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266 results for “experimental models”
Experimental data analyzed in: Signal detection models as contextual bandits
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Experimental measurements and uncertainty analysis for validation of the Building Electrical Efficiency Analysis Model (BEEAM)
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An Experimental Test of Lanchester’s Models of Combat in the Neotropical Termite Nasutitermes corniger (Blattodea: Termitidae)
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TagSeq for gene expression in non-model plants: a pilot study at the Santa Rita Experimental Range NEON core site
<p>TagSeq analysis scripts and assembled transcriptomes for four vascular plant species from the Santa Rita Experimental Range, AZ. Transcriptomes for each species were sequenced and assembled as described below. Additional details available in the associated manuscript: MS LINK. Raw reads for each available at NCBI BioProject #PRJNA599443.</p> <p> </p> <p><strong>Taxon selection and sampling </strong></p> <p>This study focused on four commonly-occurring species at the Santa Rita Experimental Range Long Term Research and Core NEON site (SRER). These include the native species <em>Tidestromia</em> <em>lanuginosa</em> (Nutt.) Standl. (Amaranthaceae; ‘woolly tidestromia’), <em>Parkinsonia</em> <em>florida</em> (Benth. ex A. Gray) S. Watson. (Fabaceae; ‘blue palo verde’), and <em>Bouteloua</em> <em>aristidoides</em> (Kunth) Griseb. (Poaceae; ‘needle grama’), as well as the introduced species <em>Eragrostis</em> <em>lehmanniana</em> Nees (Poaceae; ‘Lehmann lovegrass’; native to southern Africa). All species were identified using a combination of the historical flora of the Santa Rita Experimental Range (Medina, 2003), the Arizona Flora (Kearney et al., 1960), and the Flora of North America (Flora of North America Editorial Committee, eds. 1993). Vouchers were deposited in the University of Arizona herbarium (ARIZ). Tissue from mature plants was collected from an apparently healthy individual representing each target species during the 2017 growing season. An entire stem was sampled for <em>B. aristidoides</em> (with flowers and fruits) and <em>E. lehmanniana</em> (without flowers or fruits). Leaves and leaflets only were sampled for <em>P. florida</em> and <em>T. lanuginosa</em>.</p> <p> </p> <p><strong>RNA extraction and RNA-seq</strong></p> <p>Total RNA was extracted from tissue using the Spectrum Plant Total RNA Kit (Sigma-Aldrich Co., St. Louis, MO, USA) following Protocol A. RNA was used to prepare cDNA using Nugen’s Ovation RNA-Seq System via single primer isothermal amplification (Catalogue # 7102-A01) and automated on the Apollo 324 liquid handler (Wafergen). cDNA was quantified on the Nanodrop (Thermo Fisher Scientific) and was sheared to approximately 300 bp fragments using the Covaris M220 ultrasonicator. Libraries were generated using Kapa Biosystem’s library preparation kit (KK8201). Fragments were end repaired and A-tailed, and individual indexes and adapters (Bioo, catalogue #520999) were ligated on each separate sample. The adapter ligated molecules were cleaned using AMPure beads (Agencourt Bioscience/Beckman Coulter, A63883), and amplified with Kapa’s HIFI enzyme (KK2502). Each library was then analyzed for fragment size on an Agilent’s Tapestation, and quantified by qPCR (KAPA Library Quantification Kit, KK4835) on Thermo Fisher Scientific’s Quantstudio 5 before multiplex pooling (13-16 samples per lane) and paired-end sequencing at 2x150 bp on the Illumina NextSeq500 platform at Arizona State University’s CLAS Genomics Core facility. Raw read quality was assessed using fastQC (Andrews, 2010).</p> <p> </p> <p><strong><em>De novo</em> transcriptome assembly</strong></p> <p>Raw sequence reads were processed using the SnoWhite pipeline (Barker et al., 2010a; Dlugosch et al., 2013), which included trimming adapter sequences and bases with a quality score below 20 from the 3' ends of all reads, removing reads that are entirely primer and/or adapter fragments using TagDust (Lassmann et al., 2009), and removing polyA/T tails with SeqClean (https://sourceforge.net/projects/seqclean/). All transcriptomes were assembled with SOAPdenovo-Trans v1.03 (Xie et al., 2014) using a k-mer of 57. Assembled sequences for each species are in the files ending ".scafSeq".