cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/kam-2wn-dsn
title: Anthyllis lotoides L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/p8g-j9w-8n5
title: Ononis natrix subsp. ramosissima (Desf.) Batt.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/9yq-wyh-vxz
title: Festuca L.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/b2b-lgf-ctq
title: Minuartia rimarum (Boiss. & Balansa) Mattf.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.3535/c5n-hce-gcq
title: Poa badensis Haenke ex Willd.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.13021/orc2020/xxlvxm/ezmw8y
title: P05.zip
DOI: 10.13021/orc2020/xxlvxm/t7ktf6
title: P07.zip
DOI: 10.13021/orc2020/xxlvxm/hyxvwr
title: P04.zip
DOI: 10.13021/orc2020/xxlvxm/jhvrdh
title: P02.zip
DOI: 10.13021/orc2020/xxlvxm/fj1uln
title: P01.zip
DOI: 10.15468/dl.9yrafv
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is India",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Uncia uncia (Schreber, 1775)",
 "Year 2010-2025"
 ]
}

 The dataset includes 62 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005601-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13021/orc2020/xxlvxm/ejbqai
title: P19.zip
DOI: 10.13021/orc2020/xxlvxm/1geviz
title: P03.zip
DOI: 10.13021/orc2020/xxlvxm/9aqj3n
title: P06.zip
DOI: 10.13021/orc2020/xxlvxm/b1gyww
title: P14.zip
DOI: 10.13021/orc2020/xxlvxm/cwul6p
title: P13.zip
DOI: 10.13021/orc2020/xxlvxm/gvxnqb
title: P16.zip
DOI: 10.13021/orc2020/xxlvxm/hwcdv5
title: C01.zip
DOI: 10.13021/orc2020/xxlvxm/oqrtjn
title: C23.zip
DOI: 10.13021/orc2020/xxlvxm/ykcg8e
title: C03.zip
DOI: 10.13021/orc2020/xxlvxm/9arwbh
title: C04.zip
DOI: 10.13021/orc2020/xxlvxm/6puvag
title: C05.zip
DOI: 10.13021/orc2020/xxlvxm/wg2yaw
title: C06.zip
DOI: 10.13021/orc2020/xxlvxm/pycprn
title: C11.zip
DOI: 10.13021/orc2020/xxlvxm/eflztu
title: C09.zip
DOI: 10.13021/orc2020/xxlvxm/uwnqax
title: C12.zip
DOI: 10.13021/orc2020/xxlvxm/aze6rm
title: R02.zip
DOI: 10.13021/orc2020/xxlvxm/6nhm17
title: R04.zip
DOI: 10.13021/orc2020/xxlvxm/kpzjs6
title: R05.zip
DOI: 10.13021/orc2020/xxlvxm/ayfkod
title: R06.zip
DOI: 10.13021/orc2020/xxlvxm/r4u9oy
title: R17.zip
DOI: 10.13021/orc2020/xxlvxm/etdg5j
title: H22.zip
DOI: 10.25345/c5zc7s639
title: MassIVE MSV000096898 - Chemoproteomic Profiling of Isoprenoid-Pyrophosphate Interacting Proteins with Photoaffinity Probes
title: This dataset contains the LC-MS/MS data of three biological replicates of FPP or GGPP photoaffinity probe labeled proteins. Each replicate contains a forward and a reverse SILAC-labeled competition experiments.
DOI: 10.13021/orc2020/xxlvxm/7uf8v8
title: H25.zip
DOI: 10.13021/orc2020/xxlvxm/7uvjtn
title: H26.zip
DOI: 10.13021/orc2020/xxlvxm/jpptgs
title: R26.zip
DOI: 10.13021/orc2020/xxlvxm/sfiv61
title: R28.zip
DOI: 10.13021/orc2020/xxlvxm/vmnvuh
title: R27.zip
DOI: 10.13021/orc2020/xxlvxm/qkgtl9
title: R29.zip
DOI: 10.13021/orc2020/xxlvxm/cqkkro
title: R30.zip
DOI: 10.13021/orc2020/xxlvxm/fu4njd
title: R32.zip
DOI: 10.13021/orc2020/xxlvxm/k5zne8
title: H27.zip
DOI: 10.13021/orc2020/xxlvxm/ii4t4j
title: H02.zip
DOI: 10.13021/orc2020/xxlvxm/laerj0
title: H28.zip
DOI: 10.13021/orc2020/xxlvxm/bvoyov
title: H03.zip
DOI: 10.13021/orc2020/xxlvxm/k80wew
title: H04.zip
DOI: 10.13021/orc2020/xxlvxm/h9nfnz
title: H05.zip
DOI: 10.13021/orc2020/xxlvxm/swfg9h
title: H06.zip
DOI: 10.13021/orc2020/xxlvxm/j9cjrx
title: H29.zip
DOI: 10.13021/orc2020/xxlvxm/teilmv
title: H30.zip
DOI: 10.13021/orc2020/xxlvxm/3xbrye
title: H32.zip
DOI: 10.13021/orc2020/xxlvxm/lbjpqu
title: H34.zip
DOI: 10.21227/54mz-ne70
title: 3D Human Pose Estimation Using Ultra-low-resolution Thermal Images

