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Figure 3 in Synonymy of the water mite subgenera Orientmomonia and Kondia in the genus Momonia (Momoniidae, Acari): an evaluation based on morphology and molecular data
Figure 3 Male of Momonia(Orientmomonia) koreana. A – dorsal view of idiosoma; B – ventral view of idiosoma; C – left palp; D – I-L-1–6. E – IV-L-3–6. Scale bars: 100 μm.
Figure 5 in Synonymy of the water mite subgenera Orientmomonia and Kondia in the genus Momonia (Momoniidae, Acari): an evaluation based on morphology and molecular data
Figure 5 Maximum-likelihood phylogenetic tree based on the mitochondrial cytochrome oxidase subunit I (COI) gene sequences obtained for a set ofMomoniaspecimens. Bootstrap values (> 50%) related to the nodes are indicated (1,000 replicates).
Figure 1 in Synonymy of the water mite subgenera Orientmomonia and Kondia in the genus Momonia (Momoniidae, Acari): an evaluation based on morphology and molecular data
Figure 1 Provenance of the material used in the present study. Collection site A – Tatsuno City in Hyogo Prefecture; Collection site B – Aioi City in Hyogo Prefecture; Collection site C – Tsushima City in Nagasaki Prefecture.
Figure 4 in Synonymy of the water mite subgenera Orientmomonia and Kondia in the genus Momonia (Momoniidae, Acari): an evaluation based on morphology and molecular data
Figure 4 Female of Momonia(Kondia) sp. A – dorsal view of idiosoma; B – ventral aspect of unmounted specimen; C – ventral view of idiosoma; D – right palp; E – I-L-1–6; F – IV-L-3–6. Scale bars: 100 μm.
Companion data deposit of manuscript: Evaluating and improving the representation of bacterial contents in long-read metagenome assemblies
<p>This upload contains the metagenome assemblies and their binning results generated & described in the manuscript "Evaluating and improving the representation of bacterial contents in long-read metagenome assemblies" (preprint version: arxiv2210.00098, "Towards complete representation of bacterial contents in metagenomic samples"). </p> <p>Mapping of sample names in the file names and the descriptors used as in the manuscript can be found in table S1, which is available along with the manuscript and also included in the supplementary_tables_and_figures tar archive here.</p>
Evaluation of point-of-use treatments and biochar to reduce 1,2,3-trichloropropane (TCP) contamination in drinking water
<p>From the 1940s to the 1980s, 1,2,3-trichloropropane (TCP) was widely present as an impurity in soil fumigants to eliminate plant parasitic nematodes. TCP also saw wide usage as a degreaser and solvent in industrial processes. In rural agricultural regions with a history of fumigant use, TCP is a common pollutant in groundwater. As a potent suspected carcinogen (California MCL 5 ng/L), TCP poses a risk to communities reliant on domestic wells. Lacking the populations needed for more centralized water treatment facilities, these communities often use point-of-use (POU) treatment technologies or buy bottled water. In this study, we tested commercially available water pitchers equipped with carbon filters for point-of-use TCP treatment efficacy. As a less costly carbon alternative, we also tested low-cost, locally sourced biochar made from almond shells. Biochar could serve as a sustainable alternative to the current coconut and coal-based carbon feedstocks. Pitcher point-of-use filters removed at or above 98% of TCP in tap water derived from untreated groundwater during their lifetime of use. In our batch studies, almond biochar did absorb TCP at a lower efficiency than commercially available granulated carbon. Ultimately, the study's findings could assist affected communities and households in identifying efficient and cost-effective treatment technologies at the domestic well and household levels.</p>
Dataset for Evaluating habitat-specific interference in automated radio telemetry systems: implications for animal movement studies
