cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/7h2bd5cd65.1
title: Astragalus granule ameliorates renal injury in diabetic rats and patients with diabetic kidney disease

description: 1 Astragalus granule with losartan alleviated STZ-induced renal injury in DKD rats Significantly reduced kidney/body weight ratios and BUN were observed in AG+losartan group and Losartan group compared to Model group (P&lt;0.01)(Figure 1). Compared to the losartan group, the ACR were also significantly reduced in AG+losartan group (P&lt;0.05)(Figure 2). The results of histopathological tests of the renal tissues at the end of the experiment are shown in Figures 3. Pathological renal lesion significantly worsened in the model group. AG+losartan and losartan relieved glomerular hypertrophy and mesangial expansion (Figure 3). 2 In comparison with controls, the expression of TLR4, MyD88 and p-NF-κB significantly increased in the model group (P&lt;0.05). After 12 weeks of treatment with Astragalus granules and losartan, the expression of TLR4, MyD88 and p-NF-κB protein decreased in the AG+losartan group and Losartan group (P&lt;0.05). Compared to the losartan group, TLR4, MyD88 and p-NF-κB were also significantly reduced in AG+losartan group. In the all groups the level of NF-κB was not statistically different (Figure 4). 3 Astragalus granulesinhibited STZ-induced TNF-α and IL-1β generation in DKD rats Renal inflammation plays a key role in promoting the occurrence and development of DKD. To explore whether Astragalus granules could affect STZ-induced inflammatory cytokines production, ELISA was performed to detect the levels of TNF-α and IL-1β in blood of DKD rats. An apparent upregulation was observed in the levels of TNF-α and IL-1β in blood of DKD rats, while astragalus granules and losartan treatment strikingly inhibited the increase of TNF-α and IL-1β in DKD rats (Figure 5). 4 Astragalus granules alleviated renal injury in DKD patients The study was conducted as a randomized, controlled, prospective study. Patients were recruited over a time period of six months. Overall, 60 DKD patients with control group (n=30) and AG+losartan group (n=30) were included. The characteristics are in Table 1. There were no significantly different between the control group and AG+losartan group (Table 1). With 12 weeks treatment, the ACR in control group and AG+losartan group were significantly lower than 12 weeks ago. Meanwhile, compared to the control group, the ACR were significantly reduced in AG+losartan group (P&lt;0.05). Alanine transaminase (ALT), Aspartic transaminase (AST), Blood urea nitrogen (BUN), Serum creatinine (SCR), Serum uric Acid (SUA), Glomerular filtration rate (GFR) and Kalium (K) were similar among the groups (Table 2). 5 Astragalus granulesinhibited TNF-α and IL-1β generation in DKD patients. ELISA was performed to detect the levels of TNF-α and IL-1β in blood of DKD patients. With 12 weeks treatment, astragalus granules and losartan treatment strikingly inhibited the increase of TNF-α and IL-1β in DKD rats (P&lt;0.05)(Figure 6). But there was no significantly different in control group.
DOI: 10.21227/51r7-mn35
title: Synthetic Event Logs for Concept Drift Detection

description: Real life business processes change over time, in both planned and unexpected ways. These changes over time are called concept drifts and its detection is a big challenge in process mining since the inherent complexity of the data makes difficult distinguishing between a change and an anomalous execution. The following logs were generated synthetically in order to prove the quality of different concept drift detection algorithms.
DOI: 10.5281/zenodo.3272929
title: Binary black-hole simulation SXS:BBH:1497

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272930
title: Binary black-hole simulation SXS:BBH:1446

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272931
title: Binary black-hole simulation SXS:BBH:1443

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272932
title: Binary black-hole simulation SXS:BBH:1477

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272933
title: Binary black-hole simulation SXS:BBH:1496

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272934
title: Binary black-hole simulation SXS:BBH:1419

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273425
title: Binary black-hole simulation SXS:BBH:2043

