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1,711 results for “housing”
Seasonal high-frequency measurements of discharge, water temperature, and specific conductivity from House Stream at H2, McMurdo Dry Valleys, Antarctica (1993-2012)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. This package contains data pertaining to continuous monitored water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this metadata record describes the hydrology dataset for the McMurdo Dry Valleys' House Stream at the H2 streamgage, located in the Hoare Basin of Taylor Valley. Measurements commenced during the 1993-94 austral summer and continued through the end of the 2011-12 austral summer. The H2 streamgage was removed in December 2012 due to rising lake levels.
Daily summarized seasonal measurements of discharge, water temperature, and specific conductivity from House Stream at H2, McMurdo Dry Valleys, Antarctica (1993-2012)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. This package contains data pertaining to continuous monitored water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this metadata record describes the daily hydrological summaries for the McMurdo Dry Valleys' House Stream at the H2 streamgage, located in the Hoare Basin of Taylor Valley. Measurements commenced during the 1993-94 austral summer and continued through the end of the 2011-12 austral summer. The H2 streamgage was removed in December 2012 due to rising lake levels.
MINIATURA 6 Housing decisions, behavioral aspects of choices, price expectations and anchoring effect - Polsh case study
<p>The data was created as a result of a survey conducted in accordance with the guidelines: - the survey questionnaire consisted of approximately 30 questions and a form, - the surveyed population was defined as 1,000 households living in a large Polish city (over 450,000 inhabitants), quota selection based on the number of city inhabitants, - CAWI method (online), - completion date: 1 week. The survey was parameterized. Part of the sample is a control trial, part is an experimental trial.</p><p>Dane powstały w wyniku przeprowadzonej ankiety zgodnie z wytycznymi: - kwestionariusz badania składał się z ok. 30 pytań oraz metryczki, - badana zbiorowość określono na 1000 gospodarstw domowych zamieszkałych w dużym mieście Polski (powyżej 450 tys. ludności), dobór kwotowy na podstawie liczby mieszkańców miast, - badanie metodą CAWI (on-line), - termin realizacji 1 tydzień. Ankieta byłą sparametryzowana. Część próby stanowi próba kontrolna, część próba eksperymentalna. </p>
Household information for houses in Kasungu district participating in the Maladrone study, 2021
<p>Each row in the dataset contains information on each household participating in the Maladrone study, 2021. The information is as follows:</p><p>uniqueid: Unique ID assigned to the household, comprising of two letters corresponding to the community (ML, CK, CP) and the study house number.</p><p>under_5: Number of people under the age of 5 who live in the house at the time of asking.</p><p>over_5: Number of people over the age of 5 who live in the house at the time of asking.</p><p>under_5<i>_</i>rwt: Number of people under the age of 5 who usually sleep in the room where the CDC light trap was set.</p><p>over_5<i>_</i>rwt: Number of people over the age of 5 who usually sleep in the room where the CDC light trap was set.</p><p>number_mosquito<i>_</i>nets: Number of mosquito nets in the household.</p><p>mosquito_nets_rwt: Number of mosquito nets usually used in the room where the CDC light trap was set.</p><p>under_5<i>_</i>nets: Number of under 5s in the household who usually slept under a net.</p><p>over_5_nets: Numer of over 5s in the household who usually slept under a net.</p><p>unde_5_nets_rwt: Number of under 5s in the household who usually slept under a net in the room where the CDC light trap was set.</p><p>over_5_nets_rwt: Number of under 5s in the household who usually slept under a net in the room where the CDC light trap was set.</p><p>roof_type: Main material used for the roof of the house. Choices were iron sheet, thatched or tiled.</p><p>eaves: Whether the eaves of the house were open, partally open, or closed.</p><p>windows: Whether the windows of the house were open, partally open, or closed.</p>
Acoustics, Audibility and Political Culture in the House of Commons, 1800-34
