cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7117907
title: Chaotic fluctuations in mitochondrial function under oxidative stress. SOD2 concentrations of 0.016 mM

description: These chaotic time series of mitochondrial dynamics under conditions of oxidative stress are analyzed in detail in Kembro et al. 2018. Mitochondrial chaotic dynamics: Redox-energetic behavior at the edge of stability. Sci. Rep. (in press).<br>Mitochondrial model used was described in the project overview and in detail (Kembro et al. 2013. Biophys J 104(2):332-343; Kembro et al., 2014. Front Physiol 5:257).<br><b>Analytical methods. </b>Numerical integration of the ME-R model equations was performed with MatCont 2.4 in MATLAB 7.1, until steady-state solutions were obtained (i.e., when the magnitude of each time derivative was -10). Time series with duration of at least 6e<sup>6</sup> ms were constructed by numerical integration of model equations. To allow transient states to vanish, the system was computed during a time lapse of 2 e<sup>8</sup> ms.All studies were performed using the parameter setting optimized in our previous work (Kembro et al. 2013. Biophys J 104(2):332-343; Kembro et al., 2014. Front Physiol 5:257), with ADPm = 0.01mM, i.e. consistent with energized mitochondria under state 4 respiration.The two .txt file represents the time reference and the time series of variables output of the model, in order from left to right column: 1) Mitochondrial Ca+;2) Mitochondrial ADP; 3) Membrane potential; 4)Mitocondrial NADH; 5) Mitochondrial H+; 6) Mitochondrial Phosfate, Pi; 7) Isocitrate; 8) a-ketoglutarate; 9) Succinyl CoA; 10) Succinate; 11) Fumarate; 12) Malate; 13) Oxaloacetate; 14) NADPH; 15) Mitochondrial superoxide; 16) Extramitochondrial superoxide; 17) Mitochondrial hydrogen peroxide; 18) Extramitochondrial hydrogen peroxide; 19) Mitochondrial GSH; 20) Extramitochondrial GSH; 21)Mitochondrial GSSG; 22) Mitochondrial TrxSH2; 23) ExtramitochondrialTrxSH; 24)Mitochondrial PSSGm; 25) Extramitochondrial PSSG.<br>The parameter settings were:Model-simulated time series were calculated with 0.016 mM of SOD2, Shunt=0.04, SOD1 9.7 10<sup>-5</sup> mM. External superoxide perturbation: amplitude=1 10<sup>-7</sup> mM, period =30 s.
DOI: 10.6084/m9.figshare.7117910
title: Periodic oscillations in mitochondrial function under oxidative stress. SOD2 concentrations of 0.0164 mM

description: The time series are analyzed in detail in Kembro et al. 2018. Mitochondrial chaotic dynamics: Redox-energetic behavior at the edge of stability. Sci. Rep. (in press)<br><br>Oscillatory mitochondrial time series under conditions of oxidative stress. Mitochondrial model used was described in the project overview and in detail (Kembro et al. 2013. Biophys J 104(2):332-343; Kembro et al., 2014. Front Physiol 5:257). <br><b>Analytical methods. </b>Numerical integration of the ME-R model equations was performed with MatCont 2.4 in MATLAB 7.1, until steady-state solutions were obtained (i.e., when the magnitude of each time derivative was -10). Time series with duration of at least 6e<sup>6</sup> ms were constructed by numerical integration of model equations. To allow transient states to vanish, the system was computed during a time lapse of 2 e<sup>8</sup> ms. All studies were performed using the parameter setting optimized in our previous work (Kembro et al. 2013. Biophys J 104(2):332-343; Kembro et al., 2014. Front Physiol 5:257), with ADPm = 0.01mM, i.e. consistent with energized mitochondria under state 4 respiration.The two .txt file represents the time reference and the time series of variables output of the model, in order from left to right column: 1) Mitochondrial Ca+;2) Mitochondrial ADP; 3) Membrane potential; 4)Mitocondrial NADH; 5) Mitochondrial H+; 6) Mitochondrial Phosfate, Pi; 7) Isocitrate; 8) a-ketoglutarate; 9) Succinyl CoA; 10) Succinate; 11) Fumarate; 12) Malate; 13) Oxaloacetate; 14) NADPH; 15) Mitochondrial superoxide; 16) Extramitochondrial superoxide; 17) Mitochondrial hydrogen peroxide; 18) Extramitochondrial hydrogen peroxide; 19) Mitochondrial GSH; 20) Extramitochondrial GSH; 21)Mitochondrial GSSG; 22) Mitochondrial TrxSH2; 23) ExtramitochondrialTrxSH; 24)Mitochondrial PSSGm; 25) Extramitochondrial PSSG<br>The parameter settings were:Model-simulated time series were calculated with 0.0164 mM of SOD2, Shunt=0.04, SOD1 9.7 10<sup>-5</sup> mM. External superoxide perturbation: amplitude=1 10<sup>-7</sup> mM, period =30 s.
DOI: 10.6084/m9.figshare.7117907.v1
title: Chaotic fluctuations in mitochondrial function under oxidative stress. SOD2 concentrations of 0.016 mM

