Find research datasets worth reusing

opencc-by-4.0Mar 2021View details →

Supplementary Data for The salmon louse genome: copepod features and parasitic adaptations.

This dataset contains supporting data for the manuscript: Skern-Mauritzen et al. The salmon louse genome: copepod features and parasitic adaptations. Copepods encompass a range of ecological roles from parasites to phytoplankton grazers linking primary producers to higher trophic levels. Despite these important roles, copepod genome assemblies are scarce. Lepeophtheirus salmonis is an economically and ecologically important ectoparasitic copepod found on salmonid fish. We present the 695.4 Mbp L. salmonis genome assembly containing ≈60% repetitive regions and 13081 annotated protein-coding genes. The genome comprises 14 autosomes and a ZZ-ZW sex chromosome system. Assembly assessment identified 92.4% of the expected arthropod genes. Transcriptomics supported annotation and indicated a marked shift in gene expression after host attachment, including down-regulation of genes related to circadian rhythm coinciding with abandoning diurnal migration. The genome shows evolutionary signatures including loss of genes needed for peroxisome biogenesis, presence of numerous FNII domains, and an incomplete heme homeostasis pathway suggesting heme proteins to be obtained from the host. Despite large capacity to develop resistance against chemical treatments L. salmonis exhibits low numbers of many genes involved in detoxification. <ul> <li>Supplementary data is explained in detail and referenced in the manuscript and the file Supplementary Material 30062021 REVISED.pdf</li> <li>BUSCO-V5-results-species-comparison.tar.gz contains the raw output and results of all BUSCO  V 5.0.0 runs on the genomes in Table 1 of the manuscript and Supplementary_Table_GenomeStats.xlsx </li> <li>GCA_000181255.2_ASM18125v2_genomic.fna.RepMasker.o ...,  GCA_001005205.1_lsal_atl_canada_female_v1_genomic. ..., GCA_001005235.1_lsal_atl_canada_male_v1_genomic.fn ... and  TableS4-1-LSalAtl2s.fasta.RepMasker.out.gz contain original output from RepeatMasker</li> <li>Lsalmonis-RepeatModeler-families.fa.gz and Lsalmonis-RepeatModeler-families.stk.gz contain all repeat families as original output from RepeatModeler</li> </ul>

opencc-by-4.0Jul 2021View details →

Supplementary data: "Future operation of hydropower in Europe under high renewable penetration and climate change"

This dataset contains modelled inflow time series described in the paper "Future operation of hydropower in Europe under high renewable penetration and climate change". The inflow is derived from ten different combinations of five General Circulation Models and two Regional Climate Models at the beginning of the century ("Hydro_inflow_BOC_(...).csv"), 1991 - 2020, and at the end of the century ("Hydro_inflow_EOC_(...).csv"), 2071 - 2100, under three CO2-emissions scenarios (RCP2.6, RCP4.5, and RCP8.5). The ensemble mean for each emissions scenario is presented as well. The historical data that is not confidential is given as well. See "data_sources" for sources.

dryad40/100

Supplementary data for: Transposon mutagenesis identifies cooperating genetic drivers during keratinocyte transformation and cutaneous squamous cell carcinoma progression

