Abstract

Civil aviation air traffic undergoes many random disturbances. Air traffic controllers watch the real traffic and ensure that it is free from collision hazards in the whole airspace — the ATC sector — under their control. The ATFM service takes care that the flow capacity in each sector, called capacity of the air traffic sector, is not exceeded. In the paper an original method of model estimation of the capacity of the designed ATC sectors is described. In this method an experimentally established statistical relationship between the random variables of control load and the air traffic density is used. The capacity of a sector was found from the joint probability distribution of such a two-dimensional random variable model determined as a quanti le of adequate order. This method was verified in practice by determining the capacity of the designed new ATC sectors in FIR Warsaw. Document type: Book

Abstract

In this paper, we characterise tourists most likely to visit a coastal destination by high-speed rail (HSR). Our data came from a survey conducted among HSR passengers during 2014’s high season (July and August) at Spain’s Camp de Tarragona and Alicante Stations, each of which is near a mass tourism destination on the Mediterranean coast: the Costa Daurada and the Costa Blanca, respectively. We used responses to the survey, which presented binary discrete-choice situations, to construct a database necessary for a logistic regression model that allowed us to examine how passenger profile, trip characteristics, and stay conditions influenced the use of HSR services on visits to each coastal destination. Results highlighted significant differences in the profiles of tourists who arrived at each destination by HSR and, in turn, that no specific tourist profile is associated with HSR, even for two stations that serve sunny beach destinations. Among its implications, to analyse travellers that HSR can attract, it is vital to consider the specific characteristics of each destination and its current market. This research was funded by the Spanish Ministry of Science and Innovation (GLOBALTUR–CSO2011–23004/GEOG; MOVETUR-CS02014-51785-R) to AG. Document type: Article

Abstract

fter the emergence of the H1N1 influenza in 2009, some countries responded with travel-related controls during the early stage of the outbreak in an attempt to contain or slow down its international spread. These controls along with self-imposed travel limitations contributed to a decline of about 40% in international air traffic to/from Mexico following the international alert. However, no containment was achieved by such restrictions and the virus was able to reach pandemic proportions in a short time. When gauging the value and efficacy of mobility and travel restrictions it is crucial to rely on epidemic models that integrate the wide range of features characterizing human mobility and the many options available to public health organizations for responding to a pandemic. Here we present a comprehensive computational and theoretical study of the role of travel restrictions in halting and delaying pandemics by using a model that explicitly integrates air travel and short-range mobility data with high-resolution demographic data across the world and that is validated by the accumulation of data from the 2009 H1N1 pandemic. We explore alternative scenarios for the 2009 H1N1 pandemic by assessing the potential impact of mobility restrictions that vary with respect to their magnitude and their position in the pandemic timeline. We provide a quantitative discussion of the delay obtained by different mobility restrictions and the likelihood of containing outbreaks of infectious diseases at their source, confirming the limited value and feasibility of international travel restrictions. These results are rationalized in the theoretical framework characterizing the invasion dynamics of the epidemics at the metapopulation level. This work has been partially funded by the National Institutes of Health R21-DA024259 award, the Lilly Endowment grant 2008 1639-000 and the DTRA-1-0910039 award to AV; the EC-ICT contract no. 231807 (EPIWORK) to AV and VC; the EC-FET contract no. 233847 (DYNANETS) to AV, VC, and JJR; the ERC Ideas contract n.ERC-2007-Stg204863 (EPIFOR) to VC, PB, CP, and MT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Peer reviewed Document type: Article

Abstract

Effective symptom management is a critical component of cancer treatment. Computational tools that predict the course and severity of these symptoms have the potential to assist oncology clinicians to personalize the patient’s treatment regimen more efficiently and provide more aggressive and timely interventions. Three common and inter-related symptoms in cancer patients are depression, anxiety, and sleep disturbance. In this paper, we elaborate on the efficiency of Support Vector Regression (SVR) and Non-linear Canonical Correlation Analysis by Neural Networks (n-CCA) to predict the severity of the aforementioned symptoms between two different time points during a cycle of chemotherapy (CTX). Our results demonstrate that these two methods produced equivalent results for all three symptoms. These types of predictive models can be used to identify high risk patients, educate patients about their symptom experience, and improve the timing of pre-emptive and personalized symptom management interventions. Document type: Article

