arXiv:2603.28423v1 Announce Type: cross Abstract: We introduce a novel class of graphical models, termed profile graphical models, that represent, within a single graph, how an external factor influences the dependence structure of a multivariate set of variables. This class is quite general and includes multiple graphs and chain graphs as special cases. Profile graphical models capture the conditional distributions of a multivariate random vector given different levels of a risk factor, and learn how the conditional independence structure […]

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:::info Astounding Stories of Super-Science February, 2026, by Astounding Stories is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here. The Moors and the Fens, volume 1 (of 3) – Chapter XIII: The Spider and the Fly Astounding Stories of Super-Science February 2026: The Moors and the Fens, volume 1 (of 3) – Chapter XIII The Spider and the Fly By J. H. Riddell ::: Malcolm Frazer was quite correct in […]

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Cultural historian Thomas Berry issues a profound summons to reimagine humanity’s place within the living fabric of the Earth. He envisions a radical transformation—from a species that wounds its home to one that nurtures it—calling for the “resacralization of nature” and a renewal of our ecological consciousness. More than a philosophical reflection, Berry’s work is a moral and spiritual manifesto, demanding an overhaul of our ethics, politics, economics, and education. Only through this sweeping reorientation, he insists, can […]

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arXiv:2603.23668v1 Announce Type: new Abstract: The rapid deployment of machine learning across platforms from milliwatt-class TinyML devices to large language models has made energy efficiency a primary constraint for sustainable AI. Across these scales, performance and energy are increasingly limited by data movement and memory-system behavior rather than by arithmetic throughput alone. This work reviews energy efficient software hardware codesign methods spanning edge inference and training to datacenter-scale LLM serving, covering accelerator architectures (e.g., ASIC/FPGA dataflows, processing-/compute-in-memory designs) […]

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Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, yet early risk detection is often limited by available diagnostics. Carotid ultrasound, a non-invasive and widely accessible modality, encodes rich structural and hemodynamic information that is largely untapped. Here, we present a machine learning (ML) framework that extracts clinically meaningful representations of vascular damage (VD) from carotid ultrasound videos, using hypertension as a weak proxy label. The model learns robust features that are biologically plausible, interpretable, and strongly […]

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arXiv:2601.16233v1 Announce Type: new Abstract: HIV is a retrovirus that attacks the human immune system and can lead to death without proper treatment. In collaboration with the WHO and Wits University, we study how to improve the efficiency of HIV testing with the goal of eventual deployment, directly supporting progress toward UN Sustainable Development Goal 3.3. While prior work has demonstrated the promise of intelligent algorithms for sequential, network-based HIV testing, existing approaches rely on assumptions that are […]

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arXiv:2604.13050v1 Announce Type: new Abstract: Urban areas are intricate systems shaped by socioeconomic, environmental, and infrastructural factors, with land use patterns serving as aspects of urban morphology. This paper proposes a novel methodology leveraging frequent item set mining and unsupervised learning techniques to identify similar cities based on co-occurring land use patterns. The Copernicus program’s Urban Atlas data are used as source data. The methodology involves data preprocessing, pattern mining using the negFIN algorithm, postprocessing, and knowledge extraction […]

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