Results 151 to 160 of about 296,058 (324)
Biochemical Studies on the Lipids of Turbo cornutus. I
Akira Hayashi+2 more
openalex +2 more sources
The Fluctuating Forces Appropriate for the Calculation of Discrete Frequency Noise Generation in Subsonic Turbo-Machines [PDF]
Sanford Fleeter
openalex +1 more source
Approximate Theoretical Analysis of the Cycle for Pulse-Type Turbo Charged Two-Stroke Diesel Engine
Masashi Nagai, Tadataka Asada
openalex +2 more sources
Magnetic Resonance Imaging for Dental Pulp Assessment: A Comprehensive Review
ABSTRACT Magnetic resonance imaging (MRI) has recently emerged as a promising modality for dental applications, offering radiation‐free imaging with superior soft tissue visualization capabilities compared to x‐ray‐based techniques such as spiral or cone beam computed tomography (CBCT).
Bing Han+5 more
wiley +1 more source
Evaluation of Software‐Optimized Protocols for Acoustic Noise Reduction During Brain MRI at 7 Tesla
ABSTRACT Background MR‐generated acoustic noise may be particularly concerning at 7‐Tesla (T) systems. Noise levels can be reduced by altering gradient output using software optimization. However, such alterations might influence image quality or prolong scan times, and these optimizations have not been well characterized.
Anton Glans+7 more
wiley +1 more source
Service Experience with MITSUI B & W Turbo-charged Two Stroke Engines
Masami Fukuyama
openalex +2 more sources
RWMODEL: A program in Turbo Pascal for simulating predictions based on the Rescorla-Wagner model of classical conditioning [PDF]
Harald Lachnit+3 more
openalex +1 more source
ABSTRACT Background Kidney transplant (KTx) function assessment is important in treatment planning, while conventional MRI markers lack sensitivity for KTx function. Mechanical kidney properties may serve as MRI markers for renal allograft function. Hypothesis To determine if multifrequency MR elastography (MRE) is associated with KTx function.
Stephan Rodrigo Marticorena Garcia+4 more
wiley +1 more source
Turbo-ICL: In-Context Learning-Based Turbo Equalization
This paper introduces a novel in-context learning (ICL) framework, inspired by large language models (LLMs), for soft-input soft-output channel equalization in coded multiple-input multiple-output (MIMO) systems. The proposed approach learns to infer posterior symbol distributions directly from a prompt of pilot signals and decoder feedback.
Song, Zihang+3 more
openaire +2 more sources