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opencc-by-4.0Jan 2016View details →

Supporting Data: Self-Aligned Organic Field-Effect Transistors on Plastic with Picofarad Overlap Capacitances and Megahertz Operating Frequencies

The file contains the supporting data for the publication: S.G. Higgins, B.V.O. Muir, G. Dell'Erba, A. Perinot, M. Caironi, A.J. Campbell. Self-Aligned Organic Field-Effect Transistors on Plastic with Picofarad Overlap Capacitances and Megahertz Operating Frequencies. doi: 10.1063/1.4939045. Applied Physics Letters (2016) See 'README.txt' for a description of the contents of the compressed file.

opencc-by-4.0Oct 2021View details →

R code for archaeological examples of calculating isotopic niche space and overlap using the rKIN package

This R code was written to apply the tools of the rKIN package to calculate isotopic niche space and overlap for the three archaeological case studies for the manuscript Investigating Isotopic Niche Space: Using rKIN for Stable Isotope Studies in Archaeology published in the Journal of Archaeological Method and Theory. Raw data for the case studies are available in the supplemental Excel file.

opencc-by-4.0Jun 2023View details →

Data release for paper "Waveform systematics in identifying gravitationally lensed gravitational waves: Posterior overlap method"

This is the data release for the paper "Waveform systematics in identifying gravitationally lensed gravitational waves: Posterior overlap method", which is available on https://arxiv.org/abs/2306.12908. These results are derived from the gravitational-wave parameter-estimation results by the LIGO-Virgo-KAGRA Collaboration, released with the GWTC-1, GWTC-2, GWTC-2.1, and GWTC-3 catalogs under the following links: <ul> <li>    https://dcc.ligo.org/P1800370-v5/public</li> <li>    https://dcc.ligo.org/P2000223-v7/public</li> <li>    https://doi.org/10.5281/zenodo.6513631</li> <li>    https://doi.org/10.5281/zenodo.5546663</li> </ul> For the lensed-unlensed hypothesis test posterior overlap Bayes factors, we provide the following files for event pairs from within each observing run: <ul> <li>    blu_all_pairs_O1.txt</li> <li>    blu_all_pairs_O2.txt</li> <li>    blu_all_pairs_O3.txt</li> </ul> In each file, the column "event_pair" contains the names of the two events from the pair sorted chronologically, the column "data_releases" contains the names of the data releases from which the posterior samples of each event were taken, the column "waveform" contains the name of the waveform model used in the parameter estimation for both sets of posteriors, and the column "log10blu" contains the log10 of the Bayes factors. The differences between runs for the same event pair, only including O1-O1, O2-O2, O3-O3 pairs, where at least one run gave log10blu>0, are also given in the file "blu_differences_pairs_with_log10blu_pos.txt". The column "event_pair" contains the event pairs, the columns "waveform_{1,2}" contain the names of the waveform models used in the parameter estimation for both sets of posteriors, the columns "data_releases_{1,2}" contain the the data releases from which the posterior samples of each event were taken, the columns "log10blu_{1,2}" contain the log10 Bayes factors, and the column "difference" contains the difference between "log10blu_1" and "log10blu_2". We also provide the following files corresponding to the appendix of the paper, analyzing overlaps between posterior samples for individual events: <ul> <li>    overlap_different_runs.txt</li> <li>    overlap_same_run.txt</li> <li>    rescaled_difference_single_event.txt</li> </ul> The file "overlap_different_runs.txt" contains Bayes factors for a single event, but comparing the posteriors from different runs. The file "overlap_same_run.txt" contains Bayes factors for the overlap of a single run on a single event with itself. The file "rescaled_difference_single_event.txt" contains the difference between the results contained in the file overlap_different_runs.txt and the results in overlap_same_run.txt, taking the ones that produce the biggest difference, as per equation (A.1) in the paper. In these files, the column "event_name" is the name of the event, the column "data_release" or "data_releases" contains the name(s) of the data release(s) from which the posterior samples of each run were taken, the column "waveform" or "waveform_pair" contains the name(s) of the waveform model(s) used, and the column "log10blu" is the log10 Bayes factor obtained. In the file "rescaled_difference_single_event.txt", the columns "max_run_waveform" and "max_run_data_release" identify an entry from the "overlap_same_run.txt" file from which we use the "log10blu" to compute the value listed in the "difference" column using equation (A.1).

