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34 results for “commutation”
Evaluating the Sustainability Impacts of Intelligent Carpooling Systems for SOV Commuters in the Atlanta Region
<p>This data repository provides the data used in the following research project supported by an NCST (UTC) grant: Evaluating the Sustainability Impacts of Intelligent Carpooling Systems for SOV Commuters in the Atlanta Region.</p> <p>Please refer to Data Format and Content in the research report for meta-data information</p> <p>1. ABM Trip Table (Data Set 1):<br> CarpoolSim_input.csv<br> 2. Traffic Analysis Zones (TAZ) Shapefiles (Data Set 2):<br> TAZ+ECs_TAZ.zip<br> 3. Employment Center Shapefiles (Data Set 3):<br> TAZ+ECs_TAZ.zip<br> 4. Shortest Paths (Data Set 4):<br> path_retention.zip<br> 5. Analytical Outputs (Data Set 5):<br> summ_stats_ind.csv<br> summ_stats.csv</p>
Data from: Group size and dispersal ploys: An analysis of commuting behaviour of the pond bat (Myotis dasycneme)
<p>This study aimed to provide a description on how Pond bats (<em>Myotis dasycneme</em>) disperse, how to recognize a commuting route, and details about the effort needed to make a complete survey of one commuting route. The study area covered the provinces of Zuid-Holland, Overijssel, Friesland, Noord-Holland, and Utrecht. During 6 years of study between 2002 and 2009, researchers and bat volunteers studied pond bats along several waterways (all waterways wider than 10 m) between known roosts and their hunting areas. All the observations were made between April and September, starting 20 min before sunset. During the entire observation effort, the time (in hours and minutes) and direction of each bat was recorded. The time that each bat passed the observation location was later transformed to minutes after sunset. The number of animals on commuting route was related to the number of animals present in their respective roost.</p> <p> </p> <p>Data are organized in 3 files: <strong>commuting data 10 minutes.csv</strong>, <strong>commuting data.csv</strong> and <strong>observations waddinxveen.csv</strong>. The variables in these data files are explained here:</p> <p>Date: the observation date</p> <p>Location description: description of the location</p> <p>X Y: The coordinates of the location in RD. The RD (Rijks-Driehoek) system is the coordinate system used by the Dutch geographical service.</p> <p>Long Lat: The coordinates of the location in longitude and latitude.</p> <p>Distance over water: commuting distance over water. For each route, the distance (d) over water between roost and observation location was measured from a topographical map and expressed in kilometres.</p> <p>Moon cover: the amount of moon cover, expressed in percentages.</p> <p>Roost location: the assumed location of the roost of the bats passing on their commuting route</p> <p>Max N of bats in roost: the max number of bats observed emerging from a roost.</p> <p>Sum N of bats over 10-minute interval: the sum of all the observed bats passing in one direction within a 10-minute interval</p> <p>Time after sunset in 10 min: the begin time of each interval, measured in minutes after sunset</p> <p>Peak time after sunset: the time of the observed peak in numbers of bats, in minutes after sunset.</p> <p>Area: the municipality near the observation location.</p> <p>Total N of pond bats on route: the total number of pond bats observed on route, in the given observation time. Including foraging and returning bats.</p> <p>Total N of commuting pond bats: the total number of bats observed commuting (excluding all other behaviours).</p> <p>Time of first bat minutes after sunset: the time of the first bat, measured in minutes after sunset.</p> <p>Duration of commuting: the time in hours between the first and the last bat observed commuting.</p> <p>Observation time: the total duration (in minutes) of the observation period.</p> <p>Moon phases: a 1–3 scale, where c1 is the new moon, c2 is the first quarter, c3 half moon, c4 is the last quarter and c5 is the full moon.</p> <p>Cloud cover: estimation of the cover, using the following three categories: c1-0%–25% cover (clear night sky or some isolated clouds), c2-25%–75% cover (several scattered clouds but not covering more than 75% of the night sky), and c3- 75%–100% cover (scattered clouds covering more than 75% of the night sky to a completely overcast night sky</p> <p>Observation type: observation of either emerging bats from a roost (roost) or bats observed on commuting route (commuting).</p> <p> </p> <p>In addition, we also provide 2 pdf’s containing the observation protocols (in Dutch) for counting emerging bats (<strong>Handleiding tellen van een groep meervleermuizen.pdf</strong>) and bats along a commuting route (<strong>Handleiding vliegroute telling.pdf</strong>). The protocols are intended for professionals and citizen scientists.</p>
Driven distance by commuters to the center of major and minor cities in Europe
<p>The two files contains respectively a map of driving distances around major and minor cities in Europe. The distance is given by range of 5 km from 5 to 45 km in a resolution of 100m*100m. The encoding is uint8.</p> <p>The metropolitan areas considered in this study are those from this study of <a href="https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Archive:European_cities_%E2%80%93_the_EU-OECD_functional_urban_area_definition">functional urban area definition</a>.</p> <p>The corresponding geofile is available at <a href="https://circabc.europa.eu/ui/group/8eafb630-27cf-4fae-a4c2-f1234a123fd7/library/59bfa33a-8f4b-413d-8552-ac0a93ad7e5f/details">this adress</a>.</p> <p>Most of the cities with more than 50'000 habitants are included, some cities have been removed or added depending on the local context.</p> <p>As the geofile contains only polygones of the metropolitan areas and not the city point, the points form cities with the number of habitants have been dowloaded from <a href="http://www.naturalearthdata.com/downloads/110m-cultural-vectors/110m-populated-places/">Natural Data</a> and then selected by comparison with the polygones.</p> <p>Cities with more than 20'000 have also been selected as commuting center for rural areas. Only the cities outside the metropolitan commuting zones are included.</p> <p>The calculation of driving distances around centers have been performed with <a href="https://openrouteservice.org/">OpenRouteService</a> (personal API key required, free of charge).</p> <p> </p> <p> </p>
Benchmarks for POPL'24 Paper "Commutativity Simplifies Proofs of Parameterized Programs"
