Core Components of Cardiac Rehabilitation Programs: 2024 Update: A Scientific Statement From the American Heart Association and the American Association of Cardiovascular and Pulmonary Rehabilitation: Endorsed by the American College of Cardiology.

The science of cardiac rehabilitation and the secondary prevention of cardiovascular disease has progressed substantially since the most recent American Heart Association and American Association of Cardiovascular and Pulmonary Rehabilitation update on the core components of cardiac rehabilitation and secondary prevention programs was published in 2007. In addition, the advent of new care models, including virtual and remote delivery of cardiac rehabilitation services, has expanded the ways that cardiac rehabilitation programs can reach patients. In this scientific statement, we update the scientific basis of the core components of patient assessment, nutritional counseling, weight management and body composition, cardiovascular disease and risk factor management, psychosocial management, aerobic exercise training, strength training, and physical activity counseling.

Non-contact respiratory monitoring during sleep: comparison of the touchless flow signal with RIP signal to assess respiratory events.

Study Objectives: A non-intrusive sleep monitoring technology based on the data from a commercially available depth sensing camera has been utilized for respiratory monitoring and shown to have good performance in assessing respiratory rates across a range of rates. This non-contact, or , technology allows continuous respiratory monitoring without attaching probes to the patient. We have noticed a strikingly similar morphology between the touchless flow signal (NCM) and the flow signal derived using the chest and abdomen respiratory inductance plethysmography (RIP) bands.

Modeling complex polycrystalline alloys using a Generative Adversarial Network enabled computational platform.

Creating statistically equivalent virtual microstructures (SEVM) for polycrystalline materials with complex microstructures that encompass multi-modal morphological and crystallographic distributions is a challenging enterprise. Cold spray-formed (CSF) AA7050 alloy containing coarse-grained prior particles and ultra-fine grains (UFG) and additively manufactured (AM) Ti64 alloys with alpha laths in beta substrates. The paper introduces an approach strategically integrating a Generative Adversarial Network (GAN) for multi-modal microstructures with a synthetic microstructure builder DREAM.