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9,302 results for “DETECT”
Extirpated species in Berlin, dates of last detections, habitats, and number of Berlin's inhabitants
<p>Species loss is highly scale-dependent, following the species-area relationship. We analysed spatio-temporal patterns of species' extirpation on a multitaxonomic level using Berlin, the capital city of Germany. Berlin is one of the largest cities in Europe and has experienced a strong urbanisation trend since the late 19th century. We expected species' extirpation to be exceptionally high due to the long history of urbanisation. Analysing regional Red Lists of Threatened Plants, Animals, and Fungi of Berlin (covering 9498 species), we found that 16 % of species were extirpated, a rate 5.9 times higher than at the German scale, and 47.1 times higher than at the European scale. Species' extirpation in Berlin is comparable to that of another German city with a similarly broad taxonomic coverage, but much higher than in regional areas with less human impact. The documentation of species' extirpation started in the 18th century and is well documented for the 19th and 20th centuries. We found an average annual extirpation of 3.6 species in the 19th century, 9.6 species in the 20th century, and the same number of extirpated species as in the 19th century were documented in the 21th century, despite the much shorter time period. Our results showed that species' extirpation is higher at small than on large spatial scales, and might be negatively influenced by urbanisation, with different effects on different taxonomic groups and habitats. Over time, we found that species' extirpation is highest during periods of high human alterations and is negatively affected by the number of people living in the city. But, there is still a lack of data to decouple the size of the area and the human impact of urbanisation. However, cities might be suitable systems for studying species' extirpation processes due to their small scale and human impact.</p>
Figure 2 in Detection of enteropathogens and research of pesticide residues in Lactuca sativa from traditional and agroecological fairs
Figure 2. Difenoconazole calibration curve.
Figure 1 in Detection of respiratory viruses and expression of inflammatory cytokines in patients with acute exacerbation chronic obstructive pulmonary disease in Mongolia China
Figure 1. Distribution of Viruses.
Dataset of paper "Real Driving Emissions—Event Detection for Efficient Emission Calibration"
<p>This dataset includes signal traces and resulting data used in the publication "Real Driving Emissions—Event Detection for Efficient Emission Calibration", MDPI Gases, 2024 (doi: 10.3390/gases4030010).</p> <p>The time trace data is available in a frequency of 1 Hz.</p> <p>The general vehicle specifications are listed below. For further information please refer to the paper.</p> <table> <tbody> <tr> <td> <p><strong>Criteria</strong></p> </td> <td> <p><strong>Value</strong></p> </td> <td> <p><strong>Criteria</strong></p> </td> <td> <p><strong>Value</strong></p> </td> </tr> <tr> <td> <p>Vehicle mass</p> </td> <td> <p>> 2000 kg</p> </td> <td> <p>Drivetrain</p> </td> <td> <p>All-wheel drive (AWD)</p> </td> </tr> <tr> <td> <p>Engine</p> </td> <td> <p>Inline 4 cylinder</p> </td> <td> <p>Gearbox</p> </td> <td> <p>Automatic Transmission (AT)</p> </td> </tr> <tr> <td> <p>Max. power</p> </td> <td> <p>> 180 kW</p> </td> <td> <p>EATS</p> </td> <td> <p>Three-way catalytic converter (TWC) and Gasoline particulate filter (GPF)</p> </td> </tr> <tr> <td> <p>Max. torque</p> </td> <td> <p>> 300 Nm</p> </td> <td> <p>Fuel</p> </td> <td> <p>Gasoline</p> </td> </tr> </tbody> </table> <p> </p> <p>Description of files:</p> <ul> <li><strong>Data_Measurement_NOx_Events_HistoryInfluence</strong>: Profile of examplary cycle in 1 Hz with time [s], speed [km/h], NOx mass flow [g/s], downstream lambda sensor voltage (U_HEGO) [V], flag fuel cut-off (b_fco) [-], distance specific NOx intensity for window layout (20 %, 50 % and 80 % History) [g/km], flag for critical window intensity (b_SE for 20 %, 50 % and 80 % history) [-]. (Refers to figure 9 and 10)</li> <li><strong>Data_NOx_RelativePositionOfEmissionIntensityPeak</strong>: Map of relative position of NOx intensity peak within the detected event based on the window layout. The position is displayed over the Window Duration [s] in rows and the History Share [%] in columns. (Refers to figure 8)</li> <li><strong>Data_PN_RelativePositionOfEmissionIntensityPeak</strong>: Map of relative position of PN intensity peak within the detected event based on the window layout. The position is displayed over the Window Duration [s] in rows and the History Share [%] in columns. (Refers to figure 7)</li> <li><strong>Data_NOx_WindowDuration_NumberEvents_AverageDuration_20percHistory</strong>: Overview of statistics for number of detected events in an examplary cycle and average duration of these events for different window durations and a window layout that considers 20 % history for NOx emissions. (Refers to figure 6)</li> <li><strong>Data_PN_WindowDuration_NumberEvents_AverageDuration_20percHistory</strong>: Overview of statistics for number of detected events in an examplary cycle and average duration of these