<p>This dataset includes the auralization results obtained from the acoustic models of the House of Commons in 1800-34, as part of the research with the homonymous paper submitted in the special issue "Parliamentary History Journal" (first submission September 2023). </p><p>The auralization results represent the perceived result from the acoustic models for the two discussed scenarios (full-occupied and half-full-occupied House of Commons). We present the results from 3 different speakers at 5 listening positions as shown in the images. </p><p>The anechoic sample is an excerpt of Henry Beaufoy's speech to the House of Commons in 1792 on the subject of the slave trade, performed by John Cooper (co-author) in the anechoic chamber at the Audiolab, University of York. The perceived differences and similarities of the recorded/simulated spaces as heard in these audio files help to further verify the results of the acoustic parameters presented in this paper.</p>
Immunoglobulin G: SEC-SAXS experiment using in house SAXS instrument with in situ UV-Vis
<p>SEC-SAXS experiment using in house SAXS instrument</p> <p>Sample: Immunoglobuline G<br>Buffer: 50mM Tris, 50 mM NaCl, pH 7.6</p> <table> <tbody> <tr> <td><strong>File Name</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>SAXS_raw.zip</td> <td>Raw, unreduced data (2D images) in HDF5 format</td> </tr> <tr> <td>SAXS_reduced.zip</td> <td>SAXS data, azimutaly reduced (1D curves). Q-vaules are in 1/nm</td> </tr> <tr> <td>SAXS_UV_raw.zip</td> <td>Raw UV-Vis absorption data collected using in-situ spectrometer</td> </tr> <tr> <td>SAXS_UV_processed.zip</td> <td>UV-Vis data collected using in-situ spectrometer. Absorbance at 280nm extracted as a time series</td> </tr> <tr> <td>HPLC_raw.zip</td> <td>Data from HPLC system natively exported from control software (Unicorn)</td> </tr> <tr> <td>HPLC_extracted.zip</td> <td>Data from HPLC system exported to CSV</td> </tr> <tr> <td>DS11_fractions.zip</td> <td>UV-Vis absorption data collected usig micro volume spectrometer (DeNovix DS-11) on fractions collected using fraction collector.</td> </tr> </tbody> </table> <p> </p>
The price of safety: Order picking in warehouses with in-house traffic regulations (Supplementary material)
<p>In what follows, you will find the code and results of the paper:</p> <p>"The price of safety: Order picking in warehouses with in-house traffic regulations" published in IISE Transactions.</p> <p> </p> <p>List of files:</p> <p>- Zip file: "Order Picking Problem with in-house traffic regulations" containing C# Code used to generate solutions for all safety policies</p> <p>- Result.csv containing all generated results</p> <p>- createPlots.py containing code to generate figures and tables from the paper</p> <p> </p> <p>The C# code is object-oriented and contains a Main function in the Program.cs file that converts the Example.OPP file with the InstanceReaders to an OPPInstance and uses the Solve function from either the DynamicProgrammic.cs or RuralPostman.cs file to solve the OPPInstance with all the TrafficRegulations as described in the paper.</p> <p> </p> <p>The Example.OPP defines the Depot location (0: decentral, 1: central), AisleLength, i.e. the number of pick positions within each aisle, and other dimensions of the warehouse. Finally, the items are defined by their picking aisle, shelf, position in the shelf, and region.</p> <p> </p> <p>The dynamic program (DP) described in the paper is implemented in DynamicProgrammic.cs. A HashSet of DPNode represents each layer of the DP. A DPNode basically consists of components, nodeDegrees, and a value. Depending on the TrafficRegulation the nodeDegrees are either NodeDegreeClassic, i.e. Null, Uneven, or Even, or NodeDegreeInAndOutDifference, i.e. the difference of the in- and out-degree. To construct the solution at the end, the inEdge is also saved for each DPNode and the additional member depotIsConnected ensures that the depot is visited. The DPNodes in the next layer of the DP are created by the functions MakeNextLayerVertical and MakeNextLayerHorizontal by determining all possibleTransitions per node in the current layer and combining them into a newNode. Products are stored with their position on the shelves in the item list within a PickingAisle. All vertical possibleTransitions are determined in a preprocessing step depending on the TrafficRegulations and are saved within the respective PickingAisle. All horizontal possibleTransitions are determined during the DP with specific functions depending on the TrafficRegulation in HorizontalTransition.cs. When the layers are created, the best feasible DPNode per layer is saved and the best one, i.e. the one with the lowest value, is returned at the end.