Find research datasets worth reusing

opencc-by-4.0May 2024View details →

Datenaufbereitung zum State-of-the-Art und Fortschritt europäischer Gaia-X sowie Datenraum Initiativen mit einem Schwerpunkt auf Industrie 4.0 Anwendungsfälle

In seiner Gesamtheit umfasst der Datensatz eine Sammlung von Initiativen und Projekten, die mit Gaia-X sowie Data Spaces im Allgemeinen in Verbindung stehen. Ziel der Datensammlung war es, eine detaillierte Übersicht über bestehende Projekte zu erhalten und diese systematisch zu kategorisieren, um anschließend spezifische industrielle Anwendungsfälle herauszuarbeiten und diese zu analysieren. Der Zeitraum dieser Sammlung erstreckte sich von April 2023 bis März 2024. Anzumerken ist, dass sämtliche zur Verfügung stehenden Informationen innerhalb dieses Zeitraums in den Datensatz aufgenommen wurden. Ab März 2024 wurden keine weiteren Daten erfasst, wodurch der Datensatz den aktuellen Stand bis zu diesem Zeitpunkt widerspiegelt. Insgesamt wurden 211 Initiativen aus 281 Quellen zusammengetragen und ausgewertet. Diese unterteilen sich (über alle Domänen hinweg) in 102 Data Spaces und 93 Anwendungsfälle. Die 93 Anwendungsfälle beinhalten 47 Industrie 4.0 relevante Anwendungsfälle.

opencc-by-4.0Oct 2017View details →

A recent overview of the state-of-the-art elements of text classification - dataset

The two available datasets were used to conduct the quantitative analysis of the text classification area. The set, such as: <ol> <li>biblio.bib contains all articles that are grouped in categories</li> <li>biblio.csv contains processed records from biblio.bib, based on it were built the statistics presented in the article</li> </ol>

opencc-by-4.0Aug 2021View details →

Desk research of 107 case studies on state-of-the-art of cultural tourism interventions

The aim of Work Package 3 of the SmartCulTour project (<a href="http://www.smartcultour.eu">www.smartcultour.eu</a>) is to provide a state-of-the-art overview of cultural tourism interventions implemented in European cities and regions, thereby identifying best practices and the impacts and success conditions of cultural tourism interventions. To this end, the consortium identified 107 interesting cultural tourism interventions throughout Europe, with a geographical coverage of: Belgium (9), Italy (8), The Netherlands (8), Serbia (7), Romania (6), Croatia (5), Hungary (4), Portugal (4), Spain (4), United Kingdom (4), Finland (3), France (3), Sweden (3), Other countries (24), Multiple countries (15). The "Overview and taxonomy of 107 interventions" lists every intervention that was studied, as well as their respective classification given, based on the description and objective of the intervention. Within this table, a value of "1" is its primary categorization, with a value of "2" assigned to a secondary taxonomy. Each intervention can have multiple purposes and therefore belong to different categories.The taxonomy of cultural tourism interventions is further described in "State of the art of cultural tourism interventions" (DOI: 10.5281/zenodo.5270321). The 107 cultural tourism interventions were analyzed via desk research only during the period September 2020-January 2021, based on available secondary data and following a standardized data collection form. This form is included here as "Internal data collection form used for analysis". The forms collect data on: <ul> <li>Context and background information;</li> <li>The 'reason why' of the intervention;</li> <li>The intervention;</li> <li>Resources and tools necessary to design and implement the interventions;</li> <li>Impacts (expected, perceived and measured);</li> <li>(Perceived) success conditions and limiting factors.</li> </ul> The zip-file "Internal forms of 107 interventions" contains all 107 completed data collection forms.

opencc-by-4.0Jan 2023View details →

A "short blanket" dilemma for a state-of-the-art neural network potential for water: Reproducing experimental properties or the underlying many-body physics?

