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opencc-by-4.0Mar 2024View details →

Data from: "Rare earth elements sediment analysis tracing anthropogenic activities in the stratigraphic sequence of Alagankulam (India)"

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Figure 2. Neodendrina carnelia igen. et isp. n in Large dendrinids meet giant clam: the bioerosion trace fossil Neodendrina carnelia igen. et isp. n. in a Tridacna shell from Pleistocene-Holocene coral reef deposits, Red Sea, Egypt

Figure 2. Neodendrina carnelia igen. et isp. n. on the inner side of a Tridacna maxima bivalve shell from the Pleistocene–Holocene coral reef deposits in the Marsa Alam area, Red Sea, Egypt. (a) Inner side of valve (left; prior to sectioning) with hundreds of N. carnelia specimens, and outer surface (right) intensely bioeroded by the sponge boring Entobia isp. (b) Section of the valve (MB.W 5640) with the holotype (centre) and the paratypes (all other specimens) in various ichnogenetic stages. (c) Close-up of the holotype trace. (d–e) Respective micro-CT scan of the holotype in plan and angular views as seen from inside the substrate.

Figure 1 in Large dendrinids meet giant clam: the bioerosion trace fossil Neodendrina carnelia igen. et isp. n. in a Tridacna shell from Pleistocene-Holocene coral reef deposits, Red Sea, Egypt

Figure 1. The Pleistocene raised coral reef limestones exposed at the type locality of Neodendrina carnelia igen. et isp. n. just south of the Carnelia Beach Resort, located between El Quseir and Marsa Alam, exhibiting scleractinian corals as primary reef builders (a) and giant clams Tridacna spp. weathering from the carbonate–siliciclastic rocks (b) that mix with Holocene and modern Tridacna valves, forming a highly time-averaged assemblage (c).

Figure 4. Neodendrina carnelia igen. et isp. n in Large dendrinids meet giant clam: the bioerosion trace fossil Neodendrina carnelia igen. et isp. n. in a Tridacna shell from Pleistocene-Holocene coral reef deposits, Red Sea, Egypt

Figure 4. Neodendrina carnelia igen. et isp. n. on the outer surface of a large recent Tridacna squamosa valve from Nosy-BØ, northern Madagascar (ZMB/Mol 102671). (a) Shell surface with various encrusters as well as bioerosion traces. (b) Close-up of a cluster of N. carnelia. (c) A large specimen with distinct pitted arrays developed in most of the branches.

Figure 3 in Large dendrinids meet giant clam: the bioerosion trace fossil Neodendrina carnelia igen. et isp. n. in a Tridacna shell from Pleistocene-Holocene coral reef deposits, Red Sea, Egypt

Figure 3. SEM images (BSE detector) of Neodendrina carnelia igen. et isp. n. of the inner side of a Tridacna maxima bivalve shell from the Pleistocene–Holocene coral reef deposits in the Marsa Alam area, Red Sea, Egypt. (a–c) Overview and close-ups of the holotype. (d–e) Overview and close-up of an early ichnogenetic stage. (f–g) Overview and close-up of a specimen with authigenic gypsum crystals, calcite spar, and clay minerals within the boring as well as on the host's shell surface. (h) Different morphologies possibly developed in the trace, comprising deep open canals (1), isolated deep pits (2), shallow open canals (3), pits in shallow canals (4) and discontinuities (5). (i) Cross section of a trace showing deep (1) and shallow (2) open canals. (j–k) Overview and detail of an epoxy resin cast of a specimen, illustrating the smooth surface texture and the high degree of microbioerosion in the surrounding (partly mechanically removed to gain a view of the dendrinid).

