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30,334 results for “Responsiveness”
Data from: Species richness and evenness of European bird communities show differentiated responses to measures of productivity
<p>Understanding patterns of species diversity is crucial for ecological research and conservation, and this understanding may be improved by studying patterns in the two components of species diversity, species richness and evenness of abundance of species. Variation in species richness and evenness has previously been linked to variation in total abundance of communities as well as productivity gradients. Exploring both components of species diversity is essential because these components could be unrelated or driven by different mechanisms. The aim of this study was to investigate the relationship between species richness and evenness in European bird communities along an extensive latitudinal gradient. We examined their relationships with latitude and Net Primary Productivity, which determines energy and matter availability for heterotrophs, as well as their responses to territory densities (i.e., the number of territories per area) and community biomass (i.e., the bird biomass per area). We applied a multivariate Poisson log-normal distribution to unique long-term, high-quality time-series data, allowing us to estimate species richness of the community as well as the variance of this distribution, which acts as an inverse measure of evenness. Evenness in the distribution of abundance of species in the community was independent of species richness. Species richness increased with increasing community biomass, as well as with increasing density. Since both measures of abundance were explained by NPP, species richness was partially explained by energy-diversity theory (i.e., the more energy, the more species sustained by the ecosystem). However, species richness did not increase linearly with NPP but rather showed a unimodal relationship. Evenness was not explained either by productivity nor by any of the aspects of community abundance. This study highlights the importance of considering both richness and evenness to gain a better understanding of variation in species diversity. We encourage the study of both components of species diversity in future studies, as well as use of simulation studies to verify observed patterns between richness and evenness.</p>
A Seasonally Delayed Sea Ice Response and Arctic Amplification during the Last Glacial Inception
<p>Presented here is the datasets and corresponding codes used in creating Figures of the article "<strong><span>A Seasonally Delayed Sea Ice Response and Arctic Amplification during the Last Glacial Inception</span></strong>".</p>
Decálogo para un uso responsable de ChatGPT en la escritura académica y en su enseñanza en la universidad
<p><span><span>Se presenta un decálogo para introducir ChatGPT en la escritura académica en la universidad como asistente. Estas prácticas pueden introducirse en el aula para formar a los estudiantes. El decálogo surge de la siguiente publicación en The Conversation: https://theconversation.com/decalogo-para-escribir-mejor-con-ayuda-de-chatgpt-228547</span></span></p> <p><span><span>Presentamos un decálogo para introducir ChatGPT en la escritura académica en la universidad como asistente. Estas prácticas se pueden introducir en el aula para formar a los estudiantes. The Decalogue was created from the following publication in The Conversation: <span><span>https://theconversation.com/decalogo-para-escribir-mejor-con-ayuda-de-chatgpt-228547</span></span></span></span></p>
Reading Journal of eScience Librarianship: Responsible AI in Libraries and Archives
A special issue of Journal of eScience Librarianship was brought to my attention. The issue was on the topic of responsible AI in libraries and archives. I did a bit of distant reading against the issue, and outlined here are some of my take-aways. In short, AI is something to consider in Library Land, but not without some forethought.
Figure 1. Response curves for percent acetyl-coenzyme A in Detecting the effect of ACCase-targeting herbicides on ACCase activity utilizing a malachite green colorimetric functional assay
Figure 1. Response curves for percent acetyl-coenzyme A carboxylase (ACCase) activities of resistant and susceptible Digitaria ciliaris biotypes in response to the increasing concentrations of the ACCase-targeting herbicides, sethoxydim, clethodim,fluazifop-p-butyl, and pinoxaden.The response was modeled based on the log rate of ACCase-targeting herbicides to create equal spacing between rates using least-squares fit regression of ACCase activity to the non-treated check. Means are represented by differing symbols for each biotype, and regression equation models are represented by differing line types for each biotype. Vertical bars represent the standard errors of the means (n = 6). Digitaria ciliaris biotypes: R1 and R2, resistant; S, susceptible. The concentration of ACCase-targeting herbicides required to cause 50% inhibition of ACCase activity (IC50) was calculated from concentration-response curves. CI, confidence interval.
