Find research datasets worth reusing

Target cell-specific synaptic dynamics of excitatory to inhibitory neuron connections in supragranular layers of human neocortex

Rodent studies have demonstrated that synaptic dynamics from excitatory to inhibitory neuron types are often dependent on the target cell type. However, these target cell-specific properties have not been well investigated in human cortex, where there are major technical challenges in reliably obtaining healthy tissue, conducting multiple patch-clamp recordings on inhibitory cell types, and identifying those cell types. Here, we take advantage of newly developed methods for human neurosurgical tissue analysis with multiple patch-clamp recordings, post-hoc fluorescent in situ hybridization (FISH), machine learning-based cell type classification, and prospective GABAergic AAV-based labeling to investigate synaptic properties between pyramidal neurons and PVALB- vs. SST-positive interneurons. We find that there are robust molecular differences in synapse-associated genes between these neuron types, and that individual presynaptic pyramidal neurons evoke postsynaptic responses with heterogeneous synaptic dynamics in different postsynaptic cell types. Using molecular identification with FISH and classifiers based on transcriptomically identified PVALB neurons analyzed by Patch-seq, we find that PVALB neurons typically show depressing synaptic characteristics, whereas other interneuron types including SST-positive neurons show facilitating characteristics. Together, these data support the existence of target cell-specific synaptic properties in human cortex that are similar to rodents, thereby indicating evolutionary conservation of local circuit connectivity motifs from excitatory to inhibitory neurons and their synaptic dynamics.

opencc-by-4.0Sep 2022View details →

Investigation on Dynamic Characteristics of Lightning Return Stroke Channel

The dynamic characteristics in lightning discharge plasma channel are of great significance in studying the micro-physical mechanism of the discharge process. This paper established a simplified radiation-hydrodynamic model (SRHM) of the return stroke channel radial expansion based on the fluid dynamics theory and the time evolution characteristics of the light radiation power observed by experiments. The influence of current waveform on the dynamic characteristics of return stroke channel was investigated, and the temporal evolutions of the characteristic parameters, such as temperature, pressure and expansion speed for return stroke channel were analyzed. The results indicated that the current peak value and the risetime are important factors in determining the channel dynamics characteristics. At the initial stage of return stroke, the light radiation loss has a distinct influence on channel temperature, which leads to a transitory drop in temperature forming a bimodal waveform structure. Following the peak current, the channel reaches peak pressure, which leads to a subsequent secondary temperature peak and accelerates the expansion of the channel. Large peak current and the rise time are the indicative parameters of strong discharge and the main factors leading to lightning disaster. This work provides reference data for further research on the radial energy transport of lightning return stroke channel and the formation mechanism of shock waves.

