You can get all global flight information in 1 API call or track flights based on flight number, airline, departure/arrival airport, and more. The data updates frequently, around every 5 minutes. The details of the data include:

Geography: Location information such as latitude, longitude, altitude, and direction. Speed: Vertical and horizontal speed of aircraft. Departure and arrival: IATA codes and ICAO codes of the departure and arrival airport. Aircraft and flight: IATA and ICAO number of flight and registration number, ICAO code, and ICAO24 code of aircraft. Airline: IATA code, and ICAO code of airline. System information: Squawk, status, and last updated in Epoch.

Here's an example response from the API: [ { "geography": { "latitude": 43.5033, "longitude": -79.1297, "altitude": 7833.36, "direction": 70 }, "speed": { "horizontal": 833.4, "isGround": 0, "vertical": 0 }, "departure": { "iataCode": "YHM", "icaoCode": "CYHM" }, "arrival": { "iataCode": "YQM", "icaoCode": "CYQM" }, "aircraft": { "icaoCode": "B763", "regNumber": "CGYAJ", "icao24": "C08412" }, "airline": { "iataCode": "W8", "icaoCode": "CJT" }, "flight": { "iataNumber": "W8620", "icaoNumber": "CJT620", "number": "620" }, "system": { "updated": 1513148168, "squawk": "0000" }, "status": "en-route" } ]

Developer Information:

1) Available Endpoints &depIata= &depIcao= &arrIata= &arrIcao= &aircraftIcao= &regNum= &aircraftIcao24= &airlineIata= &airlineIcao= &flightIata= &flightIcao= &flightNum= &status= &limit= &lat=&lng=&distance=

2) Flights Tracker API Output

Specific flight based on: Flight IATA Number: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&flightIata=W8519

All flights of a specific Airlines: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&airlineIata=W8

Flights from departure location: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&depIata=MAD

Flights from arrival location: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&arrIata=GIG

Flights within a circle area based on lat and lng values and radius as the distance: GET https://aviation-edge.com/v2/public/flights?key=[API_KEY]&lat=51.5074&lng=0.1278&distance=100&arrIata=LHR

Combinations: two airports and a specific airline flying between them: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&depIata=ATL&arrIata=ORD&airlineIata=UA

You can connect to the actual flight routes around the world with your API key at any time with very fast response times. It is possible to view all routes at the same time via a single API key. For your convenience, we have also developed many different filters so that you can pull the exact data you are looking for. This way, you may get data of the routes of a specific airline, routes from or to a specific airport (both IATA and ICAO codes work), or may get an individual flight based on its flight number.

A common use of the air routes API is to develop software in the aviation industry. While Aviation Edge’s focus is to collect and maintaining aviation data, you are free to develop countless applications, tools, and platforms by using our data.

The details included in the routes data are: Departure data: IATA code, ICAO code, terminal, and time. Arrival data: IATA code, ICAO code, terminal, and time. Airline: IATA code of airline. Flight: Flight number. Aircraft: Registration number of the aircraft.

Here's an example response from the API: [ { "departureIata": "OTP", "departureIcao": "LROP", "departureTerminal": 2, "departureTime": "09:15:00", "arrivalIata": "TRN", "arrivalIcao": "LIMF", "arrivalTerminal": 1, "arrivalTime": "10:45:00", "airlineIata": "0B", "airlineIcao": "BMS", "flightNumber": "101", "codeshares": null, "regNumber": "YR-BAP" } ]

Developer information: 1) Available Endpoints &departureIata= &departureIcao= &airlineIata= &airlineIcao= &flightNumber=

2) Output Airports, Airlines or Flights routes output: GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&departureIata=OTP GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&departureIcao=LROP GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&airlineIata=0B GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&airlineIcao=BMS GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&flightNumber=101 For information about a specific route (example). GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&departureIata=OTP&airlineIata=0B&flightNumber=101