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273426
title: Binary black-hole simulation SXS:BBH:1639

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273427
title: Binary black-hole simulation SXS:BBH:1685

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273428
title: Binary black-hole simulation SXS:BBH:1915

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273429
title: Binary black-hole simulation SXS:BBH:2055

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273430
title: Binary black-hole simulation SXS:BBH:1684

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273431
title: Binary black-hole simulation SXS:BBH:1572

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275566
title: Binary black-hole simulation SXS:BBH:1070

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275569
title: Binary black-hole simulation SXS:BBH:0817

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275572
title: Binary black-hole simulation SXS:BBH:0955

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275575
title: Binary black-hole simulation SXS:BBH:0856

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275579
title: Binary black-hole simulation SXS:BBH:0776

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275580
title: Binary black-hole simulation SXS:BBH:0826

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272935
title: Binary black-hole simulation SXS:BBH:1492

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272936
title: Binary black-hole simulation SXS:BBH:1507

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272937
title: Binary black-hole simulation SXS:BBH:1451

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272938
title: Binary black-hole simulation SXS:BBH:1490

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272939
title: Binary black-hole simulation SXS:BBH:1475

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273432
title: Binary black-hole simulation SXS:BBH:1686

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273433
title: Binary black-hole simulation SXS:BBH:1789

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273434
title: Binary black-hole simulation SXS:BBH:1762

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273435
title: Binary black-hole simulation SXS:BBH:1679

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273436
title: Binary black-hole simulation SXS:BBH:1635

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273437
title: Binary black-hole simulation SXS:BBH:1702

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3274570
title: Binary black-hole simulation SXS:BBH:0296

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275584
title: Binary black-hole simulation SXS:BBH:0687

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275585
title: Binary black-hole simulation SXS:BBH:0900

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275586
title: Binary black-hole simulation SXS:BBH:0739

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275591
title: Binary black-hole simulation SXS:BBH:0655

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275593
title: Binary black-hole simulation SXS:BBH:0938

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275596
title: Binary black-hole simulation SXS:BBH:1063

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275600
title: Binary black-hole simulation SXS:BBH:0762

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3296467
title: Dataset of questionnaires for teachers developed in the frame of ENVRIPLUS project

description: The questionnaire is addressed to teachers in order to catch their needs and help in feeding the platform with targeted contents. The first part of the questionnaire focuses on objective information about the formal, quantitative and qualitative position of science class in schools, and the content and methods of teaching in different countries. The second part of the questionnaire investigates personal teacher experiences and their views on what can improve training offer about environmental science lessons and courses. The third part investigates on tools teachers have and use and on what they would have. Questionnaires were collected based on the GITF international network and in the occasion of training events for Italian teachers.This action is undertaken for the developing of Task 15.5, aimed at providing secondary school teachers and students with an e-Training Platform, based on scientific themes related to Research Infrastructures for the Environmental Sector participating to ENVRIplus project. The main actions are aimed to design, structure, develop and execute a Training course for teachers to the use of the multimedia platform.
description: {"references": ["2)\tD'Addezio, G., Locritani, M., 2018. Teacher experiences, views and proposals: first results from a questionnaire developed in the frame of ENVRIPLUS project. American Geophysical Union, Fall Meeting 2018, abstract #ED13D-0779."]}
DOI: 10.5281/zenodo.3296468
title: Dataset of questionnaires for teachers developed in the frame of ENVRIPLUS project

