cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18419/darus-1110/416
title: 00103_mask.png

description: :unav
DOI: 10.17632/swnbym4ty5.1
title: The temperature of the refrigerator

description: The datas originate from our study
DOI: 10.18419/darus-1110/417
title: 00001.png

description: :unav
DOI: 10.6084/m9.figshare.25150673
title: Supplementary tables and Other original supplementary data

description: This study employed diverse genetic methodologies, including Transcriptome-Wide Association Studies (TWAS), Mendelian Randomization (MR), FOCUS, and colocalization analysis to investigate the genetic landscape of Primary Sclerosing Cholangitis (PSC) and its association with Inflammatory Bowel Disease (IBD),. We identified seven genes that are potentially causative of PSC and four among seven demonstrate significant links to IBD and the gut-liver axis. Our research revealed a notable causal relationship between PSC and IBD, specifically Ulcerative Colitis (UC). Additionally, we explored the influence of gut microbiota and metabolites on PSC to uncover the potential intermediary roles. These findings have deepened our understanding of PSC's pathogenesis and suggested novel therapeutic targets, addressing a crucial need for effective treatment of this complicated disease.
DOI: 10.6084/m9.figshare.25150673.v2
title: Supplementary tables and Other original supplementary data

description: This study employed diverse genetic methodologies, including Transcriptome-Wide Association Studies (TWAS), Mendelian Randomization (MR), FOCUS, and colocalization analysis to investigate the genetic landscape of Primary Sclerosing Cholangitis (PSC) and its association with Inflammatory Bowel Disease (IBD),. We identified seven genes that are potentially causative of PSC and four among seven demonstrate significant links to IBD and the gut-liver axis. Our research revealed a notable causal relationship between PSC and IBD, specifically Ulcerative Colitis (UC). Additionally, we explored the influence of gut microbiota and metabolites on PSC to uncover the potential intermediary roles. These findings have deepened our understanding of PSC's pathogenesis and suggested novel therapeutic targets, addressing a crucial need for effective treatment of this complicated disease.
DOI: 10.18419/darus-1110/418
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description: :unav
DOI: 10.18419/darus-1110/419
title: 00103.png

description: :unav
DOI: 10.6084/m9.figshare.25150673.v1
title: Other Supplementary Materials

description: This study employed diverse genetic methodologies, including Transcriptome-Wide Association Studies (TWAS), Mendelian Randomization (MR), FOCUS, and colocalization analysis to investigate the genetic landscape of Primary Sclerosing Cholangitis (PSC) and its association with Inflammatory Bowel Disease (IBD),. We identified seven genes that are potentially causative of PSC and four among seven demonstrate significant links to IBD and the gut-liver axis. Our research revealed a notable causal relationship between PSC and IBD, specifically Ulcerative Colitis (UC). Additionally, we explored the influence of gut microbiota and metabolites on PSC to uncover the potential intermediary roles. These findings have deepened our understanding of PSC's pathogenesis and suggested novel therapeutic targets, addressing a crucial need for effective treatment of this complicated disease.
DOI: 10.18419/darus-1110/420
title: 00047.png

description: :unav
DOI: 10.18419/darus-1110/421
title: 00091_mask-1.png

description: :unav
DOI: 10.18419/darus-1110/422
title: 00026_mask.png

description: :unav
DOI: 10.18419/darus-1110/423
title: 00114.png

description: :unav
DOI: 10.18419/darus-1110/424
title: 00078_mask-1.png

description: :unav
DOI: 10.18419/darus-1110/425
title: 00079_mask.png

description: :unav
DOI: 10.18419/darus-1110/426
title: 00063-1.png

description: :unav
DOI: 10.18419/darus-1110/427
title: 00024-1.png

description: :unav
DOI: 10.18419/darus-1110/428
title: 00088.png

description: :unav
DOI: 10.18419/darus-1110/429
title: 00108_mask.png

description: :unav
DOI: 10.18419/darus-1110/430
title: 00074_mask-1.png

description: :unav
DOI: 10.18419/darus-1110/431
title: 00033_mask.png

description: :unav
DOI: 10.18419/darus-1110/432
title: 00057_mask.png

description: :unav
DOI: 10.18419/darus-1110/433
title: 00039.png

description: :unav
DOI: 10.18419/darus-1110/434
title: crmeta.db

description: :unav
DOI: 10.18419/darus-1110/435
title: 00072_mask-1.png

description: :unav
DOI: 10.18419/darus-1110/436
title: 00030_mask-1.png

description: :unav
DOI: 10.18419/darus-1110/437
title: 00079.png

description: :unav
DOI: 10.18419/darus-1110/438
title: 00093.png

description: :unav
DOI: 10.17632/nstvb42skt.2
title: Synergistic Impacts of Diurnal Warm Layers and Inertial-Wave Mixing on SST Warming and Upper Ocean Stratification