opencc-by-4.0Jun 2023View details →

Dynamic Slicing of WebAssembly Binaries

This is the replication package that accompanies the paper titled: "Dynamic Slicing of WebAssembly Binaries". # Slices dataset ## Generating the dataset The dynamic slices have been generated with [P-ORBS](https://syed-islam.github.io/research/program-analysis/#observation-based-program-slicing-orbs). The steps and scripts to generate the dynamic slices are included in the `slicing-steps/` directory. These steps also describe how to generate the `stats.csv` file that is included in this dataset. The static slices have been generated with [wassail](https://github.com/acieroid/wassail). The scripts to generate the static slices are included in the current directory (`generate-static-slices.sh` which relies on `run_wassail.sh`). These steps generate the file `static-stats.csv` that is included in this dataset. The `original-size.csv` file, included in this dataset, can be generated as follows: ```sh find subjects-wasm-extract-slice -name \*.c.wat -exec c_count {} \; | grep subjects > counts.txt echo 'slice,original fn slice' > evaluation/original-sizes.csv sed -E 's|^(.*) subjects-wasm-extract-slice/[^/]*/([^/]*)/.*$|\2,\1|' counts.txt >> evaluation/original-sizes.csv ``` The numbers in Table 1 of the paper (the list of programs in the dataset along with their sizes) can be generated as follows. For the WebAssembly files, we can count the function size: ``` find subjects-wasm-extract-slice -name \*.c.wat -exec c_count {} \; | grep subjects > counts.txt sed -E 's|^(.*) subjects-wasm-extract-slice/([^/]*)/.*$|\1 \2|' counts.txt | python evaluation/table1-wasm-mean.py ``` or the full program size: ``` find subjects-wasm-extract-slice -name t.wat -exec c_count {} \; | grep subjects > counts.txt sed -E 's|^(.*) subjects-wasm-extract-slice/([^/]*)/.*$|\1 \2|' counts.txt | python evaluation/table1-wasm-mean.py ``` ## Structure of the dataset The dataset is structured as follows:   - `subjects/` contains the instrumented `.c` source code, along with scripts to generate the dynamic slices. The original source code can be obtained by removing the line `printf("\nORBS:%x\n....`.   - `subjects-wasm-extract-slice/` contains the original WebAssembly programs to slice. Each program has two files: `t.wat` is the full binary file, and `name.c.wat` is the binary code of the function containing the slicing criterion.   - `all_slices/` contains the slices. For example, program `adpcm_ah1_254_expr` has the following files     - `adpcm/adpcm_ah1_254_expr/EWS_adpcm.wat`: the EWS slice     - `adpcm/adpcm_ah1_254_expr/SEW_adpcm.wat`: the SEW slice     - `adpcm/adpcm_ah1_254_expr/ESW_adpcm.wat`: the ESW slice     - `adpcm/adpcm_ah1_254_expr/static_adpcm.wat.slice`: the SWS slice     The other files are produced by intermediary steps and can be ignored. They are:     - `adpcm/adpcm_ah1_254_expr/ESW_adpcm.wat.orig`: original (unsliced) binary *file* from which SW and ESW slices are computed     - `adpcm/adpcm_ah1_254_expr/SEW_adpcm.wat.orig`: original (unsliced) binary *function* from which SEW slice  is computed     - `adpcm/adpcm_ah1_254_expr/SW_adpcm.wat`: slice of entire binary file from which ESW slice is extracted     - `adpcm/adpcm_ah1_254_expr/WS_adpcm.wat`: compiled (binary) version of dynamic C slice from which EWS slice is extracted      # Research questions ## RQ1 The script `./RQ1.py` found in the `evaluation/` directory generates:   - Figure 3 (time.pdf)   - The mean, min, max, and stddev of the times   - How many slices are computed below 10, 100, 1000, and 10000 seconds ## RQ2 The script `./RQ2.py` found in the `evaluation/` directory generates:   - Figure 4 (loc.pdf)   - The mean, median, min, max, and stddev of the sizes   - The largest differences between the approaches   - The number of slices larger than the original program    ## RQ3 and RQ4 The process for these research questions is manual and requires comparing slices. It cannot be automated.   We did make heavy use of `diff --side-by-side` in this analysis.

Data from: Remotely sensed environmental measurements detect decoupled processes driving population dynamics at contrasting scales

The increasing availability of satellite imagery has supported a rapid expansion in forward-looking studies seeking to track and predict how climate change will influence wild population dynamics. However, these data can also be used in retrospect to provide additional context for historical data in the absence of contemporaneous environmental measurements. We used 167 Landsat-5 Thematic Mapper (TM) images spanning 13 years to identify environmental drivers of fitness and population size in a well-characterized population of banner-tailed kangaroo rats (Dipodomys spectabilis) in the southwestern United States. We found evidence of two decoupled processes that may be driving population dynamics in opposing directions over distinct time frames. Specifically, increasing mean surface temperature corresponded to increased individual fitness, where fitness is defined as the number of offspring produced by a single individual. This result contrasts with our findings for population size, where increasing surface temperature led to decreased numbers of active mounds. These relationships between surface temperature and (i) individual fitness and (ii) population size would not have been identified in the absence of remotely sensed data, indicating that such information can be used to test existing hypotheses and generate new ecological predictions regarding fitness at multiple spatial scales and degrees of sampling effort. To our knowledge, this study is the first to directly link remotely sensed environmental data to individual fitness in a nearly exhaustively sampled population, opening a new avenue for incorporating remote sensing data into eco-evolutionary studies.

