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Looking forward to more evening sunlight thanks to daylight saving time this weekend? Many in the golf industry like the time change, too, and they are pushing to make that annual switch permanent. The move is intended to encourage more evening golf and to stave off efforts to establish permanent standard time, which would leave less time for an evening on the links. And it is those late afternoon players who tend to buy food and drinks in the clubhouse. We would lose 100 tee times a day if daylight saving time goes away, said Connor Farrell, general manager of Stone Creek Golf Course in Omaha, Nebraska. Switching to permanent standard time would cost us $500,000 a year.” Golf played a big role in daylight savings time Golf has deep roots in the history of daylight saving time, which begins for most states at 2 a.m. Sunday when clocks spring forward by one hour. Some credit goes to William Willett, a British builder and avid golfer who in 1905 published a pamphlet advocating for moving clocks ahead in April and returning them back to their regular settings in September. The U.S. adopted a version of that during World War I and again in World War II. Congress passed the Uniform Time Act in 1966 that set up the biannual time change, and lobbying efforts by the golf industry are largely credited for Congress expanding daylight saving time by a month in the mid-1980s. Lawmakers try to make standard time permanent But for as long as it has been around, the constant clock adjusting has drawn the ire of Americans weary of losing an hour of sleep in the spring only to be faced with the early onset of darkness in the fall. That exhaustion has led to hundreds of bills introduced in nearly every state over the years to halt the practice. The National Conference of State Legislatures reports that in the last six years, 20 states have passed measures calling for a switch to year-round daylight saving time, many at the cajoling of golf industry lobbyists. But while states could switch to permanent standard timeas Arizona and Hawaii have doneCongress would need to change the law to allow permanent daylight saving time. That hindrancealong with arguments that permanent standard time would improve sleep quality and foster safer morning commuteshas seen more states consider opting out of daylight saving time. Lawmakers in more than a dozen states have introduced bills this year to make standard time permanent. Nebraska is among several states considering competing bills to make either standard time or daylight saving time permanent. That drew Joe Kohout, a lobbyist for the Nebraska Golf Alliance, to testify in favor of year-round daylight saving time. Late afternoon golf leagues account for up to 40% of the annual revenue of some Nebraska courses, Kohout said, while a majority of golf instructors reported that nearly 50% of their lessons are taught after 4 p.m. Under permanent standard time, Nebraskas golf courses will lose revenue, be forced to raise prices, and in some cases could be driven out of business, he said. The Utah Golf Association is also fighting a bill to make standard time permanent. The argument that changing clocks twice a year is an inconvenience does not outweigh the year-round benefits of having more usable daylight hours in the evenings, it posted on social media. In Indiana, golf course owner Linda Rogers succeeded in lobbying the Legislature to institute daylight saving time in 2006. Now a state senator, Rogers is fighting an effort to return to permanent standard time. Daylight savings time allows someone that, you know, worked until 5 oclock to come out and still play at least nine holes, she said. And its not just golf. There are so many outdoor activities that people want to be outside for and enjoy later in the summertime. Golf course owners like the status quo The National Golf Course Owners Association, which has about 4,000 members, recently polled stakeholders on the matter. The vast majority favored either permanent daylight saving time or the status quo of changing the clocks, said CEO Jay Karen. Only about 6% backed a change to permanent standard time. If standard time was to be made permanent, thousands of courses would be harmed by that, Karen said. Even so, Karen’s group is not advocating for a change to permanent daylight saving because it could hurt hundreds of courses that cater to early morning golfers, he said. Those include courses in retirement communities, vacation resorts where late tee times interfere with dinner plans and Sun Belt courses where extreme late-day heat sees golfers favoring early tee times. We feel like status quo is no harm, no foul, Karen said. Republican Iowa state Representative John Wills introduced a bill this year to make the change to permanent daylight savings. But he has been under pressure to amend the bill to permanent standard time. Wills was considering it until he heard arguments on how that change could affect golf. I think I might push back in the future and say, you know, the golf industry needs this, he said. By Margery A. Beck, Associated Press