</p> <p> </p> <p>The paper describes that certain safety policies cannot be solved with the DP. These OPPInstances are solved as a RuralPostman problem (RPP) by generating a Graph that adopts the rectangular structure of the warehouse. Within the Graph, requiredEdges are determined that correspond to PickingAisles containing items. The resulting RPP can be transformed into a traveling salesman problem (TSP) as described by applying an arc-oriented Dijkstra or, in certain cases, to a generalized TSP (GTSP) where one of the two directed edges must be visited. If necessary, the GTSP is transformed to an asymmetric TSP in GTSPInstance and then solved with TSPSolver using LKH-3.exe (Helsgaun 2017, http://webhotel4.ruc.dk/~keld/research/LKH-3/). To use LKH-3.exe, the TSP instance is saved in a TSPLIB format and a parameter file (.par) for LKH and a solution file (.sol) are created in the bin folder. These files are named according to the name specified in the instance.Solve function, where one can also choose to save or delete these files afterward.</p> <p> </p> <p>For more information on LKH-3 see: Keld Helsgaun: An Extension of the Lin-Kernighan-Helsgaun TSP Solver for Constrained Traveling Salesman and Vehicle Routing Problems (Technical Report, Roskilde University, 2017)</p> <p> </p> <p>Evaluation.py</p> <p>A Python script that generates figures 8, 9, and 10 and tables 6, 7 and 8 (in csv-format) of the paper by processing data from Results.csv.</p> <p>It requires Results.csv to be in the same directory as the code.</p> <p>It also requires the following Python packages:</p> <p>- matplotlib</p> <p>- pandas</p> <p>- seaborn</p>
Barcelona House Pricing 24/10/2021
<p>El dataset creado proporciona la localización y las características principales (alquiler/venta, número de habitaciones, baños, metros cuadrados, barrio y precio) de un piso en Barcelona, a fecha 24/10/2021.</p>
The contribution of genetic and environmental effects to Bergmann's rule and Allen's rule in house mice
<p>Data associated with the manuscript, "The contribution of genetic and environmental effects to Bergmann's rule and Allen's rule in house mice".</p> <p><strong>Abstract</strong>: Distinguishing between genetic, environmental, and genotype-by-environment effects is central to understanding geographic variation in phenotypic clines. Two of the best-documented phenotypic clines are Bergmann's rule and Allen's rule, which describe larger body sizes and shortened extremities in colder climates, respectively. Although numerous studies have found inter- and intraspecific evidence for both ecogeographic patterns, we still have a poor understanding of the extent to which these patterns are driven by genetics, environment, or both. Here, we measured the genetic and environmental contributions to Bergmann's rule and Allen's rule across introduced populations of house mice (<em>Mus musculus domesticus</em>) in the Americas. First, we documented clines for body mass, tail length, and ear length in natural populations, and found that these conform to both Bergmann's rule and Allen's rule. We then raised descendants of wild-caught mice in the lab and showed that these differences persisted in a common environment and are heritable, indicating that they have a genetic basis. Finally, using a full-sib design, we reared mice under warm and cold conditions. We found very little plasticity associated with body size, suggesting that Bergmann's rule has been shaped by strong directional selection in house mice. However, extremities showed considerable plasticity, as both tails and ears grew shorter in cold environments. These results indicate that adaptive phenotypic plasticity as well as genetic changes underlie major patterns of clinal variation in house mice and likely facilitated their rapid expansion into new environments across the Americas.</p> <p>Supplemental data files are provided below.</p> <p>Code associated with the analysis of these data can be found on GitHub at <a href="https://github.com/malballinger/Ballinger_allenbergmann_AmNat_2021">https://github.com/malballinger/Ballinger_allenbergmann_AmNat_2021</a>.</p>