Supplementary Note 1: <ul> <li>S1 Text: Oncogenomic comparisons between SB candidate Trunk driver genes and their direct orthologs in human Cancer Gene Census; Pyrosequencing analysis of SB-driven keratinocyte cancer models; References.</li> </ul> Supplementary Figures 1-11: <ul> <li>S1 Fig: Overview of genetic crosses to generate SB|Trp53|Onc3 mouse model.</li> <li>S2 Fig: SB insertion patterns in activated and inactivated drivers.</li> <li>S3 Fig: Evaluating the reproducibility of SBCapSeq results from bulk cuSCC and normal skin specimens.</li> <li>S4 Fig. Hierarchical two-dimensional clustering of recurrent events in cuKA and cuSCC.</li> <li>S5 Fig. Curated biological pathways and processes enriched within SB-induced cuSCC.</li> <li>S7 Fig: ZMIZ1 metagene within the TCGA Head & Neck Squamous Cell Carcinoma (hnSCC) RNA-seq dataset.</li> <li>S8 Fig: Clonally selected SB insertions affect trunk driver proto-oncogene expression in SB-cuSCC genomes.</li> <li>S9 Fig: Clonally selected SB insertions affect trunk driver genes by inactivating expression in SB-cuSCC genomes.</li> <li>S10 Fig: CREBBP knockdown does not alter proliferation rate in cuSCC cell lines.</li> <li>S11 Fig: Gross photographs of cuSCC xenograft masses collected at necropsy showing robust TurboGFP expression.</li> <li>S12 Fig: SB T2/Onc3 TG.12740 allele donor position mapping and exclusion for SB Driver Analysis.</li> </ul> Supplementary Tables 1-20: <ul> <li>S1 Table: Tumor incidence and subgroup classifications by cohort.</li> <li>S2 Table: Specimen metafile data for projects sequenced using SBCapSeq protocol with Ion Torrent Proton sequencer.</li> <li>S3 Table: Discovery and progression SB Driver Analysis for cuSCC60_SBC.</li> <li>S4 Table: Trunk SB Driver Analysis for cuSCC60_SBC.</li> <li>S5 Table: Discovery and progression SB Driver Analysis for cuKA11_SBC.</li> <li>S6 Table: Trunk SB Driver Analysis for cuKA11_SBC.</li> <li>S7 Table: Discovery and progression SB Driver Analysis for cuSK32_SBC.</li> <li>S8 Table: SBCapSeq read depth and analysis for 4 cuSCC genomes selected for multi-region resequencing because they had intermixing of cuSCC and cuKA histologies.</li> <li>S9 Table: Enrichr gene set pathway enrichment analysis of cuSCC drivers.</li> <li>S10 Table: Summary of 7 cuSCC transcriptomes selected for whole transcriptome RNAseq analysis.</li> <li>S11 Table: BED file of SBfusion insertions in 7 cuSCC genomes by whole transcriptome RNAseq analysis.</li> <li>S12 Table: Venn diagram for overlap of genes with SBfusion reads detected by whole transcriptome RNAseq analysis and cuSCC60_SBC discovery driver.</li> <li>S13 Table: Venn diagram for overlap of genes with SBfusion reads detected by whole transcriptome RNAseq analysis and all cuSCC drivers.</li> <li>S14 Table: Transcripts per million (TPM) normalized whole transcriptome RNAseq values per gene from RNA isolated from cuSCC genomes with and without Zmiz1 insertions.</li> <li>S15 Table: Fragments Per Kilobase of Transcripts per Million (FPKM) normalized whole transcriptome RNAseq values per gene transcript from RNA isolated from cuSCC genomes with and without Zmiz1 insertions.</li> <li>S16 Table: Normalized microarray values per gene from RNA isolated from cuSCC genomes with and without Zmiz1 insertions.</li> <li>S17 Table: Normalized microarray values per probe from RNA isolated from cuSCC genomes with and without Zmiz1 insertions.</li> <li>S18 Table: All 289 genes with differential expression analysis from microarray data from RNA isolated from cuSCC genomes with and without Zmiz1 insertions with P<0.0001 and q<0.05.</li> <li>S19 Table: Lentiviral vectors containing shRNAs used in this study.</li> <li>S20 Table: TaqMan probes used in this study.</li> </ul> Supplementary Datasets 1-5: <ul> <li>S1 Data: BED file of SB insertions for cuSCC60_SBC.</li> <li>S2 Data: BED file of SB insertions for cuKA11_SBC.</li> <li>S3 Data: BED file of SB insertions for cuSK32_SBC</li> <li>S4 Data: BED file of SB insertions for 4 cuSCC genomes selected for multi-region resequencing because they had intermixing of cuSCC and cuKA histologies.</li> <li>S5 Data: Numerical data for graphs pertaining to Figure Panels Fig1A; Fig5A–E; Fig6A–B,D; Fig7C–G; Fig8A–B,D–F; Fig9A–I in the paper on the publicly availble PLOS Genetics Web site.</li> </ul>

opencc-zeroAug 2021View details →

Atmosphéries and the poetics of the in situ: the role and impact of sensors in data-to-sound transposition installations - Supplementary audio material

This audio file wishes to give an insight into NXI Gestatio Design Lab's Atmosphéries research program, and to accompany the publication "Atmosphéries and the poetics of the in situ: the role and impact of sensors in data-to-sound transposition installations". The file consists in a 7-minutes recording of the Meridian Probe, the last instrument designed within the Atmosphéries program, which allows to generate sound from on-site atmospheric data. The recorded extract then acts as a sonic representation of the atmospheric conditions found at the place of exhibition, at the time of recording - in this case, gardens of the Bussy-Rabutin's Castle (France), respectively July 31st, 2021, 17h17. For further information about the Meridian Probe's design and functioning, we invite you to read the aforementioned publication.

