Motivation. Understanding the pan-cancer mutational landscape offers critical insights into the molecular mechanisms underlying tumorigenesis. While patient-level machine learning techniques have been widely employed to identify tumor subtypes, cohort-level clustering, where entire cancer types are grouped based on shared molecular features, has largely relied on classical statistical methods. Results. In this study, we introduce a novel unsupervised contrastive learning framework to cluster 43 cancer types based on coding mutation data derived from the COSMIC database. For each cancer type, we construct two complementary mutation signatures: a gene-level profile capturing nucleotide substitution patterns across the most frequently mutated genes, and a chromosome-level profile representing normalized substitution frequencies across chromosomes. These dual views are encoded using TabNet encoders and optimized via a multi-scale contrastive learning objective (NT-Xent loss) to learn unified cancer-type embeddings. We demonstrate that the resulting latent representations yield biologically meaningful clusters of cancer types, aligning with known mutational processes and tissue origins. Our work represents the first application of contrastive learning to cohort-level cancer clustering, offering a scalable and interpretable framework for mutation-driven cancer subtyping.

Poor security allowed inmates at a prison in the US to secretly build their own computers, an investigation has found. Prisoners at Marion Correctional Institution in Ohio used digital skills workshops and computer recycling schemes to steal parts and create their own devices from them. The prison's security staff only realised what was going on when the IT department received an alert about a computer on the Ohio Department of Rehabilitation and Correction's network exceeding its daily internet usage limit. They then found that the computer being used was also logged in to an absent member of staff's account. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.

The patter of automated machinery fills the air inside wire-basket manufacturer Marlin Steel's bustling factory in a rugged industrial section of this city. Maxi Cifarelli, 25, of Baltimore, peers through safety goggles at a flat screen, her left knee bent and heel resting on her chair. Two years after earning a fine arts degree from Towson University with a specialty in interdisciplinary object design, she now spends her work days working with a personality-free machine with a name to match: a computer numerical control, or CNC, router. With automation poised to sweep through the economy, some fear that it will kill more jobs than it creates. But Cifarelli's experience is the opposite. She befriended automation, instead of fighting it, and she has a job because of it.

The patter of automated machinery fills the air inside wire-basket manufacturer Marlin Steel's bustling factory in a rugged industrial section of this city. Maxi Cifarelli, 25, of Baltimore, peers through safety goggles at a flat screen, her left knee bent and heel resting on her chair. Two years after earning a fine arts degree from Towson University with a specialty in interdisciplinary object design, she now spends her work days working with a personality-free machine with a name to match: a computer numerical control, or CNC, router. With automation poised to sweep through the economy, some fear that it will kill more jobs than it creates. But Cifarelli's experience is the opposite. She befriended automation, instead of fighting it, and she has a job because of it.

Imagine custom shirts and shoes at mass production prices with same day delivery; imagine turbine parts produced at the airport where and when they are needed; imagine a new tooth made while you're in the dentist chair. The age of smart local manufacturing is just around the corner. Often called Industry 4.0, this new wave manufacturing incorporated connected devices (internet of things: IoT), cloud computing and machine learning. The term Industry 4.0 originated in 2011 with German government-funded research on advanced manufacturing. The second industrial revolution was mass production, starting around 1870, but best known for the assembly lines of Henry Ford 1913.

Imagine custom shirts and shoes at mass production prices with same day delivery; imagine turbine parts produced at the airport where and when they are needed; imagine a new tooth made while you're in the dentist chair. The age of smart local manufacturing is just around the corner. Often called Industry 4.0, this new wave manufacturing incorporated connected devices (internet of things: IoT), cloud computing and machine learning. The term Industry 4.0 originated in 2011 with German government-funded research on advanced manufacturing. The second industrial revolution was mass production, starting around 1870, but best known for the assembly lines of Henry Ford 1913.