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50 results for “Structural performance”
Dataset of reports about MOF-based SERS substrates since 2011 until March 2023. Structure, characteristics, analytes, and performances.
<p>This dataset was generated to aid the creation of a review article addressing the use of Metal-Organic Frameworks (MOF)-based Surface Enhanced Raman Spectroscopy (SERS) platforms for the detection of Volatile Organic Compounds (VOCs).</p> <p>This dataset was generated employing the Web of Science database, encompassing manuscripts published up to March 2023. A literature search was initially conducted using a combination of keywords, including "MOF," "Metal-Organic Framework," "SERS," "Surface Enhanced Raman Spectroscopy," and "Surface Enhanced Raman Scattering." This search spanned the "Topic" category, enabling exploration across title, abstract, author keywords, and keyword-plus fields.</p> <p>From the initial pool of 238 documents, review articles and duplicates were systematically excluded, resulting in a refined collection of 182 articles. Subsequently, articles not concurrently addressing MOF and SERS or those utilizing MOF as sacrificial templates were further excluded, resulting in a final subset of 72 articles. From this curated set, relevant parameters were extracted, resulting in 229 entries for the dataset. </p> <p>Characteristics about the structure (in terms of MOF type and configuration; Plasmonic element type and configuration), target analyte (including type, phase, and incubation time), measurement specifications (in terms of laser, laser power, exposure time), and performance of the MOF-based SERS substrates were collected.</p> <p>Listed references 1-72 correspond with the manuscript number in the dataset.</p> <p>Listed references 73-80 correspond with references for selected examples of MOF pore diameters.</p>
Catalyst Supraparticles: Tuning the Structure of Spray‐Dried Pt/SiO2 Supraparticles via Salt‐Based Colloidal Manipulation to Control their Catalytic Performance
<p>This data publication is based on the metadata and raw datasets underlying the manuscript: P. Groppe, J. Reichstein, S. Carl, C. Cuadrado Collados, B.-J. Niebuur, K. Zhang, B. Apeleo Zubiri, J. Libuda, T. Kraus, T. Retzer, M. Thommes, E. Spiecker, S. Wintzheimer, K. Mandel, Catalyst Supraparticles: Tuning the Structure of Spray-Dried Pt/SiO2 Supraparticles via Salt-Based Colloidal Manipulation to Control their Catalytic Performance. Small 2024, 2310813. https://doi.org/10.1002/smll.202310813</p> <p>A detailed description of the dataset is given in the attached "Raw data assignment.xlsx"</p>
Evaluating the influence of structural properties on proximity metric performance in single cell RNA-seq data - Datasets
<p>Includes raw and processed copies of the scRNA-seq datasets used for the paper: '<strong>How does data structure impact cell-cell similarity? Evaluating the influence of structural properties on proximity metric performance in single cell RNA-seq data.'</strong></p> <p><strong>Real scRNA-seq.zip </strong>contains the Abundant (subset1) and Rare (subset 2) subsets generated to represent discretely structured datasets (sourced from<strong> </strong> Wegmann et al. 2019) and the continuously structured data (sourced from Popescu et al. 2019).</p> <p><strong>Simulated scRNA-seq.zip</strong> contains the Abundant, Moderately-Rare and Ultra-Rare subsets for discretely and continuously structured datasets. All data was simulated using the PROSSTT package in Python 3.8, as well as the dataset containing the labels to re-produce Figure 3 of the manuscript.</p> <p><strong>Results.zip </strong>contains the results for all datasets from the full analysis, in a pickled python dictionary. Code to read in and visualise results is available on the projects github</p> <p>The scripts for the dataset generation, processing and visualisation of results are available at <a href="https://github.com/Ebony-Watson/scProximitE">our github for the scProcimitE package</a>, and documentation is available <a href="https://ebony-watson.github.io/scProximitE/">here</a>.</p>
R scripts for analyzing LiDAR data to assess forest canopy structure and perform Principal Component Analysis (PCA) on derived metrics
<p>This repository contains R scripts for analyzing LiDAR data to assess forest canopy structure and perform Principal Component Analysis (PCA) on spectral and LiDAR-derived metrics. The scripts cover LiDAR data processing, canopy height model (CHM) generation, calculation of forest canopy metrics, and PCA analysis.</p>
Data for the publication: High performance of porous, hierarchically structured P2- Na0.6Al0.11 – xNi0.22 – yFex+yMn0.66O2 cathode materials