This line feature class was created to model flight lines on geo-rectified aerial photography for the State Water Project. The coordinate system for this feature class is NAD_1983_CaTM. The purpose for the creation of this dataset is to help classify the various flight groups according to the corresponding project ID and supply relevant spatial data information. To create the flight lines, archived aerial photography was first scanned and converted to .tiff file format that would be later geo-referenced to NAIP 2016. The photo centers at the ends of each fight line would be marked using the polygon drawing tool by creating an "X" from the vertex of each corner fiducial. The flight line would then be created using these photo center as reference end points using the "create feature" option in the editor toolbar.

The Schedules API service provides real-time data for the flight schedules and timetables of airports and airlines around the world and maintains this for you in our central database, always accessible with your personal API key. This is one of Aviation Edge’s core features. You can build real-time airport departure and arrival tables, keep track of delays and cancellations, track the status of flights by using our API. The data comes in JSON format, making it useful to implement to websites and build applications, tools, software, and more.

The data includes the following: - Flight Status: active, scheduled, landed, cancelled, incident, diverted, redirected. - Airport details: IATA code, ICAO code, Terminal, Gate for both departure and arrival airport - Take-off information: Scheduled, estimated and actual times on runway and that of departure/arrival. - Total delay (updated for departures) - Airline: Name, IATA code and ICAO code. - Flight: Number of Flight, IATA prefix with flight number and ICAO prefix with flight number.

Example response from the API:

[ {"airline": {"iataCode":"DL", "icaoCode":"DAL", "name":"Delta Air Lines"}, "arrival": {"actualRunway":"2021-03-03T04:15:00.000", "actualTime":"2021-03-03T04:15:00.000", "baggage":"T4", "delay":null, "estimatedRunway":"2021-03-03T04:15:00.000", "estimatedTime":"2021-03-03T04:15:00.000", "gate":"B41", "iataCode":"JFK", "icaoCode":"KJFK", "scheduledTime":"2021-03-03T05:05:00.000", "terminal":"4"}, "codeshared":null, "departure": {"actualRunway":"2021-03-03T00:10:00.000", "actualTime":"2021-03-03T00:10:00.000", "baggage":5, "delay":"16", "estimatedRunway":"2021-03-03T00:10:00.000", "estimatedTime":”2021-03-03T00:10:00.000”, "gate":"B06", "iataCode":"TLV", "icaoCode":"LLBG", "scheduledTime":"2021-03-02T23:55:00.000", "terminal":"3"}, "flight": {"iataNumber":"DL235", "icaoNumber":"DAL235", "number":"235"}, "status":"landed", "type":"arrival"} ]

Output:

For the departure schedule of a certain airport. GET http://aviation-edge.com/v2/public/timetable?key=[API_KEY]&iataCode=JFK&type=departure

For the arrival schedule of a certain airport. GET http://aviation-edge.com/v2/public/timetable?key=[API_KEY]&iataCode=JFK&type=arrival

Market Analysis of Flight Data API The global Flight Data API market is expanding rapidly, with an estimated market size of USD XXX million in 2025 and a projected CAGR of XX% during the forecast period of 2025-2033. The increasing demand for real-time flight information by airlines, travel agencies, and businesses is driving the market growth. Additionally, the rising adoption of cloud-based solutions, advancements in data analytics, and the proliferation of mobile devices are contributing to the market's expansion. Key market trends include the integration of Flight Data APIs with travel booking platforms, the development of predictive analytics to optimize flight operations, and the emergence of low-cost carriers and budget airlines driving the demand for affordable flight data. However, data privacy concerns, limitations in data coverage, and the availability of alternative flight data sources may restrain market growth. The market is segmented based on application (SMEs and large enterprises), type (cloud-based and on-premises), and region (North America, Europe, Asia Pacific, South America, and Middle East & Africa). Prominent market players include Aviationstack, FlightAware, OpenSky, Cirium, and Trawex. This report provides comprehensive insights into the Flight Data API market, covering key trends, drivers, challenges, and opportunities. It analyzes the market landscape, including market size, segmentation, and competitive analysis, to provide a clear understanding of the market dynamics. The report also includes detailed profiles of key players in the industry, providing valuable insights into their strategies, product offerings, and financial performance.

