Results 71 to 80 of about 242,529 (275)

Retractions in rheumatology: trends, causes, and implications for research integrity

Arthritis Care &Research, Accepted Article.
Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley   +1 more source

A survey of the impact of self-supervised pretraining for diagnostic tasks in medical X-ray, CT, MRI, and ultrasound

BMC Medical Imaging
Self-supervised pretraining has been observed to be effective at improving feature representations for transfer learning, leveraging large amounts of unlabelled data.
Blake VanBerlo, Jesse Hoey, Alexander Wong   +2 more
doaj   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

Advanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic Junior, Nicholas Sandor, Alexander Hart, Yuki Haruta, Magdalena Bazalova‐Carter, Marcos J. L. Santos, Makhsud I. Saidaminov   +8 more
wiley   +1 more source

Patterning the Void: Combining L‐Systems with Archimedean Tessellations as a Perspective for Tissue Engineering Scaffolds

Advanced Functional Materials, EarlyView.
This study introduces a novel multi‐scale scaffold design using L‐fractals arranged in Archimedean tessellations for tissue regeneration. Despite similar porosity, tiles display vastly different tensile responses (1–100 MPa) and deformation modes. In vitro experiments with hMSCs show geometry‐dependent growth and activity. Over 55 000 tile combinations
Maria Kalogeropoulou, Kenny A. van Kampen, Pierpaolo Fucile, Carlos Mota, Lorenzo Moroni   +4 more
wiley   +1 more source

Mechanically Tunable Bone Scaffolds: In Vivo Hardening of 3D‐Printed Calcium Phosphate/Polycaprolactone Inks

Advanced Functional Materials, EarlyView.
A 3D bone scaffold with osteogenic properties and capable of hardening in vivo is developed. The scaffold is implanted in a ductile state, and a phase transformation of the ceramic induces the stiffening and strengthening of the scaffold in vivo. Abstract Calcium phosphate 3D printing has revolutionized customized bone grafting.
Miguel Mateu‐Sanz, Pablo Varela, Laura del‐Mazo‐Barbara, Irene Lodoso‐Torrecilla, Emilio Jiménez‐Piqué, Jordi Franch, Miguel Alaminos, Maria‐Pau Ginebra   +7 more
wiley   +1 more source

Dynamic Control of Synaptic Plasticity by Competing Ferroelectric and Trap‐Assisted Switching in IGZO Transistors with Al2O3/HfO2 Dielectrics

Advanced Functional Materials, EarlyView.
A frequency‐tunable ferroelectric synaptic transistor based on a buried‐gate InGaZnO channel and Al2O3/HfO2 dielectric stack exhibits linear and reversible weight updates using single‐polarity pulses. By switching between ferroelectric and trap‐assisted modes depending on input frequency, the device simplifies neuromorphic circuit design and achieves ...
Ojun Kwon, Dong Ho Lee, Seyoung Oh, Jongwon Yoon, Hyo‐Bae Kim, Ji‐Hoon Ahn, Woojin Park, Han Seul Kim, Byungjin Cho   +8 more
wiley   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

Advanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva, Giulio Fatti, Emanuel Carlos, Guilherme Ferreira, Sumita Goswami, Suman Nandy, Luiz H. C. Mattoso, Elvira Fortunato, Caio G. Otoni, Rodrigo Martins   +9 more
wiley   +1 more source

On Leveraging Machine Learning in Sport Science in the Hypothetico-deductive Framework

Sports Medicine - Open
Supervised machine learning (ML) offers an exciting suite of algorithms that could benefit research in sport science. In principle, supervised ML approaches were designed for pure prediction, as opposed to explanation, leading to a rise in powerful, but ...
Jordan Rodu, Alexandra F. DeJong Lempke, Natalie Kupperman, Jay Hertel   +3 more
doaj   +1 more source

Do more with less: Exploring semi-supervised learning for geological image classification

Applied Computing and Geosciences
Labelled datasets within geoscience can often be small, with data acquisition both costly and challenging, and their interpretation and downstream use in machine learning difficult due to data scarcity.
Hisham I. Mamode, Gary J. Hampson, Cédric M. John   +2 more
doaj   +1 more source