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FIGURES 18–25 in The South American spider genera Mesabolivar and Carapoia (Araneae, Pholcidae): new species and a framework for redrawing generic limits
FIGURES 18–25. Mesabolivar acrensis sp. n. (18–22; ZFMK Ar 18942–43) and M. maraba sp. n. (23–25, ZFMK Ar 18948). 18–19. Male chelicerae, frontal and lateral views. 20–21, 23–24. Epigyna, ventral and lateral views. 22, 25. Cleared female genitalia, dorsal views. Abbreviations: ep, epigynal pocket; pp, pore plate; v, 'valve'. Scale lines: 0.5.
FIGURES 26–31. Mesabolivar huambisa Huber, 2000 in The South American spider genera Mesabolivar and Carapoia (Araneae, Pholcidae): new species and a framework for redrawing generic limits
FIGURES 26–31. Mesabolivar huambisa Huber, 2000. Left procursi, retrolateral views, and left bulbal processes, prolateral views; from Samiria (type locality) (26, 29, MUSM), Tabatinga (27, 30, ZFMK Ar 18950), and Belém (28, 31, ZFMK Ar 18951). Arrow points at distinctive screw-shaped sclerite. Scale lines: 0.5 (26–28), 0.3 (29–31).
FIGURES 32–47 in The South American spider genera Mesabolivar and Carapoia (Araneae, Pholcidae): new species and a framework for redrawing generic limits
FIGURES 32–47. Female epigyna in ventral and lateral views and cleared female genitalia, dorsal views, Mesabolivar pseudoblechroscelis group (part 1). 32–38. M. acrensis sp. n., from Rio Branco (32–33, 38, ZFMK Ar 18943), Cruzeiro do Sul (34–37, ZFMK Ar 18946). 39–41. M. maraba sp. n. (ZFMK Ar 18948). 42–47. M. huambisa Huber, 2000, from Samiria (42– 43, MUSM), Tabatinga (44–45, ZFMK Ar 18950), and Belém (46–47, ZFMK Ar 18951).
FIGURES 13–17 in The South American spider genera Mesabolivar and Carapoia (Araneae, Pholcidae): new species and a framework for redrawing generic limits
FIGURES 13–17. Mesabolivar acrensis sp. n. (13–15, ZFMK Ar 18942) and M. maraba sp. n. (16–17, ZFMK Ar 18948). 13– 14. Left male palp, prolateral and retrolateral views. 15–16. Left bulbal processes, prolateral views (arrow points at distinctive sclerotized area). 17. Left procursus, retrolateral view. Abbreviations: b, genital bulb; bp, bulbal process; c, coxa; f, femur; p, procursus, ta, tarsus; ti, tibia; tr, trochanter. Scale lines: 0.5 (13–14, 17), 0.3 (15–16).
FIGURES 1–12. Live specimens, Mesabolivar pseudoblechroscelis group. 1–2. M in The South American spider genera Mesabolivar and Carapoia (Araneae, Pholcidae): new species and a framework for redrawing generic limits
FIGURES 1–12. Live specimens, Mesabolivar pseudoblechroscelis group. 1–2. M. acrensis sp. n., male and female from Rio Branco. 3–4. M. maraba sp. n., male and female from Marabá. 5–6. M. huambisa Huber, 2000, male from Tabatinga, female from Belém. 7–8. M. amazonicus sp. n., male and female from Humaitá. 9–10. M. jamari sp. n., male and female from Jamari. 11–12. M. tapajos sp. n., male and female from Tapajós.