Deep neural network (DNN) potentials have recently gained popularity in computer simulations of a wide range of molecular systems, from liquids to materials. In this study, we explore the possibility of combining the computational efficiency of the DeePMD framework and the demonstrated accuracy of the MB-pol data-driven many-body potential to train a DNN potential for large-scale simulations of water across its phase diagram. We find that the DNN potential is able to reliably reproduce the MB-pol results for liquid water but provides a less accurate description of the vapor-liquid equilibrium properties. This shortcoming is traced back to the inability of the DNN potential to correctly represent many-body interactions. An attempt to explicitly include information about many-body effects results in a new DNN potential that exhibits the opposite performance, being able to correctly reproduce the MB-pol vapor-liquid equilibrium properties but losing accuracy in the description of the liquid properties. These results suggest that DeePMD-based DNN potentials are not able to correctly "learn" and, consequently, represent many-body interactions, which implies that DNN potentials may have limited ability to predict properties for state points that are not explicitly included in the training process. The computational efficiency of the DeePMD framework can still be exploited to train DNN potentials on data-driven many-body potentials, which can thus enable large-scale, "chemically accurate" simulations of various molecular systems, with the caveat that the target state points must have been adequately sampled by the reference data-driven many-body potential in order to guarantee a faithful representation of the associated properties.

opencc-by-4.0Apr 2023View details →

State of the art of studies on earthworm populations in the state of Paraná

In this review, we included all the studies performed in the state of Paraná, Brazil, which had data on earthworms. We reviewed the literature for all publications (journal articles, dissertations, theses, conference proceedings, book chapters) carried out in the state of Paraná, Brazil, which had data on earthworms. The period evaluated ranged from 1986 (earliest date in the state) to 2020. Searches were performed in online databases including Sicence Direct, Scielo, CAPES and the digital collection of dissertations and theses from Brazilian Universities (BDTD).  Overall 51 publications had earthworm data, including abundance, biomass, species, richness or just presence/absence. Data were extracted from these publications and compiled into an excel file. The dataset contains information gathered from 62 of the 399 municipalities in Paraná, and includes separation in ten geopolitical regions (IBGE 2010), as well as topographic regions and climate (Köppen, 1931). The ten geopolitical mesoregions are: West (WE), Northwest (NW), Center West (CW), Center North (CN), North Pioneer (NP), Center East (CE), Metropolitan (MT), Center South (CS), Southeast (SE) and Southwest (SW). The three topographic regions include the First, Second and Third Plateaus, and the Coastal Lowland.  Earthworm data are presented as total abundance (number of individual m-2), fresh biomass (in g m-2) and species richness (total number). We also provide information on each species encountered, its ecological category, and whether it is native or exotic to the state of Paraná. For earthworm species, ecological category information follows the classification of Bouché (1977), including the intermediate categories: e.g., anecic, epigeic, endogeic, polyhumic endogeic, mesohumic endogeic, epi-endogeic, endo-epigeic. For each species, full names (when available), and species author(s) and year of the description are provided. Geographic location is provided when possible, with latitude, longitude and altitude, soil types according to the Sistema Brasileiro de Classificação de Solos - SiBCS (Santos et al. 2018). Sampling date and season are also provided, when available. When known, the sampling method(s) used were given. These included quantitative methods involving handsorting, such as 1) the standard Tropical Soil Biology and Fertility (TSBF) Programme method (Anderson & Ingram 1993), in which soils are handsorted from monoliths 25x25 cm square to depths ranging from 10 to 40 cm (identified as TSBF in the spreadsheets); or 2) other monolith dimensions like 20x20, 40x40 and 50x50 cm (identified as Handsorting in the spreadsheets). Qualitative sampling (e.g. Bartz et al. 2014) included: 1) collecting in various niches like deeper soil layers, litter, under rocks, in and under rotting logs, next to water bodies like streams, lakes and swamps; 2) chemical extraction using a diluted formalin solution (usually over an area 50x50 cm), following recommendations of ISO 23611-1 (2017), and pouring of the solution either on the soil surface, or at the bottom of the pit; 3) electrical extraction using a modifed apparatus (Azevedo et al. 2010), based on the Octet-Method (Thielemann 1986). The determination of LUS was based on Nadolny et al. (2020), which characterized Native Vegetation, Forest Plantation (including forest with Pinus sp. and Eucalyptus sp.), Pasture, Integrated Systems (e.g., agropastoral, silvopastoral or agrosilvopastoral systems) and agricultural areas (Conventional Tillage, No-Tillage and Minimum Tillage). In addition to these, Perennial Crops, Grass Lawns and Agroforestry Systems were included. The soil chemical and physical analysis data were included in the dataset when performed in the same places as the earthworm sampling. Chemical data included: pH, H+Al, K, Ca, Mg, P, C, sum of Bases, CEC, Base saturation, N, Na. Physical data included: sand, clay and silt proportions, texture, porosity, density and resistance to penetration. All data are provided in excel format and include 5 tabs: Readme, Legend, Earthworms + environment, Species distribution and References. The Readme tab provides information on the associated publication in the Revista Brasileira de Ciência do Solo authored by Dudas et al. (see https://doi.org/10.36783/18069657rbcs20220159). The Legend tab provides a description of the variables used in the other (data) tabs. Earthworms + environment has information on the sampling methods used, the earthworm abundance, biomass and richness found at the different sampling sites in Paraná, and the data on soil and environmental variables. The Species distribution tab provides information on the species found, places of origin, ecological category, sampling method used and LUS. The References tab provides detailed bibliographic information on the sources of the data used to build the tables and the dataset. Overall, in the state of Paraná, 90 species of earthworms were found in 51 counties of the state, of which 66 were native and 24 were exotic. A large number of species (46) are likely new and still must be formally described. Higher species richness was found in native vegetation, which also had a higher proportion of native species (75%). The other LUS with more native species were: Forest Plantation (FP) and No-Tillage (NT), while Conventional Tillage (CT) sites had only 17% native species. Earthworm abundance and biomass were highest in less disturbed LUS such as agroforestry systems, native vegetation, forestry plantation, grass lawns, and permanent crops, compared to the highest disturbance LUS including soil preparation (MT and CT), where the lowest abundance and biomass were found. However, as only 16% of the 399 counties in Paraná have been sampled so far, much further research is needed in order to adequately assess the relationships between earthworms and land use.

