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2,453 results for “Architecture”
Itarsi (इटारसी, Sehore District) Madhya Pradesh. Architectural fragment with a seated Ācārya
<p>Itarsi (इटारसी, Sehore District) Madhya Pradesh. Architectural fragment with a seated Ācārya</p>
Dataset for "Architectural Security Weaknesses in Industrial Control Systems: An Empirical Study Based on Security Advisories' Vulnerability Reports"
<p>Supplementary artifacts to "<em>Architectural Security Weaknesses in Industrial Control Systems (ICS): An Empirical Study based on Disclosed Software Vulnerabilities</em>"</p> <p>Published in the Proceedings from the 2019 IEEE International Conference on Software Architecture (ICSA)</p> <p>Package Contains:</p> <p>- Raw output showing Components, CAWEs, and CVEs per report</p> <p>- Frequency Data (# of reports) for those concerns</p> <p>- ICS Component - Term Dictionary </p> <p>- HTML versions of reports studied in paper</p>
Integrative modeling results of in-cell architecture of an actively transcribing-translating expressome
<p>Repository containing good-scoring models, input files, modeling and analysis protocols for the integrative modeling of the M. pneumoniae expressome from in-cell cryo-electron tomography and crosslinking mass spectrometry using IMP.</p>
Convolutional Neural Net (CNN) models for ENCODE-Roadmap DNase-seq peaks and Transcription Factor ChIP-seq peaks - Basset architecture
<p>Deep learning models trained on epigenomic landscapes from ENCODE and Roadmap Epigenomics. The models are Basset convolutional neural networks (Kelley, et al 2016). The dataset used to train these models can be found at https://doi.org/10.5281/zenodo.4059038. The file `nn.encode-roadmap.models.basset.clf.tar.gz` contains 10 cross-validated models in Tensorflow framework files as well as details on the architecture, cross-validation scheme, and training of these models. The file `nn.encode-roadmap.models.basset.clf.np_weights.tar.gz` contains the 10 cross-validated models' weights extracted to numpy array files (.npz).</p>
Convolutional Neural Net (CNN) models for epigenomic landscapes in epidermal differentiation - Basset architecture, classification and regression
<p>Deep learning models trained on epigenomic landscapes in keratinocyte differentiation. The models are Basset convolutional neural networks (Kelley, et al 2016). The dataset used to train these models can be found at https://doi.org/10.5281/zenodo.4062509. The file `nn.ggr.models.basset.clf.tar.gz` contains 10 cross-validated models that were pretrained using ENCODE-Roadmap trained model weights as initialization weights and also 10 cross-validated models that were initialized with random weights. Similarly, the file `nn.ggr.models.basset.regr.tar.gz` contains 10 cross-validated models that were pretrained using the classification model weights as initialization weights and also 10 cross-validated models that were initialized with random weights.</p>
Architectural Feature Re-Modularization for Software Product Line Evolution
<p>Extensive maintenance leads to the Software Product Line Architecture<br> (PLA) degradation over time. When there is the need of<br> evolving the Software Product Line (SPL) to include new features,<br> or move to a new platform, a degraded PLA requires considerable<br> effort to understand and modify, demanding expensive refactoring<br> activity. In the state of the art, search-based algorithms are used to<br> improve PLA at package level. However, recent studies have shown<br> that the most variability and implementation details of an SPL are<br> described in the level of classes. There is a gap between existing<br> approaches and existing practical needs. In this work, we extend<br> the current state of the art to deal with feature modularization in<br> the level of classes by introducing a new search operator and a set<br> of objective functions to deal with feature modularization in a finer<br> granularity of the architectural elements, namely at class level. We<br> evaluated the proposal in an exploratory study with a PLA widely<br> investigated and a real-world PLA. The results of quantitative and<br> qualitative analysis point out that our proposal provides solutions<br> to properly re-modularize features in a PLA, being preferred by<br> practitioners, in order to support the evolution of SPLs.</p>
Technical Debt: A Clean Architecture Implementation
