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4,669 results for “Environment;”
Data from: Random heteropolymers preserve protein function in foreign environments
The successful incorporation of active proteins into synthetic polymers could lead to a new class of materials with functions found only in living systems. However, proteins rarely function under the conditions suitable for polymer processing. On the basis of an analysis of trends in protein sequences and characteristic chemical patterns on protein surfaces, we designed four-monomer random heteropolymers to mimic intrinsically disordered proteins for protein solubilization and stabilization in non-native environments. The heteropolymers, with optimized composition and statistical monomer distribution, enable cell-free synthesis of membrane proteins with proper protein folding for transport and enzyme-containing plastics for toxin bioremediation. Controlling the statistical monomer distribution in a heteropolymer, rather than the specific monomer sequence, affords a new strategy to interface with biological systems for protein-based biomaterials.
Data from: Testing and interpreting the shared space-environment fraction in variation partitioning analyses of ecological data
Variation partitioning analyses combined with spatial predictors (Moran's eigenvector maps, MEM) are commonly used in ecology to test the fractions of species abundance variation purely explained by environment and space. However, while these pure fractions can be tested using a classical residuals permutation procedure, no specific method has been developed to test the shared space-environment fraction (SSEF). Yet, the SSEF is expected to encompass a major driver of community assembly, that is, an induced spatial dependence effect (ISD; i.e. the reflection of a spatially structured habitat filter on a species distribution). A reliable test of this fraction is therefore crucial to properly test the presence of an ISD on ecological data. To bridge the gap, we propose to test the SSEF through spatially-constrained null models: torus-translations, and Moran spectral randomisations. We investigated the type I error rate and statistical power of our method based on two real environmental datasets and simulations of tree distributions. Ten types of tree distribution displaying contrasted aggregation properties were simulated, and their abundances were sampled in 153 regularly-distributed 20 × 20 m quadrats. The SSEF was tested for 1000 simulated tree distributions either unrelated to the environment, or filtered by environmental variables displaying contrasting spatial structures. The method proposed provided a correct type I error rate (< 0.05). The statistical power was high (> 0.9) when abundances were filtered by an environmental variable structured at broad scale. However, the spatial resolution allowed by the sampling design limited the power of the method when using a fine-scale filtering variable. This highlighted that an ISD can be properly detected providing that the spatial pattern of the filtering process is correctly captured by the sampling design of the study. An R function to apply the SSEF testing method is provided and detailed in a tutorial.
Data from: Diversification in temporally heterogeneous environments: effect of the grain in experimental bacterial populations.
Although theory established the necessary conditions for diversification in temporally heterogeneous environments, empirical evidence remains controversial. One possible explanation is the difficulty of designing experiments including the relevant range of temporal grains and the appropriate environmental tradeoffs. Here, we experimentally explore the impact of the grain on the diversification of the bacterium Pseudomonas fluorescens SBW25 in a temporally fluctuating environment by including twenty different pairs of environments and four temporal grains. In general, higher levels of diversity were observed at intermediate temporal grains. This resulted in part from the enhanced capacity of disruptive selection to generate negative genotypic correlations in performance at intermediate grains. However, the evolution of reciprocal specialization was an uncommon outcome. Although temporal heterogeneity is in theory less powerful than spatial heterogeneity to generate and maintain diversity, our results show that diversification under temporal heterogeneity is possible provided appropriate environmental grains.
Data from: The maternal cytoplasmic environment may be involved in the viability selection of gametes and zygotes
Segregation distortion is the phenomenon whereby the observed genotypic frequencies of a locus fall outside the expected Mendelian segregation ratio, and it is increasingly recognised as a potentially powerful evolutionary force. The main reason for segregation distortion is a difference in the viability of gametes and zygotes caused by viability loci in the segregating progeny. However, the maternal cytoplasm may also be involved in the viability selection of gametes and zygotes. The objectives of this study were to map the segregation distortion loci (SDL) in maize and to test the hypothesis that the viability of gametes and zygotes may also be associated with the maternal cytoplasmic environment. In the present study, a reciprocal mating design was conducted to generate an F2-segregating population. A linkage map was constructed with 126 microsatellite markers. A whole-genome scan was performed to detect the SDL in segregating populations with different maternal cytoplasm environments. Altogether, 14 SDL with strong LOD (logarithm (base 10) of odds) supports were identified in the specifically designed F2 populations. Interestingly, we found dramatic changes in the genotypic frequencies of the SDL in the two maternal cytoplasmic backgrounds, which indicated a change in the viability of gametes and zygotes in different cytoplasmic environments. Furthermore, in the JB cytoplasmic background, most of the detected SDL and complete distortion markers exhibited similar bias patterns favouring the Y53 alleles. These results suggested that selfish cytoplasmic elements may have an important role in shaping the patterns of segregation distortion in F2 populations through selective viability of gametes and zygotes.