Great Plains grassland methane dynamics

The grassland biome is an important sink for CH4, a major greenhouse gas. There is considerable uncertainty in the grassland CH4 sink capacity due to diverse environmental gradients in which grasslands occur, and many environmental conditions can affect abiotic (e.g., CH4 diffusivity into soils) and biotic (e.g., methanotrophy) factors that determine spatial and temporal CH4 dynamics. We investigated the relative importance of a soil's gas diffusivity vs. net methanotroph activity in 22 field plots in seven sites distributed across the US Great Plains by making ca. bi-weekly measures during the growing seasons over three years. We quantified net methanotroph activity and diffusivity by using an approach combining a gas tracer, chamber headspace measurements, and a mathematical model. At each plot, we also measured environmental characteristics, including water-filled pore space (WFPS), soil temperature and inorganic nitrogen contents, and examined the relative importance of these for controlling diffusivity and net methanotroph activity. At most of the plots across the seven sites, CH4 uptake rates were consistently greatest when WFPS was intermediate at the plot level. Our results show that variation in net methanotroph activity was more important than diffusivity in explaining temporal variations in net CH4 uptake, but the two factors were equally important for driving spatial variation across the seven sites. Water-filled pore space was a significant predictor for diffusivity only in plots with sandy soils. Water-filled pore space was the most important control on net methanotroph activity, with net methanotroph activity showing a parabolic response to WFPS (concave down), and the shape of this response differed significantly among sites. Moreover, we found that the WFPS level at peak net methanotroph activity was strongly correlated with mean annual precipitation of the site. These results suggest that local precipitation regime determines unique sensitivity of CH4 uptake rates to soil moisture. Our findings indicate that grassland CH4 uptake may be predicted using local soil water conditions. More variable soil moisture, potentially induced through predicted future extremes of rainfall and drought, could reduce grassland CH4 sink capacity in the future.

opencc-by-4.0May 2023View details →

Dynamic calcium-mediated stress response and recovery signatures in the fungal pathogen, Candida albicans - Supplementary Movies

Supplementary Data: movie files: Movie S1: BWP17-GCaMP 1 mM – 200 mM Ca2+ Movie S2: WT-GCaMP 1M NaCl Movie S3: BWP17-GCaMP 0.6 M Ca2+ Movie S4: WT-GCaMP 0.05% SDS Movie S5: WT-GCaMP 5 mM H2O2 Movie S6: Empty-vector 5 mM H2O2 Movie S7: cap1∆-GCaMP 5 mM H2O2 Movie S8: hog1∆-GCaMP 5 mM H2O2 Movie S9: cnb1∆-GCaMP 5 mM H2O2 Movie S10: crz1∆-GCaMP 5 mM H2O2 Movie S11: cch1∆-GCaMP 5 mM H2O2 Movie S12: yvc1∆-GCaMP 5 mM H2O2

Excited state observation of active K-Ras reveals differential structural dynamics of wild-type versus oncogenic G12D and G12C mutants

Despite the prominent role of the K-Ras protein in many different types of human cancer, major gaps in atomic-level information severely limit our understanding of K-Ras function in health and disease. Here, we report the quantitative backbone structural dynamics of K-Ras by solution NMR spectroscopy of the active state of wild-type K-Ras·GTP and two of its oncogenic P-loop mutants, G12D and G12C, using a novel nanoparticle-assisted spin relaxation method, relaxation dispersion and chemical exchange saturation transfer experiments covering the entire range of timescales from picosecond to milliseconds. Our combined experiments allow the detection and analysis of the functionally critical Switch I and Switch II regions that have previously remained largely unobservable by X-ray crystallography and NMR spectroscopy. Our data reveal cooperative transitions of K-Ras·GTP to a highly dynamic excited state that closely resembles the partially disordered K-Ras·GDP state. These results advance our understanding of differential GTPase activities and signaling properties of the WT versus mutants and may thus guide new strategies for the development of therapeutics.