Analysis of ‘APIS Flight Lines’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/c859eaab-065a-42a7-8230-789ebe71a268 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

This line feature class was created to model flight lines on geo-rectified aerial photography for the State Water Project. The coordinate system for this feature class is NAD_1983_CaTM. The purpose for the creation of this dataset is to help classify the various flight groups according to the corresponding project ID and supply relevant spatial data information. To create the flight lines, archived aerial photography was first scanned and converted to .tiff file format that would be later geo-referenced to NAIP 2016. The photo centers at the ends of each fight line would be marked using the polygon drawing tool by creating an "X" from the vertex of each corner fiducial. The flight line would then be created using these photo center as reference end points using the "create feature" option in the editor toolbar.

--- Original source retains full ownership of the source dataset ---

Information contained includes project ID, flight start date, flight end date, index confirmation, camera type, project type, production status, and whether the flight has been geo-referenced or not.

This polygon feature class was created to model the flight coverage of geo-rectified aerial photography for the State Water Project for each flight group. The coordinate system utilized for this feature class is NAD1983_CaTM. The purpose for the creation of this dataset is to help classify the various flight groups according to the corresponding project ID and supply relevant spatial data information. To create the photo centers, archived aerial photography was first scanned and converted to .tiff file format that would be later geo-referenced to NAIP 2016. The photo centers at the ends of each fight line would be marked using the polygon drawing tool by creating an "X" from the vertex of each corner fiducial. The flight line would then be created using these photo center for end points with a line feature class. The photo centers were then created by constructing points using the editor tool. To develop the coverage extent, the photo scale was inputted into an excel flight plan distance calculator to formulate coverage distance. Next, the buffer tool under the geo-processing tab was utilized to input the coverage distance found previously to create the flight coverage area.

The airports the API returns include airports that have the submitted letters anywhere in them. For example, when the letters "ist" are requested, the API returns both "Istanbul Airport" and "Bristol Airport" (among other items).

The API is particularly useful for travel agency and flight booking websites, tools or apps to display the relevant airport and cities as a list for the user to choose from.

The city and airport data the Autocomplete API returns include: - IATA code and name, - Country code and name, - Airport location (latitude and longitude) - Time zone

1) Example Fields of Use - Travel agency and flight booking/schedule tracking websites, tools, apps where users are expected to submit a departure or arrival city or airport - Any autocomplete feature related to cities or airports

2) Example Input Airports and cities with the letters containing "xyz" in them:

GET http://aviation-edge.com/v2/public/autocomplete?key=[API_KEY]&city=xyz

3) Example Output [ { "code": "AMS", "name": "Amsterdam", "cityCode": "AMS", "cityName": "Amsterdam", "countryCode": "NL", "countryName": "Netherlands", "lat": 52.3730556, "lng": 4.8922222, "timezone": "Europe/Amsterdam", "type": "city" } ], "airports": [ { "code": "ZYA", "name": "Amsterdam Centraal Railway Station", "cityCode": "AMS", "cityName": "Amsterdam", "countryCode": "NL", "countryName": "Netherlands", "lat": 52.3730556, "lng": 4.8922222, "timezone": "Europe/Amsterdam", "type": "rail_station", "isRailRoad": 1, "isBusStation": 0 }, { "code": "AMS", "name": "Schiphol", "cityCode": "AMS", "cityName": "Amsterdam", "countryCode": "NL", "countryName": "Netherlands", "lat": 52.30907, "lng": 4.763385, "timezone": "Europe/Amsterdam", "type": "airport", "isRailRoad": 0, "isBusStation": 0 } ], "airportsByCities": }, ... ]

The historical flight schedule data is perfect to create applications, plugins for websites, running analysis and creating statistics, keeping track of past delays and cancellations for insurance or flight compensation claims, and much more.

