Challenging Methods and Results Obtained from User-Generated Content in Barcelona’s Public Open Spaces

User-generated content (UGC) provides useful resources for academics, technicians and policymakers to obtain and analyse results in order to improve lives of individuals in urban settings. User-generated content comes from people who voluntarily contribute data, information, or media that then appears in a way which can be viewed by others; usually on the Web. However, to date little is known about how complex methodologies for getting results are subject to methodology-formation errors, personal data protection, and reliability of outcomes. Different researches have been approaching to inquire big data methods for a better understanding of social groups for planners and economic needs. In this chapter, through UGC from Tweets of users located in Barcelona, we present different research experiments. Data collection is based on the use of REST API; while analysis and representation of UGC follow different ways of processing and providing a plurality of information. The first objective is to study the results at a different geographical scale, Barcelona’s Metropolitan Area and at two Public Open Spaces (POS) in Barcelona, Enric Granados Street and the area around the Fòrum de les Cultures; during similar days in two periods of time - in January of 2015 and 2017. The second objective is intended to better understand how different types of POS’ Twitter-users draw urban patterns. The Origin-Destination patterns generated illustrate new social behaviours, addressed to multifunctional uses. This chapter aims to be influential in the use of UGC analysis for planning purposes and to increase quality of life

GIS and spatial data analysis: Converging perspectives

We take as our starting point the state of geographic information systems (GIS) and spatial data analysis 50 years ago when regional science emerged as a new field of enquiry. In the late 1950s and 1960s advances in computing technology were making possible forms of automated cartography that in due course would lead to th

Mapping nitrate leaching to upper groundwater in the sandy regions of The Netherlands, using conceptual knowledge

The European Community asks its Member States to provide a comprehensive and coherent overview of their groundwater chemical status. It is stated that simple conceptual models are necessary to allow assessments of the risks of failing to meet quality objectives. In The Netherlands two monitoring networks (one for agriculture and one for nature) are operational, providing results which can be used for an overview. Two regression models, based upon simple conceptual models, link measured nitrate concentrations to data from remote sensing images of land use, national forest inventory, national cattle inventory, fertiliser use statistics, atmospheric N deposition, soil maps and weather monitoring. The models are used to draw a nitrate leaching map and to estimate the size of the area exceeding the EU limit value in the early 1990s. The 95% confidence interval for the fraction nature and agricultural areas where the EU limit value for nitrate (50 mg/l) was exceeded amounted to 0.77–0.85 while the lower 97.5% confidence limit for the fraction agricultural area where the EU limit value was exceeded amounted to 0.94. Although the two conceptual models can be regarded as simple, the use of the models to give an overview was experienced as complex

Exploratory spatial data analysis for the identification of risk factors to birth defects

BACKGROUND: Birth defects, which are the major cause of infant mortality and a leading cause of disability, refer to "Any anomaly, functional or structural, that presents in infancy or later in life and is caused by events preceding birth, whether inherited, or acquired (ICBDMS)". However, the risk factors associated with heredity and/or environment are very difficult to filter out accurately. This study selected an area with the highest ratio of neural-tube birth defect (NTBD) occurrences worldwide to identify the scale of environmental risk factors for birth defects using exploratory spatial data analysis methods. METHODS: By birth defect registers based on hospital records and investigation in villages, the number of birth defects cases within a four-year period was acquired and classified by organ system. The neural-tube birth defect ratio was calculated according to the number of births planned for each village in the study area, as the family planning policy is strictly adhered to in China. The Bayesian modeling method was used to estimate the ratio in order to remove the dependence of variance caused by different populations in each village. A recently developed statistical spatial method for detecting hotspots, Getis's [Image: see text] [7], was used to detect the high-risk regions for neural-tube birth defects in the study area. RESULTS: After the Bayesian modeling method was used to calculate the ratio of neural-tube birth defects occurrences, Getis's [Image: see text] statistics method was used in different distance scales. Two typical clustering phenomena were present in the study area. One was related to socioeconomic activities, and the other was related to soil type distributions. CONCLUSION: The fact that there were two typical hotspot clustering phenomena provides evidence that the risk for neural-tube birth defect exists on two different scales (a socioeconomic scale at 6.84 km and a soil type scale at 22.8 km) for the area studied. Although our study has limited spatial exploratory data for the analysis of the neural-tube birth defect occurrence ratio and for finding clues to risk factors, this result provides effective clues for further physical, chemical and even more molecular laboratory testing according to these two spatial scales