description: Can we perceive the three-dimensional posture of the whole human body solely from extremely low-resolution thermal images (e.g., $8\times8$-pixels)?This paper investigates the possibility of this challenging task.Thermal images capture only the intensity of radiation, making them less likely to contain personal information such as facial or clothing features.Thermal sensors are commonly integrated into daily-use appliances, such as air conditioners, automatic doors, and elevators.Considering these advantages, we propose a framework for estimating three-dimensional (3D) human pose by utilizing very low resolution (only 8-pixel square) thermal images. This not only reduces the inclusion of personal information, but also opens up memory-efficient measurement capabilities with potential applications in various fields.Compared to conventional cameras, thermal images are more susceptible to variations in room temperature and subject-specific differences, such as physical build or basal body temperature.To address this challenge, we apply attribute-independent feature extraction. Specifically, we employ discriminators designed to perform feature extraction independent of subject and ambient temperature, ensuring that the extracted features are invariant to these attributes. This approach enhances the robustness of our method by enabling it to focus on the core posture-related features rather than variations due to subject or ambient temperature differences.
DOI: 10.13021/orc2020/xxlvxm/zvzhvr
title: C02.zip
DOI: 10.13021/orc2020/xxlvxm/v1lw4p
title: H22.zip
DOI: 10.13021/orc2020/xxlvxm/7t9ulq
title: H28.zip
DOI: 10.13021/orc2020/xxlvxm/7tmtos
title: H26.zip
DOI: 10.13021/orc2020/xxlvxm/wvoq2h
title: H30.zip
DOI: 10.13021/orc2020/xxlvxm/0flvps
title: H29.zip
DOI: 10.13021/orc2020/xxlvxm/6qvzfc
title: H25.zip
DOI: 10.13021/orc2020/xxlvxm/hofjeb
title: H27.zip
DOI: 10.13021/orc2020/xxlvxm/jc7pr9
title: H42.zip
DOI: 10.13021/orc2020/xxlvxm/6himz5
title: H36.zip
DOI: 10.13021/orc2020/xxlvxm/eosfpa
title: H34.zip
DOI: 10.13021/orc2020/xxlvxm/zzcwvo
title: H40.zip
DOI: 10.13021/orc2020/xxlvxm/6v6pfw
title: H43.zip
DOI: 10.13021/orc2020/xxlvxm/qreds4
title: H39.zip
DOI: 10.15468/dl.8u4fwn
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Prunus glandulosa Torr. & A.Gray"
 ]
}