Fig. 5. A in New bioerosion traces in rhynchosaur bones from the Upper Triassic of Brazil and the oldest occurrence of the ichnogenera Osteocallis and Amphifaoichnus

Fig. 5. A suite of traces in the rhynchosaurid archosauromorph Hyperodapedon mariensis (Tupi Caldas, 1933), UFRGS-PV-1581-T #14, bone fragment from Buriol Site, Brazil, Hyperodapedon AZ, Carnian. A. Two feeding traces of Osteocallis mandibulus Roberts et al., 2007, overlapped by a cluster of larger grooves. B. Natural cast formed by a cover of iron oxide showing the grooves in positive relief. Image mirrored to facilitate comparison. C, D. Clusters of grooves on different surfaces of the same bone fragment. E. Small Osteocallis mandibulus close to the trails shown in A and B.

Fig. 6 in New bioerosion traces in rhynchosaur bones from the Upper Triassic of Brazil and the oldest occurrence of the ichnogenera Osteocallis and Amphifaoichnus

Fig. 6. Clusters of grooves on bone fragments of the rhynchosaurid archosauromorph Hyperodapedon mariensis (Tupi Caldas, 1933) from Buriol Site, Brazil, Hyperodapedon AZ, Carnian. A. UFRGS-PV-1581-T #20, arcuate and paired grooves, similar to feeding traces of Osteocallis mandibulus Roberts et al., 2007, but without forming a trail. B. UFRGS-PV-1581-T #22, densely concentrated grooves, giving the bone surface an etched appearence. C. UFRGS-PV-1581-T #5, straight and arcuate grooves closely associated to an incipient Osteocallis mandibulus (arrow). D. UFRGS-PV-1581-T #26, straight and arcuate grooves and some isolated grooves. E. UFRGS-PV-1581-T #6, dentary fragment; E1, two clusters of grooves; E2, schematic drawing. F. UFRGS-PV-1581-T #17; F1, subparallel grooves; F2, subparallel grooves associated to a subcircular cluster of grooves (arrow).

Fig. 4 in New bioerosion traces in rhynchosaur bones from the Upper Triassic of Brazil and the oldest occurrence of the ichnogenera Osteocallis and Amphifaoichnus

Fig. 4. Feeding traces of Osteocallis on bone fragments of the rhynchosaurid archosauromorph Hyperodapedon mariensis (Tupi Caldas, 1933) from Buriol Site, Brazil, Hyperodapedon AZ, Carnian. A. UFRGS-PV-1581 #3; A1, Osteocallis mandibulus Roberts et al., 2007, associated to arthropod bioerosion trace fossil Amphifaoichnus isp.; A2, details of one of the trails. B. UFRGS-PV-1581 #23; B1, Osteocallis mandibulus associated to a cluster of grooves in crescent shape; B2, schematic drawing highlighting the grooves. C. UFRGS-PV-1581-T #12 showing two overlapping Osteocallis infestans Paes Neto et al., 2016. D. UFRGS-PV-1581-T #11 showing Osteocallis isp. (arrow) associated to a cluster of larger grooves.

Fig. 2 in New bioerosion traces in rhynchosaur bones from the Upper Triassic of Brazil and the oldest occurrence of the ichnogenera Osteocallis and Amphifaoichnus

Fig. 2. Identified cranial elements of the rhynchosaurid archosauromorph Hyperodapedon mariensis (Tupi Caldas, 1933) in UFRGS-PV-1581-T from Buriol Site, Brazil, Hyperodapedon AZ, Carnian. A. Left dentary in lateral view (A1) and medial view (A2) showing the dentary blade with at least one lingual tooth arrow). B. Left and right dentaries in dorsal view. C. Partial left pterygoid in medial view. D. Right maxilla in ventral view. E. Left maxilla in ventral view.

Fig. 8 in New bioerosion traces in rhynchosaur bones from the Upper Triassic of Brazil and the oldest occurrence of the ichnogenera Osteocallis and Amphifaoichnus

Fig. 8. Indiscrete borings on bone fragments of the rhynchosaurid archosauromorph Hyperodapedon mariensis (Tupi Caldas, 1933) from Buriol Site, Brazil, Hyperodapedon AZ, Carnian. A. UFRGS-PV-1581-T #3; A1, a boring in the opposite face of the arthropod bioerosion trace fossil Amphifaoichnus, but also penetrating it; A2, close up view showing the presence of bone chips in the base of the boring. B. UFRGS-PV-1581-T #7 showing a boring with one rounded termination. C. UFRGS-PV-1581-T #9; C1, an elongated boring with a rounded termination and bone chips scattered on the base; C2, close up view highlighting the bone chips scattered on the base.