Fig. 3 in SjTat-TPI facilitates adaptive T-cell responses and reduces hepatic pathology during Schistosoma japonicum infection in BALB/c mice
Fig. 3 Th1 immune response acter CD8+T cells blockage in sitro. a. CD3+CD8+T cells were successcullv blocked. The blocking ecciciencv was more than 99.6 %. b, c. Percentages oc CD4+IFN-γ+ (Th1) in Tat-TPI (T-TPI), TPI stimulated splenocvtes with or without CD8+T-cell blockage. Data are presented as the means ± SEM crom cour independent experiments. (*P <0.05; **P <0.01)
Fig. 2 in SjTat-TPI facilitates adaptive T-cell responses and reduces hepatic pathology during Schistosoma japonicum infection in BALB/c mice
Fig. 2 Immune responses in the draining popliteal lvmph nodes oc mice induced bv Tat-TPI (T-TPI) and TPI proteins. a and c. Percentages oc CD4+IFN-γ+ cells (Th1), CD8+IFN-γ+ cells (Tc1) analvsed bv FACS. b. The ratio oc CD4+ T cells to CD8+ T cells (CD4/CD8) in the draining popliteal lvmph nodes. Data are presented as the means ± SEM crom six mice in each group. (*P <0.05; **P <0.01)
Fig. 1 in SjTat-TPI facilitates adaptive T-cell responses and reduces hepatic pathology during Schistosoma japonicum infection in BALB/c mice
Fig. 1 Expression, puricication and identicication oc the cusion proteins Tat-TPI and TPI. a. Puricication oc two cusion proteins detected bv Protein Gel Electrophoresis. M: molecular weight marker, Lane 1: recombinant SjTat-TPI, Lane 2: recombinant SjTPI, Lane 3: the recombinant plasmid without puricication. b. Fusion proteins recognised bv His-Ab with Western blotting. Lane 1: recombinant SjTat-TPI, Lane 2: recombinant SjTPI. c. Fusion proteins recognised bv S. japonicum incected-mice serum with Western blotting. Lane 1: recombinant SjTat-TPI, Lane 2: recombinant SjTPI
Fig. 5 in SjTat-TPI facilitates adaptive T-cell responses and reduces hepatic pathology during Schistosoma japonicum infection in BALB/c mice
Fig. 5 Parasite burden and immune response were obsersed at 6 weeks acter S. japonicum incection in mice saccinated with T-TPI + IFA, TPI + IFA, IFA and PBS. a. Aserage number oc worms recosered. b. Aserage number oc eggs per gram (EPG) in the liser. c. Representatise granulomas with a single egg crom each group (100×). d. Aserage area oc single egg granulomas crom each group. e, f. Percentages oc CD3+CD4+IFN-γ+(Th1) and CD3+CD8+IFN-γ+(Tc1) gated crom CD3+ T cells analvsed bv FACS. Each bar represents the means ± SEM crom twelse mice per group. (*P <0.05; **P <0.01)
Fig. 4 T cell and antibodies responses acter three immunisations with T in SjTat-TPI facilitates adaptive T-cell responses and reduces hepatic pathology during Schistosoma japonicum infection in BALB/c mice
Fig. 4 T cell and antibodies responses acter three immunisations with T-TPI + IFA, TPI + IFA, IFA and PBS. a and b: Percentages oc CD3+CD4+IFN-γ+ (Th1) and CD3+CD8+IFN-γ+ (Tc1) gated crom CD3+ cells analvsed bv FACS. c. IgG, IgG1 and IgG2a lesels in mice sera were detected. Data are presented as the means ± SEM crom eight mice in each group. (*P <0.05; **P <0.01)
Fig. 3 in Regional uniqueness of tree species composition and response to forest loss and climate change
Fig. 3 | Response of tree species to climate change across biomes. The median absolute latitude and median elevation shift among species, fraction of lost and gained species, and change in taxonomic and phylogenetic composition under climate change were computed for each forest ecoregion. The boxplots show statistics for n = 239 ecoregions for Tropical Moist Broadleaf Forests, n = 14 ecoregions for Tropical Coniferous Forests, n = 55 ecoregions for Tropical Dry Broadleaf Forests, n = 26 ecoregions for Boreal Forests, n = 91 ecoregions for Temperate Broadleaf Forests, n = 49 ecoregions for Temperate Conifer Forests and n = 61 ecoregions for Mediterranean Forests. The center line of the boxplots shows the median, the box limits the quartiles, the whiskers 1.5 times the interquartile range, and the points the outliers.Changes are computed between predicted distributions with climate variables for 1981-2010 and climate projections for 2071-2100 under climate change scenario SSP 5.85. Changes in composition are computed as the Euclidean distance between scaled NMDS and evoPCA values computed at the ecoregion level. Source data are provided as a Source Data file.
