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Fig. 5 in Eight new species of the genus Anaplecta Burmeister, 1838 (Blattodea: Blattoidea: Anaplectidae) from China based on molecular and morphological data

Fig. 5. Anaplecta strigata Deng & Che sp. nov., holotype, ♂ (SWU). A. Habitus, dorsal view. B. Habitus, ventral view. C. Head, ventral view. D. Pronotum, dorsal view. E. Tegmina. F. Tegmina vein. G. Maxillary palp. H. Front femur, ventral view. I. Wings. J. Supra-anal plate, dorsal view. K. Subgenital plate, ventral view. L. Hook, ventral view. M. Left phallomere, ventral view. N. Right phallomere, ventral view. Scale bars: A–B = 2 mm; C, E–F, I = 1 mm; D, G–H, J–K, M–N = 0.5 mm; L = 0.25 mm.

Fig. 10. A–B, E in Eight new species of the genus Anaplecta Burmeister, 1838 (Blattodea: Blattoidea: Anaplectidae) from China based on molecular and morphological data

Fig. 10. A–B, E. Anaplecta omei Bey-Bienko, 1958. A. Habitus, dorsal view. B. Habitus, ventral view. E. Supra-anal plate, dorsal view. – C–D. Anaplecta basalis Bey-Bienko, 1969. C. Habitus, dorsal view. D. Habitus, ventral view. – F–I. Comparison of R1 of A. corneola Deng & Che sp. nov. from different localities. F. Guangdong Prov., Zhaoqing City (ZQ). G. Hainan Prov., Ledong County, Mt. Jianfengling (JFL1). H. Hunan Prov., Chenzhou City, Yizhang County, Mangshan National Forest Park (MS). I. Fujian Prov., Wuyishan City, (WY). Scale bars: A–B = 2 mm; C–D = 1 mm; E = 0.5 mm; F–I = 0.25 mm.

Fig. 4 in Eight new species of the genus Anaplecta Burmeister, 1838 (Blattodea: Blattoidea: Anaplectidae) from China based on molecular and morphological data

Fig. 4. Anaplecta arcuata Deng & Che sp. nov., holotype, ♂ (SWU). A. Habitus, dorsal view. B. Habitus, ventral view. C. Head, ventral view. D. Pronotum, dorsal view. E. Maxillary palp. F. Front femur, ventral view. G. Tegmina. H. Wings. I. Supra-anal plate, dorsal view. J. Subgenital plate, ventral view. K. Hook, ventral view. L. Left phallomere, ventral view. Scale bars: A–B, G–H = 2 mm; C = 1 mm; D–F, I–J = 0.5 mm; K–L = 0.1 mm.

Fig. 1 in Eight new species of the genus Anaplecta Burmeister, 1838 (Blattodea: Blattoidea: Anaplectidae) from China based on molecular and morphological data

Fig. 1. Maximum-likelihood (ML) tree derived from COI gene analysis following GTR GAMMA model with 1000 bootstrap replicates. Colored bars in red refer to the morphospecies, those in blue to MOTUs in ABGD and those in purple to MOTUs in GMYC.

Fig. 6 in Eight new species of the genus Anaplecta Burmeister, 1838 (Blattodea: Blattoidea: Anaplectidae) from China based on molecular and morphological data

Fig. 6. Anaplecta furcata Deng & Che sp. nov., holotype, ♂ (SWU). A. Habitus, dorsal view. B. Habitus, ventral view. C. Head, ventral view. D. Pronotum, dorsal view. E. Tegmina. F. Tegmina vein. G. Maxillary palp. H. Front femur, ventral view. I. Wings. J. Supra-anal plate, dorsal view. K. Supra-anal plate. L. Subgenital plate, ventral view. M. Hook, ventral view. N. Left and right phallomere, ventral view. Scale bars: A–B = 1 mm; C–F, H–N = 0.5 mm; G = 0.25 mm.

