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Soil Moisture and Temperature following experimental drought in the LEF
We used throughfall exclusion shelters to determine effects of short-term (3 month) drought on trace gas fluxes and nutrient availability in humid tropical forests in Puerto Rico. Exclusion and control plots were replicated within and across three topographic zones (ridge, slope, valley) to account for spatial heterogeneity typical of these ecosystems. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Canopy damage and recovery following Hurricane Maria using multitemporal lidar data, Mar-2017 - Mar-2020, Puerto Rico
The data archive is here: http://dx.doi.org/10.15486/ngt/1797399 please use this DOI when citing this dataset. Hurricane Maria (Category 4) snapped and uprooted canopy trees, removed large branches, and defoliated vegetation across Puerto Rico. The magnitude of forest damages and the rates and mechanisms of forest recovery following Maria provide important benchmarks for understanding the ecology of extreme events. We used airborne lidar data acquired before (2017) and after Maria (2018, 2020) to quantify landscape-scale changes in forest structure along a 439-ha elevational gradient (100 to 800 m) in the Luquillo Experimental Forest. Damages from Maria were widespread, with 73% of the study area losing ≥1 m in canopy height (mean = -7.1 m). Taller forests at lower elevations suffered more damage than shorter forests above 600 m. Yet only 13% of the study area had canopy heights ≤2 m in 2018, a typical threshold for forest gaps, highlighting the importance of damaged trees and advanced regeneration on post-storm forest structure. Heterogeneous patterns of regrowth and recruitment yielded shorter and more open forests by 2020. Nearly 45% of forests experienced initial height loss (<-1 m, 2017-2018) followed by rapid height gain (>1 m, 2018-2020), whereas 21.6% of forests with initial height losses showed little or no height gain, and 17.8% of forests exhibited no structural changes >|1| m in either period. Canopy layers <10 m accounted for most increases in canopy height and fractional cover between 2018-2020, with gains split evenly between height growth and lateral crown expansion by surviving individuals. These findings benchmark rates of gap formation, crown expansion, and canopy closure following hurricane damage. Included in the attached zip file are four TIF and four KML files. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National
MCR LTER: Coral Reef: Early life stage bottleneck determines rates of coral recovery following severe disturbance; Data for Speare et al., 2024, Ecology
The data included in this data package were collected on the north shore of Moorea, French Polynesia, from 2011-2018 to evaluate drivers of different recovery rates of corals at two depths (10m and 17m). Data on juvenile coral densities, growth, and mortality, were collected from annual time series photoquadrats. Data from two experiments on coral settlement tiles were used to evaluate how exclusion of fishes influences the density of coral recruits, and the survival of coral recruits at 10 and 17m. These data were used for analyses in the manuscript entitled "Early life stage bottleneck determines rates of coral recovery following severe disturbance". These data are in support of a publication Speare et al. (2024) Ecology. This material uses data collected by the U.S. National Science Foundation's (NSF) Moorea Coral Reef Long Term Ecological Research (MCR LTER) site under Grant No. OCE 2224354 (and earlier awards). Additional financial support to the MCR LTER site was provided through a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2024).
Measurements of tidal creek discharge measurements during tidal creek lateral exchange measurements approximately every 15 minutes from beginning of flood tide to the following low tide, Rowley, MA, PIE LTER.
Measurement of the volume of water during lateral exchange measurements in tidal creek systems draining predominantly low-elevation marsh dominated by Spartina alterniflora (LM1 and LM2) and high-elevation marsh dominated by Spartina patens (West, Nelson, HM1). Creeks are located in Rowley, MA, PIE LTER.
Water-column conductivity, salinity, dissolved oxygen, turbidity, and pH by deployed sonde during tidal creek lateral exchange measurements approximately every 5 minutes from beginning of flood tide to the following low tide, Rowley, MA, PIE LTER.
Measurement of water-column conductivity, salinity, temperature, dissolved oxygen, turbidity, and pH logged by deployed sonde in tidal creek systems draining predominantly low-elevation marsh dominated by Spartina alterniflora (LM1 and LM2) and high-elevation marsh dominated by Spartina patens (West, Nelson, HM1). Creeks are located in Rowley, MA, PIE LTER.