description: This dataset include the float measurements in the scientific analysis. This data is gridded in the vertical resolution of 2 m and temporal resolution of 30 min. For the details about the variables, please contact the authors. The title is changed to match the latest manuscript.
DOI: 10.18419/darus-1110/439
title: 00104_mask.png

description: :unav
DOI: 10.18419/darus-1110/440
title: 00066_mask.png

description: :unav
DOI: 10.18419/darus-1110/441
title: 00044_mask-1.png

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DOI: 10.18419/darus-1110/442
title: 00072.png

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DOI: 10.18419/darus-1110/443
title: 00029-1.png

description: :unav
DOI: 10.18419/darus-1110/444
title: 00032-1.png

description: :unav
DOI: 10.18419/darus-1110/445
title: 00040_mask.png

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DOI: 10.18419/darus-1110/446
title: 00003.png

description: :unav
DOI: 10.18419/darus-1110/447
title: 00032.png

description: :unav
DOI: 10.18419/darus-1110/448
title: 00085.png

description: :unav
DOI: 10.18419/darus-1110/449
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description: :unav
DOI: 10.18419/darus-1110/450
title: 00089_mask-1.png

description: :unav
DOI: 10.18419/darus-1110/451
title: 00061_mask.png

description: :unav
DOI: 10.17632/fmmr595pps.1
title: Simulated dataset on coordinated reset stimulation of homogeneous and inhomogeneous networks of excitatory leaky integrate-and-fire neurons with spike-timing-dependent plasticity

description: We present simulated data on coordinated reset stimulation (CRS) of plastic neuronal networks. The neuronal network consists of excitatory leaky integrate-and-fire neurons and plasticity is implemented as spike-timing-dependent plasticity (STDP). A synchronized state with strong synaptic connectivity and a desynchronized state with weak synaptic connectivity coexist. CRS may drive the network from the synchronized state into a desynchronized state inducing long-lasting desynchronization effects that persist after cessation of stimulation. This is used to model brain stimulation-induced transitions between a pathological state, with abnormally strong neuronal synchrony, and a physiological state, e.g., in Parkinson’s disease. During CRS, a sequence of stimuli is delivered to multiple stimulation sites – called CR sequence. We present simulated data for the analysis of long-lasting desynchronization effects of CRS with shuffled CR sequences versus non-shuffled CR sequences in which the order of stimulus deliveries to the sites remains unchanged throughout the entire stimulation period. We provide data on long-lasting desynchronization effects of shuffled and non-shuffled CRS in networks with homogeneous synaptic connectivity and networks with inhomogeneous synaptic connectivity. Homogeneous synaptic connectivity refers to a network in which the probability of a synaptic connection does not depend on the pre- and postsynaptic neurons’ locations. In contrast, inhomogeneous synaptic connectivity refers to a network in which the probability for a synaptic connection depends on the neurons’ locations. The presented neuronal network model was used to analyze the impact of the CR sequences and their shuffling on the long-lasting effects of CRS [1].
DOI: 10.18419/darus-1110/452
title: 00082_mask-1.png

description: :unav
DOI: 10.18419/darus-1110/453
title: 00096.png

description: :unav
DOI: 10.17632/fmmr595pps.2
title: Simulated dataset on coordinated reset stimulation of homogeneous and inhomogeneous networks of excitatory leaky integrate-and-fire neurons with spike-timing-dependent plasticity