<p>Data sets: SEM-images, EIS, ex situ XRD, operando XRD, electrochemical cycling.</p> <p>Abstract: Sodium-ion-batteries (SIB) are a low-cost alternative to currently used lithium-ion batteries (LIB) but suffer from poor cycling stability. Spray drying provides porous, hierarchically structured particles of cathode active material (CAM) in large amounts, suitable for up-scaling. Changing the chemical composition of the Na0.6Al0.11–xNi0.22–yFex+yMn0.66O2 layered oxides under identical synthesis conditions leads to differences in particle morphology, conductivities, sodium vacancy ordering and phase transition, therefore influencing the electrochemical performance via several mechanisms. Here, a broad overview on these changes for samples with variable nickel and iron content is presented. With increasing iron content, the particle porosity is reduced and lower of initial capacity is received for most cycling windows. Substituting half of the original Ni amount with Fe still leads to high capacities and improved cycling stability. The influence of Al as electrochemical inactive element becomes visible in stabilised cycling stability as well.</p>
Dataset: Structure Therapeutics Inc. (GPCR) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
BRAIN Journal-High Performance Data mining by Genetic Neural Network-Figure 4. Structural Crossover
<p>Guided crossover operator is based on the two point separation from parents are selected<br> Left and right parts of them are related to each other by the condition to be meaningful With this<br> new child of his parents is that. But a new generation of the random choice to have reached this<br> stage. The crossover rate is fixed for our algorithm.</p>
BRAIN Journal-High Performance Data mining by Genetic Neural Network-Figure 3. The Structure of Neural Network
<p>A neural network (NN), in the case of artificial neurons called artificial neural<br> network (ANN) or simulated neural network (SNN), is an interconnected group of natural<br> or artificial neurons that uses a mathematical or computational model for information<br> processing based on a connectionist approach to computation. In most cases an ANN is an adaptive<br> system that changes its structure based on external or internal information that flows through the<br> network[9].<br> In more practical terms neural networks are nonlinear statistical data modelling or decision<br> making tools. They can be used to model complex relationships between inputs and outputs or<br> to find patterns in data.<br> Two neurons neural network active in memory (ON or 1) or disable (Off or 0), and each<br> edge (synapses or connections between nodes) is a weight. Edges with positive weight, stimulate or<br> activate next active node, and edges with negative weight, disable or inhibit the next connected<br> node (if it is active) ones.</p>
Data for "Training data composition affects performance of protein structure analysis algorithms" by A. Derry, K. A. Carpenter, & R. B. Altman
<p><strong>Description</strong></p> <p>This repository contains all data used in "Training data composition affects performance of protein structure analysis algorithms", published in the Pacific Symposium on Biocomputing 2022 by A. Derry, K. A. Carpenter, & R. B. Altman. </p> <p>The data consists of the following files:</p> <ul> <li>ema_zenodo_data.tar.gz: train, validation, and test splits for Estimation of Model Accuracy task, in LMDB format</li> <li>design_zenodo_data.tar.gz: train, validation, and test splits for Protein Sequence Design task, in JSON format</li> <li>enz_cat_res_zenodo_data.tar.gz: train, validation, and test splits for Catalytic Residue and Enzyme Prediction task, in TF record format</li> </ul> <p>Details on dataset construction can be found in our paper and dataloaders can be found in our <a href="https://github.com/awfderry/ml-structure-bias">Github repo</a>.</p> <p><strong>Reference</strong></p> <p>A. Derry*, K. A. Carpenter*, & R. B. Altman, "Training data composition affects performance of protein structure analysis algorithms", 2021.</p> <p><strong>Dataset References</strong></p> <p>Datasets used were derived from the following works:</p> <p>Kryshtafovych, A., Schwede, T., Topf, M., Fidelis, K., & Moult, J. (2019). Critical assessment of methods of protein structure prediction (CASP)—Round XIII. In <em>Proteins: Structure, Function and Bioinformatics</em> (Vol. 87, Issue 12, pp. 1011–1020). https://doi.org/10.1002/prot.25823</p> <p>Ingraham, J., Garg, V. K., Barzilay, R., & Jaakkola, T. (2019). <em>Generative Models for Graph-Based Protein Design</em>. https://openreview.net/pdf?id=SJgxrLLKOE</p> <p>Furnham, N., Holliday, G. L., de Beer, T. A. P., Jacobsen, J. O. B., Pearson, W. R., & Thornton, J. M. (2014). The Catalytic Site Atlas 2.0: cataloging catalytic sites and residues identified in enzymes. <em>Nucleic Acids Research</em>, <em>42 </em>(Database issue), D485–D489.</p>
Impact of intercept trap type on plume structure: a potential mechanism for differential performance of intercept trap designs for Monochamus species