Metabolic recovery and compensatory shell growth of juvenile Pacific geoduck Panopea generosa following short-term exposure to acidified seawater
<p><strong>METABOLIC RECOVERY AND COMPENSATORY SHELL GROWTH OF JUVENILE PACIFIC GEODUCK <em>PANOPEA GENEROSA</em> FOLLOWING SHORT-TERM EXPOSURE TO ACIDIFIED SEAWATER</strong></p> <p><strong>Samuel J. Gurr<sup>1*</sup>, Brent Vadopalas<sup>2</sup>, Steven B. Roberts<sup>3</sup>, Hollie M. Putnam<sup>1</sup></strong></p> <p><sup>1 </sup>University of Rhode Island, College of the Environment and Life Sciences, 120 Flagg Rd, Kingston, RI 02881 USA</p> <p><sup>2 </sup>University of Washington, Washington Sea Grant, 3716 Brooklyn Ave NE, Seattle, WA 98105 USA</p> <p><sup>3 </sup>University of Washington, School of Aquatic and Fishery Sciences, 1122 NE Boat St, Seattle, WA 98105 USA</p> <p><strong>*Corresponding author:</strong> Fax: Phone:1-401-874-9510 Email: samuel_gurr@uri.edu</p> <p><strong>Abstract</strong></p> <p>While acute stressors can be detrimental, environmental stress conditioning can improve performance. To test the hypothesis that physiological status is altered by stress conditioning, we subjected juvenile Pacific geoduck, <em>Panopea generosa, </em>to repeated exposures of elevated <em>p</em>CO<sub>2</sub> in a commercial hatchery setting followed by a period in ambient common garden. Respiration rate and shell length were measured for juvenile geoduck periodically throughout short-term repeated reciprocal exposure periods in ambient (~550 µatm) or elevated (~2400 µatm) <em>p</em>CO<sub>2</sub> treatments and in common, ambient conditions, five months after exposure. Short-term exposure periods comprised an initial 10-day exposure followed by 14 days in ambient before a secondary 6-day reciprocal exposure. The initial exposure to elevated <em>p</em>CO<sub>2 </sub>significantly reduced respiration rate by 25% relative to ambient conditions, but no effect on shell growth was detected. Following 14 days in common garden, ambient conditions, reciprocal exposure to elevated or ambient <em>p</em>CO<sub>2</sub> did not alter juvenile respiration rates, indicating ability for metabolic recovery under subsequent conditions. Shell growth was negatively affected during the reciprocal treatment in both exposure histories, however clams exposed to the initial elevated <em>p</em>CO<sub>2</sub> showed compensatory growth with 5.8% greater shell length (on average between the two secondary exposures) after five months in ambient conditions. Additionally, clams exposed to the secondary elevated <em>p</em>CO<sub>2 </sub>showed 52.4% increase in respiration rate after five months in ambient conditions. Early exposure to low pH appears to trigger carry-over effects suggesting bioenergetic re-allocation facilitates growth compensation. Life stage-specific exposures to stress can determine when it may be especially detrimental, or advantageous, to apply stress conditioning for commercial production of this long-lived burrowing clam.</p> <p> </p>
Dataset corresponding to scientific paper "Improved reperfusion following alternative surgical approach for experimental stroke in mice"
<p>Acquired raw experimental data using laser speckle contrast imaging (LSCI) following middle cerebral artery occlusion (MCAO) in mice. Data obtained from mice undergoing standard CCA ligation technique and mice undergoing CCA vessel repair technique<sup>1</sup>.</p> <p>The dataset is linked to paper "Improved reperfusion following alternative surgical approach for experimental stroke in mice". </p> <p>The dataset consists of the following:</p> <ul> <li>Raw LSCI flux values, from ipsilateral and contralateral hemispheres, measured at baseline, 24hours post-MCAO and 48hours post-MCAO. </li> <li>Normalised data expressing ispilateral hemisphere as a % of the control contralateral hemisphere.</li> <li>Mean normalised values for each subject. </li> </ul> <p> </p> <p><strong>References</strong></p> <ol> <li>Trotman-Lucas,M., Kelly, M.E., Janus, J., Fern, R., Gibson, C.L. (2017) 'An alternative surgical approach reduces variability following filament induction of experimental stroke in mice'. <em>Disease Models & Mechanisms,</em> 10, 931-938.</li> </ol> <p> </p>