</p> <p> </p> <p><strong>Protein Translations</strong></p> <p>We used TransPipe (Barker et al., 2010) to identify plant proteins within the assembled transcripts for each reference transcriptome and provide protein and in-frame nucleic acid sequences for each species. The reading frame and protein translation for each sequence was identified by comparison to protein sequences from 25 sequenced and annotated plant genomes from Phytozome (Goodstein et al., 2012). Using BLASTX (Wheeler et al., 2008), best hit proteins were paired with each gene at a minimum cutoff of 30% sequence similarity over at least 150 sites. Genes that did not have a best hit protein at this level were removed. To determine the reading frame and generate estimated amino acid sequences, each gene was aligned against its best hit protein by Genewise 2.2.2 (Birney et al., 2004). Based on the highest scoring Genewise DNA-protein alignments, stop and 'N' containing codons were removed to produce estimated amino acid sequences for each gene. Output included paired DNA and protein sequences with the DNA sequence reading frame corresponding to each protein sequence. Nucleic acid sequence files end in “.fna”, whereas amino acid sequence files end in “.faa”. Numbers of sequences in each of these files correspond to the position of the sequence in the associated assembly file.</p> <p> </p> <p><strong>Custom scripts</strong></p> <p>“removePCRdups57.pl” is a Perl script that takes an input FASTQ file and removes exact duplicates identified over a supplied length at the beginning (3’ end) of the read. </p> <p>Run: perl removePCRdups57.pl <inputFASTQ> <length></p> <p> </p> <p>“create_GTF.pl” is a Perl script that takes an input FASTA file and creates a GTF file suitable for input into HtSeq-count v.0.5.4 (Anders et al., 2015).</p> <p>Run: perl create_GTF.pl <inputFASTA></p> <p> </p> <p>“combine_HtSeq.pl” is a Perl script that takes a set of htseq output files and makes a tab delim table of counts with header of sample names and first col of row names. The input file list file should be a text file with lists of Htseq files to combine on each line, where lines are tab delimited of the following form:</p> <p> <NameForOutputFile> <firstHtseqFile> <NextHtseqFile> <...etc...></p> <p>Run: perl combine_HtSeq.pl <inputFileList></p> <p> </p>
Experimental data for "Development of Experimental Techniques for Parameterization of Multi-scale Lithium-ion Battery Models"
<p>This dataset is for the validation data in Chen et al. (2020). It contains data for three different LG M50 cells undergoing an experiment in which the cells are charged in a constant-current/constant-voltage fashion and discharge at a constant current for different C-rates (C/10, C/2, 1C and 1.5C). Apart from the current and voltage, the temperatures of the cell surface and the thermal chamber in which they are cycled is recorded too.</p> <p><strong>References:</strong></p> <p>Chang-Hui Chen <em>et al</em> 2020 <em>J. Electrochem. Soc.</em> <strong>167</strong> 080534 (<a href="https://doi.org/10.1149/1945-7111/ab9050">https://doi.org/10.1149/1945-7111/ab9050</a>)</p>
MONITORING AND MODELING OF HYDROLOGICAL PROCESSES IN THE SEMIARID REGION OF BRAZIL: THE CARIRI EXPERIMENTAL BASINS
<p><strong>DATASET DESCRIPTION</strong> - Two experimental basins – the Cariri basins – were installed in a typically semiarid region in the State of Paraíba, Brazil, for obtaining reliable estimates of runoff and soil erosion in different scales to evaluate the influence of the human activities and other factors over the processes of runoff and erosion. In the first basin, located in the municipality of Sumé, the field studies were carried out at three different scales: four micro-basins with an area of around 0.5 ha; nine standard Wischmeier-type erosion plots of 100 m<sup>2</sup> and seven sample plots of 1 m<sup>2</sup>. The experimental units had varied vegetal cover and management and, except the sample plots, were subjected to natural rainfall events only, and were monitored