Methodology for testing and validating knowledge bases

A test and validation toolset developed for artificial intelligence programs is described. The basic premises of this method are: (1) knowledge bases have a strongly declarative character and represent mostly structural information about different domains, (2) the conditions for integrity, consistency, and correctness can be transformed into structural properties of knowledge bases, and (3) structural information and structural properties can be uniformly represented by graphs and checked by graph algorithms. The interactive test and validation environment have been implemented on a SUN workstation

Challenges and implications of routine depression screening for depression in chronic disease and multimorbidity: a cross sectional study

<b>Background</b> Depression screening in chronic disease is advocated but its impact on routine practice is uncertain. We examine the effects of a programme of incentivised depression screening in chronic disease within a UK primary care setting.<p></p> <b>Methods and Findings</b> Cross sectional analysis of anonymised, routinely collected data (for 2008-9) from family practices in Scotland serving a population of circa 1.8 million. Patients registered in primary care with at least one of three chronic diseases, coronary heart disease, diabetes and stroke, underwent incentivised depression screening using the Hospital Anxiety and Depression Score (HADS). <p></p> 125143 patients were identified with at least one chronic disease. 10670 (8.5%) were under treatment for depression and exempt from screening. Of the remaining, HADS were recorded for 35537 (31.1%) patients. 7080 (19.9% of screened) had raised HADS (≥8); the majority had indications of mild depression with a HADS between 8 and 10. Over 6 months, 572 (8%) of those with a raised HADS (≥8) were initiated on antidepressants, while 696 (2.4%) patients with a normal HADS (<8) were also initiated on antidepressants (relative risk of antidepressant initiation with raised HADS 3.3 (CI 2.97-3.67), p value <0.0001). Of those with multimorbidity who were screened, 24.3% had a raised HADS (≥8). A raised HADS was more likely in females, socioeconomically deprived, multimorbid or younger (18-44) individuals. Females and 45-64 years old were more likely to receive antidepressants.<p></p> <b>Limitations</b> – retrospective study of routinely collected data.<p></p> <b>Conclusions </b> Despite incentivisation, only minority of patients underwent depression screening, suggesting that systematic depression screening in chronic disease can be difficult to achieve in routine practice. Targeting those at greatest risk such as the multimorbid or using simpler screening methods may be more effective. Raised HADS was associated with a higher number of new antidepressant prescriptions which has significant resource implications. The clinical benefits of such screening remain uncertain and merit investigation

Where to improve cycling infrastructure? Assessing bicycle suitability and bikeability with open data in the city of Paris

This study proposes a method that can help in identifying potential locations for improvements of cycling infrastructures. It addresses the need for simple and effective methods to support decision-making in bicycle planning. The city of Paris is used as a case study area because it has made considerable efforts to improve cycling infrastructures and to become more bicycle-friendly in recent years. The method (1) identifies potential locations for improvements of bicycle infrastructures on a street level and (2) on a city level considering accessibility to important destinations. The main data used in this project is street data from OpenStreetMap (OSM) and cycling infrastructure data from the Atelier parisien d’urbanisme (Apur). The proposed method can be applied with commonly available data, has clear outcomes, is reproducible, and can be applied to different case study areas. We produced a map of bicycle suitability across all of Paris, and validated it for the 30 longest segments in the city with lower bike suitability. Our validation showed that combining OSM and Apur data led to a reliable dataset, with which we modelled bikeability using the underlying network overlain on a 250 m resolution grid and destinations representing leisure activities, education, shopping, city functions and public transport. The resulting map identifies regions of the city with poor bikeability, where improvements to cycling infrastructure should be investigated

Effects of traffic perturbations on bike sharing demand – a case study of public transport strikes and protests in Paris

This paper aims to contribute to a better understanding of the interactions between traffic perturbations and bike sharing use. More specifically we propose a framework for comparative spatial temporal analyses of public transport strikes and massive protests effects on bike sharing program in Paris. We find opposite effects on bike sharing demand due to public transport strikes and protests. The former causes a considerable rise in bike sharing demand particularly during the daily rush hours, while the latter precipitates a drop of activity constantly during the protest day. Our approach allows tracing bike sharing demand changes induced by traffic perturbations on an hourly level

