cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34917/21435958
title: A Case Study on the Medical Library Association’s 2019 Communities Transition Qualitative Data Set

description: In 2019, the Medical Library Association (MLA) adopted a new model of community governance and participation, referred to as the MLA Communities Transition. The Communities Transition was the culmination of long-ranging plans by MLA to support two of its strategic goals: Diversity and Inclusion, and Communities. The reorganization aimed to strengthen MLA member communities, better support programming, reduce administrative overhead, and attract new members. The 2019 - 2020 MLA Rising Stars cohort was tasked to study the Communities Transition and identify lessons that might be applicable to any major future change proposed for the organization.

A qualitative study was designed and conducted to investigate MLA member and leader perceptions of the change process, using John Kotter’s Eight Steps for Organizational Change model as a framework. A set of fifteen open-ended questions was developed based on Kotter’s model and seventeen semi-structured interviews were conducted to gather perceptions and feedback. Interview transcripts were analyzed using a grounded theory approach to explore and identify several themes across all discussions. 
Four major themes were identified: communication between leadership and membership, leadership during the change process, membership investment in change, and instituting change and future recommendations. The study revealed strengths in the overall implementation and execution of the transition, but also highlighted several perceived issues with communication and information-sharing.
Study findings were used to develop recommendations for improved communication strategies and for handling large scale changes within the organization in the future.
DOI: 10.34810/data72/258
title: 01CO_1.MR.0004.0160.2016.02.04.15.44.11.109375.67140307.IMA
DOI: 10.34810/data72/259
title: 01CO_1.MR.0004.0094.2016.02.04.15.44.11.109375.67137661.IMA
DOI: 10.34810/data72/260
title: 01CO_1.MR.0004.0222.2016.02.04.15.44.11.109375.67143816.IMA
DOI: 10.5281/zenodo.5115099
title: Functional Delta Connectivity and Impacts on Lake Ice in the Colville Delta, Alaska

description: This data is public for a manuscript under review. Corresponding code can be found on Github: https://github.com/whyana/colvilleConnectivity File and variable descriptions can be found in ReadMe_zenodo.docx OR on Github: https://github.com/whyana/colvilleConnectivity
DOI: 10.34810/data72/261
title: 01CO_1.MR.0004.0214.2016.02.04.15.44.11.109375.67143496.IMA
DOI: 10.5281/zenodo.5115102
title: Injecting Software Faults in Python Applications: The OpenStack Case Study - Supplemental Material

description: Injecting Software Faults in Python Applications: The OpenStack Case Study - Supplemental Material
DOI: 10.34810/data72/262
title: 01CO_1.MR.0004.0232.2016.02.04.15.44.11.109375.67144217.IMA
DOI: 10.34810/data72/263
title: 01CO_1.MR.0004.0091.2016.02.04.15.44.11.109375.67137540.IMA
DOI: 10.34810/data72/264
title: 01CO_1.MR.0004.0226.2016.02.04.15.44.11.109375.67143977.IMA
DOI: 10.5281/zenodo.5115114
title: Injecting Software Faults in Python Applications: The OpenStack Case Study - Supplemental Material

description: Injecting Software Faults in Python Applications: The OpenStack Case Study - Supplemental Material
DOI: 10.34810/data72/265
title: 01CO_1.MR.0004.0097.2016.02.04.15.44.11.109375.67137781.IMA
DOI: 10.6084/m9.figshare.11653200
title: Simulated Satellite Imagery

description: This data set contains the original training data and the processed result of the simulated satellite images. A third-party python library named "PyTorch CycleGAN" was used to simulate satellite images.
DOI: 10.6084/m9.figshare.11653200.v2
title: Simulated Satellite Imagery

description: This data set contains the original training data and the processed result of the simulated satellite images. A third-party python library named "PyTorch CycleGAN" was used to simulate satellite images.
DOI: 10.34810/data72/266
title: 01CO_1.MR.0004.0155.2016.02.04.15.44.11.109375.67140106.IMA
DOI: 10.6084/m9.figshare.15019593.v1
title: Madzivanzira et al. 2021 Fish and Macrophytes consumption.xlsx