Supplementary data and simulation code - "ADCY10 is a key regulator of cell cycle control"

Experimental FACS data of cell cycle analysis: The folder raw_data_FACS contains the FACS data for different concentrations of bicarbonate (hco3-_rawdata_all2.csv) and for the KH7 experiments (kh7_rawdata_all.csv). The folder summarized_data_input4analysis contains the csv-files that where used for the Bayesian analysis of cell cycle control. Details are given in the headings of the files. We also set up a webpage, where simulations of the suggested mathematical model of the cell cycle can be performed: <a href="https://cellcycle-simulation2.herokuapp.com/">https://cellcycle-simulation2.herokuapp.com/</a> The results may be used for prediction or experimental design.

A Metamorphic Origin for Europa's Ocean - Supplementary Data Files

A Metamorphic Origin for Europa's Ocean - Supplementary Data Files M. Melwani Daswani, S. D. Vance, M. J. Mayne, and C. R. Glein Jet Propulsion Laboratory, California Institute of Technology daswani@jpl.nasa.gov 2021-08-18 This folder contains the Supplementary Data files consisting of input data and output data products. The paper is accepted in Geophysical Research Letters. A preprint may be found here: <a href="https://doi.org/10.1002/essoar.10507048.1">https://doi.org/10.1002/essoar.10507048.1</a>, but please see the article on Geophysical Research Letters for the properly formatted, peer-reviewed, revised version. Contents: AccretR Europa MC-Scale composition output.xlsx Contains the composition of Europa after accretion, obtained by running the AccretR program. AccretR can be found on Zenodo: https://doi.org/10.5281/zenodo.3827540 or GitHub (most up to date): https://github.com/mmelwani/AccretR Fe-S core composition models Contains the Perple_X input and output files for constraining the composition of the Fe+-S core. Thermodynamic data used was from Saxena and Eriksson (2015), also included as a Perple_X thermodynamic file. Rcrust prograde metamorphism models Contains the input and output files for the Rcrust models, which are the metamorphic prograde path thermodynamic. Rcrust is required to run these models (http://www.sun.ac.za/english/faculty/science/earthsciences/rcrust), as well as the "meemum" program from Perple_X (https://www.perplex.ethz.ch/). The Perple_X version used was "6.8.7", and was compiled from source to enable 12 thermodynamic components (i.e. major elements). CHIM-XPT ocean column composition models Contains the CHIM-XPT input and output files, which model the ocean composition from seafloor to surface, including precipitated minerals, aqueous solutes and saturated gases. Inputs for these models were the fluids extracted from the Rcrust prograde metamorphic models. Density and volume of clathrates.xlsx Shows the calculations carried out to find the temperature, density and volume of CO2 clathrates in Europa's ocean.

Supplementary data for "Deep learning for industrial processes: Forecasting amine emissions from a carbon capture plant"

A preliminary analysis of the data already has been discussed in <a href="https://dx.doi.org/10.2139/ssrn.3812299">10.2139/ssrn.3812299</a>. Raw data Raw measurement data is in the Excel files `day*_raw.xlsx`. Model Covariate and label scaler objects are serialized in joblib format in the following files: <ul> <li>20210812_y_transformer_co2_ammonia_reduced_feature_set</li> <li>20210812_y_transformer__reduced_feature_set</li> <li>20210812_x_scaler_reduced_feature_set</li> </ul> Checkpoints of the models are in the `*.pth.tar` files.  An example for loading the models is: <pre><code class="language-python">from pyprocessta.model.tcn import TCNModelDropout model_cov = TCNModelDropout( input_chunk_length=8, output_chunk_length=1, num_layers=5, num_filters=16, kernel_size=6, dropout=0.3, weight_norm=True, batch_size=32, n_epochs=100, log_tensorboard=True, optimizer_kwargs={"lr": 2e-4}, ) model_cov.load_from_checkpoint('20210814_2amp_pip_model_reduced_feature_set_darts')</code></pre> which assumes that the checkpoints are placed as `model_best.pth.tar` in a folder called `20210812_2amp_pip_model_reduced_feature_set_darts`.

