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6,861 results for “Animation”
An animation of the proposed steps for the creation of the first RNA molecule out of steroids.
<p>An animation of the proposed steps for the creation of the first RNA molecule out of steroids.</p>
Data from: Enhancement of apoptosis by titanium alloy internal fixations during microwave treatments for fractures: an animal study
Objective: Microwaves are used in one method of physical therapy and can increase muscle tissue temperature which is useful for improving muscle, tendon and bone injuries. In the study, we sought to determine whether titanium alloy internal fixations influence apoptosis in tissues subjected to microwave treatments at 2,450 MHz and 40 W during the healing of fractures because this issue is not yet fully understood. Methods: In this study, titanium alloy internal fixations were used to treat 3.0-mm transverse osteotomies in the middle of New Zealand rabbits' femurs. After the operation, 30-day microwave treatments were applied to the 3.0 mm transverse osteotomies 3 days after the operation. The changes in the temperatures of the muscle tissues in front of the implants or the 3.0 mm transverse osteotomies were measured during the microwave treatments. To characterize the effects of titanium alloy internal fixations on apoptosis in the muscles after microwave treatment, we performed TUNEL assays, fluorescent real-time (quantitative) PCR, western blotting analyses, reactive oxygen species (ROS) detection and transmission electron microscopy examinations. Results: The temperatures were markedly increased in the animals with the titanium alloy implants. Apoptosis in the muscle cells of the implanted group was significantly more extensive than that in the non-implanted control group at different time points. Transmission electron microscopy examinations of the skeletal muscles of the implanted groups revealed muscular mitochondrial swelling, vacuolization. ROS, Bax and Hsp70 were up-regulated, and Bcl-2 was down-regulated in the implanted group. Conclusion: Our results suggest that titanium alloy internal fixations caused greater muscular tissue cell apoptosis following 2,450 MHz, 40 W microwave treatments in this rabbit femur fracture models.
Data from: Predicting animal behaviour using deep learning: GPS data alone accurately predict diving in seabirds
1.In order to prevent further global declines in biodiversity, identifying and understanding key habitats is crucial for successful conservation strategies. For example, globally, seabird populations are under threat and animal movement data can identify key at-sea areas and provide valuable information on the state of marine ecosystems. To date, in order to locate these areas, studies have used Global Positioning System (GPS) to record position and are sometimes combined with Time Depth Recorder (TDR) devices to identify diving activity associated with foraging, a crucial aspect of at-sea behaviour. However, the use of additional devices such as TDRs can be expensive, logistically difficult, and may adversely affect the animal. Alternatively, behaviours may be resolved from measurements derived from the movement data alone. However, this behavioural analysis frequently lacks validation data for locations predicted as foraging (or other behaviours). 2.Here, we address these issues using a combined GPS and TDR dataset from 108 individuals by training deep learning models to predict diving in European shags, common guillemots and razorbills. We validate our predictions using withheld data, producing quantitative assessment of predictive accuracy. The variables used to train these models are those recorded solely by the GPS device: variation in longitude and latitude, altitude, and coverage ratio (proportion of possible fixes acquired within a set window of time). 3.Different combinations of these variables were used to explore the qualities of different models, with the optimum models for all species predicting non-diving and diving behaviour correctly over 94% and 80% of the time, respectively. We also demonstrate the superior predictive ability of these supervised deep-learning models over other commonly used behavioural prediction methods such as hidden Markov models. 4.Mapping these predictions provides useful insights into the foraging activity of a range of seabird species, highlighting important at sea locations. These models have the potential to be used to analyse historic GPS datasets and further our understanding of how environmental changes have affected these seabirds over time.
Data from: Adaptation and plasticity of animal communication in fluctuating environments
Adaptations that facilitate the reception of long-range signals under challenging conditions are expected to generate signal diversity when species communicate in different habitats. While we have a general understanding of how individual communicating animals cope with conditions influencing signal detection, the extent to which plasticity and evolutionary changes in signal characteristics contribute to interspecific differences in signaling behavior is unclear. We quantified the visual displays of free-living lizards and environmental variables known to influence display detection for multiple species from two separate island radiations. We found evidence of both adaptive evolution and adaptive plasticity in display characteristics as a function of environmental conditions, but plasticity accounted for most of the observed differences in display behavior across species. At the same time, prominent differences between the two island radiations existed in aspects of signaling behavior, unrelated to the environment. Past evolutionary events have therefore played an important role in shaping the way lizards adjust their signals to challenges in present-day environments. In addition to showing how plasticity contributes to interspecific differences in communication signals, our findings suggest the vagaries of evolution can in itself lead to signal variation between species.