Fig. 2 in Regional uniqueness of tree species composition and response to forest loss and climate change
Fig. 2 | Species occupancy range distribution and loss. a Distributions of species occupancy range sizes globally (gray) and constrained to forests (at least 10% tree cover, color) for species in each forest biome. b Boxplot of relative range reduction across species in each forest biome with the center line showing the median, the box limits the quartiles, the whiskers 1.5 times the interquartile range, and the points the outliers. The distributions and boxplots are computed for n = 6810 species for Tropical Moist Broadleaf Forests, n = 588 species for Tropical Coniferous Forests, n = 1101 species for Tropical Dry Broadleaf Forests, n = 54 species for Boreal Forests, n = 1744 species for Temperate Broadleaf Forests, n = 178 species for Temperate Conifer Forests and n = 580 species for Mediterranean Forests. c Global map of median species range size constrained to forests, created with QGIS110. The gray base map corresponds to all areas for which model predictors were available. d Plot of species' median latitude against range size constrained to forests, colored by point density, where red indicates the highest density. Source data are provided as a Source Data file.
Fig. 1 in Regional uniqueness of tree species composition and response to forest loss and climate change
Fig. 1 | Gradients in taxonomic and phylogenetic composition show a near- a, c. Scatter plot of taxonomic and phylogenetic ordinations in environmental unique biodiversity signature of every single location on the planet. Taxonomic space, a 2-dimensional space made up of the 2 first axes of a PCA of the environcomposition is represented by a 3-axis non-metric dimensional scaling (NMDS) and mental variables used for species distribution modeling: mean annual temperature phylogenetic beta-diversity is represented by the 3 first axes of a phylogenetic (MAT), temperature seasonality (T season), annual precipitation (Annual P), preordination (evoPCA). Both the taxonomic and phylogenetic ordinations are com- cipitation seasonality (P season), growing season length (GSL), net primary proputed on the global community matrix derived from the modeled distributions of ductivity (NPP),silt content (Silt),coarse fragments (CF),and soil pH (pH).b, d. Map n = 10,590 tree species sampled at a resolution of 100 km, resulting in n = 12,548 of taxonomic and phylogenetic ordinations in geographical space. Source data are sites. The 3 axes of each ordination are mapped to red, green, and blue with provided as a Source Data file. The maps were created with QGIS110 and the gray minimum and maximum values corresponding to the 10th and 90th percentiles. base map corresponds to all areas for which model predictors were available.
