cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18738/t8/ckzusk/9dll9r
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DOI: 10.18738/t8/ckzusk/9xcqns
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DOI: 10.18738/t8/ckzusk/c1hlya
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DOI: 10.18738/t8/ckzusk/ckel0n
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DOI: 10.18738/t8/ckzusk/eqqy7q
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DOI: 10.18738/t8/ckzusk/gdzb6e
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DOI: 10.18738/t8/ckzusk/gmpdx0
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DOI: 10.18738/t8/ckzusk/iga3ob
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DOI: 10.18738/t8/ckzusk/lblvxo
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DOI: 10.18738/t8/ckzusk/nqxjwu
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DOI: 10.18738/t8/ckzusk/qjbzel
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DOI: 10.18738/t8/ckzusk/sdfgny
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DOI: 10.18738/t8/ckzusk/sedexk
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DOI: 10.18738/t8/ckzusk/urbvd8
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DOI: 10.18738/t8/ckzusk/vwevmv
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DOI: 10.18738/t8/ckzusk/wijfdq
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DOI: 10.18738/t8/ckzusk/xqh5bc
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DOI: 10.18738/t8/ckzusk/yrdo6k
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DOI: 10.18738/t8/ckzusk/zavwvm
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DOI: 10.18738/t8/ckzusk/zu8vlc
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DOI: 10.18738/t8/ckzusk/2pqe2p
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DOI: 10.18738/t8/ckzusk/2x6pho
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DOI: 10.18738/t8/ckzusk/4cmoj8
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DOI: 10.18738/t8/ckzusk/5rhb3e
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DOI: 10.18738/t8/ckzusk/bnabyq
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DOI: 10.18738/t8/ckzusk/eynnmk
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DOI: 10.18738/t8/ckzusk/g6cywa
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DOI: 10.18738/t8/ckzusk/h44tvo
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DOI: 10.18738/t8/ckzusk/i1kvic
title: var_clrsky_aij_JUL2005_E213TALUc.nc

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DOI: 10.18738/t8/ckzusk/ksb4my
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DOI: 10.18738/t8/ckzusk/n3k8lq
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DOI: 10.18738/t8/ckzusk/odntgt
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DOI: 10.18738/t8/ckzusk/ofn3wi
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DOI: 10.18738/t8/ckzusk/rgscoi
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DOI: 10.18738/t8/ckzusk/rhjpxe
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DOI: 10.18738/t8/ckzusk/rinbgq
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description: :unav
DOI: 10.18738/t8/ckzusk/rpqzun
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DOI: 10.18738/t8/ckzusk/s4hqb4
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DOI: 10.18738/t8/ckzusk/s8k1kv
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description: :unav
DOI: 10.18738/t8/ckzusk/uotgsd
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DOI: 10.18738/t8/ckzusk/wav017
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description: :unav
DOI: 10.18738/t8/ckzusk/yaklyc
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description: :unav
DOI: 10.18738/t8/ckzusk/030ono
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description: :unav
DOI: 10.18738/t8/ckzusk/4zknl3
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description: :unav
DOI: 10.18738/t8/ckzusk/63p0ww
title: var_clrsky_aij_JUN1864_E213TALUb.nc

description: :unav
DOI: 10.18738/t8/ckzusk/6jae0y
title: var_clrsky_aij_JUL2005_E213TALUe.nc

description: :unav
DOI: 10.18738/t8/ckzusk/aukkws
title: var_clrsky_aij_JUN2010_E213TALUd.nc

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DOI: 10.18738/t8/ckzusk/c9rlhf
title: var_clrsky_aij_JUL2010_E213TALUe.nc

description: :unav
DOI: 10.18738/t8/ckzusk/chzx0j
title: var_clrsky_aij_JUL2012_E213TALUc.nc

description: :unav
DOI: 10.18738/t8/ckzusk/crbjz1
title: var_clrsky_aij_JUN2012_E213TALUd.nc

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DOI: 10.18738/t8/ckzusk/eldqop
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DOI: 10.18738/t8/ckzusk/eyb7yd
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DOI: 10.18738/t8/ckzusk/eziu9u
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DOI: 10.18738/t8/ckzusk/fj9izh
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DOI: 10.18738/t8/ckzusk/ge7dgr
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DOI: 10.18738/t8/ckzusk/i6tdnw
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DOI: 10.18738/t8/ckzusk/i99dge
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DOI: 10.18738/t8/ckzusk/mtezas
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DOI: 10.18738/t8/ckzusk/onfj6u
title: var_clrsky_aij_JUN2011_E213TALUe.nc

description: :unav
DOI: 10.18738/t8/ckzusk/qmnc2l
title: var_clrsky_aij_JUN1861_E213TALUa.nc