Full Body Motion Capture of Single Individuals Following External Perturbations from Different Directions
<p>This dataset is composed of C3D files corresponding to full body motion of participants undergoing external perturbation at shoulder height with different sensory conditions. The temporal force profiles of the perturbations are also available.</p> <p>The following experiment received ethical approval from an ethics committee and all participants signed an informed consent form relative to the processing of their data. <br>The experiments were carried on 21 healthy young adults (10 females, 11 males). All were between 20 and 38 yo with a mean age of 27.2 (std: 4.2). Mean mass was 70.2 (std: 12.1) kg and height was 1.74 (std: 0.08) m. </p> <p>Participants motion was recorded using 45 reflective markers and a 23 Qualisys camera system (200Hz). <br>The markers were placed on participants following standardised anatomical landmarks. <br>The output signal of the force sensor was processed using a Butterworth low pass filter with a 5Hz cutoff frequency without phase shift. <br>The force sensor was synchronised with the motion capture software.<br>Tree reflective markers were also placed along the pole in order to retrieve the exact direction of the perturbations. </p>
Data for :Nitrogen availability in digestates from full-scale biogas plants following soil application as affected by operation parameters and input feedstocks
<p>This archive contains data for the paper "Nitrogen availability in digestates from full-scale biogas plants following soil application as affected by operation parameters and input feedstocks". Obtained from a soil incubation experiment for 80 days.</p><p> </p>
Coral thermotolerance retained following year-long exposure to a novel environment
<p>Description of datasets:</p> <h4>HTSeqCounts</h4> <p>Raw HTSeq count data used for downstream RNA sequencing analyses and visualisations including Principal Component Analysis and Differential Gene Expression analysis of the four habitat groups (mangrove to reef, reef to reef, wild mangrove and wild reef).</p> <h4>GO enriched gene results:</h4> <p>GO enriched genes summarised by broad categories of GO Slims for <em>Pocillopora acuta</em> corals originating from a mangrove system vs colonies from an adjacent reef site, translocated to a reef environment for one year. Samples for gene expression were collected during an acute heat stress assay to assess differentially enriched genes between mangrove and reef corals under 36 ºC. Enriched GO terms were grouped into broader functional categories using the “goSlim” function in the GSEABase R package with GOslim generic obo as the reference database to allow for a summary of key functions enriched in groups under heat stress. See manuscript methods for further detail on differential gene expression analysis.</p> <h4>2022-2023 mangrove/reef temperature and pH</h4> <p>Temperature and pH data measured in the Low Isles mangrove lagoon and reef habitat using HOBO MX2510 loggers deployed from February 2022 - February 2023. </p> <h4>Methylated DNA data</h4> <p>Percent DNA methylation relative to total DNA of mangrove to reef, reef to reef and wild mangrove groups under acute temperature stress during the February 2023 CBASS experiment.</p> <h4>Analysis code.zip</h4> <p>A copy of all R code used in the data analysis of this project</p> <p> </p>
Can a knee sleeve influence ground reaction forces and knee joint power during a step-down hop in participants following ACL reconstruction? Discrete and time-continuous datasets
