cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1066120
title: MODELIMG CROP PATTEN SYSTEM USING LINEAR PROGRAMMING

description: In agricultural situations, farmers usually faced with the problem of how to allocate their<br>limited production resources among cropping and livestock activities. Farmer's planners can offer<br>effective techniques, such as linear programming (lp) to address the problem and produce optimal<br>solution. In this paper we have demonstrated that how a farmer who has limited resources such as farmers<br>availability ,storage capacity and availability of land can be formulated as a linear programming having<br>linear objective function with three constraints
DOI: 10.6084/m9.figshare.1066805
title: Open Source

description: Data set of the sample collected at the beach and the tools used in the process
DOI: 10.6084/m9.figshare.1066805.v1
title: new fileset

description: Data set of the sample collected at the beach and the tools used in the process
DOI: 10.6084/m9.figshare.1066805.v2
title: new fileset

description: Data set of the sample collected at the beach and the tools used in the process
DOI: 10.6084/m9.figshare.1066805.v4
title: Open Source

description: Data set of the sample collected at the beach and the tools used in the process
DOI: 10.6084/m9.figshare.1066805.v3
title: new fileset

description: Data set of the sample collected at the beach and the tools used in the process
DOI: 10.6084/m9.figshare.1067056
title: Multiple Imputation by Ordered Monotone Blocks With Application to the Anthrax Vaccine Research Program

description: Multiple imputation (MI) has become a standard statistical technique for dealing with missing values. The CDC Anthrax Vaccine Research Program (AVRP) dataset created new challenges for MI due to the large number of variables of different types and the limited sample size. A common method for imputing missing data in such complex studies is to specify, for each of <i>J</i> variables with missing values, a univariate conditional distribution given all other variables, and then to draw imputations by iterating over the <i>J</i> conditional distributions. Such fully conditional imputation strategies have the theoretical drawback that the conditional distributions may be incompatible. When the missingness pattern is monotone, a theoretically valid approach is to specify, for each variable with missing values, a conditional distribution given the variables with fewer or the same number of missing values and sequentially draw from these distributions. In this article, we propose the “multiple imputation by ordered monotone blocks” approach, which combines these two basic approaches by decomposing any missingness pattern into a collection of smaller “constructed” monotone missingness patterns, and iterating. We apply this strategy to impute the missing data in the AVRP interim data. Supplemental materials, including all source code and a synthetic example dataset, are available online.
DOI: 10.6084/m9.figshare.1067056.v1
title: Multiple Imputation by Ordered Monotone Blocks With Application to the Anthrax Vaccine Research Program

description: Multiple imputation (MI) has become a standard statistical technique for dealing with missing values. The CDC Anthrax Vaccine Research Program (AVRP) dataset created new challenges for MI due to the large number of variables of different types and the limited sample size. A common method for imputing missing data in such complex studies is to specify, for each of <i>J</i> variables with missing values, a univariate conditional distribution given all other variables, and then to draw imputations by iterating over the <i>J</i> conditional distributions. Such fully conditional imputation strategies have the theoretical drawback that the conditional distributions may be incompatible. When the missingness pattern is monotone, a theoretically valid approach is to specify, for each variable with missing values, a conditional distribution given the variables with fewer or the same number of missing values and sequentially draw from these distributions. In this article, we propose the “multiple imputation by ordered monotone blocks” approach, which combines these two basic approaches by decomposing any missingness pattern into a collection of smaller “constructed” monotone missingness patterns, and iterating. We apply this strategy to impute the missing data in the AVRP interim data. Supplemental materials, including all source code and a synthetic example dataset, are available online.
DOI: 10.6084/m9.figshare.1067056.v2
title: Multiple Imputation by Ordered Monotone Blocks With Application to the Anthrax Vaccine Research Program