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This week, Apple updated half of its iPad lineup. After updating the iPad Pro and iPad mini in 2024, the company has just unveiled a third-generation iPad Air and an eleventh-generation iPad. Many fans of Apples tablets have been eagerly awaiting these updates, especially since before this week, the companys entry-level iPad had not had a refresh since October of 2022. But if you’ve been waiting until this weeks reveals, hoping for a clear picture of Apple’s iPad offerings in order to select the one best for your needs, well, Ive got bad news: the iPad lineup remains as confusing as ever. Heres why. Not all models support Apple Intelligence Apple makes four different types of iPads: the iPad Pro, the iPad Air, the iPad, and the iPad mini. Yet despite each model getting an update within the last yearone of them still lacks the hardware to run Apple’s much-hyped Apple Intelligence AI platform, which debuted in October 2024. That would be the new iPadyes, the eleventh-generation tablet that Apple announced just this week. In 2025. In a baffling move, Apple decided to equip the new iPad with just 6GB of memory and the A16 chipthe CPU Apple first introduced all the way back in 2022 in the iPhone 14 Pro series and later included in the iPhone 15 series. None of these devices can run Apple Intelligence because the AI platform requires at least 8GB of memory. It’s shocking that Apple decided to limit its new 2025 iPad to just 6GB of memory and the A16 instead of giving it the more advanced A17 Pro chip and 8GB of memory that can run Apple Intelligence and that the smaller iPad mini, introduced in 2024, has packed inside. Why would Apple do this? Ive reached out to the company for comment and have yet to hear back, but the most likely reason is that Apple wants to push customers into its higher-priced iPad models, like the iPad mini ($499) and iPad Air ($549), instead of having them buy the entry-level iPad ($349). Consumers are starting to go crazy for AI, and, in my opinion, Apple knows that by excluding Apple Intelligence from the entry-level iPad, many of them will instead opt to shell out another $150 to $200 more on an iPad that supports it. You cant fault a company for wanting to make more money. But the lack of Apple Intelligence support on the new iPad is going to confuse a lot of people. Some may buy it thinking it comes with Apple Intelligence since, you know, every other iPad does. This device is kind of already obsoleteat least if you ever want to use Apple Intelligence. The thinnest and lightest model..is not the one you would think The lack of Apple Intelligence on Apples newest iPad isnt the only thing likely to confuse consumers. Many people are drawn to tablets because they are thin and light and thus easier to lug around than a laptop. Historically, Apples thinnest and lightest devices have all fallen under a unique moniker: Air. Theres the MacBook Airthe thinnest laptop Apple sells. Theres the (very likely) upcoming iPhone Air, which will be the thinnest iPhone ever, and of course, there is the iPad Air, which is the thinnestwait, no. You would think the iPad Air would be the thinnest iPad Apple makes, but thats not true. If you want the thinnest iPad, you actually need to buy the iPad Pro (which is 5.1 mm or 5.3 mm thin, depending on screen size) and not the iPad Air (which is 6.1 mm thin). But what if you want the lightest iPad? Surely, thats the iPad Air, right? No. Thats the 11-inch iPad Pro, which weighs in at 0.98 pounds. The 11-inch iPad Air is 1.01 pounds (and if you think it’s fair to compare apples to oranges, the iPad mini with its 8.3-inch screen comes in at just 0.65 pounds, beating the iPad Air by a long shot). Do you see how confusing this could be to the average consumer? And dont even get me started on Apple Pencil compatibility (the Apple Pencil Pro works with the smaller iPad mini from 2024, but not the larger, newer iPad Apple introduced this week). Which iPad should you get? Ive long hoped that Apple would fix its confusing iPad lineup. They didnt do it last year, or the year before, and with the new iPads this week, it looks like they arent going to do it in 2025 either. So, if you are in the market for a new iPad, maybe this little cheat sheet will help you out: If you want the thinnest iPad, get an iPad Pro (not the iPad Air). If you want the lightest iPad, get the iPad mini. If you want to be able to use the Apple Pencil Pro, get the iPad Pro, iPad Air, or iPad mini. If you want Apple Intelligence, get the iPad Pro, iPad Air, or iPad miniand avoid the new iPad. And if you want a lack of confusionI guess maybe wait to see if the 2026 iPad family finally brings much-needed simplicity to Apples tablet lineup? The new 2025 iPad and iPad Air are now available to pre-order and will be released on March 12.