opencc-by-4.0Jun 2023View details →

Deeptangle Dataset: Labelled Experimental and Synthetic Videos of Swimming and Overlapping C. elegans worms

This repository contains the dataset employed in the paper <a href="https://arxiv.org/abs/2301.04460">Fast spline detection in high density microscopy data</a>. Three files are provided: 1. videos.zip: raw experimental videos. 2. labeled_data.zip: labelled sections of experimental videos used for evaluation 3. syntehthic_dataset.zip: synthetic dataset used for training Labelled data Sections are named as VIDEONAME_FRAMENUMBER_SECTIONID. All labels are in labels.json and correspond to the middle frame of the clip (05.png). Example plotting script is provided (plot_data.py). Synthetic data Clips are named as NUMBEROFWORMS_ID. Labels (for all frames) are stored in labels.npy. Example plotting script is provided (plot_data.py).   Related Paper: <a href="https://arxiv.org/abs/2301.04460">https://arxiv.org/abs/2301.04460</a> Deeptangle code: <a href="https://github.com/kirkegaardlab/deeptangle">https://github.com/kirkegaardlab/deeptangle</a> Labelling tool: <a href="https://github.com/kirkegaardlab/deeptanglelabel">https://github.com/kirkegaardlab/deeptanglelabel</a> --- If used, please cite Albert Alonso & Julius B. Kirkegaard. Fast spline detection in high density microscopy data. 2023.

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Flow discharge impact competition for food and shelter between two overlapping species of crayfish

Competition between aquatic organisms is heavily influenced by abiotic factors in the environment, specifically flow regime in aquatic systems. Flow regime has been shown to significantly affect the way in which a species uses the environmental resources and alterations in flow can exasperate competitive advantages by congenerics. However, little work has concentrated on the competitive outcome between native and invasive organisms as a function of flow regime. Here, we sought to uncover how competition between two crayfish species (the native virile crayfish [Faxonius virilis] and invasive rusty crayfish [Faxonius rusticus]) was affected by varying flow rates. To do this, we size-matched crayfish and quantified three separate behaviors (food use, shelter use, and fights) of crayfish in four different discharge levels (no discharge—0 cm3/s; low discharge—116 cm3/s; intermediate discharge—345 cm3 /s; high discharge—450 cm3/s). We found that the number of foraging bouts was significantly (p < 0.001) influenced by discharge levels for both species, where rusty crayfish foraged more often in no and discharge. The number of times crayfish sheltered also varied between species and was significantly (p < 0.001) altered by discharge level, where rusty crayfish sheltered more often in no discharge and virile crayfish sheltered more in low and intermediate discharge levels. Similarly, the number of fights that crayfish engaged in also significantly (p < 0.001) depended upon species and discharge levels. Rusty crayfish engaged in more agonistic activities in no and high discharge levels while virile crayfish participated most often in low and intermediate discharge levels

openCC (other)Apr 2024View details →

opencc-zeroFeb 2024View details →

Effects of food supplementation and helminth removal on space use and spatial overlap in wild bank vole populations

Animal space use and spatial overlap can have important consequences for population-level processes such as social interactions and pathogen transmission. Identifying how environmental variability and inter-individual variation affect spatial patterns and in turn influence interactions in animal populations is a priority for the study of animal behavior and disease ecology. Environmental food availability and macroparasite infection are common drivers of variation, but there are few experimental studies investigating how they affect spatial patterns of wildlife. Bank voles (Clethrionomys glareolus) are a tractable study system to investigate spatial patterns of wildlife and are amenable to experimental manipulations. We conducted a replicated, factorial field experiment in which we provided supplementary food and removed helminths in vole populations in natural forest habitats and monitored vole space use and spatial overlap using capture-mark-recapture methods. Using network analysis, we quantified vole space use and spatial overlap. We compared the effects of food supplementation and helminth removal and investigated the impact of season, sex, and reproductive status on space use and spatial overlap. We found that food supplementation decreased vole space use while helminth removal increased space use. Space use also varied by sex, reproductive status, and season. Spatial overlap was similar between treatments despite up to three-fold differences in population size. By quantifying the spatial effects of food availability and macroparasite infection on wildlife populations, we demonstrate the potential for space use and population density to trade off and maintain consistent spatial overlap in wildlife populations. This has important implications for spatial processes in wildlife including pathogen transmission.