<p>Technical Debt (TD) and Technical Debt Management (TDM) are terms that are receiving increasing attention from practitioners and researchers. They reflect a concern on how shortcuts taken during the software development process can incur negative impacts on software maintainability and how practitioners may use tools and techniques to mitigate the effects of the debt over time. A widely used tool to manage TD on an implementation level is SonarQube with the SQALE method, as it allows developers and managers to track debt over time. However, even SonarQube has its weaknesses since it only provides a set of architecture agnostic rules for TD, and the implementation of new rules can prove to be a challenging job. In this paper, we discuss how, during a real industrial project on a Brazilian software house, we developed a set of rules based on the Clean Architecture model, created a plug-in for SonarQube, and integrated it into our development cycle. At last, the preliminary results show that using a rigorous set of rules allows keeping track of TD on an implementation level.</p>
H.I.D.R.A.: A Hierarchical, Interactive and Dynamic Recognition Architecture for Product Categorization
<p>The Hierarchical, Interactive and Dynamic Recognition Architecture (H.I.D.R.A.) for Product Categorization is a new intelligent system architecture developed by Elo7 to easily evolve its category tree and automatically classify millions of products, thus improving the page ranking of our marketplace.</p>
Data from: ZmIBH1-1 regulates plant architecture in maize
<p>Leaf angle (LA) is a critical agronomic trait which affects grain yield through planting density in maize. Much research has been conducted in recent years to investigate the genes responsible for LA variation and a few genes were identified through map-based cloning. Here we cloned the <i>ZmIBH1-1</i> gene, which is a bHLH transcription factor with both a basic binding region and a Helix-Loop-Helix domain; and qRT-PCR results showed that <i>ZmIBH1-1</i> is a negative regulator of LA in maize. Histological analysis showed that the change in LA was mainly caused by differential cell wall lignification and cell elongation in the ligular region. To reveal the regulatory framework of <i>ZmIBH1-1</i>, we conducted RNA-Seq and DAP-Seq analysis. Overlay of the RNA-Seq and DAP-Seq results revealed 59 ZmIBH1-1 modulated target genes with annotation, and they were mainly cell wall related, cell development or hormone related genes. We have built a new regulatory model of <i>ZmIBH1-1 </i>gene controlling plant architecture in maize.</p>
Data set published in the IEEE TCAD article "Custom Multi-Cache Architectures for Heap-Manipulating Programs"
<p>This data set contains the results presented in the paper "Custom Multi-Cache Architectures for Heap-Manipulating Programs", published in the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) in 2016.</p> <p>The data set consists of two parts, a Microsoft Excel file ('FPGA_implementation_results.xlsx') and a Matlab script ('plot_cache_performance.m', in combination with measurement results in an ascii file).</p> <p>The Excel file contains<br /> - the FPGA resource utilisation,<br /> - execution time measurements,<br /> - hit rate measurement of the multi-cache system,<br /> - and power measurements</p> <p>of different FPGA designs with different on-chip cache configurations. The resource utilisation is split into FPGA slices, LUTs, FlipFlops, DSP slices and block RAMs. Results in this file can be found in Table I-IV in the paper. Please refer to the paper for more information or email f.winterstein12@imperial.ac.uk.</p> <p>The Matlab script loads a data file ('cache_performance_N16384_L1') containing the hit rate measurements for different cache sizes of two direct-mapped cache with 64bit line width. The script produces a 3D 'skyscraper' plot, i.e. a grid of coloured bars. Each bar corresponds to the hit rate measured at the particular cache size configuration. The plot is saved in the file 'surf.pdf'. The script was used to produce Figure 4 of the paper. Please refer to the paper for more information or email f.winterstein12@imperial.ac.uk.</p> <p>In addition to this description, we include an author copy of the paper. Note that this is not the official version of the paper. Please cite the original IEEE TCAD article if you use the data.</p>
Leaf growth response to mild drought: natural variation sheds light on trait architecture
<p>Plant growth and crop yield are negatively affected by a reduction in water availability. However, a clear understanding of how growth is regulated under non-lethal drought conditions is lacking. Recent advances in genomics, phenomics and transcriptomics allow in-depth analysis of natural variation. In this study, we conducted a detailed screening of leaf growth responses to mild drought in a worldwide collection of <em>Arabidopsis thaliana</em> accessions. </p> <p>The raw phenotyping can be found in:<br> - cellularData.txt -> mature (23 days after stratification; DAS) leaf epidermis (third leaf) analysed for cell area, cell number, pavement cell area, pavement cell number, stomatal index and leaf area of the analysed leaf.</p> <p>- leaf3AreaMaturity.txt -> area of the third leaf at maturity (23DAs) in mm<sup>2.