Results 81 to 90 of about 285,439 (304)

Extracellular Vesicles Modulation by an Adiponectin Receptor Agonist Provides Cardioprotection for Myocardial Ischemic Injury

open access: yesAdvanced Healthcare Materials, EarlyView.
This study demonstrates that ALY688, a drug mimicking the heart‐protective hormone adiponectin, reduces myocardial ischemia injury. ALY688 increases the production of extracellular vesicles, which carry protective cargo including adiponectin itself.
Jialing Tang   +13 more
wiley   +1 more source

Rapid and precise multifocal cutaneous tumor margin assessment using fluorescence lifetime detection and machine learning

open access: yesAPL Photonics
The precise determination of surgical margins is essential for the management of multifocal cutaneous cancers, including extramammary Paget’s disease.
Wenhua Su   +9 more
doaj   +1 more source

Learning curves for Soft Margin Classifiers

open access: yes, 2002
Typical learning curves for Soft Margin Classifiers (SMCs) learning both realizable and unrealizable tasks are determined using the tools of Statistical Mechanics.
Gordon, Mirta B.   +1 more
core   +1 more source

Instance and feature weighted k-nearest-neighbors algorithm [PDF]

open access: yes, 2016
We present a novel method that aims at providing a more stable selection of feature subsets when variations in the training process occur. This is accomplished by using an instance-weighting process -assigning different importances to instances as a ...
Belanche Muñoz, Luis Antonio   +1 more
core  

Enhanced Endoscopic Internal Drainage of Gastric Abscess Through Additively Manufactured Stents

open access: yesAdvanced Healthcare Materials, EarlyView.
Postoperative gastric leaks are often treated with off‐label biliary double‐pigtail stents, yet conventional extruded designs are not optimized for leak anatomy, can migrate, and may limit abscess evacuation. PETALS is introduced to optimize transmural drainage geometry and enable patient‐specific 3D‐printable stents.
Parima Phowarasoontorn   +14 more
wiley   +1 more source

Smart Information Retrieval: Domain Knowledge Centric Optimization Approach

open access: yesIEEE Access, 2019
In the age of the Internet of Things, online data have witnessed a significant growth in terms of volume and diversity, and research into information retrieval has become one of the important research themes in the Internet-oriented data science research.
Abduladem Aljamel   +4 more
doaj   +1 more source

Estimating weather margin seasonality in shipping using machine learning

open access: yes, 2021
Accurate predictions of fuel consumption are an essential tool in the pricing of forward cargo contracts. This thesis develops a predictive model for fuel consumption using noon report data from Handysize and Supramax vessels. In the process, we employ a wide selection of machine learning algorithms, including decision trees, shrinkage models, and an ...
Nilsson, Joakim, Nilsson, Marcus
openaire   +1 more source

Microengineered Gradient Hydrogels for Mechanobiology

open access: yesAdvanced Healthcare Materials, EarlyView.
Gradient hydrogels are used to mimic the mechanical heterogeneity in native tissues, offering powerful in vitro platforms to study cell‐material interactions in diverse pathophysiological contexts. Here, we present a comprehensive review of the design and experimental considerations for stiffness gradient hydrogels, discussing exemplary achievements ...
Shin Wei Chong   +4 more
wiley   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

open access: yesAdvanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu   +3 more
wiley   +1 more source

Exploring Kernel Machines and Support Vector Machines: Principles, Techniques, and Future Directions

open access: yesMathematics
The kernel method is a tool that converts data to a kernel space where operation can be performed. When converted to a high-dimensional feature space by using kernel functions, the data samples are more likely to be linearly separable.
Ke-Lin Du   +4 more
doaj   +1 more source

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