description: Multiple imputation (MI) has become a standard statistical technique for dealing with missing values. The CDC Anthrax Vaccine Research Program (AVRP) dataset created new challenges for MI due to the large number of variables of different types and the limited sample size. A common method for imputing missing data in such complex studies is to specify, for each of <i>J</i> variables with missing values, a univariate conditional distribution given all other variables, and then to draw imputations by iterating over the <i>J</i> conditional distributions. Such fully conditional imputation strategies have the theoretical drawback that the conditional distributions may be incompatible. When the missingness pattern is monotone, a theoretically valid approach is to specify, for each variable with missing values, a conditional distribution given the variables with fewer or the same number of missing values and sequentially draw from these distributions. In this article, we propose the “multiple imputation by ordered monotone blocks” approach, which combines these two basic approaches by decomposing any missingness pattern into a collection of smaller “constructed” monotone missingness patterns, and iterating. We apply this strategy to impute the missing data in the AVRP interim data. Supplemental materials, including all source code and a synthetic example dataset, are available online.
DOI: 10.6084/m9.figshare.1082510
title: Coherent control of nondegenerate two-photon absorption by femtosecond laser pulses

description: We investigate the dynamics of nondegenerate two-photon absorption in a cascade three-level system induced by two-color femtosecond laser pulses. It is demonstrated that optimal one-photon detunings of the field frequencies from the intermediate state can be used to control coherently the population inversion between the uppermost and the ground states. The propagation effects make the situation much more complicated. Our simulation shows the possibility of an optical soliton behavior of the two-color pulse with the help of the one-photon detuning.
DOI: 10.6084/m9.figshare.1088258
title: Persistent gamma oscillations in vitro: Utah array data from macaque temporal cortex

description: The zip file contains a 21-second segment of a Utah array recording from macaque temporal neocortex in vitro (data collected by Matt Ainsworth), saved as a .mat file. Nanomolar kainate solution was applied to induce persistent gamma oscillations. Data sampled at 10kHz. The raw data are included, organised into a 100 by 210000 matrix (100 channels, 210000 samples per channel). For description of the experimental setup and array placement, see Tomsett et al. 2014 (link below, open access - if you use this data in a publication, please cite that paper!).<br><br>The zip file also contains a matlab script to analyse the data and reproduce figure 9A from that paper. This script performs several filtering and normalisation operations on the data. It requires the Matlab Signal Processing Toolbox to work.<br><br>EDIT: updated the analysis file; original uplaod did not band-pass filter the data<br>
DOI: 10.6084/m9.figshare.1088258.v4
title: Persistent gamma oscillations in vitro: Utah array data from macaque temporal cortex

description: The zip file contains a 21-second segment of a Utah array recording from macaque temporal neocortex in vitro (data collected by Matt Ainsworth), saved as a .mat file. Nanomolar kainate solution was applied to induce persistent gamma oscillations. Data sampled at 10kHz. The raw data are included, organised into a 100 by 210000 matrix (100 channels, 210000 samples per channel). For description of the experimental setup and array placement, see Tomsett et al. 2014 (link below, open access).<br><br>The zip file also contains a matlab script to analyse the data and reproduce figure 9A from that paper. This script performs several filtering and normalisation operations on the data. It requires the Matlab Signal Processing Toolbox to work.<br>
DOI: 10.6084/m9.figshare.1089554
title: Stimulating effect of a new triterpene derived from <i>Anoectochilus elwesii</i> on glucose uptake in insulin-resistant human HepG2 cells

description: A new triterpene (<b>1</b>), 3-β-<i>O</i>-olean-11,13 (18)-diene-23,28-dioic acid, together with five known compounds (<b>2</b>–<b>6</b>), was isolated from <i>Anoectochilus elwesii</i> and their structures were elucidated by extensive spectroscopic methods and comparison with the literature data. Compound <b>1</b> was the first example of highly oxygenated triterpene obtained from <i>Anoectochilus</i> genus. The isolated compounds were evaluated on insulin-resistant human HepG2 cells for stimulating glucose uptake activity and the new compound displayed highly potent effect on the stimulation of glucose uptake in human HepG2 cells.
DOI: 10.6084/m9.figshare.1089554.v2
title: Stimulating effect of a new triterpene derived from <i>Anoectochilus elwesii</i> on glucose uptake in insulin-resistant human HepG2 cells

