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opencc-by-4.0Oct 2021View details →

High-Throughput Screening of Tribological Properties of Monolayer Films using Molecular Dynamics and Machine Learning: Supplemental Repository

Supplemental repository for the "High-Throughput Screening of Tribological Properties of Monolayer Films using Molecular Dynamics and Machine Learning" article. Contains calculated tribological properties of dual-monolayer systems from Molecular Dynamics (MD) simulation and Machine Learning (ML).

opencc-by-4.0Feb 2022View details →

Dataset related to Balazs et al. The dynamics of forearc – back-arc basin subsidence: numerical models and observations from Mediterranean subduction zones

Additional model data to publication by Balazs et al. The dynamics of forearc – back-arc basin subsidence: numerical models and observations from Mediterranean subduction zones

opencc-zeroMar 2022View details →

Unravelling processes between phenotypic plasticity and population dynamics in migratory birds

Populations can rapidly respond to environmental change via adaptive phenotypic plasticity, which can also modify interactions between individuals and their environment, affecting population dynamics. Bird migration is a highly plastic resource-tracking tactic in seasonal environments. However, the link between the population dynamics of migratory birds and migration tactic plasticity is not well understood. The quality of staging habitats affects individuals' migration timing and energy budgets in the course of migration, and can consequently affect individuals' breeding and overwintering performance, and impact population dynamics. Given staging habitats being lost in many parts of the world, our goal is to investigate responses of individual migration tactics and population dynamics in the face of loss of staging habitat, and to identify the key processes connecting them. We started by constructing and analysing a general full-annual-cycle individual-based model with a stylized migratory population to generate hypotheses on how changes in the size of staging habitat might drive changes in individual stopover duration and population dynamics. Next, through the interrogation of survey data, we tested these hypotheses by analysing population trends and stopover duration of migratory waterbirds experiencing loss of staging habitat. Our modelling exercise led to us posing the following hypotheses: the loss of staging habitat generates plasticity in migration tactics, with individuals remaining on the staging habitat for longer to obtain food due to a reduction in per capita food availability. The subsequent increasing population density on the staging habitat has knock on effects on population dynamics in the breeding and overwintering stage. Our empirical results were consistent with the modelling predictions. Our results demonstrate how environmental change that impacts one energetically costly life history stage in migratory birds can have population dynamics impacts across the entire annual cycle via phenotypic plasticity.

Mechanical data of rotary shear experiments for the manuscript: "Determination of parameters characteristic of dynamic weakening mechanisms during seismic faulting in cohesive rocks".

Mechanical data of rotary shear experiments and temperature measurements Each experiment is presented in a file with the experiment name (mechanical data of rotary shear experiment) and a file with the experiment name and _Temp (temperature measurement with the optical fiber). Mechanical data are presented in a tab-delimited file with calibrated measurements of: <ul> <li>Time (milliseconds)</li> <li>Normal stress: Normal (MPa) </li> <li>Fault displacement: Slip (mm)</li> <li>Fault velocity: Velocity (mm/s)</li> <li>Shear stress: Shearstress (MPa)</li> <li>Axial shortening: Shortening (mm).</li> </ul>

Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to detect breast malignant Lesions

We uploade the dataset of the manuscript "Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to detect breast malignant Lesions" by Current Oncology.

Molecular dynamics trajectories of protein folding

Molecular dynamics trajectories of protein folding are deposited for educational purposes. Currently, the following trajectories are available: <ul> <li>Chignolin (five independent NVT simulations up to 1.5 micro-sec): <ul> <li>`movie.pse` is a PyMOL session file of MD trajectories. </li> <li>`movie.mp4` is a movie file that shows you how a protein folds during simulation.</li> <li>xtc files (Gromacs compressed format) and corresponding tpr files.</li> <li>gro files for movie making</li> </ul> </li> </ul>   Computational setting  <ul> <li>Amber ff99SB-ILDN for protein (Lindorff-Larsen, K. et al. Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins 78, 1950–1958 (2010))</li> <li>TIP3P water model</li> <li>0.1 M salt concentration </li> <li>NVT ensemble at 300 K with V-rescale thermostat (Bussi, G., Donadio, D. & Parrinello, M. Canonical sampling through velocity rescaling. J. Chem. Phys. 126, 014101 (2007))</li> <li>Time step : 2 fs</li> <li>gromacs-2020.6</li> </ul>