description: These chaotic time series of mitochondrial dynamics under conditions of oxidative stress are analyzed in detail in Kembro et al. 2018. Mitochondrial chaotic dynamics: Redox-energetic behavior at the edge of stability. Sci. Rep. (in press).<br>Mitochondrial model used was described in the project overview and in detail (Kembro et al. 2013. Biophys J 104(2):332-343; Kembro et al., 2014. Front Physiol 5:257).<br><b>Analytical methods. </b>Numerical integration of the ME-R model equations was performed with MatCont 2.4 in MATLAB 7.1, until steady-state solutions were obtained (i.e., when the magnitude of each time derivative was -10). Time series with duration of at least 6e<sup>6</sup> ms were constructed by numerical integration of model equations. To allow transient states to vanish, the system was computed during a time lapse of 2 e<sup>8</sup> ms.All studies were performed using the parameter setting optimized in our previous work (Kembro et al. 2013. Biophys J 104(2):332-343; Kembro et al., 2014. Front Physiol 5:257), with ADPm = 0.01mM, i.e. consistent with energized mitochondria under state 4 respiration.The two .txt file represents the time reference and the time series of variables output of the model, in order from left to right column: 1) Mitochondrial Ca+;2) Mitochondrial ADP; 3) Membrane potential; 4)Mitocondrial NADH; 5) Mitochondrial H+; 6) Mitochondrial Phosfate, Pi; 7) Isocitrate; 8) a-ketoglutarate; 9) Succinyl CoA; 10) Succinate; 11) Fumarate; 12) Malate; 13) Oxaloacetate; 14) NADPH; 15) Mitochondrial superoxide; 16) Extramitochondrial superoxide; 17) Mitochondrial hydrogen peroxide; 18) Extramitochondrial hydrogen peroxide; 19) Mitochondrial GSH; 20) Extramitochondrial GSH; 21)Mitochondrial GSSG; 22) Mitochondrial TrxSH2; 23) ExtramitochondrialTrxSH; 24)Mitochondrial PSSGm; 25) Extramitochondrial PSSG.<br>The parameter settings were:Model-simulated time series were calculated with 0.016 mM of SOD2, Shunt=0.04, SOD1 9.7 10<sup>-5</sup> mM. External superoxide perturbation: amplitude=1 10<sup>-7</sup> mM, period =30 s.
DOI: 10.6084/m9.figshare.7117910.v1
title: Periodic oscillations in mitochondrial function under oxidative stress. SOD2 concentrations of 0.0164 mM

