Food research international (Ottawa, Ont.)
Jan 27, 2026
Elucidating the relationship between fruit optical properties and quality attributes is fundamental to nondestructive assessment. However, most existing studies rely on 'black box' chemometric models that correlate spectral signals with quality indic... read more
Across health care, traditional principles of biomedical ethics (autonomy, beneficence, nonmaleficence, and justice) form a base expectation for the use of new technology that applies equally to the spread of artificial intelligence (AI). These vague... read more
Proteins that impact phenotype and disease are often approximated by RNA expression, which poorly infers protein abundance. We developed DeepGxP, a deep-learning model trained on The Cancer Genome Atlas pan-cancer data, to predict protein abundance f... read more
Health inequalities are not static gradients of deprivation but emergent properties of complex, place-based social systems. This study applied a case-based complexity (CBC) approach, via the COMPLEX-IT platform, to analyse healthy life expectancy (HL... read more
The dataset presented in this article comprises anonymous transactional records and associated product metadata collected from a local Food and Beverages (F&B) Micro-Small-Medium Enterprise (MSME) operating in a local city in Indonesia. This data can... read more
We present an OpenStreetMap-derived multimodal dataset spanning 23 cities and 11,711 tile-level samples. For each 768 × 768 m tile, we provide an aligned image pair: (i) a stylized ecological baseline that generalizes green and water features togethe... read more
World generation is a fundamental capability for applications like video games, simulation, and robotics. However, existing approaches face three main obstacles: controllability, scalability, and efficiency. End-to-end scene generation models have be... read more
Visual Question Answering (VQA) often requires coupling fine-grained perception with factual knowledge beyond the input image. Prior multimodal Retrieval-Augmented Generation (MM-RAG) systems improve factual grounding but lack an internal policy for ... read more
We rigorously study the thermodynamic limit of deep neural networks (DNNS) and recurrent neural networks (RNNs), assuming that the activation functions are sigmoids. A thermodynamic limit is a continuous neural network, where the neurons form a conti... read more
Vision--language models (VLMs) achieve strong performance on many multimodal benchmarks but remain brittle on spatial reasoning tasks that require aligning abstract overhead representations with egocentric views. We introduce m2sv, a scalable benchma... read more
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