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Concept: Airport


Concentrations of 22 polycyclic aromatic hydrocarbons (PAHs) were estimated for individual particle-size distributions at the airport apron of the Taipei International Airport, Taiwan, on 48 days in July, September, October, and December of 2011. In total, 672 integrated air samples were collected using a micro-orifice uniform deposition impactor (MOUDI) and a nano-MOUDI. Particle-bound PAHs (P-PAHs) were analyzed by gas chromatography with mass selective detector (GC/MSD). The five most abundant species of P-PAHs on all sampling days were naphthalene (NaP), phenanthrene (PA), fluoranthene (FL), acenaphthene (AcP), and pyrene (Pyr). Total P-PAHs concentrations were 152.21, 184.83, and 188.94 ng/m(3) in summer, autumn, and winter, respectively. On average, the most abundant fractions of benzo[a]pyrene equivalent concentration (BaPeq) in different molecular weights were high-weight PAHs (79.29 %), followed by medium-weight PAHs (11.57 %) and low-weight PAHs (9.14 %). The mean BaPeq concentrations were 1.25 and 0.94 (ng/m(3)) in ultrafine particles (<0.1 μm) and nano-particles (<0.032 μm), respectively. The percentages of total BaPeq in nano- and ultrafine particulate size ranges were 52.4 % and 70.15 %, respectively.

Concepts: Polycyclic aromatic hydrocarbon, Aromaticity, Airport, Naphthalene, Phenanthrene, Polycyclic aromatic hydrocarbons, Pyrene, Fluoranthene


Previous studies have shown accelerated gastric emptying after sleeve gastrectomy. This study aimed to determine whether a correlation exists between immediate postoperative gastroduodenal transit time and weight loss after laparoscopic sleeve gastrectomy (LSG). Specifically, correlation tests were conducted to determine whether more rapid transit after LSG correlated with increased weight loss.

Concepts: Obesity, Airport, Public transport, Rapid transit, Commuter rail, Mark Ovenden, Public transport timetable, Rail transport


Urbanization is an important factor contributing to the global spread of dengue in recent decades, especially in tropical regions. However, the impact of public transportation system on local spread of dengue in urban settings remains poorly understood, due to the difficulty in collecting relevant locality, transportation and disease incidence data with sufficient detail, and in suitably quantifying the combined effect of proximity and passenger flow. We quantify proximity and passenger traffic data relating to 2014-2015 dengue outbreaks in Kaohsiung, Taiwan by introducing a “Risk Associated with Metro Passengers Presence” (RAMPP), which considers the passenger traffic of stations located within a fixed radius, giving more weight to the busier and/or closer stations. In order to analyze the contagion risk associated with nearby presence of one or more Kaohsiung Rapid Transit (KRT) stations, we cluster the Li’s (the fourth level administrative subdivision in Taiwan) of Kaohsiung based on their RAMPP value using the K-means algorithm. We then perform analysis of variance on distinct clusterings and detect significant differences for both years. The subsequent post hoc tests (Dunn) show that yearly incidence rate observed in the areas with highest RAMPP values is always significantly greater than that recorded with smaller RAMPP values. RAMPP takes into account of population mobility in urban settings via the use of passenger traffic information of urban transportation system, that captures the simple but important idea that large amount of passenger flow in and out of a station can dramatically increase the contagion risk of dengue in the neighborhood. Our study provides a new perspective in identifying high-risk areas for transmissions and thus enhances our understanding of how public rapid transit system contributes to disease spread in densely populated urban areas, which could be useful in the design of more effective and timely intervention and control measures for future outbreaks.

Concepts: Airport, Public transport, Rapid transit, Commuter rail, Mark Ovenden, Public transport timetable, Rail transport, Park and ride


Wildlife collisions with aircraft cost the airline industry billions of dollars per annum and represent a public safety risk. Clearly, adapting aerodrome habitats to become less attractive to hazardous wildlife will reduce the incidence of collisions. Formulating effective habitat management strategies relies on accurate species identification of high-risk species. This can be successfully achieved for all strikes either through morphology and/or DNA-based identifications. Beyond species identification, dietary analysis of birdstrike gut contents can provide valuable intelligence for airport hazard management practices in regards to what food is attracting which species to aerodromes. Here, we present birdstrike identification and dietary data from Perth Airport, Western Australia, an aerodrome that saw approximately 140,000 aircraft movements in 2012. Next-generation high throughput DNA sequencing was employed to investigate 77 carcasses from 16 bird species collected over a 12-month period. Five DNA markers, which broadly characterize vertebrates, invertebrates and plants, were used to target three animal mitochondrial genes (12S rRNA, 16S rRNA, and COI) and a plastid gene (trnL) from DNA extracted from birdstrike carcass gastrointestinal tracts.