Data for "The influence of internal variability on Earth's energy balance framework and implications for estimating climate sensitivity"
<p>This archive contains processed model output necessary for reproducing the figures in Dessler, Maurtisen, Stevens, ACP, 2018</p> <p>historicalEnsemble.nc contains data from the 100-member MPI historical ensemble</p> <p>forcing_aed_ensemble.nc contains the forcing for the historical runs</p> <p>model0001.nc is the control run of the MPI model<br> model0003.nc is an abrupt 4xCO2 run of the MPI model</p> <p>cmip5 contains data from individual CMIP5 models </p> <p>the folder "fig 5" contains zonal average fields necessary for that figure</p>
THEORY OF PLANNED BEHAVIOR FRAMEWORK AND EXAMPLE SURVEY
<p><strong>FIGURE </strong><strong>2</strong><strong>.</strong> THEORY OF PLANNED BEHAVIOR FRAMEWORK AND EXAMPLE SURVEY</p>
Space Weather Modeling Framework ensemble simulations
<p><strong>Space Weather Modeling Framework ensemble simulations</strong></p> <p>This archive contains folders for 41 simulations with the operational geospace configuration of the University of Michigan's Space Weather Modeling Framework[1]. The operational configuration uses the University of Michigan's BATS-R-US magnetohydrodynamics code[2], the Ridley ionospheric electrodynamics solver[3], and the Rice Convection Model[4] inner magnetosphere model. More details of the operational geospace configuration are given by [5].</p> <p>These simulations were performed for, and used in, the paper</p> <p>> "Perturbed Input Ensemble Modeling with the Space Weather Modeling Framework",<br> > S.K. Morley, D.T. Welling and J.R. Woodroffe,<br> > Space Weather, 2018. doi: <a href="https://doi.org/10.1029/2018SW002000">10.1029/2018SW002000</a></p> <p><em>Directory Structure</em><br> All numbered directories are members of a perturbed input ensemble. The directory labeled "orig" is the reference (unperturbed) simulation. Each directory is structured identically.</p> <p>Each run directory contains `PARAM.in`, `LAYOUT.in` and `magin_GEM.dat` files. This set of files consistutes the required inputs for each run that are invariant. That is, these files are identical between runs and control the setup of the model and the types of outputs generated. Each run directory also contains an `IMF.dat` file that sets the upstream boundary condition. This file differs between each simulation. The values in each ensemble member have been perturbed from the values given in the reference simulation using a block resampling of measurement errors between an L1 solar wind monitor and a near-Earth monitor.</p> <p>Each run directory also contains `GM` and `GM\IO2` subdirectories. The `GM\IO2` subdirectory contains simulation output from the global magnetosphere module. Three files are present for each simulation: `geoindex_e20100404-190000.log`, `magnetometers_e20100404-190000.mag`, and `log_e20100404-190000.log`. These are standard SWMF log files that can be parsed and analyzed using, for example, the `pybats` module in the SpacePy[6] software package[7]. The simulation ouput includes ground magnetic perturbations at a set of magnetic observatory locations, local K indices, an estimated Kp index, a 1 minute resolution Sym-H/Dst index equivalent and simulated auroral electrojet indices.</p> <p><br> <em>Basic Analysis</em><br> To derive the time derivative of the horizontal ground magnetic perturbation (dB/dt) the magnetometer log file can be loaded using SpacePy<br> </p> <pre><code class="language-python">>>> import spacepy.pybats.bats >>> magdata = spacepy.pybats.bats.MagFile('run_001/GM/IO2/magnetometers_e20100404-190000.mag') >>> magdata.calc_h() #calculates horizontal from North and East components >>> magdata.calc_dbdt() #calculates time derivatives</code></pre> <p>To then calculate binned maxima in the dB/dt time series, e.g., for the Yellowknife (YKC) station<br> </p> <pre><code class="language-python">>>> import datetime as dt >>> import numpy as np >>> import spacepy.toolbox as tb >>> dBdt_max20, bintimes = tb.windowMean(magdata['YKC'], time=subset['time'], winsize=dt.timedelta(minutes=20), overlap=dt.timedelta(0), st_time=dt.datetime(2010,4,5), op=np.max)</code></pre> <p><br> and to turn this into a binary event series indicating a threshold crossing<br> </p> <pre><code class="language-python">>>> threshold = 1.1 #nT/s >>> predicted_event = np.asarray(dBdt_max20) >= threshold</code></pre> <p><br> Assuming that the observational data are obtained from NASA's CCMC and similarly processed, the event validation statistics can be calculated and displayed using the PyForecastTools package[8].