description: The time series are analyzed in detail in Kembro et al. 2018. Mitochondrial chaotic dynamics: Redox-energetic behavior at the edge of stability. Sci. Rep. (in press)<br><br>Oscillatory mitochondrial time series under conditions of oxidative stress. Mitochondrial model used was described in the project overview and in detail (Kembro et al. 2013. Biophys J 104(2):332-343; Kembro et al., 2014. Front Physiol 5:257). <br><b>Analytical methods. </b>Numerical integration of the ME-R model equations was performed with MatCont 2.4 in MATLAB 7.1, until steady-state solutions were obtained (i.e., when the magnitude of each time derivative was -10). Time series with duration of at least 6e<sup>6</sup> ms were constructed by numerical integration of model equations. To allow transient states to vanish, the system was computed during a time lapse of 2 e<sup>8</sup> ms. All studies were performed using the parameter setting optimized in our previous work (Kembro et al. 2013. Biophys J 104(2):332-343; Kembro et al., 2014. Front Physiol 5:257), with ADPm = 0.01mM, i.e. consistent with energized mitochondria under state 4 respiration.The two .txt file represents the time reference and the time series of variables output of the model, in order from left to right column: 1) Mitochondrial Ca+;2) Mitochondrial ADP; 3) Membrane potential; 4)Mitocondrial NADH; 5) Mitochondrial H+; 6) Mitochondrial Phosfate, Pi; 7) Isocitrate; 8) a-ketoglutarate; 9) Succinyl CoA; 10) Succinate; 11) Fumarate; 12) Malate; 13) Oxaloacetate; 14) NADPH; 15) Mitochondrial superoxide; 16) Extramitochondrial superoxide; 17) Mitochondrial hydrogen peroxide; 18) Extramitochondrial hydrogen peroxide; 19) Mitochondrial GSH; 20) Extramitochondrial GSH; 21)Mitochondrial GSSG; 22) Mitochondrial TrxSH2; 23) ExtramitochondrialTrxSH; 24)Mitochondrial PSSGm; 25) Extramitochondrial PSSG<br>The parameter settings were:Model-simulated time series were calculated with 0.0164 mM of SOD2, Shunt=0.04, SOD1 9.7 10<sup>-5</sup> mM. External superoxide perturbation: amplitude=1 10<sup>-7</sup> mM, period =30 s.
DOI: 10.6084/m9.figshare.7117880
title: Datasets Abundant-Centre

description: Datasets used to test 9 abundant-centre hypotheses. CD=centroid distance; ED=edge distance, SUIT=suitability; MAR=marginality; MAH=Mahalanobis distance; envCD = distance from the centroid of the environmental space; envED = distance from the edge of the environmental space.
DOI: 10.6084/m9.figshare.7117880.v1
title: Datasets Abundant-Centre

description: Datasets used to test 9 abundant-centre hypotheses. CD=centroid distance; ED=edge distance, SUIT=suitability; MAR=marginality; MAH=Mahalanobis distance; envCD = distance from the centroid of the environmental space; envED = distance from the edge of the environmental space.
DOI: 10.6084/m9.figshare.7117832
title: erc_vazza_2016_1_new2.pdf

description: Parts B1 and B2 of my (successful) 2016 application to an ERC Starting Grant.(side note: the project has been moved to a different Main Host Institution after it has been granted, i.e. from the University of Hamburg to the University of Bologna). Link to the project:https://cosmosimfrazza.myfreesites.net/erc-magcow <br>
DOI: 10.6084/m9.figshare.7117826
title: Сагалевич, картинки

description: Доп файлы к статье.<br>
DOI: 10.6084/m9.figshare.7117826.v1
title: Сагалевич, картинки

description: Доп файлы к статье.<br>
DOI: 10.6084/m9.figshare.7117805
title: Early Neoproterozoic evolution of Southeast Pakistan: evidence from geochemistry, geochronology, and isotopic composition of the Nagarparkar Igneous Complex