Dataset from J. Am. Chem. Soc. paper: Off-Stoichiometric Restructuring and Sliding Dynamics of Hexagonal Boron Nitride Edges in Conditions of Oxidative Dehydrogenation of Propane

Dataset of the article "Off-Stoichiometric Restructuring and Sliding Dynamics of Hexagonal Boron Nitride Edges in Conditions of Oxidative Dehydrogenation of Propane" accepted in J. Am. Chem. Soc. - armchair.db: The ASE database of all unique surface states from the grand canonical genetic algorithm (GCGA) searches of the restructured armchair edge of h-BN. - zigzag.db: The ASE database of all unique surface states from the GCGA searches of the restructured zigzag edge of h-BN. Other key info such as DFT-calculated energies and magnetic moments are included in the metadata of each entry in the ASE databases. GCGA searches are performed using the workflow in the GOCIA package (https://github.com/zishengz/gocia)

Supplementary material/Organic carbon dynamics in clay soils: impact of management practices on microorganism structure and abundance under semi-arid conditions

Proper management of soil organic matter in arid and semi-arid regions improves organic carbon storage in the soil, helps in compact soil degradation, and mitigates climate change impacts, and preserves ecosystem functionality and sustainability food security. This study aims to provide a better insight into the biogeochemical processes that drive the organic carbon dynamics of saline clay soil in a semi-arid climate. The study is not intended to be exhaustive but contributes to analyzing the relationship between bacterial microflora, physicochemical properties, and organic carbon dynamics as a function of different soil management modes. The monitoring was carried out on three different plots located at the National Institute of Agronomic Research of Algeria. A physicochemical characterization of the soils was performed. A metagenomic study was also conducted to identify bacterial biodiversity using PCR-amplified DNA sequencing. The study results show that the control plot has the highest average organic carbon stock value at 47 Mg ha-1. This was followed by the amended plot and the conventional plot, respectively, with 43 Mg ha-1 and 38 Mg ha-1. In the context of this study, organic carbon dynamics would appear to depend on the interaction of several biotic and abiotic factors. Soil management methods would impact the density and diversity of bacterial microflora. This, in turn, affects the soil's physicochemical properties and, more specifically, organic carbon dynamics and storage.

Data of "Dissipative quantum many-body dynamics in (1+1)D quantum cellular automata and quantum neural networks"

The uploaded files contain the data of the simulations presented in the figures in <a href="https://doi.org/10.48550/arXiv.2304.11209">https://doi.org/10.48550/arXiv.2304.11209</a>.

opencc-zeroAug 2023View details →

Temporal dynamics of soil fungi in a pyrodiverse dry-sclerophyll forest

Fire is a major evolutionary and ecological driver that shapes biodiversity in forests. While above-ground community responses to fire have been well-documented, those below-ground are much less understood. However, below-ground communities, including fungi, play key roles in forests and facilitate the recovery of other organisms after fire. Here, we used internal transcribed spacer (ITS) meta-barcoding data from forests with three different times since fire [short (3 years), medium (13–19 years) and long (>26 years)] to characterize the temporal responses of soil fungal communities across functional groups, ectomycorrhizal exploration strategies and inter-guild associations. Our findings indicate that fire effects on fungal communities are strongest in the short to medium term, with clear distinctions between communities in forests with a short time (3 years) since fire, a medium time (13–19 years) and a long time (>26 years) since fire. Ectomycorrhizal fungi were disproportionately impacted by fire relative to saprotrophs, but the direction of the response varied depending on morphological structures and exploration strategies. For instance, short-distance ectomycorrhizal fungi increased with recent fire, while medium-distance (fringe) ectomycorrhizal fungi decreased. Further, we detected strong, negative inter-guild associations between ectomycorrhizal and saprotrophic fungi but only at medium and long times since fire. Given the functional significance of fungi, the temporal changes in fungal composition, inter-guild associations and functional groups after fire demonstrated in our study may have functional implications that require adaptive management to curtail.

Supporting data for:"An accurate and efficient SAXS/SANS implementation including solvation layer effects suitable for restrained Molecular Dynamics simulations."