 The dataset includes 50 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005602-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13021/orc2020/xxlvxm/0mymmi
title: H37.zip
DOI: 10.13021/orc2020/xxlvxm/mhnxax
title: H35.zip
DOI: 10.13021/orc2020/xxlvxm/gs4seq
title: H38.zip
DOI: 10.13021/orc2020/xxlvxm/3rmky1
title: H32.zip
DOI: 10.13021/orc2020/xxlvxm/gffybt
title: H02.zip
DOI: 10.13021/orc2020/xxlvxm/vqtnzg
title: H06.zip
DOI: 10.13021/orc2020/xxlvxm/89uyfe
title: H05.zip
DOI: 10.13021/orc2020/xxlvxm/ckg9jj
title: H03.zip
DOI: 10.13021/orc2020/xxlvxm/1t1m19
title: H04.zip
DOI: 10.13021/orc2020/xxlvxm/voi81h
title: H20.zip
DOI: 10.13021/orc2020/xxlvxm/c8rt1d
title: H18.zip
DOI: 10.13021/orc2020/xxlvxm/q9nqfz
title: H17.zip
DOI: 10.13021/orc2020/xxlvxm/tngw1i
title: H16.zip
DOI: 10.13021/orc2020/xxlvxm/znjef2
title: H07.zip
DOI: 10.13021/orc2020/xxlvxm/verekw
title: H15.zip
DOI: 10.13021/orc2020/xxlvxm/ywirii
title: H10.zip
DOI: 10.13021/orc2020/xxlvxm/2d8kym
title: H11.zip
DOI: 10.13021/orc2020/xxlvxm/shw2sk
title: H21.zip
DOI: 10.13021/orc2020/xxlvxm/neyud8
title: H19.zip
DOI: 10.13021/orc2020/xxlvxm/rtkerp
title: R07.zip
DOI: 10.13021/orc2020/xxlvxm/ct9glj
title: R08.zip
DOI: 10.13021/orc2020/xxlvxm/94smw8
title: R09.zip
DOI: 10.13021/orc2020/xxlvxm/pvgcqv
title: P10.zip
DOI: 10.13021/orc2020/xxlvxm/lxhllp
title: R10.zip
DOI: 10.13021/orc2020/xxlvxm/c6ukvw
title: H47.zip
DOI: 10.13021/orc2020/xxlvxm/gz8odb
title: P11.zip
DOI: 10.13021/orc2020/xxlvxm/k7b8fg
title: H49.zip
DOI: 10.13021/orc2020/xxlvxm/ki1joy
title: C10.zip
DOI: 10.13021/orc2020/xxlvxm/amvuqp
title: H08.zip
DOI: 10.13021/orc2020/xxlvxm/5mlgc9
title: H13.zip
DOI: 10.13021/orc2020/xxlvxm/pagjie
title: H14.zip
DOI: 10.13021/orc2020/xxlvxm/wck3nm
title: H09.zip
DOI: 10.13021/orc2020/xxlvxm/ennsdp
title: H48.zip
DOI: 10.13021/orc2020/xxlvxm/x5thdr
title: H41.zip
DOI: 10.13021/orc2020/xxlvxm/i7v6zc
title: H45.zip
DOI: 10.13021/orc2020/xxlvxm/7kfywc
title: H44.zip
DOI: 10.13021/orc2020/xxlvxm/wpqjlu
title: H46.zip
DOI: 10.13021/orc2020/xxlvxm/qkk2dd
title: H33.zip
DOI: 10.13021/orc2020/xxlvxm/zl6jrf
title: R20.zip
DOI: 10.13021/orc2020/xxlvxm/leuuro