description: Rocks of the early Neoproterozoic age of the world have remained in discussion for their unique identity and evolutionary history. The rocks are also present in Sindh province of Pakistan and have been in debate for a couple of years. Yet, these igneous rocks have been studied very poorly regarding U-Pb and Lu-Hf age dating. The early Neoproterozoic rocks located in Nagarparkar town of Sindh have been considered as shoulder of Malani Igneous Suite (MIS) discovered in Southwest of India. The Nagarparkar Igneous Complex (NPIC) rocks are low-grade metamorphosed, mafic and silicic rocks. These rocks are accompanied by felsic and mafic dikes. Two types of granite from NPIC have been identified as peraluminous I-type biotite granites (Bt-granites), of medium-K calc-alkaline rocks series and A-type potash granites (Kfs-granites) of high-K calc-alkaline rocks series. Geochemical study shows that these Kfs-granites are relatively high in K and Na contents and low MgO and CaO. The Bt-granites have positive Rb, Ba, and Sr with negative Eu anomalies rich with HFSEs Zr, Hf, and slightly depleted HREEs, whereas Kfs-granites have positive Rb with negative Ba, Sr, and Eu anomalies and have positive anomalies of Zr and Hf with HREEs. In addition, these rocks possess crustal material, which leads to the enrichment of some incompatible trace elements and depletion of Sr and Ba in Kfs-granites and relatively high Sr and Ba in Bt-granites, indicating a juvenile lower continental crust affinity. Zircon LA-ICP-MS U-Pb dating of these granites yielded weighted mean <sup>206</sup>Pb/<sup>238</sup>U ages ranging from 812.3 ± 14.1 Ma (<i>N</i> = 18; MSWD = 3.7); and 810 ± 7.4 Ma (<i>N</i> = 16; MSDW = 0.36) for the Bt-granites, and 755.3 ± 7.1 Ma (<i>N</i> = 21; MSDW = 2.0); NP-GG-01 and 736.3 ± 4.3 Ma (<i>N</i> = 24; MSWD = 1.05) for Kfs-granites, respectively. The Bt-granites and Kfs-granites have positive zircon ε<sub>Hf</sub><sup>(t)</sup> values, which specify that they are derived from a juvenile upper and lower continental crust. Based on the geochemical and geochronological data, we suggest that the Bt-granites were formed through lower continental crust earlier to the rifting time, whereas the Kfs-granites were formed via upper continental crust, during crustal thinning caused by Rodinia rifting. These zircon U-Pb ages 812 to 736 Ma, petrographic, and geochemical characteristics match with those of the adjacent Siwana, Jalore, Mount Abu, and Sirohi granites of MIS. Thus, we can suggest that NPIC granites and adjacent MIS can possibly be assumed as a missing link of the supercontinent Rodinia remnants.
DOI: 10.6084/m9.figshare.7117796
title: Muscular and circulatory acute molecular responses to iso-inertial exercise

description: Dataset of a study that investigated muscular and circulatory acute molecular responses to a flywheel based iso-inertial training session in resistance-trained men
DOI: 10.6084/m9.figshare.7117796.v5
title: Muscular and circulatory acute molecular responses to iso-inertial exercise

description: Dataset of a study that investigated muscular and circulatory acute molecular responses to a flywheel based iso-inertial training session in resistance-trained men
DOI: 10.6084/m9.figshare.7117679
title: One-hour social and reproductive behavioral time series of Japanese quail in diverse social environments.