description: We present simulated data on coordinated reset stimulation (CRS) of plastic neuronal networks. The neuronal network consists of excitatory leaky integrate-and-fire neurons and plasticity is implemented as spike-timing-dependent plasticity (STDP). A synchronized state with strong synaptic connectivity and a desynchronized state with weak synaptic connectivity coexist. CRS may drive the network from the synchronized state into a desynchronized state inducing long-lasting desynchronization effects that persist after cessation of stimulation. This is used to model brain stimulation-induced transitions between a pathological state, with abnormally strong neuronal synchrony, and a physiological state, e.g., in Parkinson’s disease. During CRS, a sequence of stimuli is delivered to multiple stimulation sites – called CR sequence. We present simulated data for the analysis of long-lasting desynchronization effects of CRS with shuffled CR sequences versus non-shuffled CR sequences in which the order of stimulus deliveries to the sites remains unchanged throughout the entire stimulation period. We provide data on long-lasting desynchronization effects of shuffled and non-shuffled CRS in networks with homogeneous synaptic connectivity and networks with inhomogeneous synaptic connectivity. Homogeneous synaptic connectivity refers to a network in which the probability of a synaptic connection does not depend on the pre- and postsynaptic neurons’ locations. In contrast, inhomogeneous synaptic connectivity refers to a network in which the probability for a synaptic connection depends on the neurons’ locations. The presented neuronal network model was used to analyze the impact of the CR sequences and their shuffling on the long-lasting effects of CRS [1]. More details can be found in Ref. [2].

[1] Kromer, J. A., and Tass, P. A. (2024). Sequences and their shuffling may crucially impact coordinated reset stimulation – a theoretical study. Brain Stimulation 17, P194–P196.
[2] Kromer, J.A., and Tass, P.A. (2024). Simulated dataset on coordinated reset stimulation of homogeneous and inhomogeneous networks of excitatory leaky integrate-and-fire neurons with spike-timing-dependent plasticity. Data in Brief 54, 110345.

Note: Version 2 includes the following changes:

1) References [1] and [2] added.

2) run_sim/3_run.py "data" -&gt; dataDirectory in line 159

3) Corrections related to the stimulation amplitude of non-shuffled CRS. 
In version 2, non-shuffled and shuffled CRS have the same stimulation amplitude for the same value of Astim. 
The following files have been updated accordingly:
- CRS/CRS_non_shuffled.py 
- figures/Fig2/Figure_2.png
- figures/Fig2/data/dic_mean_Weights_nonShuffled_homogeneous.pickle
- figures/Fig2/data/dic_mean_Weights_nonShuffled_inhomogeneous.pickle
DOI: 10.18419/darus-1110/454
title: 00125_mask.png

description: :unav
DOI: 10.18419/darus-1110/455
title: 00116_mask.png

description: :unav
DOI: 10.18419/darus-1110/456
title: 00071_mask-1.png

description: :unav
DOI: 10.18419/darus-1110/457
title: 00115_mask.png

description: :unav
DOI: 10.18419/darus-1110/458
title: 00012-1.png

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DOI: 10.18419/darus-1110/459
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description: :unav
DOI: 10.18419/darus-1110/460
title: 00098_mask.png

description: :unav
DOI: 10.18419/darus-1110/461
title: 00077_mask.png

description: :unav
DOI: 10.18419/darus-1110/462
title: 00007-1.png

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DOI: 10.18419/darus-1110/463
title: 00118_mask.png

description: :unav
DOI: 10.18419/darus-1110/464
title: 00014_mask.png

description: :unav
DOI: 10.18419/darus-1110/465
title: 00098_mask-1.png

description: :unav
DOI: 10.18419/darus-1110/466
title: 00060.png

description: :unav
DOI: 10.18419/darus-1110/467
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description: :unav
DOI: 10.18419/darus-1110/468
title: 00067_mask-1.png

description: :unav
DOI: 10.17632/77dhf2n3sz.1
title: Berbamine modulates the protective effect of endoplasmic reticulum stress in the kidney of diabetic rats

description: This is the original data of the article Berbamine modulates the protective effect of endoplasmic reticulum stress in the kidney of diabetic rats, which contains figure1-figure8, immunofluorescence and immunohistochemistry original plots ,Western Blot data and animal experimental data.
DOI: 10.18419/darus-1110/469
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description: :unav
DOI: 10.18419/darus-1110/470
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description: :unav
DOI: 10.18419/darus-1110/471
title: 00002-1.png

description: :unav
DOI: 10.18419/darus-1110/472
title: 00031_mask.png

description: :unav
DOI: 10.18419/darus-1110/473
title: 00098-1.png

description: :unav
DOI: 10.18419/darus-1110/474
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DOI: 10.18419/darus-1110/475
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DOI: 10.18419/darus-1110/476
title: 00013.png