title: R12.zip
DOI: 10.13021/orc2020/xxlvxm/zj5xou
title: R13.zip
DOI: 10.13021/orc2020/xxlvxm/wb29on
title: H01.zip
DOI: 10.13021/orc2020/xxlvxm/5hymyw
title: H24.zip
DOI: 10.13021/orc2020/xxlvxm/z9ngcd
title: H31.zip
DOI: 10.13021/orc2020/xxlvxm/bgnek1
title: H52.zip
DOI: 10.13021/orc2020/xxlvxm/m7cqs7
title: H54.zip
DOI: 10.13021/orc2020/xxlvxm/wlnzdh
title: H59.zip
DOI: 10.13021/orc2020/xxlvxm/0up7he
title: H57.zip
DOI: 10.13021/orc2020/xxlvxm/bymlsi
title: H56.zip
DOI: 10.13021/orc2020/xxlvxm/23mf8i
title: H55.zip
DOI: 10.13021/orc2020/xxlvxm/hktl9b
title: H58.zip
DOI: 10.13021/orc2020/xxlvxm/usqbtk
title: H53.zip
DOI: 10.13021/orc2020/xxlvxm/zwfjkg
title: H61.zip
DOI: 10.13021/orc2020/xxlvxm/xkyyr6
title: H60.zip
DOI: 10.13021/orc2020/xxlvxm/ztc4gj
title: H64.zip
DOI: 10.13021/orc2020/xxlvxm/rhzbcw
title: H68.zip
DOI: 10.13021/orc2020/xxlvxm/cjqnm3
title: H65.zip
DOI: 10.13021/orc2020/xxlvxm/bflja3
title: H66.zip
DOI: 10.13021/orc2020/xxlvxm/nhmvtg
title: H62.zip
DOI: 10.13021/orc2020/xxlvxm/ouifnp
title: H67.zip
DOI: 10.13021/orc2020/xxlvxm/erfk94
title: H63.zip
DOI: 10.13021/orc2020/xxlvxm/3ifjga
title: H70.zip
DOI: 10.13021/orc2020/xxlvxm/iesv1d
title: H71.zip
DOI: 10.13021/orc2020/xxlvxm/fe0w1l
title: H69.zip
DOI: 10.13021/orc2020/xxlvxm/sholgv
title: H50.zip
DOI: 10.13021/orc2020/xxlvxm/gaxxa7
title: H51.zip
DOI: 10.13021/orc2020/xxlvxm/ubbbag
title: H72.zip
DOI: 10.13021/orc2020/xxlvxm/kvevcm
title: H73.zip
DOI: 10.13021/orc2020/xxlvxm/abak6z
title: H74.zip
DOI: 10.13021/orc2020/xxlvxm/mcsz2o
title: H12.zip
DOI: 10.13021/orc2020/xxlvxm/iypgku
title: H81.zip
DOI: 10.13021/orc2020/xxlvxm/5wekhi
title: H76.zip
DOI: 10.13021/orc2020/xxlvxm/vmwq3f
title: H78.zip
DOI: 10.13021/orc2020/xxlvxm/miethd
title: H75.zip
DOI: 10.13021/orc2020/xxlvxm/apqzq8
title: H80.zip
DOI: 10.13021/orc2020/xxlvxm/fbnzde
title: H79.zip
DOI: 10.13021/orc2020/xxlvxm/lmdf75
title: H77.zip
DOI: 10.13021/orc2020/xxlvxm/c5ttpp
title: H84.zip
DOI: 10.13021/orc2020/xxlvxm/7ygloi
title: H85.zip
DOI: 10.6084/m9.figshare.28245617
title: Data on Birds, Regional Economy, Human Activities, and Natural Factors Applied to Machine Learning Modeling.xlsx

