cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1316563.v1
title: Termite Ducke: Phylo, Trait, and Occurrence

description: Files associated with the Termite phylogenetic and functional diversity analyses along predator and edaphic gradients in central Amazonia
DOI: 10.6084/m9.figshare.1316563.v3
title: Termite Ducke: Phylo, Trait, and Occurrence

description: Files associated with the Termite phylogenetic and functional diversity analyses along predator and edaphic gradients in central Amazonia
DOI: 10.6084/m9.figshare.1316563.v2
title: Termite Ducke: Phylo, Trait, and Occurrence

description: Files associated with the Termite phylogenetic and functional diversity analyses along predator and edaphic gradients in central Amazonia
DOI: 10.6084/m9.figshare.1316498
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316502
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316502.v1
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316496
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316498.v1
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316494
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316495
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316497
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316496.v1
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316497.v1
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316495.v1
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316493
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316494.v1
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316491
title: Hughes Communications India Ltd: The Challenge for Growth

description: Abstract Hughes Communications India Ltd. (HCIL) was the leading Very Small Aperture Terminal (VSAT) based satellite communication products and services provider in India. While talking to the press, Mr. Partho Banerjee, the President & Managing Director (PMD) of HCIL, had said that he was proud that HCIL was the flag bearer of the Indian VSAT industry. He had expressed his desire to maintain this lead in the future. While HCIL had a growth rate of 18.4% in the Financial Year 2011-12 over the previous Financial Year 2010-11, he had learnt from the media that the competition had aggressive growth plans of 40% per annum. The competition was trying to catch up with HCIL and even surpass it in the near future. For HCIL to maintain its leading position, it had to achieve a higher growth rate vis-à-vis its competition.
DOI: 10.6084/m9.figshare.1316480
title: Real world network data from "A stochastic model for detecting overlapping and hierarchical community structure"

description: This is the real world network data file including karate, dolphins, polbooks, word, football, Les Miserable, C.elegans neeural, C.elegans metabolic, and word associations netwroks, used in "A stochastic model for detecting overlapping and hierarchical community structure". These data are collected from Newman's website and the details can be found in : http://www-personal.umich.edu/~mejn/netdata/ .
DOI: 10.6084/m9.figshare.1316491.v1
title: Hughes Communications India Ltd: The Challenge for Growth

description: Abstract Hughes Communications India Ltd. (HCIL) was the leading Very Small Aperture Terminal (VSAT) based satellite communication products and services provider in India. While talking to the press, Mr. Partho Banerjee, the President & Managing Director (PMD) of HCIL, had said that he was proud that HCIL was the flag bearer of the Indian VSAT industry. He had expressed his desire to maintain this lead in the future. While HCIL had a growth rate of 18.4% in the Financial Year 2011-12 over the previous Financial Year 2010-11, he had learnt from the media that the competition had aggressive growth plans of 40% per annum. The competition was trying to catch up with HCIL and even surpass it in the near future. For HCIL to maintain its leading position, it had to achieve a higher growth rate vis-à-vis its competition.
DOI: 10.6084/m9.figshare.1316493.v1
title: Gaussian Job Archive for C24H20

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1316468
title: Supporting dataset

description: Positive and negative phosphorylation site sequence data corresponding to four kinases PKA, PKC, MAPK and CK2 divided into training and test dataset.
DOI: 10.6084/m9.figshare.1314970
title: Regulation of herpes simplex virus type 1 thymidine kinase gene expression by thyroid hormone receptor in cultured neuronal cells

description: Regulation of herpes simplex virus type 1 thymidine kinase gene expression by thyroid hormone receptor in cultured neuronal cells
DOI: 10.6084/m9.figshare.1314971
title: Effects of thyroid hormone on HSV-1 gene regulation: implications in the control of viral latency and reactivation

description: Effects of thyroid hormone on HSV-1 gene regulation: implications in the control of viral latency and reactivation
DOI: 10.6084/m9.figshare.1314969
title: Early growth response gene 1 (Egr-1) regulates HSV-1 ICP4 and ICP22 gene expression

description: Early growth response gene 1 (Egr-1) regulates HSV-1 ICP4 and ICP22 gene expression
DOI: 10.6084/m9.figshare.1314970.v1
title: Regulation of herpes simplex virus type 1 thymidine kinase gene expression by thyroid hormone receptor in cultured neuronal cells

description: Regulation of herpes simplex virus type 1 thymidine kinase gene expression by thyroid hormone receptor in cultured neuronal cells
DOI: 10.6084/m9.figshare.1316480.v2
title: Real world network data from "A stochastic model for detecting overlapping and hierarchical community structure"

