cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive157669.20241212.9.2
title: Clostridioides difficile (Hall and O'Toole 1935) Lawson et al. 2016

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive157670.20241212.9.2
title: Clostridioides difficile (Hall and O'Toole 1935) Lawson et al. 2016

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive157679.20241212.9.2
title: Desulfovibrio sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive157681.20241212.9.2
title: Enterovibrio sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive157682.20241212.9.2
title: Enterobacter cloacae (Jordan 1890) Hormaeche and Edwards 1960

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive157685.20241212.9.2
title: Enterococcus faecalis (Andrewes and Horder 1906) Schleifer and Kilpper-Bälz 1984

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive157686.20241212.9.2
title: Thermomonospora catenispora Wu et al., 2019

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive157687.20241212.9.2
title: Pectobacterium carotovorum (Jones 1901) Waldee 1945 emend. Gardan et al. 2003

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive157688.20241212.9.2
title: Escherichia coli (Migula 1895) Castellani and Chalmers 1919

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive157689.20241212.9.2
title: Escherichia coli (Migula 1895) Castellani and Chalmers 1919

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive157690.20241212.9.2
title: Escherichia coli (Migula 1895) Castellani and Chalmers 1919

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.25346/s6eecgix/q4vp8p
title: plane_6.jpg
DOI: 10.25346/s6eecgix/j0q8dj
title: plane_5.jpg
DOI: 10.25346/s6eecgix/0kucp9
title: plane_4.jpg
DOI: 10.25346/s6eecgix/vmkhwb
title: plane_3.jpg
DOI: 10.25346/s6eecgix/1sxtat
title: plane_2.jpg
DOI: 10.25346/s6eecgix/xurzvh
title: plane_1.jpg
DOI: 10.25346/s6eecgix/7sl6en
title: plane_0.jpg
DOI: 10.25346/s6eecgix/njtjhx
title: info.json
DOI: 10.25346/s6eecgix/cxkurj
title: plane_8.jpg
DOI: 10.25346/s6eecgix/czbj1h
title: plane_7.jpg
DOI: 10.25346/s6eecgix/9cpcuu
title: plane_6.jpg
DOI: 10.25346/s6eecgix/vvvlrc
title: plane_5.jpg
DOI: 10.25346/s6eecgix/usufzi
title: plane_4.jpg
DOI: 10.25346/s6eecgix/m9oxoo
title: plane_3.jpg
DOI: 10.25346/s6eecgix/r6c1g7
title: plane_2.jpg
DOI: 10.25346/s6eecgix/xxrqhl
title: plane_1.jpg
DOI: 10.25346/s6eecgix/vte5vn
title: plane_0.jpg
DOI: 10.25346/s6eecgix/0emr4j
title: materials.png
DOI: 10.25346/s6eecgix/wuqygl
title: info.json