A field study of the molecular response of brown macroalgae to heavy metal exposure: an (epi)genetic approach
<p>We used next-generation sequencing to study DNA methylation changes and DNA sequence variation (SNPs) in thalli from four populations of the brown macroalgae <em>Fucus vesiculosus</em> reciprocally transplanted between two polluted and two unpolluted sites. For this, we performed reduced representation bisulfite DNA sequencing.</p>
Data to accompany "Automatic text clustering for audio attribute elicitation experiment responses", AES 143rd Convention, New York, NY, USA, 2017
<p>This work was supported by the EPSRC Programme Grant S3A: Future Spatial Audio for an Immersive Listener Experience at Home (EP/L000539/1) and the BBC as part of the BBC Audio Research Partnership. Details about the data underlying this work, along with the terms for data access, are available from http://dx.doi.org/10.15126/surreydata.00841589.</p> <p>If you use the data, please cite the following paper:</p> <p>J. Francombe, T. Brookes, and R. Mason, “Automatic text clustering for audio attribute elicitation experiment responses”, AES 143rd Convention, New York, NY, USA, 2017</p>
Multi-Purpose Room Impulse Response Dataset Measured on a 3D Spatial Grid
<h1>Introduction</h1> <p>The sound field inside a room depends on many factors, such as the room shape, the absorption characteristics of the materials that comprise the bounding surfaces, the furniture present in the room, and the source position and its acoustic characteristics. An increasing number of publicly available room impulse response (RIR) databases that aim to provide detailed descriptions of interior sound fields can be found in the literature. These databases can be utilized in research as well as in the development and verification of signal processing algorithms that use this information on the acoustic environment. The availability of many RIR databases covering diverse scenarios is beneficial to the community.</p> <p>We provide a database of RIRs, namely the <strong>M</strong>ulti-<strong>P</strong>urpose <strong>RIR</strong> (<strong>MP-RIR</strong>) dataset, which contains 68736 RIRs measured on a dense 3D grid inside a complex-shaped room. We used a measurement robot with a rotating arm that operates as a linear guide and is capable of moving a vertical, linear array of eight omni-directional microphones. Four different sources have been used and were placed at eight different positions inside the room. A detailed desciption of the measurement campaign and the dataset is presented in the paper (https://aes2.org/publications/elibrary-page/?id=22515). </p> <h1>Contents of the MP-RIR dataset</h1> <p>In the following, the contents and the structure of the provided dataset are described:</p> <ul> <li>Sk_Mrir.npy:<br>Matrix, which contains the RIRs for all measured grid points for the loudspeaker Sk, k = 1, 2, ..., 8.<br>The matrix has the shape [N_xy, N_z, N] = [1074 x 8 x 100096], where N_xy is the number of 2D grid positions to which the robot is moving the vertical microphone array of N_z microphones. The length of each RIR is described by N.</li> <li>Mxyz.npy:<br>Matrix, which contains the microphone coordinates of the measured RIRs and corresponds to the matrices Sk_Mrir.<br>The matrix has the shape [N_xy, N_z, N_d] = [1074 x 8 x 3]. The indexing for the first two dimensions is the same as for the matrices Sk_Mrir, so that the microphone coordinates can be immediately retrieved for the provided RIRs. The third dimension with the length N_d gives access to the x-, y- and z-coordinate values in meters.</li> <li>Setup.npz<br>Dictionary, which contains parameters related to the measurement setup, with the following keys:<br> <ul> <li>angles_speaker<br>Dictionary of azimuth angles in degrees of the loudspeakers, with the keys S1, S2, ..., S8.</li> <li>coord_speaker_center<br>Dictionary, which contains the x-, y- and z-coordinates of the loudspeaker positions at the center of the base of each loudspeaker. The coordinate arrays can be accessed with the keys S1, S2, ..., S8.</li> <li>coord_polygon<br>Array of shape [4,2], which contains the x- and y-coordinates in meters of the room corners C_q, q=0,1,2,3.<br>The first dimension of the array relates to the room corners and the second dimension relates to the coordinates. </li> <li>fs<br>Sampling rate in Hz.</li> <li>T_guard<br>Guard time in samples. The guard time provides additional samples at the beginning of the RIR to increase the quality of the RIR.</li> <li>T_system<br>Delay of the measurement system in samples.</li> </ul> </li> </ul> <h1>Further Information</h1> <p>The delay of the RIRs is composed of the guard time T_guard, the system delay T_system and the acoustic delay T_ac. The guard time and system delay can be retrieved from the file Setup.npz described above.</p> <p>A gain alignment procedure was applied to align the output SPL between the loudspeakers, as described in the paper. Additionally, all RIRs were scaled by the same value, the maximum absolute peak of all measured RIRs. As a result, the maximum absolute value in each individual RIR is less or equal to 1.</p>