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DOI: 10.18738/t8/ckzusk/rcx2ey
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DOI: 10.18738/t8/ckzusk/uga4wm
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description: :unav
DOI: 10.18738/t8/ckzusk/wfq4nr
title: var_clrsky_aij_JUL2014_E213TALUc.nc

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DOI: 10.18738/t8/ckzusk/wmnpkp
title: var_clrsky_aij_JUN2002_E213TALUa.nc

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DOI: 10.18738/t8/ckzusk/wsfg6b
title: var_clrsky_aij_JUN2009_E213TALUb.nc

description: :unav
DOI: 10.18738/t8/ckzusk/xu7lwr
title: var_clrsky_aij_JUL2008_E213TALUa.nc

description: :unav
DOI: 10.18738/t8/ckzusk/y91gph
title: var_clrsky_aij_JUL2011_E213TALUc.nc

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DOI: 10.18738/t8/ckzusk/ybdvsv
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DOI: 10.18738/t8/ckzusk/ye4bqc
title: var_clrsky_aij_JUN1853_E213TALUd.nc

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DOI: 10.18738/t8/ckzusk/zcsphd
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DOI: 10.18738/t8/ckzusk/0dp38g
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DOI: 10.18738/t8/ckzusk/49v5mn
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DOI: 10.18738/t8/ckzusk/7oqui2
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DOI: 10.18738/t8/ckzusk/7vqrdr
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DOI: 10.18738/t8/ckzusk/e8eufd
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DOI: 10.18738/t8/ckzusk/eg5ee9
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DOI: 10.18738/t8/ckzusk/fe1uvf
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DOI: 10.18738/t8/ckzusk/fem0a5
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DOI: 10.18738/t8/ckzusk/fnvi0o
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DOI: 10.18738/t8/ckzusk/gv6m6l
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DOI: 10.18738/t8/ckzusk/hf9vxi
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DOI: 10.18738/t8/ckzusk/kigqpl
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DOI: 10.18738/t8/ckzusk/mdrtsg
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DOI: 10.18738/t8/ckzusk/mojwfb
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DOI: 10.18738/t8/ckzusk/ok59j6
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DOI: 10.18738/t8/ckzusk/pzauhx
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DOI: 10.18738/t8/ckzusk/rtg55g
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DOI: 10.18738/t8/ckzusk/tc4s5e
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DOI: 10.18738/t8/ckzusk/v6z0xw
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DOI: 10.18738/t8/ckzusk/z9ghq6
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DOI: 10.18738/t8/ckzusk/bqly9e
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DOI: 10.18738/t8/ckzusk/e4sz9m
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DOI: 10.18738/t8/ckzusk/ebtdbg
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DOI: 10.18738/t8/ckzusk/fh7vxh
title: var_clrsky_aij_JUN2003_E213TALUd.nc

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DOI: 10.18738/t8/ckzusk/h2cm9v
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DOI: 10.18738/t8/ckzusk/hevylg
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DOI: 10.18738/t8/ckzusk/jxaigc
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DOI: 10.18738/t8/ckzusk/ssujdl
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title: var_clrsky_aij_JUN2005_E213TALUb.nc

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DOI: 10.18738/t8/ckzusk/bhb0lz
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description: :unav
DOI: 10.18738/t8/ckzusk/js8yol
title: var_clrsky_aij_JUN2014_E213TALUe.nc

description: :unav
DOI: 10.18738/t8/ckzusk/ncq7v0
title: var_clrsky_aij_JUN2008_E213TALUa.nc

description: :unav
DOI: 10.18738/t8/ckzusk/r05ntk
title: var_clrsky_aij_JUN2009_E213TALUd.nc

description: :unav
DOI: 10.18738/t8/ckzusk/rdsafu
title: var_clrsky_aij_JUN2003_E213TALUa.nc

description: :unav
DOI: 10.18738/t8/ckzusk/spfqfl
title: var_clrsky_aij_JUN2000_E213TALUb.nc

description: :unav
DOI: 10.18738/t8/ckzusk/tdzwds
title: var_clrsky_aij_JUN2001_E213TALUa.nc

description: :unav
DOI: 10.18738/t8/ckzusk/vqmfgz
title: var_clrsky_aij_JUN2008_E213TALUc.nc

description: :unav
DOI: 10.18738/t8/ckzusk/yzckqg
title: var_clrsky_aij_JUN2011_E213TALUd.nc

description: :unav
DOI: 10.18738/t8/ckzusk/zatevw
title: var_clrsky_aij_JUN2009_E213TALUe.nc

description: :unav
DOI: 10.18738/t8/ckzusk/zvuabw
title: var_clrsky_aij_JUN2004_E213TALUa.nc

description: :unav
DOI: 10.5519/qd.88u7vukx
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (302 records)
DOI: 10.5281/zenodo.2581607
title: 2010\London\KSS45W Ceilometer A,C,D Rawdata

description: 2010\London\KSS45W\Ceilometer Rawdata
Type: Vaisala Ceilometer CL31 Instrument A, C,D
Files: Are Zipped by month
Internal  Filenames:
   Example A8112913.dat
   Letter: Ceilometer identifier: A
   Year:8  >>>> 2008
   Month : 11
   Date: 29
   Hour:13
   Format: Ascii