<h1>Abstract </h1> <p>Automated radio telemetry systems have become a popular and invaluable tool in tracking the activity and movement of wild animals. However, many environmental conditions can hinder accuracy when tracking with this technology. For instance, study sites may contain multiple habitat types, each habitat uniquely affecting the signal strength received from tagged species. To investigate the influence of a structurally diverse study site on an automated radio telemetry system, we conducted this project at a restored and managed pine barren habitat that consisted of a mix of mature pitch pine, treated pitch pine, scrub oak, and hardwood forests. This site, Montague Plains Wildlife Management Area, Montague, Massachusetts, is also a known breeding ground for Eastern whip-poor-will (Antrostomus vociferus). To measure the relationship of radio signal strength with distance across each habitat, we used radio telemetry equipment manufactured by Cellular Tracking Technologies. We produced negative exponential decay functions measuring radio signal strength over distance and tested for differences among habitat types on radio signal strength (RSS). We found that decay function parameters significantly differed by habitat type, prompting us to investigate if accounting for these differences improved location estimate accuracy. To test this, we estimated known locations using trilateration methods with and without habitat calibration. Comparing these tests indicates that habitat-specific adjustments significantly improved location accuracy. Lastly, we visualized estimated RSS-based locations of one week of whip-poor-will data and compared them to GPS data generated from the same individual. Previous studies have accounted for types of environmental interference (like elevation) in the field but have avoided incorporating habitat-specific factors by working with node networks covering a relatively small area, but in this study, we examined the potential to scale up for larger areas and in more complex habitats.</p> <p> </p>
Evaluation of Upper Tropospheric Geopotential Height Anomalies over the Tropical and Subtropical Oceans in CMIP6 Models Using GNSS Radio Occultation Observations
<p>The set-up of CESM2-CAM6 sensitivity experiments for winter season (Dec-Jan-Feb: DJF), with prognostic falling ice radiative effects on (SON) and off (NOS), is an updated two-moment stratiform cloud scheme (MG2, Gettelman & Morrison, 2015) in the CESM2 atmospheric component of CAM6. CESM2-CAM6 participated in CMIP6. Both the NOS and SON simulations were configured following the same approach as the CMIP6 "historical" run spanning from 1980 to 2014.</p> <p> </p> <p>The data are:</p> <p> </p> <p>TS: skin temperature (K)</p> <p>TAUX: zonal surface wind stress</p> <p>TAUY: meridinal surface wind stress</p> <p>DTCOND: moist condensation heating rate</p> <p>QRL: long wave heating rate</p> <p>OMEGA: vertical motion</p> <p>Z3: geopotential height</p> <p> </p>
Figure 3 in Evaluation on reducing toxicity of fluoxastrobine with doped TiO2 nanoparticles
Figure 3. Mortality rates (%) determined in X. laevis embryos and tadpoles exposed to degradation products of FLX (5 mg L-1).
Figure 2 in Evaluation on reducing toxicity of fluoxastrobine with doped TiO2 nanoparticles
Figure 2. (A) LC-MS/MS spectra of 5 mg L-1 FLX with Mn–TiO in 0.15% wt v-1 catalyst in sol before irradiation and (B) after 15 h of 2 UV-C irradiation. (C) LC-MS/MS spectra of 5 mg L-1 FLX with S–TiO in 0.1%wt v-1 catalyst in sol before irradiation and (D) after 10 2 h of UV-C irradiation.
Figure 6 in Evaluation of vertical and horizontal changes in community structure of zooplankton in a deep dam lake
Figure 6. CCA triplots for zooplankton abundance and environmental variables (variables are represented by arrows. Species are depicted by points; the numbers indicate sampling stations). Abbreviations: K.coch: K. cochlearis; K.quad: K. quadrata; K.trop: K. tropica; K.long: K. longispina; P.vulg: P. vulgaris; P.doli: P. dolichoptera; S.oblo: S. oblonga; A.prio: A. priodonta; A.brig: A. brightwelli; L.pate: L. patella; L.rhom: L. rhomboides; L.quad: L. quadridentata; Habro.: Habrotrocha sp.; F.long: F. longiseta; D.cucu: D. cucullata; D.long: D. longispina; B.long: B. longirostris; C.spha: C. sphaericus; C.rect: C. rectangula; Cyc sp: Cyclops sp.; Naup: nauplius.
