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Digital Frequency Customized Relieving Sound for Chronic Subjective Tinnitus Management: Prospective Controlled Study.

J Med Internet Res

January 2025

ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China.

Background: Tinnitus is a major health issue, but currently no tinnitus elimination treatments exist for chronic subjective tinnitus. Acoustic therapy, especially personalized acoustic therapy, plays an increasingly important role in tinnitus treatment. With the application of smartphones, personalized acoustic stimulation combined with smartphone apps will be more conducive to the individualized treatment and management of patients with tinnitus.

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Background: The centralization of decision-making power in the public health care system has a negative impact on the practice of professionals and the quality of home care services (HCS) for seniors. To improve HCS, decentralized management could be a particularly promising approach. To be effective, strategies designed to incorporate this management approach require attention to 3 elements: autonomy of local stakeholders, individual and organizational capacities, and accountability for actions and decisions.

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While the incidence of Human Immunodeficiency Virus (HIV) infection is decreasing in most age groups worldwide, it is rising among adolescents and young adults, who also face a higher rate of HIV-related deaths. This tech-savvy demographic may benefit from an online patient portal designed to enhance patient activation-empowering them to manage their health independently. However, the effectiveness of such digital health interventions on young HIV patients in Kenya remains uncertain.

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This work explores an intelligent field irrigation warning system based on the Enhanced Genetic Algorithm-Backpropagation Neural Network (EGA-BPNN) model in the context of smart agriculture. To achieve this, irrigation flow prediction in agricultural fields is chosen as the research topic. Firstly, the BPNN principles are studied, revealing issues such as sensitivity to initial values, susceptibility to local optima, and sample dependency.

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Bacterial Leaf Blight (BLB) usually attacks rice in the flowering stage and can cause yield losses of up to 50% in severely infected fields. The resulting yield losses severely impact farmers, necessitating compensation from the regulatory authorities. This study introduces a new pipeline specifically designed for detecting BLB in rice fields using unmanned aerial vehicle (UAV) imagery.

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