Publications by authors named "M WEINBERG"

Background: Urbanization is rapidly altering our ecosystem. While most wild species refrain from entering urban habitats, some flourish in cities and adapt to the new opportunities these offer. Urban individuals of various species have been shown to differ in physiology, morphology, and behavior compared to their rural counterparts.

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Bats have adapted to pathogens through diverse mechanisms, including increased resistance - rapid pathogen elimination, and tolerance - limiting tissue damage following infection. In the Egyptian fruit bat (an important model in comparative immunology) several mechanisms conferring disease tolerance were discovered, but mechanisms underpinning resistance remain poorly understood. Previous studies on other species suggested that elevated basal expression of innate immune genes may lead to increased resistance to infection.

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Over the past few years, there has been a growing awareness of the extent and consequences of sexual assault. Sexual assault has long-term consequences for the survivor's mental health and brings into question the resources available to survivors for dealing with the consequences of the assault. The positive effects of spirituality and forgiveness on mental health are well documented; however, few studies have examined how sexual assault survivors use spiritual beliefs and forgiveness to cope with posttraumatic stress disorder (PTSD) and stress symptoms.

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Animal species have evolved to enhance their survival by focusing their temporal activity on specific parts of the diurnal-nocturnal cycle. Various factors, including inter-specific competition and anti-predator behavior, as well as anthropogenic effects like light pollution, have prompted some species to expand or shift their temporal niches. Our study focuses on the temporal niche shift of the Egyptian fruit bat () to diurnal activity in Israel.

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Background: Although transcatheter aortic valve replacement has emerged as an alternative to surgical aortic valve replacement, it requires extensive healthcare resources, and optimal length of hospital stay has become increasingly important. This study was conducted to assess the potential of novel machine learning models (artificial neural network and eXtreme Gradient Boost) in predicting optimal hospital discharge following transcatheter aortic valve replacement.

Aim: To determine whether artificial neural network and eXtreme Gradient Boost models can be used to accurately predict optimal discharge following transcatheter aortic valve replacement.

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