Data from: Competitive Indices in cereal and legume mixtures in a South Asian environment
The assessment of competitive performance of mixture components is important for maximizing benefits of intercropping systems. This field study tested binary mixtures of two cereals (sorghum and pearl millet) and three forage legumes (cowpea, cluster bean and soybean), along with their sole crops on competitive indices. Sorghum-cowpea binary mixture resulted in a lower green forage yield of sorghum and cowpea by 9% and 36% respectively, but overall biomass production was increased by 30% and 117% compared to their sole crop equivalents. Partial land equivalent ratios (LER) of all component crops were higher than 0.50, indicating better land use efficiency, except of soybean in binary mixtures with cowpea and cluster bean. However, the highest LER was of sorghum-cowpea (1.55), followed by sorghum-soybean (1.48) and pearl millet-soybean (1.48) binary mixtures. Pearl millet dominated sorghum and all legumes, while cowpea remained a superior competitor among legumes as per aggressivity value index. The highest crowding ratio was exhibited by pearl millet in binary mixture with cluster bean indicating its higher competitive ability incomparison to other mixture components. Observed yield loss data indicated that pearl millet was the most resistant crop to yield loss in all binary mixtures, while soybean had the highest yield reduction. In a short term, the highest area-time equivalent ratio for sorghum-cowpea binary mixture indicated the maximum advantage for this binary mixture compared to other binary mixtures.
Data for: Fossil samples archive functional diversity in marine ecosystems: An empirical test from a present-day coastal environment (Tyler and Kowalewski)
<p>Data associated with "Fossil samples archive functional diversity in marine ecosystems: An empirical test from a present-day coastal environment" by Carrie L. Tyler and Michal Kowalewski. Data include GPS coordinates for sample localities, variables quantifying multivariate space for all three assemblages, trait data for all species, and the associated R code (Functional Fidelity.zip). Abundance data is available in Tyler and Kowalewski (2023) <a href="https://doi.org/10.7717/peerj.15574">10.7717/peerj.15574</a> at <strong><a href="https://github.com/tylercl/Multi-Taxic-Fidelity">https://github.com/tylercl/Multi-Taxic-Fidelity</a> </strong>(DOI: 10.5281/zenodo.7871639).</p>
Statistical characterization of erosion mechanics in shallow tidal environments
<p><span lang="EN-US">This study was funded by the European Union - NextGenerationEU, in the framework of the iNEST - Interconnected Nord-Est Innovation Ecosystem (iNEST ECS00000043 - CUP C43C22000340006). The views and opinions expressed are solely those of the authors and do not necessarily reflect those of the European Union, nor can the European Union be held responsible for them. The dataset was developed as part of the activities carried out by Spoke 8, Research Topic 1 (Biology of hydrosphere ecosystems), Task S8_RT1.1 (Digital Databases for Innovation in Biodiversity and Water Quality Assessment)</span></p>
Statistical characterization of suspended sediment dynamics in shallow tidal environments
<p><span lang="EN-US">This study was funded by the European Union - NextGenerationEU, in the framework of the iNEST - Interconnected Nord-Est Innovation Ecosystem (iNEST ECS00000043 - CUP C43C22000340006). The views and opinions expressed are solely those of the authors and do not necessarily reflect those of the European Union, nor can the European Union be held responsible for them. The dataset was developed as part of the activities carried out by Spoke 8, Research Topic 1 (Biology of hydrosphere ecosystems), Task S8_RT1.1 (Digital Databases for Innovation in Biodiversity and Water Quality Assessment)</span></p>
Replication Package for "Wealth Inequality in a Low Rate Environment"
Open the record for dataset details and reuse information.
