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1,465 results for “resilience”
Figure 10 in Parasites of Moroccan desert Coptodon guineensis (Pisces, Cichlidae): transition and resilience in a simplified hypersaline ecosystem
Figure 10. Abundance of infection of Coptodon guineensis at Sebkha Imlili by acanthocephalan Acanthogyrus (Acanthosentis) cf. tilapiae according to fish total length. Infection occurred in fish as small as 20 mm. Larger fish were more often infected than smaller fish.
Figure 5 in Parasites of Moroccan desert Coptodon guineensis (Pisces, Cichlidae): transition and resilience in a simplified hypersaline ecosystem
Figure 5. Unidentified metacercariae from Coptodon guineensis at Sebkha Imlili. A. Metacercaria (arrow) showing ocelli and associated with intense granulocytic reaction in intestinal mucosa. B. Fresh squash of spleen showing numerous metacercariae.
Figure 4 in Parasites of Moroccan desert Coptodon guineensis (Pisces, Cichlidae): transition and resilience in a simplified hypersaline ecosystem
Figure 4. Metacercariae of heterophyid Pygidiopsis genata from Coptodon guineensis at Sebkha Imlili. A. Numerous metacercariae encysted on the outer wall of stomach. B & C. Fresh squashes of infected tissues with clusters of live metacercariae. D. SEM of excysted metacercariae showing a pyriform scaled body with terminal oral sucker (arrow) and subequatorial acetabulum (arrowhead). E. Oral sucker unarmed. F. small ventral sucker. Insert: pectinate body scales.
Figure 6 in Parasites of Moroccan desert Coptodon guineensis (Pisces, Cichlidae): transition and resilience in a simplified hypersaline ecosystem
Figure 6. Prevalence of infection (%) of Coptodon guineensis at Sebkha Imlili. Blue bars = acanthocephalan Acanthogyrus (Acanthosentis) cf. tilapiae (December 2018: n = 93; April 2019: n = 80; July 2019: n = 92; October 2019: n = 57); Orange bars = metacercariae of Pygidiopsis genata (Dec 2018: n = 92; April 2019: n = 80; July 2019: n = 39; October 2019: n = 53); Grey bars = unidentified metacercariae (December 2018: n = 92; April 2019: n = 80; July 2019: n = 25; October 2019: n = 35).
Figure 2 in Parasites of Moroccan desert Coptodon guineensis (Pisces, Cichlidae): transition and resilience in a simplified hypersaline ecosystem
Figure 2. Acanthocephalan Acanthogyrus (Acanthosentis) cf. tilapiae from Coptodon guineensis at Sebkha Imlili. Fresh preparations. A. Female worm (gravid). B. Male worm. C. Ellipsoid eggs in gravid female. D. Proboscis and anterior trunk (montage) of male worm. Note strong anterior hooks and abruptly smaller middle and posterior hooks as well as regular rows of spines that were lost and leave rosette marks on tegument. E. Posterior end of male worm showing terminal genital opening and everted copulatory bursa. F. Posterior end of female showing terminal genital opening.
Figure 9 in Parasites of Moroccan desert Coptodon guineensis (Pisces, Cichlidae): transition and resilience in a simplified hypersaline ecosystem
Figure 9. Mean trunk length of females of acanthocephalan Acanthogyrus (Acanthosentis) cf. tilapiae in Coptodon guineensis at Sebkha Imlili (December 2018: n = 41; April 2019: n = 42; July 2019: n = 47; October 2019: n = 50). Worms were significantly smaller in April and October compared to December and July.
Figure 8 in Parasites of Moroccan desert Coptodon guineensis (Pisces, Cichlidae): transition and resilience in a simplified hypersaline ecosystem
Figure 8. Proportions of females of acanthocephalan Acanthogyrus (Acanthosentis) cf. tilapiae in Coptodon guineensis at Sebkha Imlili according to stage of maturity. Solid bars = immature females (no genitalia visible); dotted bars = ovigerous females (ovarian balls visible); striped bars = gravid females (December 2018: n = 41; April 2019: n = 42; July 2019: n = 47; October 2019: n = 50). Gravid females were present throughout the year but significantly more abundant proportionally in December and July, which may indicate a short life span of the worms and quick turnover in the fish.
Figure 3 in Parasites of Moroccan desert Coptodon guineensis (Pisces, Cichlidae): transition and resilience in a simplified hypersaline ecosystem
Figure 3. Acanthocephalan Acanthogyrus (Acanthosentis) cf. tilapiae from Coptodon guineensis at Sebkha Imlili. SEM. A. Male proboscis showing large anterior hooks markedly separated from small posterior hooks. B. Anterior trunk of female showing rows of spines. C. Female body spine.