Data from: Biogeography of Leptospira in wild animal communities inhabiting the insular ecosystem of the western Indian Ocean islands and neighboring Africa
Understanding the processes driving parasite assemblages is particularly important in the context of zoonotic infectious diseases. Leptospirosis is a widespread zoonotic bacterial infection caused by pathogenic species of the genus Leptospira. Despite a wide range of animal hosts, information is still lacking on the factors shaping Leptospira diversity in wild animal communities, especially in regions, such as tropical insular ecosystems, with high host species richness and complex biogeographical patterns. Using a large dataset (34 mammal species) and a multilocus approach at a regional scale, we analyzed the role of both host species diversity and geography in Leptospira genetic diversity in terrestrial small mammals (rodents, tenrecs and shrews) and bats from 10 different islands/countries in the western Indian Ocean (WIO) and neighboring Africa. At least four Leptospira spp. (L. interrogans, L. borgpetersenii, L. kirschneri and L. mayottensis) and several yet-unidentified genetic clades contributed to a remarkable regional Leptospira diversity, which was generally related to the local occurrence of the host species rather than the geography. In addition, the genetic structure patterns varied between Leptospira spp., suggesting different evolutionary histories in the region, which might reflect both in situ diversification of native mammals (for L. borgpetersenii) and the more recent introduction of non-native host species (for L. interrogans). Our data also suggested that host shifts occurred between bats and rodents, but further investigations are needed to determine how host ecology may influence these events.
Data from: Analysis of phylogenomic datasets reveals conflict, concordance, and gene duplications with examples from animals and plants
Background: The use of transcriptomic and genomic datasets for phylogenetic reconstruction has become increasingly common as researchers attempt to resolve recalcitrant nodes with increasing amounts of data. The large size and complexity of these datasets introduce significant phylogenetic noise and conflict into subsequent analyses. The sources of conflict may include hybridization, incomplete lineage sorting, or horizontal gene transfer, and may vary across the phylogeny. For phylogenetic analysis, this noise and conflict has been accommodated in one of several ways: by binning gene regions into subsets to isolate consistent phylogenetic signal; by using gene-tree methods for reconstruction, where conflict is presumed to be explained by incomplete lineage sorting (ILS); or through concatenation, where noise is presumed to be the dominant source of conflict. The results provided herein emphasize that analysis of individual homologous gene regions can greatly improve our understanding of the underlying conflict within these datasets. Results: Here we examined two published transcriptomic datasets, the angiosperm group Caryophyllales and the aculeate Hymenoptera, for the presence of conflict, concordance, and gene duplications in individual homologs across the phylogeny. We found significant conflict throughout the phylogeny in both datasets and in particular along the backbone. While some nodes in each phylogeny showed patterns of conflict similar to what might be expected with ILS alone, the backbone nodes also exhibited low levels of phylogenetic signal. In addition, certain nodes, especially in the Caryophyllales, had highly elevated levels of strongly supported conflict that cannot be explained by ILS alone. Conclusion: This study demonstrates that phylogenetic signal is highly variable in phylogenomic data sampled across related species and poses challenges when conducting species tree analyses on large genomic and transcriptomic datasets. Further insight into the conflict and processes underlying these complex datasets is necessary to improve and develop adequate models for sequence analysis and downstream applications. To aid this effort, we developed the open source software phyparts (https://bitbucket.org/blackrim/phyparts), which calculates unique, conflicting, and concordant bipartitions, maps gene duplications, and outputs summary statistics such as internode certainy (ICA) scores and node-specific counts of gene duplications.
Data from: Big data analysis of genes associated with neuropsychiatric disorders in an Alzheimer's disease animal model
Alzheimer's disease is a neurodegenerative disease characterized by the impairment of cognitive function and loss of memory, affecting millions of individuals worldwide. With the dramatic increase in the prevalence of Alzheimer's disease, it is expected to impose extensive public health and economic burden. However, this burden is particularly heavy on the caregivers of Alzheimer's disease patients eliciting neuropsychiatric symptoms that include mood swings, hallucinations, and depression. Interestingly, these neuropsychiatric symptoms are shared across symptoms of bipolar disorder, schizophrenia, and major depression disorder. Despite the similarities in symptomatology, comorbidities of Alzheimer's disease and these neuropsychiatric disorders have not been studied in the Alzheimer's disease model. Here, we explore the comprehensive changes in gene expression of genes that are associated with bipolar disorder, schizophrenia, and major depression disorder through the microarray of an Alzheimer's disease animal model, the forebrain specific PSEN double knockout mouse. To analyze the genes related with these three neuropsychiatric disorders within the scope of our microarray data, we used selected 1207 of a total of 45,037 genes that satisfied our selection criteria. These genes were selected on the basis of 14 Gene Ontology terms significantly relevant with the three disorders which were identified by previous research conducted by the Psychiatric Genomics Consortium. Our study revealed that the forebrain specific deletion of Alzheimer's disease genes can significantly alter neuropsychiatric disorder associated genes. Most importantly, most of these significantly altered genes were found to be involved with schizophrenia. Taken together, we suggest that the synaptic dysfunction by mutation of Alzheimer's disease genes can lead to the manifestation of not only memory loss and impairments in cognition, but also neuropsychiatric symptoms.
