Enhanced-performance flexible pressure sensors enabled by synergistic effect of hierarchical porous structures for motion sensing and deep learning-assisted speech recognition.

Comparative evaluation of SARS-CoV-2 antigens as capture and detection elements in an in-house antigen-based ELISA for COVID-19 total antibody detection.

From hatch to hen: A lifecycle perspective on acoustic-based poultry behaviour and health monitoring

Phenylalanine (Phe), an essential aromatic amino acid, is emerging as a potential biomarker of metabolic and health status in animals. Altered Phe concentrations reflect changes in metabolic, inflammatory, and disease processes. In companion animals, shifts in serum or biofluid Phe have been linked to hepatopathies, inflammatory enteropathies, and neoplastic conditions. In livestock, variations in milk or serum Phe accompany mastitis, metabolic stress, lameness, and other production-related disorders. Evidence for cats, horses, poultry, and aquaculture species remains limited. Interpretation is complicated by analytical variability, small sample sizes, and confounding factors such as diet, stress, and microbiome composition. Non-invasive sampling of milk, urine, saliva, and breath, shows promise for Phe monitoring across animal species. Advances in multi-omics, particularly metabolomics, proteomics, and microbiome analyses, can clarify mechanisms and support development of composite biomarker panels. This review evaluates current evidence on Phe as a biomarker across species, highlights gaps in research coverage and methodology, and outlines priorities for future work. Expanding studies to underrepresented species, standardizing measurement protocols, and conducting longitudinal research. Addressing these priorities is essential to establish Phe as a robust biomarker, for veterinary diagnostics, health monitoring, and the optimization of animal welfare and production systems. SHORT SUMMARY: This review looks at phenylalanine (Phe), an amino acid, as a possible health indicator in animals. Changes in Phe levels may show problems with metabolism, inflammation, or disease. Evidence is strongest for dogs and dairy cows, but limited for cats, horses, poultry, and fish. Results vary due to measurement methods and other factors. Future studies should standardize testing, include more species, and combine methods to improve Phe's usefulness in monitoring animal health.

Towards wearable electronic devices: A high linearity bionic flexible stretchable sensor based on MXene/GO nanocomposites and gradient stiffness strategy.

Experimental data for electrochemical impedance characterization of Li-ion batteries under varying state of charge, current amplitude and rest time.

A digital twin for diesel engines: Operator-infused physics-informed neural networks with transfer learning for engine health monitoring

A multi-mode coupling damage classification method for composite structures based on acoustic emission signal decomposition.

Efficient model-assisted probability of detection in guided-wave structural health monitoring systems

The ConcreteCARB dataset provides a comprehensive repository of 903 high-resolution images of concrete surfaces evaluated using the phenolphthalein test for carbonation detection. This data was collected under controlled laboratory conditions and aims to support artificial intelligence applications in civil engineering, especially in structural health monitoring tasks. The images are systematically organized into two distinct classes: "Carbonated Samples" and "No Carbonation Presence," enabling binary classification approaches. All samples were manually tested, split, and visually labelled by expert engineers to ensure reliable ground-truth classification, in accordance with standardized procedures. The dataset includes images of concrete prism elements fabricated with varying mix designs, incorporating different water-cement ratios and additives, such as industrial silica waste and natural admixtures derived from Opuntia ficus-indica. The specimens were subjected to natural atmospheric carbonation conditions for 180 days, and their carbonation fronts were revealed by phenolphthalein staining. The samples were then split manually with a chisel and hammer, and photographic documentation was performed with a Samsung SM-S901U1 smartphone using predefined settings to ensure consistency and quality across the dataset. ConcreteCARB is intended for researchers, engineers, and data scientists working on machine learning, deep learning, and computer vision solutions for concrete diagnostics. It provides valuable training and benchmarking data for the development of automated detection, classification, and segmentation models for carbonation damage assessment. Furthermore, the dataset can serve as a foundational tool for cross-comparative studies on the efficacy of AI techniques in materials degradation analysis. The openly accessible nature of the dataset through a public repository supports reproducibility and encourages the extension of AI applications in concrete durability and sustainability studies.

Dynamic borax-crosslinked transparent and antifreezing tragacanth gum-glycerol hydrogel for biomedical use.

Spatiotemporal collaborative digital twin structural health monitoring based on data mechanism fusion

Static component of nonlinear guided wave as a preferable indicator of creep damage in superalloys.

AI-Driven nanofiber platforms for essential oil delivery in dry period cows: a sustainable strategy against mastitis and antimicrobial resistance.

Structural health monitoring of offshore wind turbine towers under sparse sensor scenarios based on SEREP-iFEM

Edge-to-cloud computing and intelligence for IoT-based Structural Health Monitoring: A comprehensive review

Machine-learning-optimized T3C2Tx/Bi2Se3 nanoflower-modified screen-printed electrodes for electrochemical detection of trace Pb2+ and Cd2+ in artificial sweat.

Crowdsensing-based automated operational modal analysis for indirect bridge structural health monitoring

Decadal change (2015-2025) in seagrass cover, species composition and ecosystem quality in eastern Bintan marine protected area, Indonesia.

Does Switching to Consumer-Directed Personal Care Impact Health and Service Utilization Among Medicaid Enrollees in the New York Metropolitan Area?