description: This data supports laboratory experiments to determine potential ecological and socioeconomic impacts conferred by the crayfish species: <i>Cherax quadricarinatus</i> and <i>Procambarus clarkii</i> relative to a functionally similar native analogue, the river crab <i>Potamonautes perlatus</i>, on two static but different resources. The data contains the individual consumption rates of macrophyte and scavenging rates on fish by the three decapods. The data also contains the morphometric measurements of crayfish and crabs used for the experiments.
DOI: 10.34810/data72/267
title: 01CO_1.MR.0004.0021.2016.02.04.15.44.11.109375.67134732.IMA
DOI: 10.34810/data72/268
title: 01CO_1.MR.0004.0141.2016.02.04.15.44.11.109375.67139545.IMA
DOI: 10.34810/data72/269
title: 01CO_1.MR.0004.0093.2016.02.04.15.44.11.109375.67137621.IMA
DOI: 10.34810/data72/270
title: 01CO_1.MR.0004.0083.2016.02.04.15.44.11.109375.67137219.IMA
DOI: 10.34810/data72/271
title: 01CO_1.MR.0004.0038.2016.02.04.15.44.11.109375.67135414.IMA
DOI: 10.5517/ccdc.csd.cc217gyq
title: CCDC 1884023: Experimental Crystal Structure Determination

description: Related Article: Izumi Iwakura, Sena Hashimoto, Kotaro Okamura, Keiko Komori-Orisaku, Shoji Akai, Atsushi Yabushita|2021|New J.Chem.|45|12346|doi:10.1039/D1NJ01429C
DOI: 10.5517/ccdc.csd.cc2715cv
title: CCDC 2056706: Experimental Crystal Structure Determination

description: Related Article: Rousunara Khatun, Malay Dolai, Mihir Sasmal, Nayim Sepay, Mahammad Ali|2021|New J.Chem.|45|12678|doi:10.1039/D1NJ01492G
DOI: 10.5517/ccdc.csd.cc273d3w
title: CCDC 2058837: Experimental Crystal Structure Determination

description: Related Article: Valerii Y. Sirenko, Olesia I. Kucheriv, Dina D. Naumova, Igor V. Fesych, Rostyslav P. Linnik, Ioan-Andrei Dascălu, Sergiu Shova, Igor O. Fritsky, Il'ya A. Gural'skiy|2021|New J.Chem.|45|12606|doi:10.1039/D1NJ01089A
DOI: 10.5517/ccdc.csd.cc273d4x
title: CCDC 2058838: Experimental Crystal Structure Determination

description: Related Article: Valerii Y. Sirenko, Olesia I. Kucheriv, Dina D. Naumova, Igor V. Fesych, Rostyslav P. Linnik, Ioan-Andrei Dascălu, Sergiu Shova, Igor O. Fritsky, Il'ya A. Gural'skiy|2021|New J.Chem.|45|12606|doi:10.1039/D1NJ01089A
DOI: 10.5517/ccdc.csd.cc273d5y
title: CCDC 2058839: Experimental Crystal Structure Determination

description: Related Article: Valerii Y. Sirenko, Olesia I. Kucheriv, Dina D. Naumova, Igor V. Fesych, Rostyslav P. Linnik, Ioan-Andrei Dascălu, Sergiu Shova, Igor O. Fritsky, Il'ya A. Gural'skiy|2021|New J.Chem.|45|12606|doi:10.1039/D1NJ01089A
DOI: 10.5517/ccdc.csd.cc273d6z
title: CCDC 2058840: Experimental Crystal Structure Determination

description: Related Article: Valerii Y. Sirenko, Olesia I. Kucheriv, Dina D. Naumova, Igor V. Fesych, Rostyslav P. Linnik, Ioan-Andrei Dascălu, Sergiu Shova, Igor O. Fritsky, Il'ya A. Gural'skiy|2021|New J.Chem.|45|12606|doi:10.1039/D1NJ01089A
DOI: 10.5517/ccdc.csd.cc278rv4
title: CCDC 2064006: Experimental Crystal Structure Determination

