Parenting

H2HTalk: Evaluating Large Language Models as Emotional Companion

As digital emotional support needs grow, Large Language Model companions offer promising authentic, always-available empathy, though rigorous evaluation lags behind model advancement. We present Heart-to-Heart Talk (H2HTalk), a benchmark assessing companions across personality development and empathetic interaction, balancing emotional intelligence with linguistic fluency. H2HTalk features 4,650...

Predicting Weaning Weight of Romanov Lambs From Biometric Measurements Before Weaning Age Using Machine Learning Algorithms.

BACKGROUND: Machine learning systems learn from historical data to forecast future outcomes. In the context of livestock farming, machine learning can be utilized to predict variables such as growth rates, milk production and breeding success by analysing data related to animal health, nutrition and environmental conditions.

Innovations in Quail Welfare: Integrating Environmental Enrichment, Nutrition and Genetic Advances for Improved Health and Productivity.

The demand for ethical and sustainable poultry production is driving up the importance of quail welfare. Because quail meat and eggs are in high deman...

[Rethinking scientific integrity in plastic surgery: Reflections on editorial and institutional responsibilities].

Plastic surgery, by nature an innovative discipline, has historically relied on clinical case reports to advance its techniques. Often unique, these c...

Development and validation of an interpretable machine learning model for predicting hyperuricemia risk: Based on environmental chemical exposure.

Hyperuricemia is a global health concern, with environmental chemicals as risk factors. This study used data of multiple environmental chemical exposu...

A general deep learning model for predicting and classifying pea protein content via visible and near-infrared spectroscopy.

Rapid and accurate detection of pea protein content is crucial for breeding and ensuring food quality. This study introduces the PeaNet model, which e...

Preparation of Active On-Demand Antibacterial Hydrogel Epidermis Electrodes Based on Flora Balance Strategy for Intelligent Prostheses.

Hydrogel epidermis electrodes have demonstrated remarkable potential for stable electrophysiological signal acquisition in the field of intelligent pr...

Machine learning: An effective tool for monitoring and ensuring food safety, quality, and nutrition.

The domains of food safety, quality, and nutrition are inundated with complex datasets. Machine learning (ML) has emerged as a powerful tool in food s...

MMMG: A Massive, Multidisciplinary, Multi-Tier Generation Benchmark for Text-to-Image Reasoning

In this paper, we introduce knowledge image generation as a new task, alongside the Massive Multi-Discipline Multi-Tier Knowledge-Image Generation B...

AI Approaches to Homogeneous Catalysis with Transition Metal Complexes.

Artificial intelligence (AI) is transforming research in chemistry, including homogeneous catalysis with transition metals. Over the past 15 years, th...

VolTex: Food Volume Estimation using Text-Guided Segmentation and Neural Surface Reconstruction

Accurate food volume estimation is crucial for dietary monitoring, medical nutrition management, and food intake analysis. Existing 3D Food Volume e...

Predicting Stress, Anxiety, and Depression in Adult Men Based on Nutritional and Lifestyle Variables: A Comparative Analysis of Machine Learning Methods.

Mental health disorders like depression, anxiety, and stress (DAS) are rising globally. Understanding how diet and lifestyle influence these condition...

Multidimensional computational strategies enhance the thermostability of alpha-galactosidase.

Alpha-Galactosidase has significant industrial application value in food processing, animal nutrition and medical applications. Microbial-derived α-ga...

Ripen banana dataset: A comprehensive resource for carbide detection and ripening stage analysis to enhance food quality and agricultural efficiency.

We introduce the "Ripen Banana" dataset, a newly developed collection featuring two distinct classes of ripen banana images: carbide and non-carbide. ...

NLP for computational insights into nutritional impacts on colorectal cancer care.

Colorectal cancer (CRC) is one of the most prominent cancers globally, with its incidence rising among younger adults due to improved screening practi...

Artificial intelligence assisted nutritional risk evaluation model for critically ill patients: Integration of explainable machine learning in intensive care nutrition.

BACKGROUND AND OBJECTIVES: Critically ill patients require individualized nutrition support, with assessment tools like Nutrition Risk Screening 2002 ...

Constructing a predictive model of negative academic emotions in high school students based on machine learning methods.

Negative academic emotions reflect the negative experiences that learners encounter during the learning process. This study aims to explore the effect...

Artificial intelligence medical scribes in allied health: a solution in search of evidence?

Artificial intelligence (AI) medical scribes (AI scribes), which ambiently record and transcribe patient-clinician interactions into structured docume...

Advances in artificial intelligence for diabetes prediction: insights from a systematic literature review.

Diabetes mellitus (DM), a prevalent metabolic disorder, has significant global health implications. The advent of machine learning (ML) has revolution...

We have to go back, back to the future! Reflecting on 75 years of human factors in the UK to shape a future of responsible artificial intelligence innovation.

The origins of Human Factors (HF) are rooted in the Second World War. It is a sign of the times that 75 years on from the formation of the Ergonomics ...