RookID: an annotated dataset of vocalisations produced by individually-identified rooks housed together in an outdoors aviary in France
<p>A dataset of annotated recordings of a captive colony of rooks, recorded in Strasbourg, France in 2020 and 2021. Each rook was individually identifiable with leg rings. All recordings were taken in the morning a few hours after sunrise, when the birds were most vocally active. The colony was housed outdoors, so other noises are present, including both biotic (most notably various birds, human voices, and other animals) and abiotic (mostly car and train noises).</p> <p>Audio files (.wav): recorded at 48 kHz, 16-bit using 1 to 3 Song Meter 4 recorders (Wildlife Acoustics). Each recorder had two microphone with different gains to maximise dynamic range. The files were then manually synchronised and merged into multichannel (2 to 6) files.</p> <p>Label files (.tsv): Labels corresponding to each recording (each pair has the same name), noting the time stamps and individual emitter for each vocalisation. A single observer annotated all the recordings. Only rook vocalisations from the captive colony were annotated, not other bird vocalisations or the various noises in the data. The annotations consist of tables with 5 columns: </p> <ul> <li>Source: the individual producing the vocalisation. Note that only the bird's name is indicated. "Inc" and "Pls" are special cases: the first was for when identity could not be determined, the second when multiple individuals vocalised at once in such a manner that individuals could not be separated</li> <li>Start: starting time point for the vocalisation, in seconds (determined as the earliest point when the vocalisation was heard on any channel)</li> <li>End: ending time point for the vocalisation, in seconds (determined as the last point when the vocalisation was head on any channel)</li> <li>Event: gives information for the bird's activity at the time of the vocalisation, but largely in abbreviated form. One particular case is "sing", which correspond to vocalisations part of a song bout (which are defined as sequences of different vocalisations separated by less than approximately 10 seconds).</li> <li>Comment: other observations regarding the vocalisation. These are usually not standardised compared to the Event column. One special case is for "Pls": the Comment column then bears information regarding the identity of the individuals involved.</li> </ul> <p> </p> <p>This dataset was used in our article "Acoustic detection and identification of individual rooks in field recordings using multi-task neural networks", to train neural networks to identify individual rooks. The dataset was therefore randomly split into train-validation-test datasets. For reproducibility, we provide the "splitting.csv" which contains the information pertaining to which files go in each dataset, and two scripts to do the split automatically.</p> <p>To do so: download and unpack the RookID folder somewhere on your computer, then download splitting.csv and either of the scripts to the same location. Both scripts will MOVE, not copy, the files to new folders corresponding to each dataset.</p> <ul> <li>with split_data.R: open the scrip in an RStudio environment, edit the out_path variable to the desired location, and run the script</li> <li>with split_data.py: run the following command line: python /path/to/split_data.py --out_path path/to/desired/location (note that the script will automatically create the necessary tree structure)</li> <li>Both scripts can be run without editing the out_path variables, in which case the new folders will be created at the same location</li> </ul> <p> </p> <p>For further information, see our code at <a href="https://gitlab.com/kimartin/rook-vocalisation-detection">https://gitlab.com/kimartin/rook-vocalisation-detection</a></p> <p>For any inquiries, please contact Killian Martin (<a href="mailto:killian.martin@ens-lyon.fr?subject=Inquiry%20about%20the%20RookID%20dataset">killian.martin@ens-lyon.fr</a>)</p>
A refined method for studying foraging behaviour and body mass in group-housed European starlings.
