Results 91 to 100 of about 3,322,529 (303)
Artificial molecular machines and motors—Design and control of nanoscale motion
Molecules are constantly moving because of thermal fluctuations, but random motion alone cannot be exploited to perform directional tasks. Artificial molecular machines use chemical, electrical, or light energy to bias this motion. Molecular shuttles, rotary motors, and supramolecular pumps illustrate how nanoscale movement can be controlled and ...
Leonardo Andreoni, Alberto Credi
wiley +1 more source
Optimal Dimensionality Reduction using Conditional Variational AutoEncoder
The benefits of using Deep Learning techniques to enhance side-channel attacks performances have been demonstrated over recent years. Most of the work carried out since then focuses on discriminative models.
Sana Boussam +4 more
doaj +1 more source
Dimensionality Reduction by Weighted Connections between Neighborhoods
Dimensionality reduction is the transformation of high-dimensional data into a meaningful representation of reduced dimensionality. This paper introduces a dimensionality reduction technique by weighted connections between neighborhoods to improve K ...
Fuding Xie, Yutao Fan, Ming Zhou
doaj +1 more source
Dimensionality Reduction via Multiple Locality-Constrained Graph Optimization
In recent years, graph-based dimensionality reduction methods became increasingly more significant since they have been successfully applied in various computer vision and machine learning problems.
Caixia Zheng +6 more
doaj +1 more source
Robust dimensionality reduction for interferometric imaging of Cygnus A [PDF]
Extremely high data rates expected in next-generation radio interferometers necessitate a fast and robust way to process measurements in a big data context.
Thiran, Jean-Philippe +3 more
core +1 more source
Hijacking emergency granulopoiesis: Neutrophil ontogeny and reprogramming in cancer
Neutrophils are highly plastic innate immune cells; their functions in cancer extend beyond the tumour microenvironment. This Review summarises current understanding of neutrophil maturation and heterogeneity and highlights tumour‐induced granulopoiesis as a systemic programme that expands immature, immunosuppressive neutrophils via tumour‐derived ...
Gabriela Marinescu, Yi Feng
wiley +1 more source
Dimensionality Reduction Algorithms on High Dimensional Datasets
Classification problem especially for high dimensional datasets have attracted many researchers in order to find efficient approaches to address them. However, the classification problem has become very complicatedespecially when the number of possible ...
Iwan Syarif
doaj +3 more sources
We identify USP29 as the only DUB mirroring CA9 expression, a marker of hypoxia and HIF pathway activation associated with PCA aggressiveness. USP29 stabilizes HIF‐1α and HIF‐2α via a noncanonical mechanism that is independent of PHD/pVHL activity yet relies on proteasomal regulation, establishing USP29 as a previously unrecognized regulator of hypoxic
Amelie S Schober +16 more
wiley +1 more source
The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka +9 more
wiley +1 more source
Dimensionality reduction method for hyperspectral image analysis based on rough set theory
High-dimensional features often cause computational complexity and dimensionality curse. Feature selection and feature extraction are the two mainstream methods for dimensionality reduction.
Zhenhua Wang +5 more
doaj +1 more source

