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870 results for “boxing”
Data from: Genomic identification, characterization and differential expression analysis of SBP-box gene family in Brassica napus
Background: SBP-box genes belong to one of the largest families of transcription factors. Though members of this family have been characterized to be important regulators of diverse biological processes, information of SBP-box genes in the third most important oilseed crop Brassica napus is largely undefined. Results: In the present study, by whole genome bioinformatics analysis and transcriptional profiling, 58 putative members of SBP-box gene family in oilseed rape (Brassica napus L.) were identified and their expression pattern in different tissues as well as possible interaction with miRNAs were analyzed. In addition, B. napus lines with contrasting branch angle were used for investigating the involvement of SBP-box genes in plant architecture regulation. Detailed gene information, including genomic organization, structural feature, conserved domain and phylogenetic relationship of the genes were systematically characterized. By phylogenetic analysis, BnaSBP proteins were classified into eight distinct groups representing the clear orthologous relationships to their family members in Arabidopsis and rice. Expression analysis in twelve tissues including vegetative and reproductive organs showed different expression patterns among the SBP-box genes and a number of the genes exhibit tissue specific expression, indicating their diverse functions involved in the developmental process. Forty-four SBP-box genes were ascertained to contain the putative miR156 binding site, with 30 and 14 of the genes targeted by miR156 at the coding and 3′UTR region, respectively. Relative expression level of miR156 is varied across tissues. Different expression pattern of some BnaSBP genes and the negative correlation of transcription levels between miR156 and its target BnaSBP gene were observed in lines with different branch angle. Conclusions: Taken together, this study represents the first systematic analysis of the SBP-box gene family in Brassica napus. The data presented here provides base foundation for understanding the crucial roles of BnaSBP genes in plant development and other biological processes.
Old English Post Box
Old English Post Box captured by iPhone Source: Objaverse 1.0 / Sketchfab
Money box TARDIS
Doctor Who TARDIS moneybox - Created with Polycam Source: Objaverse 1.0 / Sketchfab
Telephone Box
Source: Objaverse 1.0 / Sketchfab
Box 2 in Towards a global list of accepted species III. Independence and stakeholder inclusion
Box 2 Main steps in the global listing process
esp32-EIT-box
Open the record for dataset details and reuse information.
Figure 3 from: Stauch KLN, Wincheski RJ, Albers J, Black TE, Reichert MS, Abramson CI (2021) Limited evidence for learning in a shuttle box paradigm in crickets (Acheta domesticus). Journal of Orthoptera Research 30(2): 155-161. https://doi.org/10.3897/jor.30.65172
Figure 3 Proportion of mean time spent on correct side of the apparatus for male crickets during each 60 s interval. Male N values: Baseline = 10, Yoked = 21, Master = 21. The bars on the data points represent the standard errors. The solid line at 0.5 indicates chance.
Figure 2 from: Stauch KLN, Wincheski RJ, Albers J, Black TE, Reichert MS, Abramson CI (2021) Limited evidence for learning in a shuttle box paradigm in crickets (Acheta domesticus). Journal of Orthoptera Research 30(2): 155-161. https://doi.org/10.3897/jor.30.65172
Figure 2 Proportion of mean time spent on correct side of the apparatus for female crickets during each 60 s interval. Female N values: Baseline = 18, Yoked = 30, and Master = 30. The bars on the data points represent the standard errors. The solid line at 0.5 indicates chance.
Figure 1 from: Stauch KLN, Wincheski RJ, Albers J, Black TE, Reichert MS, Abramson CI (2021) Limited evidence for learning in a shuttle box paradigm in crickets (Acheta domesticus). Journal of Orthoptera Research 30(2): 155-161. https://doi.org/10.3897/jor.30.65172
Figure 1 The shuttle box apparatus with propeller controller in the upper left-hand corner. In this image, one of the plexiglass covers (A) has been removed so that the shock grid can be seen more easily. In the experiments, one cricket was placed into the compartment labeled A and one cricket was placed into the compartment labeled B. A piece of filter paper was placed under the left-hand side of the shuttle box to illustrate the midpoint for the two halves of the compartment. Once the cricket was inside the compartment, the plexiglass was placed over the compartment to ensure that the cricket maintained contact with the grid.