<p>Studies have demonstrated that semiochemical-baited intercept traps differ in their performance for sampling insects, but we have an incomplete understanding of how and why intercept trap design effects vary among insects. This can significantly delay both the development of new and optimization of existing survey and detection tools. The development of a mechanistic understanding of why trap performance varies within and among species would mitigate this delay. The primary objective of this study was to develop methods to characterize and compare the odor plumes associated with intercept traps that differ in their performance for forest Coleoptera. We released CO<sub>2</sub> and measured fluctuations of this tracer gas from 175-point locations arranged in a 2-by-3-by-2-m grid cuboid downwind of a standard multiple-funnel, a modified multiple-funnel, a panel, a canopy malaise trap, and a blank control (i.e., no trap) in a greenhouse. Significant differences in trapping efficacy between these different trap designs were observed for <i>Monochamus scutellatus</i> (Say) and <i>Monochamus notatus</i> (Drury) in a field trial. Significant differences were also observed in how CO<sub>2</sub> accumulated in time at different positions downwind among these different trap designs. Turbulent dispersion is the dominant force structuring odor plumes and creates intermittency in the odor plume that is important for sustained upwind flight in insects. Methodological and instrumental limitations resulted in the inability to determine instantaneous plume structures and vortex shedding frequencies for different intercept trap designs. Although we observed differences in the odor plumes emanating downwind of the different intercept trap designs, we were unable to reconcile these differences with capture rates of the different trap designs for <i>M. scutellatus</i> and <i>M. notatus</i>.</p>
From structural phase transition to highly sensitive lifetime based luminescent thermometer: multifaceted modification of thermometric performance in Y0.9xNdxYb0.1PO4 nanocrystals
<p>The development of a highly sensitive luminescent thermometer requires a deep understanding of the correlation between the structural properties of the host material and the temperature-dependent luminescence properties of lanthanide emitters embedded in these matrices. In some cases, the presence or increased concentration of the co-dopant ions can alter not only the spectral features, but may additionally cause far-ranging structural changes that further, even more tremendously, modify the luminescence properties of the phosphor. In this work, the temperature dependent luminescence kinetics in response to structural changes induced by increasing Nd<sup>3+</sup> ion doping in Y<sub>0.9−<em>x</em></sub>Nd<sub><em>x</em></sub>Yb<sub>0.1</sub>PO<sub>4</sub> nanocrystals are investigated, which correspondingly demonstrated phase transitions from xenotime to monazite structures. Consequently, the low temperature lifetime of the <sup>2</sup>F<sub>5/2</sub> state of Yb<sup>3+</sup> elongates. Moreover, by increasing the Nd<sup>3+</sup> amount, the relative sensitivity of the Yb<sup>3+</sup> luminescence lifetime-based luminescent thermometer was enhanced and, simultaneously, the temperature at which high sensitivity is achieved was reduced. The maximal relative sensitivity was found to be 2%/K at 273 K for Nd<sub>0.9</sub>Yb<sub>0.1</sub>PO<sub>4</sub> nanocrystals.</p>
Habitat structural complexity predicts cognitive performance and behavior in western mosquitofish
<p>Urbanization and stream order alter freshwater habitat complexity (defined as the degree of variation in physical habitat structure). More complex habitats have more variation in habitat structure. Habitat complexity affects species composition and shapes animal ecology, behavior, and cognition. We used a delayed detour test to measure whether motor self-regulation and behavior of Western mosquitofish, <em>Gambusia affinis, </em>varied with habitat structural complexity that was quantified for nine populations. We predicted that motor self-regulation, motivation, and risk-taking behavior would increase with increasing habitat complexity, yet we found the opposite relationship. Lower complexity habitats offer less refuge which could increase predation pressure and select for greater risk-taking by fish with greater motor self-regulation. Our findings provide insight into how habitat complexity is related to cognitive processes and behavioral outcomes, and provide an explanation for why some species have a higher tolerance for urbanized environments.</p>
Toward Non-Corrosion and Highly Sustainable Structural Members by Using Ultra-High-Performance Materials for Transportation Infrastructure