opencc-by-4.0Aug 2023View details →

Asymmetry of AMOC Hysteresis in a State-of-the-Art Global Climate Model

These directories contain Python (v3) scripts for plotting/analysing model output. Python scripts can be found in the directory 'Program'. Model output can be found in the directory 'Data'. The processed model output are stored as NETCDF files and using the relevant scripts one can regenerate all the figures. We provided the original model output (native grid) and is only converted to yearly-averaged data (due to storage limitations). Some scripts (e.g., FOV_index.py and AMOC_transport.py) use the original model output and running these script generates in the time series, which are presented in the manuscript.

opencc-by-4.0Oct 2020View details →

How Software Organizations are using the ISO/IEC 29110 Standard's Processes: A Survey of the State of the Art and Practice

ISO/IEC 29110 was developed containing a set of industrially validated practices that can potentially be adopted by software Very Small Entities (VSE). VSEs usually have characteristics that differentiate them from organizations of different sizes, such as extremely limited resources and informal project management processes, tending to adopt Agile methods and having an historical resistance to the adoption of standards, that are in general developed for large organizations. In this sense, our research question arises: "How are software organizations using the ISO/IEC 29110 practices?". To answer this question, a Systematic Mapping Study (SM), and a Survey with software organizations were carried out in order to identify the state of the art and the state of the practice in relation to the use of the standard’s practices. The SM identified 21 primary studies reporting the use of the standard in hundreds of software organizations with positive results such as organizational learning, process improvement, improved communication, and also some negative results, such as deployment difficulties in technical areas and the need for additional time and resources. The Survey carried out with 23 software companies identified that, in general, companies do not explicitly know the content of the standard, but partially carry out, in accordance with the standard, practices related to planning, monitoring, control and execution of a project plan, and do not carry out requirements analysis or architecture and detailed design as defined in the standard.

opencc-by-4.0Apr 2024View details →

Calculated state-of-the art results for solvation and ionization energies of thousands of organic molecules relevant to battery design

