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Advances in Physical Metallurgy
This volume focuses on the wealth of existing literature on physical metallurgy, and deals with materials in different states of order and the process of order evolution. It is a valuable reference by students and researchers in the field of materials science and metallurgy.
Index Medicus
Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.
Essentials of Tuberculosis in Children
SECTION 1 INTRODUCTION SECTION 2 EPIDEMIOLOGY SECTION 3 MICROBIOLOGY AND IMMUNOPATHOGENESIS SECTION 4 CLINICAL SPECTRUM SECTION 5 DIAGNOSIS SECTION 6 MANAGEMENT
Biostimulants in Plant Protection and Performance
Biostimulants (a diverse class of compounds including substances or microorganisms) are helpful in sustainable plants growth and development. They accelerate plant growth, yield, and chemical composition even under unfavorable conditions. The main biostimulants are nitrogen-containing compounds, humic materials, some specific compounds released by microbes, plants, and animals, various seaweed extracts, bio-based nanomaterials, phosphite, silicon, and so on. Additionally, new generation products and bioproducts are being developed for sustainable plant growth and protection. Some research works in the area of biotechnology and nanobiotechnology have shown improved sustainable plant growth an...
Approaches and Applications of Deep Learning in Virtual Medical Care
The recent advancements in the machine learning paradigm have various applications, specifically in the field of medical data analysis. Research has proven the high accuracy of deep learning algorithms, and they have become a standard choice for analyzing medical data, especially medical images, video, and electronic health records. Deep learning methods applied to electronic health records are contributing to understanding the evolution of chronic diseases and predicting the risk of developing those diseases. Approaches and Applications of Deep Learning in Virtual Medical Care considers the applications of deep learning in virtual medical care and delves into complex deep learning algorithms, calibrates models, and improves the predictions of the trained model on medical imaging. Covering topics such as big data and medical sensors, this critical reference source is ideal for researchers, academicians, practitioners, industry professionals, hospital workers, scholars, instructors, and students.