Fig. 3 in Eight new species of the genus Anaplecta Burmeister, 1838 (Blattodea: Blattoidea: Anaplectidae) from China based on molecular and morphological data

Fig. 3. Anaplecta staminiformis Deng & Che sp. nov. A–M. Holotype, ♂ (SWU). A. Habitus, dorsal view. B. Habitus, ventral view. C. Head, ventral view. D. Pronotum, dorsal view. E. Maxillary palp. F. Front femur, ventral view. G. Tegmina. H. Wings. I. Supra-anal plate, dorsal view. J. Subgenital plate, ventral view. K. Hook, ventral view. L. Left phallomere, ventral view. M. Right phallomere, ventral view. – N–P. Paratype, ♂, samples from LMS (SWU). N. Hook, ventral view. O. Left phallomere, ventral view. P. Right phallomere, ventral view. Scale bars: A–B, G–H = 2 mm; C, E–F = 1 mm; D, I–J, L–M, O–P = 0.5 mm; K, N = 0.25 mm.

Tara Pacific 18S-based coral host genetic analysis data release version 1

This dataset contains 4 tables and 3 sets of figures related to the primary analysis of the 18S metabarcoding sequencing output. This dataset is only concerned with the identity of the coral host (i.e. not additional protist diversity). The samples included in this dataset have a 'sample-material_label' value of 'CORAL' and 'sampling-protocol_label' value of 'SEQ-CS4L'. They represent the coral samples collected at all 32 of the islands visited in the Tara Pacific expedition.

cigKast: A data of 3D synthetic seismic volumes with labeled paleokarsts for deep-learning-based paleokarst interpretation

cigKarst is a dataset created by the <a href="http://cig.ustc.edu.cn/">Computational Interpretation Group (CIG)</a> for the deep-learning-based peleokarst interpretation in 3D seismic images, <a href="http://cig.ustc.edu.cn/xinming/list.htm" target="_blank" rel="noopener">Xinming Wu</a> is the main contributor to the dataset. This dataset contains 120 pairs of synthetic 3D seismic images and the corresponding label images with the ground truth of the paleokarst systems simulated in the seismic images. More detail of building this dataset is discussed in the paper published at the journal of JGR Solid Earth: Wu, X., S. Yan, J. Qi, and H. Zeng, 2020, Deep learning for characterizing paleokarst collapse features in 3D seismic images. JGR, Solid Earth, Vol. 125(9), 1-23, e2020JB019685. <a href="http://cig.ustc.edu.cn/_upload/tpl/05/cd/1485/template1485/papers/wu2020karst.pdf">[PDF]</a>. doi: 10.1029/2020JB019685 Below are some brief description of the dataset: 1) The "seismic.zip" contains 120 3D seismic images, each image is with the dimension of 256X256X256;  2) The "karst.zip" contains 120 3D label images of the karsts. Each label image is with the same dimension of 256X256X256. The values in a label image are set with ones in the karst areas while zeros elsewhere, which is why the compressed label images in the karst.zip is much smaller than the seismic images compressed in the seismic.zip

New fault slip distribution for the 2010 Mw 7.2 El Mayor Cucapah earthquake based on realistic 3D finite element inversions of coseismic displacements using space geodetic data

The .csv files included in this repository contain the data used in the numerical model as input, while the .txt file is the output (slip on a regular grid of points on the fault planes from the joint inversion of the geodetic datasets.

opencc-by-4.0Dec 2020View details →

Dataset and Jupyter worksheet interpreting the (results from) small- and wide-angle scattering data from a series of boehmite/epoxy nanocomposites. Accompanies the publication "Competition of nanoparticle-induced mobilization and immobilization effects on segmental dynamics of an epoxy-based nanocomposite"

Dataset and Jupyter worksheet interpreting the (results from) small- and wide-angle scattering data from a series of boehmite/epoxy nanocomposites. Accompanies the publication "Competition of nanoparticle-induced mobilization and immobilization effects on segmental dynamics of an epoxy-based nanocomposite", by Paulina Szymoniak, Brian R. Pauw, Xintong Qu, and Andreas Schönhals. Datasets are in three-column ascii (processed and azimuthally averaged data) from a Xenocs NanoInXider SW instrument. Monte-Carlo analyses were performed using McSAS 1.3.1, other analyses are in the Python 3.7 worksheet. Graphics and result tables are output by the worksheet.