This dataset presents molecular properties critical for battery electrolyte design, specifically solvation energies, ionization potentials, and electron affinities. The dataset is intended for use in machine learning model testing and algorithm validation. The properties calculated include solvation energies using the COSMO-RS method [1] and ionization potentials and electron affinities using various high-accuracy computational methods as implemented in MOLPRO [2]. Computational details can be found in Ref. [3], with scripts used to generate the data mostly uploaded to our github repository [4]. Molecular Datasets Considered: <ul> <li> QM9 Dataset: Contains small organic molecules broadly relevant for quantum chemistry [5] </li> <li> Electrolyte Genome Project (EGP): Focuses on materials relevant to electrolytes.[6] </li> <li> GDB17 and ZINC databases: Offer a broad chemical diversity with potential application in battery technologies. [7, 8] </li> </ul> <h2>Data structure</h2> How to Load the Data: All files can be loaded with <code>import json</code> <code>with open("file.json", "r") as f:</code> <code>    data_dict = json.load(f)</code> and the filestructure can be explored with <code>data_dict.keys()</code> We have also added an example script in python that shows how to extract all data from the JSON files following this link <a href="https://github.com/chemspacelab/VienUppDa/blob/main/SolQuest/BIG_MAP_DATA/load_db.py">How to extract the data</a> Note the file structure of the the AMONS JSON files is slightly different as explained below! <h3>Solvation energies</h3> The data is stored in two types of JSON archives: files for full molecules of GDB17 and ZINC and files for amons of GDB17 and ZINC. They are structured differently as amon entries are sorted by the number of heavy atoms in the amon (e.g., all amons with 3 heavy atoms are stored in <code>ni3</code>). Because of the large number of amons with 6 or 7 heavy atoms,they are further split into <code>ni6_1</code>, <code>ni6_2</code>, and so on. A sub dictionary of an amon dictionary or a full molecule dictionary contains the following keys: <code>ECFP</code> - ECFP4 representation vector <code>SMILES</code> - SMILES string <code>SYMBOLS</code> - atomic symbols <code>COORDS</code> - atomic positions in Angstrom <code>ATOMIZATION</code> - atomization energy in [kcal/mol] <code>DIPOLE</code> - dipole moment in Debye <code>ENERGY</code> - energy in Hartree <code>SOLVATION</code> - solvation energy in [kcal/mol] for different solvents at 300 K.   Files:   <code>GDB17.json.zip</code> (unpack with unzip first with unzip <code>GDB17.json.zip</code>) - subset of GDB17 random molecules <code>AMONS_ZINC.json</code> - all amons of ZINC up to 7 heavy atoms <code>EGP.json</code>  - EGP molecules <code>AMONS_GDB17.json</code> - all amons of GDB17 up to 7 heavy atoms <code>QM9IPEA_raw_molpro_output.zip</code> - compressed folder with raw Molpro input and output files <table> <tbody> <tr> <td>File Name</td> <td>Description </td> <td>Molecules</td> </tr> <tr> <td>AMONS_GDB17.json</td> <td>GDB17 amons</td> <td>37860</td> </tr> <tr> <td>AMONS_ZINC.json</td> <td>ZINC amons   </td> <td>88771</td> </tr> <tr> <td>GDB17.json</td> <td>Subset of GDB17</td> <td>309468</td> </tr> <tr> <td>EGP.json </td> <td>EGP molecules   </td> <td>18362</td> </tr> </tbody> </table> Atomic energies $E_{at}$ at BP and def2-TZVPD level in Hartree [Ha] <table> <tbody> <tr> <td>Element</td> <td>H</td> <td>C</td> <td>N</td> <td>O</td> <td>F</td> <td>Br</td> <td>Cl</td> <td>S</td> <td>P</td> </tr> <tr> <td>Eat [Ha]</td> <td>-0.5</td> <td> -37.85</td> <td> -54.60</td> <td> -75.09</td> <td>-99.77</td> <td>-2574.40</td> <td> -460.20</td> <td> -398.16</td> <td>-341.30</td> </tr> </tbody> </table>   <table> <tbody> <tr> <td>B</td> <td>Si</td> </tr> <tr> <td>  -24.65</td> <td> -289.40</td> </tr> </tbody> </table> We follow the convention of negative atomization energies for stablity compared to the isolated atoms: $E_{atomization} = E_{mol} - \sum_{i} E_{at,i}$ Free energy of solvation at 300 K in [kcal/mol]: <h3>Ionization potentials and electron affinities</h3> The upload contains two JSON files, QM9IPEA.json and QM9IPEA_atom_ens.json. QM9IPEA.json summarizes MOLPRO calculation data grouping it along the following dictionary keys:   QM9IPEA.json <code>COORDS</code> atom coordinates in Angstroms <code>SYMBOLS</code> atom element symbols <code>ENERGY</code> total energies for each charge (0, -1, 1) and method considered <code>CPU_TIME</code> CPU times (in