural area, establishes a different social and spatial relationship with the city and its immediate surroundings. This chapter focuses on assessing the socio-spatial sustainability of the campus before and during the pandemic, together with the evaluation of UI GreenMetric World University Rankings (GreenMetric). The study has the basis of the content analysis of IZTECH GreenMetric evaluations and a critical review of sustainability issues through questionnaire technique applied to campus users, including administrative, academic staff, and students at IZTECH. The multidimensional survey has been designed to grasp the perspectives of the campus users on the sustainability performance of the campus, and to gather some intangible data on the COVID-19 period and its impacts on the use of campus spaces. In conclusion, this chapter is going to suggest a road map to guide sustainability measures of campuses for more adaptable and resilient solutions under unexpected circumstances.

An Object-Based Markov Random Field with Partition-Global Alternately Updated for Semantic Segmentation of High Spatial Resolution Remote Sensing Image

The Markov random field (MRF) method is widely used in remote sensing image semantic segmentation because of its excellent spatial (relationship description) ability. However, there are some targets that are relatively small and sparsely distributed in the entire image, which makes it easy to misclassify these pixels into different classes. To solve this problem, this paper proposes an object-based Markov random field method with partition-global alternately updated (OMRF-PGAU). First, four partition images are constructed based on the original image, they overlap with each other and can be reconstructed into the original image; the number of categories and region granularity for these partition images are set. Then, the MRF model is built on the partition images and the original image, their segmentations are alternately updated. The update path adopts a circular path, and the correlation assumption is adopted to establish the connection between the label fields of partition images and the original image. Finally, the relationship between each label field is constantly updated, and the final segmentation result is output after the segmentation has converged. Experiments on texture images and different remote sensing image datasets show that the proposed OMRF-PGAU algorithm has a better segmentation performance than other selected state-of-the-art MRF-based methods.

Identification of Cell-Type-Specific Spatially Variable Genes Accounting for Excess Zeros

Spatial transcriptomic techniques can profile gene expressions while retaining the spatial information, thus offering unprecedented opportunities to explore the relationship between gene expression and spatial locations. The spatial relationship may vary across cell types, but there is a lack of statistical methods to identify cell-type-specific spatially variable (SV) genes by simultaneously modeling excess zeros and cell-type proportions. We develop a statistical approach CTSV to detect cell-type-specific SV genes. CTSV directly models spatial raw count data and considers zero-inflation as well as overdispersion using a zero-inflated negative binomial distribution. It then incorporates cell-type proportions and spatial effect functions in the zero-inflated negative binomial regression framework. The R package pscl (Zeileis et al., 2008) is employed to fit the model. For robustness, a Cauchy combination rule is applied to integrate p-values from mutliple choices of spatial effect functions. Simulation studies show that CTSV not only outperforms the competing methods at the aggregated level but also achieves more power at the cell-type level. By analyzing pancreatic ductal adenocarcinoma spatial transcriptomic data, SV genes identified by CTSV reveal meaningful biological insights at the cell-type level. The R package to implement CTSV is available on GitHub https://github.com/jingeyu/CTSV.

Automatic update method of GIS platform drawing model based on machine learning

Aiming at the problem that the number of data bytes in the traditional automatic update technology of GIS platform is small, a method of automatic update of GIS platform graph model based on machine learning is studied. Firstly, the data of the GIS platform model is convolved by the iso-linear feature detection operator in the automatic updating technology of the GIS platform model, and the calculated data of the GIS platform model is expressed as spatial data. A reasonable updating criterion is established, the spatial relationship of GSI data is reconstructed by the measure of updating criterion, the data vector of GIS platform model updated within the updating time range is calculated, and the regional data elements in the space are constantly changed to complete the data updating of GIS platform model. The experimental results show that compared with the automatic updating method of GIS platform model, the proposed method can update more data bytes with the same number of data bytes.