Role of artificial intelligence in smart grid - a mini review.

A smart grid is a structure that regulates, operates, and utilizes energy sources that are incorporated into the smart grid using smart communications techniques and computerized techniques. The running and maintenance of Smart Grids now depend on artificial intelligence methods quite extensively. Artificial intelligence is enabling more dependable, efficient, and sustainable energy systems from improving load forecasting accuracy to optimizing power distribution and guaranteeing issue identification.

Sparse representation learning derives biological features with explicit gene weights from the Allen Mouse Brain Atlas.

Unsupervised learning methods are commonly used to detect features within transcriptomic data and ultimately derive meaningful representations of biology. Contributions of individual genes to any feature however becomes convolved with each learning step, requiring follow up analysis and validation to understand what biology might be represented by a cluster on a low dimensional plot. We sought learning methods that could preserve the gene information of detected features, using the spatial transcriptomic data and anatomical labels of the Allen Mouse Brain Atlas as a test dataset with verifiable ground truth.

'Shifting from anxiety to the new normal': A qualitative exploration on personal protective equipment use by otorhinolaryngology health-care professionals during COVID-19 pandemic.

Background: The novel coronavirus pandemic has influenced the working practice of health-care professionals who come across symptomatic and asymptomatic COVID patients in their day-to-day practice. Especially, among HCWs in otorhinolaryngology, with the risk of exposure being high, hence were mandated to use personal protective equipment (PPE).

Materials And Methods: The change in perceptions and patterns of PPE use throughout the COVID-19 pandemic was studied in detail through interviews conducted among 15 key informants, and the data were analyzed using health belief model in our study.

Cultivating diversity in the advanced practice registered nurse workforce: An exemplar from an advanced practice registered nurse fellowship program.

Diversity in the nursing workforce is an important driver of patient satisfaction, adherence to care, and quality outcomes. Systemic barriers exist that prevent individuals from underrepresented minority groups entering and advancing in the nursing workforce. To advance the health of the community we serve and with grant support from the Health Resources and Services Administration, we developed a postgraduate advanced practice registered nurse (APRN) fellowship in community health.