seconds) spent at each step of each part of the calculation <code>DISK_USAGE</code> highest total disk usage in GB <code>ATOMIZATION_ENERGY</code> atomization energy at charge 0 (all methods) <code>IONIZATION_ENERGY</code> ionization energy for all methods <code>ELECTRON_AFFINITY</code> electron affinity for all methods <code>HOMO_ENERGY</code> HOMO energy from DFHF calculations <code>LUMO_ENERGY</code> LUMO energy from DFHF calculations <code>QM9_ID</code> ID of the molecule in the QM9 dataset QM9IPEA_atom_ens.json <code>SPINS</code> the spin assigned to elements during calculations of atomic energies <code>ENERGY</code> energies of atoms using different methods     All energies are given in Hartrees with NaN indicating the calculation failed to converge. Ionization potentials and electron affinities can be recovered as energy differences between neutral and charged (+1 for ionization potentials, -1 for electron affinities) species. "CPU_time" entries contain steps corresponding to individual method calculations, as well as steps corresponding to program operation: "INT" (calculating integrals over basis functions relevant for the calculation), "FILE" (dumping intermediate data to restart file), and "RESTART" (importing restart data). The latter two steps appeared since we reused relevant integrals calculated for neutral species in charged species' calculations; we also used restart functionality to use HF density matrix obtained for the neutral species as the initial density matrix guess for the SCF-HF calculation for charged species. NaN CPU time value means the step was not present or that the calculation is invalid. Note that the CPU times were measured while parallelizing on 12 cores and were not adjusted to single-core.   QM9IPEA_atom_ens.json contains atomic energies used to calculate atomization energies in QM9IPEA.json, the dictionary keys are: <code>SPINS</code> - the spin assigned to elements during calculations of atomic energies. <code>ENERGY</code> - energies of atoms using different methods.   (Note that H has only one electron and thus does not require a level of theory beyond Hartree-Fock.) NOTE: Additional calculations were performed between publication of arXiv:2308.11196 and creation of this upload. For the version of the dataset used in the manuscript, please refer to DOI:10.5281/zenodo.8252498. <h3>Acknowledgement</h3> This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 957189 (BIG-MAP) and  No. 957213 (BATTERY 2030+). O.A.v.L. has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 772834). O.A.v.L. has received support as the Ed Clark Chair of Advanced Materials and as a Canada CIFAR AI Chair. O.A.v.L. acknowledges that this research is part of the University of Toronto’s Acceleration Consortium, which receives funding from the Canada First Research Excellence Fund (CFREF). Obtaining the presented computational results has been facilitated using the queueing system implemented at <a href="https://leruli.com">https://leruli.com</a>. The project has been supported by the Swedish Research Council (Vetenskapsrådet), and the Swedish National Strategic e-Science program eSSENCE as well as by computing resources from the Swedish National Infrastructure for Computing (SNIC/NAISS).   <h3>References</h3> [1] Klamt, A.; Eckert, F. COSMO-RS: a novel and efficient method for the a priori prediction of thermophysical data of liquids. Fluid Phase Equilibria 2000, 172, 43–72 [2] Werner, H.-J.; Knowles, P. J.; Knizia, G.; Manby, F. R.; Schutz, M. Molpro: a general-purpose quantum chemistry program package. WIREs Comput. Mol. Sci. 2012, 2, 242–253 [3] arxiv link of draft [4] <a href="https://github.com/chemspacelab/ViennaUppDa">https://github.com/chemspacelab/ViennaUppDa</a> [5] Ramakrishnan, R.; Dral, P. O.; Rupp, M.; von Lilienfeld, O. A. Quantum chemistry structures and properties of 134 kilo molecules. Sci. Data 2014, 1, 140022 [6] Qu, X.; Jain, A.; Rajput, N. N.; Cheng, L.; Zhang, Y.; Ong, S. P.; Brafman, M.; Mag- inn, E.; Curtiss, L. A.; Persson, K. A. The Electrolyte Genome Project: A big data approach in battery materials discovery. Comput. Mater. Sci. 2015, 103, 56–67  [7] Ruddigkeit, L.; van Deursen, R.; Blum, L. C.; Reymond, J.-L. Enu- meration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17. Journal of Chemical Information and Modeling 2012, 52, 2864–2875 [8] Irwin, J. J.; Shoichet, B. K. ZINC A Free Database of Commercially Available Compounds for Virtual Screening. Journal of Chemical Information and Modeling 2005, 45, 177–182.