Inferring Amazon leaf demography from satellite observations of leaf area index

Seasonal and year-to-year variations in leaf cover imprint significant spatial and temporal variability on biogeochemical cycles, and affect land-surface properties related to climate. We develop a demographic model of leaf phenology based on the hypothesis that trees seek an optimal leaf area index (LAI) as a function of available light and soil water, and fit it to spaceborne observations of LAI over the Amazon basin, 2001–2005. We find the model reproduces the spatial and temporal LAI distribution whilst also predicting geographic variation in leaf age from the basin centre (2.1 ± 0.2 years), through to the lowest values over the deciduous eastern and southern Amazon (6 ± 2 months). The model explains the observed increase in LAI during the dry season as a net addition of leaves in response to increased solar radiation. We anticipate our work to be a starting point from which to develop better descriptions of leaf phenology to incorporate into more sophisticated earth system models

Window Expeditions: A playful approach to crowdsourcing natural language descriptions of everyday lived landscapes

Measuring what citizens perceive and value about landscapes is important for landscape monitoring. Capturing temporal, spatial and cultural variation requires collection of data at scale. One potential proxy data source are textual descriptions of landscapes written by volunteers. We implemented a gamified application and crowdsourced a multilingual corpus of in-situ descriptions of everyday lived landscapes. Our implementation focused on the aesthetics of exploration, expression and fellowship in the mechanics, dynamics, aesthetics (MDA) framework. We collected 503 natural language landscape descriptions from 384 participants in English (69.7%), German (25.1%) and French (5.3%) and most contributions were made in urban areas (54.7%). The most frequent noun lemma in English was “tree” and in German “Fenster” (window). By comparing our English collection to corpora of everyday English and landscape descriptions, we identified frequent lemmas such as “tree”, “window”, “light”, “street”, “garden” and “sky” which occurred significantly more than expected. These terms hint as to important components of the everyday landscapes of our users. We suggest a number of ways in which our corpus could be used in ongoing research on landscapes, complementing existing PPGIS approaches, providing data for domain specific lexicons for landscape analysis and as an input to landscape character assessment

Identifying landscape relevant natural language using actively crowdsourced landscape descriptions and sentence-transformers

Natural language has proven to be a valuable source of data for various scientific inquiries including landscape perception and preference research. However, large high quality landscape relevant corpora are scare. We here propose and discuss a natural language processing workflow to identify landscape relevant documents in large collections of unstructured text. Using a small curated high quality collection of actively crowdsourced landscape descriptions we identify and extract similar documents from two different corpora (Geograph and WikiHow) using sentence-transformers and cosine similarity scores. We show that 1) sentence-transformers combined with cosine similarity calculations successfully identify similar documents in both Geograph and WikiHow effectively opening the door to the creation of new landscape specific corpora, 2) the proposed sentence-transformer approach outperforms traditional Term Frequency - Inverse Document Frequency based approaches and 3) the identified documents capture similar topics when compared to the original high quality collection. The presented workflow is transferable to various scientific disciplines in need of domain specific natural language corpora as underlying data

Characterising and mapping potential and experienced tranquillity : From a state of mind to a cultural ecosystem service

Funding Information: Many thanks to Graeme Willis (Campaign to Protect Rural England) and Nick Groome (Ordnance Survey) for their help in accessing the National Tranquillity Mapping Data. We would like to thank all the contributors to Geograph British Isles (Creative Commons Attribution-ShareAlike 2.5 License) whose contributions were used to map tranquil and silent locations in the Lake District.Peer reviewedPublisher PD

Investigating sense of place as a cultural ecosystem service in different landscapes through the lens of language

We are grateful for the comments and feedback of three anonymous reviewers. We thank Olga Chesnokova for her help in calculating cosine similarity measures. The research on which this paper is based was financially supported by the cogito foundation through the project ‘How language shapes our sense of place’, grant no. 15-129-R.Peer reviewedPublisher PD

‘This is not the jungle, this is my barbecho’ : semantics of ethnoecological landscape categories in the Bolivian Amazon

This work was supported from the ‘Forschungskredit’ by the University of Zurich [grant number FK-13-104]; Hans Vontobel Foundation; Maya Behn-Eschenburg Foundation; Ormella Foundation; and Parrotia Foundation.Peer reviewedPublisher PD