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32,629 results for “Dataset”
Dataset / Code: Targeted protein degradation in mycobacteria uncovers antibacterial effects and potentiates antibiotic efficacy
<p><strong>Targeted protein degradation in mycobacteria uncovers antibacterial effects and potentiates antibiotic efficacy</strong></p> <p><strong> </strong></p> <p>Harim I. Won<sup>1,#</sup>, Samuel Zinga<sup>1,#</sup>, Olga Kandror<sup>1</sup>, Tatos Akopian<sup>1</sup>, Ian D. Wolf<sup>1</sup>, Jessica T.P. Schweber<sup>1</sup>, Ernst W. Schmid<sup>2</sup>, Michael C. Chao<sup>1</sup>, Maya Waldor<sup>1</sup>, Eric J. Rubin<sup>1,*</sup>, Junhao Zhu<sup>1,3,*</sup></p> <p><strong> </strong></p> <p><sup>1</sup>Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA.</p> <p><sup>2</sup>Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Blavatnik Institute, Boston, Massachusetts 02115, USA.</p> <p><sup>3</sup>CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.</p> <p><sup>#</sup>These authors contributed equally to this work.</p> <p>*Corresponding authors: <a href="mailto:zhujh@im.ac.cn">zhujh@im.ac.cn</a> (J.Z.), <a href="mailto:erubin@hsph.harvard.edu">erubin@hsph.harvard.edu</a> (E. J. R.)</p> <p><strong> </strong></p> <p><strong>Abstract</strong></p> <p>Proteolysis-targeting chimeras (PROTACs) represent a new therapeutic modality involving selectively directing disease-causing proteins for degradation through proteolytic systems. Our ability to exploit targeted protein degradation (TPD) for antibiotic development remains nascent due to our limited understanding of which bacterial proteins are amenable to a TPD strategy. Here, we use a genetic system to model chemically-induced proximity and degradation to screen essential proteins in <em>Mycobacterium smegmatis </em>(<em>Msm</em>)<em>, </em>a model for the human pathogen <em>M. tuberculosis </em>(<em>Mtb</em>). By integrating experimental screening of 72 protein candidates and machine learning, we find that drug-induced proximity to the bacterial ClpC1P1P2 proteolytic complex leads to the degradation of many endogenous proteins, especially those with disordered termini. Additionally, TPD of essential <em>Msm </em>proteins inhibits bacterial growth and potentiates the effects of existing antimicrobial compounds. Together, our results provide biological principles to select and evaluate attractive targets for future <em>Mtb</em> PROTAC development, as both standalone antibiotics and potentiators of existing antibiotic efficacy.</p> <p> </p>
Dataset of "From Gas to Solution: The Changing Neutral Structure of Proline Upon Solvation"
Liquid-jet photoelectron spectroscopy (LJ-PES) and electronic-structure theory were employed to investigate the chemical and structural properties of the amino acid L-proline in aqueous solution for its three ionized states (protonated, zwitterionic, deprotonated). This is the first PES study of this amino acid in its most biologically relevant environment. Proline's structure in the aqueous phase under neutral conditions is zwitterionic, distinctly different from the non-ionic neutral form in the gas phase. By analyzing the carbon 1s and nitrogen 1s core-levels as well as the valence spectra of aqueous-phase proline, we found that the electronic structure is dominated by the protonation state of each constituent molecular site (the carboxyl and amine) with small yet noticeable interference across the molecule. The site-specific nature of the core-level spectra enables probing of individual molecular constituents. The valence photoelectron spectra are more difficult to interpret because of overlapping signals of proline with the solvent and pH-adjusting agents (HCl and NaOH). Yet we are able to reveal subtle effects of specific (hydrogen-bonding) interaction with the solvent on the electronic structure. We also demonstrate that the relevant conformational space is much smaller for aqueous-phase proline than it is for its gas phase analogue. This study suggests that caution must be taken when comparing photoelectron spectra for gaseous and aqueous-phase molecules, particularly if those molecules are readily protonated / deprotonated in solution.