opencc-zeroMay 2023View details →

3D printed biomedical devices and their applications: A review on state-of-the-art technologies, existing challenges, and future perspectives

This repository consists of the data that have been utilized to imagine and subsequently construct Fig. 1, Fig. 3 , Fig. 5 , Fig. 6 and Fig. 7 of the article " H. B. Mamo, M. Adamiak and A. Kunwar. 3D printed biomedical devices and their applications: A review on state-of-the-art technologies, existing challenges, and future perspectives, Journal of the Mechanical Behavior of Biomedical Materials, 143 (2023) 105930. doi: 10.1016/j.jmbbm.2023.105930 ".  Brief introduction of the files contained in this repository <ol> <li> acronyms.csv: This file consists of  the list of acronyms associated with materials and techniques used in 3D printing of biomedical devices.</li> <li>fig1a-data.csv: The csv file provides a relative ranking of different types of 3D printing techniques for biomedical applications based upon  merits and limitations (wherever applicable). The technique listed as Rank 1 is considered as the most commonly used 3D printing procedure.</li> <li> fig1b-data.csv: The csv file enlists the benfits of the 3D printing techniques in biomedical applications as compared to subtractive manufacturing methods.</li> <li> fig3-data.csv: The file contains a comparison between conventional and customized tablet printing  methods. The illustration is made through the manufacturing or printing of pharmaceutical tablets or pills.  This illustation also applies to the production of pharmaceutical capsules.  It thus illustrates that customized medicine is enabled using 3D printing technology.</li> <li> fig5-data.csv: This file enumerates the major challenges associated with 3D printing of biomedical devices.</li> <li> fig6-data.csv: The file enlists the roles of wearable smarts, cloud-based platforms and physicians in context of the hospitals implementing IoMT.</li> <li> fig7-data.csv: The aspects of IoMT Sensors,IoMT Platforms,3D Printers,Design and Prototypes within the integrated 3D printing-IoMT ecosystem are listed in the file.</li> </ol>

opencc-by-4.0Aug 2021View details →

In-depth analysis of 18 case studies on state-of-the-art of cultural tourism interventions

The aim of Work Package 3 of the SmartCulTour project (<a href="http://www.smartcultour.eu">www.smartcultour.eu</a>) is to provide a state-of-the-art overview of cultural tourism interventions implemented in European cities and regions, thereby identifying best practices and the impacts and success conditions of cultural tourism interventions. Based on the previous, desk-researched 107 interesting cultural tourism interventions see "Desk research of 107 case studies on state-of-the-art of cultural tourism interventions", DOI: 10.5281/zenodo.5213017 ), a further 18 interventions were selected for in-depth analysis. These 18 cultural tourism interventions were analyzed via a series of expert interviews, combined with document and literature analysis, performed in the period January 2021-March 2021. Description of the case studies follows a standardized case study data collection form. This form is included here as "Case study data collection form". The form collect data on: <ul> <li>Context and background information;</li> <li>The 'reason why' of the intervention;</li> <li>The intervention;</li> <li>Resources and tools necessary to design and implement the interventions;</li> <li>Impacts (expected, perceived and measured);</li> <li>(Perceived) success conditions and limiting factors.</li> </ul> The semi-structured interviews left some room for adaptability depending on the case studies. A general guide on potential interview questions is included here as "Potential questions list for case study interviews". All case studies are included as individual odt-files, starting with "detailed case study + name of the intervention".

FIG. 12 in The evolution of hermit crabs (Crustacea, Decapoda, Anomura, Paguroidea) on the basis of carapace morphology: a state-of-the-art-report

FIG. 12. — Intuitive phylogenetic tree based on carapace morphologies as outlined in the present study and on data from McLaughlin et al.(2007) and Fraaije et al.(2019). Important synapomorphies include the following: 1, cylindrical carapace; 2, cervical and branchial grooves widely separated; 3, arrow-shaped gastric region; 4, cervical groove not extending to lateral border; 5, intragastric grooves; 6, Y-linea; 7, spinose posterolateral borders.