events for different window durations and a window layout that considers 20 % history for PN emissions. (Refers to figure 5)</li> <li><strong>Data_Threshold_Statistics_NOx</strong>: Data for statistical evaluation of the threshold impact for event detection for the NOx emissions. The data are binned at a step size of 0.0001 g/km from 0 to 0.06 g/km (Threshold). For these bins, the detectable share of samples (relative) is listed for only urban samples, rural samples, motorway samples and total number of samples. (Refers to figure 4)</li> <li><strong>Data_Threshold_Window_Speed_Distance_Intensity_NOx</strong>: Data for threshold analysis. Contains the information of the analysis windows for each measurement sample that show a distance of > 0.002 km. For each window, the average window speed [km/h], the travelled window distance [km] the distance specific NOx emissions [g/km] and the integrated NOx emissions within this window [g] are displayed. (Refers to figure 3)</li> <li><strong>Overview_FinalEvent_Duration</strong>: Contains a list with the number of events and the duration of the events for the final event detection results with the named threshold values</li> <li><strong>Overview_FinalEvent_Profiles</strong>: Contains a list with the explicit data of the final event set. The time based data are displayed in a 1 Hz frequency over rows. The first column names the ID of the event, then the time in the cycle [s], the vehicle speed [km/h], the flag fuel cut-off (b_fco) [-], the downstream lambda sensor voltage (U_HEGO) [V], the Lambda value [-] and the NOx mass flow [g/s] are displayed.</li> </ul>
Dataset for Enantioselective molecular Detection by Surface-Enhanced Raman Scattering at Chiral Gold Helicoids on Grating Surface
<p>This is a dataset for a paper "Enantioselective molecular Detection by Surface-Enhanced Raman Scattering at Chiral Gold Helicoids on Grating Surface". All details about the data are included in the readme file.</p>
Data from: Early detection of human impacts using acoustic monitoring: an example with forest elephants
<p>The impacts of human activities and climate change on animal populations often take considerable time before they are reflected in typical measures of population health such as population size, demography, and landscape use. Earlier detection of such impacts could enhance the effectiveness of conservation strategies, particularly for species with slow population growth. Passive acoustic monitoring is increasingly used to estimate occupancy and population size, but this tool can also monitor subtle shifts in behavior that might be early indicators of changing impacts. Here we use data from an acoustic grid, monitoring 1250 km<sup>2</sup> of forest in the northern Republic of Congo, to study how forest elephants (<em>Loxodonta cyclotis</em>) assess the risk of poaching across a landscape that includes a national park as well as active and inactive logging concessions. By quantifying emerging patterns of behavior at the population level, arising from individual-based decisions, we gain an understanding of how elephants perceive their landscape along an axis of human disturbance. Forest elephants in relatively undisturbed forests are active nearly equally day and night. However, they become more nocturnal when exposed to a perceived risk such as poaching. We assessed elephant perception of risk by monitoring changes in the likelihood of nocturnal activity relative to differing levels of human activity. We show that logging is perceived to be a risk on short-time and small spatial scales but with little effect on animal density. However, risk avoidance persisted in areas with relatively easy access to poachers and in more open habitats where poaching has historically been concentrated. Increased nocturnal activity is a common response in many animals to human intrusion on the landscape. Provided a species is acoustically active, passive acoustic monitoring can measure changes in human impact at the early stages of such change, informing management priorities.</p>
simulated datasets for evaluating polygenic detection methods
<p>This dataset contains simulation files corresponding to a combination of each demographic model (1/2/3), environment (linear/quadratic), selection duration (200/400/600/800/1000), and simulation replicate(1-20). This resulted in 600 simulation files with 600 unique combinations of demographic models, environments, selection durations, and simulation replicates. For each individual in the genotype data file, we have the files containing the values of selective pressure(linear and quadratic environment) in the metadata folder. </p> <p>The variant position are 1-based which is default SLiM output. To compare the results with the causal loci user must make the positions 0-based (i.e. POS-1). The details are provided in a github tutorial.</p> <p>Please refer to the documentation for a detailed description of the files and folder structure.</p> <p>The article describing the simulated data and its application is accepted for publication in Nucleic Acids Research (https://doi.org/10.1093/nar/gkae1027).</p>
Fig. 2 in Detection of the invasive western conifer seed bug Leptoglossus occidentalis Heidemann, 1910 (Heteroptera: Coreidae: Coreinae) in Chile.
