Results 221 to 230 of about 60,715 (277)

Modeling the Physical Characteristics of Ultrasound Pretreated Dialium guineense Whole Fruits Using Neural Network Pattern Recognition Model

AgriFood: Journal of Agricultural Products for Food, EarlyView.
The study of Physical characteristics of agricultural materials is necessary for the design of processes and machines for food production. Length, width, thickness, sphericity, unit mass, and aspect ratio were the physical characteristics of ultrasound pretreated Dialium guineense whole fruits subjected to Neural network modeling.
Mfrekemfon Akpan, Uduak George, Okon Esua   +2 more
wiley   +1 more source

Slow-wave sleep and REM sleep differentially contribute to memory representational transformation. [PDF]

Commun Biol
Liu J, Chen D, Xia T, Zeng S, Xue G, Hu X.   +5 more
europepmc   +1 more source

Regional Differences in U.S. Consumer Preferences for Native Woody Shrubs With Varying Aesthetic Characteristics

Agribusiness, EarlyView.
ABSTRACT Native plants offer a variety of aesthetic (e.g., fall colour, fruit, flowers) and functional benefits (e.g., pollinator friendly, wildlife friendly, water management). How these benefits influence consumer choice and perceived value of native versus introduced plants is not well understood.
Alicia Rihn, Ariana P. Torres, Sue Barton, Bridget K. Behe   +3 more
wiley   +1 more source

Successful treatment of glaucoma in Sturge-Weber syndrome using PreserFlo™ microshunt with intraluminal stenting: a case report. [PDF]

Am J Ophthalmol Case Rep
Inami H, Tomita R, Yuki K.
europepmc   +1 more source

Which Method Best Predicts Postoperative Complications: Deep Learning, Machine Learning, or Conventional Logistic Regression?

Annals of Gastroenterological Surgery, EarlyView.
Deep learning has shown promise in predicting postoperative complications, particularly when using image or time‐series data. However, on tabular clinical data such as the NCD, it often underperforms compared to conventional machine learning. Integrating multimodal data may enhance predictive accuracy and interpretability in surgical care.
Ryosuke Fukuyo, Masanori Tokunaga, Hiroyuki Yamamoto, Hideki Ueno, Yusuke Kinugasa   +4 more
wiley   +1 more source

Retinal Vascular Density and Vessel Diameter in Sturge-Weber Syndrome Assessed by OCT-Angiography. [PDF]

J Clin Med
Longo R, Gusson E, Lorenzetto E, Polinelli L, Malvasi M, Panozzo G, Marchini G.   +6 more
europepmc   +1 more source

Enhancing Sensitivity across Scales with Highly Sensitive Hall Effect‐Based Auxetic Tactile Sensors

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Herein, a tactile sensor based on hall‐effect sensors with an auxetic structure, called Hall effect‐based auxetic tactile sensor (HEATS), is proposed. The change in magnetism resulting from the deformation of the auxetic structure is utilized for sensing.
Youngheon Yun, Dongchan Lee, Soyeon Lee, Salvador Pané, Josep Puigmartí‐Luis, Sungwoo Chun, Bumjin Jang   +6 more
wiley   +1 more source

Gaussian Mixture Model‐Based Data Association Incorporating a Deep Learning Network for Multivehicle Tracking and Detection in Autonomous Driving Systems

Advanced Intelligent Systems, EarlyView.
This study introduces a real‐time light detection and ranging‐camera fusion framework for vehicle detection and tracking. Using a Gaussian mixture model‐based association and improved affinity metrics, the method enhances tracking reliability in dynamic conditions.
Muhammad Adeel Altaf, Min Young Kim
wiley   +1 more source

Acoustic Identity: Linking Signature Whistles and Visual Identification in a Threatened Dolphin Population. [PDF]

Animals (Basel)
Crittenden A, Robb K, Erbe C.
europepmc   +1 more source

Multiobjective Environmental Cleanup with Autonomous Surface Vehicle Fleets Using Multitask Multiagent Deep Reinforcement Learning

Advanced Intelligent Systems, EarlyView.
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck, Samuel Yanes, Manuel Perales, Daniel Gutiérrez, Sergio Toral   +4 more
wiley   +1 more source