description: The first sheet, named <b>Machine learning data</b>, is a collection of bird species distribution data, human activities, and natural factors for machine learning modeling. The second sheet, named <b>Avian species data</b>, contains detailed bird species distribution data, including the report count for each region.
DOI: 10.13021/orc2020/xxlvxm/y76qc0
title: H23.zip
DOI: 10.13021/orc2020/xxlvxm/j4c13i
title: H83.zip
DOI: 10.6084/m9.figshare.28245617.v1
title: Data on Birds, Regional Economy, Human Activities, and Natural Factors Applied to Machine Learning Modeling.xlsx

description: The first sheet, named <b>Machine Learning Data</b>, is a collection of bird species distribution data, human activities, and natural factors for machine learning modeling. The second sheet, also named <b>Machine Learning Data</b>, contains detailed bird species distribution data, including the report count for each region.
DOI: 10.13021/orc2020/xxlvxm/bopdki
title: H82.zip
DOI: 10.13021/orc2020/xxlvxm/iew1xe
title: H88.zip
DOI: 10.13021/orc2020/xxlvxm/7d3yut
title: H86.zip
DOI: 10.13021/orc2020/xxlvxm/4gdnvq
title: H89.zip
DOI: 10.13021/orc2020/xxlvxm/3eidjg
title: H90.zip
DOI: 10.13021/orc2020/xxlvxm/fsu0vn
title: H87.zip
DOI: 10.13021/orc2020/xxlvxm/nlexxg
title: R22.zip
DOI: 10.13021/orc2020/xxlvxm/i0rrs0
title: R11.zip
DOI: 10.13021/orc2020/xxlvxm/zv9r4i
title: R18.zip
DOI: 10.13021/orc2020/xxlvxm/3uzrel
title: R42.zip
DOI: 10.13021/orc2020/xxlvxm/m9gcox
title: R14.zip
DOI: 10.13021/orc2020/xxlvxm/cph5ej
title: R23.zip
DOI: 10.13021/orc2020/xxlvxm/frfznm
title: R25.zip
DOI: 10.13021/orc2020/xxlvxm/5m888s
title: R16.zip
DOI: 10.13021/orc2020/xxlvxm/zxogz9
title: R19.zip
DOI: 10.13021/orc2020/xxlvxm/gvom8m
title: R24.zip
DOI: 10.13021/orc2020/xxlvxm/y4mthx
title: R15.zip
DOI: 10.13021/orc2020/xxlvxm/2eno2f
title: R01.zip
DOI: 10.13021/orc2020/xxlvxm/6wdfvr
title: R37.zip
DOI: 10.13021/orc2020/xxlvxm/5pcddn
title: R36.zip
DOI: 10.13021/orc2020/xxlvxm/owjjpz
title: R35.zip
DOI: 10.13021/orc2020/xxlvxm/ft6z4w
title: R40.zip
DOI: 10.13021/orc2020/xxlvxm/jjbmsl
title: R33.zip
DOI: 10.13021/orc2020/xxlvxm/rxqr9f
title: R34.zip
DOI: 10.13021/orc2020/xxlvxm/oddxu8
title: R38.zip
DOI: 10.13021/orc2020/xxlvxm/pkqlda
title: R50.zip
DOI: 10.13021/orc2020/xxlvxm/tswu53
title: R41.zip
DOI: 10.13021/orc2020/xxlvxm/1ekjix
title: R43.zip
DOI: 10.13021/orc2020/xxlvxm/w35rcr
title: R49.zip
DOI: 10.13021/orc2020/xxlvxm/zibjdk
title: R48.zip
DOI: 10.13021/orc2020/xxlvxm/ya7vdh
title: R03.zip
DOI: 10.15468/dl.8q7pk8
title: Occurrence Download

description: A dataset containing 1563 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Notocrypta paralysos (Wood-Mason & de Nicéville, 1881)"
 ]
}