from 1982 to 1991. The total runoff and total sediment yield were determined for each of the events of precipitation. The installations of the second basin, in the near municipality of São João do Cariri, were planned for the continuation of the studies initiated at Sumé, and include erosion plots (100 m<sup>2</sup>), micro-basins, and sub-basins, which are being monitored for runoff and sediment production up to now. Among them, two nested micro-basins were monitored to detect any scale effect at the micro-basin level. Nearly 600 events of natural precipitation, that produced runoff in at least one of the experimental units, have been registered. This bulk of data was utilised to evaluate the influence of various factors, including cultivation practices. The data collected so far has been successfully used to calibrate hydrological models for plots and micro-basins. Parameters have been tested by means of cross validations among micro-basins and sub-basins.</p> <p><strong>FILENAMES </strong>– The data files are divided into three categories: Description of the equipment utilized for collecting data and their locations, the data collected from the monitored experimental basins and another with maps, figures and pictures. The file names are designated with the basin name and the content. The files describing the equipment comprise: BASINNAME_DATADESCRIPTION, where BASINNAME could be EBS or EBSJC. The files with the data collected in the experimental basins are denominated like: BASINNAME_DATANAME. The DATANAME will be one of the three that may be, precipitation, runoff and sediment yield, or climatologic data. The file with maps and other information are identified as: BASINNAME_GEOPHYSICDATANAME, and BASINNAME_PICTURES. The geophysical data refer to topographic data, soil data, land cover and the drainage network. Graphs, pictures, etc., are included in the PICTURES file.</p> <p><strong>DATAFORMAT </strong>– The data file about equipment and localization as well as the data collected in experimental units are of the type “. csv”, the geophysical data are of either “.dwg” or “.shp”. The figures and picture are in the format: .jpeg, .png or .tif.</p> <p><strong>ACKNOWLEDGEMENTS </strong>– SUDENE – the Superintendency for the Development of the Northeast of Brazil with the cooperation of ORSTOM – the French Government Agency for Technical Cooperation Overseas was responsible for implementing the program of Representative and Experimental Basins in the region beginning in the decade of 1970. Pierre Audry, Eric Cadier, Jean Leprun and Michel Molinier, hydrologists and soil scientists from France played key roles in the selection of site, installation of experimental units and beginning the operation of the EBS. Beronildo Freitas was the engineer from SUDENE responsible for technical coordination and administration. The contributions of other researchers and technical people have been listed by Srinivasan and Galvão (2003). The installation of the research catchment at São João de Cariri had the valuable collaboration of GTZ, the cooperation Agency of the Government of Germany. Dr. Ing Ubald Koch was responsible for getting all the equipment, installing them and conducting research work along with the members of the Hydrology Research Group of the Federal Universities of Paraiba and Campina Grande. Late prof. Manoel Gilberto de Barros efficiently coordinated the field work. Eduardo Figueiredo, Celso Santos and Ricardo Aragão have made note worthy contributions. The Ministry of Science and Technology of Brazil has provided the bulk of the financial support needed for the operation of the basins, through its main funding agencies of CNPq (National Council for Development of Science and Technology) and FINEP (Agency for Financing research Studies and Projects).</p>
Experimental Data for: Research Perspective on Supporting Software Engineering via Physical 3D Models
<p>Experimental data for the experiment presented in the technical report 1507: "Research Perspective on Supporting Software Engineering via Physical 3D Models"</p>
Development of predictive models of the kinetics of a hydrogen abstraction reaction combining quantum-mechanical calculations and experimental data
