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There are many multiple-stage racing competitions in various sports such as swimming, running, or cycling. The wide availability of affordable tracking devices facilitates monitoring the position along with the race of all participants, even for non-professional contests. Getting real-time information of contenders is useful but also unleashes the possibility of creating more complex visualization systems that ease the understanding of the behavior of all participants during a simple stage or throughout the whole competition. In this paper we focus on bicycle races, which are highly popular, especially in Europe, being the Tour de France its greatest exponent. Current visualizations from TV broadcasting or real-time tracking websites are useful to understand the current stage status, up to a certain extent. Unfortunately, still no current system exists that visualizes a whole multi-stage contest in such a way that users can interactively explore the relevant events of a single stage (e.g. breakaways, groups, virtual leadership...), as well as the full competition. In this paper, we present an interactive system that is useful both for aficionados and professionals to visually analyze the development of multi-stage cycling competitions. This work has been supported in part by project TIN2017-88515-C2-1-R(GEN3DLIVE), from the Spanish Ministerio de Economía y Competitividad, by 839 FEDER (EU) funds and by the Grant No. PID2019-106426RB-C31 / AEI / 10.13039/501100011033 from the Spanish Government.

The automatic generation of road networks from GPS tracks is a challenging problem that has been receiving considerable attention in the last years. Although dozens of methods have been proposed, current techniques suffer from two main shortcomings: the quality of the produced road networks is still far from those produced manually, and the methods are slow, making them not scalable to large inputs. In this paper, we present a fast four-step density-based approach to construct a road network from a set of trajectories. A key aspect of our method is the use of an improved version of the Slide method to adjust trajectories to build a more compact density surface. The network has comparable or better quality than that of state-of-the-art methods and is simpler (includes fewer nodes and edges). Furthermore, we also propose a split-and-merge strategy that allows splitting the data domain into smaller regions that can be processed independently, making the method scalable to large inputs. The performance of our method is evaluated with extensive experiments on urban and hiking data This work was supported by the Spanish Government under Grants PID2019- 106426RB-C31 and PID2019-104129GB-I00/AEI/10.13039/501100011033; the Catalan Government under grants 2017-SGR-1101 and 2017-SGR-1640; the Universitat de Girona under grant PONTUdG2019/11; and the Chinese Academy of Sciences President’s International Fellowship Initiative under grant 2021VTB0004. Yuejun Guo acknowledges the support from Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya and the European Social Fund

The computation of the intersection family of two large families of unsorted sets is an interesting problem from the mathematical point of view which also appears as a subproblem in decision making applications related to market research or temporal evolution analysis problems. The problem of intersecting two families of sets F and F is to find the family I of all the sets which are the intersection of some set of F and some other set of F. In this paper, we present an efficient parallel GPU-based approach, designed under CUDA architecture, to solve the problem. We also provide an efficient parallel GPU strategy to summarize the output by removing the empty and duplicated sets of the obtained intersection family, maintaining, if necessary, the sets frequency. The complexity analysis of the presented algorithm together with experimental results obtained with its implementation is also presented. We present a GPU-parallel algorithm to find the intersection family of 2 big families of small sets.We extract information from the intersection family eliminating the empty and repeated sets.We present the theoretical complexity analysis of the presented algorithm.We provide experimental results showing the scalability and robustness of the parallel strategy.

We provide an approach to solve the problem of locating a disk so that its overlap area with a piecewise circular domain is near-optimal when considering partial converage. To this purpose, we introduce the concept of overlap area map. Both, overlap area maps and near-optimal locations, provide useful tools for solving problems related to the placement, for example, of emergency warning sirens, cellular towers or radio receiving stations, that are commonly encountered in the location science field. We present parallel algorithms on graphics processing units (GPUs) for computing an overlap area map and obtaining a set of near-optimal locations from the overlap area map. These algorithms have as a key element the overlap area computation process to which we pay special attention. In addition, we describe a way of visualizing the obtained solutions. Integration of computation and visualization facilitates decision makers, with an iterative what-if-analysis process, to gain more information in order to facilitate the selection of an appropriate location. Finally, we also provide and discuss experimental results showing the efficiency and scalability of our approach Work partially funded by the Ajut per la millora de la productivitat científica/UdG/3/Ref. MPCUdG2016-031UdG52211-C2-2-R. We also acknowledge NVIDIA Corporation for the donation of the Tesla K40 GPU

