cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22214487
title: PREDICTION OF DEM PARAMETERS OF COATED FERTILIZER PARTICLES BASED ON GA-BP NEURAL NETWORK

description: ABSTRACT To provide an efficient and reliable calibration method with reduced time cost and increased accuracy, the angle of repose (AoR) in the simulation is batch-processed based on Python and the GA-BP neural network is used to improve the prediction accuracy of the DEM parameters of coated fertilizer particles. The single-factor test data were firstly interpolated to obtain sufficient training samples, thus avoiding the drawback that the BP network tends to fall into the local minimum during the training process. Then the GA-BP neural network was trained in combination with the orthogonal combination test, and the fitted correlation coefficients were all greater than 0.975, indicating that the algorithm has strong generalization performance and good stability. The predicted values matched the expected output values, indicating that the GA-BP neural network can accurately predict the nonlinear function output, and the network predicted output can be approximated as the actual output of the function. With the actual AoR as the output value, the simulation value of the AoR was obtained as 24.457° when the coefficient of restitution (CoR), coefficient of static friction (CoSF), and coefficient of rolling friction (CoRF) were 0.509, 0.176, and 0.0332, respectively, and the relative error with the actual value was 0.068%, indicating that the well-fitted GA-BP neural network could accurately predict the DEM parameters of fertilizer particles.
DOI: 10.6084/m9.figshare.13294585.v1
title: Additional file 1 of Paxillin mediates ATP-induced activation of P2X7 receptor and NLRP3 inflammasome

description: Additional file 1.
DOI: 10.6084/m9.figshare.9631595.v1
title: Additional file 5: of Genetic determinants controlling maize rubisco activase gene expression and a comparison with rice counterparts

description: Table S4. SNP markers associated with the expression of OsRCA in association population. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.19593941
title: Additional file 4 of A stepwise data interpretation process for renal amyloidosis typing by LMD-MS

description: Additional file 4: Supplementary Table 2. S-score calculation in validation set.
DOI: 10.6084/m9.figshare.19593941.v1
title: Additional file 4 of A stepwise data interpretation process for renal amyloidosis typing by LMD-MS

description: Additional file 4: Supplementary Table 2. S-score calculation in validation set.
DOI: 10.6084/m9.figshare.23788408
title: Additional file 5 of Identification and evaluation of circulating exosomal miRNAs for the diagnosis of postmenopausal osteoporosis

description: Additional file 5. The target gene list of differential expression exosomal miRNAs in sequencing data.
DOI: 10.6084/m9.figshare.23788310
title: Additional file 3 of Diagnostic value and immune infiltration characterization of YTHDF2 as a critical m6A regulator in osteoarthritic synovitis

description: Additional file 3: The ceRNA network of YTHDF2.
DOI: 10.6084/m9.figshare.23788405
title: Additional file 4 of Identification and evaluation of circulating exosomal miRNAs for the diagnosis of postmenopausal osteoporosis

description: Additional file 4. The differential expression exosomal miRNAs of three published datasets.
DOI: 10.6084/m9.figshare.19593938
title: Additional file 3 of A stepwise data interpretation process for renal amyloidosis typing by LMD-MS

description: Additional file 3: Supplementary Table 1. Normalized SC of amyloid proteins of validation specimens.
DOI: 10.6084/m9.figshare.19593938.v1
title: Additional file 3 of A stepwise data interpretation process for renal amyloidosis typing by LMD-MS

description: Additional file 3: Supplementary Table 1. Normalized SC of amyloid proteins of validation specimens.
DOI: 10.6084/m9.figshare.19593944
title: Additional file 5 of A stepwise data interpretation process for renal amyloidosis typing by LMD-MS

description: Additional file 5: Supplementary Table 3. λ-κ calculation of immunoglobulin related amyloidosis in validation set.
DOI: 10.6084/m9.figshare.13294834
title: Additional file 1 of SNHG17 promotes the proliferation and migration of colorectal adenocarcinoma cells by modulating CXCL12-mediated angiogenesis

description: Additional file 1: Table S1. Sequences for PCR primers and transfection plasmids.
DOI: 10.6084/m9.figshare.9631790.v1
title: Additional file 9: of Genotyping, generation and proteomic profiling of the first human autosomal dominant osteopetrosis type II-specific induced pluripotent stem cells

description: Table S1. Proteomic analysis revealed the similar expression of pluripotency markers in the ADO2-iPSCs and NC-iPSCs. Table S2 GO functional enrichment analysis of the DEPs of the ADO2-iPSCs. Table S3 KEGG functional enrichment analysis of the DEPs of the ADO2-iPSCs. Table S4 Protein domain functional enrichment analysis of the DEPs of the ADO2-iPSCs. Table S5 GO functional enrichment analysis of the differently Khib-modified proteins of the ADO2-iPSCs. Table S6 KEGG functional enrichment analysis of the differently Khib-modified proteins of the ADO2-iPSCs. Table S7 Protein domain functional enrichment analysis of the differently Khib-modified proteins of the ADO2-iPSCs. (XLSX 32 kb)
DOI: 10.6084/m9.figshare.23788453
title: Additional file 12 of Early-life prophylactic antibiotic treatment disturbs the stability of the gut microbiota and increases susceptibility to H9N2 AIV in chicks

