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During the Covid-19 pandemic, real-time social media data could in principle be used as an early predictor of a new epidemic wave. This possibility is examined here by employing a neural ordinary differential equation (n...

As a non-destructive and rapid technique, optical scatterometry has gained widespread use in the measurement of film thickness and optical constants. The recent advances in deep learning have presented new and powerful a...

Accurate velocity estimation plays a key role in ensuring precise motion control and safe navigation of ground robots. Ground-view event cameras provide a reliable sensing modality for this task. They exploit the static ...

ObjectiveTo investigate the safety and efficacy of magnesium sulfate as an adjuvant in pulsed radiofrequency (PRF) stimulation of the greater occipital nerve for the treatment of occipital neuralgia.MethodsConsecutive pa...

Abstract In the realm of engineering practice, various factors such as limited availability of measurement data and complex working conditions pose significant challenges to obtaining accurate load spectra. Thus, accurat...

Devices based on two-dimensional photonic-crystal nanocavities, which are defined by their air hole patterns, usually require a high quality (Q) factor to achieve high performance. We demonstrate that hole patterns with ...

Postnatal hippocampal neurogenesis is essential for learning and memory. Hippocampal neural precursor cells (NPCs) can be induced to proliferate and differentiate into either glial cells or dentate granule cells. Notably...

ABSTRACT The growing use of neural networks in privacy‐sensitive applications necessitates architectures that inherently protect both data and model integrity. We present a model‐inversion‐resistant physical unclon...

Abstract The study of multi classification of data has become one of the important issues which geographical studies focus on especially those which take their data from satellites. Two ways of classification has been ta...

Optimization of design parameters based on electromagnetic simulation of microwave circuits is a timeconsuming and iterative procedure. To provide a fast and accurate frequency response for a given case study, this paper...

The search for new energy sources has intensified today worldwide. In Argentina, bioenergy continues to be the energy with minor participation in the energy matrix. Therefore, research should focus on searching for new s...

Abstract Thermal stress in electric two-wheeler hub motors is a major bottleneck affecting drivetrain reliability, safety, and efficiency—especially under varied terrain, aggressive riding profiles, and sensor reliabil...

Recent advances in protein structure prediction, such as AlphaFold, have demonstrated the power of deep neural architectures like the Evoformer for capturing complex spatial and evolutionary constraints on protein confor...

BackgroundReactive lymphoid hyperplasia (RLH) is frequently identified in pediatric appendectomy specimens performed for suspected acute appendicitis. However, its associated neural and stromal alterations remain incompl...

In recent years, convolutional neural networks and deep neural networks have been used extensively in various fields of analytical chemistry. The use of these models for calibration tasks has been highly effective; howev...

Sitagliptin (SIT) is a dipeptidyl peptidase-4 (DPP-4) inhibitor that enhances the effects of incretin hormones, such as Glucose-dependent Insulinotropic Peptide (also known as Gastric Inhibitory Polypeptide, GIP) and Glu...

Abstract Background Postherpetic neuralgia (PHN) is a neuropathic pain syndrome that can be resistant to traditional therapies and severely impairs quality of life. The serratus posterior superior intercostal plane block...

Abstract This study uses the Levenberg–Marquardt strategy with feed forward neural networks (LMS-FNN) to inspect the Soret-Dufour effect on radiative hybrid nanofluid flow across a Riga plate with gyrotactic microorgan...

ABSTRACT Deep learning profoundly impacts various areas, such as face recognition and language translation. Owing to the increasingly high computational costs of training neural architectures, it is intractable to manual...

While interactions between neural crest and placode cells are critical for the proper formation of the trigeminal ganglion, the mechanisms underlying this process remain largely uncharacterized. Here, by using chick embr...

Abstract High-density, long-term stable decoding of whole-brain function is crucial for advancing basic neuroscience research and developing neural disorder therapies. However, two major challenges remain: the lack of sc...

Airport planning depends to a large extent on the levels of activity that are anticipated. To plan the facilities and infrastructures of an airport system and to be able to satisfy future needs, it is essential to predic...

Abstract Background Chronic kidney disease (CKD) frequently causes death in older cats; its early detection is challenging. Objectives To build a sensitive and specific model for early prediction of CKD in cats using art...

Abstract The last decade witnessed a great evolution on the fields of computer science, artificial intelligence, communication and data transmission. This evolution draw the attention of specialists to design a modern cr...