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People who experience nightmares weekly or more frequently face three times higher risk of dying before age 70 compared to those having nightmares less than monthly, according to research by Dr. Abidemi Otaiku at Imperial College London. His analysis of six long-term studies covering more than 180,000 adults and 2,500 children found frequent nightmares predict early death more strongly than smoking, obesity, poor diet, or physical inactivity. Among 174 people who died prematurely, 31 experienced at least weekly nightmares. Otaiku's research shows chromosomes of nightmare-prone individuals display accelerated aging patterns linked to stress hormones, accounting for roughly 40% of their increased mortality risk. Effective nightmare treatment options are currently limited and require more medical research, the report adds.

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Conscientiousness levels among young adults have fallen substantially since 2014 as people in their twenties and thirties report increased distractibility and carelessness alongside decreased tenacity and commitment-making, according to Financial Times analysis of Understanding America Study data. The personality trait, which research links to longer lifespans, career success, and relationship durability, has witnessed its steepest decline during and after the pandemic. Young adults simultaneously showed rising neuroticism scores and declining extroversion measures, transforming from society's most outgoing age group to its most introverted.

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Google announced Friday it will roll out an AI-powered redesign of Google Finance over the coming weeks in the United States. The update adds natural language query processing for financial research questions with comprehensive AI responses including relevant links, advanced charting tools with technical indicators and candlestick charts, expanded market data covering commodities and additional cryptocurrencies, and a live news feed displaying real-time headlines.

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Computer scientists at Tsinghua University and Stanford have developed an algorithm that surpasses a fundamental speed limit that has constrained network pathfinding calculations since 1984. The team's approach to the shortest-path problem -- finding optimal routes from one point to all others in a network -- runs faster than Dijkstra's 1956 algorithm and its improvements by avoiding the sorting process that created the decades-old computational barrier. Led by Ran Duan at Tsinghua, the researchers combined clustering techniques with selective application of the Bellman-Ford algorithm to identify influential nodes without sorting all paths by distance. The algorithm divides graphs into layers and uses Bellman-Ford to locate key intersection points before calculating paths to other nodes. The technique works on both directed and undirected graphs with arbitrary weights, solving a problem that stymied researchers after partial breakthroughs in the late 1990s and early 2000s applied only to specific weight conditions.

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