Role of transcutaneous electrical nerve stimulation in alleviation of tinnitus in normal hearing subjects.

Background: Subjective tinnitus is characterized by perception of sound in the absence of any external or internal acoustic stimuli. Many approaches have been developed over the years to treat tinnitus (medical and nonmedical). However, no consensus has been reached on the optimal therapeutic approach.

Empowering nurse leaders: readiness for AI integration and the perceived benefits of predictive analytics.

Introduction: Artificial Intelligence (AI) is increasingly being integrated into healthcare, particularly through predictive analytics that can enhance patient care and operational efficiency. Nursing leaders play a crucial role in the successful adoption of these technologies.

Aim: This study aims to assess the readiness of nursing leaders for AI integration and evaluate their perceptions of the benefits of AI-driven predictive analytics in healthcare.

Developing an artificial diet for rearing (Hymenoptera: Figitidae) on spotted-wing drosophila.

(Matsumura) (Diptera: Drosophilidae) is a global invasive pest attacking soft-skinned fruit. The specialist larval parasitoid wasp, (Ihering), was recently approved in Europe and the United States for classical biological control releases against . Rearing methods are essential for supporting innundative releases but current methods using fresh fruit are costly and susceptible to variation in host quality.

Predicting image memorability from evoked feelings.

While viewing a visual stimulus, we often cannot tell whether it is inherently memorable or forgettable. However, the memorability of a stimulus can be quantified and partially predicted by a collection of conceptual and perceptual factors. Higher-level properties that represent the "meaningfulness" of a visual stimulus to viewers best predict whether it will be remembered or forgotten across a population.

Weakly-supervised thyroid ultrasound segmentation: Leveraging multi-scale consistency, contextual features, and bounding box supervision for accurate target delineation.

Weakly-supervised learning (WSL) methods have gained significant attention in medical image segmentation, but they often face challenges in accurately delineating boundaries due to overfitting to weak annotations such as bounding boxes. This issue is particularly pronounced in thyroid ultrasound images, where low contrast and noisy backgrounds hinder precise segmentation. In this paper, we propose a novel weakly-supervised segmentation framework that addresses these challenges.