<p>Datasets and R script corresponding to the following manuscript:</p> <p>A refined method for studying foraging behaviour and body mass in group-housed European starlings.</p> <p>Laboratory experiments on passerine birds have been important for testing hypotheses regarding the effects of environmental variables on the adaptive regulation of body mass. However, previous work in this area has suffered from poor ecological validity and animal welfare due to the requirement to house birds individually in small cages to facilitate behavioural measurement and frequent catching for weighing. Here we describe the social foraging system, a novel technology that permits continuous collection of individual-level data on operant foraging behaviour and body mass from group-housed European starlings (<em>Sturnus vulgaris</em>). We demonstrate rapid acquisition of operant key pecking, followed by foraging and body mass data from two groups of six birds maintained on a fixed-ratio operant schedule under closed economy for 11 consecutive days. Birds gained 6.0 ± 1.2 g (mean ± sd) between dawn and dusk each day and lost an equal amount overnight. Individual daily mass gain trajectories were non-linear, with the rate of gain decelerating between dawn and dusk. Within-bird variation in daily foraging effort (key pecks) positively predicted within-bird variation in dusk mass. However, between-bird variation in mean foraging effort was uncorrelated with between-bird variation in mean mass, potentially indicative of individual differences in daily energy requirements. We conclude that the social foraging system delivers refined data collection and offers potential for improving our understanding of mass regulation in starlings and other species.<strong> </strong></p>
Houses for sale in the Salamanca and Villaverde district of Madrid in April 2022
<p>Dataset that contains data scraped from the websites of <a href="https://www.fotocasa.es/es/">Fotocasa</a> and <a href="https://www.idealista.com/">Idealista</a> between 4<sup>th</sup> and 7<sup>th</sup> April 2022 and it is meant only for academic purposes.</p> <p>Each record describes a house for sale in the Salamanca and Villaverde districts of Madrid by the following fields: id, url, title, location, price, m2, rooms, floor, num-photos, floor-plan, view3d, video, home-staging, description, photo_urls and source.</p> <p>The context of this project is the Data Science Master’s Degree of UOC (Universitat Oberta de Catalunya), specifically the subject Data Typology and Life Cycle’.</p>
A private house in 'Marea'/Philoxenite transformed into a monastic institution and other Christian hybrid buildings in the Mareotis region - additional illustrations
<p>Set of three documents on potsherds (ostraca) has been found in Philoxenite (Egypt). All three of the ostraca, M200249 (= Document A), M200250 (= Document B), and M200251 (= Document C) are preserved in their entirety, in the sense that the sherds, meant to serve as the canvas for the documents, were not broken when they were thrown out into the rubbish pit in the piscina.</p> <p>The photos uploaded here provide supplementary material for an article discussing the content of these ostraca. </p> <p> </p>
Housing development in Yinchuan
<p><strong>Coordinador del Seminario:</strong> Carlos A. Navarrete Ulloa.<br> <strong>Expositor</strong>: Briseida Corzo Rivera</p> <p><strong>Comité Ejecutivo PRONACE-Vivienda</strong></p> <ul> <li>Fernando Córdova Canela, Centro Universitario de Arte, Arquitectura y Diseño, Universidad de Guadalajara (UdeG).</li> <li>Francisco Javier Porras Sánchez, Instituto de Investigaciones Dr. José María Luis Mora.</li> <li>Gabriel Castañeda Nolasco, Universidad Autónoma de Chiapas (UNACH).</li> <li>Carlos A. Navarrete Ulloa, Centro Universitario de Tonalá, (UdeG).</li> </ul> <p>Exposición realizada en el marco del PRONACE Vivienda en el cual se comenta la lectura:</p> <p>Meng Wang, Aleksandra Krstikj y Hisako Koura (2017) Study on the housing supply and public programs impacts on the housing development in Yinchuan City, Western China. Journal of Architecture and Planning, 82, 469-476. <a href="https://doi.org/10.3130/aija.82.469">https://doi.org/10.3130/aija.82.469</a></p>