Fig. 2.- Leptoglossus occidentalis, hemelytral ivory veins, detail.
Fig. 1 in Detection of the invasive western conifer seed bug Leptoglossus occidentalis Heidemann, 1910 (Heteroptera: Coreidae: Coreinae) in Chile.
Fig. 1.- Leptoglossus occidentalis, living specimen in Valparaíso, Chile.
Dataset and code for article "Expanded detection and impact of BAP1 alterations in cancer"
<p>Dataset and code for article titled "Expanded detection and impact of <em>BAP1 </em>alterations in cancer". Includes Singularity image and Nextflow code for somatic variant calling pipeline. Also includes figure code (qmd, html, and pdf formats), analysis code (qmd), and public raw and processed data of reasonable file size. Controlled-access data and large file size data (e.g., combined dataset of pan-cancer individual RNA-seq files) must be downloaded separately from the TCGA Genomic Data Commons or PanCanAtlas Publication pages. R code written in R version 4.4.1 and provided with R environment (renv) information.</p>
Sample Dataset for Automated Detection of Cheating Codes
<p><span>This project includes a resampled dataset and statistical code for analyzing various subcategories of cheating codes. The dataset is derived from an initial collection of SQL queries from HackerRank (</span><span><a href="../record/8199741">https://zenodo.org/record/8199741</a></span><span>). Originally, the dataset contained 5,767,890 correct codes and only 1,992 cheating codes. To address the issue of data imbalance, we implemented a resampling strategy to achieve a more balanced data distribution. Specifically, undersampling techniques were used to reduce the number of correct codes while retaining all cheating codes. From 22 programming problems, we randomly selected 20,000 correct codes from each problem. This approach aimed to balance data representation across different problem types, enhancing the model’s adaptability and generalization. After resampling, the dataset consisted of 440,000 correct codes and 1,992 cheating codes.</span></p>
Dataset for "AACVD Synthesized Tungsten Oxide-NWs loaded with Osmium oxide as Gas Sensor Array: Enhancing Detection with PCA and ANNs"
<p>Dataset with the gas senisng mesurements for Osmium oxide decorated tunsten oxide gas sensors</p>
Fig. 3 in Evidence of Ehrlichia chaffeensis in Argentina through molecular detection in marsh deer (Blastocerus dichotomus)
Fig. 3. Dead marsh deer with high tick burden.
Codes, Catalogues and Data for "Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Seismicity from a Downhole Array"
<p><strong>Codes, Catalogues and Data available for:</strong> <br>"Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Seismicity from a Downhole Array"</p> <p><strong>Catalog</strong> folder: Contains the CMM (beam-forming based) event catalogue as well as event and station information for the PNR-1z site.</p> <p><strong>Classification Test</strong> folder: Jupyter notebooks that run the classification tests and mseed input data of isolated phases (P, S, Noise).</p> <p><strong>DL_model_catalogues</strong> folder: Contains full catalogues for each DL phase picker (GPD, U-GPD, EQT and PhaseNet) and the LinMEF-filtered catalogues.</p> <p><strong>Model_run_docs</strong> folder: Util/core files for PhaseNet and EQTransformer to read data with different sampling frequencies (i.e., not 100 Hz)</p> <p><strong>Data</strong> folder: Contains one hour of continuous downhole data (11th December 2018, 9am-10am) from the PNR-1z dataset.</p>
Crab giant pulse detected with the Dwingeloo radio telescope on 2024-07-30
<p>This is a 0.2 second recording of a giant pulse of the Crab Pulsar, recorded with the Dwingeloo Radio Telescope. The data format is SigMF: the metadata file contains all metadata, while the data file contains raw 16-bit IQ samples. The recorded bandwidth is 400-420 MHz.</p>
Tree detected
<p>The repository contains a dataset of labeled trees and the related trained YOLO models 'best.pt' and 'last.pt. The training images are generated from the original images using geometric transformations from the Albumentations library. The folder "train_original" contains the original images without any augmentations.</p> <p>In the file names, the presence of the suffix "<em>aug</em>" indicates that the image has been modified from its original version. For example, "DJI_20240525115520_0002_aug_0.jpg" is an augmented image, meaning that the original image "DJI_20240525115520_0002.jpg" has been altered using various augmentation techniques to create this new version.</p>
The application of a mode of double preconcentration and double stripping steps in combination with a flow system to decrease the detection limit and increase the selectivity of determinations in stripping analysis of As(III)
