Publications by authors named "N E Hadidi"

Introduction: Stroke is a significant health burden for veterans and the fifth leading cause of death for women. Compared to civilian women, women veterans have significant multimorbid physical and mental health conditions contributing to their stroke risk. This scoping review aimed to synthesize evidence on the stroke risk factors specific to U.

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Introduction: Stroke can have profound psychosocial health implications. These constructs are often overlooked and undertreated yet can be as devastating as the physical, functional, and cognitive consequences after stroke.

Aim: This scientific statement aims to evaluate 5 important aspects of psychosocial health (depression, stress, anxiety, fatigue, and quality of life) after a stroke to provide a framework for related nursing care across the poststroke continuum.

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Gene therapeutics are promising for treating diseases at the genetic level, with some already validated for clinical use. Recently, nanostructures have emerged for the targeted delivery of genetic material. Nanomaterials, exhibiting advantageous properties such as a high surface-to-volume ratio, biocompatibility, facile functionalization, substantial loading capacity, and tunable physicochemical characteristics, are recognized as non-viral vectors in gene therapy applications.

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Potato chips are popular high-consuming ready-to-eat meals in all of the world which specially attract a lot of attention from youth and children. Reducing oil absorption and improving the quality of chips are major undertakings within the industry. This research aimed to find the best ultrasonic bath-based method by investigating the optimal ultrasonic pre-treatment and developing an ultrasound (US) assisted frying system (UAFS) to reduce the oil absorption of potato chips while maintaining an acceptable quality.

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Decision-making emerges from distributed computations across multiple brain areas, but it is unclear the brain distributes the computation. In deep learning, artificial neural networks use multiple areas (or layers) to form optimal representations of task inputs. These optimal representations are to perform the task well, but so they are invariant to other irrelevant variables.

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