Dataset of "A Monte Carlo Approach for Simulating Electrical Conductivity in Highly Porous Ceramic Composites: Impact of Internal Structure"
<p>3D structure of lanthanum strontium manganite and yttria-stabilized zirconia composites is predicted based on conductivity measurements using Monte Carlo 3D equivalent circuit network approach. Validation experimental impedance spectra; scanning electron micrographs; cross sections of model simulation or prediction (MSP).</p>
Dataset for training the Surrogate Model of microlaser neurons on the reduced MNIST classification task
<p>This dataset was used to train a surrogate multilayer perceptron surrogate model of microlaser neurons.</p> <p>It is in csv format. It was generated using the Yamada Model as found in </p> <p><span>Selmi F, Braive R, Beaudoin G, Sagnes I, Kuszelewicz R and Barbay S 2014 Relative Refractory Period in an Excitable Semiconductor Laser <em>Phys. Rev. Lett.</em> <strong>112</strong> 183902</span>.</p>
Mineral spectral refractive index and bulk optical property dataset for aerosol studies
<p>Version 1.3, updated 11/15/2024.</p> <p>Added a file with 27 regional dust sample mineral composition information 'NewRegionalSamples.xlsx',</p> <p>along with the refractive index data.</p> <p>All refractive index files here have 127 rows (wavelengths) and 27 columns (samples)</p> <p>'kall27_coarse.dat' is the imaginary part of the coarse mode. </p> <p>'kall27_fine.dat' is the imaginary part of the fine mode.</p> <p>'nall27_coarse.dat' is the real part of the coarse mode.</p> <p>'nall27_fine.dat' is the real part of the fine mode.</p> <p>Version 1.2, updated 04/23/2024.<br>Major changes: <br>Changed all the data file names to new format: "mix"+{property name}+{number}, rearranged the number of mixing samples</p> <p>Updated all the bulk optical property data. This version use constant values of standard deviation in the lognormal size distribution settings for the coarse mode and the fine mode respectively.</p> <p>The phase matrices are separated from the other bulk properties due to their large file sizes. The readme file is updated correspondingly. The information of scattering angles (498 angles in total) is uploaded as "TAMUdust2020_Angle.dat".</p> <p>Added supplemental file data in 'Supplemental.tar.gz'.</p> <p>Additional refractive indices are zipped in 'AdditionalRefInd.tar.gz'</p> <p>Version 1.1, updated 03/14/2024.<br>Major changes: <br>Added mixed bulk properties for "0 (99%coarse+1%fine)" and "11 (2.0 µm coarse+ 0.4 µm fine)";<br>Added "reff.dat" in the 'BulkProperties.tar.gz'. The data include four columns: fine mode fraction, bulk projected area <A>, bulk volume <V>, effective radius r_eff. The information is for mixed sample number 0 to 11, each corresponds to one row.<br>Added refractive indices for chlorite, mica, smectite, pyroxene, vermiculite and pyroxenes. These groups can be applied in some other models.</p> <p>Version 1.0, uploaded 01/02/2024.</p> <p>This database include supplemental data and files for the publication of this paper:</p> <p>Sensitivities of Spectral Optical Properties of Dust Aerosols to their Mineralogical and Microphysical Properties. Yuheng Zhang, M. Saito, P. Yang, G. L. Schuster, and C. R. Trepte, J. Geophys. Res. Atmos. 2024.</p> <p> </p> <p>*****************************************</p> <p>The supplemental data include:</p> <p>1) 'GroupRefInd.tar.gz' Mineral (group) refractive index files.<br>E. g., 1All_Illite.dat contains the complex refractive index files of illite group. Format (from left to right columns): Wavelength (unit: µm), Real part (n), Imaginary part (k), standard deviation of n, standard deviation of k.</p> <p>The file 'fine_log.dat' includes the mean and standard deviation values of n and k for all the generated fine mode dust samples at 11,044 wavelengths from 0.2 to 50 micron.</p> <p>The file 'fine_log127.dat' only includes the values at 127 wavelengths from 0.2 to 50 micron (defined in 'swav.txt' and 'lwav.txt'), and is used for the bulk property computations.</p> <p>The files 'coarse_log.dat' and 'coarse_log127.dat' are for the coarse mode dust samples.</p> <p>2) 'CompositionFraction.xlsx': Mineral composition data sources/references and composition data (mean and standard deviation values of each group).<br>'Vlog_coarse.dat': Randomly generated VOLUME FRACTION of 9 mineral groups for the coarse mode dust. Left to right: Illite, Kaolinite, Montmorillonite (Other clays), Quartz, Feldspar, Carbonate, Gypsum (Sulphate), Hematite, Goethite.</p> <p>'Vlog_fine.dat': For the fine mode dust.</p> <p>3) 'RefSources.xlsx': The data source references of mineral refractive indices. We didn't include the olivine, other silicates, soot and titanium-rich minerals in the paper, but the refractive indices are available for those who are interested. Chlorite, Mica and Vermiculite group are mentioned in some studies, and we included the refractive indices for these minerals as well.</p> <p>4) 'DustSamples.tar.gz' Dust sample refractive index files.