opencc-by-4.0Mar 2024View details →

Train and Evaluation Code, Road Classification Models and Test set of the paper "Impact of Image Resolution and Image Overlap on the Prediction Performance of Convolutional Neural Networks Trained for Road Classification"

This repository contains the Python scripts built for training and evaluation of the implementation, together with the test data and the resulting road classification models corresponding to the paper "Impact of Image Resolution and Image Overlap on the Prediction Performance of Convolutional Neural Networks Trained for Road Classification". The scripts make use of the Tensorflow with Keras framework and the additional required dependencies. The training and validation set is based on the binary SROADEX dataset (https://zenodo.org/records/6482346) that was re-split into tiles that feature the image resolutions (256 x 256, 512 x 512, and 1024 x 1024 pixels) and image overlaps (0% and 12.5%) considered in this study. The data have been generated using scripts developed in Python using Open Source libraries (GDAL/OGR and MapScript) for rasterization of vector cartography that represents the axes of the different types of roads (urban, interurban and rural). This binary road data contains information from 16 full orthoimages (28.5 km * 18.5 km) with spatial resolution of 0.5 m/pixel from the insular and peninsular Spanish territory. Due to the size on disk of approximately 546 gigabytes, this training and validation data is only available upon request from the corresponding author. The test set has been generated from a novel area of 28.5 km * 18.5 km and features binary road labels. The test sets are provided in the repository for each resolution (with no overlap), so that additional DL models can be evaluated on the same data and compared with the results achieved in this study. The structure of the information shared in this repository is as follows: The scripts have been grouped by tile resolution (256, 512 and 1024). First, the test set and the evaluation script can be found. For each tile resolution, there are two subfolders (corresponding to the "no overlap" and "12.5% overlap"). In each case, the Python scripts for training the models in the three repetitions are shared, and the trained models (H5 format) are shared in compressed form. Finally, for each resolution we also share the testing dataset which consists of two folders. The material is distributed under a CC-BY 4.0 license.

openmit-licenseApr 2024View details →

Assessing the Overlap of Science Knowledge Graphs: A Quantitative Analysis — exact and related matches

Results of the 'Assessing the Overlap of Science Knowledge Graphs: A Quantitative Analysis'  papers. There are 2 datasets: <ul> <li>'exact_matches.csv': contains detailed information about the concepts present both in OpenAlex and OpenAIRE.</li> <li>'related_matches.csv': contains detailed information about the concepts from OpenAlex and OpenAIRE that were not present in both KGs but got aligned following the algorithm presented in the paper.</li> </ul> The detailed information refers to the following column: <ul> <li>Category1: name of the first category</li> <li>Source1: source of the first category ('OpenAlex' or 'OpenAIRE')</li> <li>Category2: name of the second category</li> <li>Source2: source of the first category ('OpenAlex' or 'OpenAIRE')</li> <li>Similarity: semantic similarity value of the two categories</li> <li>PapersInC1: number of papers from the collected dataset belonging to the first category</li> <li>PapersInC2: number of papers from the collected dataset belonging to the second category</li> <li>PapersInBoth: number of papers from the collected dataset belonging to both of the categories</li> <li>Agreement: the value of the agreement of the categories in the tw KGs (Intersection over Union)</li> </ul>

opencc-by-4.0Mar 2016View details →

Fig. 2 in A closer look at the main actors of Neotropical floodplain food webs: functional classification and niche overlap of dominant benthic invertebrates in a floodplain lake of Paraná River

Fig. 2. Cluster plot depicting trophic similarity (Morisita index) among species of dominant benthic invertebrates in a floodplain lake of ParanÁ River, Argentina. Dotted line depicts the threshold similarity of 0.6.

opencc-by-4.0Mar 2016View details →

Fig. 3 in A closer look at the main actors of Neotropical floodplain food webs: functional classification and niche overlap of dominant benthic invertebrates in a floodplain lake of Paraná River

Fig. 3. Non Metric Multidimensional scaling plot. Circles depicts taxa classified as gatherer collectors (Aulodrilus pigueti, Pristina leidyi, Dero vagus, Nais communis, Pelomus sp., Cladopelma sp., Endotribelos sp., Polypedilum sp., Chironomus sp., Parachironomus sp., Phaenopsectra sp., Americabaetis sp., Baetis sp., Campsurus violaceus, Hyalella curvispina, Crynellus sp.) [Triangles: Tanypodinae (Coelotanypus sp., Procladius sp. and Ablabesmyia (Karelia); inverted triangle: Sympetrum sp.; square: Monopelopia sp.; cross: Pomacea canaliculata].