<p>The files contain the electronic structure calculations for all the levels of theory tested in this work.</p>
Experimental data for "Spot-On: robust model-based analysis of single-particle tracking experiments"
<p><strong>Overview of experimental spaSPT data</strong></p> <p>To comprehensively test Spot-On over many different conditions, we conducted 1064 spaSPT experiments. The raw data is freely available and the purpose of this ReadMe file is to describe the organization, acquisition parameters and format of the data. The data is for 4 different cell lines imaged over 15 different conditions yielding a total of 60 different conditions. The four cell lines were:</p> <ul> <li> <p>U2OS C32 Halo-CTCF</p> </li> <li> <p>U2OS H2B-Halo-SNAP</p> </li> <li> <p>U2OS Halo-3xNLS</p> </li> <li> <p>mESC (JM8.N4) C3 Halo-Sox2</p> </li> </ul> <p>The cell lines were constructed in different ways. U2OS C32 Halo-CTCF was made by homozygous endogenous N-terminal tagging of CTCF in human osteosarcoma U2OS cells using CRISPR/Cas9-mediated genome-editing as described (C32 refers to clone number 32)<sup>1</sup>. We note the CTCF is an essential gene and that N-terminal tagging did not appear to affect CTCF function or expression level according to a series of control experiments<sup>1</sup>. Moreover, C32 Halo-CTCF has been authenticated using Short Tandem Repeat (STR) profiling (performed by Dr. Alison N. Killilea at the UC Berkeley Cell Culture Facility) against the following loci: THO1, D5S818, D13S317, D7S820, D16S539, CSF1PO, AMEL, vWA and TPOX. The C32 Halo-CTCF cell line showed a 100% match with U2OS.</p> <p>U2OS H2B-Halo-SNAP was made through random integration of a H2B-HaloTag-SNAP-Tag transgene expressed using the EF1a promoter with an IRES-NeoR gene for drug selection. After transfection, cells were selected using G418 until a pure cell population was obtained. This cell line has also been described previously<sup>1</sup>. The wild-type U2OS cell line used to make this cell line was also authenticated using STR profiling against the same loci as C32 and also showed a 100% match with U2OS.</p> <p>U2OS Halo-3xNLS was made through random integration of a FLAG-Halo-3xNLS (3x SV40 NLS: PKKKRKV) transgene expressed using the EF1a promoter. NeoR for drug selection was separately expressed using an SV40 promoter. After transfection, cells were selected using G418 until a pure cell population was obtained. This cell line has also been described previously<sup>1</sup>. The wild-type U2OS cell line used to make this cell line was also authenticated using STR profiling against the same loci as C32 and also showed a 100% match with U2OS.</p> <p>mESC C3 Halo-Sox2 was made through homozygous N-terminal tagging of Sox2 in JM8.N4<sup>2</sup> mouse embryonic stem cells using CRISPR/Cas9-mediated genome editing as previously described (C3 refers to clone number 3)<sup>3</sup>. The functionality of the C3 Halo-Sox2 knock-in was validated through control experiments and pluripotency through teratoma assays as described previously<sup>3</sup>.</p> <p>Each file contains single-molecule trajectories from a single cell imaged over 30,000 frames. Localization and tracking was performed using a custom-written Matlab implementation of the MTT-algorithm<sup>4</sup> and the following settings: Localization error: 10<sup>-6.25</sup>; deflation loops: 0; Blinking (frames): 1; max competitors: 3; max <em>D</em> (m<sup>2</sup>/s): 20.</p> <p>The same 15 conditions were used for each of the 4 cell lines.</p> <p><strong>ExpA PA-JF549</strong></p> <p>The purpose of this experiment was to test the effect of “motion-blurring” on the Spot-On estimated <em>D</em><sub>FREE</sub> and <em>F</em><sub>BOUND</sub>. 5 different experimental conditions were considered. Full details are given in the Methods section. Briefly, cells were grown overnight on plasma-cleaned 25 mm circular coverslips either directly (U2OS) and MatriGel coated as described<sup>1</sup>. Cell were labeled with 5-50 nM PA-JF549<sup>5</sup> for around 15-30 min, washed twice and medium exchanged to phenol-red free medium. 