Abstract

Background: The clinical benefit of helicopter transport over ground transportation for interfacility transport is unproven. We sought to determine actual practice patterns, utilization, and outcomes of patients undergoing interfacility transport for neurosurgical conditions. Methodology/Principal Findings: We retrospectively examined all interfacility helicopter transfers to a single trauma center during 2008. We restricted our analysis to those transfers leading either to admission to the neurosurgical service or to formal consultation upon arrival. Major exclusion criteria included transport from the scene, death during transport, and transport to any area of the hospital other than the emergency department. The primary outcome was time interval to invasive intervention. Secondary outcomes were estimated ground transportation times from the referring hospital, admitting disposition, and discharge disposition. Of 526 candidate interfacility helicopter transfers to our emergency department in 2008, we identified 167 meeting study criteria. Seventy-five (45%) of these patients underwent neurosurgical intervention. The median time to neurosurgical intervention ranged from 1.0 to 117.8 hours, varying depending on the diagnosis. For 101 (60%) of the patients, estimated driving time from the referring institution was less than one hour. Four patients (2%) expired in the emergency department, and 34 patients (20%) were admitted to a non-ICU setting. Six patients were discharged home within 24 hours. For those admitted, in-hospital mortality was 28%. Conclusions/Significance: Many patients undergoing interfacility transfer for neurosurgical evaluation are inappropriately triaged to helicopter transport, as evidenced by actual times to intervention at the accepting institution and estimated ground transportation times from the referring institution. In a time when there is growing interest in health care cost containment, practitioners must exercise discretion in the selection of patients for air ambulance transport—particularly when it may not bear influence on clinical outcome. Neurosurgical evaluation via telemedicine may be one strategy for improving air transport triage. Document type: Article

Abstract

We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspaces and improve it by guiding the design of new ones. Specifically, we compare the performance of three community detection algorithms, also by using a null model which takes into account the spatial distance between nodes, and we discuss their ability to find communities that could be used to define new control units of the airspace. Comment: 22 pages, 14 figure Document type: Article

Abstract

Much of our knowledge of the course of animal and plant evolution is based on shape. Recognition, description, arrangement, rearrangement, organization, reorganization, and interpretation of shape are the prime working tools of the paleontologist, the life blood of the systematist, the raw material of the evolutionist, and the dilemma of the developmental biologist. Keith Thomson's book, Morphogenesis and Evolution, deals with how shape changes both in ontogeny and in phylogeny. Morphogenesis is the study of the development of shape over an individual lifetime; evolution includes changes in shape throughout phylogeny. The development of form has been treated as a separate discipline since the German Naturphilosophie of Oken (1779-1851) and His (183 1-1904) and has been linked to phylogeny since von Baer (1792-1876). For Darwin, morphology was the soul of natural history (Darwin, 1910 p. 358), development and embryology, "one of the most important subjects in the whole round of natural history" (Darwin, 1910 p. 363). Mayr (1982 p. 468) believes that "evolutionary morphology" did not arise until the 1950's, with the distinction between function and role and the exploration of preadaptation, multiple functions, and multiple pathways. An integrated treatment of"morphogenesis and evolution" or, better, of morphogenesis as an evolutionary process therefore addresses, or should address, key questions in development, in evolution, and in the consequences of the one for the other. In developmental biology, and certainly in general treatises on animal development (of which the second edition of Scott Gilbert's [19881 Developmental Biology is the best currently available), morphogenesis is normally treated alongside differentiation (specialization of the parts of the embryo). This is not because morphogenesis and differentiation always proceed handin-hand, for even when they occur contemporaneously in space and time, each may be under separate and independent developmental control (see Maclean and Hall, 1987), but because the two, along with growth, constitute the triad of developmental processes. Morphogenesis normally occurs alongside cellular differentiation in growing tissues or organs. Differentiating cells often change shape as they grow (either by

Abstract

The presence of wildlife in airport areas poses substantial hazards to aviation. Wildlife aircraft collisions (hereafter wildlife strikes) cause losses in terms of human lives and direct monetary losses for the aviation industry. In recent years, wildlife strikes have increased in parallel with air traffic increase and species habituation to anthropic areas. In this paper, we used an ecological approach to wildlife strike risk assessment to eight Italian international airports. The main achievement is a site-specific analysis that avoids flattening wildlife strike events on a large scale while maintaining comparable airport risk assessments. This second version of the Birdstrike Risk Index (BRI2) is a sensitive tool that provides different time scale results allowing appropriate management planning. The methodology applied has been developed in accordance with the Italian Civil Aviation Authority, which recognizes it as a national standard implemented in the advisory circular ENAC APT-01B. Document type: Article

Abstract

Structural brain networks may be reconstructed from diffusion MRI tractography data and have great potential to further our understanding of the topological organisation of brain structure in health and disease. Network reconstruction is complex and involves a series of processesing methods including anatomical parcellation, registration, fiber orientation estimation and whole-brain fiber tractography. Methodological choices at each stage can affect the anatomical accuracy and graph theoretical properties of the reconstructed networks, meaning applying different combinations in a network reconstruction pipeline may produce substantially different networks. Furthermore, the choice of which connections are considered important is unclear. In this study, we assessed the similarity between structural networks obtained using two independent state-of-the-art reconstruction pipelines. We aimed to quantify network similarity and identify the core connections emerging most robustly in both pipelines. Similarity of network connections was compared between pipelines employing different atlases by merging parcels to a common and equivalent node scale. We found a high agreement between the networks across a range of fiber density thresholds. In addition, we identified a robust core of highly connected regions coinciding with a peak in similarity across network density thresholds, and replicated these results with atlases at different node scales. The binary network properties of these core connections were similar between pipelines but showed some differences in atlases across node scales. This study demonstrates the utility of applying multiple structural network reconstrution pipelines to diffusion data in order to identify the most important connections for further study. Document type: Article