description: Additional file 12: Supplementary Table 1. Group setting of the study. Supplementary Table 2. Sequencing depth of the 16S rRNA genes for the samples in the long-term treatment trial. Supplementary Table 3. Results of the PERMANOVA test in the LAT trial. Supplementary Table 4. Sequencing depth of the 16S rRNA genes for the samples in the short-term treatment trial. Supplementary Table 5. Information of samples used for metagenomic sequencing. Supplementary Table 6. Relative abundance of ARG types.
DOI: 10.6084/m9.figshare.19593971.v1
title: Additional file 1 of Identification and validation of glomerulotubular crosstalk genes mediating IgA nephropathy by integrated bioinformatics

description: Additional file 1.
DOI: 10.6084/m9.figshare.19593971
title: Additional file 1 of Identification and validation of glomerulotubular crosstalk genes mediating IgA nephropathy by integrated bioinformatics

description: Additional file 1.
DOI: 10.6084/m9.figshare.9631793.v1
title: Additional file 4: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S4. Comparison of nucleotide diversity among all samples, Asian rice and wild rice. (XLSX 17 kb)
DOI: 10.6084/m9.figshare.13302562.v1
title: Nonparametric Estimation and Testing for Positive Quadrant Dependent Bivariate Copula

description: In many practical scenarios (e.g., finance, system reliability, etc.), it is often of interest to estimate a bivariate distribution and test for some desired association properties like positive quadrant dependent (PQD) or negative quadrant dependent (NQD). Often estimation and testing for PQD/NQD property are performed using copula models as it then eliminates the need for estimating marginal distributions. Many parametric copula families have been used that allow for controlling the PQD/NQD property by a finite dimensional parameter (often just real-valued) and the problem reduces to the straightforward estimation and testing for fixed dimensional parameter using standard statistical methodologies (e.g., maximum likelihood). This article extends such a line of work by dropping any parametric assumptions and provides a fully data-dependent automated approach to estimate a copula and test for PQD property. The estimator is shown to be large-sample consistent under a set of mild regularity conditions. Numerical illustrations based on simulated data are also provided to compare the performance of the proposed testing procedure with some available methods and applications to real case studies are also provided.
DOI: 10.6084/m9.figshare.9631808.v1
title: Additional file 7: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S7. IAM, TPM and SMM hypothesis of selection events. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.9631823.v1
title: Additional file 9: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S9 Ka and Ks value among chloroplast genome. (XLSX 17 kb)
DOI: 10.6084/m9.figshare.23788292
title: Additional file 1 of MFNG is an independent prognostic marker for osteosarcoma

description: Additional file 1. Table S1. The prognosis-related gene in OS.
DOI: 10.6084/m9.figshare.23788295
title: Additional file 2 of MFNG is an independent prognostic marker for osteosarcoma

description: Additional file 2. Table S2. The univariate and multivariate Cox regression analysis.
DOI: 10.6084/m9.figshare.23788298.v1
title: Additional file 3 of MFNG is an independent prognostic marker for osteosarcoma

description: Additional file 3. Table S3. The differentially expressed genes in high-MFNG group versus low-MFNG group.
DOI: 10.5281/zenodo.3158930
title: Scout Core Measures Scenario Analysis

description: These data underpin a scenario analysis of U.S. building energy use, emissions, and costs out to 2050 using Scout (scout.energy.gov), a reproducible and granular model of U.S. building energy use developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office.<br> <br> The scenario analysis explores uncertainty in the progression of both U.S. energy demand- and supply-side conditions that affect U.S. building energy use and CO<sub>2</sub> emissions out to 2050. For electric power supply, we consider two levels: one corresponding to the 2018 AEO reference case ("RB"), and another corresponding to the 2018 AEO $25 carbon allowance fee side case ("HR"), which achieves a high level of renewable electricity penetration---approximately 45% of total power generation by 2050. Three different sets of energy conservation measures (ECMs) are considered across the scenarios. The performance guidelines ECM set ("1T") includes currently available technologies that meet existing codes and/or voluntary recognition programs (e.g., ENERGY STAR). The best available ECM package ("2T'') includes the most efficient commercially-available technologies per EIA data and other sources. The prospective ECM package ("3T'') includes research-grade technologies that could be released over the next decade as outlined by the U.S. Department of Energy's Building Technologies Office Multi-Year Program Plan. Finally, we explore two levels of technology switching from on-site fossil fuels to electricity: the basic level ("FS0'') introduces fuel switching without any incentives; and the incentivized level ("FS20'') reduces the installed cost of fuel switching measures by 20%.
DOI: 10.5281/zenodo.3706923
title: Scout Core Measures Scenario Analysis