DOI: 10.25346/s6eecgix/tsfsyn
title: msXV_007v.relight
DOI: 10.25346/s6eecgix/f9m5ky
title: msXV_007v_65_49.jpg
DOI: 10.25346/s6eecgix/tyk7ul
title: msXV_007v_65_48.jpg
DOI: 10.25346/s6eecgix/jm2hhe
title: msXV_007v_65_47.jpg
DOI: 10.25346/s6eecgix/qxoofi
title: msXV_007v_65_46.jpg
DOI: 10.25346/s6eecgix/gvl6wt
title: msXV_007v_65_45.jpg
DOI: 10.25346/s6eecgix/xdhdy8
title: msXV_007v_65_44.jpg
DOI: 10.25346/s6eecgix/whrrsr
title: msXV_007v_65_43.jpg
DOI: 10.25346/s6eecgix/tnulaz
title: msXV_007v_65_42.jpg
DOI: 10.25346/s6eecgix/ecw21z
title: msXV_007v_65_41.jpg
DOI: 10.25346/s6eecgix/7iwmkz
title: msXV_007v_65_40.jpg
DOI: 10.25346/s6eecgix/ml9thk
title: msXV_007v_65_39.jpg
DOI: 10.25346/s6eecgix/dgf1pl
title: msXV_007v_65_38.jpg
DOI: 10.25346/s6eecgix/1sbhe9
title: msXV_007v_65_37.jpg
DOI: 10.25346/s6eecgix/jxglpp
title: msXV_007v_47_36.jpg
DOI: 10.25346/s6eecgix/8u1lcc
title: msXV_007v_47_35.jpg
DOI: 10.25346/s6eecgix/tknji6
title: msXV_007v_47_34.jpg
DOI: 10.25346/s6eecgix/tppwz6
title: msXV_007v_47_33.jpg
DOI: 10.25346/s6eecgix/sa8d7w
title: msXV_007v_47_32.jpg
DOI: 10.25346/s6eecgix/tk6nax
title: msXV_007v_47_31.jpg
DOI: 10.25346/s6eecgix/inniyb
title: msXV_007v_47_30.jpg
DOI: 10.25346/s6eecgix/yixbol
title: msXV_007v_47_29.jpg
DOI: 10.25346/s6eecgix/w8tgy0
title: msXV_007v_47_28.jpg
DOI: 10.25346/s6eecgix/qq8w6p
title: msXV_007v_47_27.jpg
DOI: 10.25346/s6eecgix/zkzqts
title: msXV_007v_47_26.jpg
DOI: 10.25346/s6eecgix/xh3cia
title: msXV_007v_47_25.jpg
DOI: 10.25346/s6eecgix/emve2w
title: msXV_007v_31_23.jpg
DOI: 10.25346/s6eecgix/3tf9lh
title: msXV_007v_31_22.jpg
DOI: 10.25346/s6eecgix/d7bv47
title: msXV_007v_31_21.jpg
DOI: 10.25346/s6eecgix/n4t6xz
title: msXV_007v_31_20.jpg
DOI: 10.25346/s6eecgix/kmja2k
title: msXV_007v_31_19.jpg
DOI: 10.25346/s6eecgix/urgwlx
title: msXV_007v_31_18.jpg
DOI: 10.25346/s6eecgix/dsf1pi
title: msXV_007v_31_17.jpg
DOI: 10.25346/s6eecgix/ydcpdi
title: msXV_007v_31_16.jpg
DOI: 10.25346/s6eecgix/2fouwa
title: msXV_007v_31_15.jpg
DOI: 10.25346/s6eecgix/wsavpv
title: msXV_007v_31_14.jpg
DOI: 10.25346/s6eecgix/lmj46f
title: msXV_007v_31_13.jpg
DOI: 10.25346/s6eecgix/zngihd
title: msXV_007v_15_12.jpg
DOI: 10.25346/s6eecgix/edr5w4
title: msXV_007v_15_11.jpg
DOI: 10.18112/openneuro.ds006758.v1.0.0
title: VirginiaTech_AFA_Tactile
DOI: 10.25346/s6eecgix/k7x1bk
title: msXV_007v_15_10.jpg
DOI: 10.25346/s6eecgix/rnry6w
title: msXV_007v_15_09.jpg
DOI: 10.25346/s6eecgix/pjxqvc
title: msXV_007v_15_08.jpg
DOI: 10.25346/s6eecgix/wqa4zl
title: msXV_007v_15_07.jpg
DOI: 10.25346/s6eecgix/jaxzbs