opencc-by-4.0Mar 2016View details →

Fig. 1 in A closer look at the main actors of Neotropical floodplain food webs: functional classification and niche overlap of dominant benthic invertebrates in a floodplain lake of Paraná River

Fig. 1. Relative importance (IRI) of food items for analyzed taxa of dominant benthic invertebrates in a floodplain lake of ParanÁ River, Argentina (parenthesis indicate sample size).

opencc-zeroFeb 2024View details →

Vibroscape analysis reveals acoustic niche overlap and plastic alteration of vibratory courtship signals in ground-dwelling wolf spiders

Soundscape ecology has enabled researchers to investigate natural interactions among biotic and abiotic sounds as well as their influence on local animals. To expand the scope of soundscape ecology to encompass substrate-borne vibrations (i.e. vibroscapes), we developed methods for recording and analyzing sounds produced by ground-dwelling arthropods to characterize the vibroscape of a deciduous forest floor using inexpensive contact microphone arrays followed by automated sound filtering and detection in large audio datasets. Through the collected data, we tested the hypothesis that closely related species of Schizocosa wolf spider partition their acoustic niche. In contrast to previous studies on acoustic niche partitioning, two closely related species - S. stridulans and S. uetzi - showed high acoustic niche overlap across space, time, and/or signal structure. Finally, we examined whether substrate-borne noise, including anthropogenic noise (e.g., airplanes) and heterospecific signals, promotes behavioral plasticity in signaling behavior to reduce the risk of signal interference. We found that all three focal Schizocosa species increased the dominant frequency of their vibratory courtship signals in noisier signaling environments. Also, S. stridulans males displayed increased vibratory signal complexity with an increased abundance of S. uetzi, their sister species with which they are highly overlapped in the acoustic niche.

opencc-by-4.0Mar 2022View details →

Trajectory with Overlapping Projections x-ray Computed Tomography (TOP-CT) dataset of 23 mandarins moving over a circular trajectory

SummaryThis dataset is a collection of X-ray projection images of 23 mandarins moving over a circular trajectory in such a way that the projections of multiple adjacent mandarins overlap. The dataset was acquired to test out Trajectory with Overlapping Projections x-ray Computed Tomography (TOP-CT), about which a paper is published in IEEE Transactions on Computational Imaging [Schut 2022]. DescriptionSample informationThe samples are 23 mandarins. The first 10 are of the Nadorcott cultivar, and the remaining 13 are of the Clemenrubi cultivar. The diameter of the mandarins ranges between 50 and 58 mm. Per sample metadata can be found in the mandarin_metadata.csv file.Scanner informationThe dataset is acquired in the FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. The CT scanner consists consists of a cone-beam microfocus polychromatic X-ray point source, and a 1944x1536 pixel, 14-bit, flat detector panel (Dexela1512NDT). Full details can be found in [Coban 2020].Scanning geometryThe mandarins were moved according to a custom scanning protocol, with the intention to simulate a conveyor belt setup. A wooden disk was attached on top of the rotation stage and six evenly spaced object positions were marked on the disk at a fixed distance from the center of rotation. Pieces of cardboard tube were used as sample holders to make sure the mandarins wouldn't roll as the disk would rotate and to raise them from the disk without attenuating too much of the X-ray signal. The rotation stage was positioned in such a way that over a full rotation of the disk, each mandarin would be completely in view of the detector for more than 180 degrees of the rotation, while there would also be a position at which it would be completely out of view. An image illustrating the exact dimensions is included in mandarin_carousel_dimensions.png.The scan was performed in phases. Every phase 400 projection images were acquired, while rotating the disk for 60 degrees. This would rotate one of the positions out of view of the scanning setup. Before the first 6 phases a mandarin was added on the position that was out of view of the setup. For the phases after that the position that would be out of view would contain a mandarin that had rotated the full circle so that mandarin was replaced with a new mandarin. At the last 6 phases there would be no new mandarins left to add so the mandarin that was out of view of the setup would only be removed. The projection images acquired from each phase were concatenated resulting in a dataset of 11200 projections. At most 5 mandarins were in view at a given time.Note: Due to a small oversight while scanning, the 19th mandarin is not included on projections 9200-9205. This area can be masked out during reconstruction.Scanning settingsA peak voltage of 90kV was used, the target power was set to 49.5W and the spectrum was pre-filtered using 0.1mm of copper. An exposure time of 200 ms was used for each projection. A start-stop acquisition scheme was used to minimize vibrations and to make adding and removing mandarins easier: After each projection image was acquired, the stage was rotated to a new position and the scanner was paused for 200 ms before acquiring the next projection image. Darkfield and flatfield images were acquired before and after all the mandarins were scanned using the average over 200 images. 2x2 pixel hardware binning was used and all images were cropped to a 500 pixel high region around the center, resulting in 11200 projection images of 956x500 pixels (11.1GB uncompressed). All images are stored in .tif format.Reconstructing volumesThe repository <a href="https://github.com/D1rk123/top-ct_experiments">https://github.com/D1rk123/top-ct_experiments</a> contains code for TOP-CT simulations and reconstructions. The script mandarin_carousel_experiment.py was specifically written to reconstruct volumes for each separate mandarin from this dataset. Research group These datasets are produced by the Computational Imaging group at Centrum Wiskunde & Informatica (CI-CWI) in Amsterdam, The Netherlands: <a href="https://www.cwi.nl/research/groups/computational-imaging">https://www.cwi.nl/research/groups/computational-imaging</a>Contact details dirk [dot] schut [at] cwi [dot] nlAcknowledgments This work was funded by the Dutch Research Council (NWO) through the UTOPIA project (ENWSS.2018.003). The authors also acknowledge TESCAN-XRE NV for their collaboration and support of the FleX-ray laboratory.References[Schut 2022] D. E. Schut, K. J. Batenburg, R. van Liere, and T. van Leeuwen, "TOP-CT: Trajectory with Overlapping Projections X-ray Computed Tomography", 2022, IEEE Transactions on Computational Imaging [Coban 2020] S. B. Coban, F. Lucka, W. J. Palenstijn, D. Van Loo, and K. J. Batenburg, "Explorative imaging and its implementation at the FleX-ray Laboratory," J. Imaging, vol. 6, no. 18, 2020, doi: 10.3390/jimaging6040018.If you use (parts of) this data in a publication, please consider citing the first article.