We have developed many parameters you can use to pull the exact data you need without having to spend too much time filtering it on your end. We've asked many developers around the world to find out which pieces of data they would need the most, and created the parameters based on this feedback.

The data includes: - Airline: Name, IATA and ICAO codes of the airline. - Departure and arrival: IATA codes and ICAO codes of the departure and arrival location. - Departure and arrival times: Scheduled, estimated and actual arrival and departure times, as well as runway times in local time. - Status: The latest status information of the flight which may be active (for departure schedules), landed (for arrival schedules), cancelled or unknown - Delay: Total delay amount in minutes for delayed flights

Example response from the API: { "type": "departure", "status": "active", "departure": { "iataCode": "jfk", "icaoCode": "kjfk", "terminal": "7", "delay": 10, "scheduledTime": "2020-09-25t20:15:00.000", "estimatedTime": "2020-09-25t20:09:00.000", "actualTime": "2020-09-25t20:25:00.000", "estimatedRunway": "2020-09-25t20:25:00.000", "actualRunway": "2020-09-25t20:25:00.000"}, "arrival": { "iataCode": "lhr", "icaoCode": "egll", "terminal": "5", "scheduledTime": "2020-09-26t08:20:00.000", "estimatedTime": "2020-09-26t07:32:00.000" }, "airline": { "name": "aer lingus", "iataCode": "ei", "icaoCode": "ein" }, "flight": { "number": "8814", "iataNumber": "ei8814", "icaoNumber": "ein8814" }, "codeshared": { "airline": { "name": "british airways", "iataCode": "ba", "icaoCode": "baw" }, "flight": { "number": "114", "iataNumber": "ba114", "icaoNumber": "baw114"} } },

2) Historical Schedules API Output - Developer Information For the departure schedule of a certain airport on a certain date. GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=departure&date_from=YYYY-MM-DD

For the arrival schedule of a certain airport on a certain date. GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=arrival&date_from=YYYY-MM-DD

For the schedule of a certain airport of a certain date range (also available for arrival). GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=departure&date_from=YYYY-MM-DD&date_to=YYYY-MM-DD

For the schedule of a certain airport on a certain date (or range) but only flights with a certain status. GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=arrival&date_from=YYYY-MM-DD&date_to=YYYY-MM-DD&status=cancelled

For tracking individual historical flights. GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=departure&date_from=YYYY-MM-DD&date_to=YYYY-MM-DD&flight_number=[1234]

For filtering the flights of a certain airline from the arrival schedule of a certain airport on a certain date (also available for departure schedules and as a date range). GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=arrival&date_from=YYYY-MM-DD&&airline_iata=TK

Important Tips: - Currently possible to get dates that are up to 1 year earlier than the current date (this will expand soon). - The date range can go up to 28 days for a single API call but may be shorter around 3-5 days for airports with heavy traffic.

API operated by Louisville Metro that returns AQI information from local sensors operated by APCD. Shows the latest hourly data in a JSON feed.The Air Quality Index (AQI) is an easy way to tell you about air quality without having to know a lot of technical details. The “Metropolitan Air Quality Index” shows the AQI from the monitor in Kentuckiana that is currently detecting the highest level of air pollution. See: https://louisvilleky.gov/government/air-pollution-control-district/servi...See the air quality map (Louisville Air Watch) for more details: airqualitymap.louisvilleky.gov/#Read the FAQ for more information about the AQI data: https://louisvilleky.gov/government/air-pollution-control-district/louis...If you'd prefer air quality forecast data (raw data, maps, API) instead, please see AIRNow: https://www.airnow.gov/index.cfm?action=airnow.local_city&zipcode=40204&...See the Data Dictionary section below for information about what the AQI numbers mean, their corresponding colors, recommendations, and more info and links.To download daily snapshots of AQI for the last 25 years, visit the EPA website, set your year range, and choose, Louisville KY. Then download with the CSV link at the bottom of the page.IFTTT integration trigger that fires and after retrieving air quality from Louisville Metro air sensors via the APIGives a forecast instead of the current conditions, so you can take action before the air quality gets bad.The U.S. EPA AirNow program (www.AirNow.gov) protects public health by providing forecast and real-time observed air quality information across the United States, Canada, and Mexico. AirNow receives real-time air quality observations from over 2,000 monitoring stations and collects forecasts for more than 300 cities.Sign up for a free account and get started using the RSS data feed for Louisville. https://docs.airnowapi.org/feedsAir Quality Forecast via AirNowAQI Level - Value and Related Health Concerns LegendGood 0-50 GreenAir quality is considered satisfactory, and air pollution poses little or no risk.Moderate 51-100 YellowAir quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to air pollution.Unhealthy for Sensitive Groups 101-150 OrangeMembers of sensitive groups may experience health effects. The general public is not likely to be affected.Unhealthy 151-200 RedEveryone may begin to experience health effects; members of sensitive groups may experience more serious health effects.Very Unhealthy 201-300 PurpleHealth alert: everyone may experience more serious health effects.Hazardous > 300 Dark PurpleHealth warnings of emergency conditions. The entire population is more likely to be affected.Here are citizen actions APCD recommends on air quality alert days, that is, days when the forecast is for the air quality to reach or exceed the “unhealthy for sensitive groups” (orange) level:Don’t idle your car. (Recommended all the time; see the second link below.)Put off mowing grass with a gas mower until the alert ends.“Refuel when it’s cool” (pump gasoline only in the evening or night).Avoid driving if possible. Share rides or take TARC.Check on neighbors with breathing problems.Here are some links in relation to the recommendations:KAIRE, www.helptheair.org/Idle Free Louisville, www.helptheair.org/idle-freeTARCTicket to Ride, tickettoride.org/Lawn Care for Cleaner Air (rebates)Contact:Bryan FrazerBryan.Frazar@louisvilleky.gov

Api - Air Quality Programmatic Apis
This dataset falls under the category Environmental Data Air Quality Data.
It contains the following data: Air Pollution: real-time air quality
This dataset was scouted on 2022-02-05 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://aqicn.org/city/mumbai/See URL for data access and license information.

This line feature class was created to model flight lines on geo-rectified aerial photography for the State Water Project. The coordinate system for this feature class is NAD_1983_CaTM. The purpose for the creation of this dataset is to help classify the various flight groups according to the corresponding project ID and supply relevant spatial data information. To create the flight lines, archived aerial photography was first scanned and converted to .tiff file format that would be later geo-referenced to NAIP 2016. The photo centers at the ends of each fight line would be marked using the polygon drawing tool by creating an "X" from the vertex of each corner fiducial. The flight line would then be created using these photo center as reference end points using the "create feature" option in the editor toolbar.

Api - Air Quality Programmatic Apis)
This dataset falls under the category Environmental Data – Air Quality Data.
It contains the following data: Air Pollution: real-time air quality . The data can be accessed using the following URL / API Endpoint: https://aqicn.org/city/indonesia/kemayoran/
This dataset was scouted on 01/06/2022 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. See URL for data access and license information.

We asked whether the insect peptide hormone corazonin changes honey bee flight behavior. To address this question, we injected bees with corazonin or a negative control, placed them back in their colony, and measured their daily flight activity.For "concentrationsFlightActivity.xlsx":Fifty 9d old bees were injected in the head with 2µl of a low (25ng/µl), middle (125ng/µl), or high (250ng/µl) dose of CRZ peptide in 1X Ringer’s solution, or 1X Ringer’s solution alone (control). The bees were then marked according to the treatment they received and were returned to their respective hives. For 5 days post-injection (10-15d post-emergence), the entrance of each hive was monitored for 10 minutes each hour for five hours (06:00-11:00 MST, 50 minutes daily per hive). The number of painted bees that left or returned to the hive during this time and their paint color was recorded.Columns in data sheet represent the concentration of peptide injected ("treatment"), whether a flight event was observed ("F vs NF"), hive number ("hive"), age of bee that was observed flying ("age"), and the trial ("round").For "2019FlightActivity.xlsx":Injections and behavioral observations were conducted in June/July 2019 for bees injected at 9d of age. Approximately 700-800 NEBs were obtained, marked, and distributed equally into four separate hives. The marked bees were collected from the hive at 9d and injected with 2µl of CRZ peptide (125ng/µl) or an equivalent concentration of scramble peptide (125ng/µl; negative control) in 1X Ringer’s solution. Each bee was then re-marked according to the treatment they received (CRZ or scramble control) and returned to their hive. Post-treatment flight activity was monitored for five days, for 50 minutes per hive each day. After each daily observation period, we also counted the number of painted bees of both treatments that were found on the frames and hive body or dead bees on the bottom board or at the hive entrance. The data represent whether an individual was observed flying ("F") or was alive but did not fly ("NF").The columns represent whether the individual observed was injected with the control or corazonin peptide ("treatment"), whether the individual observed was flying or alive but not flying ("F vs NF"), the hive number ("hive"), and the age of the observed bee in days post-emergence ("age").For "2020FlightActivity.xlsx":Injections and behavioral observations were conducted in April/May/June 2020 (injected at 8d of age). Approximately 700-800 NEBs were obtained, marked, and distributed equally into four separate hives, as described above. The marked bees were collected from the hive at 8d (Trial 2) and injected with 2µl of CRZ peptide (125ng/µl) or an equivalent concentration of scramble peptide (125ng/µl; negative control) in 1X Ringer’s solution. Each bee was then re-marked according to the treatment they received (CRZ or scramble control) and returned to their hive. Post-treatment flight activity was monitored for five days (10-15d post-emergence) for 50 minutes per hive each day. After each daily observation period, we also counted the number of painted bees of both treatments that were found on the frames and hive body or dead bees on the bottom board or at the hive entrance. The data represent whether an individual was observed flying ("F") or was alive but was not flying ("NF").The columns represent whether the individual observed was injected with the control or corazonin peptide ("treatment"), whether the individual observed was flying or alive but not flying ("F vs NF"), the hive number ("hive"), and the age of the observed bee in days post-emergence ("age").For "injectionSurvivalExperiment.xlsx":Individuals were collected from the entrances of 3 separate colonies and were anesthetized on wet ice for ~15 minutes. The bees were kept separate according to the hive they were collected from. Half of the bees from each hive were handled for ~30-45 seconds and marked with paint on the thorax. The other half of the bees were injected with 2µl of 1X Ringer’s solution (182mM KCl, 46mM NaCl, 3mM CaCl2 dihydrate, 10mM Tris-HCl) in the center of the head on the anterior (face) side, just behind the antennae (as in (Corby-Harris et al., 2019)) and marked with a different color paint. All bees were kept on ice until the injections were complete, warmed at room temperature until they were active, and returned to their source hive. At 24 and 48h post-treatment, we searched the ground near the hives and then opened and inspected the colony for painted bees. The painted bees (live or dead) were counted. This was repeated for three colonies and for three trials (13 February, 26 February, and 18 March 2018). Columns in data sheet represent the colony number, the time of the observation post-treatment ("time of death"), whether the painted bee was observed or not (i.e., censored) at that time point ("censored"), the trial number ("trial"), and whether the bee was injected or simply handled but not injected ("treatment"). [file added January 2025]For "vgCrzExpressionCagesInIncubator.xlsx":The head tissue from 6 bees per cage (10 cages, 5 pollen-fed, 5 pollen-starved) was pooled and crushed in ice-cold TRIzol. RNA was extracted from the head tissue using a “hybrid” TRIzol-column protocol (Untergasser, 2008). The DNased RNA was used as a template for cDNA synthesis using the revertAid First Strand cDNA Synthesis Kit and the supplied random hexamer primer.Gene expression was measured using the synthesized cDNA. In addition to the vg and actin primers used in previous studies (Corby-Harris et al., 2014; Corby-Harris et al., 2016), a crz primer-probe set was developed based on the Apis mellifera crz mRNA sequence (NCBI accession AB201717.1). Expression of vg and actin was assayed using SsoAdvanced Universal SYBR Green Supermix, the cDNA, and primers for vg and actin (the reference gene). Crz gene expression was assayed using the cDNA, the crz primer-probe, and iTaq Universal Probes Supermix. One positive (Apis mellifera gDNA) and one negative control (water) were assayed for each primer pair. All samples were run in triplicate. Expression (Ct) values were averaged across the technical replicates. Gene expression (relative to actin) was calculated using the 2−ΔΔCt method (Livak and Schmittgen, 2001).The columns represent the cage number ("cage"), the age that the individuals were sampled in days ("age"), whether the individual observed was flying or alive but not flying ("F vs NF"), the hive number ("hive"), expression of crz relative to actin ("crz_expression"), expression of vg relative to actin ("vg_expression"), and whether the bees in the cage were fed pollen or no pollen ("treatment"). [file added January 2025]

Sky Airlines S A Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Landing is a critical phase for flying animals, whereby many rely on visual cues to perform controlled touchdown. Foraging honeybees rely on regular landings on flowers to collect food, crucial for colony survival and reproduction. Here, we explore how honeybees utilize optical-expansion cues to regulate approach flight speed when landing on vertical surfaces. Three sensory-motor control models have been proposed for landings of natural flyers. Landing honeybees maintain a constant optical-expansion-rate set-point, resulting in a gradual decrease in approach velocity and gentile touchdown. Bumblebees exhibit a similar strategy, but they regularly switch to a new constant optic-expansion-rate set-point. Meanwhile, landing birds fly at a constant time-to-contact to achieve faster landings. Here, we re-examined the landing strategy of honeybee by fitting the three models to individual approach flights of honeybees landing on platforms with varying optic-expansion cues. Surprisingly, the landing model identified in bumblebees proves to be the most suitable for these honeybees. This reveals that honeybees adjust their optic-expansion-rate in a stepwise manner. Bees flying at low optic-expansion-rates tended to stepwise increase their set-point, while those flying at high optic-expansion-rates tend to stepwise decrease it. This modular landing control system enables honeybees to land rapidly and reliably under a wide range of initial flight conditions and visual landing platform patterns. The remarkable similarity between the landing strategies of honeybees and bumblebees suggests that this may also be prevalent among other flying insects. Furthermore, these findings hold promising potential for bioinspired guidance systems in flying robots.

This datasets contains information about number of flight, passengers, and cargo in Saudi Arabia's Domestic airports, for 2016- 2019. Data from General Authority for Statistics . Export API data for more datasets to advance energy economics research.Source : Saudi Arabian Airlines Organization.

This is an api that provides continuous real time as well as historic data from the network of air quality monitoring stations that are part of the national air quality monitoring network managed in cooperation between the Environmental Protection Agency and Dublin City Council, as well as other stations set up by Dublin City Council to monitor local air quality conditions. This api also provides access to Dublin City Council's network of environmental sound level monitors. For more information, visit https://dublincityairandnoise.ie/

Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries

https://developer.airfranceklm.com/apis/open_data

Discover our real-time information — Real-time flight schedule and fare offers — Flight schedules in real time — Services of each flight