title: msXV_007v_15_06.jpg
DOI: 10.25346/s6eecgix/hich94
title: msXV_007v_15_05.jpg
DOI: 10.25346/s6eecgix/g5rwi7
title: msXV_007v_15_04.jpg
DOI: 10.25346/s6eecgix/7rsnsq
title: msXV_007v_15_03.jpg
DOI: 10.25346/s6eecgix/ra3nic
title: msXV_007v_15_02.jpg
DOI: 10.25346/s6eecgix/kjmbsa
title: msXV_007v_15_01.jpg
DOI: 10.25346/s6eecgix/ozxadb
title: msXV_007v_0_ring.jpg
DOI: 10.25346/s6eecgix/rznzxi
title: msXV_007v.jpg
DOI: 10.25346/s6eecgix/uflshm
title: msXL_344v_65_48.tif
DOI: 10.25346/s6eecgix/nxah08
title: msXL_344v_65_47.tif
DOI: 10.25346/s6eecgix/2mgbmf
title: msXL_344v_65_46.tif
DOI: 10.25346/s6eecgix/d2lxlj
title: msXL_344v_65_45.tif
DOI: 10.25346/s6eecgix/bbndjt
title: msXL_344v_65_44.tif
DOI: 10.25346/s6eecgix/75kjxd
title: msXL_344v_65_43.tif
DOI: 10.25346/s6eecgix/uimar3
title: msXL_344v_65_42.tif
DOI: 10.25346/s6eecgix/agoews
title: msXL_344v_65_41.tif
DOI: 10.25346/s6eecgix/muplsg
title: msXL_344v_65_40.tif
DOI: 10.25346/s6eecgix/1ohoso
title: msXL_344v_65_39.tif
DOI: 10.25346/s6eecgix/km3d8t
title: msXL_344v_65_38.tif
DOI: 10.25346/s6eecgix/41hkyn
title: msXL_344v_65_37.tif
DOI: 10.25346/s6eecgix/rapkui
title: msXL_344v_46_36.tif
DOI: 10.25346/s6eecgix/etzkha
title: msXL_344v_46_35.tif
DOI: 10.25346/s6eecgix/ifadce
title: msXL_344v_46_34.tif
DOI: 10.25346/s6eecgix/bevepi
title: msXL_344v_46_33.tif
DOI: 10.25346/s6eecgix/u5wyhy
title: msXL_344v_46_32.tif
DOI: 10.25346/s6eecgix/ib2kcw
title: msXL_344v_46_31.tif
DOI: 10.25346/s6eecgix/zww6oc
title: msXL_344v_46_30.tif
DOI: 10.25346/s6eecgix/enrh4u
title: msXL_344v_46_29.tif
DOI: 10.25346/s6eecgix/md4tjx
title: msXL_344v_46_28.tif
DOI: 10.25346/s6eecgix/xrubsr
title: msXL_344v_46_27.tif
DOI: 10.25346/s6eecgix/pfkkor
title: msXL_344v_46_26.tif
DOI: 10.25346/s6eecgix/r83x1k
title: msXL_344v_46_25.tif
DOI: 10.25346/s6eecgix/c0x12j
title: msXL_344v_31_24.tif
DOI: 10.25346/s6eecgix/tnha7s
title: msXL_344v_31_23.tif
DOI: 10.25346/s6eecgix/slsxc7
title: msXL_344v_31_22.tif
DOI: 10.25346/s6eecgix/xb1xwh
title: msXL_344v_31_21.tif
DOI: 10.25346/s6eecgix/v4hk75
title: msXL_344v_31_20.tif
DOI: 10.25346/s6eecgix/wnmxbq
title: msXL_344v_31_19.tif
DOI: 10.25346/s6eecgix/tnucgc
title: msXL_344v_31_18.tif
DOI: 10.25346/s6eecgix/4t8kru
title: msXL_344v_31_17.tif
DOI: 10.25346/s6eecgix/bvmrhr
title: msXL_344v_31_16.tif
DOI: 10.25346/s6eecgix/rt4pnc
title: msXL_344v_31_15.tif
DOI: 10.25346/s6eecgix/vgehfm
title: msXL_344v_31_14.tif
DOI: 10.25346/s6eecgix/9vmihy
title: msXL_344v_31_13.tif
DOI: 10.25346/s6eecgix/klk0v6
