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FIGURE 8 in The parasitic barnacle Peltogaster reticulata Shiino, 1943 (Rhizocephala, Peltogastridae) fromRussian watersof the Sea of Japan:morphological description molecular identification and complete larval development

FIGURE 8. Outlines of antennules (Al I–Al V), antenna (An) and mandible (Md) of the naupliar stages of Peltogaster reticulata. 1–6, antennular setae; bs, basipod seta. Scale bar 25 µm.

FIGURE 11. Peltogaster reticulata, nauplius IV. A in The parasitic barnacle Peltogaster reticulata Shiino, 1943 (Rhizocephala, Peltogastridae) fromRussian watersof the Sea of Japan:morphological description molecular identification and complete larval development

FIGURE 11. Peltogaster reticulata, nauplius IV. A, ventral view; B, hind body; C, furca; D, antennule. De, denticles; 5, 6, antennular setae.

FIGURE 3 in The parasitic barnacle Peltogaster reticulata Shiino, 1943 (Rhizocephala, Peltogastridae) fromRussian watersof the Sea of Japan:morphological description molecular identification and complete larval development

FIGURE 3. Transverse sections of the externa of Peltogaster reticulata. A, mature ovary; B, embryos; C, colleteric gland; D, colleteric gland near posterior end; E, left and right receptacles (colleteric gland does not reach the stalk); F, left receptacle near anterior end; G, receptacle duct; H, receptacle duct before outlet in the mantle cavity. Cg, colleteric gland; em, embryos; ov, ovary; m, mantle; r, receptacle; rd, receptacle duct; sh, shield; st, stalk.

FIGURE 10. Peltogaster reticulata, nauplius III. A in The parasitic barnacle Peltogaster reticulata Shiino, 1943 (Rhizocephala, Peltogastridae) fromRussian watersof the Sea of Japan:morphological description molecular identification and complete larval development

FIGURE 10. Peltogaster reticulata, nauplius III. A, ventral view; B, frontolateral horn; C, hind body with furca; D, antennular setae; E, antenna. Bs, basipod seta; se, subterminal seta; su, suture.

FIGURE 2 in The parasitic barnacle Peltogaster reticulata Shiino, 1943 (Rhizocephala, Peltogastridae) fromRussian watersof the Sea of Japan:morphological description molecular identification and complete larval development

FIGURE 2. SEM showing cuticle structure of the externa of Peltogaster reticulata. A, external cuticle (arrows show longitudinal and transverse ridges); B, internal cuticle; C, a group of two retinacula on one base; D, groups of two or four retinacula; E, a single balloon-like retinaculum; F, lamp-brush retinaculum is released out of balloon-like envelope.

FIGURE 9. Peltogaster reticulata, nauplius II. A in The parasitic barnacle Peltogaster reticulata Shiino, 1943 (Rhizocephala, Peltogastridae) fromRussian watersof the Sea of Japan:morphological description molecular identification and complete larval development

FIGURE 9. Peltogaster reticulata, nauplius II. A, ventral view; B, dorsal view; C, flotation collar; D, head shield setae; E, the third head shield seta with subterminal pore; F, head shield pore; G, attachment ridge; H, frontolateral horn; I, labrum; J, hind body; K, furca; L, antennules and antennae. Bs, basipod seta; cf, cuticular fringes; fc, flotation collar; po, pore on shield head (D) and on attachment disc (G); se, subterminal seta; su, suture; 1, 2, 2a, anterior head shield setae; 1–5, antennular setae.

FIGURE 6 in The parasitic barnacle Peltogaster reticulata Shiino, 1943 (Rhizocephala, Peltogastridae) fromRussian watersof the Sea of Japan:morphological description molecular identification and complete larval development

FIGURE 6. Body outlines (ventral view) of male and female larvae of Peltogaster reticulata. A, NI–NV, naupliar stages; B, cypris stages; C, head shield of nauplius III (dorsal view with setation); D, carapace of cyprid (lateral view with lattice organs). 1–5, head shield setae (C), lattice organs (D); p, pore; pf, porefield. Scale bar 100 µm.

