Results 141 to 150 of about 1,144,592 (210)
Responsive Materials, EarlyView.Carbon dots are emerging as versatile electrochemiluminescent nanomaterials whose structure, surface states, and interfacial design jointly determine ECL pathways and performance. This review highlights how mechanistic understanding and materials engineering enable programmable CD‐ECL systems for bioanalysis, imaging, and future intelligent analytical ...
Yuhan Zhao, Zixuan Chen, Jun‐Jie Zhu
wiley +1 more source
Graceful game on some graph classes
A graceful labeling of a graph G with m edges consists in labeling the vertices of G with distinct integers from 0 to m such that each edge is uniquely identified by the absolute difference of the labels of its endpoints.
Deise L. de Oliveira +4 more
core +1 more source
Sustainable Development, EarlyView.ABSTRACT The uneven labour‐market consequences of climate transition are now well established; the unresolved question is how decarbonisation is converted into unequal worker trajectories and why policies framed as inclusive repeatedly reach workers unevenly. This critical narrative review, supported by systematic search procedures, synthesises a final
Jacob Kwakye
wiley +1 more source
The role of the host—Neutrophil biology
Periodontology 2000, EarlyView., 2023 Abstract Neutrophilic polymorphonuclear leukocytes (neutrophils) are myeloid cells packed with lysosomal granules (hence also called granulocytes) that contain a formidable antimicrobial arsenal. They are terminally differentiated cells that play a critical role in acute and chronic inflammation, as well as in the resolution of inflammation and wound ...
Iain L. C. Chapple +4 more
wiley +1 more source
Graceful and residually graceful graphs
, 2006 Graph labeling is an assignment of integers to the vertices and/or edges of a graph, subject to certain conditions. The first type of labeling was introduced by Rosa as early as 1967. It is called -valuation and, more popularly known as graceful labeling
Tan, Michele Go
core
Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning
SmartBot, EarlyView.Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo +2 more
wiley +1 more source
Super Fibonacci Graceful Labeling of Some Special Class of Graphs
, 2014 : A Smarandache-Fibonacci Triple is a sequence S(n), n ≥ 0 such that S(n) = S(n − 1) + S(n − 2), where S(n) is the Smarandache function for integers n ≥ 0. Certainly, it is a generalization of Fibonacci sequence. A Fibonacci graceful labeling and a super
S. Navaneethakrishnan +2 more
core
Spatial Statistics for Screening Molecular Structures
Small, EarlyView.Deep architectures for materials discovery demand vast training data and obscure the structure‐property link. This review shows how spatial statistics offer a physically grounded alternative: voxelized fields and two‐point correlations, compressed by principal component analysis, yield convex, interpretable descriptors. Lean surrogates then reach sub‐2%
Pranoy Ray, Surya R. Kalidindi
wiley +1 more source
Towards the Graceful Tree Conjecture: A Survey
A graceful labelling of an undirected graph G with n edges is a one-to-one function from the set of vertices of G to the set {0, 1, 2,...,n} such that the induced edge labels are all distinct. An induced edge label is the absolute value of the difference
Brankovic, Ljiljana +3 more
core
Small Methods, EarlyView.This comprehensive review delivers an engineering‐centric analysis of microfluidic molecular diagnostic chips, breaking them down into foundational modules from fluid manipulation to bio‐sensing. Beyond chip design, it evaluates sample‐to‐answer integration strategies and commercial readiness levels.
Donghoon Koo +7 more
wiley +1 more source