description: Related Article: Yi-Hong Cai, Hsin-Yun Chih, Gene-Hsiang Lee, Chung K. Lai|2021|New J.Chem.|45|12557|doi:10.1039/D1NJ02001C
DOI: 10.5517/ccdc.csd.cc27fn8m
title: CCDC 2068700: Experimental Crystal Structure Determination

description: Related Article: Manfredi Caruso, Massimo Cametti, Kari Rissanen, Javier Martí-Rujas|2021|New J.Chem.|45|12448|doi:10.1039/D1NJ02175C
DOI: 10.5517/ccdc.csd.cc27m6fj
title: CCDC 2074037: Experimental Crystal Structure Determination

description: Related Article: Gianluca Accorsi, Agostina-Lina Capodilupo, Rosa María Claramunt, Guy J. Clarkson, A. Farrán, Francesco G. Gatti, Salvador León, Silvia Venturi|2021|New J.Chem.|45|12471|doi:10.1039/D1NJ01677F
DOI: 10.5517/ccdc.csd.cc27m6gk
title: CCDC 2074038: Experimental Crystal Structure Determination

description: Related Article: Gianluca Accorsi, Agostina-Lina Capodilupo, Rosa María Claramunt, Guy J. Clarkson, A. Farrán, Francesco G. Gatti, Salvador León, Silvia Venturi|2021|New J.Chem.|45|12471|doi:10.1039/D1NJ01677F
DOI: 10.5517/ccdc.csd.cc27m6hl
title: CCDC 2074039: Experimental Crystal Structure Determination

description: Related Article: Gianluca Accorsi, Agostina-Lina Capodilupo, Rosa María Claramunt, Guy J. Clarkson, A. Farrán, Francesco G. Gatti, Salvador León, Silvia Venturi|2021|New J.Chem.|45|12471|doi:10.1039/D1NJ01677F
DOI: 10.5517/ccdc.csd.cc27n716
title: CCDC 2075017: Experimental Crystal Structure Determination

description: Related Article: Sha Zhang, Feng-Hua Kang, Jian-Bing Tan, De-Kun Chen, Min Kuang, Wen-Xuan Wang, Kang-Ping Xu, Zhen-xing Zou|2021|New J.Chem.|45|12700|doi:10.1039/D1NJ01993G
DOI: 10.5517/ccdc.csd.cc27rjl4
title: CCDC 2078196: Experimental Crystal Structure Determination

description: Related Article: Wei Zhou, Zheng Li, You-Ping Tian, Xiao-Xue Han, Xiong-Li Liu|2021|New J.Chem.|45|12356|doi:10.1039/D1NJ02257A
DOI: 10.5517/ccdc.csd.cc27rjm5
title: CCDC 2078197: Experimental Crystal Structure Determination

description: Related Article: Wei Zhou, Zheng Li, You-Ping Tian, Xiao-Xue Han, Xiong-Li Liu|2021|New J.Chem.|45|12356|doi:10.1039/D1NJ02257A
DOI: 10.5517/ccdc.csd.cc1pfdr8
title: CCDC 1562020: Experimental Crystal Structure Determination

description: Related Article: Thamodharan Viswanathan, Nallasamy Palanisami|2021|New J.Chem.|45|12509|doi:10.1039/D1NJ01652K
DOI: 10.5517/ccdc.csd.cc27mddp
title: CCDC 2074222: Experimental Crystal Structure Determination

description: Related Article: Jamie N. Melville, Paul V. Bernhardt|2021|Inorg.Chem.|60|9709|doi:10.1021/acs.inorgchem.1c01001
DOI: 10.5517/ccdc.csd.cc27n6x1
title: CCDC 2075013: Experimental Crystal Structure Determination