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DOI: 10.18419/darus-1110/477
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DOI: 10.18419/darus-1110/478
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DOI: 10.18419/darus-1110/479
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description: :unav
DOI: 10.18419/darus-1110/480
title: 00084_mask.png

description: :unav
DOI: 10.18419/darus-1110/481
title: KR04_17.las

description: :unav
DOI: 10.18419/darus-1110/482
title: KR04_17_u1_v0.jpg

description: :unav
DOI: 10.18419/darus-1110/483
title: KR04_17.mtl

description: :unav
DOI: 10.17632/5mnp26mxp8.1
title: Golkarian-Jabbarzadeh-1-Data

description: These data are provided for "Graphene nanoplates bending under multi-part asymmetric conditions based on 3D elasticity and new modified couple stress theories: comparison with the Molecular Mechanics method" article written by authors and their co-authors.
DOI: 10.18419/darus-1110/484
title: KR04_17.ply

description: :unav
DOI: 10.18419/darus-1110/485
title: KR04_17_u0_v0.jpg

description: :unav
DOI: 10.18419/darus-1110
title: 3D Photogrammetric-Data for KR04-17

description: Research data (*.las, *.ply and *.obj format) which was obtained by Photogrammetric/Computer Vision 3D digitization as well as original images which were the base for the 3D reconstruction process. Explanation about the 3D data format: Las (Is the normal data format for laser scanned point cloud data and also for photogrammetric 3D model.) Ply or Ply + jpg (The software RealityCapture encoded texture mesh in a single ply file while the software Agisoft metashape exported textured mesh in ply format + .jpg.) Obj + mtl + jpg (Obj stores a texture mesh together with mtl and jpg file. Obj file contains information of geometric vertices, texture vertices, vertex normal, polygon face element etc. The Mtl file defines the texture information of the faces. Mtl normally refers to a jpg for storing the actual texture.) Explanation about the mask image (if available): To avoid lots of background information in the 3D reconstruction process, well-aligned images to generate a rough model were applied. Afterwards a mask for each image could be calculated according to the 3D model. In the next step, original images together with the corresponding masks are applied to implement the reconstruction, which is free from the influence of the background information. This dataset is part of the digital gyroscope collection. For more information about the collection and its creation, please see the documentation dataset: Niklaus, Maria, 2021, "Information about the Gyrolog data repository", doi: 10.18419/darus-821, DaRUS.To refer to the whole collection: Wagner, Jörg F.; Ceranski, Beate; Fritsch, Dieter; Mammadov, Gasim; Niklaus, Maria; Schweizer, Timo; Simon, Sven; Zhan, Kun, 2021, "Digital Gyroscope Collection Created by the Project 'Gyrolog'", doi: 10.18419/darus-gyrolog, DaRUS.
DOI: 10.18419/darus-1110/486
title: KR04_17.obj

description: :unav
DOI: 10.18419/darus-1111/1
title: 00004991.JPG

description: :unav
DOI: 10.18419/darus-1111/2
title: 00005056.JPG

description: :unav
DOI: 10.5281/zenodo.12819596
title: The role of non-native plant species in modulating riverbank erosion: a systematic review - extracted coded articles dataset

description: Data extraction sheet of code typologies for the review titled: The role of non-native plant species in modulating riverbank erosion: a systematic review. The uploaded csv file contains all the extracted values for each typology.
DOI: 10.18419/darus-1111/3
title: 00005090.JPG

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DOI: 10.18419/darus-1111/4
title: 00005258.JPG

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DOI: 10.18419/darus-1111/5
title: 00005197.JPG

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DOI: 10.18419/darus-1111/6
title: 00005286.JPG

description: :unav
DOI: 10.5281/zenodo.11102487
title: Supplementary material of ""Enhancing QSAR models for anti-inflammatory activity: Using decision trees and rotation forest to predict NO inhibition by Aspergillus metabolites"

description: The study focuses on employing advanced QSAR modeling techniques to predict NO inhibitory metabolites from Aspergillus. It utilizes decision trees, the Ranker method, and CorrelationAttributeEval for attribute selection, enhanced by Rotation Forest and AdaBoost, with classifiers like Artificial Neural Networks and J48 Trees. The QSAR models, using an ensemble approach with Rotation Forest and AdaBoost.M1 in a KNIME workflow, selected seven molecular descriptors from a dataset of diverse Aspergillus anti-inflammatory metabolites. The RF-enhanced model excelled in capturing complex relationships and enhancing predictive performance. It identified electrotopological state, topological distances, and secondary amides as key contributors to NO inhibition. This model shows promising potential for identifying new anti-inflammatory drugs based on computational techniques.