Predicting placenta transcriptional regulatory interactions based on spatial gene expression data and convolutional neural network

Aims: The dysfunction of placenta development is correlated to the defects of pregnancy and fetal growth. The detailed molecular mechanism of placenta development is not identified in human due to the lack of material in vivo. Image-based reconstructions of GRN are still very underdeveloped. Methods and Results: In this study, first-trimester chorionic villus and decidua tissues were collected. Next, we present a machine-learning system to infer gene interaction networks of the human placenta from immunofluorescence images of trophoblast specific transcription factors obtained by a high-resolution scanner. Conclusions: The experimental results show that deep learning models reveal regulatory roles that have not yet been fully recognized. The spatial expression data reveal new regulatory relationships that traditional experiments have failed to recognize, and has allowed the development of gene regulation networks based on the spatial distribution of gene expression. We demonstrate the effectiveness of this approach in building networks using high-resolution images of the human placenta. Our analysis is of certain significance for further exploration of the development of the placenta and the occurrence of pregnancy-related diseases in the future. The datasets and analysis provide a useful source for the researchers in the field of the maternal-fetal interface and the establishment of pregnancy.

opencc-by-4.0Jan 2021View details →

Supplementary Data for: ONT-based draft genome for Alternaria atra

Species of Alternaria (phylum Ascomycota, family Pleosporaceae) are known as serious plant pathogens, causing major losses on a wide range of crops. Alternaria atra (Preuss) Woudenb. & Crous (previously known as Ulocladium atrum) can grow as a saprophyte on many hosts and causes Ulocladium blight on potato. It has been reported that it can also be used as a biocontrol agent against a.o. Botrytis cinerea. Here we present a scaffold-level reference genome assembly for A. atra. The assembly contains 43 scaffolds with a total length of 39.62 Mbp, with scaffold N50 of 3,893,166 bp , L50 of 4 and the longest 10 scaffolds containing 89.9% of the assembled data. RNA Seq-guided, gene prediction using BRAKER resulted in 12,173 protein-coding genes with their functional annotation.

opencc-by-4.0Jan 2021View details →

Data from" Euphotic Zone Metabolism in the North Pacific Subtropical Gyre Based on Oxygen Dynamics"

This data set provides measurements of oxygen to argon molar ratios from discrete samples collected within the mixed layer at the long-term sampling site (Station ALOHA) of the Hawaii Ocean Time-Series program, within the North Pacific Subtropical Gyre, between November 2013 and January 2019 (near-monthly cruises). Samples were measured by membrane inlet mass spectrometry following Ferrón et al. (2015). Version 2 had corrected longitude data (in decimal degrees east). Version 3 includes a new file with estimated rates of net community production, gross oxygen production and community respiration for the mixed layer.

opencc-by-4.0Jun 2021View details →

Annual Maxima of Station-based Rainfall Data over Different Accumulation Durations

Description These data were used in the study "Flexible and Consistent Quantile Estimation for Intensity-Duration-Frequency Curves" (Fauer et al., 2021). Rainfall data were collected from stations by the German Meteorological Service (DWD) and Wupperverband (corrected data). Raw time series data from the German Meteorological Service is publicly available under https://opendata.dwd.de/climate_environment/CDC/observations_germany/climate/. Only the annual precipitation maxima over different durations are published here. Files <ul> <li>yearMax.csv: This file contains aggregated rainfall data over different durations and for different stations.</li> <li>meta.csv: This file contains additional information of the different stations such as longitude, latitude, altitude, temporal resolution (m=minutely, h=hourly, d=daily), group. The same group is assigned to stations which have a distance of less than 250 meters and can be treated as one station.</li> </ul> Abstract of the according study We suggest a flexible parametric model for describing intensity duration frequency relationships (IDF-curves) in a consistent way, i.e., without crossing of different quantiles for a wide range of durations (1 min to 5 days). The model is based on the duration-dependent formulation of the generalized extreme value distribution (GEV). The original model shows a power-law like behaviour for the quantiles for a wide range of durations and takes care of a deviation from this scaling relation (curvature) for small durations. We extend the model with two features: i) different power-law exponents for different quantiles (multiscaling) and ii) deviation from the power-law for large durations (flattening). Based on the quantile skill score, we investigate the performance of the resulting flexible model with respect to the benefit of the individual features (curvature, multiscaling, flattening) with simulated and empirical data. We provide detailed information on the duration and probability ranges for which specific features or a systematic combination of features leads to improvements for stations in a case study area in the Wupper catchment (Germany). Our results show that allowing curvature or multiscaling improves the model only for very short or long durations, respectively, but leads to disadvantages in modeling the other duration ranges. In contrast, allowing flattening on average leads to an improvement for medium durations between 1 hour and 1 day without affecting other duration regimes. Overall, the new parametric form offers a flexible and performant model for consistently describing IDF relations over a wide range of durations.   Acknowledgements We would like to thank the German Weather Service (DWD), and the Wupperverband, especially Marc Scheibel, for maintaining the station-based rainfall gauge and providing us with data.