description: A new triterpene (<b>1</b>), 3-β-<i>O</i>-olean-11,13 (18)-diene-23,28-dioic acid, together with five known compounds (<b>2</b>–<b>6</b>), was isolated from <i>Anoectochilus elwesii</i> and their structures were elucidated by extensive spectroscopic methods and comparison with the literature data. Compound <b>1</b> was the first example of highly oxygenated triterpene obtained from <i>Anoectochilus</i> genus. The isolated compounds were evaluated on insulin-resistant human HepG2 cells for stimulating glucose uptake activity and the new compound displayed highly potent effect on the stimulation of glucose uptake in human HepG2 cells.
DOI: 10.6084/m9.figshare.1089554.v1
title: Stimulating effect of a new triterpene derived from <i>Anoectochilus elwesii</i> on glucose uptake in insulin-resistant human HepG2 cells

description: A new triterpene (<b>1</b>), 3-β-<i>O</i>-olean-11,13 (18)-diene-23,28-dioic acid, together with five known compounds (<b>2</b>–<b>6</b>), was isolated from <i>Anoectochilus elwesii</i> and their structures were elucidated by extensive spectroscopic methods and comparison with the literature data. Compound <b>1</b> was the first example of highly oxygenated triterpene obtained from <i>Anoectochilus</i> genus. The isolated compounds were evaluated on insulin-resistant human HepG2 cells for stimulating glucose uptake activity and the new compound displayed highly potent effect on the stimulation of glucose uptake in human HepG2 cells.
DOI: 10.6084/m9.figshare.1091383
title: Ethanol Suppresses PGC-1α Expression by Interfering with the cAMP-CREB Pathway in Neuronal Cells

description: Alcohol intoxication results in neuronal apoptosis, neurodegeneration and manifest with impaired balance, loss of muscle coordination and behavioral changes. One of the early events of alcohol intoxication is mitochondrial (Mt) dysfunction and disruption of intracellular redox homeostasis. The mechanisms by which alcohol causes Mt dysfunction, disrupts cellular redox homeostasis and triggers neurodegeneration remains to be further investigated. Proliferator-activated receptor gamma co-activator 1-alpha (PGC-1α) plays critical roles in regulating Mt biogenesis and respiration, cellular antioxidant defense mechanism, and maintenance of neuronal integrity and function. In this study, we sought to investigate whether alcohol causes Mt dysfunction and triggers neurodegeneration by suppressing PGC-1α expression. We report that ethanol suppresses PGC-1α expression, and impairs mitochondrial function and enhances cellular toxicity in cultured neuronal cell line and also in human fetal brain neural stem cell-derived primary neurons. Moreover, we report that cells over-expressing exogenous PGC-1α or treated with Rolipram, a selective phosphodiesterase-4 inhibitor, ameliorate alcohol-induced cellular toxicity. Further analysis show that ethanol decreases steady-state intracellular cAMP levels, and thus depletes phosphorylation of cAMP-response element binding protein (p-CREB), the key transcription factor that regulates transcription of PGC-1a gene. Accordingly, we found PGC-1α promoter activity and transcription was dramatically repressed in neuronal cells when exposed to ethanol, suggesting that ethanol blunts cAMP→CREB signaling pathway to interfere with the transcription of PGC-1α. Ethanol-mediated decrease in PGC-1α activity results in the disruption of Mt respiration and function and higher cellular toxicity. This study might lead to potential therapeutic intervention to ameliorate alcohol-induced apoptosis and/or neurodegeneration by targeting PGC-1α.
DOI: 10.6084/m9.figshare.1091383.v1
title: Ethanol Suppresses PGC-1α Expression by Interfering with the cAMP-CREB Pathway in Neuronal Cells