description: The questionnaire is addressed to teachers in order to catch their needs and help in feeding the platform with targeted contents. The first part of the questionnaire focuses on objective information about the formal, quantitative and qualitative position of science class in schools, and the content and methods of teaching in different countries. The second part of the questionnaire investigates personal teacher experiences and their views on what can improve training offer about environmental science lessons and courses. The third part investigates on tools teachers have and use and on what they would have. Questionnaires were collected based on the GITF international network and in the occasion of training events for Italian teachers.This action is undertaken for the developing of Task 15.5, aimed at providing secondary school teachers and students with an e-Training Platform, based on scientific themes related to Research Infrastructures for the Environmental Sector participating to ENVRIplus project. The main actions are aimed to design, structure, develop and execute a Training course for teachers to the use of the multimedia platform.
description: {"references": ["2)\tD'Addezio, G., Locritani, M., 2018. Teacher experiences, views and proposals: first results from a questionnaire developed in the frame of ENVRIPLUS project. American Geophysical Union, Fall Meeting 2018, abstract #ED13D-0779."]}
DOI: 10.5523/bris.3l2y3f6tdptcr2rcseeei6b26h
title: Ontogenetic sequence of Psittacosaurus lujiatunensis braincases
title: 3D models of three Psittacosaurus lujiatunensis braincases

description: Three segmented braincases (hatchling, IVPP V15451; juvenile, IVPP V22647; adult IVPP V12617) of Psittacosaurus lujiatunensis. Specimens scanned are housed in the Institute of Vertebrate Paleontology and Paleoanthropology, Beijing. Elements include: basioccipital (light green), basisphenoid (purple), supraoccipital (pink), paroccipital processed (yellow), parietal (red), frontal (light blue), prootic (dark green), laterosphenoid (dark blue), orbitosphenoid (orange).
DOI: 10.17632/4mm5w8w99s.1
title: dataset for the paper "A supply-demand model of the size of public sector and Wagner's law"

description: Data collected from open sources, such as World Bank Development indicators
DOI: 10.17632/rpr7yykzx8.1
title: Hot deformation data for Haynes 214, Haynes 230 and Inconel 740H

description: Gleeble iso-T true stress-strain data at 1000C-1200C in 50C steps for 0.01/s - 1/s; EBSD IPF and BC of geometric centers of sectioned samples; ThermoCalc 2015 calculated property diagrams for stable phases and data tables with compositional changes vs. T for all phases
DOI: 10.5281/zenodo.3272940
title: Binary black-hole simulation SXS:BBH:1493

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272941
title: Binary black-hole simulation SXS:BBH:1506

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272942
title: Binary black-hole simulation SXS:BBH:1423

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272943
title: Binary black-hole simulation SXS:BBH:1481

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272944
title: Binary black-hole simulation SXS:BBH:1452

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272945
title: Binary black-hole simulation SXS:BBH:1428

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272946
title: Binary black-hole simulation SXS:BBH:1471

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272947
title: Binary black-hole simulation SXS:BBH:1458

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272948
title: Binary black-hole simulation SXS:BBH:1444

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273438
title: Binary black-hole simulation SXS:BBH:1928

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273441
title: Binary black-hole simulation SXS:BBH:1771

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273442
title: Binary black-hole simulation SXS:BBH:1956

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273443
title: Binary black-hole simulation SXS:BBH:1843

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273444
title: Binary black-hole simulation SXS:BBH:1814

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275601
title: Binary black-hole simulation SXS:BBH:1075

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275602
title: Binary black-hole simulation SXS:BBH:0922

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275604
title: Binary black-hole simulation SXS:BBH:0852

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275605
title: Binary black-hole simulation SXS:BBH:0910

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275607
title: Binary black-hole simulation SXS:BBH:0636

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275608
title: Binary black-hole simulation SXS:BBH:1007

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275609
title: Binary black-hole simulation SXS:BBH:0748

