Results 151 to 160 of about 31,081 (304)

Conductive Additives for Next‐Generation Batteries: Emphasizing the Potential of Bio‐Derived 3D Carbon Architectures at Electrode–Electrolyte Interfaces

open access: yesAdvanced Materials Interfaces, EarlyView.
3D conductive frameworks can maintain continuous electron transport, mechanical stability, and interfacial integrity, helping next‐generation batteries operate more efficiently. This Review examines their relevance to Si anodes, all‐solid‐state batteries, and dry‐processed electrodes, and highlights bio‐derived carbons as sustainable, structurally ...
SeoYoung Ha   +5 more
wiley   +1 more source

Musical Word Embedding for Music Tagging and Retrieval

open access: yes
Word embedding has become an essential means for text-based information retrieval. Typically, word embeddings are learned from large quantities of general and unstructured text data.
Doh, SeungHeon   +3 more
core   +2 more sources

BioEISense: A Microfluidic Platform for Real‐Time Monitoring of Staphylococcus aureus Biofilm Formation and the Efficacy of Antibiofilm Agents

open access: yesAdvanced Materials Interfaces, EarlyView.
BioEISense is a microfluidic device with integrated impedance sensors, for real‐time, label‐free monitoring of S. aureus biofilms. In this study, the biofilm culture conditions were optimized to support sensitive and reproducible detection of biofilm formation and eradication under dynamic flow‐through conditions. The system was also validated for both
Jéssica Amorim   +6 more
wiley   +1 more source

Interface‐Engineered Binary Framework Composites: Advancing Porous Materials for Precision Medicine

open access: yesAdvanced Materials Interfaces, EarlyView.
Binary framework composites integrate two complementary porous architectures into a unified platform, enabling multifunctional design, enhanced structural tunability, and improved physicochemical performance. By combining high surface area, ordered porosity, interfacial synergy, and versatile functionalization, these hybrid materials offer new ...
Navid Rabiee   +3 more
wiley   +1 more source

Comparative Study for Sentiment Analysis of Financial Tweets with Deep Learning Methods

open access: yesApplied Sciences
Nowadays, Twitter is one of the most popular social networking services. People post messages called “tweets”, which may contain photos, videos, links and text. With the vast amount of interaction on Twitter, due to its popularity, analyzing Twitter data
Erkut Memiş   +4 more
doaj   +1 more source

Recent Advances of Slip Sensors for Smart Robotics

open access: yesAdvanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang   +8 more
wiley   +1 more source

Deterministic Compression of Word Embeddings

open access: yesIEEE Access
Word embeddings are an indispensable technology in the field of artificial intelligence, particularly when working with natural language processing models. To further enhance their usability, several studies have tackled the compression of word embeddings while maintaining task performance.
Yuki Nakamura   +3 more
openaire   +2 more sources

Liquid Metal‐Based Stretchable Strain Sensor for Fruit Growth Monitoring

open access: yesAdvanced Materials Technologies, EarlyView.
Schematic overview of the fruit growth sensor development workflow, including sensor fabrication by injection molding, electromechanical and environmental characterization, mechanical stability testing, electronic readout integration, and outdoor field validation for monitoring of fruit growth under practical orchard conditions.
Asad Ullah   +7 more
wiley   +1 more source

Learning Sentiment-Specific Word Embedding via Global Sentiment Representation

open access: yes, 2018
Context-based word embedding learning approaches can model rich semantic and syntactic information. However, it is problematic for sentiment analysis because the words with similar contexts but opposite sentiment polarities, such as good and bad, are ...
Wang, Weiping   +4 more
core   +1 more source

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