In this paper we propose, motivate and solve multiple bichromatic mutual nearest neighbor queries in the plane considering multiplicative weighted Euclidean distances. Given two sets of facilities of different types, a multiple bichromatic mutual ( k , k ' ) -nearest neighbor query finds pairs of points, one of each set, such that the point of the first set is a k-nearest neighbor of the point of the second set and, at the same time, the point of the second set is a k ' -nearest neighbor of the point of the first set. These queries find applications in collaborative marketing and prospective data analysis, where facilities of one type cooperate with facilities of the other type to obtain reciprocal benefits. We present a sequential and a parallel algorithm, to be run on the CPU and on a Graphics Processing Unit, respectively, for solving multiple bichromatic mutual nearest neighbor queries. We also present the time and space complexity analysis of both algorithms, together with their theoretical comparison. Finally, we provide and discuss experimental results obtained with the implementation of the proposed sequential and a parallel algorithm. HighlightsWe define and motivate multiple mutual bichromatic weighted nearest neighbor queries.We solve 2d multiple mutual nearest neighbor queries sequentially and parallelly.We theoretically analyze and compare the time and space complexity of both algorithms.We experimentally show the algorithms to be effective, robust and scalable.

We address the problem of tracking and detecting interactions between the different groups of runners that form during a race. In athletic races control points are set to monitor the progress of athletes over the course. Intuitively, a {\it group} is a sufficiently large set of athletes that cross a control point together. After adapting an existing definition of group to our setting we go on to study two types of group evolution patterns. The primary focus of this work are {\it evolution patterns}, i.e. the transformation and interaction of groups of athletes between two consecutive control points. We provide an accurate geometric model of the following evolution patterns: survives, appears, disappears, expands, shrinks, merges, splits, coheres and disbands, and present algorithms to efficiently compute these patterns. Next, based on the algorithms introduced for identifying evolution patterns, algorithms to detect {\it long-term patterns} are introduced. These patterns track global properties over several control points: surviving, traceable forward, traceable backward and related forward and backward. Experimental evaluation of the algorithms provided is presented using real and synthetic data. Using the data currently available, our experiments show how our algorithms can provide valuable insight into how running races develop. Moreover, we also show how, even if dense (synthetic) data is considered, our algorithms are also able to process it in real time.

Cobalt is an essential trace element but may cause toxic effects upon occupational or environmental exposure. Women accumulate more cobalt than men at similar exposure levels which may be related to higher metabolic iron loss. During pregnancy these losses are much stronger but their influence on cobalt intake has not been studied. We have studied the associations between changes in hemoglobin and cobalt urinary excretion during pregnancy. 391 pairs of urine and blood samples from pregnant women were collected during the 12th and 32nd weeks of pregnancy and were analyzed for cobalt and hemoglobin. Mean concentrations of urinary cobalt were 0.73 and 1.6. μg/g creatinine during the first and third trimesters, respectively (p, Financial support is acknowledged from projects: CROME-LIFE (LIFE12 ENV/GR/001040), HEALS (FP7-ENV-2013- 603946), Consolider-Ingenio GRACCIE (CSD2007-00067) and MARATO TV3 090431. Funding from Generalitat de Catalunya is also acknowledged (2009 SGR 1178).

Seafood consumption provides a significant amount of arsenic, although in its organic, nontoxic forms. Mediterranean populations may incorporate high levels of this metalloid as a consequence of seafood consumption. In the present study, the significance of this input among pregnant women from a Mediterranean city (Sabadell, Catalonia, Spain) is assessed. Total urinary arsenic was analyzed in 489 pairs of urine samples, corresponding to the 12th and 32 th weeks of pregnancy. Association of arsenic content with seafood and other dietary items were studied. Geometric mean concentrations were 34 and 37 μg/g creatinine during the first and third trimesters, respectively. The observed concentrations were similar to those reported in studies from other Mediterranean countries. The differences between both periods were not statistically significant. The only dietary factor significantly and positively associated with total urinary arsenic in both series of samples was seafood, particularly lean fish. Moreover, lean fish consumption during both periods was found to be the main determinant for differences in levels of arsenic between the first and third trimesters, which confirms the association between high levels of total urinary arsenic and seafood consumption.

Background: There is insufficient epidemiological evidence for deciding whether prenatal exposure to the current low-levels of metals in developed countries may affect neuropsychological function in early childhood. Objectives: Our goal was to evaluate potential neurotoxic effects of prenatal exposure to seven metals (cobalt, copper, arsenic, cadmium, antimony, thallium and lead), during the 1st and 3rd trimester of pregnancy, on child neuropsychological development at 4 years of age. Materials and methods: This study was based on a population-based birth cohort established in Sabadell (Catalonia, Spain) as part of the INMA [Environment and Childhood] Project. Metals were measured in 485 urine samples collected from mothers during the 1st and 3rd trimester of pregnancy. We assessed the neuropsychological development of 553 4-year-olds with the McCarthy Scales of Childrens' Abilitites (MSCA), together with their ADHD symptomatology, using the ADHD-DSM-IV criteria. A total of 385 children were included in the present study. Results: We found no statistically significant associations between metals and general cognitive scale or executive function of the MSCA. We found negative coefficients for the exposure to cadmium 1st trimester, cadmium 3rd trimester and lead 3rd trimester on the general cognitive score of MSCA, although these results were not significant. We did not find any association between prenatal exposure to metals and ADHD symptomatology at the age of 4 years. Conclusions: Our results do not suggest that prenatal exposure to current low-levels of metals impairs children's cognitive development during preschool years., a Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain b Universitat Pompeu Fabra, Barcelona, Spain c CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain d Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research, Barcelona, Catalonia, Spain e Institute for Risk Assessment Sciences, Division of Environmental Epidemiology, Utrecht University, Netherlands f Department of Environmental Health, Harvard School of Public Health, Boston, MA, United States g IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain

Background: There is increasing interest in the potential effects of polybrominated diphenyl ethers (PBDEs) on children’s neuropsychological development, but only a few small studies have evaluated such effects. Objectives: Our goal was to examine the association between PBDE concentrations in colostrum and infant neuropsychological development and to assess the influence of other persistent organic pollutants (POPs) on such association. Methods: We measured concentrations of PBDEs and other POPs in colostrum samples of 290 women recruited in a Spanish birth cohort. We tested children for mental and psychomotor development with the Bayley Scales of Infant Development at 12–18 months of age. We analyzed the sum of the seven most common PBDE congeners (BDEs 47, 99, 100, 153, 154, 183, 209) and each congener separately. Results: Increasing Σ7PBDEs concentrations showed an association of borderline statistical significance with decreasing mental development scores (β per log ng/g lipid = –2.25; 95% CI: –4.75, 0.26). BDE-209, the congener present in highest concentrations, appeared to be the main congener responsible for this association (β = –2.40, 95% CI: –4.79, –0.01). There was little evidence for an association with psychomotor development. After adjustment for other POPs, the BDE-209 association with mental development score became slightly weaker (β = –2.10, 95% CI: –4.66, 0.46). Conclusions: Our findings suggest an association between increasing PBDE concentrations in colostrum and a worse infant mental development, particularly for BDE-209, but require confirmation in larger studies. The association, if causal, may be due to unmeasured BDE-209 metabolites, including OH-PBDEs (hydroxylated PBDEs), which are more toxic, more stable, and more likely to cross the placenta and to easily reach the brain than BDE-209. This study was funded by grants from Instituto de Salud Carlos III (Red INMA G03/176, CB06/02/0041, FIS-PI06/0867, and FIS-PS09/00090), Spanish Ministry of Health (FIS-PI041436 and FIS- PI081151), Generalitat de Catalunya-CIRIT (1999SGR 00241), Department of Health of the Basque Government (2005111093 and 2009111069), the Provincial Government of Gipuzkoa (DFG06/004 and DFG08/001), and Fundación Roger Torné

Antimony and copper are common components of brake linings. The occurrence of these two metals in urban atmospheric aerosols has been related to vehicular use. Urine samples (n=466) taken during the 32nd week of pregnancy were analyzed for Sb and Cu in pregnant women from an urban area (Sabadell, Catalonia, Spain). The geometric mean levels were 0.28 and 13μg/g creatinine, respectively. Positive significant associations between urine concentrations of Sb and seasonality, intensity of physical exercise, working activities and traffic intensity at their home streets were observed. Cu showed the same trends but without statistical significance. In both cases, the estimated dietary ingestion of these two metals was larger than the inhalation inputs but the difference was much higher for Cu than for Sb. While Sb has no dietary role, Cu is an essential element which is also incorporated into humans through diet. The results suggest that inhalation of atmospheric particles may also constitute a source of Sb in pregnant women and general population of urban areas.