FIGURE 5 in The parasitic barnacle Peltogaster reticulata Shiino, 1943 (Rhizocephala, Peltogastridae) fromRussian watersof the Sea of Japan:morphological description molecular identification and complete larval development

FIGURE 5. Size-frequency distribution of male (black bars) and female (grey bars) cyprids of Peltogaster reticulata.

FIGURE 7. Peltogaster reticulata, nauplius I. A in The parasitic barnacle Peltogaster reticulata Shiino, 1943 (Rhizocephala, Peltogastridae) fromRussian watersof the Sea of Japan:morphological description molecular identification and complete larval development

FIGURE 7. Peltogaster reticulata, nauplius I. A, ventral view; B, dorsal view; C, details of B; D, frontolateral horn; E, appendages. Al, antennule; an, antenna; fh, frontolateral horn; fr, furcal rami; md, mandible; po, pore; se, subterminal seta; su, suture; 2, 2a, head shield setae.

opencc-by-4.0May 2020View details →

Using White-Box Test Generation During Development: A Replicated Study

This package contains the artifacts for our external, differentiated replication of an empirical study on using white-box test generation. The original experiment is described in the following paper. <blockquote> José Miguel Rojas, Gordon Fraser, and Andrea Arcuri. 2015. Automated unit test generation during software development: a controlled experiment and think-aloud observations. In Proceedings of the 2015 International Symposium on Software Testing and Analysis (ISSTA 2015), 338–349. DOI: 10.1145/2771783.2771801 </blockquote> 30 developers and students participated in the experiment in January 2016. The main difference in the replication was using the IntelliTest test generator tool instead of EvoSuite. The contents of the package are the followings. <ul> <li>/assignments <ul> <li>session_starts_endings.csv - Timestamps when each session was started</li> <li>assignments_with_projects.csv - Assigments of participants to projects, classes and sessions</li> </ul> </li> <li>/projects <ul> <li>/golden - Contains the golden implementation and test suites of all 4 classes</li> <li>/user - Contains the user implementation and test method stubs of all 4 classs</li> </ul> </li> <li>/results <ul> <li>time_merged.csv - File of timing analysis containing each test run of subjects</li> <li>results.csv - Contains the coverage and other required data of each participant tasks</li> <li>exit.csv - Answers of the exit survey</li> <li>background.csv - Answers of the background questionnaire</li> </ul> </li> <li>/scripts <ul> <li>/ps <ul> <li>Get-Results.ps1 - Gets the results of both tasks for one specified participant (invokes MSBuild, MSTest, VisualMutator, OpenCover)</li> <li>Get-Failures-Errors.ps1 - Gets failures and errors of both tasks for one specified participant (invokes MSBuild, MSTest)</li> <li>Get-TimeData.ps1 - Iterates over all test runs for each participant</li> </ul> </li> <li>/r <ul> <li>likert.R - Generates the Likert chart</li> <li>si_st.R - Generates table of subject implementation executed with subject test suites</li> <li>gi_st.R - Generates table of results where subject test suites was run on golden implementation</li> <li>time_spent_tests.R - Generates a table of time and activity of testing</li> <li>errors_failures.R - Generates table of errors and failures obtained using the golden test suite</li> <li>correlation_analysis.R - Generates table containing correlation between lack of correctness and IntelliTest usage</li> </ul> </li> </ul> </li> </ul>

openother-ncFeb 2020View details →

TAU Urban Acoustic Scenes 2020 Mobile, Development dataset

TUT Urban Acoustic Scenes 2020 Mobile development dataset consists of 10-seconds audio segments from 10 acoustic scenes: <ul> <li>Airport - airport</li> <li>Indoor shopping mall - shopping_mall</li> <li>Metro station - metro_station</li> <li>Pedestrian street - street_pedestrian</li> <li>Public square - public_square</li> <li>Street with medium level of traffic - street_traffic</li> <li>Traveling by a tram - tram</li> <li>Traveling by a bus - bus</li> <li>Traveling by an underground metro - metro</li> <li>Urban park - park</li> </ul> The dataset contains in total 64 hours of audio. Version 2 fixes synchronization between 118 segments from devices A, B, and C, and removes 5 incorrect audio segments.