See Vaisala CL31 Manual

 Site: KSS45W
Country UK
City London
Location King’s College London (K)/ Strand Campus (S)/ Strand Building (S)
Height: on roof
Location King’s College London (K)/ Strand Campus (S)/ Strand Building (S) 45W  - 45 m W of KSS tower
Height: on roof - up on (half floor >1 m)


 


Lidar (Barlow)
Publications
Kotthaus S, CSB Grimmond 2018: Atmospheric Boundary Layer Characteristics from Ceilometer Measurements Part 1: A new method to track mixed layer height and classify clouds QJRMS https://doi.org/10.1002/qj.329
Kotthaus S, E O'Connor, C Münkel, C Charlton-Perez, CSB Grimmond 2016: Recommendations for processing atmospheric backscatter profiles from Vaisala CL31 Ceilometers Atmos. Meas. Tech., 9, 3769-3791, 10.5194/amt-9-3769-2016   
Loridan T, CSB Grimmond, BD Offerle, DT Young, T Smith, L Järvi, F Lindberg 2011: Local-Scale Urban Meteorological Parameterization Scheme (LUMPS): longwave radiation parameterization & seasonality related developments J. of Applied Meteorology & Climatology. 50: 185-202 doi: 10.1175/2010äMC2474.1
DOI: 10.5281/zenodo.2581608
title: 2010\London\KSS45W Ceilometer A,C,D Rawdata

description: 2010\London\KSS45W\Ceilometer Rawdata
Type: Vaisala Ceilometer CL31 Instrument A, C,D
Files: Are Zipped by month
Internal  Filenames:
   Example A8112913.dat
   Letter: Ceilometer identifier: A
   Year:8  >>>> 2008
   Month : 11
   Date: 29
   Hour:13
   Format: Ascii

See Vaisala CL31 Manual

 Site: KSS45W
Country UK
City London
Location King’s College London (K)/ Strand Campus (S)/ Strand Building (S)
Height: on roof
Location King’s College London (K)/ Strand Campus (S)/ Strand Building (S) 45W  - 45 m W of KSS tower
Height: on roof - up on (half floor >1 m)


 


Lidar (Barlow)
Publications
Kotthaus S, CSB Grimmond 2018: Atmospheric Boundary Layer Characteristics from Ceilometer Measurements Part 1: A new method to track mixed layer height and classify clouds QJRMS https://doi.org/10.1002/qj.329
Kotthaus S, E O'Connor, C Münkel, C Charlton-Perez, CSB Grimmond 2016: Recommendations for processing atmospheric backscatter profiles from Vaisala CL31 Ceilometers Atmos. Meas. Tech., 9, 3769-3791, 10.5194/amt-9-3769-2016   
Loridan T, CSB Grimmond, BD Offerle, DT Young, T Smith, L Järvi, F Lindberg 2011: Local-Scale Urban Meteorological Parameterization Scheme (LUMPS): longwave radiation parameterization & seasonality related developments J. of Applied Meteorology & Climatology. 50: 185-202 doi: 10.1175/2010äMC2474.1
DOI: 10.18738/t8/z7tcae/mkgbsm
title: LSK014_32.20um_8bu_540x540x1150.raw292.tif
DOI: 10.15468/dl.gex3fr
title: Occurrence Download

description: A dataset containing 123058 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bombus terrestris (Linnaeus, 1758), Andrena haemorrhoa (Fabricius, 1781), Xylocopa appendiculata Smith, 1852, Trigona carbonaria Smith, 1854, Melipona beecheii Bennett, 1831, Apis andreniformis Smith, 1857, Apis florea Fabricius, 1787, Apis laboriosa Smith, 1871, Apis dorsata Fabricius, 1793, Apis cerana Fabricius, 1793, Apis mellifera Linnaeus, 1758)",
 "Year is 2020"
 ]
}

 The dataset includes 123058 records from 339 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002949-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26302/sshade/experiment_lb_20250307_001
title: Vis-NIR reflectance spectra (i=0°, e=30°) measured at ambient conditions of pressure and temperature of Murchison (CM2 chondrite) shocked at 5 GPa, 10 GPa, 20 GPa and 40 GPa
DOI: 10.18738/t8/z7tcae/y5soqq
title: LSK014_32.20um_8bu_540x540x1150.raw131.tif
DOI: 10.5281/zenodo.14889067
title: Requirements Extraction from MBSE: SLR data selection

description: This dataset contains the selection of articles and data extraction results from the Systematic Literature Review (SLR) conducted on Requirements Extraction from MBSE topic. The dataset includes information on the study selection, quality assessment, inclusion/exclusion criteria, and key extracted data from the selected studies.