<br> </p> <pre><code class="language-python">>>> import verify >>> c_table = verify.Contingency2x2.fromBoolean(predicted_event, observed_event) >>> ctable.summary(ci='bootstrap', verbose=True)</code></pre> <p> </p> <p><em>Footnotes</em><br> [1] Tóth, G., I. V. Sokolov, T. I. Gombosi, D. R. Chesney, C. R. Clauer, D. L. D. Zeeuw, K. C. Hansen, K. J. Kane, W. B. Manchester, R. C. Oehmke, K. G. Powell, A. J. Ridley, I. I. Roussev, Q. F. Stout, O. Volberg, R. A. Wolf, S. Sazykin, A. Chan, B. Yu, and J. KÃşta (2005), Space weather modeling framework: A new tool for the space science community, Journal of Geophysical Research: Space Physics, 110(A12), doi:10.1029/2005JA011126.</p> <p>[2] de Zeeuw, D. L., T. I. Gombosi, C. P. T. Groth, K. G. Powell, and Q. F. Stout (2000), An adaptive MHD method for global space weather simulations, IEEE Transactions on Plasma Science, 28(6), 1956–1965, doi:10.1109/27.902224.</p> <p>[3] Ridley, A. J., T. I. Gombosi, and D. L. DeZeeuw (2004), Ionospheric control of the magnetosphere: conductance, Annales Geophysicae, 22(2), 567–584, doi:10.5194/angeo-22-567-2004.</p> <p>[4] Toffoletto, F., S. Sazykin, R. Spiro, and R. Wolf (2003), Inner magnetospheric modeling with the Rice convection model, Space Science Reviews, 107(1), 175–196, doi: 10.1023/A:1025532008047.</p> <p>[5] Haiducek, J. D., D. T. Welling, N. Y. Ganushkina, S. K. Morley, and D. S. Ozturk (2017), SWMF global magnetosphere simulations of January 2005: Geomagnetic indices and cross-polar cap potential, Space Weather, 15(12), 1567–1587, doi: 10.1002/2017SW001695.</p> <p>[6] Morley, S. K., J. Koller, D. T. Welling, B. A. Larsen, M. G. Henderson, and J. T. Niehof (2011), Spacepy - a Python-based library of tools for the space sciences, in Proceedings of the 9th Python in science conference (SciPy 2010), Austin, TX.</p> <p>[7] SpacePy is packaged on PyPI, with the official git repository on SourceForge and an unofficial mirror on github.</p> <p>[8] PyForecastTools is packaged on PyPI and the repository is on github. The latest release is archived on Zenodo with doi: 10.5281/zenodo.1256921. The citation for v1.0.1 is Steve Morley. (2018, June 28). drsteve/PyForecastTools: PyForecastTools: Version 1.0.1 (Version v1.0.1). Zenodo. http://doi.org/10.5281/zenodo.1299389</p> <p> </p>
data and appendix for paper "From Analytical Purposes to Data Visualizations: A Decision Process Guided by a Conceptual Framework and Eye Tracking"
<p>the folder contains the following:</p> <p>1. Data from the pre-experiment questionnaire provided to the participants (pre-experiment_data.xlsx)</p> <p>2. Questions and answer data (answers_accuracy.xlsx)</p> <p>3. Online figures appendix (figures.pdf)</p>
FIGURE 5 in Bryozoan framework composition in the oddly shaped reefs from Abrolhos Bank, Brazil, southwestern Atlantic: taxonomy and ecology
FIGURE 5. Scanning electron micrographs of five bryozoan species. A, B. Stylopoma variabilis n. sp. A. Detail of a small fragment showing some zooids and an ooecium. B. Frontal view of one ooecium showing the crescent-shaped aperture and the fused and asymmetrical labellum. C–E. Stylopoma hastata n. sp. C. Detail of part of the colony showing zooids and different kinds of avicularia: small and triangular lateral oral avicularia, two large and spear-shaped interzooidal avicularia, and a giant elongated and curved avicularium. D. Detail of the distal part of a zooid showing the orifice with U-shaped sinus, small condyles, and a triangular lateral avicularium. E. Detail of a giant avicularium with curved, elongate rostrum. F. Hippaliosina imperfecta, detail of two zooids with a pair of elongate distal avicularia. G. Utinga castanea, detail of the colony showing zooids with different kinds of avicularia and ooecia with a pair of small avicularia. H. Arthropoma cecilii, detail of fertile and infertile zooids showing orifices, perforate frontal walls and smooth ooecia.