<br>The files are enclosed in four folders: fine_sw/ fine_lw/ coarse_sw/ coarse_lw/.</p> <p>fine: fine mode. coarse: coarse mode.</p> <p>'sw' means shortwave (< 4 µm, in total 76 wavelengths defined in 'swav.txt') while 'lw' means longwave (>= 4 µm, in total 51 wavelengths defined in 'lwav.txt').</p> <p>All files start with 'rdn', which means that they are computed based on randomly generated composition (data given in sheet 2 of 'CompositionFraction.xlsx').</p> <p>The four digit number after 'rdn' is the index of each dust sample. In total, there are 5,000 samples. The sample composition is the same for the same sample index in the same size mode (fine/coarse). Data file format (from left to right columns): real part, imaginary part.</p> <p>5) 'BulkProperties.tar.gz' Bulk property files (excluding phase matrices)<br>'mixqx.dat' files format (from left to right columns): Extinction efficiency (Qext), Scattering efficiency (Qsca), Backscattering efficiency (Qbck), and Asymmetry coefficient (Qasy). To obtain asymmetry factor, use Qasy/Qsca.</p> <p>'mixbkx.dat' files format (from left to right columns): P11(pi) P12(pi) P22(pi) P33(pi) P34(pi) P44(pi).</p> <p>'x' refers to the number at the end of the file name. It can be 100 ~ 112, each represents a setting of coarse and fine mode effective radius and volume fraction (see details in "reff.dat")</p> <p>'reff.dat' contains the effective radius information of the mixture. It has 7 columns: File number "x", Fine mode volume fraction, Fine mode effective radius (µm), Coarse mode effective radius (µm), Bulk projected area (µm^2), Bulk volume (µm^3), Bulk effective radius (µm).</p> <p>6) 'PhaseMatrices.tar.gz' Phase matrices data<br>'mixphswx.dat' files contain phase matrix results at 532 nm (shortwave). From left to right: P11, P12, P22, P33, P34, P44.</p> <p>'mixphlwx.dat' files contain phase matrix results at 10.5 µm (longwave).</p> <p>There are 635,000 rows in each data file. 635,000 rows = 127 wavelengths * 5,000 samples. Row 1~127 is sample 1, row 128~254 is sample 2, etc.. Suggest to use matlab function 'reshape(property, 127, 5000)' for each column when processing the data.</p> <p>7) 'Supplemental.tar.gz'</p> <p>We also include data files mentioned in the supplemental file of the paper. The adjusted source data files of the nine mineral groups are included.</p> <p>The supplemental bulk property files are named based on the figure number.</p> <p>8) 'AdditionalRefInd.tar.gz'</p> <p>We also include additional refractive indices for chlorite, smectite, vermiculite, mica, dolomite, titanium-rich minerals, pyroxenes and soot. These data can be useful in other models.</p> <p>For more detailed information and datasets, please contact: Yuheng Zhang, yuheng98@tamu.edu or yuhengz98@qq.com.</p>
A Dataset of sEMG and Self-Perceived Fatigue Levels for Muscle Fatigue Analysis
<p>Muscle fatigue is a risk factor for injuries in athletes and workers. This brings relevance to the study of this biochemical process to allow its identification and prevention.</p> <p>This dataset contains raw surface electromyographic (sEMG) data collected using the Delsys Trigno system, focusing on eight muscles, four per arm, from 13 healthy adult participants. Participants performed a series of 12 upper-body dynamic movements, consisting of 4 uni-articular and 2 complex/compound movements per arm. In addition to raw sEMG data, the dataset includes participants' self-reported fatigue levels. </p> <p><strong>Data Structure:</strong></p> <ul> <li><strong>sEMG Data.zip:</strong> Recorded in 1259 Hz, formatted as .csv.</li> <li><strong>self_perceived_fatigue_index.zip:</strong> Time-stamped fatigue ratings in 0-2 level, recorded at 50hz.</li> <li><strong>Protocol:</strong> Includes trial description, movements illustration and sampling frequencies.</li> <li><strong>Code</strong>: Jupyter Notebook file containing the base code to read and compute classic fatigue metrics such as Median Frequency and Mean Frequency.</li> <li><strong>Metadata:</strong> Includes participant anthropometrics, exercise habits and caffeine intake on the day of the trials.</li> </ul> <p>This dataset may contribute to the testing of new fatigue detection algorithms and analysis of the underlying mechanisms.</p>
Dataset for ELGO-DIMITRA Data Management Practices & Requirements: A Scoping Report
<p>This is a comprehensive data repository of the <em>data management survey</em> carried out in Autumn of 2023 through a collaboration between the <a href="https://opensciencestudies.eu/">PHIL_OS</a> project and the <a href="https://agres.elgo.gr/">Research Directorate of the Hellenic Agricultural Organization ELGO-DIMITRA</a>.</p> <p>Please cite as: </p> <blockquote> <p>Tsiroukis F., Leonelli S. and ELGO-DIMITRA (2024) <em>Dataset for ELGO-DIMITRA Data Management Practices & Requirements: A Scoping Report.</em> PHIL_OS Report. DOI: 10.5281/zenodo.14003418</p> </blockquote>
Dataset for "An Alternative Chlorine-Assisted Optimization of CdS/Sb2Se3 Solar Cells: Towards Understanding of Chlorine Incorporation Mechanism"