<p>Using a cross-over design, we estimated GRF and knee kinematics and kinetics during a step-down hop for 30 participants (age 26.1 [SD 6.7] years, 14 women) following ACL reconstruction (median 16 months post-surgery) with and without wearing a knee sleeve. In a subsequent randomised clinical trial, participants in the ‘Sleeve Group’ (n=9) then wore the sleeve for 6 weeks at least 1 hour daily, while a ‘Control Group’ (n=9) did not wear the sleeve. Statistical parametric mapping (SPM) was used to compare (1) GRF trajectories in the three planes as well as knee joint power between three conditions at baseline (uninjured side, unsleeved injured and sleeved injured side); (2) within-participant changes for GRF and knee joint power trajectories from baseline to follow-up between groups. We also compared discrete peak GRFs and power, rate of (vertical) force development, and mean knee joint power in the first 5% of stance phase. Time-continuous and discrete data are included in this dataset.</p>
Altered infective proficiency of the gut microbiome following COVID-19
<p><strong>The effects of SARS-CoV-2 infections comprise of many heterogeneous symptoms including several involving the human gastrointestinal tract. We assess the effects of COVID-19 on the host microbiome</strong></p>
Continuous monitoring of patient mobility for 18 months using inertial sensors following traumatic knee injury: a case study
<p><strong>This repository contains raw data relating to: </strong>Continuous monitoring of patient mobility for 18 months using inertial sensors following traumatic knee injury: a case study Mueller A., Hoefling H., Nuritdinow T., et al. DOI: 10.1159/000490919</p> <p><strong>Metadata and processed data derived from the raw data deposited here is available here:</strong> https://github.com/Novartis/mueller_et_al_2018</p> <p><strong>Article Abstract</strong></p> <p>Continuous patient activity monitoring during rehabilitation, enabled by digital technologies, will allow the objective capture of real-world mobility and aligning treatment to each individual’s recovery trajectory in real time. To explore the feasibility and added value of such approaches, we present a case study of a 36-year-old male participant monitored continuously for activity levels and gait parameters using a waist-worn inertial sensor following a tibial plateau fracture on the right side, sustained as a result of a high-energy trauma during a sporting accident. During rehabilitation, data were collected for a period of 553 days, with > 80% daytime compliance, until the participant returned to near full mobility. The participant completed a daily diary with the annotation of major events (falls, near falls, cycling periods, or physiotherapy sessions) and key dates in the patient’s recovery, including medical interventions, transitioning off crutches, and returning to work. We demonstrate the feasibility of collecting, storing, and mining of continuous digital mobility data and show that such data can detect changes in mobility and provide insights into long-term rehabilitation. We make both raw data and annotations available as a resource with the aspiration that further methods and insights will be built on this initial exploration of added value and continue to demonstrate that continuous monitoring can be deployed to aid rehabilitation.</p>
Investigating the effect of cochlear synaptopathy on envelope following responses using a model of the auditory nerve