The dataset is structured as follows:



Article Selection: Metadata of articles retrieved from databases, including title, authors, publication year, and reason for inclusion/exclusion.

Quality Assessment: Evaluation criteria applied to assess the rigor and relevance of each study.

Data Extraction: Key findings from the selected articles, such as motivation, research method, application context, results, and conclusions. All plots referred to each property are in this dataset.


This dataset provides valuable insights into the research landscape and facilitates further analysis and replication of the systematic review process.
DOI: 10.5281/zenodo.14889068
title: Requirements Extraction from MBSE: SLR data selection

description: This dataset contains the selection of articles and data extraction results from the Systematic Literature Review (SLR) conducted on Requirements Extraction from MBSE topic. The dataset includes information on the study selection, quality assessment, inclusion/exclusion criteria, and key extracted data from the selected studies.

The dataset is structured as follows:



Article Selection: Metadata of articles retrieved from databases, including title, authors, publication year, and reason for inclusion/exclusion.

Quality Assessment: Evaluation criteria applied to assess the rigor and relevance of each study.

Data Extraction: Key findings from the selected articles, such as motivation, research method, application context, results, and conclusions. All plots referred to each property are in this dataset.


This dataset provides valuable insights into the research landscape and facilitates further analysis and replication of the systematic review process.
DOI: 10.6084/m9.figshare.28575020
title: Phytochemical profiling, <i>in silico</i> molecular docking and ADMET prediction of alkaloid rich fraction of <i>Elaeocarpus angustifolius</i> blume seeds against Alzheimer’s disease

description: The limitations of current Alzheimer’s disease (AD) therapies necessitate novel treatment approaches. <i>Elaeocarpus angustifolius</i> Blume, a plant traditionally used in India for neurological disorders, was investigated for its therapeutic potential in AD. <i>E. angustifolius</i> alkaloid-rich fraction (EAF) was analysed using LCMS and GCMS, identifying 66 phytochemicals. Compounds were evaluated using Schrodinger software against key AD targets obtained from Protein Data Bank (PDB), including recombinant human acetylcholinesterase (PDB ID: 4EY7), β-secretase (PDB ID: 6C2I), TNF-α converting enzyme (PDB ID: 2FV5), glycogen synthase kinase 3 (PDB ID: 1Q5K), and amyloid-β precursor protein (PDB ID: 1AAP). Among the identified compounds, (+)-Elaeocarpine, Genistein, Caffeic acid, Avenalumic acid, Verimol A, Apigenin 7-glucoside, and (1xi,3xi)-1,2,3,4-Tetrahydro-1-methyl-β-carboline-3-carboxylic acid exhibited the highest binding affinities. ADMET analysis confirmed favourable profiles for these phytochemicals. The study suggests that these compounds present in EAF could be promising candidates for developing novel AD therapies.
DOI: 10.18738/t8/z7tcae/mwimi8
title: CalibrationVS.m
DOI: 10.18738/t8/z7tcae/6mirdm
title: calPickVS_SS304_fun0_76.2.mat
DOI: 10.18738/t8/z7tcae/cy4jtv
title: LSK014_32.20um_8bu_540x540x1150.raw197.tif
DOI: 10.18738/t8/z7tcae/zpucpm
title: LSK014_32.20um_8bu_540x540x1150.raw193.tif
DOI: 10.18738/t8/z7tcae/nvfk7d
title: dataMP_LSK059_fun0_38.2.mat
DOI: 10.5281/zenodo.14882222
title: GiroE 2024: Smartwatch data from non-competitive athletes during an e-bike multi-stage race

description: The dataset presents data collected using nine Garmin fēnix® 7 smartwatches during the GiroE 2024, an e-bike event running alongside the Giro d'Italia. The data was logged using a custom application that recorded raw sensor data at maximum frequency, including GNSS, heart rate, altitude, compass, accelerometer, and temperature. Collected as part of a national research programme funded by the Italian Ministry of University and Research, the dataset could be of interests for studies on cyclist behavior, road conditions, and heart rate modeling. It can aid smartwatch data integration research and possibly serve as a reference for clinical trials in similar conditions.