<p>The current strategies in the development of Sb2Se3 thin film solar cells involve fabrication and optimization of<br>superstrate and substrate device architectures, with the preferable choice for TiO2 and CdS heterojunction layers.<br>For CdS-based superstrate cells, several studies reported the necessity to apply CdCl2 or other metal halide-based<br>post-deposition treatment (PDT), highlighting improvement of CdS/Sb2Se3 device efficiency. However, the need,<br>effect, and mechanism of such PDT are very often not described. Additionally, the fact that many groups have not<br>succeeded in demonstrating its benefits suggests that this strategy is not straightforward, requiring a deeper<br>understanding towards a more unified concept. The present study proposes an alternative approach to the<br>challenging CdCl2 PDT of CdS in CdS/Sb2Se3 device, involving controllable Cl incorporation in CdS films by<br>systematically varying the concentration of NH4Cl in the CBD precursor solution from 1 to 8 mM. Structural and<br>electrical characterizations are correlated with advanced measurements of Scanning Kelvin Probe, surface<br>photovoltage, and atomic force microscopy to understand the impact of Cl incorporation on the properties of CdS<br>films and CdS/Sb2Se3 devices. The validity of Cl incorporation in the CdS lattice and interdiffusion processes at<br>the CdS-Sb2Se3 interface is confirmed by secondary ion mass spectrometry analysis. It is demonstrated that<br>incorporation of 1 mM of NH4Cl, as a Cl source in CBD CdS, can boost the PCE of CdS/Sb2Se3 by ~20 %. With this<br>approach, we offer new perspectives on the optimization methodology for Cl-based CdS/Sb2Se3 device processing<br>and complementary understanding of the physiochemistry behind these processes.</p>
Dataset: The Role of News Consumption on Influencers' Facebook Pages in Threat Perception and Political Conservatism During Times of COVID-19: A Comparative Study between the USA, Spain, and Egypt
<p>Este archivo ofrece los datos en bruto de una encuesta examina el impacto del consumo de noticias en las páginas de Facebook de los influencers en la motivación del conservadurismo político durante amenazas como el terrorismo o las pandemias. Muestra: N=1309, jóvenes de entre 18 y 35 años en Estados Unidos, España y Egipto. Trabajo de campo realizado entre el 10 de agosto de 2021 y el 5 de septiembre de 2021.</p> <p><span>Dataset correspondiente al proyecto El rol de la ciudadanía en la comunicación política digital CI-COMPOL (PID2020-119492GB-I00) financiado por MCIN/AEI/10.13039/501100011033/. IP: Andreu Casero-Ripollés, Departamento de Ciencias de la Comunicación, Universitat Jaume I de Castellón</span></p>
Dataset: Percepciones de la ciudadanía sobre el uso político de los servicios móviles de mensajería instantánea y sus efectos sobre la democracia
<p>Los datos en bruto procedentes de esta encuesta se refieren al contexto de España. Su objetivo es conocer las opiniones y actitudes de la ciudadanía en relación con dos aspectos: a) percepción de los servicios móviles de mensajería instantánea como herramientas de participación política; y b) percepción de los efectos que estas plataformas tienen sobre la democracia. La muestra total es de 1106 ciudadanos residentes en España. El trabajo de campo se realizó en mayo de 2023 mediante un panel online administrado por Qualtrics.</p> <p><span>Dataset correspondiente al proyecto El rol de la ciudadanía en la comunicación política digital CI-COMPOL (PID2020-119492GB-I00) financiado por MCIN/AEI/10.13039/501100011033/. IP: Andreu Casero-Ripollés, Departamento de Ciencias de la Comunicación</span></p>
Dataset for: Associating Mechano-electrochemical Phenomena to Stochastic Current Events in Micro-Electrochemical Cells Containing TiNb2O7 Particles
<p>This is the raw data used in a manuscript that will be submitted to ChemElectroChem. If you have any questions, please email the creators.</p>
Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2019 Dataset
<p>High-throughput computational screening of metal-organic frameworks rely on the availability of<strong><em> </em></strong>atomic coordinate files which can be used as input to simulation software packages. CoRE MOF Datasets are derived from Cambridge Structural Database (CSD) and also from the World Wide Web.