 
description: The study focuses on employing advanced QSAR modeling techniques to predict NO inhibitory metabolites from Aspergillus. It utilizes decision trees, the Ranker method, and CorrelationAttributeEval for attribute selection, enhanced by Rotation Forest and AdaBoost, with classifiers like Artificial Neural Networks and J48 Trees. The QSAR models, using an ensemble approach with Rotation Forest and AdaBoost.M1 in a KNIME workflow, selected seven molecular descriptors from a dataset of diverse Aspergillus anti-inflammatory metabolites. The RF-enhanced model excelled in capturing complex relationships and enhancing predictive performance. It identified electrotopological state, topological distances, and secondary amides as key contributors to NO inhibition. This model shows promising potential for identifying new anti-inflammatory drugs based on computational techniques.
DOI: 10.5281/zenodo.12807264
title: Supplementary material of "Anti-inflammatory boosted QSAR models for predicting Nitric Oxide inhibition by bioactive metabolites from Aspergillus species""

description: The study focuses on employing advanced QSAR modeling techniques to predict NO inhibitory metabolites from Aspergillus. It utilizes decision trees, the Ranker method, and CorrelationAttributeEval for attribute selection, enhanced by Rotation Forest and AdaBoost, with classifiers like Artificial Neural Networks and J48 Trees. The QSAR models, using an ensemble approach with Rotation Forest and AdaBoost.M1 in a KNIME workflow, selected seven molecular descriptors from a dataset of diverse Aspergillus anti-inflammatory metabolites. The RF-enhanced model excelled in capturing complex relationships and enhancing predictive performance. It identified electrotopological state, topological distances, and secondary amides as key contributors to NO inhibition. This model shows promising potential for identifying new anti-inflammatory drugs based on computational techniques.








 
description: The study focuses on employing advanced QSAR modeling techniques to predict NO inhibitory metabolites from Aspergillus. It utilizes decision trees, the Ranker method, and CorrelationAttributeEval for attribute selection, enhanced by Rotation Forest and AdaBoost, with classifiers like Artificial Neural Networks and J48 Trees. The QSAR models, using an ensemble approach with Rotation Forest and AdaBoost.M1 in a KNIME workflow, selected seven molecular descriptors from a dataset of diverse Aspergillus anti-inflammatory metabolites. The RF-enhanced model excelled in capturing complex relationships and enhancing predictive performance. It identified electrotopological state, topological distances, and secondary amides as key contributors to NO inhibition. This model shows promising potential for identifying new anti-inflammatory drugs based on computational techniques.
DOI: 10.5281/zenodo.12820680
title: Supplementary material of "Anti-inflammatory boosted QSAR models for predicting Nitric Oxide inhibition by bioactive metabolites from Aspergillus species""

description: The study focuses on employing advanced QSAR modeling techniques to predict NO inhibitory metabolites from Aspergillus. It utilizes decision trees, the Ranker method, and CorrelationAttributeEval for attribute selection, enhanced by Rotation Forest and AdaBoost, with classifiers like Artificial Neural Networks and J48 Trees. The QSAR models, using an ensemble approach with Rotation Forest and AdaBoost.M1 in a KNIME workflow, selected seven molecular descriptors from a dataset of diverse Aspergillus anti-inflammatory metabolites. The RF-enhanced model excelled in capturing complex relationships and enhancing predictive performance. It identified electrotopological state, topological distances, and secondary amides as key contributors to NO inhibition. This model shows promising potential for identifying new anti-inflammatory drugs based on computational techniques.








 
description: The study focuses on employing advanced QSAR modeling techniques to predict NO inhibitory metabolites from Aspergillus. It utilizes decision trees, the Ranker method, and CorrelationAttributeEval for attribute selection, enhanced by Rotation Forest and AdaBoost, with classifiers like Artificial Neural Networks and J48 Trees. The QSAR models, using an ensemble approach with Rotation Forest and AdaBoost.M1 in a KNIME workflow, selected seven molecular descriptors from a dataset of diverse Aspergillus anti-inflammatory metabolites. The RF-enhanced model excelled in capturing complex relationships and enhancing predictive performance. It identified electrotopological state, topological distances, and secondary amides as key contributors to NO inhibition. This model shows promising potential for identifying new anti-inflammatory drugs based on computational techniques.
DOI: 10.18419/darus-1111/7
title: 00005165.JPG

description: :unav
DOI: 10.18419/darus-1111/8
title: 00005313.JPG

description: :unav