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In modern times, the collection of data is not a big deal but using it in a meaningful is a challenging task. Different organizations are using artificial intelligence and machine learning for collecting and utilizing the data. These should also be used in the medical because different disease requires the prediction. One of these diseases is asthma that is continuously increasing and affecting more and more people. The major issue is that it is difficult to diagnose in children. Machine learning algorithms can help in diagnosing it early so that the doctors can start the treatment early. Machine learning algorithms can perform this prediction so this study will be helpful for both the doctors and patients. There are different machine learning predictive algorithms are available that have been used for this purpose.

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Vulnerable populations, such as patients with mental illnesses, are known to be overly influenced during disasters and pandemics. However, little is known about how people with autism spectrum disorder (ASD), one of the most common neurodevelopmental conditions in the world with a prevalence of 1%, are affected by health-related disasters, particularly the current Covid-19 pandemic. We investigated how individuals with ASD responded to Covid-19 in terms of comprehension and adherence to implemented measures; changes in their behavioral problems; and how the anxiety levels of their caregivers relate to these behavioral changes. Our sample consisted of 50 individuals with ASD (30 male and 20 female; ages ranged from 3 to 14). The majority of our participants had trouble grasping what Covid-19 is and the measurements it necessitates. They also encountered difficulties in implementing pandemic-related social distance and hygiene regulations. During this time, the majority of students stopped receiving special education. In terms of increased stereo-types, aggression, hypersensitivity, behavioral problems, and sleep and appetite changes, we observed a Covid-19-related clinical presentation that resembled PTSD in individuals with ASD. Aberrant Behavior Checklist (ABC) subscales differed significantly before and after the pandemic conditions. There were differences among the caregivers’ anxiety levels between the current behavioral problem levels to the behavioral problem levels prior to the pandemic. The difference in ABC total score, and specifically the lethargy/social withdrawal subscale score, predicted the anxiety score of the parents. Our findings suggest that the Covid-19 period poses unique challenges for people with ASD and their caregivers, emphasizing the importance of targeted, distance special education interventions and other support services for this population.

The velocity dependence on the magnetic friction and the magnetic field dependence on the terminal velocity of the magnets moving on the conductor plane were investigated. A mechanical friction effect was eliminated by attaching the magnet to a cart which moves almost frictionless on the plane. From the relation between the terminal velocity and acceleration of the cart, the magnetic friction acting on the cart was found to be linearly dependent on the velocity. The magnetic field dependence on the terminal velocity was also investigated under the various magnetic fields and fixed acceleration. The terminal velocity of the moving cart decreases linearly with respect to the increasing relative magnetic field intensity.