 The dataset includes 1563 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005603-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13021/orc2020/xxlvxm/6hjg41
title: R45.zip
DOI: 10.13021/orc2020/xxlvxm/edspmy
title: R31.zip
DOI: 10.13021/orc2020/xxlvxm/kcwnyx
title: R46.zip
DOI: 10.13021/orc2020/xxlvxm/fxc7ge
title: R39.zip
DOI: 10.13021/orc2020/xxlvxm/6ieb0v
title: R44.zip
DOI: 10.13021/orc2020/xxlvxm/spxa4c
title: R21.zip
DOI: 10.13021/orc2020/xxlvxm/x5q7nw
title: R60.zip
DOI: 10.13021/orc2020/xxlvxm/taj3jn
title: R56.zip
DOI: 10.13021/orc2020/xxlvxm/uvnrq4
title: R51.zip
DOI: 10.13021/orc2020/xxlvxm/wyaxy5
title: R52.zip
DOI: 10.13021/orc2020/xxlvxm/ovg4w4
title: R55.zip
DOI: 10.13021/orc2020/xxlvxm/zep9u0
title: R47.zip
DOI: 10.13021/orc2020/xxlvxm/n6jrcw
title: R58.zip
DOI: 10.13021/orc2020/xxlvxm/etiunp
title: R57.zip
DOI: 10.13021/orc2020/xxlvxm/jx8r0n
title: R54.zip
DOI: 10.13021/orc2020/xxlvxm/j3y0vj
title: R53.zip
DOI: 10.13021/orc2020/xxlvxm/p5mzab
title: R59.zip
DOI: 10.13021/orc2020/xxlvxm/lrx2ws
title: H09.zip
DOI: 10.13021/orc2020/xxlvxm/07ruwc
title: H08.zip
DOI: 10.13021/orc2020/xxlvxm/nkcwe0
title: H48.zip
DOI: 10.13021/orc2020/xxlvxm/aqd1gk
title: H13.zip
DOI: 10.13021/orc2020/xxlvxm/uxprsa
title: H14.zip
DOI: 10.13021/orc2020/xxlvxm/ungeay
title: H45.zip
DOI: 10.13021/orc2020/xxlvxm/xcxyyp
title: H33.zip
DOI: 10.13021/orc2020/xxlvxm/owehkh
title: H19.zip
DOI: 10.13021/orc2020/xxlvxm/y0alcg
title: H44.zip
DOI: 10.13021/orc2020/xxlvxm/1bljsy
title: H21.zip
DOI: 10.13021/orc2020/xxlvxm/28yhzh
title: H46.zip
DOI: 10.13021/orc2020/xxlvxm/sjtubi
title: H41.zip
DOI: 10.13021/orc2020/xxlvxm/0uv6va
title: H61-70.zip
DOI: 10.13021/orc2020/xxlvxm/akoog1
title: R01-10.zip
DOI: 10.13021/orc2020/xxlvxm/4hblzz
title: R11-20.zip
DOI: 10.13021/orc2020/xxlvxm/43ln3q
title: R61-70.zip
DOI: 10.13021/orc2020/xxlvxm/rrcvst
title: R51-60.zip
DOI: 10.13021/orc2020/xxlvxm/ye3fte
title: R21-30.zip
DOI: 10.13021/orc2020/xxlvxm/vgh6x6
title: R41-50.zip
DOI: 10.13021/orc2020/xxlvxm/oscw32
title: R31-40.zip
DOI: 10.13021/orc2020/xxlvxm/xrrpur
title: P05.zip
DOI: 10.13021/orc2020/xxlvxm/ouikoy
title: P04.zip
DOI: 10.13021/orc2020/xxlvxm/xr9hda
title: P02.zip
DOI: 10.13021/orc2020/xxlvxm/99twz7
title: P01.zip
DOI: 10.13021/orc2020/xxlvxm/qnfrrc
title: P07.zip
DOI: 10.13021/orc2020/xxlvxm/ez82en
title: P08.zip
DOI: 10.13021/orc2020/xxlvxm/pab6c0
title: P03.zip
DOI: 10.13021/orc2020/xxlvxm/2n1iou
title: P14.zip
DOI: 10.13021/orc2020/xxlvxm/9p8iyb
title: P06.zip
DOI: 10.13021/orc2020/xxlvxm/dqitjp
title: P16.zip
DOI: 10.13021/orc2020/xxlvxm/orsgdw
title: P18.zip
DOI: 10.13021/orc2020/xxlvxm/wmfxxb
title: P20.zip
DOI: 10.13021/orc2020/xxlvxm/yiv5qi
title: P17.zip
DOI: 10.13021/orc2020/xxlvxm/3uxnqh
title: P10.zip
DOI: 10.13021/orc2020/xxlvxm/ymfm0c
title: P09.zip
DOI: 10.13021/orc2020/xxlvxm/dgofex
title: P15.zip
DOI: 10.13021/orc2020/xxlvxm/i397x3
title: P11.zip
DOI: 10.13021/orc2020/xxlvxm/y5fyzb
title: P12.zip
DOI: 10.13021/orc2020/xxlvxm/kod1m5
title: P13.zip
DOI: 10.13021/orc2020/xxlvxm/vvokzk
title: P19.zip
DOI: 10.5281/zenodo.11238926
title: Attenuated sex-related DNA methylation differences in cancer highlight the magnitude bias mediating existing disparities