</p> <p><strong>Nomenclatures:</strong></p> <p>LCD (Largest Cavity Diameter), PLD (pore limiting diameter), LFPD (Largest Sphere along the Free Path), ASA (Accessible Surface Area), NASA (Non-accessible surface area), AV_VF (Void Fraction, 0 - 1), NAV (Non Accessible Volume)</p> <p><strong>Dataset Directory Organization</strong></p> <p>CoREMOF2019_public_v2.zip: dataset with CR and NCR classifications</p> <p>1. CR dataset: computaion-ready (<em>N</em> = 10,367)</p> <ul> <li> ASR: all solvent removed (<em>N</em> = 6,603)</li> <li> FSR: free solvent removed (<em>N</em> = 3,764)</li> </ul> <p>2. NCR: not computaion-ready (<em>N</em> = 8,714)</p> <ul> <li> ASR: all solvent removed (<em>N</em> = 5,417) <ul> <li>Both: NCR determined by Chen_Manz and mofchecker (<em>N</em> = 2,597)</li> <li>Chen_Manz: NCR determined by Chen_Manz (<em>N</em> = 958)</li> <li>mofchecker: NCR determined by mofchecker (<em>N</em> = 1,859)</li> <li>PACMAN_fail: NCR determined by Chen_Manz and mofchecker, and fail to predict PACMAN charges (<em>N</em> = 3)</li> </ul> </li> <li> FSR: free solvent removed (<em>N</em> = 3,297) <ul> <li>Both: NCR determined by Chen_Manz and mofchecker (<em>N</em> = 1,646)</li> <li>Chen_Manz: NCR determined by Chen_Manz (<em>N</em> = 463)</li> <li>mofchecker: NCR determined by mofchecker (<em>N</em> = 1,185)</li> <li>PACMAN_fail: NCR determined by Chen_Manz and mofchecker, and fail to predict PACMAN charges (<em>N</em> = 3)</li> </ul> </li> </ul> <p>2. NCR_detail.xlsx: details of all structures by mofchecker and Chen_Manz for each NCR cases</p> <p><strong>November, 24 2024</strong></p> <ul> <li>Re-ordering of folders such that top level directory is based on computation-ready and not-computation ready classification.</li> </ul> <p><strong>November, 13 2024</strong></p> <ul> <li>Classification of Computation-Ready (CR) and Not Computation-Ready (NCR) Structures based on <a href="https://pubs.rsc.org/en/content/articlelanding/2020/ra/d0ra02498h">Chen & Manz</a> (RSC Adv., 2020,10, <a>26944-26951</a>) and <a href="https://github.com/kjappelbaum/mofchecker">MOFChecker </a>program by <a href="https://github.com/kjappelbaum">Kevin M. Jablonka</a>)</li> <li>ML-predicted DDEC6 partial atomic charges based on <a href="https://github.com/mtap-research/PACMAN-charge">PACMAN</a></li> </ul> <p><strong>Acknowledgements</strong></p> <ul> <li>This reserach is supported by the National Research Foundation of Korea (No. 2016R1D1A1B3934484, NRF-2020R1C1C1010373, RS-2024-00449431)</li> <li>This research is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-17ER16362 (Predictive Hierarchical Modeling of Chemical Separations and Transformations in Functional Nanoporous Materials: Synergy of Electronic Structure Theory, Molecular Simulations, Machine Learning, and Experiment)</li> </ul>
Product Images for Life Cycle Assessment Dataset For Peritoneal Dialysis and Haemodialysis in Modena
<p>The database contains a collection of images showcasing the individual components of peritoneal dialysis (PD) products, along with their corresponding weights. These images serve as a visual record for life cycle assessment (LCA) purposes, focusing on the material composition and environmental impact of each product.</p> <ol> <li> <p><strong>Patient Education Materials</strong>: Photographs of educational materials provided to patients, with accompanying data on the weight of the paper and packaging.</p> </li> <li> <p><strong>Catheters and Surgical Kits</strong>: Images display the disassembled components of PD catheters and surgical kits, including tubing, connectors, and packaging. Each image is annotated with the precise weight of the individual components.</p> </li> <li> <p><strong>Dialysis Solution Bags</strong>: The database includes images of both CAPD and APD solution bags, separated into their constituent parts (e.g., plastic bag, solution, and protective wrapping), with weights noted for each component.</p> </li> <li> <p><strong>Connection Devices and Consumables</strong>: Detailed images of connection devices, clamps, and other consumable items, with individual component weights clearly labeled.</p> </li> <li> <p><strong>Packaging and Transport Materials</strong>: Photographs of transport packaging, such as cardboard boxes and plastic wraps, alongside recorded weights for each element.</p> </li> <li> <p><strong>Maintenance Items</strong>: Visuals of terminal catheter sets, cleaning agents, and related products, each accompanied by their respective weight data.</p> </li> <li> <p><strong>Disposal Components</strong>: Images of used solution bags, syringes, and other single-use items, separated into recyclable and non-recyclable components, with weights specified for each.</p> </li> </ol> <p>This image-based database provides a clear and comprehensive reference for the material breakdown and weight distribution of PD product components, essential for conducting a thorough LCA and identifying areas for environmental improvement.</p>
Dataset of "Marcus cross relation in the space of H-atom abstraction reactions boosted through off-diagonal thermodynamics"