description: These data underpin a scenario analysis of U.S. building energy use, emissions, and costs out to 2050 using Scout (scout.energy.gov), a reproducible and granular model of U.S. building energy use developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office.<br> <br> The scenario analysis explores uncertainty in the progression of both U.S. energy demand- and supply-side conditions that affect U.S. building energy use and CO<sub>2</sub> emissions out to 2050. For electric power supply, we consider two levels: one corresponding to the 2019 AEO reference case ("RB"), and another corresponding to the 2018 AEO $25 carbon allowance fee side case ("HR"), which achieves a high level of renewable electricity penetration---approximately 45% of total power generation by 2050. Three different sets of energy conservation measures (ECMs) are considered across the scenarios. The performance guidelines ECM set ("1T") includes currently available technologies that meet existing codes and/or voluntary recognition programs (e.g., ENERGY STAR). The best available ECM package ("2T'') includes the most efficient commercially-available technologies per EIA data and other sources. The prospective ECM package ("3T'') includes research-grade technologies that could be released over the next decade as outlined by the U.S. Department of Energy's Building Technologies Office Multi-Year Program Plan. Finally, we explore two levels of technology switching from on-site fossil fuels to electricity: the basic level ("FS0'') introduces fuel switching without any incentives; and the incentivized level ("FS20'') reduces the installed cost of fuel switching measures by 20%. <strong>New in Version 2:</strong> Updated Scout version to 0.5.1 (utilizes site energy data, technology cost, performance, and lifetime data, site-source energy conversion factors, greenhouse gas emissions factors, and technology adoption model coefficients from the AEO 2019 Reference Case). Updated performance guidelines ECM set to conform to the latest versions of ENERGY STAR and ASHRAE 90.1-2019. Removed the following ECMs from the prospective ECM set after determining that there are insufficient data to support heating performance COPs: Prospective Residential Integrated ASHP (FS) Prospective Residential NVC HVAC (FS) Prospective Commercial NVC HVAC (FS) Prospective Residential AVCT HVAC (FS) Prospective Commercial AVCT HVAC (FS) Added site energy outputs ( “Results-Site” folders within each scenario) while retaining captured energy outputs (“Results-Source” folders).
DOI: 10.6084/m9.figshare.23788295.v1
title: Additional file 2 of MFNG is an independent prognostic marker for osteosarcoma

description: Additional file 2. Table S2. The univariate and multivariate Cox regression analysis.
DOI: 10.6084/m9.figshare.19069831.v1
title: Additional file 2 of The PB1 gene from H9N2 avian influenza virus showed high compatibility and increased mutation rate after reassorting with a human H1N1 influenza virus

description: Additional file 2: Table S1. Specific indexes (Barcodes) for reassortant viruses from different hosts. Table S2 Primer sequence for segment amplification of HA gene. Table S3 Total substitution frequency (Fi) at every location at HA ORF region. Table S4 The summary of mutation information. Only the locations with Fi &gt; 0.01 were listed. Table S5 The genetic distances of HA from reassortant viruses and WSN strain.
DOI: 10.6084/m9.figshare.23788405.v1
title: Additional file 4 of Identification and evaluation of circulating exosomal miRNAs for the diagnosis of postmenopausal osteoporosis

description: Additional file 4. The differential expression exosomal miRNAs of three published datasets.
DOI: 10.6084/m9.figshare.23788408.v1
title: Additional file 5 of Identification and evaluation of circulating exosomal miRNAs for the diagnosis of postmenopausal osteoporosis

description: Additional file 5. The target gene list of differential expression exosomal miRNAs in sequencing data.
DOI: 10.6084/m9.figshare.23788411.v1
title: Additional file 6 of Identification and evaluation of circulating exosomal miRNAs for the diagnosis of postmenopausal osteoporosis

description: Additional file 6. The p-value of Delong test between different diagnostic models.
DOI: 10.6084/m9.figshare.19593944.v1
title: Additional file 5 of A stepwise data interpretation process for renal amyloidosis typing by LMD-MS

description: Additional file 5: Supplementary Table 3. λ-κ calculation of immunoglobulin related amyloidosis in validation set.
DOI: 10.15156/bio/sh1193635.09fu
title: SH1193635.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1193636.09fu
title: SH1193636.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1193637.09fu
title: SH1193637.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1193638.09fu
title: SH1193638.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1193639.09fu
title: SH1193639.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1193640.09fu
title: SH1193640.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1193641.09fu
title: SH1193641.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.