Introduction: The aims of the present study are to assess the temporal trends of organochlorine compounds (OCs) concentrations and total serum burdens from birth until adolescence and the influence of breastfeeding in these temporal trends. Methods: In 1997 two birth cohort studies were set up in Ribera d'Ebre (N=102) and the island of Menorca (N=482), Spain. Concentrations (ng/mL) of OCs [pentachlorobenzene (PeCB), four isomers of hexachlorocyclohexane (HCH), hexachlorobenzene (HCB), dichlorodiphenyltrichloroethane (4,4'-DDT), dichlorodiphenyldichloroethylene (4,4'-DDE) and seven polychlorobiphenyl congeners (σ7PCBs)] were measured in cord blood and at the age of 4 and 14years. The total serum burdens (ng) of these compounds were estimated based on the total blood volume (mL) of children at the different ages. We compared median concentrations and total serum burdens of these OCs at the different time-points of follow-up between children of Ribera d'Ebre and Menorca and between breastfed and non-breastfed children. Results: From birth until adolescence concentrations of all OCs drastically reduced. These reductions were mainly derived from the dilution of OCs, associated to an increase in total blood volume of children at the age of 4 and 14years. Despite the reduction in OCs concentrations, the total serum burdens of 4,4'-DDE and σ7PCBs, were higher in adolescents than at birth. Increases in OCs total serum burden occurred both in breastfed and non-breastfed children, but were significantly higher in the first. Conclusions: Even after decades of banning OCs production and use, current young generations in westernized countries are still bioaccumulating these compounds. Given the potential health effects of OCs, especial attention should be paid in the control of secondary emissions in the environment and in the control of food production and contamination. In countries with endemic malaria it is important to work towards effective alternatives to the use of DDT. © 2014 Elsevier Ltd., This study was supported by grants from the Spanish Ministry of Health (FIS-97/1102, FIS 97/0588, 00/0021-2, PI061756, PS0901958 and FIS PS09/00362), the Instituto de Salud Carlos III (Red INMA G03/176 and CB06/02/0041), Fundació La Caixa (97/009-00 and 00/077-00), and the Generalitat de Catalunya-CIRIT 1999SGR 00241. Finally, the authors would like to be grateful to the families in Flix and Menorca participating in the study, to the high school management team of Flix for their interest and collaboration, and to Rosa Maria Sabaté, the nurse of the health center of Flix, for her support and commitment.

Let P and F be sets of n ≥ 2 and m ≥ 2 points in a plane, respectively. We study the problem of finding the minimum angle α ϵ [2Π/m, 2Π] such that one can install at each point of F a stationary rotating floodlight with illumination angle α, initially oriented in a suitable direction, in such a way that, at all times, every target point of P is illuminated by at least one floodlight. All floodlights rotate clockwise at unit speed. We provide bounds for the case in which the elements of P ⋃ F are on a given line, and present exact results for the case in the plane in which we have two floodlights and many target points. We further consider the non-rotating version of the problem and look for the minimum angle α such that one can install a non-rotating floodlight with illumination angle α at each point of F, in such a way that every target point of P is illuminated by at least one floodlight. We show that this problem is NP-hard and hard to approximate.

In this paper we propose and solve multiple bichromatic mutual nearest neighbor queries in the plane considering multiplicative weighted Euclidean distances. These multiple queries are related to the mutual influence of two sets of facilities of different type, in which facilities of the first type cooperates with facilities of the second type in order to obtain reciprocal benefits. The studied problems find applications, for example, in collaborative marketing. We present a parallel algorithm, to be run on a Graphics Processing Unit, for solving multiple bichromatic mutual nearest neighbor queries. We also present the complexity analysis of the algorithm, and provide and discuss experimental results that show the scalability of our approach.

In this paper we study a problem that arises in the competitive facility location field. Facilities and customers are represented by points of a planar Euclidean domain. We associate a weighted distance to each facility to reflect that customers select facilities depending on distance and importance. We define, by considering weighted distances, the k-influence region of a facility as the set of points of the domain that has the given facility among their k-nearest/farthest neighbors. On the other hand, we partition the domain into subregions so that each subregion has a non-negative weight associated to it which measures a characteristic related to the area of the subregion. Given a weighted partition of the domain, the k-influence region problem finds the points of the domain where are new facility should be opened. This is done considering the known weight associated to the new facility and ensuring a minimum weighted area of its k-influence region. We present a GPU parallel approach, designed under CUDA architecture, for approximately solving the k-influence region problem. In addition, we describe how to visualize the solutions, which improves the understanding of the problem and reveals complicated structures that would be hard to capture otherwise. Integration of computation and visualization facilitates decision makers with an iterative what-if analysis process, to acquire more information to obtain an approximate optimal location. Finally, we provide and discuss experimental results showing the efficiency and scalability of our approach Work partially supported by the Spanish Ministerio de Economia y Competitividad under Grant TIN2010-20590-C02-02

Data analysis and knowledge discovery in trajectory databases is an emerging field with a growing number of applications such as managing traffic, planning tourism infrastructures, analyzing professional sport matches or better understanding wildlife. A well-known collection of patterns which can occur for a subset of trajectories of moving objects exists. In this paper, we study the popular places pattern, that is, locations that are visited by many moving objects. We consider two criteria, strong and weak, to establish either the exact number of times that an object has visited a place during its complete trajectory or whether it has visited the place, or not. To solve the problem of reporting popular places, we introduce the popularity map. The popularity of a point is a measure of how many times the moving objects of a set have visited that point. The popularity map is the subdivision, into regions, of a plane where all the points have the same popularity. We propose different algorithms to efficiently compute and visualize popular places, the so-called popular regions and their schematization, by taking advantage of the parallel computing capabilities of the graphics processing units. Finally, we provide and discuss the experimental results obtained with the implementation of our algorithms We thank the reviewers for their suggestions and comments. Authors are partially supported by the Spanish MCI grant TIN2010-20590-C02-02