title: msXL_344v_15_12.tif
DOI: 10.25346/s6eecgix/ojtflf
title: msXL_344v_15_11.tif
DOI: 10.25346/s6eecgix/28hn2i
title: msXL_344v_15_10.tif
DOI: 10.25346/s6eecgix/mwdub4
title: msXL_344v_15_09.tif
DOI: 10.25346/s6eecgix/5uvfbm
title: msXL_344v_15_08.tif
DOI: 10.25346/s6eecgix/xtatpf
title: msXL_344v_15_07.tif
DOI: 10.25346/s6eecgix/kxhqfk
title: msXL_344v_15_06.tif
DOI: 10.25346/s6eecgix/dnj8o6
title: msXL_344v_15_05.tif
DOI: 10.25346/s6eecgix/swnww7
title: msXL_344v_15_04.tif
DOI: 10.25346/s6eecgix/tooc5a
title: msXL_344v_15_03.tif
DOI: 10.25346/s6eecgix/rqbywx
title: msXL_344v_15_02.tif
DOI: 10.25346/s6eecgix/97llae
title: msXL_344v_15_01.tif
DOI: 10.25346/s6eecgix/lm09bm
title: msXL_344v_0_ring.tif
DOI: 10.25346/s6eecgix/gvvhxy
title: msXL_344v.tif
DOI: 10.25346/s6eecgix/cxjucs
title: plane_8.jpg
DOI: 10.25346/s6eecgix/wyoftb
title: plane_7.jpg
DOI: 10.25346/s6eecgix/zlnuee
title: plane_6.jpg
DOI: 10.25346/s6eecgix/dfv9ql
title: plane_5.jpg
DOI: 10.25346/s6eecgix/isjl2u
title: plane_4.jpg
DOI: 10.25346/s6eecgix/ryauqw
title: plane_3.jpg
DOI: 10.25346/s6eecgix/qjbon4
title: plane_2.jpg
DOI: 10.25346/s6eecgix/xjohrm
title: plane_1.jpg
DOI: 10.25346/s6eecgix/8bwsys
title: plane_0.jpg
DOI: 10.25346/s6eecgix/adsaf4
title: info.json
DOI: 10.5281/zenodo.17282578
title: Bulk RNA-seq of human endometrial organoids treated with hTSC-conditioned medium (hTSC-CM)
DOI: 10.5281/zenodo.17282579
title: Bulk RNA-seq of human endometrial organoids treated with hTSC-conditioned medium (hTSC-CM)
DOI: 10.25346/s6eecgix/ogtxeb
title: plane_8.jpg
DOI: 10.25346/s6eecgix/zusquj
title: plane_7.jpg
DOI: 10.25346/s6eecgix/usb3e9
title: plane_6.jpg
DOI: 10.25346/s6eecgix/oqz3sk
title: plane_5.jpg
DOI: 10.25346/s6eecgix/nh4rph
title: plane_4.jpg
DOI: 10.25346/s6eecgix/vzfrbe
title: plane_3.jpg
DOI: 10.25346/s6eecgix/4k7fbe
title: plane_2.jpg
DOI: 10.25346/s6eecgix/siv2n6
title: plane_1.jpg
DOI: 10.25346/s6eecgix/z40y3q
title: plane_0.jpg
DOI: 10.25346/s6eecgix/rwuds6
title: materials.png
DOI: 10.25346/s6eecgix/vo3bc1
title: info.json
DOI: 10.25346/s6eecgix/gsra8c
title: msXL_344v.relight
DOI: 10.25346/s6eecgix/kstdkl
title: 334v_RTI_HSH27.rti
DOI: 10.25346/s6eecgix/vfs8k9
title: msXL_344v_65_48.jpg
DOI: 10.25346/s6eecgix/xcmrep
title: msXL_344v_65_47.jpg
DOI: 10.25346/s6eecgix/todvau
title: msXL_344v_65_46.jpg
DOI: 10.25346/s6eecgix/k8ayxf
title: msXL_344v_65_45.jpg
DOI: 10.26023/x2wp-s330-g807
title: ACCLIP: Low Rate (LRT - 1 sps) Navigation, State Parameter, and Microphysics Flight-Level Data. Version 1.1