description: This is the real world network data file including karate, dolphins, polbooks, word, football, Les Miserable, C.elegans neeural, C.elegans metabolic, and word associations netwroks, used in "A stochastic model for detecting overlapping and hierarchical community structure". These data are collected from Newman's website and the details can be found in : http://www-personal.umich.edu/~mejn/netdata/ .
DOI: 10.6084/m9.figshare.1314967
title: Lytic HSV-1 infection induces the multifunctional transcription factor Early Growth Response-1 (EGR-1) in rabbit corneal cells

description: Lytic HSV-1 infection induces the multifunctional transcription factor Early Growth Response-1 (EGR-1) in rabbit corneal cells
DOI: 10.6084/m9.figshare.1314968
title: Repressor element-1 silencing transcription factor/neuronal restrictive silencer factor (REST/NRSF) can regulate HSV-1 immediate-early transcription via histone modification

description: Repressor element-1 silencing transcription factor/neuronal restrictive silencer factor (REST/NRSF) can regulate HSV-1 immediate-early transcription via histone modification
DOI: 10.6084/m9.figshare.1316480.v1
title: Complex network data from "A stochastic model for detecting overlapping and hierarchical community structure"

description: This is the data file including karate, dolphins, polbooks, word, football, Les Miserable, C.elegans neeural and C.elegans metabolic networks, used in "A stochastic model for detecting overlapping and hierarchical community structure". These data are collected from Newman's website and the details can be found in : http://www-personal.umich.edu/~mejn/netdata/ .
DOI: 10.6084/m9.figshare.1314968.v1
title: Repressor element-1 silencing transcription factor/neuronal restrictive silencer factor (REST/NRSF) can regulate HSV-1 immediate-early transcription via histone modification

description: Repressor element-1 silencing transcription factor/neuronal restrictive silencer factor (REST/NRSF) can regulate HSV-1 immediate-early transcription via histone modification
DOI: 10.6084/m9.figshare.1314967.v1
title: Lytic HSV-1 infection induces the multifunctional transcription factor Early Growth Response-1 (EGR-1) in rabbit corneal cells

description: Lytic HSV-1 infection induces the multifunctional transcription factor Early Growth Response-1 (EGR-1) in rabbit corneal cells
DOI: 10.6084/m9.figshare.1314929
title: Xenopus

description: developmental
DOI: 10.6084/m9.figshare.1314929.v1
title: Xenopus

description: developmental
DOI: 10.6084/m9.figshare.1314899
title: HIGGS Signal Events for Machine Learning

description: Signals (y=1) events from the first one million events in the HIGGS machine learning dataset at: http://archive.ics.uci.edu/ml/datasets/HIGGS The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator. The last seven features are functions of the first 21 features; these are high-level features derived by physicists to help discriminate between the two classes. There is an interest in using deep learning methods to obviate the need for physicists to manually develop such features. Benchmark results using Bayesian Decision Trees from a standard physics package and 5-layer neural networks are presented in a paper here: http://rdcu.be/cb58. In the Nature paper the full dataset was used, not just hte first 1million which were uploaded here.
DOI: 10.6084/m9.figshare.1314900
title: HIGGS Background Events for Machine Learning

description: Background (y=0) events from the first one million events in the HIGGS machine learning dataset at: http://archive.ics.uci.edu/ml/datasets/HIGGS The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator. The last seven features are functions of the first 21 features; these are high-level features derived by physicists to help discriminate between the two classes. There is an interest in using deep learning methods to obviate the need for physicists to manually develop such features. Benchmark results using Bayesian Decision Trees from a standard physics package and 5-layer neural networks are presented in a paper here: http://rdcu.be/cb58. In the Nature paper the full dataset was used, not just hte first 1million which were uploaded here.
DOI: 10.6084/m9.figshare.1314901
title: A study of <i>Sarcocornia</i> A.J. Scott (Chenopodiaceae) from Western Mediterranean Europe

description: The latest publications on <i>Sarcocornia</i> taxonomy and phylogeny recognize six taxa in this genus on the Iberian Peninsula: <i>S. perennis</i>, <i>S. fruticosa</i>, <i>S. alpini</i>, <i>S. alpini</i> subsp. <i>carinata, S. hispanica</i>, and <i>S. pruinosa</i>. The present study represents a comprehensive revision of the different taxa in the <i>Sarcocornia</i> genus present in Western Mediterranean Europe by means of morphological, micromorphological and phylogenetic internal transcribed spacer (ITS) analysis. Morphological and micromorphological data were studied from <i>Sarcocornia</i> samples from 113 populations in coastal salt marshes and inland salt pans in Portugal, France, Spain and Italy. Sixteen new ITS sequences were obtained from Mediterranean <i>Sarcocornia</i> species and analysed together with previous reported data. Published karyological, ecological and biogeographical data from Western Mediterranean Europe were also reviewed. The results indicate the presence of a new species, <i>S. lagascae</i>, found growing in coastal Mediterranean areas of the Iberian Peninsula. The species <i>S. fruticosa</i> was found to be absent from the Iberian territories.
DOI: 10.6084/m9.figshare.1314894
title: Biological support media influence the bacterial biofouling community in reverse osmosis water reclamation demonstration plants