<p>Proton-coupled electron transfer (PCET) and hydrogen-atom transfer (HAT) reactions play critical roles in biological processes and modern organic synthesis. The kinetics of these processes can align with the principles described in the renowned Marcus cross relation (MCR), a framework initially formulated to describe electron transfer mechanisms. The MCR provides an outstanding link between the kinetics of PCET/HAT reaction involving two distinct reactants and two related auxiliary self-exchange reactions – each between a molecule of one of the reactants and its coupled radical. In this study, we investigate the applicability and limitations of the canonical MCR across over 300 PCET and HAT reactions, providing a comprehensive theoretical analysis. Our findings reveal the need for an enhanced framework that incorporates ‘off-diagonal’ thermodynamic factors—asynchronicity and frustration. Of these factors, asynchronicity, which quantifies the imbalance between the proton vs. electron transfer components of the reaction, is identified as the dominant contributor to the improved predictive accuracy of the MCR. Notably, the incorporation of off-diagonal thermodynamics yields a more pronounced enhancement for HAT reactions than for PCET reactions. This advancement offers a refined theoretical basis for understanding H-atom abstraction mechanisms and underscores the importance of off-diagonal effects in PCET/HAT chemistry.</p>
Dataset of "Neutron imaging and molecular simulation of systems from methane and p‑xylene"
<p>The dataset contains parameterizations, and input files for molecular dynamics simulations used in the study of methane dissolution in p-xylene. For selected conditions, full simulation data, i.e., trajectories and energetics are provided. All used simulation results data are provided in the table, along with the measured experimental data.</p>
Triaxial accelerometer gait dataset: foot and lower back motion during normal and metronome walking
<p><strong>This dataset contains accelerometric data collected from young and older individuals walking in a controlled environment. The data were recorded using two triaxial accelerometers, one attached to the participant's lower back and the other attached to the foot. Participants were instructed to walk back and forth along a 205-meter corridor under two different conditions:</strong></p> <p><strong>Normal walking: </strong>Participants walked at their preferred walking speed, reflecting their natural gait and pace.</p> <p><strong>Metronome walking: </strong>Participants synchronized their walking pace to a metronome set to their preferred walking cadence. This condition introduced a rhythmic element to the walking pattern, allowing for the study of gait changes when adhering to an external tempo.</p> <p><strong>Another condition was also measured to introduce a more variable and dynamic walking pattern that reflects everyday pedestrian movement in a real-world context.</strong></p> <p><strong>Free outdoor walking:</strong> Older participants engaged in approximately 5 minutes of free walking in an urban environment, navigating city streets. During this activity, only the lumbar accelerometer was used to record data. </p>
Dataset of "Preparation of novel lithiated high-entropy spinel type oxyhalides and their electrochemical performance in Li-ion batteries "
<p>Electrochemical measurements carried out using the 2032-coin cells with the Li-metal anode have shown voltammetric charge capacities of 450, 694, and 593 mAh g-1 for HEOFe, LiHEOFeCl, and LiHEOFeF, respectively.<br>Galvanostatic chronopotentiometry at 1 C rate confirmed high initial charge capacities for all the samples but galvanostatic curves exhibited a capacity decay over 100 charging/discharging cycles. Raman spectroelectrochemistry measured on the LiHEOFeF sample proved the reversibility of the electrochemical process for initial charging/discharging cycles. Electrochemical impedance spectroscopy revealed the lowest initial charge transfer resistance for LiHEOFeCl and its gradual decrease both for LiHEOFeCl and LiHEOFeF during galvanostatic cycling, whereas the charge transfer resistance of HEOFe slightly increases over 100 galvanostatic cycles due to different mechanism of the electrochemical reduction. </p>
Dataset on Weather-related disasters in agriculture in Italy - WDA
<h1><strong>Abstract</strong></h1> <p>The dataset is the supplementary material for the following journal paper:</p> <p>Pontrandolfi A, Alilla R, De Natale F, Nuti R, Parisse B, Pepe AG, Dataset on Weather-related Disasters in Agriculture (WDA) in Italy 2005–2021, Data in Brief <br><a href="https://doi.org/10.1016/j.dib.2025.111323">https://doi.org/10.1016/j.dib.2025.111323</a></p> <p>The database on Weather-related disasters in agriculture (WDA) is a part of the cloud storage which hosts the materials of the <a href="https://agrometeo.crea.gov.it/">Observatory for agricultural meteorology and climatology</a> of the Research Center for Agriculture and Environment belonging to the Council for Agricultural Research and Economics (CREA). The Observatory website has a specific section devoted to <a href="https://agrometeo.crea.gov.it/dati-e-analisi__trashed/rischio-meteorologico-in-agricoltura/">weather-related risk in agriculture</a>.</p> <p>A specific relational SQL database has been created fo data entry information from the official decrees of WDA declaration in Italy.</p> <p>From this relational SQL database, a <strong>dataset </strong>of WDA has been extracted for the period from 2005 to 2021 and here published</p> <p>The WDA dataset aims to make available useful data for weather-related risk assessment and analysis in the Italian agricultural sector.</p> <h2>Attached content:</h2> <ul> <li>pdf file "A_Description_Dataset_Weather_related_disasters_agriculture_v1.2"</li> <li>csv file "Dataset_Weather_related_disasters_agriculture_v1.2"</li> <li>csv file "DiscoveryMD_Dataset_Weather_related_disasters_agriculture_v1.2"</li> <li>xlsx file "StructuralMD_Dataset_Weather_related_disasters_agriculture_v1.2"</li> </ul>