Figure 4 in Evaluation of vertical and horizontal changes in community structure of zooplankton in a deep dam lake
Figure 4. The Shannon–Weaver species diversity index (Hʹ) based on numbers of individuals during the study period.
Figure 1 in Evaluation of vertical and horizontal changes in community structure of zooplankton in a deep dam lake
Figure 1. Map of Karakaya Dam Lake on the Euphrates River in eastern Anatolia. Sampling stations surveyed in this study are indicated.
Figure 3 in Evaluation of vertical and horizontal changes in community structure of zooplankton in a deep dam lake
Figure 3. Vertical distribution of zooplankton in the lake. Total density (ind m–3) of main zooplankton groups was demonstrated at different depths by horizontal bars.
Figure 2 in Evaluation of vertical and horizontal changes in community structure of zooplankton in a deep dam lake
Figure 2. Vertical profiles (every 5 m of depth) of temperature (°C) and dissolved oxygen (mg L–1) in the study area. Illustrations were formed for the vertical zooplankton sampling period.
Evaluating the Role of Biochar in Altering Chlorinated Phenol Behavior in Alluvial Soil Systems
<div> <div> <div> <div> <div> </div> </div> </div> </div> </div> <div> <div> <div> <div> <div> <div> <p>Row and modelled data were obtained for four types of chlorinated phenols during transport in sandy alluvial soil and biochar-enriched soil. Raw data are provided for the characterization of sandy alluvial soil used in this study. The data are used for the preparation of a manuscript titled <em>Evaluating the Role of Biochar in Altering Chlorinated Phenol Behavior in Alluvial Soil Systems</em>.</p> </div> </div> </div> </div> </div> </div>
Extended Evaluation Data of TrADS: a Trust-Aware Decentralized Social Network
<p>This dataset includes the evaluation data for the Paper "TrADS: a Trust-Aware Decentralized Social Network".<br>Within the ZIP File the following files are included in the dataset:</p> <ul> <li><strong>survey.pdf:</strong> The survey as PDF print. IFrames of TrADS used during the survey are hidden in the PDF.</li> <li><strong>all.xlsx:</strong> An Excelfile containing all the following .CSV files as worksheets.</li> <li><strong>raw_data.csv:</strong> The raw data exported from the used survey tool of the conducted empircal user study.</li> <li><strong>group1_unfiltered.csv:</strong> All participants' data of group 1.</li> <li><strong>group2_unfiltered.csv:</strong> All participants' data of group 2.</li> <li><strong>group1.csv:</strong> All filtered participants' data of group 1, who correctly answered the control questions.</li> <li><strong>group1_ueq_data.csv:</strong> All filtered participants's ueq+ question responses of group 1. Only including the questions 1 - 4 but not the question about dimension importance (q5).</li> <li><strong>group1_ueq_importance.csv:</strong> All filtered participants's ueq+ question responses about personal importance of group 1. Only including the question 5 about dimension importance.</li> <li><strong>group1_ueq_kpis:</strong> Including the ueq+ KPI values of all participants in group 1.</li> <li><strong>group2.csv:</strong> All filtered participants' data of group 2, who correctly answered the control questions.</li> <li><strong>group2_ueq_data.csv:</strong> All filtered participants's ueq+ question responses of group 2. Only including the questions 1 - 4 but not the question about dimension importance (q5).</li> <li><strong>group2_ueq_importance.csv:</strong> All filtered participants's ueq+ question responses about personal importance of group 2. Only including the question 5 about dimension importance.</li> <li><strong>group2_ueq_kpis:</strong> Including the ueq+ KPI values of all participants in group 2.</li> <li><strong>participants.csv:</strong> General information about participants grouped by both groups and joint.</li> <li><strong>likert_questions.csv:</strong> Mean Values and Standard Deviations (Std) of all statements rated on a 5-point Likert scale. It includes Means and Stds for Group 1, Group 2, Group 1 + Group 2 concatinated, and the values of the first user study published in the previous paper on TrADS <a href="https://zenodo.org/records/10641724" target="_blank" rel="noopener">(also available in previous dataset on Zenodo)</a>.</li> </ul>