Approximate Entropy of Spiking Series Reveals Different Dynamical States in Cortical Assemblies

Self-organized criticality theory proved that information transmission and computational performances of neural networks are optimal in critical state. By using recordings of the spontaneous activity originated by dissociated neuronal assemblies coupled to Micro-Electrode Arrays (MEAs), we tested this hypothesis using Approximate Entropy (ApEn) as a measure of complexity and information transfer. We analysed 60 min of electrophysiological activity of three neuronal cultures exhibiting either sub-critical, critical or super-critical behaviour. The firing patterns on each electrode was studied in terms of the inter-spike interval (ISI), whose complexity was quantified using ApEn. We assessed that in critical state the local complexity (measured in terms of ApEn) is larger than in sub- and super-critical conditions. Our estimations were stable when considering epochs as short as 5 min. These preliminary results indicate that ApEn has the potential of being a reliable and stable index to monitor local information transmission in a neuronal network during maturation. Thus, ApEn applied on ISI time series appears to be potentially useful to reflect the overall complex behaviour of the neural network, even monitoring a single specific location.

opencc-by-4.0Jun 2022View details →

Dataset (II) related to publication: Discrepancy in interactions and conformational dynamics of pregnane X receptor (PXR) bound to an agonist and a novel competitive antagonist

MD simulation data related to the publication Rashidian et al.: Discrepancy in interactions and conformational dynamics of pregnane X receptor (PXR) bound to an agonist and a novel competitive antagonist. <a href="https://doi.org/10.1016/j.csbj.2022.06.020">https://doi.org/10.1016/j.csbj.2022.06.020</a> Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files) dataset I: systems SRL+Co, C-100 and BAY-1797 dataset I: each file contains all branched replicas and the main replica. dataset1:  C_100_Replica1 contains four branched replicas and the main replica. The two of four branched replicas which stem from the middle of the main replica named: b_c_D1_r1_2285 (corresponding name in the SI data is R1_a) and b_c_D1_2285_r1_2 (corresponding name in the SI data is R1_b). dataset1: C_100_Replica2–5 , each file contains one main replica and the two branches. dataset I: system SRL+Co ;each file contains one main replica dataset I: system BAY-1797; each file contains one main replica dataset II:system SRL ; each file contains one main replica.

opencc-by-4.0Jun 2022View details →

Dataset (I) related to publication: Discrepancy in interactions and conformational dynamics of pregnane X receptor (PXR) bound to an agonist and a novel competitive antagonist

opencc-zeroMar 2022View details →

A dynamic ancestral graph model and GPU-based simulation of a community based on metagenomic sampling

In this paper we present an ancestral graph model of the evolution of a guild in an ecological community. The model is based on a metagenomic sampling design in that a random sample is taken at the community, as opposed the taxon, level and species are discovered by genetic sequencing. The specific implementation of the model envisions an ecological guild that was founded by colonization at some point in the past that then potentially undergoes diversification by natural selection. Within the graph, species emerge and evolve through the diversification process and their densities in the graph are dynamic and governed by both ecological drift and random genetic drift, as well as differential viability. We employ the 3% sequence divergence rule at a marker locus to identify Operational Taxonomic Units. We then explore approaches to see if there are indirect signals of the diversification process, including population genetic and ecological approaches. In terms of population genetics, we study the joint site frequency spectrum of OTUs, as well its associated statistics. In terms of ecology, we study the species (or OTU) abundance distribution. For both we observe deviations from neutrality, which indicates that there may be signals of diversifying selection in metagenomic studies under certain conditions. The model is available as a GPU-based computer program in C/C++ and using OpenCL, with the long-term goal of adding functionality iteratively to model large-scale eco-evolutionary processes for metagenomic data.