opencc-by-nc-4.0Mar 2021View details →

Overlap of vitamin A and vitamin D target genes with CAKUT-related processes

Underlying data of our study "<a href="http://doi.org/10.12688/f1000research.51018.2">Overlap of vitamin A and vitamin D target genes with CAKUT-related processes</a>" are provided here.   Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) are a group of abnormalities affecting the kidneys and their outflow tracts. Vitamins are among the environmental factors that are considered for CAKUT aetiology. In this study, we collected vitamin A and vitamin D target genes and computed their overlap with CAKUT-related gene sets. We observed in particular significant overlaps between vitamin A target genes and CAKUT causal genes or genes involved in renal system development.

opencc-zeroApr 2022View details →

Supplementary data from 'Predicting the distribution of Australian frogs and their overlap with Batrachochytrium dendrobatidis under climate change'

Aim: Amphibians, with over 40% of assessed species listed as threatened, are disproportionately at risk in the global extinction crisis. Among the many factors implicated in the current and ongoing loss of amphibian biodiversity are climate change and the disease chytridiomycosis, caused by the fungus Batrachochytrium dendrobatidis (Bd). These two threats are of particular concern in Australia, where Bd has been implicated in the declines of at least 43 frog species, and climate change is emerging as an additional threat. Here, we explore how climate change is likely to affect the distributions of Australian frog species and Bd to the year 2100, as well as how the spatial and climatic niche overlap between <a>chytridiomycosis-declined </a>frogs and Bd could shift. Location: Australia Methods: We used species distribution modelling to infer the current and future distribution of 141 Australian frog species and Bd, under two emissions scenarios. We used metrics of niche similarity, including Schoener's D and the Niche Margin Index, to quantify predicted alterations to spatial interactions between Bd and frog species. Results: Climate change is likely to have a variable impact on frog distributions in Australia, with some 23 and 47 species, primarily in southern Australia, predicted to lose at least 30% of their current distributions under low and high emissions scenarios, respectively. In contrast, 69 and 68 species, respectively, have potential to increase their distributions, primarily in northern Australia. While the distribution of Bd is predicted to decrease, the proportional spatial and niche overlap between Bd and susceptible frog species is predicted to remain little changed, and in some cases, to increase. Main conclusions: Although effects will be variable across the continent, climate change is likely to be a threatening factor to a number of Australian frog species. Additionally, chytridiomycosis is likely to remain a significant threat to many frog species, as any reductions to the pathogen's distribution largely coincide with geographic range contractions of chytridiomycosis-susceptible species.