Local spatial regression models : a comparative analysis on soil contamination

Spatial data analysis focuses on both attribute and locational information. Local analyses deal with differences across space whereas global analyses deal with similarities across space. This paper addresses an experimental comparative study to analyse the spatial data by some weighted local regression models. Five local regression models have been developed and their estimation capacities have been evaluated. The experimental studies showed that integration of objective function based fuzzy clustering to geostatistics provides some accurate and general models structures. In particular, the estimation performance of the model established by combining the extended fuzzy clustering algorithm and standard regional dependence function is higher than that of the other regression models. Finally, it could be suggested that the hybrid regression models developed by combining soft computing and geostatistics could be used in spatial data analysis

Graph Regionalization with Clustering and Partitioning: an Application for Daily Commuting Flows in Albania

The paper presents an original application of the recently proposed spatial data mining method named GraphRECAP on daily commuting flows using 2011 Albanian census data. Its aim is to identify several clusters of Albanian municipalities/communes; propose a classification of the Albanian territory based on daily commuting flows among municipalities/communes. Starting from 373 local units, we first applied a spatial clustering technique without imposing any constraining strategy. Based on the input variables, we obtained 16 clusters. In the second step of our analysis, we impose a set of constraining parameters to identify intermediate areas between the local level (municipality/commune) and the national one. We have defined 12 derived regions (same number as the actual Albanian prefectures but with different geographies). These derived regions are quite different from the traditional ones in terms of both geographical dimensions and boundarie

Distinct and shared functions of ALS-associated proteins TDP-43, FUS and TAF15 revealed by multisystem analyses

The RNA-binding protein (RBP) TAF15 is implicated in amyotrophic lateral sclerosis (ALS). To compare TAF15 function to that of two ALS-associated RBPs, FUS and TDP-43, we integrate CLIP-seq and RNA Bind-N-Seq technologies, and show that TAF15 binds to ∼4,900 RNAs enriched for GGUA motifs in adult mouse brains. TAF15 and FUS exhibit similar binding patterns in introns, are enriched in 3′ untranslated regions and alter genes distinct from TDP-43. However, unlike FUS and TDP-43, TAF15 has a minimal role in alternative splicing. In human neural progenitors, TAF15 and FUS affect turnover of their RNA targets. In human stem cell-derived motor neurons, the RNA profile associated with concomitant loss of both TAF15 and FUS resembles that observed in the presence of the ALS-associated mutation FUS R521G, but contrasts with late-stage sporadic ALS patients. Taken together, our findings reveal convergent and divergent roles for FUS, TAF15 and TDP-43 in RNA metabolism.National Institutes of Health (U.S.) (Grant HG007005

A Bi-Functional Anti-Thrombosis Protein Containing Both Direct-Acting Fibrin(ogen)olytic and Plasminogen-Activating Activities

Direct-acting fibrin(ogen)olytic agents such as plasmin have been proved to contain effective and safety thrombolytic potential. Unfortunately, plasmin is ineffective when administered by the intravenous route because it was neutralized by plasma antiplasmin. Direct-acting fibrin(ogen)olytic agents with resistance against antiplasmin will brighten the prospect of anti-thrombosis. As reported in ‘Compendium of Materia Medica’, the insect of Eupolyphaga sinensis Walker has been used as traditional anti-thrombosis medicine without bleeding risk for several hundreds years. Currently, we have identified a fibrin(ogen)olytic protein (Eupolytin1) containing both fibrin(ogen)olytic and plasminogen-activating (PA) activities from the beetle, E. sinensis. Objectives: To investigate the role of native and recombinant eupolytin1 in fibrin(ogen)olytic and plasminogen-activating processes. Methods and Results: Using thrombus animal model, eupolytin1 was proved to contain strong and rapid thrombolytic ability and safety in vivo, which are better than that of urokinase. Most importantly, no bleeding complications were appeared even the intravenous dose up to 0.12 µmol/kg body weight (3 times of tested dose which could completely lyse experimental thrombi) in rabbits. It is the first report of thrombolytic agents containing both direct-acting fibrin(ogen)olytic and plasminogen-activating activities. Conclusions: The study identified novel thrombolytic agent with prospecting clinical potential because of its bi-functional merits containing both plasmin- and PA-like activities and unique pharmacological kinetics in vivo