Concepts: DNA, Gene, RNA, Species, Ribosomal RNA, Bird, Airport, Airline


The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at:

Concepts: Scientific method, Statistics, European Union, Prediction, Futurology, Prophecy, Airport, Airline


Disease spreading through human travel networks has been a topic of great interest in recent years, as witnessed during outbreaks of influenza A (H1N1) or SARS pandemics. One way to stop spreading over the airline network are travel restrictions for major airports or network hubs based on the total number of passengers of an airport. Here, we test alternative strategies using edge removal, cancelling targeted flight connections rather than restricting traffic for network hubs, for controlling spreading over the airline network. We employ a SEIR metapopulation model that takes into account the population of cities, simulates infection within cities and across the network of the top 500 airports, and tests different flight cancellation methods for limiting the course of infection. The time required to spread an infection globally, as simulated by a stochastic global spreading model was used to rank the candidate control strategies. The model includes both local spreading dynamics at the level of populations and long-range connectivity obtained from real global airline travel data. Simulated spreading in this network showed that spreading infected 37% less individuals after cancelling a quarter of flight connections between cities, as selected by betweenness centrality. The alternative strategy of closing down whole airports causing the same number of cancelled connections only reduced infections by 18%. In conclusion, selecting highly ranked single connections between cities for cancellation was more effective, resulting in fewer individuals infected with influenza, compared to shutting down whole airports. It is also a more efficient strategy, affecting fewer passengers while producing the same reduction in infections.

Concepts: Infectious disease, Infection, Influenza, Transmission and infection of H5N1, Pandemic, 2009 flu pandemic, Influenza A virus subtype H1N1, Airport


In recent years, the U.S. commercial airline industry has achieved unprecedented levels of safety, with the statistical risk associated with U.S. commercial aviation falling to 0.003 fatalities per 100 million passengers. But decades of research on organizational learning show that success often breeds complacency and failure inspires improvement. With accidents as rare events, can the airline industry continue safety advancements? This question is complicated by the complex system in which the industry operates where chance combinations of multiple factors contribute to what are largely probabilistic (rather than deterministic) outcomes. Thus, some apparent successes are realized because of good fortune rather than good processes, and this research intends to bring attention to these events, the near-misses. The processes that create these near-misses could pose a threat if multiple contributing factors combine in adverse ways without the intervention of good fortune. Yet, near-misses (if recognized as such) can, theoretically, offer a mechanism for continuing safety improvements, above and beyond learning gleaned from observable failure. We test whether or not this learning is apparent in the airline industry. Using data from 1990 to 2007, fixed effects Poisson regressions show that airlines learn from accidents (their own and others), and from one category of near-misses-those where the possible dangers are salient. Unfortunately, airlines do not improve following near-miss incidents when the focal event has no clear warnings of significant danger. Therefore, while airlines need to and can learn from certain near-misses, we conclude with recommendations for improving airline learning from all near-misses.

Concepts: Airport, Northwest Airlines, Aircraft, Airline, Avianca, Airlines, Civil aviation, Southwest Airlines


The purpose was to assess if variation in sagittal plane landing kinematics is associated with variation in neuromuscular activation patterns of the quadriceps-hamstrings muscle groups during drop vertical jumps (DVJ).

Concepts: Knee, Sartorius muscle, Synovial joint, Joints, Flexion, Airport, Gracilis muscle


To describe a novel technique of creating a landing strip within the trabecular meshwork to guide trabecular micro-bypass stent (iStent) implantation in patients who underwent phacoemulsification.

Concepts: Airport, Trabecular meshwork, Runway


Air traffic represents an important way of social mobility in the world, and many ongoing discussions are related to the impacts that air transportation has on local air quality. In this study, moss Sphagnum girgensohnii was used for the first time in the assessment of trace element content at the international airport. The moss bags were exposed during the summer of 2013 at four sampling sites at the airport ‘Nikola Tesla’ (Belgrade, Serbia): runway (two), auxiliary runway and parking lot. According to the relative accumulation factor (RAF) and the limit of quantification of the moss bag technique (LOQT), the most abundant elements in the samples were Zn, Na, Cr, V, Cu and Fe. A comparison between the element concentrations at the airport and the corresponding values in different land use classes (urban central, suburban, industrial and green zones) across the city of Belgrade did not point out that the air traffic and associated activities significantly contribute to the trace element air pollution. This study emphasised an easy operational and robust (bio)monitoring, using moss bags as a suitable method for assessment of air quality within various microenvironments with restriction in positioning referent instrumental devices.

Concepts: Iron, Serbs, Airport, Abundance of the chemical elements, Nikola Tesla, Radar, Sphagnum, Belgrade