opencc-by-4.0May 2020View details →

Text Analyses of Survey Data on "Mapping Research Output to the Sustainable Development Goals (SDGs)"

This package contains data on five text analysis types (term extraction, contract analysis, topic modeling, network mapping), based on the survey data where researchers selected research output that are related to the 17 Sustainable Development Goals (SDGs). This is used as input to improve the current SDG classification model v4.0 to v5.0 <a href="https://sustainabledevelopment.un.org/sdgs">Sustainable Development Goals</a> are the 17 global challenges set by the United Nations. Within each of the goals specific targets and indicators are mentioned to monitor the progress of reaching those goals by 2030. In an effort to capture how research is contributing to move the needle on those challenges, we earlier have made an initial classification model than enables to quickly identify what research output is related to what SDG. (This <a href="https://aurora-network.global/project/sdg-analysis-bibliometrics-relevance/">Aurora SDG dashboard</a> is the initial outcome as proof of practice.) The initiative started from the Aurora Universities Network in 2017, in the working group "<a href="https://aurora-network.global/activity/societal-impact-and-relevance-of-research-sirr/">Societal Impact and Relevance of Research</a>", to investigate and to make visible 1. what research is done that are relevant to topics or challenges that live in society (for the proof of practice this has been scoped down to the SDGs), and 2. what the effect or impact is of implementing those research outcomes to those societal challenges (this also have been scoped down to research output being cited in policy documents from national and local governments an NGO's). Context of this dataset | classification model improvement workflow The classification model we have used are 17 different search queries on the Scopus database. <ul> <li>SDG search queries version 4.0 (SQv4) have been created, Published here: <ul> <li><a href="https://doi.org/10.5281/zenodo.3817443">Search Queries for "Mapping Research Output to the Sustainable Development Goals (SDGs)" v4.0 by Aurora Universities Network (AUR) doi:10.5281/zenodo.3817443</a></li> </ul> </li> <li>A survey has been distributed to senior researchers to test the robustness of SQv4. Published here: <ul> <li><a href="https://doi.org/10.5281/zenodo.3798385">Survey data of "Mapping Research output to the Sustainable Development Goals SDGs" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385</a></li> </ul> </li> <li>This text analysis has been made as one of the inputs to improve the classification model. Published here: <ul> <li><a href="https://doi.org/10.5281/zenodo.3832090">Text Analyses of Survey Data on "Mapping Research Output to the Sustainable Development Goals SDGs" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3832090</a></li> </ul> </li> <li>Improved SDG search queries version 5.0 (SQv5) have been created, Published here: <ul> <li><a href="https://doi.org/10.5281/zenodo.3817445">Search Queries for "Mapping Research Output to the Sustainable Development Goals (SDGs)" v5.0 by Aurora Universities Network (AUR) doi:10.5281/zenodo.3817445</a></li> </ul> </li> </ul> Methods used to do the text analysis <ol> <li>Term Extraction: after text normalisation (stemming, etc) we extracted 2 terms in bigrams and trigrams that co-occurred the most per document, in the title, abstract and keyword</li> <li>Contrast analysis: the co-occurring terms in publications (title, abstract, keywords), of the papers that respondents have indicated relate to this SDG (y-axis: True), and that have been rejected (x-axis: False). In the top left you'll see term co-occurrences that a clearly relate to this SDG. The bottom-right are terms that are appear in papers that have been rejected for this SDG. The top-right terms appear frequently in both and cannot be used to discriminate between the two groups.