<p>Corresponding data set for Tran-SET Project No. 18STUTA01. Abstract of the final report is stated below for reference:</p> <p>"This research focused on investigating a highly sustainable and efficient reinforced concrete structural member for future infrastructure by utilizing emerging high-performance materials. These materials include ultra-high-performance fiber-reinforced concrete (UHP-FRC) and corrosion-resistant high-strength fiber-reinforced polymer (FRP) bars. Four reduced scale UHP-FRC specimens were tested under large displacement reversals to prove the proposed new ductile-concrete strong-reinforcement (DCSR) design concept by fully utilizing these ultra-high-performance materials. Micro steel fibers were incorporated into three specimens and ultra-high molecular weight polyethylene fibers were blended into the fourth specimen. One specimen with ASTM A1035 MMFX high-strength steel rebars, one with high-strength glass fiber reinforced polymer (GFRP) rebars, and two with high-strength basalt fiber reinforced plastic (BFRP) rebars were tested. The beams had a reinforcement ratio of 14% to 15%. The test results concluded that the beams could sustain very large cyclic drift ratios without major damage in the UHP-FRC material, which provided ample shear strength and confinement to the reinforcement throughout the testing. Even with the high amount of reinforcement, UHP-FRC’s superior ductility provided a very stable cyclic behavior up to some very large drift ratios. Because of the DCSR design, all specimens also exhibited a self-centering ability, which considerably reduces the residual displacement after being subjected to large displacement reversals. The test results also show that the high damage-resistance and self-centering characteristics of the proposed UHP-FRC flexural members can provide excellent resilience for building structures."</p>
Obuasi case study data: Performance of neutral SNP barcodes to determine genetic diversity and structure of Plasmodium falciparum in Africa
<p>A small number of informative biallelic single nucleotide polymorphisms (SNPs) have been proposed to be an economical method to fast-track the genotyping and relatedness analysis of <em>Plasmodium</em> <em>falciparum</em> in malaria-endemic areas. Whilst used successfully in low-transmission areas where infections are monoclonal and highly related, we present the first study to evaluate the performance of these 24- and 96-SNP molecular barcodes in African countries characterised by moderate-to-high transmission. Using haplotypes generated from the MalariaGEN <em>P. falciparum</em> Community Project version 6 database, 52.3% of infections were multiclonal, generating high frequencies of mixed-allele calls (MACs) per isolate. Both multiclonality and low heterozygosity of SNPs impeded haplotype construction for analyses of relatedness. Although fewer SNPs provided usable data, these SNP barcodes weakly identified genetic differentiation across large geographic distances. However, both minor and major alleles' frequencies were temporally unstable. We conclude that these standardised SNP barcodes are vulnerable to ascertainment bias. While large numbers of SNPs acquired by whole-genome sequencing and computational methods to construct haplotypes present a way forward, these approaches may not be practical or cost-effective for surveillance on large scales in malaria-endemic areas. </p>
Habitat structural complexity predicts cognitive performance and behavior in western mosquitofish
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Impact of intercept trap type on plume structure: a potential mechanism for differential performance of intercept trap designs for Monochamus species
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Obuasi case study data: Performance of neutral SNP barcodes to determine genetic diversity and structure of Plasmodium falciparum in Africa
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Structural and chemical changes in He+ bombarded polymers and related performance properties
<p><span>Folder zawiera pliki excel, każdy z nich odpowiada jednemu wykresowi z publikacji i zawiera dane pozwalające na wykonanie wykresu.</span></p>
Examining factors affecting sustainable performance of building projects using structural equation modeling
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Supplementary Data for "Exploring structure-function relationships in engineered receptor performance using computational structure prediction"
<p>These data are supplementary data for the manuscript "<strong>Exploring structure-function relationships in engineered receptor performance using computational structure prediction</strong>", which has been submitted for consideration for publication. These data include protein structure predictions used in this study.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.