</sup></p> <p>- leaf3AreaProliferation.txt -> area of the third leaf at proliferation (last day of full cell proliferation; 8-10 DAS) in mm<sup>2</sup>.</p> <p>- rosetteArea Maturity.txt -> projected rosette area at maturity (22DAS)</p> <p>The phenotyping results have been normalised for batch effects ('experiment' in raw data)</p> <p>- allPhenotypesNormalised.txt -> contains the normalised data for all the measured phenotypes</p> <p>All datafiles indicate the accession name ('Accession'), the unique identifier for each accessions ('Ecotype_ID') as used in the 1001genomes project (www.1001genomes.org) and the treatment ('C' indicate well-watered plants, 'S' the mild-drought treated plants).</p> <p>These results and methodological results are described in Clauw et al. (2016, The Plant Cell).</p> <p>Citation:</p> <p><strong>Clauw, Pieter, Frederik Coppens, Arthur Korte, Dorota Herman, Bram Slabbinck, Stijn Dhondt, Twiggy Van Daele, et al. 2016. “Leaf Growth Response to Mild Drought: Natural Variation in Arabidopsis Sheds Light on Trait Architecture.” The Plant Cell, October. doi:10.1105/tpc.16.00483.</strong></p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
On the Understandability of Semantic Constraints for Behavioral Software Architecture Compliance: A Controlled Experiment
<p>Software architecture compliance is concerned with the alignment of implementation with its desired architecture and detecting potential inconsistencies. The study is specifically concerned with behavioral architecture compliance. That is, the focus is on semantic alignment of implementation and architecture. In particular, the study evaluates three representative approaches for describing semantic constraints in terms of their understandability, namely natural language descriptions as used in many architecture documentations today, a structured language based on specification patterns that abstract underlying temporal logic formulas, and a structured cause-effect language that is based on Complex Event Processing. We conducted a controlled experiment with 190 participants using a simple randomized design with one alternative per experimental unit.</p>
Nicosia, Cyprus. Bedesten, interior, architectural fragments revealed by excavation.
<p>Nicosia, Cyprus. Bedesten, interior, architectural fragments revealed by excavation in southern aisles, as restored and conserved in 2010.</p>
Matrix multiplication software and results bundle for paper "Tuning and optimization for a variety of many-core architectures without changing a single line of implementation code using the Alpaka library" for P^3MA submission
<p>This is the archive containing the matrix multiplication software and the results of the publication "<em>Tuning and optimization for a variety of many-core architectures without changing a single line of implementation code using the Alpaka library</em>" submitted to the P^3MA workshop 2017.</p> <p><strong>The archive has the following content:</strong></p> <ul> <li>Source code for the (tiled) matrix multiplication in "src": <ul> <li>regular version in "src/matmul": <ul> <li>Remote: https://github.com/theZiz/matmul.git (copy will be removed)</li> <li>Branch: topic-compatible-alpaka-0-1-0</li> <li>Commit: a63ba4810d6bfcca62c68dd57408af15028e78a3</li> </ul> </li> <li>forked version for XL in "src/matmul": <ul> <li>Remote: https://github.com/theZiz/matmul.git (copy will be removed)</li> <li>Branch: topic-xl-workaround</li> <li>Commit: 1fee028eccb8cf7b677e8071233e08aa9f81846a</li> </ul> </li> </ul> </li> <li>The compiled binaries and the results of the tuning and scaling runs are in "runs" in sub folders for each type of run and architectures.</li> </ul>
Smart 3D super-resolution microscopy reveals the architecture of the RNA scaffold in a nuclear body
<p>Data associated with the article "Smart 3D super-resolution microscopy reveals the architecture of the RNA scaffold in a nuclear body". A README.txt is provided that explains the data provided.</p>
Survey on the implementation of digital technology architecture in teacher training
<p>This file contains the results of a detailed survey exploring the implementation of digital technology architecture in teacher education. The survey was designed to assess how educational institutions are integrating advanced digital tools into their professional development programmes and the impact this has on teaching and learning. The data collected provides valuable insight into the effectiveness of these technologies in the educational environment, areas of success and challenges that still need to be addressed to optimise educator training in the digital age.</p>
Mesh dataset for the paper "Bending-Reinforced Grid Shells for Free-form Architectural Surfaces"