Fig. 1. Geological and geographic context. A in New bioerosion traces in rhynchosaur bones from the Upper Triassic of Brazil and the oldest occurrence of the ichnogenera Osteocallis and Amphifaoichnus

Fig. 1. Geological and geographic context. A. Location of the Paraná Basin in Brazil. B. Limits of the Triassic rocks of Rosário do Sul Group and the Triassic rocks of Paraná Basin in Rio Grande do Sul state. C. Location of the Buriol Site, locality of UFRGS-PV-1581-T, and nearby Predebon and Janner sites. D. Chrono-, lito-, and biostratigraphy of southern Brazilian Triassic (modified from Schultz et al. 2020). Arrow indicates stratigraphical position of UFRGS-PV-1581-T; * refers to absolute ages from Langer et al. (2018); ** refers to absolute ages from Philipp et al. (2018).

Fig. 7 in New bioerosion traces in rhynchosaur bones from the Upper Triassic of Brazil and the oldest occurrence of the ichnogenera Osteocallis and Amphifaoichnus

Fig. 7. Subcircular clusters on bone fragments of the rhynchosaurid archosauromorph Hyperodapedon mariensis (Tupi Caldas, 1933) from Buriol Site, Brazil, Hyperodapedon AZ, Carnian. A. UFRGS-PV-1581-T #17; A1, subcircular cluster connected to a cluster of grooves; A2, schematic drawing. B. UFRGS-PV-1581-T #13; B1, subcircular cluster associated to an irregular cluster of grooves (arrow), possibly a partially preserved subcircular cluster; B2, schematic drawing. C. UFRGS-PV-1581-T #16 showing an isolated subcircular cluster of grooves.

Fig. 3 in New bioerosion traces in rhynchosaur bones from the Upper Triassic of Brazil and the oldest occurrence of the ichnogenera Osteocallis and Amphifaoichnus

Fig. 3. Arthropod bioerosion trace fossil Amphifaoichnus isp. on bone fragments of the rhynchosaurid archosauromorph Hyperodapedon mariensis (Tupi Caldas, 1933) from Buriol Site, Brazil, Hyperodapedon AZ, Carnian. A. UFRGS-PV-1581-T #3; A1, close up showing Amphifaoichnus isp. (note the bone chips) associated to a perpendicular boring (dashed outline) and feeding traces of Osteocallis mandibulus Roberts et al., 2007 (arrow; see also Fig. 4A1); A2, axial view of µCT scan showing the internal morphology of the tube, meniscate structures and the perpendicular boring; A3, coronal view of µCT scan showing the trace (dotted surface) and the destruction of both cortical (black outline) and trabecular bone. B. UFRGS-PV-1581-T #4; B1, specimen arrow) showing the uneven distribution of bone chips in the filling; B2, specimen in transversal view showing the rounded morphology of the filling. C. UFRGS-PV-1581-T #10; C1, specimen in negative relief with a small portion of filling still preserved (arrow); C2, close up of filling; C3, specimen in transversal view showing the U-shape of the boring.