Diversity in citations to a single study: Supplementary data set for citation context network analysis

Introduction This document describes the data set used for all analyses in 'Diversity in citations to a single study: A citation context network analysis of how evidence from a prospective cohort study was cited' accepted for publication in Quantitative Science Studies [1]. Data Collection The data collection procedure has been fully described [1]. Concisely, the data set contains bibliometric data collected from Web of Science Core Collection via the University of Edinburgh’s Library subscription concerning all papers that cited a cohort study, Paul et al. [2], in the period <1985. This includes a full list of citing papers, and the citations between these papers. Additionally, it includes textual passages (citation contexts) from 343 citing papers, which were manually recovered from the full-text documents accessible via the University of Edinburgh’s Library subscription. These data have been cleaned, converted into network readable datasets, and are coded into particular classifications reflecting content, which are described fully in the supplied code book and within the manuscript [1].  Data description All relevant data can be found in the attached file 'Supplementary_material_Leng_QSS_2021.xlsx', which contains the following five workbooks: <ul> <li>“Overview” includes a list of the content of the workbooks.</li> <li>“Code Book” contains the coding rules and definitions used for the classification of findings and paper titles.</li> <li>“Node attribute list” includes a workbook containing all node attributes for the citation network, which includes Paul et al. [2] and its citing papers as of 1984. Highlighted in yellow at the bottom of this workbook is two papers that were discarded due to duplication - remove these if analysing this dataset in a network analysis. The columns refer to:</li> </ul> <ol> <li>Id, the node identifier</li> <li>Label, the formal citation of the paper to which data within this row corresponds. Citation is in the following format: last name of first author, year of publication, journal of publication, volume number, start page, and DOI (if available).  </li> <li>Title, the paper title for the paper in question.</li> <li>Publication_year, the year of publication.</li> <li>Document_type, the document type (e.g. review, article)</li> <li>WoS_ID, the paper’s unique Web of Science accession number.</li> <li>Citation_context, a column specifying whether citation context data is available from that paper</li> <li>Explanans, the title explanans terms for that paper;</li> <li>Explanandum, the explanandum terms for that paper.</li> <li>Combined_Title_Classification, the combined terms used for fig 2 of the published manuscript.</li> <li>Serum_cholesterol_(SC), a column identifying papers that cited the serum cholesterol findings.</li> <li>Blood_Pressure_(BP), a column identifying papers that cited the blood pressure findings.</li> <li>Coffee_(C), a column identifying papers that cited the coffee findings.</li> <li>Diet_(D), a column identifying papers that cited the dietary findings.</li> <li>Smoking_(S), a column identifying papers that cited the smoking findings.</li> <li>Alcohol_(A), a column identifying papers that cited the alcohol findings.</li> <li>Physical_Activity_(PA), a column identifying papers that cited the physical activity findings.</li> <li>Body_Fatness (BF), a column identifying papers that cited the body fatness findings.</li> <li>Indegree, the number of within network citations to that paper, calculated for the network shown in Fig 4 of the manuscript.</li> <li>Outdegree, the number of within network references of that paper as calculated for the network in Fig 4.</li> <li>Main_component, a column specifying whether a node is contained in the largest weakly connect component as shown in Fig 4 of the manuscript.</li> <li>Cluster, provides the cluster membership number as discussed within the manuscript (Fig 5).</li> </ol> <ul> <li>“Edge list” includes a workbook including the edges for the network. The columns refer to:</li> </ul> <ol> <li>Source, contains the node identifier of the citing paper.</li> <li>Target, contains the node identifier of the cited paper.</li> </ol> <ul> <li>“Citation context classification” includes a workbook containing the WoS accession number for the paper analysed, and any finding category discussed in that paper established via context analysis (see the code book for definitions). The columns refer to:</li> </ul> <ol> <li>Id, the node identifier</li> <li>Finding_Class, the findings discussed from Paul et al. within the body of the citing paper.  </li> </ol> <ul> <li> “Citation context data” includes a workbook containing the WoS accession number for papers in which citation context data was available, the citation context passages, the reference number or format of Paul et al. within the citing paper, and the finding categories discussed in those contexts (see code book for definitions). The columns refer to:</li> </ul> <ol> <li>Id, the node identifier</li> <li>Citation_context, the passage copied from the full text of the citing paper containing discussion of the findings of Paul et al.</li> <li>Reference_in_citing_article, the reference number or format of Paul et al. within the citing paper.</li> <li>Finding_class, the findings discussed from Paul et al. within the body of the citing paper. </li> </ol> Software recommended for analysis For the analyses performed within the manuscript, Gephi version 0.9.2 was used [3], and both the edge and node lists are in a format that is easily read into this software. The Sci2 tool was used to parse data initially [4]. Notes <ol> <li>Leng, R. I. (Forthcoming). Diversity in citations to a single study: A citation context network analysis of how evidence from a prospective cohort study was cited. Quantitative Science Studies.</li> <li>Paul, O., Lepper, M. H., Phelan, W. H., Dupertuis, G. W., Macmillan, A., McKean, H., et al. (1963). A longitudinal study of coronary heart disease. Circulation, 28, 20-31. <a href="https://doi.org/10.1161/01.cir.28.1.20">https://doi.org/10.1161/01.cir.28.1.20</a>.</li> <li>Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media.</li> <li>Sci2 Team. (2009). Science of Science (Sci2) Tool. Indiana University and SciTech Strategies. Stable URL: <a href="https://sci2.cns.iu.edu">https://sci2.cns.iu.edu</a></li> </ol>