CBF-Based STL Motion Planning for Social Navigation in Crowded Environment
<p>Video of submitted paper entitled "CBF-Based STL Motion Planning for Social Navigation in Crowded Environment"</p><p> </p>
Mentorship Education and the Training Environment_Dataset_Suiter et.al.
<p>We here provide the dataset used in the manuscript titled "Mentorship Education and the Training Environment"</p>
ear-EEG dataset for AAD task in Multiple-speaker environment
<div> <p>Please cite these original paper where this dataset was presented:</p> <p>YJ Yan, X Xu, H Zhu, P Tian, ZS Ge, X Wu, J Chen "Auditory Attention Decoding in Four-Talker Environment with EEG" which was accepted in INTERSPEECH 2024 and we will update more details after the closing of INTERSPEECH 2024.</p> <p>X. Xu, B.Wang, Y. Yan, X.Wu, and J. Chen, “A DenseNet-Based Method for Decoding Auditory Spatial Attention with EEG,” in ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Seoul, Korea, Republic of: IEEE, Apr. 2024, pp. 1946–1950.</p> <p>H. Zhu <em>et al</em>., "Using Ear-EEG to Decode Auditory Attention in Multiple-speaker Environment," <em>ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</em>, Hyderabad, India, 2025, pp. 1-5, doi: 10.1109/ICASSP49660.2025.10890810.</p> <p>The details of the setup for the experiment was mentioned in the original paper.</p> </div> <p><em>[1] Z. Fu, X. Wu, and J. Chen, “Congruent audiovisual speech enhances </em><em>auditory attention decoding with EEG,” Journal of Neural </em><em>Engineering, vol. 16, no. 6, p. 066033, Nov. 2019.</em></p> <p><em>[2] P. J. Sch ̈afer, F. I.</em><em> Corona-Strauss, R. Hannemann, S. A. Hillyard, </em><em>and D. J. Strauss, “Testing the Limits of the Stimulus Reconstruction </em><em>Approach: Auditory Attention Decoding in a Four-</em><em>Speaker Free Field Environment,” Trends in Hearing, vol. 22, p. </em><em>233121651881660, Jan. 2018.</em></p> <p><em>[3] T. Qu, Z. Xiao, M. Gong, Y. Huang, X. Li, and X. Wu, </em><em>“Distance-Dependent Head-Related Transfer Functions Measured </em><em>With High Spatial Resolution Using a Spark Gap,” IEEE Transactions </em><em>on Audio, Speech, and Language Processing, vol. 17, no. 6, </em><em>pp. 1124–1132, Aug. 2009.</em></p> <p><em><br>In our code repository https://github.com/zhl486/Ear_EEG_code.git , we have provided the envelopes of the experimental stimuli. If you require the original speech stimuli for auditory attention decoding (AAD) tasks, please feel free to contact us via email 2301111611@stu.pku.edu.cn and provide a brief explanation of your research needs.<br></em></p>
Dataset: Effect of Zr addition on the corrosion resistance of Ti-Mo alloy in the H2O2-containing inflammatory environment
<p><strong>Title: Effect of Zr addition on the corrosion resistance of Ti-Mo alloy in the H2O2-containing inflammatory environment</strong></p> <p>Authors: Agata Sotniczuk, Agata Sotniczuk, Witold Chromiński, Damian Kalita, Halina Garbacz, Chenyang Xie, Junhui Tang, Baojie Dou, Marcin Pisarek, Aleksandra Baron-Wiecheć, Łukasz Kurpaska, Fan Sun, Kevin Ogle</p> <p><strong>Corresponding Author: Agata Sotniczuk ORCID: 0000-0002-3468-0468</strong></p> <p>This record contains files generated in the preparation process of the following publication:<br>Effect of Zr addition on the corrosion resistance of Ti-Mo alloy in the H2O2-containing inflammatory environment<br>Agata Sotniczuk, Agata Sotniczuk, Witold Chromiński, Damian Kalita, Halina Garbacz, Chenyang Xie, Junhui Tang, Baojie Dou, Marcin Pisarek, Aleksandra Baron-Wiecheć, Łukasz Kurpaska, Fan Sun, Kevin Ogle submitted to Applied Surface Science (Elsevier)</p> <p><strong>This research was funded in whole by National Science Centre, Poland [2023/48/C/ST11/00085]: Sonatina 7 grant.