eCall ROAD MAP IMPLEMENTATION STUDY

eCall is an emergency call either generated manually by vehicle occupants or automatically via activation of in-vehicle sensors when an accident occurs. When activated, the in-vehicle eCall system establishes a 112-voice connection directly with the relevant PSAP (Public Safety Answering Point), which is a public authority or a private eCall centre that operates under the regulation and/or authorisation of a public body.eCall, European eCall Implementation Platform, National eCall Implementation

Fuzzy clustering with spatial-temporal information

Clustering geographical units based on a set of quantitative features observed at several time occasions requires to deal with the complexity of both space and time information. In particular, one should consider (1) the spatial nature of the units to be clustered, (2) the characteristics of the space of multivariate time trajectories, and (3) the uncertainty related to the assignment of a geographical unit to a given cluster on the basis of the above com- plex features. This paper discusses a novel spatially constrained multivariate time series clustering for units characterised by different levels of spatial proximity. In particular, the Fuzzy Partitioning Around Medoids algorithm with Dynamic Time Warping dissimilarity measure and spatial penalization terms is applied to classify multivariate Spatial-Temporal series. The clustering method has been theoretically presented and discussed using both simulated and real data, highlighting its main features. In particular, the capability of embedding different levels of proximity among units, and the ability of considering time series with different length

A spatio-temporal geodatabase of mortalities due to respiratory tract diseases in Tehran, Iran between 2008 and 2018: a data note

Objectives Respiratory tract diseases (RTDs) are among the top five leading causes of death worldwide. Mortality rates due to respiratory tract diseases (MRRTDs) follow a spatial pattern and this may suggest a potential link between environmental risk factors and MRRTDs. Spatial analysis of RTDs mortality data in an urban setting can provide new knowledge on spatial variation of potential risk factors for RTDs. This will enable health professionals and urban planners to design tailored interventions. We aim to release the datasets of MRRTDs in the city of Tehran, Iran, between 2008 and 2018. Data description The Research data include four datasets; (a) mortality dataset which includes records of deaths and their attributes (age, gender, date of death and district name where death occurred), (b) population data for 22 districts (age groups with 5 years interval and gender by each district). Furthermore, two spatial datasets about the city are introduced; (c) the digital boundaries of districts and (d) urban suburbs of Tehran

Monitoring Urban Sprawl and Sustainable Urban Development Using the Moran Index: A Case Study of Stellenbosch, South Africa

Abstract: The management of urban sprawl is fundamental to achieving sustainable urban development. Monitoring urban sprawl is, however, challenging. This study proposes the use of two spatial statistics, namely global Moran and local Moran to indentify statistically significant urban sprawl hot and cold spots. The findings reveal that the Moran indexes are sensitive to the distance band spatial weight matrices employed and that multiple bands should be used when these indexes are used. The authors demonstrate how the indexes can be used in combination with various visualisation methods to support planning decisions

The development of passive health surveillance by a sentinel network of family practitioners in South Africa

Objective. For the South African Sentinel Practitioner Research Network (SASPREN), a volunteer network of family practitioners in South Africa, to develop a health surveillance system through the surveillance of important health events.Motivation. The incidence of important preventable diseases and the burden of disease are not reliably known in South Africa, both in the public and private sector. Incidence rates determined at primary care level could help with planning and delivery of appropriate health services and monitoring of the impact of intervention programmes.Methods. Altogether 183 sentinel practitioners were recruited in nine provinces, from 2 478 doctors invited to participate. Of these 120 were active in reporting all their new cases of 13 selected health events to the study centre on mailed postcards. After data-capturing, incidence rates were calculated for defined periods. Feedback was given to the sentinels through a newsletter and personalised reports.Results. A network of sentinel family practitioners has been established in South Africa, and can provide incidence rates for both diseases and interventions through a simple and cheap surveillance system. The calculated rates demonstrated periodic trends for certain events, as well as inter-provincial, -gender and -population group differences.Conclusions. As the validity of the dataset and its generalisation to the whole population is uncertain, its usefulness as point estimates of incidence rates isunknown. This information serves as an important pointer for further research. The trends of these rates may provide a valuable tool for monitoring the impact of public health policies