opencc-by-4.0Sep 2021View details →

Supplementary data for the manuscript "Comparison of computational and experimental saturation vapor pressures of α-pinene + O3 oxidation products"

COSMO-files of potential ozonolysis products of α-pinene for the manuscript: Hyttinen, N., Pullinen, I., Nissinen, A., Schobesberger, S., Virtanen, A., and Yli-Juuti, T.: Comparison of computational and experimental saturation vapor pressures of α-pinene + O3 oxidation products, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2021-775, in review, 2021.

opencc-by-4.0Sep 2021View details →

Supplementary Data for "The state and fate of lake ice thickness in the Northern Hemisphere"

This dataset consists of four files including (1) Lake ice thickness of 16 large lakes measured by satellite altimeters for 1992-2019 (Altimetric LIT for 16 large lakes.xlsx); (2) Daily lake ice thickness and lake surface snow depth of 1,313 lakes with an area > 50 km2 in the Northern Hemisphere modeled by a one-dimensional remote sensing lake ice model for 2003-2018 (in NetCDF format); (3) Future lake ice thickness and surface snow depth for 2071-2099 modeled by the lake ice model with a modified ice growth module (table S1.xlsx); (4) A lookup table containing lake IDs, names, locations, and areas. This daily lake ice and snow thickness dataset could provide a benchmark for the estimation of global lake ice and snow mass, thereby improving our understanding of the ecological and economical significance of freshwater ice as well as its response to climate change.

opencc-by-4.0Dec 2020View details →

"Decision support systems halve fungicide use compared to calendar-based strategies without increasing disease risk". Supplementary Data 1.

"Decision support systems halve fungicide  compared to calendar-based strategies without increasing disease risk". Supplementary Data 1.https://doi.org/10.1038/s43247-021-00291-8 | www.nature.com/commsenv Dataset includes the results of 80 independent experiments reported in 22 articles and it  has a dimension of 329 rows x 42 columns. Further information in "Description Supplementary Data 1.pdf" file.  This dataset was assembled including also the data from the publication Agronomy 2020, 10(4), 560; https://doi.org/10.3390/agronomy10040560.

opencc-by-4.0Oct 2021View details →

Supplementary Data for "Convergent evolution as an indicator for selection during acute HIV-1 infection"

Supplementary Data 1. Position of all identified mutations in the env gene. This file contains detailed information about the identity of the observed mutations. It provides the position in the HXB2 genome, the amino acid change they cause in the different genetic backgrounds and the number of HIV-1 subtypes (out of a total of 170) the mutations occurs in. Supplementary Data 2. Position of all identified mutations in the rev exon part of the env gene. Same as Supplementary Data 1, except that only mutations and amino acid substitutions in the rev exon 2 are shown. Supplementary Program. With this program one can redo the analyses and simulations of the manuscript.

opencc-by-4.0Dec 2018View details →

Use and sharing of raw data in the Journal Citation Reports' Emergency Medicine Category: Metrics and Journals including supplementary material classification sorted by quartile of the JCR emergency medicine category.