description: Related Article: Sha Zhang, Feng-Hua Kang, Jian-Bing Tan, De-Kun Chen, Min Kuang, Wen-Xuan Wang, Kang-Ping Xu, Zhen-xing Zou|2021|New J.Chem.|45|12700|doi:10.1039/D1NJ01993G
DOI: 10.5517/ccdc.csd.cc26bsw7
title: CCDC 2036169: Experimental Crystal Structure Determination

description: Related Article: Yu Wang, Siyu Xu, Heng Li, Haixia Ma, Yazhou Zhang, Zhaoqi Guo|2021|New J.Chem.|45|12705|doi:10.1039/D1NJ02345D
DOI: 10.5517/ccdc.csd.cc26bt0d
title: CCDC 2036173: Experimental Crystal Structure Determination

description: Related Article: Yu Wang, Siyu Xu, Heng Li, Haixia Ma, Yazhou Zhang, Zhaoqi Guo|2021|New J.Chem.|45|12705|doi:10.1039/D1NJ02345D
DOI: 10.5517/ccdc.csd.cc26bt1f
title: CCDC 2036174: Experimental Crystal Structure Determination

description: Related Article: Yu Wang, Siyu Xu, Heng Li, Haixia Ma, Yazhou Zhang, Zhaoqi Guo|2021|New J.Chem.|45|12705|doi:10.1039/D1NJ02345D
DOI: 10.34810/data72/272
title: 01CO_1.MR.0004.0024.2016.02.04.15.44.11.109375.67134852.IMA
DOI: 10.34810/data72/273
title: 01CO_1.MR.0004.0173.2016.02.04.15.44.11.109375.67140828.IMA
DOI: 10.34810/data72/274
title: 01CO_1.MR.0004.0190.2016.02.04.15.44.11.109375.67141510.IMA
DOI: 10.34810/data72/275
title: 01CO_1.MR.0004.0239.2016.02.04.15.44.11.109375.67144498.IMA
DOI: 10.34810/data72/276
title: 01CO_1.MR.0004.0120.2016.02.04.15.44.11.109375.67138703.IMA
DOI: 10.34810/data72/277
title: 01CO_1.MR.0004.0152.2016.02.04.15.44.11.109375.67139986.IMA
DOI: 10.34810/data72/278
title: 01CO_1.MR.0004.0169.2016.02.04.15.44.11.109375.67140668.IMA
DOI: 10.34810/data72/279
title: 01CO_1.MR.0004.0076.2016.02.04.15.44.11.109375.67136939.IMA
DOI: 10.25345/c5jg09
title: MassIVE MSV000087855 - Complementary proteomic approaches identify HIP1 as a context dependent regulator of cell migration and invasion.
title: The epithelial-to-mesenchymal transition (EMT) is a fundamental process in metazoan development and is important for fibrosis, wound healing, and tumor metastasis. Transforming growth factor TGF-beta induces EMT by triggering a signaling cascade that initiates with the clathrin-mediated endocytosis of the ligand-receptor complex. There is growing evidence that endocytosis is a key player in EMT and cancer progression. Here we demonstrate the power of using orthogonal proteomic approaches to examine protein dynamics during EMT. Using TGF-beta as an inducer of EMT, we identified endocytic components that were up-regulated in mesenchymal cells. We then showed that HIP1, a component of the clathrin mediated endocytic machinery, modulates cell migration and invasion upon EMT induction and in metastatic cancer cells. HIP1 knock-down and overexpression led to changes in the abundance of several secreted proteins with known roles in tumor metastasis. Protein interaction and sub-cellular co-localization studies indicate that HIP1 interacts with components of, and resides at, multiple sites of vesicular trafficking that rely on both clathrin-dependent and clathrin-independent mechanisms.
DOI: 10.34810/data72/280
title: 01CO_1.MR.0004.0019.2016.02.04.15.44.11.109375.67134652.IMA
DOI: 10.34810/data72/281
title: 01CO_1.MR.0004.0136.2016.02.04.15.44.11.109375.67139344.IMA
DOI: 10.34740/kaggle/dsv/2442730
title: US counties COVID 19 dataset
DOI: 10.6084/m9.figshare.12197655
title: Fake Satellite Imagery

