For centuries, people have believed the moon could alter their sleep. Breakthroughs, discoveries, and DIY tips sent every weekday. You've gone to bed at your usual time, skipped that afternoon coffee, and made your bedroom cool, dark, and quiet-- just like the experts recommend . Then you notice the silver light spilling through your curtains. Could that be what's keeping you awake?

Philosophy professor Dr. Susan Schneider joins'Fox & Friends First' to discuss the impact of artificial intelligence on students' performance in the classroom. Staying awake to watch "just one more episode" is a classic excuse for delaying bedtime. And with popular shows like Peacock's "Love Island" airing almost every night as the drama unfolds live, there's more pressure to finish the latest episode and to engage in conversation with others the next day. In addition to making us sleepier in the morning, staying awake to watch TV is not good for the brain, according to Daniel Amen, a psychiatrist, brain imaging doctor and founder of Amen Clinics in California. "'I just have to watch the last episode' of whatever show you're watching, and you end up cutting out half an hour or an hour of sleep," he said in an interview with Fox News Digital.

That was the average length of time an adult could focus on a screen for in 2021, according to research by Gloria Mark, a professor of informatics at the University of California. Twenty years ago, in 2004, that number stood at two-and-a-half minutes. Our attention spans – how long we're able to concentrate without being distracted – are shrinking. Our focus – how intensely we can think about things – is suffering too. The causes: technology that's designed to demand our attention; endless tools for procrastination at our fingertips; rising stress and anxiety disorders; and poor sleep quality.

Wherever you are reading this – on the couch or in bed – there is a good chance that you are doing it on some sort of screen. According to a 2022 review, almost everyone upped their screentime during the Covid pandemic, and there is little evidence that use has gone back down. While that may or may not be bad for all sorts of reasons, a concern for many people is blue light, and whether its haunting glow is affecting our bodies in ways sunshine doesn't. Could it somehow be bad light? To start with the basics: blue light sits on the short-wave, high-energy end of the visible spectrum, close to the UV rays that can lead to provably harmful effects on the skin and retinas.

It is commonplace to use data containing personal information to build predictive models in the framework of empirical risk minimization (ERM). While these models can be highly accurate in prediction, results obtained from these models with the use of sensitive data may be susceptible to privacy attacks. Differential privacy (DP) is an appealing framework for addressing such data privacy issues by providing mathematically provable bounds on the privacy loss incurred when releasing information from sensitive data. Previous work has primarily concentrated on applying DP to unweighted ERM. We consider an important generalization to weighted ERM (wERM). In wERM, each individual's contribution to the objective function can be assigned varying weights. In this context, we propose the first differentially private wERM algorithm, backed by a rigorous theoretical proof of its DP guarantees under mild regularity conditions. Extending the existing DP-ERM procedures to wERM paves a path to deriving privacy-preserving learning methods for individualized treatment rules, including the popular outcome weighted learning (OWL). We evaluate the performance of the DP-wERM application to OWL in a simulation study and in a real clinical trial of melatonin for sleep health. All empirical results demonstrate the viability of training OWL models via wERM with DP guarantees while maintaining sufficiently useful model performance. Therefore, we recommend practitioners consider implementing the proposed privacy-preserving OWL procedure in real-world scenarios involving sensitive data.

Although the use of AI tools in music composition and production is steadily increasing, as witnessed by the newly founded AI song contest, analysis of music produced using these tools is still relatively uncommon as a mean to gain insight in the ways AI tools impact music production. In this paper we present a case study of "Melatonin", a song produced by extensive use of BassNet, an AI tool originally designed to generate bass lines. Through analysis of the artists' work flow and song project, we identify style characteristics of the song in relation to the affordances of the tool, highlighting manifestations of style in terms of both idiom and sound.

As COVID-19 continues to spread throughout the world, particularly with cases rising during what some have termed the "fall surge," repurposing drugs already approved by the U.S. Food and Drug Administration for new therapeutic purposes continues to be the most efficient and cost-effective approach to treat or prevent the disease. According to the findings published today in PLOS Biology, a novel artificial intelligence platform developed by Lerner Research Institute researchers to identify possible drugs for COVID-19 repurposing has revealed melatonin as a promising candidate. Analysis of patient data from Cleveland Clinic's COVID-19 registry also revealed that melatonin usage was associated with a nearly 30 percent reduced likelihood of testing positive for SARS-CoV-2 (the virus that causes COVID-19) after adjusting for age, race, smoking history and various disease comorbidities. Notably, the reduced likelihood of testing positive for the virus increased from 30 to 52 percent for African Americans when adjusted for the same variables. "It is very important to note these findings do not suggest people should start to take melatonin without consulting their physician," said Feixiong Cheng, Ph.D., assistant staff in Cleveland Clinic's Genomic Medicine Institute and lead author on the study.

During winter when the nights are long and days short, getting up for work in the dark and coming home in the dark can be grim. Some of us succumb to the January blues, leading to increased illness, reduced productivity and a general feeling of melancholy. But can clever lighting improve our sleep patterns and lift our moods? "I only feel like I start to breathe properly again after the solstice," says Jacqueline Hazelton, a professor at the US Naval War College in Rhode Island. She's referring to the winter solstice - usually 21 December - the point after which the days start lengthening again following the longest night of the year.

Sleep is a naturally recurring state of mind and body, characterized by altered consciousness, relatively inhibited sensory activity, inhibition of nearly all voluntary muscles, and reduced interactions with surroundings.[1] It is distinguished from wakefulness by a decreased ability to react to stimuli, but is more easily reversed than the state of being comatose. Sleep occurs in repeating periods, in which the body alternates between two distinct modes known as non-REM and REM sleep. Although REM stands for "rapid eye movement", this mode of sleep has many other aspects, including virtual paralysis of the body. A well-known feature of sleep is the dream, an experience typically recounted in narrative form, which resembles waking life while in progress, but which usually can later be distinguished as fantasy. During sleep, most of the body's systems are in an anabolic state, helping to restore the immune, nervous, skeletal, and muscular systems; these are vital processes that maintain mood, memory, and cognitive performance, and play a large role in the function of the endocrine and immune systems.[2] The internal circadian clock promotes sleep daily at night. The diverse purposes and mechanisms of sleep are the subject of substantial ongoing research.[3] The advent of artificial light has substantially altered sleep timing in industrialized countries.[4] Humans may suffer from various sleep disorders, including dyssomnias, such as insomnia, hypersomnia, narcolepsy, and sleep apnea; parasomnias, such as sleepwalking and REM behavior disorder; bruxism; and circadian rhythm sleep disorders. The most pronounced physiological changes in sleep occur in the brain.[5]

When someone commits suicide, their family and friends can be left with the heartbreaking and answerless question of what they could have done differently. Colin Walsh, data scientist at Vanderbilt University Medical Center, hopes his work in predicting suicide risk will give people the opportunity to ask "what can I do?" while there's still a chance to intervene. Walsh and his colleagues have created machine-learning algorithms that predict, with unnerving accuracy, the likelihood that a patient will attempt suicide. In trials, results have been 80-90% accurate when predicting whether someone will attempt suicide within the next two years, and 92% accurate in predicting whether someone will attempt suicide within the next week. The prediction is based on data that's widely available from all hospital admissions, including age, gender, zip codes, medications, and prior diagnoses.