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Microplasticsthe tiny particles of plastic shed when litter breaks downare everywhere, from the deep sea to Mount Everest, and many researchers worry that they could harm human health. I am a machine learning researcher. With a team of scientists, I have developed a tool to make identification of microplastics using their unique chemical fingerprint more reliable. We hope that this work will help us learn about the types of microplastics floating through the air in our study area, Michigan. Microplasticsa global problem The term plastic refers to a wide variety of artificially created polymers. Polyethylene, or PET, is used for making bottles; polypropylene, or PP, is used in food containers; and polyvinyl chloride, or PVC, is used in pipes and tubes. Microplastics are small plastic particles that range in size from 1 micrometer to 5 millimeters. The width of a human hair, for comparison, ranges from 20 to 200 micrometers. Most scientific studies focus on microplastics in water. However, microplastics are also found in the air. Scientists know much less about microplastics in the atmosphere. When scientists collect samples from the environment to study microplastics, they usually want to know more about the chemical identities of the microplastic particles found in the samples. Fingerprinting microplastics Just as fingerprinting uniquely identifies a person, scientists use spectroscopy to determine the chemical identity of microplastics. In spectroscopy, a substance either absorbs or scatters light, depending on how its molecules vibrate. The absorbed or scattered light creates a unique pattern called the spectrum, which is effectively the substances fingerprint. Just like a forensic analyst can match an unknown fingerprint against a fingerprint database to identify the person, researchers can match the spectrum of an unknown microplastic particle against a database of known spectra. However, forensic analysts can get false matches in fingerprint matching. Similarly, spectral matching against a database isnt foolproof. Many plastic polymers have similar structures, so two different polymers can have similar spectra. This overlap can lead to ambiguity in the identification process. So, an identification method for polymers should provide a measure of uncertainty in its output. That way, the user can know how much to trust the polymer fingerprint match. Unfortunately, current methods dont usually provide an uncertainty measure. Data from microplastic analyses can inform health recommendations and policy decisions, so its important for the people making those calls to know how reliable the analysis is. Conformal prediction Machine learning is one tool researchers have started using for microplastic identification. First, researchers collect a large dataset of spectra whose identities are known. Then, they use this dataset to train a machine learning algorithm that learns to predict a substances chemical identity from its spectrum. Sophisticated algorithms whose inner workings can be opaque make these predictions, so the lack of an uncertainty measure becomes an even greater problem when machine learning is involved. Our recent work addresses this issue by creating a tool with an uncertainty quantification for microplastic identification. We use a machine learning technique called conformal prediction. Conformal prediction is like a wrapper around an existing, already trained machine learning algorithm that adds an uncertainty quantification. It does not require the user of the machine learning algorithm to have any detailed knowledge of the algorithm or its training data. The user just needs to be able to run the prediction algorithm on a new set of spectra. To set up conformal prediction, researchers collect a calibration set containing spectra and their true identities. The calibration set is often much smaller than the training data required for training machine learning algorithms. Usually just a few hundred spectra are enough for calibration. Then, conformal prediction analyzes the discrepancies between the predictions and correct answers in the calibration set. Using this analysis, it adds other plausible identities to the algorithms single output on a particular particles spectrum. Instead of outputting one, possibly incorrect, prediction like this particle is polyethylene, it now outputs a set of predictionsfor example, this particle could be polyethylene or polypropylene. The prediction sets contain the true identity with a level of confidence that users can set themselvessay, 90%. Users can then rerun the conformal prediction with a higher confidencesay, 95%. But the higher the confidence level, the more polymer predictions given by the model in the output. It might seem that a method that outputs a set rather than a single identity isnt as useful. But the size of the set serves as a way to assess uncertaintya small set indicates less uncertainty. On the other hand, if the algorithm predicts that the sample could be many different polymers, theres substantial uncertainty. In this case, you could bring in a human expert to examine the polymer closely. Testing the tool To run our conformal prediction, my team used libraries of microplastic spectra from the Rochman Lab at the University of Toronto as the calibration set. Once calibrated, we collected samples from a parking lot in Brighton, Michigan, obtained ther spectra, and ran them through the algorithm. We also asked an expert to manually label the spectra with the correct polymer identities. We found that conformal prediction did produce sets that included the label the human expert gave it. Microplastics are an emerging concern worldwide. Some places such as California have begun to gather evidence for future legislation to help curb microplastic pollution. Evidence-based science can help researchers and policymakers fully understand the extent of microplastic pollution and the threats it poses to human welfare. Building and openly sharing machine learning-based tools is one way to help make that happen. Ambuj Tewari is a professor of statistics at the University of Michigan. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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