<p>Dataset containing the recorded and simulated data reported in the manuscript "Investigating the effect of cochlear synaptopathy on envelope following responses using a model of the auditory nerve" published in the Journal of the Association for Research in Otolaryngology, JARO (<a href="https://doi.org/10.1007/s10162-019-00721-7">https://doi.org/10.1007/s10162-019-00721-7</a>):</p> <ol> <li>RECORDED Envelope Following Responses (EFR) in normal-hearing (NH) threshold and hearing-impaired (HI) human listeners using deeply (m = 85%) and shallowly (m = 25%) modulated sinusoidally amplitude modulated (SAM) tones.</li> <li>SIMULATED EFRs using the auditory nerve (AN) model by Zilany et al. (2009, 2014).</li> </ol> <p>Files content and structure:</p> <p><strong>Recorded EFRs</strong></p> <p><strong>Fig. 2:</strong></p> <ul> <li><em>fig2__recorded_efr.csv</em>: <br> EFR recordings as a function of stimulus level (EFR magnitude-level functions) for the NH and HI listeners using two modulation depths.</li> </ul> <p>The file containing the recorded EFR data have the following columns:</p> <ul> <li><em>lvl</em>: Stimulation level</li> <li><em>m85_ok: </em>EFR magnitude (dB re to 1 µV) using m = 85%. Significant responses (F-test = 1)</li> <li><em>m85_ko: </em>EFR magnitude (dB re to 1 µV) using m = 85%. Non-significant responses (F-test = 0)</li> <li><em>m85_bkg: </em>Estimated background noise magnitude (dB re to 1 µV) for the recordings when m = 85%</li> <li><em>m25_ok: </em>EFR magnitude (dB re to 1 µV) using m = 25%. Significant responses (F-test = 1)</li> <li><em>m25_ko: </em>EFR magnitude (dB re to 1 µV) using m = 25%. Non-significant responses (F-test = 0)</li> <li><em>m25_bkg: </em>Estimated background noise magnitude (dB re to 1 µV) for the recordings when m = 25% </li> <li><em>subj: </em>Listener id</li> <li>hearing: Hearing group (nh | hi) of the listener</li> </ul> <p><strong>Simulated EFRs:</strong></p> <p><strong><em>Files with the simulation results summing across frequency and SR fiber type</em></strong></p> <p><strong>Fig. 4:</strong></p> <ul> <li><em>fig4a__simul_efr__nh_23ohc_13ihc__no_cs.csv</em>: <br> Simulated EFR magnitude-level function for the NH threshold listeners (average) assuming 2/3 of OHC loss and 1/3 of IHC loss (Fig. 4a).</li> <li><em>fig4b__simul_efr__nh_slp_thres_all_ohc__no_cs.csv</em>: <br> Simulated EFR magnitude-level function for the NH threshold listeners (average) assuming sloping threshold at extended high frequencies (EHF) and all of OHC loss (Fig. 4b).</li> <li><em>fig4c__simul_efr__nh_slp_thres_all_ihc__no_cs.csv</em>: <br> Simulated EFR magnitude-level function for the NH threshold listeners (average) assuming sloping threshold at extended high frequencies (EHF) and all of IHC loss (Fig. 4c).</li> <li><em>fig4d__simul_efr__hi_23ohc_13ihc__no_cs.csv</em>: <br> Simulated EFR magnitude-level function for the HI listeners (average) assuming 2/3 of OHC loss and 1/3 of IHC loss (Fig. 4d).</li> <li><em>fig4e__simul_efr__hi_all_ohc__no_cs.csv</em>: <br> Simulated EFR magnitude-level function for the HI threshold listeners (average) assuming all of OHC loss (Fig. 4e).</li> <li><em>fig4f__simul_efr__hi_all_ihc__no_cs.csv</em>: <br> Simulated EFR magnitude-level function for the HI threshold listeners (average) assuming all of IHC loss (Fig. 4f).</li> <li><em>fig4g__simul_efr__hi_slp_thres_23ohc_13ihc__no_cs.csv</em>: <br> Simulated EFR magnitude-level function for the HI listeners (average) assuming sloping threshold at EHF and 2/3 of OHC loss and 1/3 of IHC loss (Fig. 4d).</li> <li><em>fig4h__simul_efr__hi_slp_thres_all_ohc__no_cs.csv</em>: <br> Simulated EFR magnitude-level function for the HI threshold listeners (average) assuming sloping threshold at EHF and all of OHC loss (Fig. 4e).</li> <li><em>fig4i__simul_efr__hi_slp_thres_all_ihc__no_cs.csv</em>: <br> Simulated EFR magnitude-level function for the HI threshold listeners (average) assuming sloping threshold at EHF and and all of IHC loss (Fig. 4f).</li> </ul> <p> </p> <p><strong>Fig. 5:</strong></p> <ul> <li><em>fig5a__simul_efr__nh__cs_ms_ls_100p.csv</em>: <br> Simulated EFR magnitude-level function for the NH threshold listeners (average) assuming cochlear synaptopathy (CS) of a 100% of loss of only medium- and low-spontaneous rate (SR) AN fibers (Fig. 5a).</li> <li><em>fig5b__simul_efr__nh09_cs__approx</em>.