</li> <li>Network map: This diagram shows the cluster-network of terms co-occurring in the publications related to this SDG, selected by the respondents (accepted publications only).</li> <li>Topic model: This diagram shows the topics, and the related terms that make up that topic. The number of topics is related to the number of of targets of this SDG.</li> <li>Contingency matrix: This diagram shows the top 10 of co-occurring terms that correlate the most.</li> </ol> Software used to do the text analyses CorTexT: The <a href="https://www.cortext.net/">CorTexT Platform</a> is the digital platform of LISIS Unit and a project launched and sustained by IFRIS and INRAE. This platform aims at empowering open research and studies in humanities about the dynamic of science, technology, innovation and knowledge production. Resource with interactive visualisations Based on the text analysis data we have created a website that puts all the SDG interactive diagrams together. For you to scrall through. <a href="https://sites.google.com/vu.nl/sdg-survey-analysis-results/">https://sites.google.com/vu.nl/sdg-survey-analysis-results/</a> Data set content In the dataset root you'll find the following folders and files: <ul> <li>/sdg01-17/ <ul> <li>This contains the text analysis for all the individual SDG surveys.</li> </ul> </li> <li>/methods/ <ul> <li>This contains the step-by-step explanations of the text analysis methods using Cortext.</li> </ul> </li> <li>/images/ <ul> <li>images of the results used in this README.md.</li> </ul> </li> <li>LICENSE.md <ul> <li>terms and conditions for reusing this data.</li> </ul> </li> <li>README.md <ul> <li>description of the dataset; each subfolders contains a README.md file to futher describe the content of each sub-folder.</li> </ul> </li> </ul> Inside an /sdg01-17/-folder you'll find the following: <ul> <li>This contains the step-by-step explanations of the text analysis methods using Cortext.</li> <li>/sdg01-17/sdg04-sdg-survey-selected-publications-combined.db <ul> <li>his contains the title, abstract, keywords, fo the publications in the survey, including the and accept or rejection status and the number of respondents</li> </ul> </li> <li>/sdg01-17/sdg04-sdg-survey-selected-publications-combined-accepted-accepted-custom-filtered.db <ul> <li>same as above, but only the accepted papers</li> </ul> </li> <li>/sdg01-17/extracted-terms-list-top1000.csv <ul> <li>the aggregated list of co-occuring terms (bigrams and trigrams) extracted per paper.</li> </ul> </li> <li>/sdg01-17/contrast-analysis/ <ul> <li>This contains the data and visualisation of the terms appearing in papers that have been accepted (true) and rejected (false) to be relating to this SDG.</li> </ul> </li> <li>/sdg01-17/topic-modelling/ <ul> <li>This contains the data and visualisation of the terms clustered in the same number of topics as there are 'targets' within that SDG.</li> </ul> </li> <li>/sdg01-17/network-mapping/ <ul> <li>This contains the data and visualisation of the terms clustered in co-occuring proximation of appearance in papers</li> </ul> </li> <li>/sdg01-17/contingency-matrix/ <ul> <li>This contains the data and visualisation of the top 10 terms co-occuring</li> </ul> </li> </ul> note: the .csv files are actually tab-separated. Contribute and improve the SDG Search Queries We welcome you to join the Github community and to fork, branch, improve and make a pull request to add your improvements to the new version of the SDG queries. <a href="https://github.com/Aurora-Network-Global/sdg-queries">https://github.com/Aurora-Network-Global/sdg-queries</a>