Data from: Mitochondrial genomes of domestic animals need scrutiny
More than 1000 complete or near-complete mitochondrial DNA (mtDNA) sequences have been deposited in GenBank for eight common domestic animals (cattle, dog, goat, horse, pig, sheep, yak and chicken) and their close wild ancestors or relatives, as well. Nevertheless, few efforts have been performed to evaluate the sequence data quality. Herein, we conducted a phylogenetic survey of these complete or near-complete mtDNA sequences based on mtDNA haplogroup trees for the eight animals. We show that errors due to artificial recombination, surplus of mutations, and phantom mutations, do exist in 14.5% (194/1342) of mtDNA sequences and all of them should be treated with wide caution. We propose some caveats for future mtDNA studies of domestic animals.
Data from: Machine learning to classify animal species in camera trap images: applications in ecology
Motion‐activated cameras ("camera traps") are increasingly used in ecological and management studies for remotely observing wildlife and are amongst the most powerful tools for wildlife research. However, studies involving camera traps result in millions of images that need to be analysed, typically by visually observing each image, in order to extract data that can be used in ecological analyses. We trained machine learning models using convolutional neural networks with the ResNet‐18 architecture and 3,367,383 images to automatically classify wildlife species from camera trap images obtained from five states across the United States. We tested our model on an independent subset of images not seen during training from the United States and on an out‐of‐sample (or "out‐of‐distribution" in the machine learning literature) dataset of ungulate images from Canada. We also tested the ability of our model to distinguish empty images from those with animals in another out‐of‐sample dataset from Tanzania, containing a faunal community that was novel to the model. The trained model classified approximately 2,000 images per minute on a laptop computer with 16 gigabytes of RAM. The trained model achieved 98% accuracy at identifying species in the United States, the highest accuracy of such a model to date. Out‐of‐sample validation from Canada achieved 82% accuracy and correctly identified 94% of images containing an animal in the dataset from Tanzania. We provide an r package (Machine Learning for Wildlife Image Classification) that allows the users to (a) use the trained model presented here and (b) train their own model using classified images of wildlife from their studies. The use of machine learning to rapidly and accurately classify wildlife in camera trap images can facilitate non‐invasive sampling designs in ecological studies by reducing the burden of manually analysing images. Our r package makes these methods accessible to ecologists.
Data from: Performance assessment of two whole-lake acoustic positional telemetry systems - is reality mining of free-ranging aquatic animals technologically possible?
Acoustic positional telemetry systems (APTs) represent a novel approach to study the behaviour of free ranging aquatic animals in the wild at unprecedented detail. System manufactures promise remarkably high temporal and spatial resolution. However, the performance of APTs has rarely been rigorously tested at the level of entire ecosystems. Moreover, the effect of habitat structure on system performance has only been poorly documented. Two APTs were deployed to cover two small lakes and a series of standardized stationary tests were conducted to assess system performance. Furthermore, a number of tow tests were conducted to simulate moving fish. Based on these data, we quantified system performance in terms of data yield, accuracy and precision as a function of structural complexity in relation to vegetation. Mean data yield of the two systems was 40 % (Lake1) and 60 % (Lake2). Average system accuracy (acc) and precision (prec) were Lake1: acc = 3.1 m, prec = 1.1 m; Lake2: acc = 1.0 m, prec = 0.2 m. System performance was negatively affected by structural complexity, i.e., open water habitats yielded far better performance than structurally complex vegetated habitats. Post-processing greatly improved data quality, and sub-meter accuracy and precision were, on average, regularly achieved in Lake2 but remained the exception in the larger and structurally more complex Lake1. Moving transmitters were tracked well by both systems. Whereas overestimation of moved distance is inevitable for stationary transmitters due to accumulation of small tracking errors, moving transmitters can result in both over- and underestimation of distances depending on circumstances. Both deployed APTs were capable of providing high resolution positional data at the scale of entire lakes and are suitable systems to mine the reality of free ranging fish in their natural environment. This opens important opportunities to advance several fields of study such as movement ecology and animal social networks in the wild. It is recommended that thorough performance tests are conducted in any study utilizing APTs. The APTs tested here appear best suited for studies in structurally simple ecosystems or for studying pelagic species. In such situations, the data quality provided by the APTs is exceptionally high.
iBOL DNA barcode data for animals (COI)
<p>International Barcode of Life project (iBOL) Data Packages for animals, releases 0.5-6.00.</p>
Dataset animal-vs-empty collected by camera trap prototype for research purposes
Open the record for dataset details and reuse information.