PLUMED_NEST_REPO.zip contains the plumed.dat file and the template PDB used to perform the metainference MD simulations of Gelsolin and UP1-RNA, with and without the Solvation Layer Contribution. TRAJECTORIES.zip contains the Gelsolin and UP1-RNA trajectories and additional data generated with GROMACS. In details: -Gelsolin. Production Molecular Dynamics Parameter file (production.mdp), a topology file (topol.top), and 3 folders: TPRs (with 10 TPR files -one for each replica-), TRJ_SLC_OFF (with data from simulations without Solvation Layer Contribution), and TRJ_SLC_ON (with data from simulations with Solvation Layer Contribution). The last two contain an index file, a trajectory obtained from the concatenation of the 10 replicas (concat.xtc), and a template PDB file. -UP1-RNA. TPR file (md.tpr) and 2 folders: TRJ_SLC_OFF (with data from simulations without solvent correction), and TRJ_SLC_ON (with data from simulations with solvent correction). Each folder contains an index file, a template PDB file and a trajectory file (trj.xtc)

Tidal Effects on Dynamics and Freshwater Transport of a Medium-scale River Plume with Multiple Outlets

Data for submitted paper "Tidal Effects on Dynamics and Freshwater Transport of a Medium-scale River Plume with Multiple Outlets"

Discovery of enhanced lattice dynamics in a single-layered hybrid perovskite

This repository presents the raw data for the paper "Discovery of enhanced lattice dynamics in a single-layered hybrid perovskite", published as an open-access article in Science Advances at <a href="https://www.science.org/doi/10.1126/sciadv.adg4417">https://www.science.org/doi/10.1126/sciadv.adg4417</a>. Data presented in the Supplementary Materials will be provided upon request. For such requests or general questions regarding the paper, please contact Zhuquan Zhang (<a href="mailto:zhuquan@mit.edu">zhuquan@mit.edu</a>), Keith Nelson (<a href="mailto:kanelson@mit.edu">kanelson@mit.edu</a>), or Edoardo Baldini (<a href="mailto:edoardo.baldini@austin.utexas.edu">edoardo.baldini@austin.utexas.edu</a>).

opencc-by-4.0May 2022View details →

Dynamic stability of synthetic power grid models

This repository contains three datasets of synthetic power grids and their dynamic stability. 1. 10,000 grids of size 20 (ds20) stored in dataset020.zip 2. 10,000 grids of size 100 (ds100) stored in dataset100.zip 3. 1 Texan power grid model with 1,910 nodes (texas) stored intexas.zip   There are three tasks SNBS (regression) and the identification of troublemakers using regression and thresholding based on the maximum frequency deviation or classification based on binary targets.

opencc-zeroAug 2023View details →

Reproductive output and telomere dynamics following calcium supplementation in wild Tree Swallows (Tachycineta bicolor)

This data was the result of an experiment investigating whether biologically relevant differences in reproductive investment influence fitness in a wild bird species. We employed calcium supplementation to experimentally modify reproductive output in Tree Swallow mothers and offspring and we used telomere dynamics during the breeding season as a proxy for fitness. To confirm that calcium supplementation positively impacts reproductive parameters at our study site, we initiated a 4-year trial of calcium supplementation with our Tree Swallow study population. In the following two breeding seasons, we used calcium supplementation to experimentally alter reproductive output and measured telomere length in mothers immediately before egg-laying and shortly before fledging to determine the direct relationship between reproductive investment and telomere shortening in this species. Our study includes one hundred eighty-eight nests initiated and monitored over six breeding seasons.

Raw data for model implementation examples in paper "Incorporating Detected/Undetected Cooperative and Uncooperative Individuals, and Dynamic Transmission Probabilities in Epidemiological Models"

This dataset contains the historical daily new case numbers referenced in the paper titled "Incorporating Detected/Undetected Cooperative and Uncooperative Individuals, and Dynamic Transmission Probabilities in Epidemiological Models." These numbers were utilized to estimate the basic reproduction number R0 and the aggregated epidemic control measure Kr(t) parameters within the model, as shown in the example implementation section of the paper.

Global Datasets of Hourly Carbon and Water Fluxes Simulated Using a Satellite-based Process Model with Dynamic Parameterizations

This new global hourly dataset serves as a 'handshake' among process-based models, remote sensing, and the eddy covariance flux network, providing a reliable long-term estimate of global gross primary productivity (GPP) and evapotranspiration (ET) with diurnal patterns and facilitating studies related to ecosystem functional properties, global carbon, and water cycles. The dataset include the GPP and ET of sunlit and shaded leaf components at an hourly timescale and a spatial resolution of 0.25-degree from 2001 to 2020.