The institutional perspective on informal housing
<p><strong>Coordinador del Seminario:</strong> Carlos A. Navarrete Ulloa.<br> <strong>Expositor</strong>: Luis Adolfo Ortega Granados</p> <p><strong>Comité Ejecutivo PRONACE-Vivienda</strong><br> Fernando Córdova Canela, Centro Universitario de Arte, Arquitectura y Diseño, Universidad de Guadalajara (UdeG). Francisco Javier Porras Sánchez, Instituto de Investigaciones Dr. José María Luis Mora.<br> Gabriel Castañeda Nolasco, Universidad Autónoma de Chiapas (UNACH). Carlos A. Navarrete Ulloa, Centro Universitario de Tonalá, (UdeG).</p> <p>Exposición realizada en el marco del PRONACE Vivienda en el cual se comenta la lectura:</p> <p>Dekel. T. (2020) The Institutional Perspective on Informal Housing. Habitat International, 106, 102287 https://doi.org/10.1016/j.habitatint.2020.102287</p>
The rise of housing LAOG
<p><strong>Coordinador del Seminario</strong>: Carlos A. Navarrete Ulloa.</p> <p><strong>Expositor</strong>: Luis Adolfo Ortega Granados</p> <p><strong>Comité Ejecutivo PRONACE-Vivienda</strong></p> <ul> <li>Fernando Córdova Canela, Centro Universitario de Arte, Arquitectura y Diseño, Universidad de Guadalajara (UdeG).</li> <li>Francisco Javier Porras Sánchez, Instituto de Investigaciones Dr. José María Luis Mora.</li> <li>Gabriel Castañeda Nolasco, Universidad Autónoma de Chiapas (UNACH).</li> <li>Carlos A. Navarrete Ulloa, Centro Universitario de Tonalá, (UdeG).</li> </ul> <p>Exposición realizada en el marco del PRONACE Vivienda en el cual se comenta la lectura:</p> <p>Harris, R. & Godwin, A. (2007) The Rise of Housing in International Development: The Effects of Economic Discourse. Habitat International, 31(1), 1-11</p> <p><a href="http://dx.doi.org/10.1016/j.habitatint.2005.10.004">http://dx.doi.org/10.1016/j.habitatint.2005.10.004</a></p>
Social housing is good for everyone
<p><strong>Coordinador del Seminario:</strong> Carlos A. Navarrete Ulloa.<br> <strong>Expositor</strong>: Ramona Esmeralda Velázquez García<br> <strong>Comité Ejecutivo PRONACE-Vivien</strong>da</p> <ul> <li>Fernando Córdova Canela, Centro Universitario de Arte, Arquitectura y Diseño, Universidad de Guadalajara (UdeG).</li> <li>Francisco Javier Porras Sánchez, Instituto de Investigaciones Dr. José María Luis Mora.</li> <li>Gabriel Castañeda Nolasco, Universidad Autónoma de Chiapas (UNACH).</li> <li>Carlos A. Navarrete Ulloa, Centro Universitario de Tonalá, (UdeG).</li> </ul> <p>Exposición realizada en el marco del PRONACE Vivienda en el cual se comenta la lectura:</p> <p>Khalid, M. (2015). Social housing is good por everyone. A benefits-Cost analysis. In J. Silver & J. Brandon (Eds.), Poor Housing: A Silent Crisis. Fernwood Publishing </p>
HOUSE_2_09/30/22
Documentation material from the Mastic pilot of the Mingei project
FORTH_MASTIC_HOUSE_09/30/22
Documentation material from the Mastic pilot of the Mingei project
The dataset of Hong Kong Housing transaction records (1997-2018, after an incoming data quality processing)
<p>These detailed housing transaction records of over 2 million property rights entries in Hong Kong's property markets over the past 23 years (1997 - 2018).</p>
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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.