30,000 frames were collected at a camera exposure time (Andor iXon Ultra 897; frame-transfer mode; vertical shift speed: 0.9 μs; -70C) of 9.5 ms which together with a ~447 μs camera integration time gave a frame rate of ~100 Hz. PA-JF549 dyes were photo-activated during the ~447 μs camera integration time using 405 nm pulses and the 405 nm pulse intensity optimized to achieve a mean density of 1 molecule per frame per nucleus. The JF549 dye was excited using a 561 nm laser and the total number of excitation photons kept constant but either delivered during a 1 ms pulse, a 2 ms pulse, a 4 ms pulse, a 7 ms pulse or with constant illumination.</p> <p>For each cell line and condition, 4 replicates were performed. We count a replicate as an independent experiment performed on a different day. For each replicate around 5 cells were imaged. Occasionally, fewer than 5 cells are available. To avoid tracking errors, we removed cells with too high a localization density from the analysis. All of this information is available in the file name. For example, “U2OS_C32_Halo-CTCF_PA-JF549_1ms-561nm_100Hz_rep2_cell03” refers to the third cell imaged in the second replicate of U2OS C32 Halo-CTCF using a 1 ms excitation pulse of 561 nm laser at a frame rate of 100 Hz. Similarly, “U2OS_C32_Halo-CTCF_PA-JF549_cont-561nm_100Hz_rep4_cell01” refers to the first cell imaged in the fourth replicate of U2OS C32 Halo-CTCF using constant 561 nm laser at a frame rate of 100 Hz.</p> <p>The five ExpA_PAJF549 conditions are separated by cell line such that each cell line is provided in a separate directory. E.g. the directory “U2OS_H2B_ExpA_PAJF549” contains all data for the U2OS H2B-Halo-SNAP cell line.</p> <p><strong>ExpA PA-JF646</strong></p> <p>This experiment was exactly identical to the “ExpA_PA-JF549” experiment except cell were labeled with PA-JF646<sup>5</sup> and excited using a 633 nm laser. The file names and data organization was otherwise the same and the same five excitation conditions were considered.</p> <p><strong>ExpB PA-JF646</strong></p> <p>The purpose of this experiment was to test if the Spot-On estimated <em>D</em><sub>FREE</sub> and <em>F</em><sub>BOUND</sub> values would depend on the frame rate. In particular, all four proteins exhibit some levels of apparent anomalous diffusion, which could cause a dependence on the frame rate. Cells were labeled with PA-JF646 and grown and imaged as described above. Photo-activation took place during the ~447 μs camera integration time and JF646 dyes were excited using 1 ms stroboscopic 633 nm excitation pulses. To change the frame rate, the camera exposure time was set to 4.5 ms (~201 Hz), 5.5 ms (~167 Hz), 7 ms (~134 Hz), 13 ms (~74 Hz) and 19.5 ms (~50 Hz) when also counting the ~447 μs camera integration time. All of this information is available in the file name. For example, “U2OS_Halo-3xNLS_PA-JF646_1ms-633nm_74Hz_rep2_cell04” refers to the fourth cell imaged in the second replicate of U2OS Halo-3xNLS using a 1 ms excitation pulse of 633 nm laser at a frame rate of 74 Hz. Similarly, “mESC_C3_Halo-Sox2_PA-JF646_1ms-633nm_201Hz_rep1_cell03” refers to the third cell imaged in the first replicate of mESC Halo-Sox2 using a 1 ms excitation pulse of 633 nm laser at a frame rate of 201 Hz.</p> <p><strong>Data format</strong></p> <p>All data is available in two different formats: CSV-files and Matlab MAT-files. Both file formats are readable by the web-version of Spot-On. The Matlab version of Spot-On is only able to read the MAT-files. The CSV format consists of comma-separated values and contains headers. If opened with Microsoft Excel, it should appear as shown:</p> <p>Here the “frame” column contains the frame number in which the molecule was detected. The “t” column contains the timestamp. The “trajectory” column contains the trajectory number. For example, trajectory number 1 was only detected in frame 13 after which it disappeared. In contrast, trajectory number 4 was detected in frames 20, 21 22, 23 and 24. Finally, the “x” and “y” columns contain the x,y coordinates of the localization in units of micrometers (μm).</p> <p>The MAT-files contain a structure array named “trackedPar”. trackedPar contains three variables:</p> <ul> <li> <p>trackedPar.xy: “xy” is a matrix with 2 columns and a number of rows corresponding to the number of localizations in that trajectory. The first column is the x-coordinate and the second column is the y-coordinate. The units are micrometers (μm).</p> </li> <li> <p>trackedPar.Frame: “Frame” is a column vector where each element is the frame where the particle was localized.</p> </li> <li> <p>trackedPar.TimeStamp: “TimeStamp” is a column vector where each element is the timepoint where the particle was localized.</p> </li> </ul> <p>Each element in the structure array “trackedPar” correspond to a different trajectory.</p>