opencc-by-4.0Apr 2024View details →

BioPropaPhenKG Towards Monkeypox and COVID-19 Case Tracing and Analysing

This repository contains: <ul> <li>The BioPropaPhen ontology created from PropaPhen, being specialized with UMLS and World Knowledge Graph ontologies;</li> <li>A neo4j 4.4.3 dump file of the BioPropaPhenKG knowledge graph with WHO ground truth data about COVID-19 and Monkeypox, and enhanced presence edges between UMLS entities to World KG entities for evaluating the<a href="https://github.com/Gabriel382/DDPF-Health-Risks"> Description-Detection-Prediction Framework </a></li> </ul> The datasets used for enhancing the KG are: <table> <tbody> <tr> <td>Phenomenon</td> <td>Dataset</td> <td>Period</td> <td>Documents</td> <td>Source</td> <td>Link</td> </tr> <tr> <td>COVID-19</td> <td>Aylien</td> <td>Nov-2019</td> <td>8</td> <td>Online News</td> <td>ttps://aylien.com/resources/datasets/coronavirus-dataset</td> </tr> <tr> <td>COVID-19</td> <td>CORD-19</td> <td>Dec-2019</td> <td>720</td> <td>Medical Articles</td> <td>https://allenai.org/data/cord-19</td> </tr> <tr> <td>COVID-19</td> <td>RedditCOVID</td> <td>Feb-2020</td> <td>4,980</td> <td>Social Media</td> <td>https://paperswithcode.com/dataset/the-reddit-covid-dataset</td> </tr> <tr> <td>Monkeypox</td> <td>Mined from BBC</td> <td>May-2022</td> <td>27</td> <td>Online News</td> <td> </td> </tr> <tr> <td>Monkeypox</td> <td>Mined from Pubmed</td> <td>June-2022</td> <td>36</td> <td>Medical Articles</td> <td> </td> </tr> <tr> <td>Monkeypox</td> <td>MonkeyPox2022</td> <td>May-2022</td> <td>33,826</td> <td>Social Media</td> <td>https://doi.org/10.3390/idr14060087</td> </tr> </tbody> </table>

opencc-by-4.0Apr 2024View details →

Particulate atmospheric concentrations of trace metals and leachable nutrients in air at the Southeastern Mediterranean Sea (1994-1999)

Table 1 dataset contains aerosol concentrations of trace metals (Cd, Pb, Cu, Zn, Cr, Mn, Fe and Al) at the SE Mediterranean coast of Israel, collected between 1994 and 1999. Total suspended particles (TSP) in air were collected on Whatman QM-A quartz microfibre filters and on Whatman 41 filters (both 20.3 cm x 25.4 cm), by high-volume sampler (HVS).  The HVS was located on the roof of the National Institute of Oceanography (NIO) at Tel-Shikmona, Israel (located on the shore, 22 m above sea level) and at Maagan Michael, Israel (about 900m from shore, 13 m above sea level). Analyses were carried out after total digestion with HF following the procedure of ASTM (1983). Further details in Herut et al., 2001. Table 2 dataset contains leachable inorganic nitrogen (NO3 + NO2, NH4) and phosphorus (PO4) concentrations in aerosol (total suspended particles in air) samples collected on Whatman 41 filters between April 1996 and January 1999. The atmospheric sampling was performed on the roof of the National Institute of Oceanography (NIO) at Tel-Shikmona (TS), Israel (located on the shore and inside the sea, 22 m above sea level). Leaching experiments were performed to evaluate the amount of seawater leachable nitrate, ammonium, and phosphate from the TSP using SE Mediterranean low nutrient low chlorophyll surface seawater. Further details in Herut et al., 2002. Herut, B., Nimmo, M., Medway, A., Chester, R., & Krom, M. D. (2001). Dry atmospheric inputs of trace metals at the Mediterranean coast of Israel (SE Mediterranean): sources and fluxes. Atmospheric Environment, 35(4), 803-813.&rlm; Herut, B., Collier, R., & Krom, M. D. (2002). The role of dust in supplying nitrogen and phosphorus to the Southeast Mediterranean. Limnology and Oceanography, 47(3), 870-878.&rlm; Herut, B., Krom, M. D., Pan, G., & Mortimer, R. (1999). Atmospheric input of nitrogen and phosphorus to the Southeast Mediterranean: Sources, fluxes, and possible impact. Limnology and Oceanography, 44(7), 1683-1692.&rlm;

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The entorhinal cortex modulates trace fear memory formation and neuroplasticity in the lateral amygdala via cholecystokinin