description: This dataset includes airborne measurements obtained from the NSF/NCAR HIAPER GV aircraft (Tail Number N677F) during the ACCLIP project. The files contain low rate navigation, state parameter, and microphysics flight-level data in netCDF format.
DOI: 10.25346/s6eecgix/cn2xfg
title: msXL_344v_65_44.jpg
DOI: 10.6084/m9.figshare.30291571
title: <b>High-Resolution Local Climate Zone Mapping via Deep Mixed-Scene Decomposition of Remote Sensing Imagery</b>

description: <b>High-Resolution Local Climate Zone Mapping via Deep Mixed-Scene Decomposition of Remote Sensing Imagery</b>
DOI: 10.6084/m9.figshare.30291571.v1
title: <b>High-Resolution Local Climate Zone Mapping via Deep Mixed-Scene Decomposition of Remote Sensing Imagery</b>

description: <b>High-Resolution Local Climate Zone Mapping via Deep Mixed-Scene Decomposition of Remote Sensing Imagery</b>
DOI: 10.25346/s6eecgix/ttm6uy
title: msXL_344v_65_43.jpg
DOI: 10.25346/s6eecgix/elpyku
title: msXL_344v_65_42.jpg
DOI: 10.25346/s6eecgix/cb4pdw
title: msXL_344v_65_41.jpg
DOI: 10.25346/s6eecgix/gayjqu
title: msXL_344v_65_40.jpg
DOI: 10.25346/s6eecgix/dvclbd
title: msXL_344v_65_39.jpg
DOI: 10.25346/s6eecgix/bfe75g
title: msXL_344v_65_38.jpg
DOI: 10.13012/b2idb-6684845_v1
title: Computational data and mesh files for Nine circles of elastic brittle fracture: A series of challenge problems to assess fracture models

description: This dataset accompanies the research paper "Nine circles of elastic brittle fracture: A series of challenge problems to assess fracture models" by Kamarei, Zeng, Dolbow, and Lopez-Pamies, CMAME (2026). The dataset contains computational mesh files, figure data, and supporting materials for nine standardized challenge problems designed to assess fracture models in isotropic elastic brittle materials under quasi-static loading conditions.

The nine challenge problems span the complete range of fracture nucleation and propagation mechanisms: strength nucleation (uniaxial tension, biaxial tension, torsion), Griffith nucleation (pure-shear, double cantilever beam, trousers), and strength-Griffith mediated nucleation (single edge notch, indentation, poker-chip).

The dataset includes:
 High-quality mesh files for all nine challenge problems
 Figure data and results for both linear elastic (soda-lime glass) and non-linear elastic (PU elastomer) brittle materials
DOI: 10.25346/s6eecgix/dxpuey
title: msXL_344v_65_37.jpg
DOI: 10.25346/s6eecgix/srwbsc
title: msXL_344v_46_36.jpg
DOI: 10.25346/s6eecgix/2aibcu
title: msXL_344v_46_35.jpg
DOI: 10.25346/s6eecgix/njpvdq
title: msXL_344v_46_34.jpg
DOI: 10.25346/s6eecgix/v5chqj
title: msXL_344v_46_33.jpg
DOI: 10.25346/s6eecgix/aruukg
title: msXL_344v_46_32.jpg
DOI: 10.25346/s6eecgix/goo7bg
title: msXL_344v_46_31.jpg
DOI: 10.25346/s6eecgix/yh5cz3
title: msXL_344v_46_30.jpg
DOI: 10.25346/s6eecgix/7zmxll
title: msXL_344v_46_29.jpg
DOI: 10.25346/s6eecgix/cil6hf
title: msXL_344v_46_28.jpg
DOI: 10.25346/s6eecgix/pxhofw
title: msXL_344v_46_27.jpg
DOI: 10.25346/s6eecgix/z99pix
title: msXL_344v_46_26.jpg
DOI: 10.25346/s6eecgix/hesutt
title: msXL_344v_46_25.jpg
DOI: 10.25346/s6eecgix/6d29u8
title: msXL_344v_31_24.jpg
DOI: 10.25346/s6eecgix/vepza4
title: msXL_344v_31_23.jpg
DOI: 10.25346/s6eecgix/mygebs
title: msXL_344v_31_22.jpg
DOI: 10.25346/s6eecgix/ns4vjg
title: msXL_344v_31_21.jpg
DOI: 10.25346/s6eecgix/cpi2gm
title: msXL_344v_31_20.jpg
DOI: 10.25346/s6eecgix/5cxtlz
title: msXL_344v_31_19.jpg
DOI: 10.25346/s6eecgix/s53pdj
title: msXL_344v_31_18.jpg
DOI: 10.25346/s6eecgix/oz7ml3
title: msXL_344v_31_17.jpg
DOI: 10.25346/s6eecgix/zvcjea
title: msXL_344v_31_16.jpg
DOI: 10.25346/s6eecgix/i1xz1u
title: msXL_344v_31_15.jpg
DOI: 10.25346/s6eecgix/squebc
title: msXL_344v_31_14.jpg
DOI: 10.25346/s6eecgix/bfe062
title: msXL_344v_31_13.jpg
DOI: 10.25346/s6eecgix/qtvpts
title: msXL_344v_15_12.jpg
DOI: 10.25346/s6eecgix/ccglnc
title: msXL_344v_15_11.jpg
DOI: 10.25346/s6eecgix/lur4iy
title: msXL_344v_15_10.jpg
DOI: 10.25346/s6eecgix/makfqp
title: msXL_344v_15_09.jpg
DOI: 10.25346/s6eecgix/qlww0q
title: msXL_344v_15_08.jpg
DOI: 10.25346/s6eecgix/k2tqaq
title: msXL_344v_15_07.jpg
DOI: 10.25346/s6eecgix/fnanez
title: msXL_344v_15_06.jpg
DOI: 10.25346/s6eecgix/xn7qdr
title: msXL_344v_15_05.jpg
DOI: 10.25346/s6eecgix/gwrqzq
title: msXL_344v_15_04.jpg
DOI: 10.25346/s6eecgix/dsl2og
title: msXL_344v_15_03.jpg
DOI: 10.25346/s6eecgix/ph0skh
title: msXL_344v_15_02.jpg
DOI: 10.25346/s6eecgix/cfxycd
title: msXL_344v_15_01.jpg
DOI: 10.7910/dvn/msn1hw
title: Rapid passage to ordered states in Rydberg atom arrays

