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Seven million cancers a year are preventable, says report

BBC News

Seven million people's cancer could be prevented each year, according to the first global analysis. A report by World Health Organization (WHO) scientists estimates 37% of cancers are caused by infections, lifestyle choices and environmental pollutants that could be avoided. This includes cervical cancers caused by human papilloma virus (HPV) infections which vaccination can help prevent, as well as a host of tumours caused by tobacco smoke from cigarettes. The researchers said their report showed there is a powerful opportunity to transform the lives of millions of people. Some cancers are inevitable - either because of damage we unavoidably build up in our DNA as we age or because we inherit genes that put us at greater risk of the disease.


Long-Term Probabilistic Forecast of Vegetation Conditions Using Climate Attributes in the Four Corners Region

McPhillips, Erika, Lee, Hyeongseong, Xie, Xiangyu, Baylis, Kathy, Funk, Chris, Gu, Mengyang

arXiv.org Machine Learning

Weather conditions can drastically alter the state of crops and rangelands, and in turn, impact the incomes and food security of individuals worldwide. Satellite-based remote sensing offers an effective way to monitor vegetation and climate variables on regional and global scales. The annual peak Normalized Difference Vegetation Index (NDVI), derived from satellite observations, is closely associated with crop development, rangeland biomass, and vegetation growth. Although various machine learning methods have been developed to forecast NDVI over short time ranges, such as one-month-ahead predictions, long-term forecasting approaches, such as one-year-ahead predictions of vegetation conditions, are not yet available. To fill this gap, we develop a two-phase machine learning model to forecast the one-year-ahead peak NDVI over high-resolution grids, using the Four Corners region of the Southwestern United States as a testbed. In phase one, we identify informative climate attributes, including precipitation and maximum vapor pressure deficit, and develop the generalized parallel Gaussian process that captures the relationship between climate attributes and NDVI. In phase two, we forecast these climate attributes using historical data at least one year before the NDVI prediction month, which then serve as inputs to forecast the peak NDVI at each spatial grid. We developed open-source tools that outperform alternative methods for both gross NDVI and grid-based NDVI one-year forecasts, providing information that can help farmers and ranchers make actionable plans a year in advance.


The Download: chatbots for health, and US fights over AI regulation

MIT Technology Review

Plus: how wastewater tracking could help curb measles' rise in the US. Can ChatGPT Health do better? For the past two decades, there's been a clear first step for anyone who starts experiencing new medical symptoms: Look them up online. The practice was so common that it gained the pejorative moniker "Dr. But times are changing, and many medical-information seekers are now using LLMs. According to OpenAI, 230 million people ask ChatGPT health-related queries each week.


Heist game Relooted gets a release date

Engadget

Apple's Siri AI will be powered by Gemini Reclaim stolen African artifacts with your crew on February 10. The intriguing Africanfuturist heist game,, is out on February 10. Developed by independent South African studio Nyamakop, the game focuses on a ragtag crew from Johannesburg that liberates real-life African artifacts from a series of fictionalized Western museums. You have to carefully plan each heist with your fellow teammates, knowing where to place each crew member and how you're going to get in and out in one piece. Once you've grabbed the artifact you're looking for in each mission, an alarm will sound and you have a limited amount of time to escape, so good preparation is vital.


Large Language Models' Expert-level Global History Knowledge Benchmark (HiST-LLM)

Neural Information Processing Systems

Large Language Models (LLMs) have the potential to transform humanities and social science research, yet their history knowledge and comprehension at a graduate level remains untested. Benchmarking LLMs in history is particularly challenging, given that human knowledge of history is inherently unbalanced, with more information available on Western history and recent periods. We introduce the History Seshat Test for LLMs (HiST-LLM), based on a subset of the Seshat Global History Databank, which provides a structured representation of human historical knowledge, containing 36,000 data points across 600 historical societies and over 2,700 scholarly references. This dataset covers every major world region from the Neolithic period to the Industrial Revolution and includes information reviewed and assembled by history experts and graduate research assistants.


Mystery as flock of UFOs seen hovering above power station for more than a year

Daily Mail - Science & tech

Kimberly Guilfoyle's bitter reaction to Don Jr's engagement with Bettina Anderson as scorned ex insists she'wants what's best' for the first son Simone Biles is slammed by furious animal rights activists after allegedly chopping her dog's EARS off The full story of Nick Reiner and these murders is so much more unbearable than everyone thinks. Even Hollywood wouldn't dare write it: MAUREEN CALLAHAN I sneakily looked at my perfect son's phone... What a terrible mistake! Rob Reiner and his wife's cause of death revealed'It was a cover up': Kirsty MacColl's ex-husband speaks out 25 years on from Fairytale of New York singer's death... and says she was'killed by speedboat driven by the richest man in Mexico' Reiner family bombshell as insiders reveal who is paying for Nick's celebrity lawyer... their secret motive... and who will REALLY inherit $200m fortune Trump's border patrol boss gets in VERY public spat with city mayor as he gives him rude awakening Chilling new video of Nick Reiner making disturbing comments about murder... as friend reveals dad Rob's tragic failed attempt to save him: 'I'm going to kill that f***ing dog' Tara Reid speaks out for the first time since THAT video emerged... and tells KATIE HIND why she is convinced she was spiked after watching CCTV How Bettina Anderson's engagement ring measures up to Kimberly Guilfoyle's... and which Don Jr spent most money on Elon Musk is blasted on social media over'pathetic' comments about Sydney Sweeney's breasts Biohacker Bryan Johnson says he will be immortal in 15 years... as he finally'cracks' the secret to living forever Natalee Holloway's killer Joran van der Sloot attempts to take his own life inside maximum-security Peruvian prison Chilling new details of father's death a day before facing justice for leaving his daughter, 2, to die in a hot car Pouty dine-and-dash diva interrupts judge MULTIPLE times as she's hauled to court for bill-skipping spree Sign up for our US Editor's Picks newsletter to get all the biggest exclusive stories A small town sheriff has admitted he is perplexed by a series of mysterious flying objects which have been bewildering locals in his Wyoming community for more than a year. Unidentified flying objects [ UFOs ] have been regularly spotted for 13 months above the Jim Bridger Power Plant and Sweetwater County's Red Desert. John Grossnickle, the Sheriff of Sweetwater County, saw lit-up, drone-like objects as recently as December 13, his spokesman Jason Mower told Cowboy State Daily .