description: This data set contains the original training data and the processed result of the fake satellite images. Also, the codes to detect fake satellite images are also attached.<br>
DOI: 10.6084/m9.figshare.12197655.v1
title: Fake Satellite Imagery

description: This data set contains the original training data and the processed result of the fake satellite images. Also, the codes to detect fake satellite images are also attached.<br>
DOI: 10.34810/data72/282
title: 01CO_1.MR.0004.0087.2016.02.04.15.44.11.109375.67137380.IMA
DOI: 10.34810/data72/283
title: 01CO_1.MR.0004.0208.2016.02.04.15.44.11.109375.67142231.IMA
DOI: 10.34810/data72/284
title: 01CO_1.MR.0004.0092.2016.02.04.15.44.11.109375.67137580.IMA
DOI: 10.5066/f70z728b
title: Digital elevation model outputs from wetland accreting rate model of ecosystem resilience (WARMER) at ten year intervals from 2010-2110

description: Digital elevation model outputs from wetland accreting rate model of ecosystem resilience (WARMER) at ten year intervals from 2010-2110. Baseline elevations were collected with RTK GPS units and LiDAR elevations in non-surveyed areas were also corrected using LEAN method. Historical accretion rates were collected at each salt marsh and used to parameterize WARMER, predicting future elevations. These data support the following publication: Rosencranz JA, Thorne KM, Buffington KJ, et al. Sea-level rise, habitat loss, and potential extirpation of a salt marsh specialist bird in urbanized landscapes. Ecol Evol. 2018;00:1-11. https://doi.org/10.1002/ece3.4196
DOI: 10.34810/data72/285
title: 01CO_1.MR.0004.0131.2016.02.04.15.44.11.109375.67139144.IMA
DOI: 10.34810/data72/286
title: 01CO_1.MR.0004.0052.2016.02.04.15.44.11.109375.67135976.IMA
DOI: 10.34810/data72/287
title: 01CO_1.MR.0004.0067.2016.02.04.15.44.11.109375.67136578.IMA
DOI: 10.34810/data72/288
title: 01CO_1.MR.0004.0015.2016.02.04.15.44.11.109375.67134491.IMA
DOI: 10.21227/h4xq-4h55
title: Ultra High Frequency AcousticCoda Waves

description: Due to the multi-path propagation and extreme sensitivity to minor changes in the propagation medium, the coda waves open new fascinating possibilities in non-destructive evaluation and acoustic imaging. However, their noise-like structure and high spurious sensitivity for ambient conditions (temperature, humidity, and others) make it challenging to perform localized inspection in the overall coda wave evolution. While existing deterministic solutions reach their limit in handling complex data, emerging techniques such as deep learning-based algorithms have shown a promising potential to overcome these limitations. This paper proposes a deep neural network that paves the way to make the complex features of coda waves more handleable to reliably exploit coda waves in several applications even in a changing or unstable environment. Specifically, designed a Coda-Convolutional Neural Network that is able to identify coda waves with 95.65% precision in a silicon chaotic cavity including 5 emitters and 16 receivers using ultra-high frequency ultrasonic coda waves.
DOI: 10.34810/data72/289
title: 01CO_1.MR.0004.0027.2016.02.04.15.44.11.109375.67134973.IMA
DOI: 10.34810/data72/290
title: 01CO_1.MR.0004.0203.2016.02.04.15.44.11.109375.67142031.IMA
DOI: 10.34810/data72/291
title: 01CO_1.MR.0004.0012.2016.02.04.15.44.11.109375.67134371.IMA
DOI: 10.34810/data72/292
title: 01CO_1.MR.0004.0140.2016.02.04.15.44.11.109375.67139505.IMA
DOI: 10.34810/data72/293
title: 01CO_1.MR.0004.0010.2016.02.04.15.44.11.109375.67134291.IMA
DOI: 10.34810/data72/294
title: 01CO_1.MR.0004.0137.2016.02.04.15.44.11.109375.67139385.IMA
DOI: 10.34810/data72/295
title: 01CO_1.MR.0004.0148.2016.02.04.15.44.11.109375.67139826.IMA
DOI: 10.34810/data72/296
title: 01CO_1.MR.0004.0044.2016.02.04.15.44.11.109375.67135655.IMA
DOI: 10.34810/data72/297
title: 01CO_1.MR.0004.0102.2016.02.04.15.44.11.109375.67137981.IMA
DOI: 10.34810/data72/298
title: 01CO_1.MR.0004.0078.2016.02.04.15.44.11.109375.67137019.IMA
DOI: 10.34810/data72/299
title: 01CO_1.MR.0004.0049.2016.02.04.15.44.11.109375.67135856.IMA
DOI: 10.34810/data72/300
title: 01CO_1.MR.0004.0164.2016.02.04.15.44.11.109375.67140467.IMA
DOI: 10.6073/pasta/cd31aee986142acd28e50ecb517c3c31
title: Microbial Sampling from Shark River Slough and Taylor Slough, Everglades National Park, South Florida, USA (FCE LTER) from January 2001 to Present