Although the neural circuitry underlying fear memory formation is important in fear-related mental disorders, it is incompletely understood. Here, we utilized trace fear conditioning to study the formation of trace fear memory. We identified the entorhinal cortex (EC) as a critical component of sensory signaling to the amygdala. Moreover, we used the loss of function and rescue experiments to demonstrate that release of the neuropeptide cholecystokinin (CCK) from the EC is required for trace fear memory formation. We discovered that CCK-positive neurons extend from the EC to the lateral nuclei of the amygdala (LA), and inhibition of CCK-dependent signaling in the EC prevented long-term potentiation of sensory signals to the LA and formation of trace fear memory. Altogether, we suggest a model where sensory stimuli trigger the release of CCK from EC neurons, which potentiates sensory signals to the LA, ultimately influencing neural plasticity and trace fear memory formation.

opencc-zeroNov 2021View details →

opencc-by-4.0Feb 2022View details →

Anonymized GTP Tunnel Trace in Mobile IoT

Extensive dataset containing one whole month of create and delete events as well as the total, received, and transmitted volume of devices. We obtained data tunnel related events and volume values over 30 days in October 2021. In total the dataset contains a sample of 500000 unique devices that generate 155 million individual data tunnels.

opencc-by-4.0Jan 2021View details →

AndroCT: Ten Years of App Call Traces in Android

A large-scale dataset on the dynamic profiles based on function calls of 35,974 benign and malicious Android apps from 10 historical years (2010 through 2019). Function calls are a commonly used means to model program behaviors, which may contribute to various code analysis approaches to assuring software correctness, reliability, and security. In particular, our dataset includes dynamic profiles of each app resulting from the same-length of time (10 mins) of being exercised by randomly generated inputs on both emulator and real device, enabling interesting and useful app analysis that reason about app behaviors in an evolutionary perspective while informing the differences of app behaviors on different run-time hardware platforms. Since we have 20 yearly datasets associated with 35,974 unique Android apps across the 10 years, profiling these apps took 12,000 hours. Considering the costs of filtering out apps that were originally sampled but that we were unable to profile (due to various reasons such as broken APKs, not being executable because of incompatibility issues, not instrumentable, etc.), we took over two years to produce all these traces. We hope to save future researchers' time in producing such a set of dynamic data to enable their empirical and technical work.  ================== Thanks for your interest in our dataset. Collecting this dataset took tremendous computational and human effort. Thus, please observe the following restrictions in using our dataset:     -  Do not redistribute this dataset without our consent.    -  Do not make commercial usage of this dataset.    -  Get a faculty, or someone in a permanent position, to agree and commit to these conditions.    -  When publishing your work that uses our dataset, please cite the following MSR 2021 data paper. @inproceedings{AndroidCT,   title = {AndroCT: Ten Years of App Call Traces in Android},   author = {<a href="https://2021.msrconf.org/profile/wenli">Wen Li</a>, <a href="https://2021.msrconf.org/profile/xiaoqinfu">Xiaoqin Fu</a>, and <a href="https://2021.msrconf.org/profile/haipengcai">Haipeng Cai</a>},   booktitle = {The 18th International Conference on Mining Software Repositories (MSR 2021), Data Showcase Track},   year = {2021}, }

opencc-by-4.0Mar 2022View details →

Mining Fork-Including Software Development Traces

This dataset relates to the paper: Mining Fork-Including Development Traces (abstract below) Authors: Iris Reinhartz-Berger and Amir Tomer Starting point: readme.txt Open-source software development is a common practice that encourages collaborative development and reuse across projects. Forking is a way to make a copy of an existing project and explore it for different purposes. Two types of forks are commonly mentioned in the literature: contributing forks which continue the development lines of the forked projects and aim at merging the contribution back to the forked projects; and independently developed forks which open new lines of development deviating from the forked projects. In this study, we aim to explore characteristics of fork-involving software development traces. Analyzing 880 Java projects and their related action and observation events, with process mining and statistical techniques, we found that the occurrence of certain event types may predict the fork type, while the creation of certain fork types increase the involvement of users in the forked projects.