description: This dataset contains the source data for Figures 2-7 presented in the research article "Rapid passage to ordered states in Rydberg atom arrays(https://arxiv.org/abs/2504.19214)".
DOI: 10.25346/s6eecgix/wbqde3
title: msXL_344v_0_ring.jpg
DOI: 10.25346/s6eecgix/pghay6
title: msXL_344v.jpg
DOI: 10.25346/s6eecgix/evnieb
title: msXL_334v_65_49.tif
DOI: 10.25346/s6eecgix/fqukmy
title: msXL_334v_65_48.tif
DOI: 10.25346/s6eecgix/mzzmo4
title: msXL_334v_65_47.tif
DOI: 10.25346/s6eecgix/i4arq6
title: msXL_334v_65_46.tif
DOI: 10.25346/s6eecgix/kdvbjz
title: msXL_334v_65_45.tif
DOI: 10.25346/s6eecgix/uyyugh
title: msXL_334v_65_44.tif
DOI: 10.25346/s6eecgix/kbk0u7
title: msXL_334v_65_43.tif
DOI: 10.25346/s6eecgix/ml5poi
title: msXL_334v_65_42.tif
DOI: 10.25346/s6eecgix/bysss4
title: msXL_334v_65_41.tif
DOI: 10.25346/s6eecgix/hub0fy
title: msXL_334v_65_40.tif
DOI: 10.25346/s6eecgix/tnokht
title: msXL_334v_65_39.tif
DOI: 10.25346/s6eecgix/jngnvh
title: msXL_334v_65_38.tif
DOI: 10.25346/s6eecgix/npfiyn
title: msXL_334v_48_37.tif
DOI: 10.25346/s6eecgix/rynb4l
title: msXL_334v_48_36.tif
DOI: 10.25346/s6eecgix/opyxeq
title: msXL_334v_48_35.tif
DOI: 10.25346/s6eecgix/hnkdnj
title: msXL_334v_48_34.tif
DOI: 10.25346/s6eecgix/bb4qom
title: msXL_334v_48_33.tif
DOI: 10.25346/s6eecgix/smuzty
title: msXL_334v_48_32.tif
DOI: 10.25346/s6eecgix/wlyeao
title: msXL_334v_48_31.tif
DOI: 10.25346/s6eecgix/7j4xvu
title: msXL_334v_48_30.tif
DOI: 10.25346/s6eecgix/tn8u4e
title: msXL_334v_48_29.tif
DOI: 10.25346/s6eecgix/wil3su
title: msXL_334v_48_28.tif
DOI: 10.25346/s6eecgix/5rahcx
title: msXL_334v_48_27.tif
DOI: 10.25346/s6eecgix/tseggc
title: msXL_334v_48_26.tif
DOI: 10.7910/dvn/um5ugx
title: Stock Market Next Day Forecast Data