opencc-zeroMar 2022View details →

Abiotic stress and biotic factors mediate range dynamics on opposing edges

Aim: In the face of global change, understanding causes of range limits is one of the most pressing needs in biogeography and ecology. A prevailing hypothesis is that abiotic stress forms cold (upper latitude/altitude) limits whereas biotic interactions create warm (lower) limits. A new framework – Interactive Range-Limit Theory (iRLT) – asserts that positive biotic factors such as food availability can ameliorate abiotic stress along cold edges, whereas abiotic stress can have a positive effect and mediate biotic interactions (e.g., competition) along warm limits. Location: Northeastern US Taxon: Carnivora Methods: We evaluated two hypotheses of iRLT using occupancy and structural equation modeling (SEM) frameworks based on data collected over a six-year period (2014–2019) of six carnivore species across a broad latitudinal (42.8–45.3°N) and altitudinal (3–1451 m) gradient. Results: We found that snow directly limits populations, but prey or habitat availability can influence range dynamics along cold edges. For example, bobcats (Lynx rufus) and coyotes (Canis latrans) were limited by deep snow and long winters, but the availability of prey had a strong positive effect. Conversely, snow had a strong positive effect on the warm limits of Canada lynx (Lynx canadensis), countering the negative effect of competition with the phylogenetically-similar bobcat and with coyotes, highlighting how climate mediates competition between species. Main conclusions: We used an integrated dataset that included competitors and prey species collected at the same spatial and temporal scale. As such, this design, along with a causal modeling framework (SEM), allowed us to evaluate community-wide hypotheses at macroecological scales and identify coarse-scale drivers of species' range limits. Our study supports iRLT and underscores the need to consider direct and indirect mechanisms for studying range dynamics and species' responses to global change.

Data archive for the publication: Multi-variable compensated quantum yield measurements of upconverting nanoparticles with high dynamic range: a systematic approach

The two compressed repositories contain raw and analysed data for the following publication on Optics Express:  <a href="https://doi.org/10.1364/OE.452874">Multi-variable compensated quantum yield measurements of upconverting nanoparticles with high dynamic range: a systematic approach</a> The code for processing and analysing these data is available on GitHub and it has its own DOI.  To access the code and for instructions on how to run the it follow the link: <a href="https://github.com/Biophotonics-Tyndall/QY-System-paper">Biophotonics-Tyndall/QY-System-paper (github.com)</a>.

Short-term social dynamics following anthropogenic and natural disturbances in a free-living mammal

Anthropogenic disturbances are widely recognized for their far-reaching consequences on the survival and reproduction of wildlife, but we understand comparatively little about their effects on the social lives of group-living animals. Here we examined these short-term changes in affiliative behavior as part of a long-term study on a human-tolerant and socially flexible population of California ground squirrels (Otospermophilus beecheyi). We used social network analysis to examine short-term changes in affiliative behavior and individual consistency in response to disturbances by humans, domestic dogs, or a natural predator (the coyote). Overall, juveniles were more involved than adults in affiliative interactions, but the short-term directional effects of these acute disturbances on social cohesion varied by disturbance type. Human and dog presence reduced aboveground connectivity, particularly for juveniles, whereas disturbances by coyotes generally promoted it. Beyond these effects, we also detected non-random responses to disturbances, though individuals were not very consistent in their directional response to different disturbance types. Our results demonstrate the flexible changes in social behavior triggered by short-term disturbances imposed by humans and other threats. More generally, our findings elucidate the underappreciated sensitivity of animal social interactions to short-term ecological disturbances, raising key questions about their consequences on the social lives of animals.

Data from: SARS-CoV-2 antibody dynamics in blood donors and COVID-19 epidemiology in eight Brazilian state capitals

The COVID-19 situation in Brazil is complex due to large differences in the shape and size of regional epidemics. Here we tested monthly blood donation samples for IgG antibodies from March 2020 to March 2021 in eight of Brazil's most populous cities. The inferred attack rate of SARS-CoV-2 adjusted for seroreversion in December 2020, before the Gamma VOC was dominant, ranged from 19.3% (95% CrI 17.5% - 21.2%) in Curitiba to 75.0% (95% CrI 70.8% - 80.3%) in Manaus. Seroprevalence was consistently smaller in women and donors older than 55 years. The age-specific infection fatality rate (IFR) differed between cities and consistently increased with age. The infection hospitalisation rate (IHR) increased significantly during the Gamma-dominated second wave in Manaus, suggesting increased morbidity of the Gamma VOC compared to previous variants circulating in Manaus. The higher disease penetrance associated with the health system's collapse increased the overall IFR by a minimum factor of 2.91 (95% CrI 2.43 – 3.53). These results highlight the utility of blood donor serosurveillance to track epidemic maturity and demonstrate demographic and spatial heterogeneity in SARS-CoV-2 spread.