Codes and animal_2 dataset used in MCCP experiments
<h3>Code:</h3> <p>Mode_code.zip is the packaged code, for a description of the code see README.md.</p> <p>The same code was uploaded by us at <a href="https://github.com/Simba-brother/MCCP" target="_blank" rel="noopener">https://github.com/Simba-brother/MCCP</a></p> <h3><strong>Dataset</strong></h3> <p><strong>./merged_data</strong>: Mixing of party A and party B on the training and test sets.</p> <p><strong>./merged_model:</strong> Model structure of MCC.</p> <p><strong>./OriginModel:</strong> Assessment results of the teacher model.</p> <p><strong>./party_A: </strong>Party A's dataset and model.</p> <p><strong>./party_B: </strong>Party B's dataset and model.</p> <p><strong>./MCCP: </strong>MCCP method training weights and a:ssessment results.</p> <p><strong>./CFL: </strong>CFL method training weights and assessment results.</p> <p><strong>./HMR:</strong> HMR method training weights and assessment results.</p> <p><strong>./Dummy:</strong> Dummy method assessment results.</p> <p><strong>./DecisionTree:</strong> Decision method training weights and assessment results.</p> <p><strong>./LogisticRegression: </strong>LogisticRegression method training weights and assessment results.</p> <h3>Download addresses of other Datasets and Models</h3> <div> <div>Since the data set and model are large and the platform has limitations, we upload the remaining data sets and models to the link below. If necessary, you can download them through the link below.</div> </div> <p><a href="https://pan.quark.cn/s/09b446b8f944" target="_blank" rel="noopener">https://pan.quark.cn/s/09b446b8f944</a></p> <p> </p> <p> </p> <p> </p>
Top Popular Animes
<p>Top popular animes dataset from myanimelist. Done with Python.</p> <p>Animes més populars de myanimelist. Fet amb Python.</p> <p>Cada fila del dataset corespon a un anime.</p> <p>- Nom: títol del anime.<br> - Nota: Nota mitja de les valoracions dels usuaris.<br> - Ranking: Posició en el ranking de més populars.<br> - Seguidors: Nombre de seguidors en la pagina.<br> - Tipus: tipus del anime, el qual pot ser “TV” (serie de TV), “Movie” (pelicula), “OVA” i <br> “Special” (episodis espacials) i “ONA” (serie online).<br> - Episodis: Número d’episodis totals.<br> - Llicència: Llista de distribuïdors.<br> - Estudi: Llista de productors.<br> - Gènere: temes relacionats amb aquell anime (exemple: Misteri, Suspens, etc.).<br> - Demografia: categoria japonesa per saber a qui va dirigit l’anime, per exemples: Shounen(adolecent masculí), Shojo(adolecent femení), Ecchi (adults), etc.<br> - Edat: Rang d’edat per visualitzar l’anime</p>
Machine learning-aided design of composite mycotoxin detoxifier material for animal feed
<p>Model codes and dataset associated to "Machine learning-aided design of composite mycotoxin detoxifier material for animal feed, Giulia Lo Dico, Siska Croubels, Verónica Carcelén, and Maciej Haranczyk, Sci. Rep., 2022".</p>
Fig. 5 in Trichinellosis Of Wild Animals In Ukraine And Its Danger To The Public
Fig. 5. Frequency of trichinellosis for the population of Ukraine, 1986–2018.
Source data: Transmission of SARS-CoV-2 from humans to animals and potential host adaptation
<p>All source data required for reproducing the results of the associated manuscript. Contains data inputs for all associated custom code hosted on Zenodo (https://doi.org/10.5281/zenodo.6528187).</p>
Bronze Animal Finial, late 12th-11th century BCE
Ancient Chinese bronze finial in the shape of an animal, late 12th - 11th century BCE, now in the collection of the Minneapolis Institute of Art. More Information: https://collections.artsmia.org/art/1155/finial-with-animal-china Source: Objaverse 1.0 / Sketchfab
Figure 1 from: Polilov AA (2017) First record of Megaphragma (Hymenoptera, Trichogrammatidae) in Columbia, and third animal species known to have anucleate neurons. Journal of Hymenoptera Research 60: 181-185. https://doi.org/10.3897/jhr.60.19907
Figure 1 - Habitus of Megaphragma caribea, SEM: A dorsal view B lateral view.
Figure 10 from: Tandberg AHS, Vader W (2018) On a new species of Amphilochus from deep and cold Atlantic waters, with a note on the genus Amphilochopsis (Amphipoda, Gammaridea, Amphilochidae). In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 103–134. https://doi.org/10.3897/zookeys.731.19899
Figure 10 Amphilochus hamatus. Mouthparts. IINH37894. Scale bars: 0.1 mm.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.