Experimental Data for Natural Disaster Mobility Model and Typhoon Haiyan Scenario
<p>The experimental data set for running the <em>Typhoon Haiyan</em> scenario with the <em>Natural Disaster Mobility Model</em> presented in the paper:</p> <p>Milan Stute, Max Maass, Tom Schons, and Matthias Hollick, “<strong>Reverse Engineering Human Mobility in Large-scale Natural Disasters</strong>,” to appear in <em>ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)</em>, November 2017, Miami Beach, USA.</p>
Data supporting "Lessons learned from multi-objective automatic optimizations of classical three-site rigid water models using microscopic and macroscopic target experimental observables"
<p>This repository contains the set of data and the code to reproduce the results shown in "Lessons learned from multi-objective automatic optimizations of classical three-site rigid water models using microscopic and macroscopic target experimental observables" published on Journal of Chemical Engineering and Data (DOI: 10.1021/acs.jced.3c00538).</p>
Research data supporting ""Lessons learned from multi-objective automatic optimizations of classical three-site rigid water models using microscopic and macroscopic target experimental observables""
<p>This repository contains the set of data and the code to reproduce the results shown in "Lessons learned from multi-objective automatic optimizations of classical three-site rigid water models using microscopic and macroscopic target experimental observables" published on Journal of Chemical Engineering and Data (DOI: 10.1021/acs.jced.3c00538).</p>
Modelling data for: Short-course combination treatment for experimental chronic Chagas disease
<p><span>Chagas disease, caused by the protozoan parasite <em>Trypanosoma</em> <em>cruzi</em>, affects millions of people in the Americas and across the world leading to considerable morbidity and mortality. Current treatment options, benznidazole (BNZ) and nifurtimox, offer limited efficacy and often lead to adverse side effects due to long treatment durations. Better treatment options are therefore urgently required. Here we describe a pyrrolopyrimidine series, identified through phenotypic screening, that offers a clear opportunity to improve on current treatments. In vitro cell-based washout assays demonstrate that compounds in the series are incapable of killing all parasites, however, combining these pyrrolopyrimidines with a sub-efficacious dose of BNZ can clear all parasites in vitro after five days. Importantly, these findings were replicated in a clinically predictive<em> in vivo</em> model of chronic Chagas disease, where five days of treatment with the combination was sufficient to prevent parasite relapse. Comprehensive mechanism of action studies, supported by ligand-structure modelling, show that compounds from this pyrrolopyrimidine series inhibit the Q</span><sub><span>i</span></sub><span> active site of <em>T. cruzi</em> cytochrome <em>b</em>, part of the cytochrome <em>bc1</em> complex of the electron transport chain. Knowledge of the molecular target enabled a cascade of assays to be assembled to evaluate selectivity over the human cytochrome <em>b</em> homologue. As a result, a highly selective and efficacious lead compound was identified. The combination of our lead compound with BNZ rapidly clears<em> T. cruzi</em> parasites, both <em>in vitro</em> and <em>in vivo</em>, and shows great potential to overcome key issues associated with currently available treatments. </span></p>
Dataset: Testing for effects of growth rate on isotope trophic discrimination factors and evaluating the performance of Bayesian stable isotope mixing models experimentally: a moment of truth?