Computational Artifacts for the Paper "Are Noise-resilient Logical Timers useful for Performance Analysis?"
<p>This repository contains computational artifacts for the paper "Are Noise-resilient Logical Timers useful for Performance Analysis?" to be submitted to <a href="https://sc-protools-workshop.github.io/protools24/">ProTools@SC24.</a></p> <p>See also the <a href="https://sc24.supercomputing.org/program/papers/reproducibility-initiative/">SC24 reproducibility initiative.</a></p> <p> </p> <p>Contains</p> <ul> <li>Source code of <a href="https://doi.org/10.5281/zenodo.10822140">Score-P </a>, including implementation of the logical clock algorithm from the paper</li> <li>Software to post-process the Cube files generated by measurements</li> <li>Benchmarks <ul> <li>Source code</li> <li>Configuration skripts</li> <li>Measurement results, including output logs, Cube files</li> <li>Post-processing skripts and results</li> </ul> </li> </ul> <p> </p>
Figure 3. Distribution of Q3 values-Secondary Structure Prediction of Protein using Resilient Back Propagation Learning Algorithm
<p>The estimated accuracy for the α- helices (QH), β- strands (QE), C-coil states (QC), and three<br> state together (Q3) for the system is shown in Figure 3.</p>
Figure 2. PAM250 matrix for the encoded sequence-Secondary Structure Prediction of Protein using Resilient Back Propagation Learning Algorithm
<p>The PAM matrix (Dayhoff et al., 1978) describes the probability that original amino acid<br> will be replaced by another amino acid over a defined evolutionary interval. The unit of<br> evolutionary divergence is defined as the interval in which 1% of the amino acids have been<br> changed between two sequences. The work uses PAM250, which assumes the occurrence of 250-<br> point mutations per 100 amino acids.<br> So, for the given the protein sequence GIVEQCCASVCSLYQLENYCN, A will be replaced<br> by 1 -3 0 1 -3 -1 0 5 -2 -3 -4 -2 -3 -5 0 1 0 -7 -5 -1 as shown in Figure 2.</p>
Figure 1: Snapshot of the CB396 dataset-Secondary Structure Prediction of Protein using Resilient Back Propagation Learning AlgorithmSecondary Structure Prediction of Protein using Resilient Back Propagation Learning Algorithm
<p>The dataset used for this work is CB396. This dataset contains 396 non-redundant sequences<br> derived from the 3Dee database created by Cuff and Barton (Cuff & Barton, 1999). It contains 396<br> proteins with their respective secondary structure as shown in Figure 1.</p>
Influence of storm sequencing and beach recovery on sediment transport and beach resilience data set at CIEM large scale wave flume.
<p>The Influence of storm sequencing and beach recovery on sediment transport and beach resilience (RESIST) experiments project proposes to study experimentally sequences of storm induced erosion and beach recovery, with a particular focus on the poorly known morphodynamic processes under low energy conditions. Series of large scale experimental tests were done to collect data on the cross-shore hydrodynamics, sediment transport and beach evolution. The main aim of this proposal is to investigate the influence of sequences of beach erosion-recovery in the overall beach profile evolution.</p> <p>The tested wave conditions (2 erosive and 3 Accretive bichromatic conditions) were combined to form three sequences of changing high/mild energy conditions. Each condition started from an initial beach 1/15 handmade profile.</p> <p>The experiments were carried out in the large scale wave flume CIEM at Universitat Politècnica de Catalunya (UPC), Barcelona within the program of Transnational Access of Hydralab+.</p> <p>Due to its size, the data set can not be placed on this repository and will be provided on demand. Please contact with the authors or with the data manager of the CIEM installation.</p>
Supplements to "Digital traces of climate risks: assessing the communication impact of Paris resilience strategy".