Mapping the Evolution of "Clusters": A Meta-analysis

This paper presents a meta-analysis of the “cluster literature” contained in scientific journals from 1969 to 2007. Thanks to an original database we study the evolution of a stream of literature which focuses on a research object which is both a theoretical puzzle and an empirical widespread evidence. We identify different growth stages, from take-off to development and maturity. We test the existence of a life-cycle within the authorships and we discover the existence of a substitutability relation between different collaborative behaviours. We study the relationships between a “spatial” and an “industrial” approach within the textual corpus of cluster literature and we show the existence of a “predatory” interaction. We detect the relevance of clustering behaviours in the location of authors working on clusters and in measuring the influence of geographical distance in co-authorship. We measure the extent of a convergence process of the vocabulary of scientists working on clusters.Cluster, Life-Cycle, Cluster Literature, Textual Analysis, Agglomeration, Co-Authorship

Prediction of spatial distribution for some land use allometric characteristics in land use planning models with geostatistic and Geographical Information System (GIS) (Case study: Boein and Miandasht, Isfahan Province, Iran)

Although traditional census can present unbiased information about different land uses, it is spatial independent and do not present particular  information about spatial distribution of studied characteristic. In this study, we used geostatistic and Geographical Information System (GIS) to estimate some different land uses allometric characteristics in Isfahan Province (Iran). Thus, samples information was surveyed considering their geographic position in the studied area. After optimizing variogram parameters,  empirical variogram was prepared to investigate spatial structure of different land uses allometric characteristics. Our results confirme that spatial  structure for the quantitative characteristics of different land uses has a moderate degree of spatial correlation, except for type variable that has no spatial structure. Nugget effect for variogram obtained from the quantitative characteristics of different land uses was equal to 35 to 64%. We used ordinary Kriging for preparing Kriging map and Kriging standard deviation of different land uses. Also, we used geostatistic and GIS to compare geostatistical and algebraic interpolation methods and nine different interpolation methods (Kriging, local polynomial methods, inverse distance weighted, radial basis functions, global polynomial, moving average  weighted, natural neighbor, nearest neighbor and triangulation with Linear Interpolation) were investigated. Spatial distribution of different land uses quantitative characteristics were validated with ordinary Kriging and algebraic methods. Our results confirm that ordinary Kriging has more accuracy than other methods for spatial prediction of different land uses quantitative characteristics.Key words: Geostatistic, interpolation method, land use allometric  characteristics, Kriging

Genetic diversity of Epimedium elatum (Morren & Decne) revealed by RAPD characterization

Epimedium elatum (Morren & Decne) is a rare perennial monotypic medicinal herb of Berberidaceae family, endemic to high altitude shady coniferous forests of Northwestern Himalayas in India. Traditionally, it has been used in local health care system for treatment of many ailments. In the present study, a total of ten RAPD markers were used for assessment of genetic diversity in twenty accessions of E. elatum, collected from diverse ecozones in Jammu and Kashmir. Ten primers amplified a total of 100 polymorphic bands with average of 10 bands per assay unit. Primer OPO-07 generated maximum number of bands (15) & produced highest polymorphic information content (0.39), marker index (5.96) and resolving power (8.9), thereby distinguishing E. elatum genotypes. The study showed moderate level of genetic polymorphism in twenty accessions of E. elatum. RAPD data set revealed association between genetic diversity and eco-geographic distribution of most E. elatum genotypes, and thereby proved useful tool for their genetic/molecular characterization. There is an urgent need for developing quick conservation strategies to save its natural germplasm from extinction in the Northwestern Himalayas

Microreact: visualizing and sharing data for genomic epidemiology and phylogeography

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets