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1,581 results for “walking”
Taking a Memory Out for a Walk. Urban Auscultation
<p>In a group of ten-fifteen people maximum (adjusting to covid rules), we will go on a walk at the surroundings of Ars Electronica; guided by a leader that will give instructions on the data collections to make; take careful notes about what happens and produce a series of experimental inventories or archives and a final cosmogram. Each spot introduces approaches to accounting data in the city realm: from public memory, metaphors, senses, and ecologies, and ways to bridge our inter/dependences with our environment. Accompanied by our urban sketcher we are documenting visually.</p> <p>Spot 1 – Collect examples of “algorithm” histories.<br> Spot 2 – Collect examples of “data” uncertainties.<br> Spot 3 – Collect examples of “data” extraction.<br> Spot 4 – Collect examples of the olfactory/ tactile/ sonic dimensions<br> Make an inventory / Dealing with an archive<br> Create a “cosmogram” mapping out the different elements involved.</p>
Quantifying ethnic segregation in cities through random walks
<p><strong>Overview</strong></p> <p>This repository contains the coverage time distributions used to produce the figures and statistics for the paper:</p> <p>S. Sousa, V. Nicosia "Quantifying ethnic segregation in cities through random walks". arXiv: <a href="https://arxiv.org/abs/2010.10462">https://arxiv.org/abs/2010.10462</a></p> <p><strong>Data</strong></p> <p>The <strong>ccp.zip</strong> file contains two subfolders with the coverage time distributions for the US and UK systems. Each file contains a line per node of the network with the format:</p> <pre><code>"Node ID" "[list with the CCT for each fraction c]"</code></pre> <p>Note that each line will always contain 101 columns where the first column identifies the node and the remaining ones represent the average coverage time to reach a fraction c of classes.</p> <p>The <strong>dfa.zip file</strong> contains the following folders:</p> <ul> <li><strong>distances:</strong> each line corresponds to one repetition of the walk, it shows the area travelled by the walker, the length of the trajectory and perimeter.</li> <li><strong>exponents: </strong> The output file contains two columns, respectively for \epsilon and F(\epsilon).</li> <li><strong>results_ids</strong>: Time series of the visited nodes</li> </ul> <p>The <strong>synthetic.zip</strong> file contains the coverage time distributions for the experiment with different lattice sizes (scale-test) and the experiment with distinct spatial patterns for the population distribution (topology-test). The format follows the same as in ccp.zip folder.</p> <p> </p> <p><strong>Code</strong></p> <p>The reader interested in replicating the methods used to create the data can obtain the python scrips in the following repository:</p> <p><a href="https://github.com/segregation-rw/ethnic-segregation-rw">https://github.com/segregation-rw/ethnic-segregation-rw</a></p> <p>Note that the repository also includes the code to simulate the CCT random walks on the adjacency graphs so that the whole simulation can be replicated.</p>
Data from: Adaptive multi-objective control explains how humans make lateral maneuvers while walking
<p>To successfully traverse their environment, humans often perform maneuvers to achieve desired task goals while simultaneously maintaining balance. Humans accomplish these tasks primarily by modulating their foot placements. As humans are more unstable laterally, we must better understand how humans modulate lateral foot placement. We previously developed a theoretical framework and corresponding computational models to describe how humans regulate lateral stepping during straight-ahead continuous walking. We identified goal functions for step width and lateral body position that define the walking task and determine the set of all possible task solutions as Goal Equivalent Manifolds (GEMs). Here, we used this framework to determine if humans can regulate lateral stepping during non-steady-state lateral maneuvers by minimizing errors consistent with these goal functions. Twenty young healthy adults each performed four lateral lane-change maneuvers in a virtual reality environment. Extending our general lateral stepping regulation framework, we first re-examined the requirements of such transient walking tasks. Doing so yielded new theoretical predictions regarding how steps during any such maneuver should be regulated to minimize error costs, consistent with the goals required at each step and with how these costs are adapted at each step during the maneuver. Humans performed the experimental lateral maneuvers in a manner consistent with our theoretical predictions. Furthermore, their stepping behavior was well modeled by allowing the parameters of our previous lateral stepping models to adapt from step to step. To our knowledge, our results are the first to demonstrate humans might use evolving cost landscapes in real time to perform such an adaptive motor task and, furthermore, that such adaptation can occur quickly – over only one step. Thus, the predictive capabilities of our general stepping regulation framework extend to a much greater range of walking tasks beyond just normal, straight-ahead walking.</p>
Why does the metabolic cost of walking increase on compliant substrates?
<p>Walking on compliant substrates requires more energy than walking on hard substrates, but the biomechanical factors that contribute to this increase are debated. Previous studies suggest various causative mechanical factors, including disruption to pendular energy recovery, increased muscle work, decreased muscle efficiency and increased gait variability. We test each of these hypotheses simultaneously by collecting a large kinematic and kinetic data set of human walking on foams of differing thickness. This allowed us to systematically characterise changes in gait with substrate compliance, and, by combining data with mechanical substrate testing, drive the very first subject-specific computer simulations of human locomotion on compliant substrates to estimate the internal kinetic demands on the musculoskeletal system. Negative changes to pendular energy exchange or ankle mechanics are not supported by our analyses. Instead, we find that the mechanistic causes of increased energetic costs on compliant substrates are more complex than captured by any single previous hypothesis. We present a model in which elevated activity and mechanical work by muscles crossing the hip and knee are required to support the changes in joint (greater excursion and maximum flexion) and spatiotemporal kinematics (longer stride lengths, stride times and stance times, and duty factors) on compliant substrates.</p>
Gyroscope sensor data of shank motion during normal and barefoot walking
<p>The measurements were performed in closed and disturbance free space, where an unobstructed 10 m walkway was arranged. All tests were performed on a hard floor surface first with shoes that were adapt for walking (indoor sports shoes, sneakers etc.) and afterwards walking barefooted the same protocol. The subjects had clothing which did not restrict lower limb movement. In each test, the 10 m walking was repeated three times. Prior to testing, the procedure was demonstrated, and the sensors were carefully positioned to correct locations. The subjects were instructed to walk with their own natural walking velocity and to begin each 10 m walk from a completely stationary position.</p>
5G-EMIT Project: EMF measurements of 2G/3G/4G/5G frequency bands captured with a MVG EME Spy Evolution sensor while walking in LOS and NLOS to two antennas through the Esch-Belval Area, Luxembourg (2022-11-10)
<p>During the 5G-EMIT project, EMF measurements of relevant mobile frequency bands have been taken at various sites around known antennas.</p> <p>Focus was in measuring the the following standard frequency bands:</p> <ul> <li>5G 700 <ul> <li>Band 28 FDD down</li> <li>758 - 803 MHz (Luxembourg: 758 - 788 MHz)</li> </ul> </li> <li>LTE 800 <ul> <li>Band 20 FDD down<br> 791 - 821 MHz</li> </ul> </li> <li>GSM 900 <ul> <li>Band 8 FDD down</li> <li>925 - 960 MHz</li> </ul> </li> <li>GSM/LTE 1800 <ul> <li>Band 3 FDD down</li> <li>1805 - 1880 MHz</li> </ul> </li> <li>UMTS 2100 <ul> <li>Band 1 FDD down</li> <li>2110 - 2170 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 38 TDD</li> <li>2570 - 2620 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 7 FDD down</li> <li>2620 - 2690 MHz</li> </ul> </li> <li>5G 3500 <ul> <li>Band 78 TDD</li> <li>3300 - 3800 MHz (Luxembourg: 3400 - 3800 MHz)</li> </ul> </li> </ul> <p><br> Two sensor have been used: The MVG EME Spy Evolution and a sensor developed by IMEC/University of Ghent.</p> <ul> <li>The MVG Spy Evolution sensor is able to measure all of the requested frequency bands as defined by the standard.</li> <li>The IMEC/University of Ghent sensor is only able to measure the LTE 800, GSM 900, GSM/LTE 1800 bands as defined by the standard.<br> In the 5G 3500 band it is only able to measure the range of 3550-3700 MHz (3465-3785 MHz within a -5db response).</li> </ul> <p>The datasets of the ZIP file has following structure:</p> <ul> <li>measurements: <ul> <li>the files of the measurements as provided by the sensor or application</li> <li>combined file of measurements in case the measurements have been split into several parts</li> <li>potentially analysis files of the measurements </li> </ul> </li> <li>pictures: <ul> <li>pictures of the antennas</li> <li>pictures of the sensor</li> <li>pictures of the location of the sensor</li> </ul> </li> <li>Readme.txt: <ul> <li>Used time-zone in the tables</li> <li>Used units in the tables</li> <li>Calculation of the total values in the tables</li> <li>Used labels of the the frequency bands</li> <li>Used sensor (MVG EME Spy Evolution or IMEC/University of Ghent)</li> <li>Locations of the target antennas</li> <li>Potentially location of the fixed sensor</li> </ul> </li> </ul>
5G-EMIT Project: EMF measurements of 2G/3G/4G/5G frequency bands captured with a MVG EME Spy Evolution sensor while walking in LOS and NLOS to two antennas through the Esch-Belval Area, Luxembourg (2023-02-15)
<p>During the 5G-EMIT project, EMF measurements of relevant mobile frequency bands have been taken at various sites around known antennas.</p> <p>Focus was in measuring the the following standard frequency bands:</p> <ul> <li>5G 700 <ul> <li>Band 28 FDD down</li> <li>758 - 803 MHz (Luxembourg: 758 - 788 MHz)</li> </ul> </li> <li>LTE 800 <ul> <li>Band 20 FDD down<br> 791 - 821 MHz</li> </ul> </li> <li>GSM 900 <ul> <li>Band 8 FDD down</li> <li>925 - 960 MHz</li> </ul> </li> <li>GSM/LTE 1800 <ul> <li>Band 3 FDD down</li> <li>1805 - 1880 MHz</li> </ul> </li> <li>UMTS 2100 <ul> <li>Band 1 FDD down</li> <li>2110 - 2170 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 38 TDD</li> <li>2570 - 2620 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 7 FDD down</li> <li>2620 - 2690 MHz</li> </ul> </li> <li>5G 3500 <ul> <li>Band 78 TDD</li> <li>3300 - 3800 MHz (Luxembourg: 3400 - 3800 MHz)</li> </ul> </li> </ul> <p><br> Two sensor have been used: The MVG EME Spy Evolution and a sensor developed by IMEC/University of Ghent.</p> <ul> <li>The MVG Spy Evolution sensor is able to measure all of the requested frequency bands as defined by the standard.</li> <li>The IMEC/University of Ghent sensor is only able to measure the LTE 800, GSM 900, GSM/LTE 1800 bands as defined by the standard.<br> In the 5G 3500 band it is only able to measure the range of 3550-3700 MHz (3465-3785 MHz within a -5db response).</li> </ul> <p>The datasets of the ZIP file has following structure:</p> <ul> <li>measurements: <ul> <li>the files of the measurements as provided by the sensor or application</li> <li>combined file of measurements in case the measurements have been split into several parts</li> <li>potentially analysis files of the measurements </li> </ul> </li> <li>pictures: <ul> <li>pictures of the antennas</li> <li>pictures of the sensor</li> <li>pictures of the location of the sensor</li> </ul> </li> <li>Readme.txt: <ul> <li>Used time-zone in the tables</li> <li>Used units in the tables</li> <li>Calculation of the total values in the tables</li> <li>Used labels of the the frequency bands</li> <li>Used sensor (MVG EME Spy Evolution or IMEC/University of Ghent)</li> <li>Locations of the target antennas</li> <li>Potentially location of the fixed sensor</li> </ul> </li> </ul>
5G-EMIT Project: EMF measurements of 2G/3G/4G/5G frequency bands captured with a MVG EME Spy Evolution sensor while walking in LOS and NLOS to two antennas through the Esch-Belval Area, Luxembourg (2022-10-17)
<p>During the 5G-EMIT project, EMF measurements of relevant mobile frequency bands have been taken at various sites around known antennas.</p> <p>Focus was in measuring the the following standard frequency bands:</p> <ul> <li>5G 700 <ul> <li>Band 28 FDD down</li> <li>758 - 803 MHz (Luxembourg: 758 - 788 MHz)</li> </ul> </li> <li>LTE 800 <ul> <li>Band 20 FDD down<br> 791 - 821 MHz</li> </ul> </li> <li>GSM 900 <ul> <li>Band 8 FDD down</li> <li>925 - 960 MHz</li> </ul> </li> <li>GSM/LTE 1800 <ul> <li>Band 3 FDD down</li> <li>1805 - 1880 MHz</li> </ul> </li> <li>UMTS 2100 <ul> <li>Band 1 FDD down</li> <li>2110 - 2170 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 38 TDD</li> <li>2570 - 2620 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 7 FDD down</li> <li>2620 - 2690 MHz</li> </ul> </li> <li>5G 3500 <ul> <li>Band 78 TDD</li> <li>3300 - 3800 MHz (Luxembourg: 3400 - 3800 MHz)</li> </ul> </li> </ul> <p><br> Two sensor have been used: The MVG EME Spy Evolution and a sensor developed by IMEC/University of Ghent.</p> <ul> <li>The MVG Spy Evolution sensor is able to measure all of the requested frequency bands as defined by the standard.</li> <li>The IMEC/University of Ghent sensor is only able to measure the LTE 800, GSM 900, GSM/LTE 1800 bands as defined by the standard.<br> In the 5G 3500 band it is only able to measure the range of 3550-3700 MHz (3465-3785 MHz within a -5db response).</li> </ul> <p>The datasets of the ZIP file has following structure:</p> <ul> <li>measurements: <ul> <li>the files of the measurements as provided by the sensor or application</li> <li>combined file of measurements in case the measurements have been split into several parts</li> <li>potentially analysis files of the measurements </li> </ul> </li> <li>pictures: <ul> <li>pictures of the antennas</li> <li>pictures of the sensor</li> <li>pictures of the location of the sensor</li> </ul> </li> <li>Readme.txt: <ul> <li>Used time-zone in the tables</li> <li>Used units in the tables</li> <li>Calculation of the total values in the tables</li> <li>Used labels of the the frequency bands</li> <li>Used sensor (MVG EME Spy Evolution or IMEC/University of Ghent)</li> <li>Locations of the target antennas</li> <li>Potentially location of the fixed sensor</li> </ul> </li> </ul> <p> </p>
5G-EMIT Project: EMF measurements of 2G/3G/4G/5G frequency bands captured with a MVG EME Spy Evolution sensor while walking in LOS and NLOS to several antennas through Luxembourg Center, Luxembourg (2023-04-06)
<p>During the 5G-EMIT project, EMF measurements of relevant mobile frequency bands have been taken at various sites around known antennas.</p> <p>Focus was in measuring the the following standard frequency bands:</p> <ul> <li>5G 700 <ul> <li>Band 28 FDD down</li> <li>758 - 803 MHz (Luxembourg: 758 - 788 MHz)</li> </ul> </li> <li>LTE 800 <ul> <li>Band 20 FDD down<br> 791 - 821 MHz</li> </ul> </li> <li>GSM 900 <ul> <li>Band 8 FDD down</li> <li>925 - 960 MHz</li> </ul> </li> <li>GSM/LTE 1800 <ul> <li>Band 3 FDD down</li> <li>1805 - 1880 MHz</li> </ul> </li> <li>UMTS 2100 <ul> <li>Band 1 FDD down</li> <li>2110 - 2170 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 38 TDD</li> <li>2570 - 2620 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 7 FDD down</li> <li>2620 - 2690 MHz</li> </ul> </li> <li>5G 3500 <ul> <li>Band 78 TDD</li> <li>3300 - 3800 MHz (Luxembourg: 3400 - 3800 MHz)</li> </ul> </li> </ul> <p><br> Two sensor have been used: The MVG EME Spy Evolution and a sensor developed by IMEC/University of Ghent.</p> <ul> <li>The MVG Spy Evolution sensor is able to measure all of the requested frequency bands as defined by the standard.</li> <li>The IMEC/University of Ghent sensor is only able to measure the LTE 800, GSM 900, GSM/LTE 1800 bands as defined by the standard.<br> In the 5G 3500 band it is only able to measure the range of 3550-3700 MHz (3465-3785 MHz within a -5db response).</li> </ul> <p>The datasets of the ZIP file has following structure:</p> <ul> <li>measurements: <ul> <li>the files of the measurements as provided by the sensor or application</li> <li>combined file of measurements in case the measurements have been split into several parts</li> <li>potentially analysis files of the measurements </li> </ul> </li> <li>pictures: <ul> <li>pictures of the antennas</li> <li>pictures of the sensor</li> <li>pictures of the location of the sensor</li> </ul> </li> <li>Readme.txt: <ul> <li>Used time-zone in the tables</li> <li>Used units in the tables</li> <li>Calculation of the total values in the tables</li> <li>Used labels of the the frequency bands</li> <li>Used sensor (MVG EME Spy Evolution or IMEC/University of Ghent)</li> <li>Locations of the target antennas</li> <li>Potentially location of the fixed sensor</li> </ul> </li> </ul>
Data from: Global change in brain state during spontaneous and forced walk in Drosophila is composed of combined activity patterns of different neuron classes
<p><span>Movement-correlated brain activity has been found across species and brain regions. Here, we used fast whole-brain lightfield imaging in adult <em>Drosophila </em>to investigate the relationship between walk and brain-wide neuronal activity. We observed a global change in activity that tightly correlated with spontaneous bouts of walk. While imaging specific sets of excitatory, inhibitory, and neuromodulatory neurons highlighted their joint contribution, spatial heterogeneity in walk- and turning-induced activity allowed parsing unique responses from subregions and sometimes individual candidate neurons. For example, previously uncharacterized serotonergic neurons were inhibited during walk. While activity onset in some areas preceded walk onset exclusively in spontaneously walking animals, spontaneous and forced walk elicited similar activity in most brain regions. These data suggest a major contribution of walk and walk-related sensory or proprioceptive information to global activity of all major neuronal classes.</span></p>
Electroretinogram data and thermographic data from walking and sitting bumblebees
<p>The behavioral state of animals has profound effects on neuronal information processing. Locomotion changes the response properties of visual interneurons in the insect brain, but it is still unknown if it also alters the response properties of photoreceptors. Photoreceptor responses become faster at higher temperatures. It has therefore been suggested that thermoregulation in insects could improve temporal resolution in vision, but direct evidence for this idea has so far been missing. Here, we compared electroretinograms from the compound eyes of tethered bumblebees that were either sitting or walking on an air supported ball. We found that the visual processing speed strongly increased when the bumblebees were walking. By monitoring the eye temperature during recording, we saw that the increase in response speed was in synchrony with a rise in eye temperature. By artificially heating the head, we show that the walking-induced temperature increase of the visual system is sufficient to explain the rise in processing speed. We also show that walking accelerates the visual system to the equivalent of a 14-fold increase in light intensity. We conclude that the walking-induced rise in temperature accelerates the processing of visual information – an ideal strategy to process the increased information flow during locomotion.</p>
Рис. 1. ПреΔпочтитеΛьное отношение паукообразных (1 – Galeodes araneoides, 2 – Lycosa praegrandis, 3 – Mesobuthus eupeus) к объектам питания по способу переΔвижения жертвы: I – Λетающие; II – прыгающие; III – бегающие; IV – хоΔящие; V – поΛзающие; VI – маΛопоΔвижные; VII – непоΔвижные. Fig. 1. Preferred attitude of arachnids (1 – Galeodes araneoides, 2 – Lycosa praegrandis, 3 – Mesobuthus eupeus) to food objects by the method of movement of pray: I – flying; II – jumping; III – running; IV – walking; V – crawling; VI – sluggish; VII – motionless. in Comparison of trophic spectra and hunting strategies of some large arachnids (Arachnida: Scorpiones, Solifugae, Aranei) in semi-desert biocenoses of Gobustan (Eastern Azerbaijan)
Рис. 1. ПреΔпочтитеΛьное отношение паукообразных (1 – Galeodes araneoides, 2 – Lycosa praegrandis, 3 – Mesobuthus eupeus) к объектам питания по способу переΔвижения жертвы: I – Λетающие; II – прыгающие; III – бегающие; IV – хоΔящие; V – поΛзающие; VI – маΛопоΔвижные; VII – непоΔвижные. Fig. 1. Preferred attitude of arachnids (1 – Galeodes araneoides, 2 – Lycosa praegrandis, 3 – Mesobuthus eupeus) to food objects by the method of movement of pray: I – flying; II – jumping; III – running; IV – walking; V – crawling; VI – sluggish; VII – motionless.
"I made the recording because Iam an amateur recording engineer and also work for a radio station. At the time, Iwas researching for a religious programme, for the radio and by pure chance and good luck, Iwas in the centre of York at the time the street preacher was there. Iam building up a personal library of 'ambient sounds' to use on various radio shows as 'sound effects'. The recording was taken outside St Helen's Church in St Helen's Square, in the centre of York. There was a fairly large crowd walking about, shopping. It was a Saturday. Some people were standing and listening to the man, some were mocking him, others didn't even notice. It was a sunny day, with a slight wind. St Helen's square is a large 'meeting place' for people with seats, flowers and usually musicians. I live in the centre of York and hear a lot of very interesting sounds there, everything from busking musicians, to many foreign languages, church bells, animals and much more. Ireally liked the recording of the preacher as it is quite clear that he passionately believes what he is saying. He was unaware that Iwas recording him. Iwish Ihad captured his whole sermon. He, and other members of his church visit the centre of York quite often, and preach there. Idon't know the name of his church." [Jools/vedas]19 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"I made the recording because Iam an amateur recording engineer and also work for a radio station. At the time, Iwas researching for a religious programme, for the radio and by pure chance and good luck, Iwas in the centre of York at the time the street preacher was there. Iam building up a personal library of 'ambient sounds' to use on various radio shows as 'sound effects'. The recording was taken outside St Helen's Church in St Helen's Square, in the centre of York. There was a fairly large crowd walking about, shopping. It was a Saturday. Some people were standing and listening to the man, some were mocking him, others didn't even notice. It was a sunny day, with a slight wind. St Helen's square is a large 'meeting place' for people with seats, flowers and usually musicians. I live in the centre of York and hear a lot of very interesting sounds there, everything from busking musicians, to many foreign languages, church bells, animals and much more. Ireally liked the recording of the preacher as it is quite clear that he passionately believes what he is saying. He was unaware that Iwas recording him. Iwish Ihad captured his whole sermon. He, and other members of his church visit the centre of York quite often, and preach there. Idon't know the name of his church." [Jools/vedas]19
"I'm something of an untrained, unofficial cultural anthropologist myself. Ihave a business interviewing people to capture their personal histories. I'm always interested how people fit into their world and how they affect their world. I'm a graphic designer who works in the same building as the printing presses that I recorded. Iwalk past the presses every day on my way to talk to the folks in the prepress department. I'm on friendly but not drinking terms with the pressmen. I'm a friend with the prepress manager. Three Heidelberg presses are installed side by side in an open warehouse-like room. The presses are about twenty feet long and about five feet high. With their series of four humps or mounds where each printing cylinder is located, the presses remind one of giant, gray, mechanical caterpillars. Each press has a cyan cylinder, a magenta cylinder, a yellow cylinder and a black cylinder – so the humps are brightly colored. The presses are well lit by banks of fluorescent lights hanging from the ceiling over each press. When you walk into the press room you hear the sound of rock music blaring from a boom box radio mixed with the general din of the presses. It is only when you walk up to a press like Idid for the recordings that you really start to hear the individual strains of clicking, clacking and mechanical, syncopated chattering. When I made my recordings I was intrigued by the subtle variations in the sounds produced by these machines that aren't apparent when you first walk through the door. The pressmen were kind enough to allow me to walk right up to the presses and poke my microphone quite close to the rotating press cylinders. Iuse a Danish Pro Audio microphone about the size of a pencil eraser. An extremely sensitive mic with the capacity for capturing loud sounds such as the presses up close. Rotating the mic to one side or the other focused on the unique sounds coming from one cylinder or the other." [Kevin/KMerrell]18 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"I'm something of an untrained, unofficial cultural anthropologist myself. Ihave a business interviewing people to capture their personal histories. I'm always interested how people fit into their world and how they affect their world. I'm a graphic designer who works in the same building as the printing presses that I recorded. Iwalk past the presses every day on my way to talk to the folks in the prepress department. I'm on friendly but not drinking terms with the pressmen. I'm a friend with the prepress manager. Three Heidelberg presses are installed side by side in an open warehouse-like room. The presses are about twenty feet long and about five feet high. With their series of four humps or mounds where each printing cylinder is located, the presses remind one of giant, gray, mechanical caterpillars. Each press has a cyan cylinder, a magenta cylinder, a yellow cylinder and a black cylinder – so the humps are brightly colored. The presses are well lit by banks of fluorescent lights hanging from the ceiling over each press. When you walk into the press room you hear the sound of rock music blaring from a boom box radio mixed with the general din of the presses. It is only when you walk up to a press like Idid for the recordings that you really start to hear the individual strains of clicking, clacking and mechanical, syncopated chattering. When I made my recordings I was intrigued by the subtle variations in the sounds produced by these machines that aren't apparent when you first walk through the door. The pressmen were kind enough to allow me to walk right up to the presses and poke my microphone quite close to the rotating press cylinders. Iuse a Danish Pro Audio microphone about the size of a pencil eraser. An extremely sensitive mic with the capacity for capturing loud sounds such as the presses up close. Rotating the mic to one side or the other focused on the unique sounds coming from one cylinder or the other." [Kevin/KMerrell]18
"I was on vacation in Mala, living in a self-catering holiday cottage, together with my girlfriend (we're together for 11 years now), recovering from a heavy workload in the second half of 2008. We were sitting outside, probably sipping a beer, when we heard the sound of bells approaching. Stepping on the stones that enclose the little forecourt of the cottage, we could just see the goat herd being driven by. Idashed for my R09 (recording equipment) to get that impression – but too slowly too late, it seemed, the herd had disappeared and with it the sound. When Iwas about to pack my R09 again the sound appeared to come back, so Idashed down the driveway, just in time to see the herd pass, and then Ifollowed it a couple of hundred meters, walking behind the herd, trying not to breathe or make stepping sounds, eventually, when dogs started barking and a car approached from behind, I stopped and let the goats go on, the car passes, honks ... and Icut the recording and walk back to the cottage." [Peter/ptroxler]13 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"I was on vacation in Mala, living in a self-catering holiday cottage, together with my girlfriend (we're together for 11 years now), recovering from a heavy workload in the second half of 2008. We were sitting outside, probably sipping a beer, when we heard the sound of bells approaching. Stepping on the stones that enclose the little forecourt of the cottage, we could just see the goat herd being driven by. Idashed for my R09 (recording equipment) to get that impression – but too slowly too late, it seemed, the herd had disappeared and with it the sound. When Iwas about to pack my R09 again the sound appeared to come back, so Idashed down the driveway, just in time to see the herd pass, and then Ifollowed it a couple of hundred meters, walking behind the herd, trying not to breathe or make stepping sounds, eventually, when dogs started barking and a car approached from behind, I stopped and let the goats go on, the car passes, honks ... and Icut the recording and walk back to the cottage." [Peter/ptroxler]13
Efficacy and Safety of a Hospital Walking Program for Older Adults
ClinicalTrials.gov study NCT00715962. IPD Sharing: YES. Countries: 1. Publications: 1.
Reproducibility of 6 Minute Walk Tests for Oxygen Desaturation
ClinicalTrials.gov study NCT00740220. IPD Sharing: UNDECIDED. Countries: 1. Publications: 34.
Implementing a Hospital-Based Walking Program (STRIDE): Function QUERI 2.0
ClinicalTrials.gov study NCT04868656. IPD Sharing: YES. Countries: 1. Publications: 2.
Walking or hanging: the role of habitat use for body shape evolution in lacertid lizards
Open the record for dataset details and reuse information.
Data from: Global change in brain state during spontaneous and forced walk in Drosophila is composed of combined activity patterns of different neuron classes
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ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.