description: This is supplementary data for the manuscript, "Attenuated sex-related DNA methylation differences in cancer highlight the magnitude bias mediating existing disparities"
DOI: 10.5281/zenodo.11238927
title: Attenuated sex-related DNA methylation differences in cancer highlight the magnitude bias mediating existing disparities

description: This is supplementary data for the manuscript, "Attenuated sex-related DNA methylation differences in cancer highlight the magnitude bias mediating existing disparities"
DOI: 10.13021/orc2020/xxlvxm/wx6hva
title: R41-50.zip
DOI: 10.13021/orc2020/xxlvxm/wrxycy
title: R61-70.zip
DOI: 10.13021/orc2020/xxlvxm/7dxkfq
title: R11-20.zip
DOI: 10.13021/orc2020/xxlvxm/hpcsb7
title: R31-40.zip
DOI: 10.13021/orc2020/xxlvxm/i08ydg
title: R51-60.zip
DOI: 10.13021/orc2020/xxlvxm/maqpra
title: R01-10.zip
DOI: 10.13021/orc2020/xxlvxm/szc5xo
title: R21-30.zip
DOI: 10.13021/orc2020/xxlvxm/hy1eiv
title: P11-20.zip
DOI: 10.13021/orc2020/xxlvxm/x5maww
title: P01-10.zip
DOI: 10.13021/orc2020/xxlvxm/bexslg
title: H01-10.zip
DOI: 10.13021/orc2020/xxlvxm/efxlqb
title: H11-20.zip
DOI: 10.13021/orc2020/xxlvxm/eqono3
title: H21-30.zip
DOI: 10.13021/orc2020/xxlvxm/eyykrj
title: C01-10.zip
DOI: 10.13021/orc2020/xxlvxm/gzdaea
title: H51-60.zip
DOI: 10.13021/orc2020/xxlvxm/i9qpqs
title: H31-40.zip
DOI: 10.13021/orc2020/xxlvxm/imq9bk
title: A_Read_Me.txt
DOI: 10.13021/orc2020/xxlvxm/nrsndy
title: H41-50.zip
DOI: 10.13021/orc2020/xxlvxm/oaqgqg
title: C11-20.zip
DOI: 10.13021/orc2020/xxlvxm/wwfovy
title: C21-30.zip
DOI: 10.13021/orc2020/xxlvxm/yl2lgj
title: H61-70.zip
DOI: 10.13021/orc2020/xxlvxm/zqzv3l
title: H71-80.zip
DOI: 10.13021/orc2020/xxlvxm
title: Deformable Object Tracking Dataset (DOT)