Managing multiple threats: Evaluating the efficacy of broad-scale introduced predator management in improving native mammal resilience to fire
<p>Preventing further biodiversity loss requires understanding which processes threaten biodiversity and the effectiveness of management actions in mitigating them. Threatening processes can interact in complex and unexpected ways, but different threats are often managed independently. Here, we develop a conceptual model to identify the conditions needed for management of a single threat to achieve a net conservation benefit in systems with multiple interacting threats, and demonstrate its relevance in a replicated case-study experiment. In Australia, introduced red foxes (<em>Vulpes vulpes</em>) and feral cats (<em>Felis catus</em>) may hunt vulnerable native mammals more effectively after fire, due to loss of understory vegetation. However, the efficacy of broad-scale control of introduced predators in improving native mammal resilience to fire has not been quantified. Moreover, many studies assessing the impacts of prescribed fire on species rely on a much smaller number of independent replicates. Using a natural before-after control-impact experiment with 14 prescribed fires, each > 200 ha, we tested whether existing landscape-scale fox baiting programs influenced the immediate effects of prescribed fire on these two introduced predators and five medium-sized native mammals, including the threatened long-nosed potoroo (<em>Potorous tridactylus</em>) and southern brown bandicoot (<em>Isoodon obesulus</em>). Fox occupancy increased across both treatments post-fire, but baiting reduced the magnitude of increase. In contrast, mean feral cat occupancy remained constant in unbaited areas post-fire, but nearly doubled in fox-controlled areas, possibly due to a mesopredator release. Existing landscape-scale fox control programs did not clearly improve the short-term resilience of native mammals to prescribed fire (at least under the current fire and fox management regimes in our study landscapes). These results likely emphasise the need to integrate fire and predator management strategies for threatened faunal conservation iIn the presence of acute disturbances such as fire, threatened native mammals may require more intensive and integrated management of fire and introduced predators, such as (e.g., through more intensive targeted predator controlbaiting around fire events, or intensive protection usingthrough natural or artificial refuges).</p>
Papers and KPIs for the Evaluation of Renewable Energy Communities' Performance
<p>This database contains the methodology used to explore and identify the papers that containes KPIs related to the evaluation of RECs performance. This methodology is divided into three phases: </p> <p>1.1) <em>Papers Exploration – </em>Comprehensive search of papers in the field of RECs using Scopus and Web Of Science databases;</p> <p>1.2) <em>Papers Screening</em> – Initial screening of collected literature based on research domain and accessibility;</p> <p>1.3) <em>Papers Eligibility</em> – Further filtering papers by extracting those that explicitly define KPIs through mathematical formulations in the context of the RECs.</p> <p> In the <em>Papers Exploration</em> step, the authors conducted a systematic review of the state-of-the-art of literature on performance metrics in the context of the renewable energy community. The search was conducted in March 2024 using the search engines Scopus and Web Of Science (the used queries are detailed explain in thte database). The output of this phase is a large database of the most recent and relevant studies, cataloged by the following information: authors, article title, abstract, author keywords, index keywords, and year of publication. At this stage, only journal articles and research works published after 2010 were considered. In the <em>Papers Screening</em> phase, the articles are further filtered by the authors screening manually all papers based on keywords, titles, and abstracts, removing articles not relevant to the