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August 12, 2025—Dogs that excel at detecting cancer, the math trick hidden in your credit card number and whether chikungunya virus could spread to the U.S. —Robin Lloyd, Contributing Editor | | Individual dogs' personalities, and how we interpret their behaviors, may be key to disease sniffing at scale. Johner Images/Getty Images | | Dogs with pessimistic personalities are better than more optimistic dogs at detecting cancer by sniffing out scent cues in volatile organic compounds found in human breath, sweat, blood and urine, reports science journalist Rohini Subrahmanyam. The finding could help resolve questions about why dogs vary greatly in their olfactory accuracy. Down the line, insights like this could lead to less invasive, scalable diagnostic methods, including electronic noses under development to detect cancer and other diseases from urine samples. For now, dogs outperform electronic sniffers. How they did it: Researchers first primed dogs to associate each of two screens at one end of a room with either a tasty treat or an empty bowl, positive and negative associations, respectively. Then, dogs were classified based on how quickly they investigated additional bowls subsequently placed behind two new screens located between the initial positive and negative spots. The faster investigators were classified as optimistic and the slower ones as pessimistic. In the third experiment, classified dogs were assessed for how accurately they could pick out a disease scent it had previously been trained to pick out. What the experts say: "The dogs, because of their amazing sense of smell and detection capabilities, are demonstrating to us what technology could look like 10 to 15 years from now," says Amritha Mallikarjun of the University of Pennsylvania. | | The last digit of your credit card number is computed and then assigned to satisfy an error-checking mathematical test that helps sniff out invalid credit card numbers, writes freelance puzzle creator Jack Murtagh. This fairly simple but powerful test, called the Luhn algorithm after the IBM researcher who patented it in 1960, dominates credit-card verification. Single digit mistakes, as well as adjacent digit swaps—for the most part, will be detected. The algorithm (see the story for a graphic illustration and application of it) does not guarantee a valid credit card number, but it can quickly spot an invalid one. Why this matters: The Luhn algorithm, which requires very little processing power, saves time for consumers and businesses, replacing the need for a professional validation service. No third party needs to be contacted by the computer performing the arithmetic. Barcodes, package tracking numbers, bank account numbers and ISBN identifiers on books also are checked for errors with similar schemes. What the experts say: "Next time a checkout page flashes that annoying error message, remember: a simple piece of math under the hood just saved a little time and money for everyone involved," writes Murtagh.
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Can you unscramble this? Reassemble the cover of our May 1927 issue, showing an unusual apparatus to measure the energy delivered by ingesting food—one that researchers claim is "perfectly comfortable and may be used for several hours without discomfort." To celebrate Scientific American's 180th anniversary, we're publishing a jigsaw every weekday to show off some of our most fascinating magazine covers over the years. Take a tour here through the covers so far. | | Murtagh's credit card essay reminded me of how many vendors authorized such payments when I was a kid, before "plastic" became a widely used global payment system. Merchants would make a telephone call to the card processor or consult a book that indexed invalid card numbers. It could take several minutes for your card to get a thumbs-up or thumbs-down. In 2015, David Pogue wrote for Scientific American about the future of credit cards, mobile payments and fraud detection. A decade later, it's interesting to see the extent to which his forecast was accurate in this dynamic field. | | We always like to hear from you. Please send your validated thoughts, queries and other feedback to us at: newsletters@sciam.com. —Robin Lloyd, Contributing Editor
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