Is AI already conscious? Evidence is 'far too limited' to definitively say artificial intelligence hasn't made the leap, expert claims

Daily Mail - Science & tech

Rob Reiner and his wife's cause of death revealed Dan Bongino announces he's QUIT FBI to return to popular talk show The full story of Nick Reiner and these murders is so much more unbearable than everyone thinks. Even Hollywood wouldn't dare write it: MAUREEN CALLAHAN I sneakily looked at my perfect son's phone... What a terrible mistake! US car dealer charged with FRAUD after bankruptcy revealed depths of American's debt crisis Tara Reid speaks out for the first time since THAT video emerged... and tells KATIE HIND why she is convinced she was spiked after watching CCTV Chilling new details of father's death a day before facing justice for leaving his daughter, 2, to die in a hot car Pouty dine-and-dash diva interrupts judge MULTIPLE times as she's hauled to court for bill-skipping spree Karoline Leavitt close-up from Vanity Fair's Susie Wiles interview sparks fury: 'Shameful' Symptoms of deadly'super flu' sweeping the US explained and how to tell it apart from Covid Earthquakes stir fear in America's Heartland as deadly fault zone awakens Scandal rocks Trump's deportation force: DHS insiders say boss Kristi Noem's'lover' made'unethical, immoral' requests to agency leaders Disgraced Michigan coach Sherrone Moore had'long history' of domestic violence against victim of alleged knife attack, lawyer claims'Flowing red blood' surging in Persian Gulf sparks wild claims that God's biblical plagues have returned Evidence is'far too limited' to definitively say artificial intelligence hasn't made the leap, expert claims READ MORE: T here may already be a'slightly conscious' AI out in the world Artificial intelligence ( AI) is already helping to solve problems in finance, research and medicine. But could it be reaching consciousness? Dr Tom McClelland, a philosopher from the University of Cambridge has warned that current evidence is'far too limited' to rule this dystopian possibility out.


Fully Bayesian Spectral Clustering and Benchmarking with Uncertainty Quantification for Small Area Estimation

Fúquene-Patiño, Jairo

arXiv.org Machine Learning

In this work, inspired by machine learning techniques, we propose a new Bayesian model for Small Area Estimation (SAE), the Fay-Herriot model with Spectral Clustering (FH-SC). Unlike traditional approaches, clustering in FH-SC is based on spectral clustering algorithms that utilize external covariates, rather than geographical or administrative criteria. A major advantage of the FH-SC model is its flexibility in integrating existing SAE approaches, with or without clustering random effects. To enable benchmarking, we leverage the theoretical framework of posterior projections for constrained Bayesian inference and derive closed form expressions for the new Rao-Blackwell (RB) estimators of the posterior mean under the FH-SC model. Additionally, we introduce a novel measure of uncertainty for the benchmarked estimator, the Conditional Posterior Mean Square Error (CPMSE), which is generalizable to other Bayesian SAE estimators. We conduct model-based and data-based simulation studies to evaluate the frequentist properties of the CPMSE. The proposed methodology is motivated by a real case study involving the estimation of the proportion of households with internet access in the municipalities of Colombia. Finally, we also illustrate the advantages of FH-SC over existing Bayesian and frequentist approaches through our case study.


A Statistical Framework for Spatial Boundary Estimation and Change Detection: Application to the Sahel Sahara Climate Transition

Tivenan, Stephen, Sahoo, Indranil, Qian, Yanjun

arXiv.org Machine Learning

Spatial boundaries, such as ecological transitions or climatic regime interfaces, capture steep environmental gradients, and shifts in their structure can signal emerging environmental changes. Quantifying uncertainty in spatial boundary locations and formally testing for temporal shifts remains challenging, especially when boundaries are derived from noisy, gridded environmental data. We present a unified framework that combines heteroskedastic Gaussian process (GP) regression with a scaled Maximum Absolute Difference (MAD) Global Envelope Test (GET) to estimate spatial boundary curves and assess whether they evolve over time. The heteroskedastic GP provides a flexible probabilistic reconstruction of boundary lines, capturing spatially varying mean structure and location specific variability, while the test offers a rigorous hypothesis testing tool for detecting departures from expected boundary behaviors. Simulation studies show that the proposed method achieves the correct size under the null and high power for detecting local boundary shifts. Applying our framework to the Sahel Sahara transition zone, using annual Koppen Trewartha climate classifications from 1960 to 1989, we find no statistically significant decade scale changes in the arid and semi arid or semi arid and non arid interfaces. However, the method successfully identifies localized boundary shifts during the extreme drought years of 1983 and 1984, consistent with climate studies documenting regional anomalies in these interfaces during that period.