description: Alcohol intoxication results in neuronal apoptosis, neurodegeneration and manifest with impaired balance, loss of muscle coordination and behavioral changes. One of the early events of alcohol intoxication is mitochondrial (Mt) dysfunction and disruption of intracellular redox homeostasis. The mechanisms by which alcohol causes Mt dysfunction, disrupts cellular redox homeostasis and triggers neurodegeneration remains to be further investigated. Proliferator-activated receptor gamma co-activator 1-alpha (PGC-1α) plays critical roles in regulating Mt biogenesis and respiration, cellular antioxidant defense mechanism, and maintenance of neuronal integrity and function. In this study, we sought to investigate whether alcohol causes Mt dysfunction and triggers neurodegeneration by suppressing PGC-1α expression. We report that ethanol suppresses PGC-1α expression, and impairs mitochondrial function and enhances cellular toxicity in cultured neuronal cell line and also in human fetal brain neural stem cell-derived primary neurons. Moreover, we report that cells over-expressing exogenous PGC-1α or treated with Rolipram, a selective phosphodiesterase-4 inhibitor, ameliorate alcohol-induced cellular toxicity. Further analysis show that ethanol decreases steady-state intracellular cAMP levels, and thus depletes phosphorylation of cAMP-response element binding protein (p-CREB), the key transcription factor that regulates transcription of PGC-1a gene. Accordingly, we found PGC-1α promoter activity and transcription was dramatically repressed in neuronal cells when exposed to ethanol, suggesting that ethanol blunts cAMP→CREB signaling pathway to interfere with the transcription of PGC-1α. Ethanol-mediated decrease in PGC-1α activity results in the disruption of Mt respiration and function and higher cellular toxicity. This study might lead to potential therapeutic intervention to ameliorate alcohol-induced apoptosis and/or neurodegeneration by targeting PGC-1α.
DOI: 10.6084/m9.figshare.1109602
title: Estimation of symmetry-constrained Gaussian graphical models: application to clustered dense networks

description: We propose a model selection algorithm for high-dimensional clustered data. Our algorithm combines a classical penalized likelihood method with a composite likelihood approach in the framework of coloured graphical Gaussian models. Our method is designed to identify high-dimensional dense networks with a large number of edges but sparse edge classes. Its empirical performance is demonstrated through simulation studies and a network analysis of a gene expression dataset.
DOI: 10.6084/m9.figshare.1109602.v1
title: Estimation of symmetry-constrained Gaussian graphical models: application to clustered dense networks

description: We propose a model selection algorithm for high-dimensional clustered data. Our algorithm combines a classical penalized likelihood method with a composite likelihood approach in the framework of coloured graphical Gaussian models. Our method is designed to identify high-dimensional dense networks with a large number of edges but sparse edge classes. Its empirical performance is demonstrated through simulation studies and a network analysis of a gene expression dataset.
DOI: 10.6084/m9.figshare.1112399
title: data of patients with painful DPN

description: Data of VAS, 2-PD, BDI-DPN, NCV, SCA
DOI: 10.6084/m9.figshare.1112399.v1
title: data of patients with painful DPN

description: Data of VAS, 2-PD, BDI-DPN, NCV, SCA
DOI: 10.6084/m9.figshare.1117723
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v1
title: Global 5mC and 5hmC levels in seven pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in seven pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v2
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v3
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v4
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v5
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v6
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v7
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v8
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v9
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v10
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v11
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.
DOI: 10.6084/m9.figshare.1117723.v12
title: Global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines investigated by UPLC-MS/MS

description: We performed UPLC-MS/MS to investigate global 5mC and 5hmC levels in sixteen pairs of HCC and non-HCC samples and two HCC cell lines (97L and LM6 cells). We found that 5mC and 5hmC were frequently decreased in 71% and 100% of the HCC specimens, respectively, compared with non-HCC specimens. Correspondingly, 5mC and 5hmC levels in the two HCC cell lines remained relatively low.