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Dataset results
57 results for “novel hybrid”
MuSHRoom: Multi-Sensor Hybrid Room Dataset for Joint 3D Reconstruction and Novel View Synthesis (iPhone Part 3)
<p>Metaverse technologies demand accurate, real-time, and immersive modeling on consumer-grade hardware for both non-human perception (e.g., drone/robot/autonomous car navigation) and immersive technologies like AR/VR, requiring both structural accuracy and photorealism. However, there exists a knowledge gap in how to apply geometric reconstruction and photorealism modeling (novel view synthesis) in a unified framework.</p><p>To address this gap and promote the development of robust and immersive modeling and rendering with consumer-grade devices, first, we propose a real-world Multi-Sensor Hybrid Room Dataset (MuSHRoom). Our dataset presents exciting challenges and requires state-of-the-art methods to be cost-effective, robust to noisy data and devices, and can jointly learn 3D reconstruction and novel view synthesis, instead of treating them as separate tasks, making them ideal for real-world applications. Second, we benchmark several famous pipelines on our dataset for joint 3D mesh reconstruction and novel view synthesis. Finally, in order to further improve the overall performance, we propose a new method that achieves a good trade-off between the two tasks. Our dataset and benchmark show great potential in promoting the improvements for fusing 3D reconstruction and high-quality rendering in a robust and computationally efficient end-to-end fashion.</p>
Figure 5 from: Abdullah AH, Alarareh AK, Al-Sha'er MA, Habashneh AY, Awwadi FF, Bardaweel SK (2024) Docking, synthesis, and anticancer assessment of novel quinoline-amidrazone hybrids. Pharmacia 71: 1-12. https://doi.org/10.3897/pharmacia.71.e117192
Figure 5 X-ray structure of 10b.
Scheme 1 from: Abdullah AH, Alarareh AK, Al-Sha'er MA, Habashneh AY, Awwadi FF, Bardaweel SK (2024) Docking, synthesis, and anticancer assessment of novel quinoline-amidrazone hybrids. Pharmacia 71: 1-12. https://doi.org/10.3897/pharmacia.71.e117192
Scheme 1 Synthetic route to compound 8.
Scheme 2 from: Abdullah AH, Alarareh AK, Al-Sha'er MA, Habashneh AY, Awwadi FF, Bardaweel SK (2024) Docking, synthesis, and anticancer assessment of novel quinoline-amidrazone hybrids. Pharmacia 71: 1-12. https://doi.org/10.3897/pharmacia.71.e117192
Scheme 2 Synthetic route for compounds 10a–l.
Figure 3 from: Abdullah AH, Alarareh AK, Al-Sha'er MA, Habashneh AY, Awwadi FF, Bardaweel SK (2024) Docking, synthesis, and anticancer assessment of novel quinoline-amidrazone hybrids. Pharmacia 71: 1-12. https://doi.org/10.3897/pharmacia.71.e117192
Figure 3 The Amidrazones structures of antitumor compounds 1–5.
Figure 6 from: Abdullah AH, Alarareh AK, Al-Sha'er MA, Habashneh AY, Awwadi FF, Bardaweel SK (2024) Docking, synthesis, and anticancer assessment of novel quinoline-amidrazone hybrids. Pharmacia 71: 1-12. https://doi.org/10.3897/pharmacia.71.e117192
Figure 6 Layer structure of 10b (top) and the three-dimensional structure of 10b (bottom).
Figure 2 from: Abdullah AH, Alarareh AK, Al-Sha'er MA, Habashneh AY, Awwadi FF, Bardaweel SK (2024) Docking, synthesis, and anticancer assessment of novel quinoline-amidrazone hybrids. Pharmacia 71: 1-12. https://doi.org/10.3897/pharmacia.71.e117192
Figure 2 Anticancer drugs with their structures.