description: The diversity of the bacterial community developed in different stages of two reverse osmosis (RO) water reclamation demonstration plants designed in a wastewater treatment plant (WWTP) in Tarragona (Spain) was characterized by applying 454-pyrosequencing of the 16S rRNA gene. The plants were fed by secondary treated effluent to a conventional pretreatment train prior to the two-pass RO system. Plants differed in the material used in the filtration process, which was sand in one demonstration plant and Scandinavian schists in the second plant. The results showed the presence of a highly diverse and complex community in the biofilms, mainly composed of members of the Betaproteobacteria and Bacteroidetes in all stages, with the presence of some typical wastewater bacteria, suggesting a feed water origin. Community similarities analyses revealed that samples clustered according to filter type, highlighting the critical influence of the biological supporting medium in biofilm community structure.
DOI: 10.6084/m9.figshare.1314899.v1
title: HIGGS

description: Signals (y=1) events from the first one million events in the HIGGS machine learning dataset at: http://archive.ics.uci.edu/ml/datasets/HIGGS The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator. The last seven features are functions of the first 21 features; these are high-level features derived by physicists to help discriminate between the two classes. There is an interest in using deep learning methods to obviate the need for physicists to manually develop such features. Benchmark results using Bayesian Decision Trees from a standard physics package and 5-layer neural networks are presented in a paper here: http://rdcu.be/cb58. In the Nature paper the full dataset was used, not just hte first 1million which were uploaded here.
DOI: 10.6084/m9.figshare.1314901.v2
title: A study of <i>Sarcocornia</i> A.J. Scott (Chenopodiaceae) from Western Mediterranean Europe

description: The latest publications on <i>Sarcocornia</i> taxonomy and phylogeny recognize six taxa in this genus on the Iberian Peninsula: <i>S. perennis</i>, <i>S. fruticosa</i>, <i>S. alpini</i>, <i>S. alpini</i> subsp. <i>carinata, S. hispanica</i>, and <i>S. pruinosa</i>. The present study represents a comprehensive revision of the different taxa in the <i>Sarcocornia</i> genus present in Western Mediterranean Europe by means of morphological, micromorphological and phylogenetic internal transcribed spacer (ITS) analysis. Morphological and micromorphological data were studied from <i>Sarcocornia</i> samples from 113 populations in coastal salt marshes and inland salt pans in Portugal, France, Spain and Italy. Sixteen new ITS sequences were obtained from Mediterranean <i>Sarcocornia</i> species and analysed together with previous reported data. Published karyological, ecological and biogeographical data from Western Mediterranean Europe were also reviewed. The results indicate the presence of a new species, <i>S. lagascae</i>, found growing in coastal Mediterranean areas of the Iberian Peninsula. The species <i>S. fruticosa</i> was found to be absent from the Iberian territories.
DOI: 10.6084/m9.figshare.1314894.v2
title: Biological support media influence the bacterial biofouling community in reverse osmosis water reclamation demonstration plants

description: The diversity of the bacterial community developed in different stages of two reverse osmosis (RO) water reclamation demonstration plants designed in a wastewater treatment plant (WWTP) in Tarragona (Spain) was characterized by applying 454-pyrosequencing of the 16S rRNA gene. The plants were fed by secondary treated effluent to a conventional pretreatment train prior to the two-pass RO system. Plants differed in the material used in the filtration process, which was sand in one demonstration plant and Scandinavian schists in the second plant. The results showed the presence of a highly diverse and complex community in the biofilms, mainly composed of members of the Betaproteobacteria and Bacteroidetes in all stages, with the presence of some typical wastewater bacteria, suggesting a feed water origin. Community similarities analyses revealed that samples clustered according to filter type, highlighting the critical influence of the biological supporting medium in biofilm community structure.
DOI: 10.6084/m9.figshare.1314899.v3
title: HIGGS Signal Events for Machine Learning

description: Signals (y=1) events from the first one million events in the HIGGS machine learning dataset at: http://archive.ics.uci.edu/ml/datasets/HIGGS The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator. The last seven features are functions of the first 21 features; these are high-level features derived by physicists to help discriminate between the two classes. There is an interest in using deep learning methods to obviate the need for physicists to manually develop such features. Benchmark results using Bayesian Decision Trees from a standard physics package and 5-layer neural networks are presented in a paper here: http://rdcu.be/cb58. In the Nature paper the full dataset was used, not just hte first 1million which were uploaded here.
DOI: 10.6084/m9.figshare.1314900.v1
title: HIGGS background