description: We favor the conformation of divergent social environments by using the preselecting animals based on a combination of the 4 behavioral tests described in the project description. Social groups composed of three adult quail, 2 females and 1 male (156-171 days old). We evaluated social and reproductive behavior in these groups.Groups were housed in a white wooden apparatus measuring 80 x 40 x 40 cm (width x length x height, respectively) with wood-shavings on the floor. A feeder and an automatic nipple drinker were positioned in opposite corners of the apparatus. Nylon monofilament line was extended over the top of the boxes with a 1 cm separation in order to prevent the birds from escaping without interfering with their visualization. A video camera was suspended 1.5m above the box. Since only 4 social groups could be tested simultaneously, the setup was repeated 3 consecutive times. For convenience boxes in which each social group were placed were numbered 1-12, where boxes 1-4 were tested simultaneously first, 5-8 second and 9-12 last.We used the ANY-MAZE@ to register the following behaviors as described in Caliva et al. (2017) during a one-hour period between 9 and 10 am inmediatly after placing in box (Day1) after 48h of habituation to the novel setting (Day3):<b>Pecks: </b>when one bird raises its head and vigorously pecks the other bird’s body (usually on the head).<b>Grabs: </b>when a male catches (“grabs”) with their beak the neck or head region of the female.<b>Mounts: </b>while performing a grab, the male approaches a female from behind, and places both feet on the dorsal surface of its torso, stepping over the females’ tail.<b>Cloacal contacts: </b>during mounting, the male lifts his tail and tilts his pelvis underneath the other bird and briefly presses its cloaca against the female.<b>Threats: </b>one bird stands with its neck and head raised in front of the other bird that usually has its head at a lower level than the first.<b>Chase: </b>a bird runs after another that is escaping.<b>Foraging:</b> pecking at the ground or actively moving litter with beak. <b>Feeding:</b> peaking at food in the feeding trough. <b>Dust bathing:</b> vertical wing shakes in a lying position .Time series denote with the number one changes towards actively performing the given behavior, while the number zero indicates cessation of that behavior. <br>All time series are stored as text files (.txt). Considering that the 36 animals were evaluated in 12 mixed-sex groups of 3 birds in individual experimental boxes, each subject quail was identified by their experimental group number (Box), ID number of wing band, and sex (femaleA, femaleB or male). In the case of females an indication A or B is used to discriminate between the two. In the file name an indication of the corresponding bird is provided as "BoxNº_IDNº_sex_DayNº" <br>Data descriptor submitted to Sci Data "High resolution behavioral time series of Japanese quail within their their social environment"<b></b>
DOI: 10.6084/m9.figshare.7117673
title: CESM1CAM5 global coupled climate model ensemble simulations 1850-1979. All forcing and regional aerosol experiments (SST, precipitation, AOD, MOC)

description: Monthly sea surface temperature (SST), aerosol optical depth (AOD), precipitation (PRECIP), and Meridional Overturning Circulation (MOC) data from historical experiments (1850-1979) with the global coupled model CESM1-CAM5.<br>The data are from three experiments with 8 members each:<br>1) a CMIP5 standard all-forcing experiments (BTAL, in the publication ALL) <br><br>2) an experiment with all forcings except anthropogenic aerosol emissions from North America (BTALnNA, in the publication noNA, 8 members) and<br><br>3) an experiment with all forcings except anthropogenic aerosol emissions from Europe (BTALnEU, in the publication NoEU, 8 members) are kept at pre-industrial levels.<br>For more details on the model configuration, details of the modified emissions, and the definitions of the North American and European region, respectively, see reference:<br>Undorf, S., M. Bollasina, B. Booth, and G. Hegerl (2018), Contrasting the effects of the 1850‐1975 increase in sulphate aerosols from North America and Europe on the Atlantic in the CESM model, <i>Geophys. Res. Lett.</i>, 45, https://doi.org/10.1029/2018GL079970.<br>When using these data, please ensure to acknowledge the CESM project and the UK National Supercomputing Service ARCHER in addition to the reference above.<br><br>NOTE! The time coordinate needs to be corrected half a month backwards in all files.<br>
DOI: 10.6084/m9.figshare.7117673.v1
title: CESM1CAM5 global coupled climate model ensemble simulations 1850-1979. All forcing and regional aerosol experiments (SST, precipitation, AOD, MOC)

