Results 141 to 150 of about 188,828 (316)
Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira +13 more
wiley +1 more source
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu +5 more
wiley +1 more source
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo +5 more
wiley +1 more source
Parity-violating excitation of the Δ(1232): hadron structure and new physics [PDF]
Nimai C. Mukhopadhyay +4 more
openalex +1 more source
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley +1 more source
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley +1 more source
Status of the Jefferson Lab Polarized Beam Physics Program and Preparations for Upcoming Parity Experiments [PDF]
Joseph Grames
openalex +1 more source
Respiratory Involvement in HIST1H1E‐Related Rahman Syndrome: A Case of Severe Mixed Apnea
ABSTRACT Rahman syndrome (HIST1H1E‐related neurodevelopmental syndrome, OMIM #617537) is a rare autosomal‐dominant condition caused by truncating variants in the C‐terminal domain of the HIST1H1E gene. It is characterized by macrocephaly, hypotonia, craniofacial anomalies, and multisystem anomalies.
Nada Barakat +4 more
wiley +1 more source
Erratum: Physical Realization of the Parity Anomaly in Condensed Matter Physics [Phys. Rev. Lett. 57, 2967 (2986)] [PDF]
Eduardo Fradkin +2 more
openalex +1 more source
Confessions of a Poverty Researcher: My Journey Through the Foothills of Scholarship
ABSTRACT This paper describes the key events, experiences and ideas that influenced the author's career as a poverty researcher. He describes how his early disillusion with economics was replaced by a spark of interest in social issues and how his migration from the UK to Australia in the mid‐1970s provided the impetus to begin what became a lifetime ...
Peter Saunders
wiley +1 more source