description: Background (y=0) events from the first one million events in the HIGGS machine learning dataset at: http://archive.ics.uci.edu/ml/datasets/HIGGS The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator. The last seven features are functions of the first 21 features; these are high-level features derived by physicists to help discriminate between the two classes. There is an interest in using deep learning methods to obviate the need for physicists to manually develop such features. Benchmark results using Bayesian Decision Trees from a standard physics package and 5-layer neural networks are presented in a paper here: http://rdcu.be/cb58. In the Nature paper the full dataset was used, not just hte first 1million which were uploaded here.
DOI: 10.6084/m9.figshare.1314899.v2
title: HIGGS signal

description: Signals (y=1) events from the first one million events in the HIGGS machine learning dataset at: http://archive.ics.uci.edu/ml/datasets/HIGGS The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator. The last seven features are functions of the first 21 features; these are high-level features derived by physicists to help discriminate between the two classes. There is an interest in using deep learning methods to obviate the need for physicists to manually develop such features. Benchmark results using Bayesian Decision Trees from a standard physics package and 5-layer neural networks are presented in a paper here: http://rdcu.be/cb58. In the Nature paper the full dataset was used, not just hte first 1million which were uploaded here.
DOI: 10.6084/m9.figshare.1314901.v1
title: A micromorphologic and phylogenetic study of <i>Sarcocornia</i> A.J. Scott (Chenopodiaceae) from Western Mediterranean Europe

description: The latest publications on <i>Sarcocornia</i> taxonomy and phylogeny recognize six taxa in this genus on the Iberian Peninsula: <i>S. perennis</i>, <i>S. fruticosa</i> and <i>S.</i><i>alpini</i>, <i>S. alpini</i> subsp. <i>carinata,</i><i>S. hispanica</i>, and <i>S. pruinosa</i>. The present study represents a comprehensive revision of the different taxa in the <i>Sarcocornia</i> genus present in Western Mediterranean Europe by means of morphological, micromorphological and phylogenetic internal transcribed spacer (ITS) analysis. Morphological and micromorphological data were studied from <i>Sarcocornia</i> samples from 113 populations in coastal salt marshes and inland salt pans in Portugal, France, Spain and Italy. Sixteen new ITS sequence were obtained from Mediterranean <i>Sarcocornia</i> species and analysed together with previous reported data. Published karyological, ecological and biogeographical data from Western Mediterranean Europe were also reviewed. The results indicate the presence of a new species, <i>S. lagascae</i>, found growing in coastal Mediterranean areas of the Iberian Peninsula. The species <i>S. fruticosa</i> was found to be absent from the Iberian territories. Departamento de Biología (Botánica), Facultad de Ciencias, Universidad Autónoma de Madrid, Cantoblanco. E-28049 Madrid, Spain. Tel: +34-914978100; Fax: +34-914978300
DOI: 10.6084/m9.figshare.1314894.v1
title: Biological support media influence the bacterial biofouling community in reverse osmosis water reclamation demonstration plants

description: The diversity of the bacterial community developed in different stages of two reverse osmosis (RO) water reclamation demonstration plants designed in a wastewater treatment plant (WWTP) in Tarragona (Spain) was characterized by applying 454-pyrosequencing of the 16S rRNA gene. The plants were fed by secondary treated effluent to a conventional pretreatment train prior to the two-pass RO system. Plants differed in the material used in the filtration process, which was sand in one demonstration plant and Scandinavian schists in the second plant. The results showed the presence of a highly diverse and complex community in the biofilms, mainly composed of members of the Betaproteobacteria and Bacteroidetes in all stages, with the presence of some typical wastewater bacteria, suggesting a feed water origin. Community similarities analyses revealed that samples clustered according to filter type, highlighting the critical influence of the biological supporting medium in biofilm community structure.
DOI: 10.6084/m9.figshare.1314900.v2
title: HIGGS Background Events for Machine Learning

description: Background (y=0) events from the first one million events in the HIGGS machine learning dataset at: http://archive.ics.uci.edu/ml/datasets/HIGGS The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator. The last seven features are functions of the first 21 features; these are high-level features derived by physicists to help discriminate between the two classes. There is an interest in using deep learning methods to obviate the need for physicists to manually develop such features. Benchmark results using Bayesian Decision Trees from a standard physics package and 5-layer neural networks are presented in a paper here: http://rdcu.be/cb58. In the Nature paper the full dataset was used, not just hte first 1million which were uploaded here.