<p><span>Discerning assimilated diets of wild animals using stable isotopes is well established where potential dietary items in food webs are isotopically distinct. With the advent of mixing models, and Bayesian extensions of such models (Bayesian Stable Isotope Mixing Models, BSIMMs), statistical techniques available for these efforts have been rapidly increasing. The accuracy with which BSIMMs quantify diet, however, depends on several factors including uncertainty in tissue discrimination factors (TDFs; <em>Δ</em>) and identification of appropriate error structures. Whereas performance of BSIMMs has mostly been evaluated with simulations, here we test the efficacy of BSIMMs by raising domestic broiler chicks (<em>Gallus gallus domesticus</em>) on four isotopically distinct diets under controlled environmental conditions, ideal for evaluating factors that affect TDFs and testing how BSIMMs allocate individual birds to diets that vary in isotopic similarity. For both liver and feather tissues,<em> δ</em><sup>13</sup>C and <em>δ </em><sup>15</sup>N values differed among dietary groups. <em>Δ</em><sup>13</sup>C of liver, but not feather, was negatively related to the rate at which individuals gained body mass. For <em>Δ</em><sup>15</sup>N, we identified effects of dietary group, sex, and tissue type, as well as an interaction between sex and tissue type</span><span><span>, </span></span><span><span>with f</span></span><span>emales having higher liver <em>Δ</em><sup>15</sup>N relative to males. For both tissues, BSIMMs allocated most chicks to correct dietary groups, especially for models using combined TDFs rather than diet specific TDFs, and those applying a multiplicative error structure. These findings provide new information on how biological processes affect TDFs and confirm that adequately accounting for variability in consumer isotopes is necessary to optimize performance of BSIMMs. Moreover, they demonstrate experimentally that these types of models reliably characterize consumed diets when appropriately parameterized.<span> </span></span></p>
Incoherent phenomena in anisotropic periodic structures: from modeling to experimental demonstration
<p>Experimental measurement of difracted light Fig. 9 (subplot a consists of Grating_520_90_740_medium, columns 14 and 16) and Fig. 10 (reflection and transmission spectra of diffraction order generated by attached Python code) in the article Incoherent phenomena in anisotropic periodic<br>structures: from modeling to experimental demonstration.</p>
Supplementary Material for "Model-Free Analysis of Experimental Residual Diploar Couplings in Small Organic Compounds"
<p>NMR Spectra (CLIP-HSQC, perfectCLIP-HSQC, TSE-PSYCHEDELIC) of isopinocampheol in six alignment conditions.</p> <p>Simulation input (experimental RDC data in six alignment media, input geometries, keywords) and output files (simulation / geometry trajectories, alignment data, SECONDA analysis) for isopinocampheol runs with the TITANIA software.</p>
A model of digestive tooth corrosion in lizards: experimental tests and taphonomic implications
<p>Abstract </p><p>Corrosion patterns induced by gastric fluids on the skeleton of prey animals may depend on the nature of the corrosive agents (acid, enzymes) as well as on the composition of the hard parts and the soft tissues that surround them. We propose a framework for predicting and interpreting corrosion patterns on lizard teeth, our model system, drawing on the different digestive pathways of avian and non-avian vertebrate predators. We propose that high-acid, low-enzyme systems (embodied by mammalian carnivores) will lead to corrosion of the tooth crowns, whereas low-acid, high-enzyme systems (embodied by owls) will lead to corrosion of the tooth shafts. We test our model experimentally using artificial gastric fluids (with HCl and pepsin) and feeding experiments, and phenomenologically using wild-collected owl pellets with lizard remains. Finding an association between the predictions and the experimental results, we then examine corrosion patterns on nearly 900 fossil lizard jaws. Given an appropriate phylogenetic background, our focus on physiological rather than taxonomic classes of predators allows the extension of the approach into Deep Time.</p><p></p>
The Effect of Stromal Vascular Fraction (SVF) & Scaffolds Application on Fracture Healing with Bone Defect as Assessed Through Osteocalcin and Bone Morphogenetic Protein-2 (BMP-2) Biomarker Examination: Experimental Study on Murine Model
<p>This data is the raw data for the manuscript with titled The Effect of Stromal Vascular Fraction (SVF) & Scaffolds Application on Fracture Healing with Bone Defect as Assessed Through Osteocalcin and Bone Morphogenetic Protein-2 (BMP-2) Biomarker Examination: Experimental Study on Murine Model.</p>
Experimental realization of the 1D random field Ising model
<p>We have measured magnetic-field-induced avalanches in a square artificial spin ice array of interacting nanomagnets. Starting from the ground state ordered configuration, we imaged the individual nanomagnet moments after each successive application of an incrementally increasing field. The statistics of the evolution of the moment configuration show good agreement with the canonical one-dimensional random field Ising model. We extract information about the microscopic structure of the arrays from our macroscopic measurements of their collective behavior, demonstrating a process that could be applied to other systems exhibiting avalanches.</p>
Experimental and modeling study of metal-insulator interfaces to control the electronic transport in single nanowire memristive device - Dataset
<p>This is the dataset of "Experimental and modeling study of metal-insulator interfaces to control the electronic transport in single nanowire memristive device"</p>
ScienceDex guides
Understand access before you commit
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.