description: The Deformable Object Tracking Dataset, DOT, is a large real-world dataset for tracking deformable objects with little or no texture. The key technology is to use UV fluorescent markers to provide features for correspondence tracking while maintain the object's original appearance. DOT has about one million video frames of four types of deformable objects: paper, cloth, rope and hands. For each motion, DOT provideS 2D videos with and without markers from multiple viewpoints, 3D models of the deformed object, and tracked ground truth correspondences in both 2D and 3D.
DOI: 10.13021/orc2020/xxlvxm/45vrei
title: R21-30.zip
DOI: 10.13021/orc2020/xxlvxm/8gwdsh
title: P11-20.zip
DOI: 10.13021/orc2020/xxlvxm/fvfqn7
title: R11-20.zip
DOI: 10.13021/orc2020/xxlvxm/jjbuu8
title: R51-60.zip
DOI: 10.13021/orc2020/xxlvxm/nothln
title: R31-40.zip
DOI: 10.13021/orc2020/xxlvxm/rp2wgk
title: R41-50.zip
DOI: 10.13021/orc2020/xxlvxm/sut1w3
title: P01-10.zip
DOI: 10.13021/orc2020/xxlvxm/vs3j50
title: R01-10.zip
DOI: 10.13021/orc2020/xxlvxm/x5yaju
title: H81-90.zip
DOI: 10.13021/orc2020/xxlvxm/ymmeaa
title: R61-70.zip
DOI: 10.60656/beb1b7797dca462f
title: Custom collection of ice effective radius data from Lampedusa on 17 Aug 2024
DOI: 10.6084/m9.figshare.28245680.v1
title: Two new species of Polyporales from Swat, Pakistan: A phylogenetic and morphologicalstudy

description: These files contain ITS and LSU multiple sequence alignments generated using MAFFT for the genera <i>Phlebia</i> and <i>Xanthoperenniporia</i>. They are supplementary materials for the study titled <i>"Two new species of Polyporales from Swat, Pakistan: A phylogenetic and morphological study"</i>. The alignments support phylogenetic analyses and provide insights into the evolutionary relationships of the studied species.
DOI: 10.6084/m9.figshare.28245680
title: Two new species of Polyporales from Swat, Pakistan: A phylogenetic and morphologicalstudy

description: These files contain ITS and LSU multiple sequence alignments generated using MAFFT for the genera <i>Phlebia</i> and <i>Xanthoperenniporia</i>. They are supplementary materials for the study titled <i>"Two new species of Polyporales from Swat, Pakistan: A phylogenetic and morphological study"</i>. The alignments support phylogenetic analyses and provide insights into the evolutionary relationships of the studied species.
DOI: 10.15468/dl.6vykvs
title: Occurrence Download

description: A dataset containing 736 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Chinese Taipei)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Prunus mume (Siebold) Siebold & Zucc."
 ]
}

 The dataset includes 736 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005605-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dk7zwm
title: Occurrence Download

description: A dataset containing 491 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((95.09832 -3.86396,126.90168 -3.86396,126.90168 8.86396,95.09832 8.86396,95.09832 -3.86396))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Heliocypha biseriata (Selys, 1859)"
 ]
}

 The dataset includes 491 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005606-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18150/ds8936
title: Optimized process parameters and catalytic data for the continuous reduction of nitroaromatics to aromatic amines

description: This dataset provides comprehensive review of experimental data from the continuous flow hydrogenation of nitroaromatic compounds, aimed at optimizing process parameters and evaluating catalytic performance in both microreactor and packed-bed reactor systems. The dataset includes the following:SET 1: Data realated to the hydrogenation of nitroaromatic compounds in PBR and CSTR reactors.SET 2: Data realated to the hydrogenation of nitroaromatic compounds in membrane reactors.SET 3: Data realated to the hydrogenation of nitroaromatic compounds in flow-mode processes over photocatalysts.SET 4: Summary of continous-flow mode reactors used for the catalytic hydrogenation of nitroaromatic compounds.SET 5: Data realated to the hydrogenation of nitroaromatic compounds in flow-mode processes over metallic catalysts.The literature research was carried out within Opus 25 project (UMO-2023/49/B/ST8/01029) granted by National Science Center (Poland). Aim of the project is to develop new generation of catalytical technology for the production of aromatic amines.