<p><span>Due to the fact that arsenic </span><span>has very harmful and toxic effects on living organisms </span><span>monitoring of its content in various environmental samples </span><span>at trace level concentrations</span><span> </span><span>is desirable and highly recommended. Such advantages as low cost and portable instrumentation, achieving low detection limits and most of all the possibility of the direct determination of As(III) with no separation step make stripping voltammetry suitable for the determination of arsenic.</span><span> </span><span> <br></span></p> <p><span>These data concer the application of double deposition and double stripping steps mode in combination with a flow system for anodic stripping voltammetric determination of As(III) ions. An advantage of the proposed way of the voltammetric measurements is a decrease of the detection limit as compared to the values obtained using a traditional three-electrode system thanks to an initial preconcentration of the analyte on the first working electrode as well as the significant increase in a selectivity of As(III) determination thanks to the possibility of solution exchange after the first deposition step.</span></p> <p><span><span>The proposed way of the voltammetric measurements leads to the following analytical advantages: (i) a decrease of the detection limit as compared to the values obtained using traditional three-electrode system by an initial preconcentration of the analyte using the large-surface area electrode; (ii) an increase of the selectivity of voltammetric determinations thanks to the application of a flow system and exchange the solution after the first deposition step; (iii) simplification of performing the measurements in comparison to the original version of double accumulation and stripping steps mode due to the lack of a need to change the position of the first working electrode; (iv) the possibility of analysis of samples with a complex matrix thanks to the use of a flow system leading to minimization of matrix effects in the second deposition step. The developed procedure of As(III) determination offers a wide linear dynamic range in the range from 1 × 10<sup>-9</sup> to 5 × 10<sup>-8</sup> mol L<sup>-1</sup> at a deposition time of 120 s at both working electrodes. The detection limit for As(III) determination was 4.8 × 10<sup>-10</sup> mol L<sup>-1</sup>. The undoubted advantage of the described procedure is its high selectivity. The tolerable limit of excess of Cu(II), which is the main interferent in the course of anodic stripping voltammetric As(III) determination, was significantly increased thanks to the solution exchange after the first deposition step. The correctness of the proposed procedure was confirmed by analysis of a real water sample and lake water certified reference material by obtaining satisfactory recovery values. The additional advantage of the proposed procedure is a miniaturization of the measurement system and the use of environmentally friendly electrodes.</span></span></p>
Figure 6 in New host detection of the parasitic mite, Erythraeus pistacicus (Trombidiformes: Erythraeidae) from Iran and indication of possible infection with bacterial symbionts
Figure 6. Haplotype network of Cardinium endosymbionts based on 16S rDNA sequences.
Figure 4 in New host detection of the parasitic mite, Erythraeus pistacicus (Trombidiformes: Erythraeidae) from Iran and indication of possible infection with bacterial symbionts
Figure 4. Haplotype network of Wolbachia endosymbionts based on wsp gene.
Dataset for "Mean Birds: Detecting Aggression and Bullying on Twitter"
<p>In recent years, bullying and aggression against social media users have grown significantly, causing serious consequences to victims of all demographics. Nowadays, cyberbullying affects more than half of young social media users worldwide, suering from prolonged and/or coordinated digital harassment. Also, tools and technologies geared to understand and mitigate it are scarce and mostly ineffective. In this paper, we present a principled and scalable approach to detect bullying and aggressive behaviour on Twitter. We propose a robust methodology for extracting text, user, and network-based attributes, studying the properties of bullies and aggressors, and what features distinguish them from regular users. We nd that bullies post less, participate in fewer online communities, and are less popular than normal users. Aggressors are relatively popular and tend to include more negativity in their posts. We evaluate our methodology using a corpus of 1.6M tweets posted over 3 months, and show that machine learning classication algorithms can accurately detect users exhibiting bullying and aggressive behaviour, with over 90% AUC.</p>
ScienceDex guides
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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.