Dataset of "Balancing Activity and Stability through Compositional Engineering of Ternary PtNi–Au Alloy ORR Catalysts"
<p>A systematic comparative analysis of the activity-stability relationship for compositionally tuned PtNi-Au model layers, prepared by magnetron co-sputtering, was conducted using a diverse range of complementary characterization techniques and electrochemistry, supported by density functional theory calculations. Our study reveals that progressively increasing the Au concentration in the Pt50Ni50 alloy from 3 to 15 at.% leads to opposing catalyst activity and stability trends. Specifically, we observe a decrease in ORR activity accompanied by an increase in catalyst stability, manifested in the suppression of both Pt and Ni dissolution. Despite the reduced activity compared to PtNi, the PtNi–Au alloy with 15 at.% Au still exhibits nearly three times the activity of monometallic Pt. It also demonstrates a significantly improved dissolution stability relative to the PtNi alloy and even monometallic Pt. These findings provide valuable insights into the intricate balance between activity and stability in multimetallic ORR catalysts, paving the way for the design of cost-effective and durable materials for PEMFCs.</p>
Occurrence Record Dataset from "Annotated checklist of the bees of Bonaire, with a focus on host plants"
<p>This is the occurrence dataset created for the publication "Annotated checklist of the bees of Bonaire, with a focus on host plants" (<a href="https://natuurtijdschriften.nl/pub/1026875" target="_blank" rel="noopener">https://natuurtijdschriften.nl/pub/1026875</a>).</p> <p>Observation and specimen data were assembled for this dataset, with the majority of records obtained during the Bonaire Estafette Expeditie (BEE). All citizen science records from Observation.org and iNaturalist.org up to December 2023 have been critically reviewed.<br>A project was created (<a href="https://www.inaturalist.org/projects/flower-visitors-and-pollinators-of-the-caribbean" target="_blank" rel="noopener">Flower visitors and pollinators of the Caribbean</a>) to improve standardized data collecting of plant-pollinator interactions and on <a href="https://observation.org/">observation.org</a> the standardized fields for interactions were used.<br>Records from passive trapping methods are not included. All bees were either observed or collected by hand or insect net. The majority of specimens will be accessible in the collection of Naturalis Biodiversity Center (RMNH), Leiden (the Netherlands). A synoptic collection is retained at the University of Tartu Zoological Collections in Tartu, Estonia (TUZ).</p> <p>The occurrence dataset (Version 1.4 and later) is:</p> <ul> <li>conform Darwin Core (DwC): <a href="https://dwc.tdwg.org/terms/">https://dwc.tdwg.org/terms</a></li> <li>in the data format CSV (tab delimited values) and UTF-8 encoded</li> </ul> <p> </p> <p><strong>DwC terms (Column labels) used in the dataset with their description:</strong></p> <table> <tbody> <tr> <td><strong>Column label</strong></td> <td><strong>Column description</strong></td> </tr> <tr> <td>occurrenceID</td> <td>Unique identifier or URI (GUID) for each record, mainly unique URLs generated by the web-based data holder.</td> </tr> <tr> <td>catalogNumber</td> <td>Unique code derived from URI in occurrenceID. Each specimen bears a label with this identifier and multimedia are tagged with this identifier.</td> </tr> <tr> <td>recordNumber</td> <td>Sample field ID used to manage data of preserved specimen occurrence records.</td> </tr> <tr> <td>otherCatalogNumbers</td> <td>Other unique identifiers used on specimen labels, but not derived from an URI.</td> </tr> <tr> <td>scientificName</td> <td>The scientific name of the lowest taxonomic rank to which the individual(s) was identified.</td> </tr> <tr> <td>scientificNameAuthorship</td> <td>The author name and year of publication in accordance with ICZN rules.</td> </tr> <tr> <td>verbatimIdentification</td> <td>The original identification, including qualifiers if needed.</td> </tr> <tr> <td>individualCount</td> <td>The number of individuals present at the time of the occurrence.</td> </tr> <tr> <td>sex</td> <td>The sex of the individual(s). The values female, male or unknown are used, if a mixed group is observed multiple values are listed.</td> </tr> <tr> <td>lifeStage</td> <td>The life stage of the individual(s).</td> </tr> <tr> <td>basisOfRecord</td> <td>The specific nature of the data record at the time of the identification (e.g. PreservedSpecimen).