description: Stock market forecasting remains a complex and challenging task to forecast, traditional technical analysis methods like RSI, EMA, and Candlestick Patterns often fail to analyze the stock market time series pattern with many recent studies have now explored forecasting using machine learning or neural networks, other studies have improved the increase in accuracy or decrease in regression loss by applying technical indicator and sentiment analysis. This paper aims to analyze the performance of the combined reinforcement learning and machine learning models in predicting the stock market’s next day trend by incorporating both technical and sentiment-based features. Technical indicators were derived from historical price data focused on multi-timeframe trend and swing trend in the market, then sentiment features were extracted using FinBERT from Benzinga Pro as a reliable financial news source. The reinforcement learning model used is the Proximal Policy Optimization model, while a variety of machine learning models, such as XGBoost, Gradient Boosting, Random Forest, Decision Tree, K-Nearest Neighbor, Support Vector Machine, and Logistic Regression were trained to assess its predictive performance. Results indicate that the ensemble model outperformed the other tested machine learning models with an accuracy score of 69.97%. These reports highlight the effectiveness of the ensemble model combining sentiment and technical features to enhance stock market predictions accuracy. However, limitations such as news data availability and the small training time, remain a key challenge that could potentially increase the performance. Future research could experiment with alternative models, more training time, advance technical patterns, and more news datasets.
DOI: 10.25346/s6eecgix/tqrd9g
title: msXL_334v_48_25.tif
DOI: 10.25346/s6eecgix/tkuzy6
title: msXL_334v_31_24.tif
DOI: 10.25346/s6eecgix/oyrl1f
title: msXL_334v_31_23.tif
DOI: 10.25346/s6eecgix/ygighr
title: msXL_334v_31_22.tif
DOI: 10.25346/s6eecgix/behcn0
title: msXL_334v_31_21.tif
DOI: 10.25346/s6eecgix/o4e4fe
title: msXL_334v_31_20.tif
DOI: 10.25346/s6eecgix/gzfkwf
title: msXL_334v_31_19.tif
DOI: 10.25346/s6eecgix/qh2e7k
title: msXL_334v_31_18.tif
DOI: 10.25346/s6eecgix/agcpgp
title: msXL_334v_31_17.tif
DOI: 10.25346/s6eecgix/rvsk97
title: msXL_334v_31_16.tif
DOI: 10.5281/zenodo.14963466
title: Nanomaterial-Induced Mitochondrial Biogenesis Enhances Intercellular Mitochondrial Transfer Efficiency in Human Mesenchymal Stem Cells

description: Raw data (GraphPad files, confocal images, uncropped western blot images ) of the publication titled "Nanomaterial-Induced Mitochondrial Biogenesis Enhances Intercellular Mitochondrial Transfer Efficiency"
DOI: 10.5281/zenodo.15723625
title: Nanomaterial-Induced Mitochondrial Biogenesis Enhances Intercellular Mitochondrial Transfer Efficiency in Human Mesenchymal Stem Cells