</strong></p> <p><strong>Designations:</strong><br>TiMo: titanium alloy with 12 weight % of molybdenum (Ti-12Mo) fabricated by arc melting technique followed by cold rolling and heat treatment<br>TiMoZr: titanium alloy with 12 weight % of molybdenum and 5 weight% of zirconium (Ti-12Mo-5Zr) fabricated by arc melting technique cold rolling and heat treatment (950 Celsius degrees/30 minutes) followed by water quenching<br>EBSD: Electron backscattered diffraction<br>PBS: Phosphate buffer saline solution<br>OCP: Open circuit potential<br>EIS: Electrochemical impedance spectroscopy<br>PSP: Potentiostatic polarization<br>ICP-AES: Inductively coupled plasma atomic emission spectrometer<br>AESEC: Atomic emission spectroelectrochemistry <br>XPS: X-ray photoelectron spectroscopy<br>SEM: Scanning electron microscope<br>TEM: Transmission electron microscope<br>HAADF STEM: High-angle annular dark-field imaging in a scanning transmission electron microscope <br>EDS: Energy dispersive spectroscopy<br>|Z|: impedance modulus [Ohm·cm^2]<br>vTi - dissolution rate for titanium [ng·s^-1·cm^-2]<br>vMo - dissolution rate for molybdenum [ng·s^-1·cm^-2]<br>vZr - dissolution rate for zirconium [ng·s^-1·cm^-2]<br>vƩ TiMo - total elemental dissolution rate for TiMo alloy[ng·s^-1·cm^-2]<br>vƩ TiMoZr - total elemental dissolution rate for TiMoZr alloy[ng·s^-1·cm^-2]<br>jƩ TiMo - total elemental current for TiMo alloy [µA·cm^-2]<br>jƩ TiMoZr- total elemental current for TiMoZr alloy [µA·cm^-2]<br>je TiMo - total electrochemical current for TiMo alloy [µA·cm^-2]<br>je TiMoZr - total electrochemical current for TiMoZr alloy [µA·cm^-2]</p> <p><strong>General remarks: Conditions of corrosion tests (OCP, EIS, AESEC):</strong><br>1) Solution: PBS+0.1M H2O2<br>2) Temperature: 37 Celsius degrees<br>3) Electrodes: reference electrode - Ag/AgCl/KCl (sat), counter electrode-platinum plate<br>4) EIS: potential - OCP±10 mV, frequency range - 1000 Hz down to 0.01 Hz, surface area: 0.785 cm2<br>5) AESEC: tests were performed in a flow cell and the flow rate of solution was 1 ml/min, surface area: 1 cm2. AESEC procedure: step 1) OCP monitoring (1200s), step 2) PSP at -1V (1200s), step 3) OCP monitoring (2700s)</p> <p>Files formats: Raw data and calculated results of OCP, EIS and AESEC tests: .xls, SEM micrographs: .tif, TEM micrographs/ EBSD /EDS maps: .jpg or .tif<br>Units are provided in brackets.</p> <p>Content of data files is described in details in README_APSUC2024.txt file</p> <p>DOI: 10.5281/zenodo.13903531</p> <p>Data are published under Creative Commons Zero v1.0 Universal (CC0) license</p> <p><strong>How to cite Dataset</strong>: Sotniczuk, A., Chromiński, W., Kalita, D., Garbacz, H., Xie, C., Tang, J., Dou, B., Pisarek, M., Baron-Wiecheć, A., Kurpaska, Ł., Sun, F., & Ogle, K. (2024). Dataset: Effect of Zr addition on the corrosion resistance of Ti-Mo alloy in the H2O2-containing inflammatory environment [Data set]. Zenodo. https://doi.org/10.5281/zenodo.13903531</p>
Figure 3 from: Palchetti MV, Cantero JJ, Morales-Fierro V, Barboza GE, Moreira-Muñoz A (2021) Living in extreme environments: distribution of Lycium humile (Solanaceae), an endemic halophyte from the Altiplano-Puna region, South America. PhytoKeys 185: 1-15. https://doi.org/10.3897/phytokeys.185.71377
Figure 3 Distribution map of Lycium humile (light-blue circles) in the Altiplano-Puna region.