opencc-zeroMay 2022View details →

Niche overlap in rodents increases with competition but not ecological opportunity: A role of inter-individual difference

<div> Niche variation at population level mediates niche packing (i.e., patterns of species' spread within the niche space) and species coexistence at community level. Competition and ecological opportunity (resource diversity) are two of the main mechanisms underlying niche variation. Dense niche packing could occur through increased niche partitioning or increased niche overlap. In this study we used stable carbon and nitrogen isotope data of 635 individual rodents from 4 species across 9 sites in the montane region of a subtropical island to test the effects of competition and ecological opportunity on population isotope niche size, inter-individual niche difference within population, and inter-specific niche overlap within community. We used the Bayesian Standard Ellipse Area (SEAB, the ellipse area enclosed by carbon and nitrogen isotope values of organisms on a bi-plot) to estimate population niche size and inter-specific niche overlap. Inter-individual niche difference within population was quantified as isotopic divergence and isotopic uniqueness. We used rodent abundance (the number of unique individuals captured) to measure competition and plant isotope niche size (plant SEAB) to measure ecological opportunity. The rodents experienced competition as evidenced by a negative relationship between population change rate and conspecific abundance. Rodent population niche size increased with ecological opportunity but not competition. The inter-individual niche difference (isotopic uniqueness) increased with competition (inter-specific competition only) but not ecological opportunity. At community level, inter-specific niche overlap (herbivore—omnivore pair only) increased with competition (the combined abundance of the pair) but not ecological opportunity. This study demonstrated that isotope niche variation of the rodents could be hierarchically influenced by ecological opportunity and competition, with the former setting the limit of population niche size across communities and the latter shaping inter-individual niche difference and inter-specific niche overlap within communities. Under strong intra-specific competition and limited ecological opportunity for niche expansion, individuals may choose to increase their isotopic uniqueness from conspecifics at the cost of overlapping with heterospecifics of different trophic roles within the community niche space as overall competition increases. Denser niche packing of these rodent communities might be achieved through increased niche overlap. </div>

opencc-by-4.0Dec 2021View details →

Text-fig. 5. Paramblypterus vratislaviensis (AGASSIZ, 1833). Scale bars 5 mm. a: drawing of the skull roof in dorsal view, locality Olivětín, NM-M 2213; b, c: photograph and drawing of the left maxila in lateral view, locality Ruprechtice, NM-M 64696; d: right parietal in dorsal view, locality Ruprechtice "Pod Světlinou", P 64741; e: left maxilla in lateral view, locality Ruprechtice "Pod Světlinou", P 64738; f, g: photograph and drawing of the left mandible in medial view, locality Ruprechtice "Pod Světlinou", P 64738. Abbreviations: ap – anterior pit line, Dpt – dermopterotic, Dsph – dermosphenotic, eo – edge overlapped by surrounding bones, Fr – frontal, mp – medial pit line, Na – nasal, Pa – parietal, pp – posterior pit line, Ptr – postrostral, soc – supraorbital canal, socp – pores of the supraorbital canal. in Actinopterygians Of The Broumov Formation (Permian) In The Czech Part Of The Intra-Sudetic Basin (The Czech Republic)

Text-fig. 5. Paramblypterus vratislaviensis (AGASSIZ, 1833). Scale bars 5 mm. a: drawing of the skull roof in dorsal view, locality Olivětín, NM-M 2213; b, c: photograph and drawing of the left maxila in lateral view, locality Ruprechtice, NM-M 64696; d: right parietal in dorsal view, locality Ruprechtice "Pod Světlinou", P 64741; e: left maxilla in lateral view, locality Ruprechtice "Pod Světlinou", P 64738; f, g: photograph and drawing of the left mandible in medial view, locality Ruprechtice "Pod Světlinou", P 64738. Abbreviations: ap – anterior pit line, Dpt – dermopterotic, Dsph – dermosphenotic, eo – edge overlapped by surrounding bones, Fr – frontal, mp – medial pit line, Na – nasal, Pa – parietal, pp – posterior pit line, Ptr – postrostral, soc – supraorbital canal, socp – pores of the supraorbital canal.