Results 161 to 170 of about 1,167,728 (343)
A Competing Risk Analysis of Executions and Cancellations in a Limit Order Market [PDF]
The competing risks technique is applied to the analysis of times to execution and cancellation of limit orders submitted on an electronic trading platform.
Bidisha Chakrabarty +3 more
core
Reevaluating the Activity of ZIF‐8 Based FeNCs for Electrochemical Ammonia Production
Though receiving much attention, the field of electrochemical nitrogen reduction reaction (eNRR) to ammonia is marked by doubts about whether this reaction is possible in aqueous media. This work sheds light on this question for iron single‐atom on N‐doped carbon (FeNC) catalysts—a class of well‐known catalysts that is also worth testing for the sister
Caroline Schneider +6 more
wiley +1 more source
A solvent‐free mechanochemistry‐enabled supramolecular engineering strategy is developed to directly synthesize covalent‐interconnected two‐dimensional atomic‐layered carbon nitride nanosheets photocatalyst, bypassing conventional top‐down exfoliation requirements.
Fanglei Yao +7 more
wiley +1 more source
Analyzing Competing Risk Data Using the R timereg Package [PDF]
In this paper we describe flexible competing risks regression models using the comp.risk() function available in the timereg package for R based on Scheike et al. (2008).
Mei-Jie Zhang, Thomas H. Scheike
core +1 more source
This review highlights recent advances in label‐free optical biosensors based on 2D materials and rationally designed mixed‐dimensional nanohybrids, emphasizing their synergistic effects and novel functionalities. It also discusses multifunctional sensing platforms and the integration of machine learning for intelligent data analysis.
Xinyi Li, Yonghao Fu, Yuehe Lin, Dan Du
wiley +1 more source
Competing risks analysis for discrete time‐to‐event data [PDF]
Matthias Schmid, Moritz Berger
openalex +1 more source
Non‐covalent protein–protein interactions mediated by SH3, PDZ, or GBD domains enable the self‐assembly of stable and biocatalytically active hydrogel materials. These soft materials can be processed into monodisperse foams that, once dried, exhibit enhanced mechanical stability and activity and are easily integrated into microstructured flow ...
Julian S. Hertel +5 more
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Electrically Tunable On‐Chip Topological Photonics with Integrated Carbon Nanotubes
This work demonstrates electrically tunable on‐chip topological THz devices by integrating 2D carbon nanotube (CNT) sheets with valley‐Hall photonic crystals, enabling broadband transmission modulation (71% modulation depth) and tunable narrowband filtering (0.54 GHz shift) through electrically induced thermal tuning. This advancement paves the way for
Jifan Yin +7 more
wiley +1 more source