Supplementary material 1 from: Phillips HRP, Cameron EK, Eisenhauer N (2022) Illuminating biodiversity changes in the 'Black Box'. Research Ideas and Outcomes 8: e87143. https://doi.org/10.3897/rio.8.e87143
SoilFaUNa Sampling Protocol
J1 Low Ions MD Traj b (Huge box, 64-nt HJ and 24-nt HJ systems)
<p>J1 Low Ions MD Traj b</p> <p>With AMBER topology file and NetCDF trajectories.</p>
SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Black-Box Machine-Generated Text Detection
<p>Large language models (LLMs) are becoming mainstream and easily accessible, ushering in an explosion of machine-generated content over various channels, such as news, social media, question-answering forums, educational, and even academic contexts. Recent LLMs, such as ChatGPT and GPT-4, generate remarkably fluent responses to a wide variety of user queries. The articulate nature of such generated texts makes LLMs attractive for replacing human labor in many scenarios. However, this has also resulted in concerns regarding their potential misuse, such as spreading misinformation and causing disruptions in the education system. Since humans perform only slightly better than chance when classifying machine-generated vs. human-written text, there is a need to develop automatic systems to identify machine-generated text with the goal of mitigating its potential misuse.</p> <p>We offer three subtasks over two paradigms of text generation: (1) <strong>full text</strong> when a considered text is entirely written by a human or generated by a machine; and (2) <strong>mixed text</strong> when a machine-generated text is refined by a human or a human-written text paraphrased by a machine.</p>
Figure 3 in Charles Darwin's early beetle collections: 'Darwin's beetle box' and the Down House box
Figure 3. Down House box, with labelled position codes.
Figure 1 in Charles Darwin's early beetle collections: 'Darwin's beetle box' and the Down House box
Figure 1. Darwin's insect cabinet in Christ's College, Cambridge.
Do Developers Use Static Application Security Testing (SAST) Tools Straight Out of the Box? A large-scale Empirical Study
Open the record for dataset details and reuse information.
Fig. 2 in Dipteran Assemblages In Red-Footed Falcon (Falco Vespertinus) Nest Boxes
Fig. 2. Phenology of emergence of Carnus hemapterus imagoes from three years old accumulated nest material (collected in 2009), grouped by the last breeding bird species (n =
Data from: Y-box protein 1 is required to sort microRNAs into exosomes in cells and in a cell-free reaction
Exosomes are small vesicles that are secreted from metazoan cells and may convey selected membrane proteins and small RNAs to target cells for the control of cell migration, development and metastasis. To study the mechanisms of RNA packaging into exosomes, we devised a purification scheme based on the membrane marker CD63 to isolate a single exosome species secreted from HEK293T cells. Using immunoisolated CD63-containing exosomes we identified a set of miRNAs that are highly enriched with respect to their cellular levels. To explore the biochemical requirements for exosome biogenesis and RNA packaging, we devised a cell-free reaction that recapitulates the species-selective enclosure of miR-223 in isolated membranes supplemented with cytosol. We found that the RNA-binding protein Y-box protein I (YBX1) binds to and is required for the sorting of miR-223 in the cell-free reaction. Furthermore, YBX1 serves an important role in the secretion of miRNAs in exosomes by HEK293T cells.
Data from: Genomic BLUP decoded: a look into the black box of genomic prediction
Genomic best linear unbiased prediction (BLUP) is a statistical method that uses relationships between individuals calculated from single-nucleotide polymorphisms (SNPs) to capture relationships at quantitative trait loci (QTL). We show that genomic BLUP exploits not only linkage disequilibrium (LD) and additive-genetic relationships, but also cosegregation to capture relationships at QTL. Simulations were used to study the contributions of those types of information to accuracy of genomic estimated breeding values (GEBVs), their persistence over generations without retraining, and their effect on the correlation of GEBVs within families. We show that accuracy of GEBVs based on additive-genetic relationships can decline with increasing training data size and speculate that modeling polygenic effects via pedigree relationships jointly with genomic breeding values using Bayesian methods may prevent that decline. Cosegregation information from half sibs contributes little to accuracy of GEBVs in current dairy cattle breeding schemes but from full sibs it contributes considerably to accuracy within family in corn breeding. Cosegregation information also declines with increasing training data size, and its persistence over generations is lower than that of LD, suggesting the need to model LD and cosegregation explicitly. The correlation between GEBVs within families depends largely on additive-genetic relationship information, which is determined by the effective number of SNPs and training data size. As genomic BLUP cannot capture short-range LD information well, we recommend Bayesian methods with t-distributed priors.
Figure 8 in An illustrated key and synopsis of the families and genera of carybdeid box jellyfishes (Cnidaria: Cubozoa: Carybdeida), with emphasis on the "Irukandji family" (Carukiidae)
Figure 8. Nematocysts of Morbakka virulenta; for identifications and sizes see cnidome description.
Figure 6 in An illustrated key and synopsis of the families and genera of carybdeid box jellyfishes (Cnidaria: Cubozoa: Carybdeida), with emphasis on the "Irukandji family" (Carukiidae)
Figure 6. Nematocysts of Malo filipina; for identifications and sizes see cnidome description.
ScienceDex guides
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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.