opencc-by-4.0Apr 2022View details →

Data Archive for "Acceleration as a proxy for energy expenditure in a facultative-soaring bird: comparing dynamic body acceleration and time-energy budgets to heart rate"

Heart rate, acceleration, and respirometry data from four wild-caught gulls during climate chamber and treadmill calibration measurements (2018), as well as heart rate and acceleration data from five free-ranging gulls from a colony on Texel, NL during the breeding season (May - July, 2019).

opencc-by-4.0Apr 2022View details →

Dynamic deformation calculation of articular cartilage and cells using resonance-driven laser scanning microscopy - Deformable Registration Validation Dataset

This dataset includes the supporting input files, scripts, and output files for validation tests of lsmgridtrack v0.3 applied to resonance scanned images.

opencc-by-4.0Jul 2019View details →

Fig. 1 in Structure And Dynamics Of Crucians' Settlements (Cypriniformes, Сarassius) In Water Systems Of Eastern Ukraine

Fig. 1. The places of collecting crucian carp selections from the water systems of Eastern Ukraine.

Eco-evolutionary dynamics modulate plant responses to global change depending on plant diversity and species identity

Global change has dramatic impacts on grassland diversity. However, little is known about how fast species can adapt to diversity loss and how this affects their responses to global change. Here, we performed a common garden experiment testing whether plant responses to global change are influenced by their selection history and the conditioning history of soil at different plant diversity levels. Using seeds of four grass species and soil samples from a 14-year-old biodiversity experiment, we grew the offspring of the plants either in their own soil or in soil of a different community, and exposed them either to drought, increased nitrogen input, or a combination of both. Under nitrogen addition, offspring of plants selected at high diversity produced more biomass than those selected at low diversity, while drought neutralized differences in biomass production. Moreover, under the influence of global change drivers, soil history, and to a lesser extent plant history, had species-specific effects on trait expression. Our results show that plant diversity modulates plant-soil interactions and growth strategies of plants, which in turn affects plant eco-evolutionary pathways. How this change affects species' response to global change and whether this can cause a feedback loop should be investigated in more detail in future studies.

opencc-by-4.0Apr 2022View details →

Insights into the stability of engineered mini-proteins from their dynamic electronic properties

Coordinates and partial charges from GFN2-xTB and wPBEh/cc-pvdz for 20 ps x 20 replicas for two variants of Trp-cage (TC5b and TC10b) as supporting information.

Data from: Decipher soil organic carbon dynamics and driving forces across China using machine learning

The dynamics of soil organic carbon (SOC) play a critical role in modulating global warming. However, the long-term spatiotemporal changes of SOC at large scale and the impacts of driving forces remain unclear. In this study, we investigated the dynamics of SOC in different soil layers across China through the 1980s to 2010s using a machine learning approach and quantified the impacts of the key factors based on factorial simulation experiments. Our results showed that the latest (2000-2014) SOC stock in the first meter soil (SOC100) was 80.68 ± 3.49 Pg C, of which 42.6% was stored in the top 20 cm, sequestrating carbon with a rate of 30.80 ± 12.37 g C m-2 yr-1 since the 1980s. Our experiments focusing on the recent two periods (2000s and 2010s) revealed that climate change exerted the largest relative contributions to SOC dynamics in both layers and warming or drying can result in SOC loss. However, the influence of climate change weakened with soil depth, while the opposite for vegetation growth. Relationships between SOC and forest canopy height further confirmed this strengthened impact of vegetation with soil depth, and highlighted the carbon sink function of deep soil in mature forest. Moreover, our estimates suggested that SOC dynamics in 71% of topsoil were controlled by climate change and its coupled influence with environmental variation (CE). Meanwhile CE and the combined influence of climate change and vegetation growth dominated the SOC dynamics in 82.05% of the first meter soil. Additionally, the national cropland topsoil organic carbon increased with a rate of 23.6 ± 7.6 g C m-2 yr-1 since the 1980s, and the widely applied nitrogenous fertilizer was a key stimulus. Overall, our study extended the knowledge about the dynamics of SOC and deepened our understanding about the impacts of the primary factors.