description: Monthly sea surface temperature (SST), aerosol optical depth (AOD), precipitation (PRECIP), and Meridional Overturning Circulation (MOC) data from historical experiments (1850-1979) with the global coupled model CESM1-CAM5.<br>The data are from three experiments with 8 members each:<br>1) a CMIP5 standard all-forcing experiments (BTAL, in the publication ALL) <br><br>2) an experiment with all forcings except anthropogenic aerosol emissions from North America (BTALnNA, in the publication noNA, 8 members) and<br><br>3) an experiment with all forcings except anthropogenic aerosol emissions from Europe (BTALnEU, in the publication NoEU, 8 members) are kept at pre-industrial levels.<br>For more details on the model configuration, details of the modified emissions, and the definitions of the North American and European region, respectively, see reference:<br>Undorf, S., M. Bollasina, B. Booth, and G. Hegerl (2018), Contrasting the effects of the 1850‐1975 increase in sulphate aerosols from North America and Europe on the Atlantic in the CESM model, <i>Geophys. Res. Lett.</i>, 45, https://doi.org/10.1029/2018GL079970.<br>When using these data, please ensure to acknowledge the CESM project and the UK National Supercomputing Service ARCHER in addition to the reference above.<br><br>NOTE! The time coordinate needs to be corrected half a month backwards in all files.<br>
DOI: 10.6084/m9.figshare.7117628.v1
title: Observations on Random Sampling Reduction Algorithms

description: Abstract:Development of efficient solvers of the (approximated) shortest vector problem over lattices is an important research area because the security of lattice-based schemes is based on the hardness of the shortest vector problem. Random sampling reduction is an approach to construct efficient solvers of the shortest vector problem by combining lattice basis reduction and sampling of short lattice vectors. In this talk, we show our observations on random sampling reduction algorithms, and recently proposed our probabilistic analysis framework (IACR ePrint 2018/815).<br><br>Note:This is revised version to fix several typos.To make the slide easier to read, three correlation heatmaps are uploaded separately.<br>
DOI: 10.6084/m9.figshare.7117598.v2
title: Comics Forum Tweetage 2014-2018. Scholarly Twitter Archive Numeralia

description: Presentation prepared to support Ernesto Priego's participation in Keynote: Possibilities and Perspectives- The Next Decade of Comics Scholarship, Comics Forum 2018, Leeds Library, Friday 21 September 2018. <br><br>Version 1 until Friday 10am; Version 2 final version.<br>
DOI: 10.6084/m9.figshare.7117628.v2
title: Observations on Random Sampling Reduction Algorithms

description: Abstract:Development of efficient solvers of the (approximated) shortest vector problem over lattices is an important research area because the security of lattice-based schemes is based on the hardness of the shortest vector problem. Random sampling reduction is an approach to construct efficient solvers of the shortest vector problem by combining lattice basis reduction and sampling of short lattice vectors. In this talk, we show our observations on random sampling reduction algorithms, and recently proposed our probabilistic analysis framework (IACR ePrint 2018/815).<br><br>Note:This is revised version to fix several typos.To make the slide easier to read, three correlation heatmaps are uploaded separately.<br>
DOI: 10.6084/m9.figshare.7117544
title: Thy1-jRGECO1a transgenic mouse lines confocal microscopy data

description: <b><i>Thy1 </i></b><b>transgenic mice expressing the red fluorescent calcium indicator jRGECO1a for neuronal population imaging <i>in vivo</i></b> Hod Dana<sup>1,2</sup>, Ondrej Novak<sup>1,3</sup>, Michael Guardado-Montesino<sup>1</sup>, James W. Fransen<sup>4</sup>Amy Hu<sup>1</sup>, Bart G. Borghuis<sup>4</sup>, Caiying Guo<sup>1</sup>, Douglas S. Kim<sup>1</sup>, Karel Svoboda<sup>1</sup> <sup>1 </sup><em>Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA </em><em><sup>2 </sup></em><em>Present address: Department of Neurosciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH </em><em><sup>3 </sup></em><em>Department of Auditory Neuroscience, Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Prague, Czech Republic</em><sup>4 </sup>Department of Anatomical Sciences and Neurobiology, University of Louisville School of Medicine, Louisville, KY<em> </em><em> </em><em>Supplementary Images:</em><em>High-resolution confocal images for mouse lines GP8.20, GP8.31, GP8.58, GP8.62.</em>For details see Dana et al Plos One, 2018