description: We collected monthly observations of water microbial characteristics from each of the FCE LTER sites beginning in February 2001. Bacteria counts using DAPI epifluorescence, heterotrophic bacteria production with tritiated Thymidine uptake, and algal energetics and chl a using the PAM fluorometer were determined from each of the water samples. Bacteria counts in Shark River Slough in the freshwater end of the transect revealed highest bacteria numbers upon marsh rewetting after the dry down. The highest overall count of bacteria was found at the most freshwater point adjacent to the perimeter of the water conservation area but only in March of 2001. Peak numbers of bacteria in the saline end of Shark River transect occurred in December and July. There is some evidence that these higher bacteria numbers in the SR transect are associated with higher salinities. Highest bacteria counts along the Taylor slough transect were observed at the mouth of the Taylor River with peak counts in the wet season in October. Bacteria densities also increased from the eastern to western end of the transect in Florida Bay. Heterotrophic bacterial production did not relate closely bacteria numbers and exhibited highest numbers in the dry season. There was no discernible relationship between salinity and bacteria production as seen in bacteria numbers. Monthly observations using PAM fluorometry revealed that brown algae was the greatest contribution to the algal chal a pool and this relationship was consistent across all FCE LTER sites. Converse to the pattern of bacteria abundance along the Shark River transect, there was evidence that algal biomass decreases from freshwater to estuary. In the Shark River, algal energetics increased from marsh to estuary as well as in the panhandle region of the Taylor River transect. From these observations we conclude the behavior of the microbial loop and interactions generated between functional guilds is highly variable along individual transects and between the Shark River and Taylor River transect. Wet dry season dynamics partially explain temporal variability in microbial dynamics along the individual transects yet responses were unique for each section of the transect as freshwater versus estuarine versus Bay. Relationships between salinity and microbial parameters in this case, were not easily discerned but were more consistent within the two river transects than between river transects.
DOI: 10.34810/data72/301
title: 01CO_1.MR.0004.0186.2016.02.04.15.44.11.109375.67141349.IMA
DOI: 10.34810/data72/302
title: 01CO_1.MR.0004.0240.2016.02.04.15.44.11.109375.67144538.IMA
DOI: 10.34810/data72/303
title: 01CO_1.MR.0004.0199.2016.02.04.15.44.11.109375.67141870.IMA
DOI: 10.34810/data72/304
title: 01CO_1.MR.0004.0217.2016.02.04.15.44.11.109375.67143616.IMA
DOI: 10.34810/data72/305
title: 01CO_1.MR.0004.0039.2016.02.04.15.44.11.109375.67135454.IMA
DOI: 10.34810/data72/306
title: 01CO_1.MR.0004.0213.2016.02.04.15.44.11.109375.67143456.IMA
DOI: 10.34810/data72/308
title: 01CO_1.MR.0004.0236.2016.02.04.15.44.11.109375.67144377.IMA
DOI: 10.25919/615b-vt08
title: Parkes observations for project PX500 semester 2021APRS_12