</td> </tr> <tr> <td>identifiedBy</td> <td>The name of the person who made the identification in the field or based on collected evidence (e.g. specimen or photo).</td> </tr> <tr> <td>identificationQualifier</td> <td>In case the identification could be given only to a species group 'cf.' is recorded.</td> </tr> <tr> <td>dateIdentified</td> <td>The year when the identification was made.</td> </tr> <tr> <td>previousIdentifications</td> <td>The scientific name originally given to the observed or collected individual(s).</td> </tr> <tr> <td>order</td> <td>The name of the order (e.g. Hymenoptera).</td> </tr> <tr> <td>family</td> <td>The name of the family (e.g. Apidae).</td> </tr> <tr> <td>genus</td> <td>The name of the genus (e.g. Apis).</td> </tr> <tr> <td>subgenus</td> <td>The name of the subgenus (e.g. Apis).</td> </tr> <tr> <td>specificEpithet</td> <td>The name of the species, epithet as given in dwc:scientificName.</td> </tr> <tr> <td>taxonRank</td> <td>The taxonomic rank of the most specific name in dwc:scientificName.</td> </tr> <tr> <td>eventDate</td> <td>The date-time when the event was observed and recorded. The event date uses the ISO 8601-1:2019 standard, with the following formatting being used: format YYYY-MM-DD, or YYYY if only the year is known. If time of capture is known, then format is YYYY-MM-DDTHH:MM, with HH:MM the local time.</td> </tr> <tr> <td>year</td> <td>The year in which the event was observed and recorded.</td> </tr> <tr> <td>month</td> <td>The month in which the event was observed and recorded.</td> </tr> <tr> <td>day</td> <td>The day in which the event was observed and recorded.</td> </tr> <tr> <td>eventTime</td> <td>The time or interval during which the event occurred.</td> </tr> <tr> <td>samplingProtocol</td> <td>The name or description of the collecting or recording method used.</td> </tr> <tr> <td>behavior</td> <td>A description of the behavior shown by the individual(s) recorded in this occurrence.</td> </tr> <tr> <td>decimalLatitude</td> <td>The geographic latitude in decimal degrees recorded by a GPS device (WGS84) when observing and recording the occurrence.</td> </tr> <tr> <td>decimalLongitude</td> <td>The geographic longitude in decimal degrees recorded by a GPS device (WGS84) when observing and recording the occurrence.</td> </tr> <tr> <td>geodeticDatum</td> <td>The ellipsoid, geodetic datum, or spatial reference system (SRS) upon which the geographic coordinates given in dwc:decimalLatitude and dwc:decimalLongitude is based.</td> </tr> <tr> <td>verbatimLocality</td> <td>The original textual description of the place.</td> </tr> <tr> <td>island</td> <td>The name of the island.</td> </tr> <tr> <td>countryCode</td> <td>The standard ISO 3166-1 alpha-2 country code for the country.</td> </tr> <tr> <td>coordinateUncertaintyInMeters</td> <td> <p>The horizontal distance (in meters) from the given dwc:decimalLatitude and dwc:decimalLongitude describing the smallest circle containing the actual location, usually the EPE (Estimated Position Error) from the GPS device. The EPE is here measured as the horizontal position error in meters.</p> </td> </tr> <tr> <td>recordedBy</td> <td>A person, group, or organization observing and recording the occurrence.</td> </tr> <tr> <td>associatedTaxa</td> <td>The type of association and the scientific name of the host taxon is recorded that is associated/has relationship with the taxon in dwc:scientificName. The association/relationship is recorded using the format as in the following example: "floral host":"Lantana sp."</td> </tr> <tr> <td>occurrenceRemarks</td> <td>Comments or notes about the dwc:Occurrence.</td> </tr> <tr> <td>associatedSequences</td> <td>A list (concatenated and separated) of identifiers (publication, global unique identifier, URI) of genetic sequence information.</td> </tr> <tr> <td>typeStatus</td> <td>A list (concatenated and separated) of nomenclatural types (type status, typified scientific name, publication) applied to the subject.</td> </tr> <tr> <td>collectionCode</td> <td>The name, acronym, coden, or initialism identifying the collection or data set from which the record was derived.</td> </tr> <tr> <td>identificationRemarks</td> <td>Comments or notes about the identification.</td> </tr> <tr> <td>identificationReferences</td> <td>A reference or list of references (publication, global unique identifier, URI) used for the identification.</td> </tr> <tr> <td>nameAccordingTo</td> <td>A reference to the checklist or publication that was followed to record the name in dwc:scientificName.</td> </tr> <tr> <td>samplingEffort</td> <td>The amount of effort, expressed in minutes or hours, to obtain and record the occurrences.</td> </tr> <tr> <td>occurrenceStatus</td> <td>A statement about the presence or absence of a taxon during the time of an event.</td> </tr> <tr> <td>disposition</td> <td>The current state of a specimen with respect to a collection.</td> </tr> <tr> <td>language</td> <td>The language of the record using ISO 639-1 codes, e.g. en</td> </tr> </tbody> </table>
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.