context of the RECs. In addition, articles for which it was not possible to access the full text are excluded. In the <em>Papers Eligibility</em> phase, the articles are entirely read to identify those articles that directly address the use of performance metrics. The eligibility criterion used by the reviewers’ team refers to the explicit definition of KPIs through mathematical formulas combined with their direct usage to evaluate RECs’ performances. The main objective of this phase is therefore to identify those articles that explicitly define and use KPIs, so that they can later be collected and labeled, based on their definition and usage.<br><br></p> <p>In additions, KPIs are extracted from the papers deemed elegible generating Tables A1, A2, A3 and A4. In these tables, similar KPIs are aggregated together in one single mathematical definition based on the methodology described in <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4991932">Key Performance Indicators for Renewable Energy Communities: A Comprehensive Review by Lorenzo Giannuzzo, Minuto Francesco Demetrio, Daniele Salvatore Schiera, Samuele Branchetti, Carlo Petrovich, Angelo Frascella, Nicola Gessa, Andrea Lanzini :: SSRN</a></p>
Evaluation of high-resolution WRF simulation in urban areas - Effect of different physics schemes on simulation performance in the Rhine-Main-Neckar area
<p>This dataset contains data sampled from a WRF sensitivity study saved in NetCDF format. The study was run over 4 months of the year 2020. The folders contain the following data:</p> <table> <tbody> <tr> <td><strong>File</strong></td> <td><strong>Datasets</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>wrf_met_sample_full.nc</td> <td>all</td> <td>WRF meteorology sampled at the 19 weather stations in the simulation domain</td> </tr> <tr> <td>wrf_met_sample_full_and_quant.nc</td> <td>all</td> <td>As above, but resampled onto the measured meteorology and with summary statistics</td> </tr> <tr> <td>wrf_met_sample_full_ucmheights.nc</td> <td>only 2020_12</td> <td>Same as wrf_met_sample_full.nc but only for the run using the vertical layer distribution of UCM</td> </tr> <tr> <td>wrf_met_sample_full_and_quant_ucmheights.nc</td> <td>only 2020_12</td> <td>Same as wrf_met_sample_full_and_quant.nc but only for the run using the vertical layer distribution of UCM</td> </tr> <tr> <td>wrf_pblh_sample_full.nc</td> <td>all</td> <td>WRF PBLH (and custom PBLH_RIB) sampled at the 2 radio sonde stations in the simulation domain</td> </tr> <tr> <td>wrf_pblh_sample_full_and_quant.nc</td> <td>all</td> <td>As above, but resampled onto the measured meteorology and with summary statistics</td> </tr> <tr> <td>era5_met_sample_full.nc</td> <td>all</td> <td>ERA5 meteorology sampled at the 19 weather stations in the simulation domain</td> </tr> <tr> <td>era5_met_sample_full_and_quant.nc</td> <td>all</td> <td>As above, but resampled onto the measured meteorology and with summary statistics</td> </tr> <tr> <td>era5_pblh_sample_full_and_quant.nc</td> <td>all</td> <td>WRF PBLH (and custom PBLH_RIB) sampled at the 2 radio sonde stations in the simulation domain, resampled onto the measured meteorology and with summary statistics</td> </tr> </tbody> </table> <p>Each of these files contains the samples and statistics as NetCDF Variables. These Variables have multiple dimensions, which describe the individual datapoints. For the WRF samples, these dimensions are:</p> <table> <tbody> <tr> <td><strong>Dimension</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>Time</td> <td>time since start of simulation</td> </tr> <tr> <td>station_id</td> <td>the ID of the station where the sample was taken (meteo - length 19, PBLH - length 2)</td> </tr> <tr> <td>pbl</td> <td>Planetary Boundary Layer scheme (Bou-Lac / MYJ / YSU)</td> </tr> <tr> <td>lsm</td> <td>Land Surface Model scheme (N / NMP)</td> </tr> <tr> <td>slm</td> <td>Surface Layer Model scheme (MM5 / MO)</td> </tr> <tr> <td>urb</td> <td>Urban Parametrization scheme (SLUCM / BEP)</td> </tr> </tbody> </table> <p>Not all combinations between different simulation schemes exist, so some values in the NetCDF Variables are NaNs.</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.