Raw data belonged to the study of use and sharing of raw research data in the Journal Citation Reports' Emergency Medicine Category.

opencc-by-4.0Sep 2022View details →

Data, code and supplementary material for "A data integration framework for spatial interpolation of temperature observations using climate model data"

Each zipped file contains code and data to reproduce the results in the paper and supplementary material. The Cyprus folder contains also the files to run the model, as well as the associated results. The Morocco folder only contains the results and the code used to manipulate it.

Supplementary data for 'Melting and refreezing in an ice shelf basal channel at the grounding line of the Kamb Ice Stream, West Antarctica' Whiteford et al 2022

These data are described in detail by 'Melting and refreezing in an ice shelf basal channel at the grounding line of the Kamb Ice Stream, West Antarctica' Whiteford et al 2022. 'ApRES dataset.zip' contains raw ApRES data and processed results from a spatial survey of basal mass balance, detailed in Sections 2.2.4 and 3.2.2 of the above paper. README.md describes the file contents. 'radar_dataset.tar.gz' contains raw data from a low frequency radar survey profiling ice thickness, detailed in Section 2.2.1 of the above paper.   'channel_base_surface_map' contains six files. *_Ice_thickness is raster data of an estimation of ice thickness in the area. This is produced through processing radar data 'radar_dataset.tar.gz' and interpolation, described in Sections 2.2.2 and 3.1.2. *_REMA_surf is raster data of the ice surface, sampled a REMA strip from 9 November 2016 (Howat 2019).  Ice_base is raster data  calculated by subtracting the ice thickness from this surface. *_x_grid and *_y_grid are the x and y UTM coordinates accompanying the raster data, in Antarctic Polar Stereographic projection. *_extent is the x and y extent of the area covered by raster data. Reference: Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J., & Morin, P. (2019). The Reference Elevation Model of Antarctica. Cryosphere, 13 (2)

Supplementary Data for AGouTI - flexible Annotation of Genomic and Transcriptomic Intervals

The data allows to replicate the use-case scenario described in the manuscript "AGouTI - flexible Annotation of Genomic and Transcriptomic Intervals" by Jan G. Kosiński and Marek Żywicki.

opencc-by-nc-4.0Mar 2022View details →

Supplementary data files for Manzano-Marín et. al. 2022 "Co-obligate symbioses have repeatedly evolved across aphids, but partner identity and nutritional contributions vary across lineages"

The data set consists of four parts: 1) "FISH_data":TIF-formatted files or unmerged and merged fluorescent channels of FISH microscopies of Anoecia corni and Sipha maydis embryos. 2) "genome_data": GenBank- and FASTA-formatted files of genome assemblies and annotations for Buchnera and co-obligate symbionts. 3) "pathway_data": Presence/absence tables of genes/pseudogenes coding for enzymes involved in the biosynthesis of essential amino acids and B vitamins in ODS spreadsheets and tab-separated value formats. Also, list of genes and pseudogenes of Buchnera genomes. 4) "phylogeny_data": FASTA-formatted nucleotide alignment files, NEXUS-formatted files used for Bayesian phylogenetic reconstruction, and resulting trees. For Buchnera, manually-curated orthologous groups of proteins are also included as flat text files. In addition, the files to infer gene losses by maximum parsimony in Count are included in the "Buchnera_count" folder.

Supplementary materials (processed data) for paper "Electrical signal transfer characteristics of mycelium-bound composites and fungal fruiting bodies."

Processed data for paper "Electrical signal transfer characteristics of mycelium-bound composites and fungal fruiting bodies."

Supplementary materials (raw data) for paper "Electrical signal transfer characteristics of mycelium-bound composites and fungal fruiting bodies"

Raw data (B&K 891, C60 and VNA instruments) for the paper "Electrical signal transfer characteristics of mycelium-bound composites and fungal fruiting bodies"