<em>csv</em>: <br> Simulated EFR magnitude-level function to approximate the data for the NH threshold listener NH09 including CS (Fig. 5b).</li> <li><em>fig5c__simul_efr__hi04_cs__approx</em>.<em>csv</em>: <br> Simulated EFR magnitude-level function to approximate the data for the HI listener HI04 including CS (Fig. 5c).</li> </ul> <p> </p> <p><strong>Fig. 6:</strong></p> <p>Files with the simulation results for the NH threshold listener in different characteristic frequency (CF) bands and SR fiber types</p> <ul> <li><em>fig6__simul_efr__nh_cf_band_analys__no_cs__m12.mat</em>: <br> Simulated EFR magnitude-level function for the NH using a SAM tone with m = 12%.</li> <li><em>fig6__simul_efr__nh_cf_band_analys__no_cs__m25.mat</em>: <br> Simulated EFR magnitude-level function for the NH using a SAM tone with m = 25%.</li> <li><em>fig6__simul_efr__nh_cf_band_analys__no_cs__m50.mat</em>: <br> Simulated EFR magnitude-level function for the NH using a SAM tone with m = 50%.</li> <li><em>fig6__simul_efr__nh_cf_band_analys__no_cs__m85.mat</em>: <br> Simulated EFR magnitude-level function for the NH using a SAM tone with m = 85%.</li> <li><em>fig6__simul_efr__nh_cf_band_analys__no_cs__m100.mat</em>: <br> Simulated EFR magnitude-level function for the NH using a SAM tone with m = 100%.</li> </ul> <p> </p> <p><strong>Fig. 7:</strong></p> <ul> <li><em>fig7a__simul_efr__bw_analys__32oct_[20, 40, 60, 80, 100]p.csv</em>: <br> Simulated EFR magnitude-level function for the NH threshold listeners assuming CS of a bandwidth (BW) of 3/2-octave for a loss of AN fibers ranging from 20% to 100% (Fig. 7a).</li> <li><em>fig7b__simul_efr__bw_analys__1oct_[20, 40, 60, 80, 100]p.csv</em>: <br> Simulated EFR magnitude-level function for the NH threshold listeners assuming CS of a bandwidth (BW) of 1-octave for a loss of AN fibers ranging from 20% to 100% (Fig. 7b).</li> <li><em>fig7c__simul_efr__bw_analys__13oct_[20, 40, 60, 80, 100]p.csv</em>:<br> Simulated EFR magnitude-level function for the NH threshold listeners assuming CS of a bandwidth (BW) of 1/3-octave for a loss of AN fibers ranging from 20% to 100% (Fig. 7c).</li> </ul> <p> </p> <p>-----------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p> </p> <p>The structure of the .csv files that contain the EFR simulations is:</p> <ul> <li><em>lvl</em>: Stimulation level</li> <li><em>mgn_mxxx: </em>Simulated EFR magnitude (a.u. in dB) for each modulation depth (100%, 85%, 50%, 25% and 12%)</li> <li><em>bkg_mxxx: </em>Estimate of the background noise floor (a.u. in dB) for each modulation depth. </li> <li><em>ftest_mxxx: </em>Result of the F-test statistical test (0 or 1) for each modulation depth.</li> </ul> <p> </p> <p>The structure of the .mat files that contain the EFR simulations is:</p> <ul> <li><em>exper_type</em>: Name of the simulated experiment</li> <li><em>species</em>: Species used in the AN model (in this study is always 2: human)</li> <li><em>species_age</em>: (Not used in this work). Age of the animal when species is 4: mouse</li> <li>modulation<em>: </em>Modulation depth of the SAM tone used in the simulation <em>(100%, 85%, 50%, 25% or 12%)</em></li> <li><em>f_on: </em>Center frequency of the on-frequency band (<em>2000 Hz</em>)</li> <li><em>f_off_hf: </em>Center frequency of the first off-frequency band (<em>3000 Hz</em>)</li> <li><em>f_off_vhf: </em>Center frequency of the second off-frequency band (<em>7000 Hz</em>) </li> <li><em>f_off_uvhf: </em>Center frequency of the third off-frequency band (<em>12000 Hz</em>)</li> <li><em>lvl_vect: </em>Stimulus level vector <em>(from 5 to 100 dB SPL, in steps of 5 dB)</em></li> <li><em>simul_efr </em> Structure with the simulated data <ul> <li>The data structure contains many fields which are matricies of size 3x20. The columns are the 20 stimulus levels defined in <em>lvl_vect</em>, and the first row is the simulated EFR, the second row is the estimates background noise floor in the simulation, and the third row is the output of the F-test statistics.