description: Raw data (GraphPad files, confocal images, uncropped western blot images ) of the publication titled "Nanomaterial-Induced Mitochondrial Biogenesis Enhances Intercellular Mitochondrial Transfer Efficiency"
DOI: 10.25346/s6eecgix/86ajqm
title: msXL_334v_31_15.tif
DOI: 10.25346/s6eecgix/xci9ro
title: msXL_334v_31_14.tif
DOI: 10.25346/s6eecgix/nbjvkm
title: msXL_334v_31_13.tif
DOI: 10.25346/s6eecgix/7st1tj
title: msXL_334v_22_73.tif
DOI: 10.25346/s6eecgix/1prvuh
title: msXL_334v_22_72.tif
DOI: 10.25346/s6eecgix/v6avhr
title: msXL_334v_22_71.tif
DOI: 10.25346/s6eecgix/dv0odd
title: msXL_334v_22_70.tif
DOI: 10.25346/s6eecgix/veszbk
title: msXL_334v_22_69.tif
DOI: 10.25346/s6eecgix/fedwmz
title: msXL_334v_22_68.tif
DOI: 10.25346/s6eecgix/1sz1nl
title: msXL_334v_22_67.tif
DOI: 10.25346/s6eecgix/5reurn
title: msXL_334v_22_66.tif
DOI: 10.25346/s6eecgix/3lz6g3
title: msXL_334v_22_65.tif
DOI: 10.25346/s6eecgix/2twegh
title: msXL_334v_22_64.tif
DOI: 10.25346/s6eecgix/6ewlat
title: msXL_334v_22_63.tif
DOI: 10.25346/s6eecgix/r9s5ch
title: msXL_334v_22_62.tif
DOI: 10.25346/s6eecgix/1vdfl2
title: msXL_334v_15_12.tif
DOI: 10.25346/s6eecgix/ru5ngo
title: msXL_334v_15_11.tif
DOI: 10.25346/s6eecgix/4vmkbt
title: msXL_334v_15_10.tif
DOI: 10.25346/s6eecgix/mouz30
title: msXL_334v_15_09.tif
DOI: 10.25346/s6eecgix/jpnfqo
title: msXL_334v_15_08.tif
DOI: 10.25346/s6eecgix/9xnyso
title: msXL_334v_15_07.tif
DOI: 10.25346/s6eecgix/5zxuz0
title: msXL_334v_15_06.tif
DOI: 10.25346/s6eecgix/fssl18
title: msXL_334v_15_05.tif
DOI: 10.25346/s6eecgix/otcbit
title: msXL_334v_15_04.tif
DOI: 10.25346/s6eecgix/rhmt64
title: msXL_334v_15_03.tif
DOI: 10.25346/s6eecgix/cknmry
title: msXL_334v_15_02.tif
DOI: 10.25346/s6eecgix/r2wzdz
title: msXL_334v_15_01.tif
DOI: 10.25346/s6eecgix/dklyjb
title: msXL_334v_10_61.tif
DOI: 10.25346/s6eecgix/2ddyf2
title: msXL_334v_10_60.tif
DOI: 10.25346/s6eecgix/wtctkv
title: msXL_334v_10_59.tif
DOI: 10.25346/s6eecgix/lpvley
title: msXL_334v_10_58.tif
DOI: 10.25346/s6eecgix/bgvj9f
title: msXL_334v_10_57.tif
DOI: 10.25346/s6eecgix/kiwwul
title: msXL_334v_10_56.tif
DOI: 10.25346/s6eecgix/xrajxj
title: msXL_334v_10_55.tif
DOI: 10.26023/qxva-qqaw-t109
title: ACCLIP: Low Rate (LRT - 1 sps) Navigation, State Parameter, and Microphysics Flight-Level Data - ICARTT format. Version 1.1

description: This data set includes airborne measurements obtained from the NSF/NCAR HIAPER GV aircraft (Tail Number N677F) during the ACCLIP project. The files contain low rate navigation, state parameter, and microphysics flight-level data in ICARTT format.
DOI: 10.25346/s6eecgix/hn7o1t
title: msXL_334v_10_54.tif
DOI: 10.25346/s6eecgix/4xbpk3
title: msXL_334v_10_53.tif
DOI: 10.25346/s6eecgix/lrksfx
title: msXL_334v_10_52.tif
DOI: 10.25346/s6eecgix/dvr5ia
title: msXL_334v_10_51.tif
DOI: 10.25346/s6eecgix/vicuss
title: msXL_334v_10_50.tif
DOI: 10.25346/s6eecgix/lm9ayo
title: msXL_334v_0_ring.tif
DOI: 10.25346/s6eecgix/mkoa0v
title: msXL_334v.tif
DOI: 10.25346/s6eecgix/xddmiz
title: plane_8.jpg
DOI: 10.25346/s6eecgix/byatty
title: plane_7.jpg
DOI: 10.25346/s6eecgix/ffqmju
title: plane_6.jpg
DOI: 10.25346/s6eecgix/njbrno
title: plane_5.jpg
DOI: 10.25346/s6eecgix/9wrmef
title: plane_4.jpg
DOI: 10.25346/s6eecgix/ak3dvz
title: plane_3.jpg
DOI: 10.25346/s6eecgix/pnwfiw
title: plane_2.jpg
DOI: 10.25346/s6eecgix/xjtfuv
title: plane_1.jpg
DOI: 10.25346/s6eecgix/20zv3d
title: plane_0.jpg
DOI: 10.25346/s6eecgix/2uezgi
title: info.json
DOI: 10.25346/s6eecgix/ybnizs
title: plane_8.jpg
DOI: 10.25346/s6eecgix/rjodbn
title: plane_7.jpg
DOI: 10.25346/s6eecgix/6qk67e
title: plane_6.jpg
DOI: 10.25346/s6eecgix/kn85bv
title: plane_5.jpg
DOI: 10.25346/s6eecgix/vofoqm
title: plane_4.jpg