FIGURE 1 in Bryozoan framework composition in the oddly shaped reefs from Abrolhos Bank, Brazil, southwestern Atlantic: taxonomy and ecology
FIGURE 1. Maps and in situ photographs of the study area and sampling method. A. Regional location of study area (black square—Abrolhos Bank, AB). B. Local reef habitats (light grey) and the two sampling sites (Parcel dos Abrolhos, PA and California Reef, CR). C. Aerial view of PA reefs southeastern from Abrolhos Archipelago. D. Closer aerial view of PA reefs. E. Core sampling using a submersible hydraulic drill by rebreather diving. F. CR pinnacle structure at 25 m depth. Photos: Áthila Bertoncini, F. Moraes and G. Amado-Filho.
FIGURE 7 in Bryozoan framework composition in the oddly shaped reefs from Abrolhos Bank, Brazil, southwestern Atlantic: taxonomy and ecology
FIGURE 7. In situ underwater photographs of six bryozoan species recorded from Abrolhos Bank, Brazil. A, B. Steginoporella magnilabris. C. Reptadeonella bipartita. D. Celleporaria atlantica. E. Stylopoma variabilis n. sp. F. Utinga castanea. G. Arthropoma cecilii. Photos by Áthila Bertoncini/Rede Abrolhos.
FIGURE 3 in Bryozoan framework composition in the oddly shaped reefs from Abrolhos Bank, Brazil, southwestern Atlantic: taxonomy and ecology
FIGURE 3. Scanning electron micrographs of four bryozoan species. A. Metrarabdotos aff. jani, detail of some autozooids showing orifice with small, slit-shaped sinus and lateral, elongate avicularium. B. Metrarabdotos sp., general view of the fragment showing some autozooids with almost circular orifice and a pair of lateral distal avicularium. C–G. Parasmittina distincta n. sp. C. General view of a fragment showing autozooids with two oral spine bases and different kinds of avicularia: shoe-shaped, triangular and elongate. D. General view of a fragment showing autozooids with almost circular orifice, large lyrula, three or four oral spine bases and shoe-shaped avicularium. E. Detail of orifice showing four oral spine bases, large anvil-shaped lyrula and prominent condyles. F. Detail of two autozooids with two and three distal oral spines and short and large triangular lateral avicularium. G. General view of a fragment showing autozooid with two oral distal spines, lyrula and a putative ooecium. H. Parasmittina abrolhosensis n. sp., general view of a fragment showing some autozooids with different kinds of avicularia, orifice circular with three to four oral spine bases and tall and narrow lyrula.
FIGURE 6 in Bryozoan framework composition in the oddly shaped reefs from Abrolhos Bank, Brazil, southwestern Atlantic: taxonomy and ecology
FIGURE 6. Scanning electron micrographs of three bryozoan species. A. Gemelliporina glabra, fragment showing orifices and a small avicularium. B, C. Plesiocleidochasma acuminata n. sp. B. General view of a fragment showing infertile zooids. C. Detail of some zooids showing cleithridiate orifices, a few scattered areolar pores and acuminate avicularia with rostra ending in a sharp and elongate tip. D–F. Rhynchozoon aff. rostratum. D. General view of a colony part showing some zooids with peristomial tubercles and frontal avicularia. E. Detail of some autozooids showing peristomial tubercles and frontal, triangular avicularia. F. Detail of one zooid showing distally beaded orifice and a suboral lateral avicularium with a triangular rostrum, and a suboral umbo.
FIGURE 2 in Bryozoan framework composition in the oddly shaped reefs from Abrolhos Bank, Brazil, southwestern Atlantic: taxonomy and ecology
FIGURE 2. Scanning electron micrographs of six bryozoan species. A. Steginoporella magnilabris, part of the colony showing the shape and disposition of the autozooids. B. Labioporella tuberculata, part of the colony with some autozooids. C, D. Crassimarginatella winstonae n. sp., general view of the colony with autozooids and one avicularium. E. Detail of the colony showing an interzooidal avicularium. E. Exechonella sp., general view of a colony fragment. F. Reptadeonella bipartita, general view of colony part showing some autozooids with elliptic orifice, median avicularium and ascopore. G, H. Celleporaria atlantica, detail of some zooids showing orifices, and suboral avicularia on umbos. H. Detail of an autozooid showing an avicularium at the base of the umbo.