opencc-by-4.0Apr 2020View details →

Human nasal epithelial organoids for therapeutic development in cystic fibrosis

Table S1: Individual subject demographics and available clinical data for selected participants contributing functional data. Figure S1: Example measurement of µOCT ciliary beat frequencies, Figure S2: Organoid CFTR (green) co-localization with apical ZO-1 (red). (A) To illustrate the location of the ZO-1 staining within the organoid, an alpha-blended 3-D volume reconstruction was created with the fluorescence intensity increased to reveal the organoid’s shape and orient the reader to the location of the 2D co-localization image below. (B) Magnified view of the yellow frame in (A) to better visualize the CFTR and ZO-1 overlay, Video S1: Brightfield video of luminal movement of mucus, Video S2: µOCT video of luminal movement of mucus, Video S3: Brightfield video of luminal cilia beating, Video S4: µOCT video of cilia beating, Video S5: FIS assay of non-CF organoids, Video S6: FIS assay of F508del/P67L organoids. Video S7: FIS assay of F508del/F508del organoids.

opencc-by-4.0May 2020View details →

Data citation for a forward stratigraphic-based porosity and permeability model developed for the Volve field, Norway.

The data, models, and script presented here are those used for developing a forward stratigraphic simulation. The data include: 24 suits of well logs, seismic data, forward stratigraphic simulation scenarios of the shallow marine depositional setting, synthetic wells derived from the stratigraphic model, and 3-D reservoir models in Eclipse and RMS formats. In addition, a short script from the property calculator tool in Petrel, which is was used to classify lithofacies-associations in the stratigraphic model is also provided. The Petrel software license and code used in GPM software to undertake these forward stratigraphic simulations cannot be provided, because Schlumberger, who are the developers of the software do not allow its code to be shared in any publication.

opencc-by-4.0Feb 2019View details →

Memos of Coding - Factors Influencing the Software Development Productivity

The list of theoretical codes, their definitions, and references of the related studies (the complete memos) regarding the investigation and syntheses of factors influencing software development productivity.

Evolution of reduced minimum critical size as a response to selection for rapid pre-adult development in Drosophila melanogaster.

Adult body size in holometabolous insects is directly proportional to the time spent during the larval period. The larval duration can be divided into two parts- (i) pre-critical duration-time required to attain a critical size/critical weight that would result in successful completion of development and metamorphosis even under non-availability of nutrition beyond the time of attainment of critical size, and (ii) post-critical duration-the time duration from attainment of critical size till pupation. It is of interest to decipher the relative contribution of the two larval growth phases (from the hatching of the egg to attainment of critical size or from the attainment of critical size to pupation- post-critical duration) to the final adult size. Many studies using Drosophila melanogaster have shown that, selecting populations for faster development result in the emergence of small adults. Some of these studies have indirectly reported the evolution of smaller critical size. Using two kinds of D. melanogaster populations, one of which is selected for faster/accelerated pre-adult development and the other their ancestral control, we demonstrate that the final adult size is determined by the time spent as larvae post the attainment of critical size despite having increased growth rate during the second larval instar. Our populations under selection for faster per-adult development are exhibiting adaptive-bail out due to intrinsic food limitation as against extrinsic food limitation in the yellow dung fly.

The post-embryonic ontogeny of the early Cambrian trilobite Estaingia bilobata from South Australia: trunk development and phylogenetic implications

Trilobites are one of the most diverse and abundant fossil groups from the early Palaeozoic, and as such are useful for answering important questions about early animal evolution, including developmental processes. Ontogenetic information for a large number of trilobite species has been published, but cases where multiple articulated specimens are known across the full range of developmental stages are rare. The early Cambrian (Series 2, Stage 4) Emu Bay Shale biota from Kangaroo Island (South Australia) is numerically dominated by trilobites, particularly articulated specimens of the ellipsocephaloid Estaingia bilobata, which are present in densities of >600 individuals per square metre on certain bedding planes. Here we describe the essentially complete post-embryonic ontogenetic series of E. bilobata from the Emu Bay Shale, and investigate patterns of growth relating to articulation and segmentation in this early Cambrian arthropod. Estaingia bilobata exhibits the hypoprotomeric mode of growth, with the epimorphic phase (the cessation of trunk segment generation) reached prior to the onset of the holaspid period. The meraspid pygidium had an extended equilibrium period where anterior segment release into the thorax was matched by sub-terminal segment generation. Previously undocumented morphological features of E. bilobata, including the hypostome and bispinose pleural tips in holaspides, are also described. The growth characteristics and morphological features of E. bilobata documented herein strengthen close phylogenetic relationships between the Estaingiidae, Ellipsocephalidae and Xystriduridae.