<p>These supplements correspond the data used in the PhD thesis : “Digital traces of climate risks: assessing the impact of Paris resilience strategy”, published in 2019 on <a href="http://theses.fr/">theses.fr</a> by Rosa Vicari (HM&Co - École des Ponts ParisTech), under the supervision of Daniel Schertzer (HM&Co - École des Ponts ParisTech).</p> <p>More precisely the data set corresponds to the corpora and term lists that are used in the analysis (based on advanced text mining and graph representation) of press articles and tweets concerning flood events in France and strategic documents released by public authorities.</p> <p>The dataset includes the following files:</p> <p>- Suppl2-2016Parisflood-termlist.csv : the list of terms extracted from the corpus of press articles covering the 2016 Seine River flood.</p> <p>- Suppl6-Cotedazflood-termlist.csv: the list of terms extracted from the corpus of press articles covering the 2015 Côte-d'Azur flood.</p> <p>- Suppl7-Corpus-PA-Strategies.csv : the corpus of strategic documents released by public authorities to cope with flood risk in Paris.</p> <p>- Suppl8-Term-list-PA-Strategies.csv : the list of terms extracted from the corpus of strategic documents released by public authorities to cope with flood risk in Paris (2003 - 2017).</p> <p>The following files are not available and cannot be shared for copyright reasons:</p> <p>- Suppl1-2016Parisflood-corpus.csv : the corpus of press articles covering the 2016 Seine River flood.</p> <p>- Suppl3-2018Parisflood-corpus.csv : the corpus of press articles covering the 2018 Seine River flood.</p> <p>- Suppl5-Cotedazflood-corpus.csv : the corpus of press articles covering the 2015 Côte-d'Azur flood.</p> <p>The following file is not available and cannot be shared for privacy reasons:</p> <p>- Suppl4 - Tweet corpus - 2016 Paris flood.csv : the corpus of tweets covering the 2016 Seine River flood.</p>
Figure 8 in Substratum stability and coral reef resilience: insights from 90 years of disturbances on a reef in American Samoa
Figure 8. Large coral colonies thrive on solid reef rock blocks in the field of rubble. This demonstrates that substratum stability is the key determining factor under relatively uniform conditions of water quality and larval recruitment.
Figure 2 in Substratum stability and coral reef resilience: insights from 90 years of disturbances on a reef in American Samoa
Figure 2. Water quality in inner Pago Pago Harbor greatly improved and remained improved after tuna canneries were required to modify their waste disposal processes in 1991. Data were taken by the American Samoa Environmental Protection Agency and the figure is from Craig et al. 2005 with permission.
Figure 1 in Substratum stability and coral reef resilience: insights from 90 years of disturbances on a reef in American Samoa
Figure 1. Acropora exposed at low tide on Alfred Mayor's transect near Aua in Pago Pago Harbor in 1917 (reprinted from Mayor 1924 with permission of the Carnegie Institution, Washington, DC).
Figure 3 in Substratum stability and coral reef resilience: insights from 90 years of disturbances on a reef in American Samoa
Figure 3. Density of corals from 1917 to 2007 along the Aua transect from the shore to the reef crest.
Figure 9 in Substratum stability and coral reef resilience: insights from 90 years of disturbances on a reef in American Samoa
Figure 9. Unattached colonies of Pavona divaricata and Porites cylindrica with living tissue on all sides.
Climate Change Adaptive Resilience Analysis Dataset
<p><span>Greenhouse gas escalation and severely deteriorated environment with global warming and climate change impose substantial difficulties in energy resilience for adaption and mitigation of climate change and zero-carbon transitions. However, uncertainties in supply-demand from climate change and climate-adaptive resilience for electrified and integrative PV-battery-building systems remain unclear. In this research, following </span><span>zero-energy building design principles and innovative U-value/M-value battery sizing methods</span><span>, a </span><span>tailored</span><span> </span><span>‘kWp-kWh-m<sup>2</sup>’ design approach is proposed with </span><span>intrinsic relationships of prosumer-storage</span><span> to achieve renewable self-sufficiency and avoid battery oversizing</span><span> in both centralized and distributed forms.<a name="OLE_LINK1"></a> Comprehensive analysis is conducted by assessing economic-environmental indicators, such as levelized costs of storage, net present values, decarbonization potentials, and policy incentives, followed by the evaluation of provincial system configurations considering energy system variations across diverse climate change conditions and geographic areas. </span><span>Results reveal significant regional variations induced by climatic conditions, resource availability, local grid energy structure, and electricity prices. Notably, the long-term economic-ecological viability of the proposed PV-battery-building system is highlighted, especially with optimal battery integrations. As climate change progresses, the research provides invaluable guidelines for zero-energy transitions from optimal system design, provincial-level system configurations, and performance evaluation, guiding the strategic investment and targeted policy interventions towards sustainability transformations.</span></p> <p><span>The comprehensive dataset encompasses 25-year time series of instantaneous photovoltaic (PV) generation, building electricity demand, PV-battery system performance, and battery capacity sizing procedures across five distinct climatic regions in China. This data accounts for the impacts of different climate change scenarios, including the typical year as well as the Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 for the years 2020, 2030, 2060, and 2100. </span></p>
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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.