FIGURE 4 in Bryozoan framework composition in the oddly shaped reefs from Abrolhos Bank, Brazil, southwestern Atlantic: taxonomy and ecology
FIGURE 4. Scanning electron micrographs of three bryozoan species. A–D. Parasmittina abrolhosensis n. sp. A. Detail of some autozooids showing the orifice, lyrula, condyles and three or four oral spine bases, and a lateral elongate avicularium. B. Detail of an elongate lateral avicularium with serrated rostrum. C. Detail of an autozooid showing the orifice with anvil, tall lyrula and a pair of condyles, and a large and spatulate avicularium. D. Detail of a fragment showing some fertile autozooids. E, F. Hemismittoidea asymmetrica n. sp. E. Detail of some autozooids showing the orifice with six and seven distal spines, large anvil-shaped lyrula, large and triangular avicularia, and a perforated ooecium. F. Detail of a fertile zooid showing a perforated ooecium and orifice with a pair of spines others, hidden by the ooecium. G, H: Stylopoma variabilis n. sp. G. Detail of a fragment showing autozooids and two elongate, spatulate interzooidal avicularia. H. Detail of the distal region of an autozooid showing the orifice with U-shaped sinus, condyles and small triangular lateral avicularium.
Metal−Organic Frameworks as Efficient Oral Detoxifying Agents
<p>Poisoning and accidental oral intoxication are<br> major health problems worldwide. Considering the insufficient<br> efficacy of the currently available detoxification treatments, a<br> pioneering oral detoxifying adsorbent agent based on a single<br> biocompatible metal−organic framework (MOF) is here<br> proposed for the efficient decontamination of drugs commonly<br> implicated in accidental or voluntary poisoning. Furthermore, the<br> in vivo toxicity and biodistribution of a MOF via oral<br> administration have been investigated for the first time. Orally<br> administered upon a salicylate overdose, this MOF is able to<br> reduce the salicylate gastrointestinal absorption and toxicity more<br> than 40-fold (avoiding histological damage) while exhibiting exceptional gastrointestinal stability (<9% degradation), poor<br> intestinal permeation, and safety.</p>
PROPTI - An Generalised Inverse Modelling Framework - Data Set
<p><strong>Contents</strong></p> <p>Data set supplementary to the conference paper "<a href="https://www.researchgate.net/publication/328933654_PROPTI_-_A_Generalised_Inverse_Modelling_Framework">PROPTI - A Generalised Inverse Modelling Framework</a>", presented at the <em>3rd European Symposium on Fire Safety Science</em>, ESFSS 2018 in Nancy, France.</p> <p> </p> <p><strong>Technical Information</strong></p> <p>Each ZIP archive represents a sub-directory of the original directory. For the analysis script to work properly out of the box it is necessary to keep this structure. Thus, simply extract all archives into the same directory.</p> <p>Note: Size on disc, after extraction, is about 260 MB.</p>
HISMACITY pro Dataset Framework
<p>The tool targets small municipalities in Europe. Through the award-winning certification system, the Protocol supports the fulfillment of best practices. Such practices can enhance town attractiveness to counteract excessive land use due to urban growth and to reduce demographic decline in internal areas. The research methodology is grounded on building a dynamic dataset using Geo Big Data, Local Data, Mobile Data (via ICT), and Real Time Data through sensors. This tool aims at building algorithms to calculate indicators measuring the quality standards of integrated interventions. The reason is to reach specific goals within the defined Priority Areas of the Historical Small Smart City. Being highly adaptive, the framework follows Urban Responsive Design principles based on weighted suitability models that can be calibrated by changing the input data and the weights of the linear combinations formula. The research results highlight varying framework data, including the tool’s development procedures and practicality.</p>
Computation-Ready, Experimental Metal–Organic Frameworks
<p>Experimentally refined crystal structures for metal–organic frameworks (MOFs) often include solvent molecules and partially occupied or disordered atoms. This creates a major impediment to applying high-throughput computational screening to MOFs. To address this problem, we have constructed a database of MOF structures that are derived from experimental data but are immediately suitable for molecular simulations. </p> <p>The development of the CoRE MOF 2014 database is described in “Computation-ready, experimental metal-organic frameworks: A tool to enable high-throughput screening of nanoporous crystals” Chung, Y.G. et al., Chem. Mater. 2014, 26, 6185-6192 (DOI: <a href="https://doi.org/10.1021/cm502594j">10.1021/cm502594j</a>). The CoRE MOF 2014 database was developed through a collaboration of research groups participating in the Nanoporous Materials Genome Center that is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-12ER16362.</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.