Results 41 to 50 of about 2,569,797 (292)
HoloDetect: Few-Shot Learning for Error Detection
, 2019 We introduce a few-shot learning framework for error detection. We show that data augmentation (a form of weak supervision) is key to training high-quality, ML-based error detection models that require minimal human involvement. Our framework consists of
Bengio Yoshua +9 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Psychological safety (PS) is essential for teamwork, communication, and patient safety in complex healthcare environments. In pediatric oncology, interprofessional collaboration occurs under high emotional and organizational demands. Low PS may increase stress, burnout, and adverse events.
Alexandros Rahn +4 more
wiley +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Chronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is steadily increasing. Türkiye has experienced a similar rise in both the incidence and prevalence of renal replacement therapy over the past decades; however, national‐level projections of future ...
Arzu Akgül +2 more
wiley +1 more source
A methodology for the generation of efficient error detection mechanisms [PDF]
, 2011 A dependable software system must contain error detection mechanisms and error recovery mechanisms. Software components for the detection of errors are typically designed based on a system specification or the experience of software engineers, with their
Anand, Sarabjot Singh +3 more
core +1 more source
FEBS Letters, EarlyView.In this study, we present the structure of AcrIE8.1, a previously uncharacterized anti‐CRISPR protein that inhibits the type I‐E CRISPR‐Cas system. Through a combination of structural and biochemical analyses, we demonstrate that AcrIE8.1 directly binds to the Cas11 subunit of the Cascade complex to inhibit the CRISPR‐Cas system.
Young Woo Kang, Hyun Ho Park
wiley +1 more source
Testing based on the RELAY model of error detection [PDF]
, 1987 RELAY, a model for error detection, defines revealing conditions that guarantee that a fault originates an error during execution and that the error transfers through computations and data flow until it is revealed. This model of error detection provides
Richardson, Debra J. +1 more
core
A Cre‐dependent lentiviral vector for neuron subtype‐specific expression of large proteins
FEBS Letters, EarlyView.We designed a versatile and modular lentivector comprising a Cre‐dependent switch and self‐cleaving 2A peptide and tested it for co‐expression of GFP and a 2.8 kb gene of interest (GOI) in mouse cortical parvalbumin (PV+) interneurons and midbrain dopamine (TH+) neurons.
Weixuan Xue +6 more
wiley +1 more source
ECS Sensors PlusAdditive manufacturing in the realm of 3D printing has transformed the manufacturing sector, providing unmatched freedom in design and rapid prototyping abilities.
Prateek Mehta +5 more
doaj +1 more source
Knowledge Error Detection via Textual and Structural Joint Learning
Big Data Mining and AnalyticsKnowledge graphs are essential tools for representing real-world facts and finding wide applications in various domains. However, the process of constructing knowledge graphs often introduces noises and errors, which can negatively impact the performance
Xiaoyu Wang +4 more
doaj +1 more source
FEBS Letters, EarlyView.Bifidobacterium bifidum establishes symbiosis with infants by metabolizing lacto‐N‐biose I (LNB) from human milk oligosaccharides (HMOs). The extracellular multidomain enzyme LnbB drives this process, releasing LNB via its catalytic glycoside hydrolase family 20 (GH20) lacto‐N‐biosidase domain.
Xinzhe Zhang +5 more
wiley +1 more source