<p>If using this dataset, please cite the paper: </p> <p>Laccone, F., Pietroni, N., Cignoni, P., Malomo, L.: Bending-Reinforced Grid Shells for Free-form Architectural Surfaces. Computer-Aided Design. Available online 23 December 2023, 103670.</p> <p>https://doi.org/10.1016/j.cad.2023.103670</p>
Dataset and Analysis Scripts for Survey "Understanding Security Tactics in Microservice APIs using Annotated Software Architecture Decomposition Models -- A Controlled Experiment"
<pre>Dataset, R-Scripts and questionnaire templates for our survey <em>Understanding Security Tactics in Microservice APIs using Annotated Software Architecture Decomposition Models -- A Controlled Experiment.</em></pre>
Genetic Architecture Reconciles Linkage and Association Studies of Complex Traits
<p>This (zipped) folder contains 3 sub-folders:</p> <p>#**********************************************************************************************************<br>The "bin" folder contains fuctions and gentic maps needed for analyes<br>bin \<br> predLink.R - function to predict linkage <br> sibREML_v0.1.1.R - function to run SibREML<br> sim-sib-array.R - script to simulate sib-pairs from parental haplotypes<br> Summarised_genetic_map_bcf.txt - genetic map per 0.5-cM long segments, based on map from bcftools <br> (BCFtools: https://samtools.github.io/bcftools/bcftools.html)<br> Summarised_genetic_map_OMNI.txt - genetic map per 0.5-cM long segments, based on OMNI map <br> (https://github.com/joepickrell/1000-genomes-genetic-maps/tree/master/interpolated_OMNI)<br>#**********************************************************************************************************</p> <p> </p> <p>#**********************************************************************************************************<br>The "SIM" folder contains the simulation pipeline (scripts 01-15) as well as IBD sharing and simulated phenotypes for Simulated sib-pairs.<br>SIM \<br> 01_sim-sib-array.sh *pre-run*<br> 02_bed_recode_bcf_map.sh *pre-run*<br> 03_make_merlin.R *pre-run*<br> 04_error_merlin.sh *pre-run*<br> 05_merlin_IBD.sh *pre-run*<br> 06_sample_causal_snps.R *pre-run*<br> 07_simulate_pheno.sh *pre-run*<br> 08_bhat_gwas.R *can be run using provided data* <br> 09_Linkage_VH.R *can be run using provided data* <br> 10_predLink.R *can be run using provided data*<br> 11_phi_hat.R *can be run using provided data*<br> 12_IBD_Mb.R *can be run using provided data*<br> 13_IBD_cM_recombrate_stratified.R *can be run using provided data*<br> 14_SibREML.R *can be run using provided data*<br> 15_SibREML_stratified_Q4.R *can be run using provided data*<br> causal_snps \ *provided causal SNPs*<br> IBD_results \ *provided IBD-probabilities for 1000 simulated sib-pairs*<br> Linkage_VH_results \ <br> pheno \ *provided simulated phenotypes (h2=1) for 8 genetic architectures*<br> Phi_hat_results.txt<br> predicted \<br> README<br> SibREML_results.txt<br> SibREML_stratified_Q4.txt</p> <p>The data can be used to run Linkage analysis, predict linkage, estimate phi_hat, <br>as well as estimate non-stratified and recombination rate stratified sib-heritability (h2_FS and c).<br>The README is provided within the folder. <br>#**********************************************************************************************************</p> <p> </p> <p>#**********************************************************************************************************<br>The "HT_BMI" folder contains data and scripts to predict linkage and estimate phi_hat for height and BMI.<br>HT_BMI \<br> 01_predLink_HT_BMI.R<br> 02_phi_hat_HT_BMI.R<br> gws_sumstats \ *provided summary GWAS summary statistics to predict linkage for height and BMI*<br> Linkage_results \ *provided linkage meta-analysis results for height and BMI from this study*<br> Phi_hat_results_HT_BMI.txt<br> PREDLINK_bmi.txt<br> PREDLINK_height.txt<br> README<br>The README is provided within the folder.<br>#**********************************************************************************************************</p> <p><strong> </strong></p>
Genetic architecture of immune cell DNA methylation in the rhesus macaque
<p><strong>Complete model outputs from rhesus macaque (<em>Macaca mulatta</em>) whole blood meQTL and eQTL analyses in article, "Genetic architecture of immune cell DNA methylation in the rhesus macaque". </strong></p> <p><strong><em>cis</em> meQTL model output (SNP-CpG associations):</strong> </p> <ol> <li>IMAGE_573_meqtl_model_res_wPVE.txt: <ul> <li>Model results from IMAGE meQTL mapping including all genome, chromatin state annotations, and PVE estimates</li> </ul> </li> <li>pqlseq_allimagesnps_res_converged_wpve.txt: <ul> <li>Model results from PQLseq meQTL mapping including PVE estimates </li> </ul> </li> </ol> <p><strong><em>cis</em> eQTL model output (SNP-gene associations): </strong></p> <ol> <li>eqtl_res_sva5_gemma_172samples_qvalue.txt: <ul> <li>Model results from GEMMA eQTL mapping </li> </ul> </li> </ol> <p> </p>
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.