Room Impulse Responses for Low-Frequency Sound Field Control
<h2>About</h2> <div> <div> <div> <p>A dataset of room impulse responses (RIRs) measured in the low frequency range, for different measurement signal lengths, in two rooms with different acoustic conditions. Acquired with the purpose of low-frequency sound zones rendering and evaluation, the dataset can be used in general for different sound field control methods.</p> <p>By design, the dataset is composed of two sets of RIRs: one intended for the design of the control strategies, and another one intended for evaluation [1]. The RIRs of the first set, obtained with measurement signals of different length, allow exploring the influence of the acquisition time of the RIRs in the control methods [2]. The RIRs of the second set allow evaluating the sound field generated at and around the position of the RIRs of the first set.</p> <p>The RIRs were acquired with the Synchronized Swept-Sine (SSS) method, proposed by Novak et al. [3], at a samplig frequency of 48 kHz with SSS signals varying from 15 Hz to 600 Hz. The obtained RIRs were re-sampled to 1.2 kHz.</p> <p>Two files with different contents have been added:</p> <ul> <li><strong>RIR_LF_SFC_Light:</strong> contains the documentation, MatLab codes, and the ready-to-use RIRs stored as 3D-arrays in .mat files.<br><br></li> <li><strong>RIR_LF_SFC_Full:</strong> in addition to files in <strong>RIR_LF_SFC_Light</strong>, it contains the original SSS signals and the signals recorded during the measurements. These were used to retrieve the RIRs and therefore, can be used for custom purposes. <br><br></li> </ul> </div> </div> </div> <div> <h2>Citation</h2> <p>Please cite the database with the following paper:</p> <p>@inproceedings{cadavid_ATvsSS_2024,<br>title={Spatial Sampling versus Acquisition Time of Room Impulse<br> Responses for Low-Frequency Sound Zones},<br> author={Cadavid, Jos{\'e} and M{\o}ller, Martin Bo and van Waterschoot, Toon and Bech, S{\o}ren and {\O}stergaard, Jan},<br> booktitle={Audio Engineering Society Convention 156},<br> year={2024},<br> organization={Audio Engineering Society} }</p> <h2>Acknowledgements</h2> <p>The authors would like to thank <a href="https://orcid.org/0000-0002-1452-2227" target="_blank" rel="noopener">Antonin Novak</a>, <a href="https://orcid.org/0000-0002-2175-6603" target="_blank" rel="noopener">Christian S. Pedersen</a>, and Claus Vestergaard for their help with the RIRs measurements.</p> <p>This project has received funding from the European Union’s (EU) Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Actions Grant No. 956369.</p> </div>
Figure 1 in Evaluation of perennial Glycine species for response to Meloidogyne incognita, Rotylenchulus reniformis, and Pratylenchus penetrans
Figure 1: Representative images of soybean and perennial Glycine species roots at 8 weeks post-inoculation of Meloidogyne incognita. Gall index rating is given in parentheses A, susceptible check G. max cv. Pickett 71. B, resistant check G. max cv. Forrest. C, G. tomentella PI 339655. D, G. latifolia PI 559298. E, G. latifolia PI 559300. F, G. tabacina PI 373990.
Anonymized Responses to the Student Expectation of Learning Analytics Questionnaire (SELAQ) in 2022 and 2023
<p>Contains responses of 566 bachelor students to the Student Expectation of Learning Analytics Questionnaire (SELAQ) conducted at Bochum University of Applied Sciences in Germany in fall 2022 and summer 2023. The Questionnaire consists of 12 statements (in the dataset: enumerated from 1-12) which are evaluated by students regarding both their desire and their expectation (in the dataset: D and E). This results in 24 items (in the dataset: 1D, 1E, 2D, 2E, ..., 12D, 12E). Each item is evaluated by the students on a Likert-scale from 1 (strongly disagree) to 7 (strongly agree). Additionally, the students' study track (in the dataset: Study_Track) and their current semester (in the dataset: Semester) were also recorded. The questionnaires were carried out in paper form at the beginning of lectures. Statements 1, 2, 3, 5 and 6 deal with ethical and privacy expectations, while statements 4, 7, 8, 9, 10, 11 and 12 deal with service feature expectations regarding learning analytics. For a text version of the items, please refer to the paper related to this dataset (DOI 10.1145/3636555.3636923), the additional descriptions below or the attached description file.</p>
Figure 3 in Response of Invasive Longhorn Beetles (Coleoptera: Lamiinae) to Known Cerambycid Aggregation-Sex Pheromones in the Puna District of Hawaii Island
Figure 3. Mean (± SE) numbers of PLB (Lagocheirus obsoletus) caught in traps baited with solvent control, fuscumol acetate, or monochamol (experiment 1). Means with an asterisk are significantly different than the solvent control (max-t test, p <0.05).
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.