description: This proposal relates to time purchased by the Chinese Academy of Sciences for Parkes follow-up confirmation and timing of FAST discoveries. As the observing time has been purchased this proposal (and the related PX501) does not require TAC grading. The primary reason for submitting a proposal is to ensure an outreach statement and that the proposal is entered into OPAL for the data archive to access. The Chinese team have two time requests. The time scheduled for the first, relating to this proposal, will be allocated in blocks of 24 hours and the data will become available in the data archive with an 18 month embargo period. The second type of time will be scheduled in shorter blocks and the data archived with a 10 year embargo.
DOI: 10.25919/bc2z-0b45
title: Parkes observations for project PX500 semester 2021APRS_13

description: This proposal relates to time purchased by the Chinese Academy of Sciences for Parkes follow-up confirmation and timing of FAST discoveries. As the observing time has been purchased this proposal (and the related PX501) does not require TAC grading. The primary reason for submitting a proposal is to ensure an outreach statement and that the proposal is entered into OPAL for the data archive to access. The Chinese team have two time requests. The time scheduled for the first, relating to this proposal, will be allocated in blocks of 24 hours and the data will become available in the data archive with an 18 month embargo period. The second type of time will be scheduled in shorter blocks and the data archived with a 10 year embargo.
DOI: 10.34810/data72/309
title: 01CO_1.MR.0004.0181.2016.02.04.15.44.11.109375.67141149.IMA
DOI: 10.5281/zenodo.5115195
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Stylianos Chatzimanolis, https://orcid.org/0000-0001-9008-0611. Claims were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.34810/data72/310
title: 01CO_1.MR.0004.0115.2016.02.04.15.44.11.109375.67138503.IMA
DOI: 10.34810/data72/311
title: 01CO_1.MR.0004.0059.2016.02.04.15.44.11.109375.67136257.IMA
DOI: 10.34810/data72/312
title: 01CO_1.MR.0004.0219.2016.02.04.15.44.11.109375.67143696.IMA
DOI: 10.34810/data72/313
title: 01CO_1.MR.0004.0080.2016.02.04.15.44.11.109375.67137099.IMA
DOI: 10.34810/data72/314
title: 01CO_1.MR.0004.0220.2016.02.04.15.44.11.109375.67143736.IMA
DOI: 10.34810/data72/315
title: 01CO_1.MR.0004.0001.2016.02.04.15.44.11.109375.67133930.IMA
DOI: 10.34810/data72/316
title: 01CO_1.MR.0004.0174.2016.02.04.15.44.11.109375.67140868.IMA
DOI: 10.34810/data72/317
title: 01CO_1.MR.0004.0206.2016.02.04.15.44.11.109375.67142151.IMA
DOI: 10.34810/data72/318
title: 01CO_1.MR.0004.0187.2016.02.04.15.44.11.109375.67141389.IMA
DOI: 10.34810/data72/319
title: 01CO_1.MR.0004.0101.2016.02.04.15.44.11.109375.67137941.IMA
DOI: 10.34810/data72/320
title: 01CO_1.MR.0004.0107.2016.02.04.15.44.11.109375.67138182.IMA
DOI: 10.34810/data72/321
title: 01CO_1.MR.0004.0057.2016.02.04.15.44.11.109375.67136177.IMA
DOI: 10.34810/data72/322
title: 01CO_1.MR.0004.0182.2016.02.04.15.44.11.109375.67141189.IMA
DOI: 10.34810/data72/323
title: 01CO_1.MR.0004.0230.2016.02.04.15.44.11.109375.67144137.IMA
DOI: 10.34810/data72/324
title: 01CO_1.MR.0004.0070.2016.02.04.15.44.11.109375.67136698.IMA
DOI: 10.34810/data72/325
title: 01CO_1.MR.0004.0125.2016.02.04.15.44.11.109375.67138903.IMA