<p>This archive contains the benchmark programs used in the POPL'24 paper <i>"Commutativity Simplifies Proofs of Parameterized Programs"</i> by A. Farzan, D. Klumpp and A. Podelski. <a href="https://doi.org/10.1145/3632925">https://doi.org/10.1145/3632925</a></p><p>A preprint of the paper can be found at <a href="https://arxiv.org/abs/2311.02673">https://arxiv.org/abs/2311.02673</a>.</p>
Data and code from: Three decades of wildlife-vehicle collisions in a protected area: main roads and long-distance commuting trips to migratory prey increase spotted hyena roadkills in the Serengeti
<p>This is the first release. Potential updates will be available on GitHub: <a href="https://github.com/MarwanNaciri/Three_decades_of_spotted_hyena_roadkill_in_a_protected_area">https://github.com/MarwanNaciri/Three_decades_of_spotted_hyena_roadkill_in_a_protected_area</a></p>
Framing the cross-border commuting literature: a systematic review and bibliographic analysis
<p>The dataset consist of the 134 publications selected for the systematic literature review on cross-border commuting. </p>
Spectra of random Non-commutative Geometries
<p>The data in this upload was generated using the code in https://github.com/LisaGlaser/MCMCv4 using initialisation files generated using the scripts iniprep which are also supplied here.<br> The data was analysed in the articles 1612.00713 and 1902.03590.</p>
E-Bike Commuting and Health in Overweight College Students
ClinicalTrials.gov study NCT07114991. IPD Sharing: YES. Countries: 1. Publications: 3.
Commute Survey: Twin Cities Household Ecosystem Project
We designed our methods to estimate carbon, nitrogen, and phosphorus fluxes through individual households, and to address two primary questions: 1. How are these fluxes distributed across households? 2. What biophysical and socioeconomic factors contribute to differences in these fluxes across households? Our hybrid approach combines: 1. A mailed survey 2. Energy provider records 3. On-the-ground landscape measurements 4. A computational tool (the Household Flux Calculator) 4. Parcel data (interpreted using GIS) The resulting dataset includes information on biophysical and socioeconomic variables that potentially influence household-level fluxes of elements. Using this method to study element fluxes at the household level allows us to explicitly link consumption choices and element fluxes.
Coping with the commute: behavioural responses to wind conditions in a foraging seabird
Movement is a necessary yet energetically expensive process for motile animals. Yet how individuals modify their behaviour to take advantage of environmental conditions and hence optimise energetic costs during movement remains poorly understood. This is especially true for animals that move through environments where they cannot easily be observed. We examined the behaviour during commuting flights of black-legged kittiwakes Rissa tridactyla breeding on Middleton Island, Alaska in relation to wind conditions they face. By simultaneously deploying GPS and accelerometer devices on incubating birds we were able to quantify the timing, destination, course and speed of flights during commutes to foraging patches, as well as how wing beat frequency and strength relate to flight speeds. We found that kittiwakes did not preferentially fly in certain wind conditions. However, once in the air they exhibited plasticity by increasing their air speed (the speed at which they fly relative to the wind) when travelling into headwinds and decreasing their air speed when flying with tailwinds. This strategy maximises flight range, whereby the greatest air distance is covered per unit of energy expenditure. Furthermore, we identified a biomechanical link behind this behaviour: that to achieve these changes in flight speeds, kittiwakes altered their wing beat strength, but not wing beat frequency. Using this information, we demonstrate that the cost of flying into a headwind outweighs the benefit of flying with a tailwind of equivalent speed, therefore exploiting a tailwind when commuting to a foraging patch would not be beneficial if having to return in the same direction with the same conditions. Our findings suggest that extrinsic factors, such as prey availability, have a more influential role in determining when and where birds fly during foraging trips than do wind conditions. However, once flying, kittiwakes exhibit behavioural plasticity to minimise transport costs.
Evaluating Sustainability Impacts of Intelligent Carpooling/Vanpooling System among SOV Commuters – Phase II: Park and Ride Interactions
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Comparative modelling study of exposure to respiratory aerosols in an office, meeting room, commuter train, and lunch room
<p>The data set contains all input and output files from a comparative study on indoor transmission of infectious diseases. The study comprises</p> <p>- 4 indoor environments: Public transport (commuter train), shared office, meeting room, lunch room; for each of those</p> <p>- 3 breathing manoeuvres: tidal breathing, speaking, coughing; for each of those</p> <p>- 2 emission scenarios: mean emissions, maximum emissions; and for each indoor setting</p> <p>- 2 ventilation scenarios: poor ventilation, high ventilation rate.</p> <p>The simulations were performed with the computational fluid dynamics program FDS. A full description of all input and output data will be published shortly.</p>
Socio-ecological Intervention to Promote Active Commuting to Work
ClinicalTrials.gov study NCT02250261. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Active Commuting To Improve Well-being and Health in Everyday Life
ClinicalTrials.gov study NCT01962259. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Effect of Commute Traffic on Vascular Function
ClinicalTrials.gov study NCT05454930. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Health Effects of Commuter Cycling
ClinicalTrials.gov study NCT01236222. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Immature gannets follow adults in commuting flocks providing a potential mechanism for social learning
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Fast food in the city? Nomadic flying-foxes commute less and hang around for longer in urban areas
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Urban flyways survey on bat commuting along movement corridors
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Coping with the commute: behavioural responses to wind conditions in a foraging seabird
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