Figure 1 from: Palchetti MV, Cantero JJ, Morales-Fierro V, Barboza GE, Moreira-Muñoz A (2021) Living in extreme environments: distribution of Lycium humile (Solanaceae), an endemic halophyte from the Altiplano-Puna region, South America. PhytoKeys 185: 1-15. https://doi.org/10.3897/phytokeys.185.71377
Figure 1 Lycium humileA overview of a plant in its habitat B flower C fruits D plant architecture.
Inlists for paper: Stripped-Envelope Stars in Different Metallicity Environments I. Evolutionary Phases, Classification and Populations
<p>MESA input files for the models presented in the paper "Stripped-Envelope Stars in Different Metallicity Environments I. Evolutionary Phases, Classification and Populations".</p> <p>The files included here can reproduce both the stellar models discussed in the paper (he_star_model.zip), as well as the initial helium star models (initial_model.zip). Some models used different numerical parameters to achieve convergence to core collapse. A table (MESA_params.dat) is included here with the specific models that have parameters that differ from the standard ones, and the value used for the parameters used in these models. To reproduce a model from this list, the parameters must be changed in the inlist_project file contained in he_star_model.zip.</p> <p>Also included is a table (lifetimes.dat) containing values of different parameters used in each simulation, as well as the data obtained from these models, used to create Figs. 4 and 5.</p>
Bird habitat preference in urban environments
<p>We provide three data sets that were used to estimate bird habitat preference in an urban environment.<br> The Phi-bird preferences and Logistic-bird preference data sets contain the necessary information to estimate bird habitat preference via the Phi association coefficient and logistic regression, respectively. Additionally, the estimates obtained with each approach are presented. In the Phi-bird preferences data set, the bird records collected from unstructured citizen science data and structured scientific information are shown. <br> Finally, the Validation data set presents all the information used to validate the reliability of both, the Phi association coefficient and the Logistic regression methods</p>
The conventional genetic basis for obesity is impacted by adverse childhood experiences: a multi-ethnic study of gene-environment effects
<p>Adverse Childhood Experiences are stressful and traumatic events occurring before the age of eighteen known to cause mental and physical health problems, including increased risk of obesity. Obesity remains an ongoing national challenge with no predicted solution. </p> <p>We examine a subset of the Healthy Nevada Project, focusing on a multi-ethnic cohort of 15,886 sequenced participants with recalled adverse childhood events to study how ACEs and their genotype-environment interactions affect BMI. Specifically, the Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records and social health determinants questionnaire to identify: (1) the effect of ACEs on BMI in the absence of genetics; (2) the effect of genotype-environment interactions on BMI; (3) how these gene-environment interactions differ from canonical genetic associations of BMI. </p> <p>The study found very strong significant associations between the number of adverse childhood experiences and adult obesity. Additionally, we identified fifty-five common and rare variants that exhibited gene-interaction effects including three variants in the CAMK1D gene and four variants in LHPP; both genes are linked to schizophrenia. Surprisingly, none of the variants identified with interactive effects were in canonical obesity-related genes. Here we show the delicate balance between genes and environment, and how the two strongly influence each other.</p>
Supplemental Files for The Microbiome and Volatile Organic Compounds Reflect the State of Decomposition in an Indoor Environment
<p>Supplemental File 1: Operational taxonomic unit (OTU) matrix, taxonomy table, and metadata of decomposing swine microbiome data (uploaded file into R)</p> <p>Supplemental File 2: Volatile Organic Compounds identified in each stage of decomposition with functional group, retention time, peak area, and logarithmic value of relative peak area</p> <p>Supplemental File 3: Random forest analysis output including predictor species for each sampling location and Groupings</p>
Predicting the solvation of organic compounds in aqueous environments: from alkanes and alcohols to pharmaceuticals
<p>Please refer to the article entitled "Predicting the solvation of organic compounds in aqueous environments: from alkanes and alcohols to pharmaceuticals" for full detail.</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.