</li> <li>The structure fields can be divided in 4 groups: <ul> <li><em>ihc_</em> Responses from the IHC (not shown in the paper)</li> <li><em>an_hs_</em> Responses from the High-SR fibers in the AN</li> <li><em>an_ms_</em> Responses from the Medium-SR fibers in the AN</li> <li><em>an_ls_</em> Responses from the Low-SR fibers in the AN</li> </ul> </li> <li>Each group has 5 responses corresponding to the on-frequency band (<em>_on</em>) and the three off-frequency bands (<em>_off_hf</em>, <em>_off_vhf</em>, <em>_off_uvhf</em>); and the sum across frequencies (<em>_across_f</em>)</li> </ul> </li> </ul>
Data for: Sequential infection of Daphnia magna by a gut microsporidium followed by a haemolymph yeast decreases transmission of both parasites
<p>This dataset supports the findings presented in:<br> <br> Manzi, F., Halle, S., Seemann, L., Ben-Ami, F., & Wolinska, J. (2021). Sequential infection of <em>Daphnia magna</em> by a gut microsporidium followed by a haemolymph yeast decreases transmission of both parasites. <em>Parasitology,</em> 1-42. doi:10.1017/S0031182021001384</p>
Seasonal trajectories of plant-pollinator interaction networks differ following phenological mismatches along an urbanization gradient - Data and code
<p>Dataset and code used in the article "Seasonal trajectories of plant-pollinator interaction networks differ following phenological mismatches along an urbanization gradient", by A. Fisogni et al., published in Landscape and Urban Planning (2022, 226:104512, <a href="https://www.sciencedirect.com/science/article/pii/S016920462200161X?via%3Dihub">https://doi.org/10.1016/j.landurbplan.2022.104512</a>)</p>
Pathobionts in the tumour microbiota predict survival following resection for colorectal cancer - pre-processed data
<p>A multicentre, prospective observational study was conducted of colorectal cancer (CRC) patients undergoing primary surgical resection in the United Kingdom and Czech Republic. Analysis was performed using metataxonomics (microbiome) and ultra-performance liquid chromatography mass spectrometry (UPLC-MS, metabolomics). Both datasets were pre-processed as described in the methods section of the main article. The data here were used as the input to the data analysis workflows available from <a href="https://github.com/jmp111/CRC">Github</a>.</p>
Data from: Capacity and selection in immersive visual working memory following naturalistic object disappearance
<p>Trial datasets and timeseries datasets associated with the experiment reported in the manuscript "Capacity and selection in immersive visual working memory following naturalistic object disappearance", by Babak Chawoush, Dejan Draschkow & Freek van Ede</p>
Fruit-feeding butterfly community data analysed in "Recovery patterns in community composition of fruit-feeding butterflies following 26 years of active forest restoration"
<p>Community data of fruit-feeding butterflies collected from Kibale National Park, Uganda, in the periods 2011-2012 and 2020-2021 analysed in our paper Korkiatupa et al. 2023: "Recovery patterns in community composition of fruit-feeding butterflies following 26 years of active forest restoration" (<em>Ecosphere</em> <span>14</span>(<span>5</span>): e4514. <a href="https://doi.org/10.1002/ecs2.4514">https://doi.org/10.1002/ecs2.4514</a>).</p> <p>The table consists of two parts. First part shows counts of individuals of butterfly species in each study site. Second part shows the metadata: code of studysite, census (2011-2012/2020-2021), planting year (planting year or "Primary forest"), and coordinates (WGS 84 coordinate system).</p>
Example data set for NG-QTAIM eigenvector-following trajectories: rotary f-NAIBP motor
<p>Example dataset for NG-QTAIM eigenvector following trajectories: the F-NAIBP molecular rotary motor.</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.