Dynamics of Shoreline Change in the Coastal Region of Rupat Island, Riau, Indonesia

shoreline changes in coastal of Rupat Island

Date set for the manuscript: Exploring the temporal dynamics of methane ebullition in a subtropical freshwater reservoir

The dataset supports the findings of the manuscript entitled ‘Exploring the Temporal Dynamics of Methane Ebullition in a Subtropical Freshwater Reservoir’. The results of the manuscript are based on continuous in-situ measurements conducted at Passaúna Reservoir, located in the southern part of Brazil (South America). The monitoring was carried out from 2017 to 2020, during which a comprehensive set of environmental variables was obtained from various studies. The primary objective of the manuscript was to comprehend the temporal dynamics of ebullition flux in the reservoir. Therefore, time series data of ebullition and relevant environmental variables were analyzed across different time scales, ranging from minutes to daily resolutions. Statistical and data driven models were tested to predict ebullition at varying time scales, considering the influence of environmental variables. The findings are discussed in the manuscript. Here, xlsx files and Matlab scripts are provided. The xlsx files contain time series data for environmental variables ('Environmental_Variables_TimeSeries') and ebullition flux ('Ebullition_Flux_TimeSeries'). Separate sheets were utilized for different time intervals, namely 5 minutes (dt=5min), 10 minutes (dt=10min), 1 hour (dt=1hr), and 1 day (dt=1d). Explanations and units are provided within the column labels, while 'NaN' denotes missing data. Matlab scripts for all the empirical models that were tested, as outlined in the manuscript's supporting information (Tables S1 and S2), have been made available (detailed in the following table). These scripts were developed using MatLab R2023a. <table> <tbody> <tr> <td> File (.m) </td> <td> Description </td> </tr> <tr> <td> Main scripts </td> </tr> <tr> <td> TableS1_Empirical_Models_Literature </td> <td> Empirical models from the literature tested. (Table S1 in the manuscript) </td> </tr> <tr> <td> TableS2_FirstPart_Reffited_Models </td> <td> Empirical models from the literature refitted. (Table S2 in the manuscript) </td> </tr> <tr> <td> TableS2_SecondPart_New_Models </td> <td> New empirical models implemented. (Table S2 in the manuscript) </td> </tr> <tr> <td> TableS2_SecondPart_New_Models_GAM_Timescales </td> <td> Generalized additive models (GAM) applied to predict ebullition at different timescales. (Table S2 in the manuscript). </td> </tr> <tr> <td> PredictedR2_GAM_models </td> <td> Calculate the predicted R-squared for GAM. </td> </tr> <tr> <td> Functions (need for the main scripts) </td> </tr> <tr> <td> load_TimeSeries </td> <td> Import time series of environmental variables from excel sheets into MatLab. </td> </tr> <tr> <td> load_EbullitionTS </td> <td> Import time series of ebullition from excel sheets into MatLab. </td> </tr> <tr> <td> units_description </td> <td> Description containing units of the variables. </td> </tr> <tr> <td> Bin_xdata </td> <td> Creates data binning of X and Y based on X data. </td> </tr> <tr> <td> RelativeError </td> <td> Calculate the relative error of accumulated flux between measured and simulated. </td> </tr> <tr> <td> ANN5Neurons_Retrained_Deshmukh2014 </td> <td> Trained Artificial Neural Network based on the ANN proposed by Deshmukh et al. (2014). </td> </tr> <tr> <td> ANN_Passauna_20Neurons </td> <td> Trained Artificial Neural Network with the addition of more environmental variables. </td> </tr> </tbody> </table>   Financial support The field measurements were financed by the German Federal Ministry of Education and Research (BMBF, Grant 02WGR1431A), in the framework of the research project MuDak-WRM (https://www.mudak-wrm.kit.edu). This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. Tobias Bleninger received productivity stipend from the National Council for Scientific and Technological Development (CNPq, grant no. 312211/2020-1, call no. 09/2020). Michael Männich received productivity stipend from the National Council for Scientific and Technological Development (CNPq, grant no. 308744/2021-7, call no. 04/2021). Andreas Lorke received financial support from the German Research Foundation (DFG, grant number LO1150/16-1).