opencc-by-4.0Apr 2017View details →

Data of "H2S dosimeter with controllable percolation threshold based on semi-conducting copper oxide thin films" published in JSSS 2017

Raw data to the Paper "H2S dosimeter with controllable percolation threshold based on semi-conducting copper oxide thin films" published in "Journal of Sensors and Sensor Systems". Acknowledgement and Funding in the txt.file

opencc-by-4.0May 2017View details →

A rule based Tibetan part-of-speech (POS) tagger for the creation of gold standard training data

This rule based Tibetan part-of-speech (POS) tagger was prepared in the course of the research project 'Tibetan in Digital Communication' (2012-2015) hosted at SOAS, University of London and funded by the UK's Arts and Humanities Research Council (grant code: AH/J00152X/1). For a description of the tag set see Garrett et al. 2014. and Garrett et al. 2015. For a description of the tagger itself see Garrett et al. 2014. Note that the tagger must be used together with a lexicon (for example Hill & Garrett 2017a). One must use one's own script to tag all words with all tags in the lexicon and then apply the tagger to remove incorrect tags. On the associated corpus of 318,230 words (Hill & Garrett 2017b) the lexical tagger (i.e. simply applying all available tags to all words) tags 141,911 words with the correct unique tag, achieves as accuracy of 1.000 (by definition getting the right tag among others for each word) with an ambiguity of 2.73111. In contrast, the Rule Tagger tags 241,256 words with the correct unique tag, achieves an accuracy of 0.99893 and an ambiguity of 1.38577. Because this tagger does not achieve ambiguity 1.000 it is not suitable for tagging large scale corpora, but instead is useful for the creation of gold standard training data. N.B. In some rare cases the tagger removes all POS-tags.

opencc-by-4.0Jun 2017View details →

Individual-based simulation model of annual movement paths for the Darwin's frog (R code and data)

Desprition of the R code I constructed an individual-based simulation model that describes the movement path of an individual Rhinoderma darwinii through 3-month displacement steps. This model was primarily developed to evaluate the age-specific movement behaviour of Darwin's frogs, however, I also used it to provide better estimates (i.e. alleviating for movement censoring) of age-specific annual displacements in the species. I developed several variations of this model through a combination of different random walk sub-models for juveniles and adults: uncorrelated non-stationary random walks (NRW), correlated non-stationary random walks (CRW), and stationary random walks (SRW). The NRW and CRW were modelled as a first-order Markovian process where the location of an individual i in time t depends on its spatial location in t - 1. The NRW is unbiased, i.e., there is no preferred direction in each movement step. In contrast, the CRW includes persistence in the directionality of movement, so there is a correlation between successive step orientations. Finally, the SRW assumes that individuals have an activity centre to which all their spatial locations are related. Related data are provided (y.txt, x.txt and age.txt)

opencc-by-4.0Aug 2017View details →

Ex-situ X-ray computed tomography data for a non-crimp fabric based fibre composite under fatigue loading

Ex-situ X-ray CT fatigue testing data sets published as a data in brief: "Ex-situ X-ray computed tomography data for a non-crimp fabric based fibre composite under fatigue loading", Data in brief, 2017, doi.org/10.1016/j.dib.2017.10.074. Together with the following article: K. M. Jespersen and L. P. Mikkelsen, “Three dimensional fatigue damage evolution in non-crimp glass fibre fabric based composites used for wind turbine blades,” Compos. Sci. Technol. (In press), 2017, 10.1016/j.compscitech.2017.10.004.