Data from: Reprograming of epigenetic mechanisms controlling host insect immunity and development in response to egg-laying by a parasitoid wasp

Parasitoids are insects that use other insects as hosts. They sabotage host cellular and humoral defenses to promote the survival of their offspring by injecting viruses and venoms along with their eggs. Many pathogens and parasites disrupt host epigenetic mechanisms to overcome immune system defenses, and we hypothesized that parasitoids may utilize the same strategy. We used the ichneumon wasp Pimpla turionellae as a model idiobiont parasitoid to test this hypothesis, with pupae of the greater wax moth Galleria mellonella as the host. We found that parasitoid infestation involves the suppression of host immunity-related effector genes and the modulation of host genes involved in developmental hormone signaling. The transcriptional reprogramming of host genes following the injection of parasitoid eggs was associated with changes in host epigenetic mechanisms. The introduction of parasitoids resulted in a transient decrease in host global DNA methylation and the modulation of acetylation ratios for specific histones. Genes encoding regulators of histone acetylation and deacetylation were mostly downregulated in the parasitized pupae, suggesting that parasitoids can suppress host transcription. We also detected a strong parasitoid-specific effect on host microRNAs regulating gene expression at the post-transcriptional level. Our data therefore support the hypothesis that parasitoids may favor the survival of their offspring by interfering with host epigenetic mechanisms to suppress the immune system and disrupt development.

openother-openJun 2020View details →

Data and Code Accompanying the Study "Developing an annotation framework for word formation processes in comparative linguistics"

Cite the source of the dataset as: <blockquote> Schweikhard, N. E. and List, J.-M. (2020): Developing an annotation framework for word formation processes in comparative linguistics. SKASE Journal of Theoretical Linguistics. 17.1: 2-26. </blockquote>

Herbicide, fertilization, and planting density effects on intensively managed loblolly pine early stand development

Production forestry in the southeast US has been partially transitioned to intensively managed short rotations (~10 years), in which multiple silvicultural interventions are performed during forest development. Understanding the responses to silvicultural practices and continued refinement of site-specific recommendations is critical to sustainably maximize forest production. We evaluated the effects of silvicultural practices (herbicide, fertilization, and planting density) on growth, stand homogeneity, and above- and belowground biomass accumulation and partitioning of loblolly pine (Pinus taeda) throughout early stand development (age 5 years) in the southeastern US. Five treatments with eight replications each were tested: no herbicide and no fertilization (C); herbicide only (H); herbicide and half-reduced fertilization rate (R); herbicide and full fertilization (F); and increased stand density (60+ %; 1346 vs. 2152 trees per hectare) with herbicide and full fertilization rate (D). Allometric equations generated from destructive harvests were applied to annual diameter measurements to estimate plot-level biomass and allocation. Herbicide was crucial to promote stand uniformity and increase yield (~600+ % stem biomass compared with C at age 5). Aboveground biomass was similar in R and F treatments, which was, on average, ~25% higher than in H at age 5. Increasing planting density along with multiple herbicide and fertilizer applications yielded higher biomass without compromising individual tree size (diameter and height). There was little effect of silviculture practices on allocation patterns. Our results parallel what was found for fertilization with herbicide from a number of loblolly stands under similar conditions and indicate a ~28% volume gain with fertilization during early stand development. Similarly, our results were consistent with other studies implementing similar differences in planting density and suggest a ~26% volume gain through early stand development with an initial 60% increase in planting density. Our study helps to understand complex relationships between production and silvicultural practices during early stand development and demonstrates that silvicultural prescriptions can be optimized to increase sustainability of production forestry.