FIG. 9 in The evolution of hermit crabs (Crustacea, Decapoda, Anomura, Paguroidea) on the basis of carapace morphology: a state-of-the-art-report

FIG. 9. — Changes in taxonomic composition amongst paguroid assemblages within reefal settings during the Late Jurassic (Oxfordian, Kimmeridgian and Tithonian) and mid-Cretaceous (Albian) compared to modern faunas. Grey, Gastrodoridae; orange, cylindrical carapace; blue, non-cylindrical carapace.

FIG. 2 in The evolution of hermit crabs (Crustacea, Decapoda, Anomura, Paguroidea) on the basis of carapace morphology: a state-of-the-art-report

FIG. 2. — Branchial condensation in representatives of the families Parapylochelidae (A, B), Gastrodoridae (C), Xylopaguridae (D, E) and Pylojacquesidae (F).

FIG. 5 in The evolution of hermit crabs (Crustacea, Decapoda, Anomura, Paguroidea) on the basis of carapace morphology: a state-of-the-art-report

FIG. 5. — Isochelous chelae of Schobertella simonsenetlangi Schweigert, Fraaije, Havlik & Nützel, 2013 (SMNS 70555, Staatliches Museum für Naturkunde Stuttgart, Germany, from the Lower Jurassic (upper Pliensbachian) Amaltheenton Formation of Iggingen near Aalen, southwestern Germany. Scale bars: 5 mm.

FIG. 1 in The evolution of hermit crabs (Crustacea, Decapoda, Anomura, Paguroidea) on the basis of carapace morphology: a state-of-the-art-report

FIG. 1. — Branchial condensation in basal paguroid genera: A, Platykotta Chablais, Feldmann & Schweitzer, 2011; B, Schobertella Schweigert, Fraaije, Havlik & Nützel, 2013; C, Eopaguropsis Fraaije, Krzemiński, Van Bakel, Krzemińska & Jagt, 2012.

FIG. 8 in The evolution of hermit crabs (Crustacea, Decapoda, Anomura, Paguroidea) on the basis of carapace morphology: a state-of-the-art-report

FIG. 8. — Schobertella simonsenetlangi Schweigert, Fraaije, Havlik & Nützel, 2013 (SMNS 70555; see also Fig. 5), from the Lower Jurassic (upper Pliensbachian) Amaltheenton Formation of Iggingen near Aalen, southwestern Germany: (A) showing new details of shield morphology, compared to Eopaguropsis nidiaquilae Fraaije, Krzemiński, Van Bakel, Krzemińska & Jagt, 2012 (B) (see Fraaije et al. 2012c: fig. 2d). Scale bars: 10 mm.

FIG. 4 in The evolution of hermit crabs (Crustacea, Decapoda, Anomura, Paguroidea) on the basis of carapace morphology: a state-of-the-art-report

FIG. 4. — Changes in the massetic regions through time; from the Late Jurassic Annuntidiogenes jurassicus Fraaije, 2014 (A) to the mid-Cretaceous (late Albian) Annuntidiogenes worfi Fraaije, van Bakel, Jagt, Klompmaker & Artal, 2009 (B) and extant Paguristes sp. (C).

FIG. 3 in The evolution of hermit crabs (Crustacea, Decapoda, Anomura, Paguroidea) on the basis of carapace morphology: a state-of-the-art-report

FIG. 3. — Reduction of rostral length during the Late Jurassic in representatives of the families Gastrodoridae (A), Parapylochelidae (B) and Pylochelidae (C).

FIG. 7 in The evolution of hermit crabs (Crustacea, Decapoda, Anomura, Paguroidea) on the basis of carapace morphology: a state-of-the-art-report

FIG. 7. — The oldest example of heterochelous paguroid claws from the Upper Jurassic of the Wimereux area (Boulonnais, northwestern France); an individual preserved in situ in the internal mould of a Vetigastropoda (private collection of Mr Gilles Dron). The maximum diameter of the gastropod is about 7 cm.