Figure 8 from: Abdullah AH, Alarareh AK, Al-Sha'er MA, Habashneh AY, Awwadi FF, Bardaweel SK (2024) Docking, synthesis, and anticancer assessment of novel quinoline-amidrazone hybrids. Pharmacia 71: 1-12. https://doi.org/10.3897/pharmacia.71.e117192
Figure 8 ADME analysis of synthetic amidrazone structures (blue dot).
Figure 1 from: Abdullah AH, Alarareh AK, Al-Sha'er MA, Habashneh AY, Awwadi FF, Bardaweel SK (2024) Docking, synthesis, and anticancer assessment of novel quinoline-amidrazone hybrids. Pharmacia 71: 1-12. https://doi.org/10.3897/pharmacia.71.e117192
Figure 1 Structure representation of quinoline-based natural alkaloids.
Dataset for a Novel Hybrid Cryptography Algorithm for RDP Security
<p>The dataset consists of 95 rows and 8 columns. Each row contains information about an alphanumeric character (e.g. (A-Z), (a-z), (0-9), punctuation, and all special characters). The columns were created based on the steps of the proposed hybrid cryptography algorithm. The features include ASCII_Equivalent, Hex_Values, S_box_Conversion, Decimal_Values_of_S_box, RSA_Encrypted_Values, Replaced_Values, Group, and Class, with Class being the dependent variable. The characters in the Replaced_Values column are assigned a class of 0 or 1 depending on the presence of uppercase or lowercase letters. The dataset was generated using small RSA keys for convenience.</p>
Eradicating Barrett's Esophagus Using Radiofrequency Ablation or a Novel Hybrid Argon Plasma Coagulation Technique
ClinicalTrials.gov study NCT03621319. IPD Sharing: NO. Countries: 1. Publications: 0.
Stochastic gain of susceptibility suggests a novel mechanism of resistance to hybrid dysgenesis in Drosophila virilis
GEO Series GSE108298. Drosophila virilis. 19 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Novel Lung Cancer-Related Genes Identified by a Non-Gapped Array-Comparative Genomic Hybridization Microarray in Asian and Caucasian Populations
GEO Series GSE21276. Homo sapiens. 60 samples. Type: Genome variation profiling by genome tiling array.
Novel Self-Adhesive Composite Hybrid Versus Conventional Composite in Restoration of Carious Primary Teeth.
ClinicalTrials.gov study NCT05173753. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
A novel hybrid kinase is essential for regulating the σB-mediated stress response of Bacillus cereus.
GEO Series GSE14589. Bacillus cereus ATCC 14579. 4 samples. Type: Expression profiling by array.
Novel gene discovery in up to 10 ETEC strains and production of species microarray. Discovery of conserved and unique ETEC genes by comparative genome hybridization studies.
GEO Series GSE25601. Escherichia coli. 216 samples. Type: Genome variation profiling by array.
MuSHRoom: Multi-Sensor Hybrid Room Dataset for Joint 3D Reconstruction and Novel View Synthesis (Mesh)
<p>Metaverse technologies demand accurate, real-time, and immersive modeling on consumer-grade hardware for both non-human perception (e.g., drone/robot/autonomous car navigation) and immersive technologies like AR/VR, requiring both structural accuracy and photorealism. However, there exists a knowledge gap in how to apply geometric reconstruction and photorealism modeling (novel view synthesis) in a unified framework.</p><p>To address this gap and promote the development of robust and immersive modeling and rendering with consumer-grade devices, first, we propose a real-world Multi-Sensor Hybrid Room Dataset (MuSHRoom). Our dataset presents exciting challenges and requires state-of-the-art methods to be cost-effective, robust to noisy data and devices, and can jointly learn 3D reconstruction and novel view synthesis, instead of treating them as separate tasks, making them ideal for real-world applications. Second, we benchmark several famous pipelines on our dataset for joint 3D mesh reconstruction and novel view synthesis. Finally, in order to further improve the overall performance, we propose a new method that achieves a good trade-off between the two tasks. Our dataset and benchmark show great potential in promoting the improvements for fusing 3D reconstruction and high-quality rendering in a robust and computationally efficient end-to-end fashion.</p>
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
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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.