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/6bd45hb393.1
title: Relationships Between Sibling Physical Abuse and Lifetime Aggression after Using Statistical Controls for Poly-Victimization

description: This data set was obtained through a survey on Amazon's Mechanical Turk (MTurk) that included questions about various forms of childhood maltreatment; the Buss-Perry Aggression Questionnaire; and the Lifetime Assessment of Violent Acts. Questions about attachment and conduct disturbance were also included as a secondary objective. Variables have already been computed. SPA= Sibling Physical Abuse; CPA=Childhood Physical Abuse; CSA= Childhood Sexual Abuse; OPA= Observed Parental Violence; BULL=Bullying; CEA= Childhood Emotional Abuse. BPAQ and LAVA variables are labeled in accordance with labels used in their respective developmental studies. Results showed that sibling physical abuse, occurring as infrequently as once per year, was associated with a range of lifetime aggression indicators.
DOI: 10.17632/86j5dmrptz.1
title: Data for: The Distance Perception During Self-Movement

description: Data from two experiments on distance perception in open fields. In these experiments, the observers perform the task in three conditions: i) running on a treadmill, with the visual field clear of obstacles; ii) standing on the treadmill but looking at the target through a transparent screen in which a visual stimulus that induced vection was presented; iii) standing on the treadmill with the visual field free of obstacles (control condition).
DOI: 10.17632/zsy2m2s637.1
title: Data for: Biaxial Mechanics of 3D Fiber Deposited Ply-Laminate Scaffolds for Soft Tissue Engineering Part I: Experimental Evaluation

description: Data for: Biaxial Mechanics of 3D Fiber Deposited Ply-Laminate Scaffolds for Soft Tissue Engineering Part I: Experimental Evaluation
DOI: 10.5281/zenodo.3272949
title: Binary black-hole simulation SXS:BBH:1503

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272950
title: Binary black-hole simulation SXS:BBH:1505

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272951
title: Binary black-hole simulation SXS:BBH:1441

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272952
title: Binary black-hole simulation SXS:BBH:1486

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272953
title: Binary black-hole simulation SXS:BBH:1434

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272954
title: Binary black-hole simulation SXS:BBH:1491

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3272955
title: Binary black-hole simulation SXS:BBH:1847

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273445
title: Binary black-hole simulation SXS:BBH:1787

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273446
title: Binary black-hole simulation SXS:BBH:1593

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273447
title: Binary black-hole simulation SXS:BBH:1626

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273448
title: Binary black-hole simulation SXS:BBH:1662

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273449
title: Binary black-hole simulation SXS:BBH:1715

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273450
title: Binary black-hole simulation SXS:BBH:1863

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273451
title: Binary black-hole simulation SXS:BBH:1746

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3273452
title: Binary black-hole simulation SXS:BBH:1952

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3274571
title: Binary black-hole simulation SXS:BBH:0212

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275610
title: Binary black-hole simulation SXS:BBH:0832

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275611
title: Binary black-hole simulation SXS:BBH:1051

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275612
title: Binary black-hole simulation SXS:BBH:1054

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275615
title: Binary black-hole simulation SXS:BBH:0819

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275616
title: Binary black-hole simulation SXS:BBH:0675

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275619
title: Binary black-hole simulation SXS:BBH:0665

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275620
title: Binary black-hole simulation SXS:BBH:0882

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275623
title: Binary black-hole simulation SXS:BBH:0987

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3275624
title: Binary black-hole simulation SXS:BBH:1047

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/gnn4rvxbr8.1
title: Kasugai et al Neuron 2019 D-16-02077R1

description: Associative learning is thought to involve different forms of activity-dependent synaptic plasticity. While previous studies have mostly focused on learning-related changes occurring at excitatory glutamatergic synapses, we found that associative learning such as fear conditioning also entails long-lasting functional and structural plasticity of GABAergic synapses onto pyramidal neurons of the murine basal amygdala. Fear conditioning-mediated structural remodeling of GABAergic synapses was associated with a change in mIPSC kinetics and an increase in the fraction of synaptic benzodiazepine-sensitive (BZD) GABAA receptors containing the α2 subunit, without altering the intrasynaptic distribution and overall amount of BZD-GABAA receptors. These structural and functional synaptic changes were partly reversed by extinction training. These findings provide evidence that associative learning, such as Pavlovian fear conditioning and extinction, sculpts inhibitory synapses to regulate inhibition of active neuronal networks, a process which may tune amygdala circuit responses to threat.