Journal of Biomimetics, Biomaterials and Biomedical Engineering Vol. 42

Erscheinungsjahr 2019
ISBN: 978-3-0357-2013-6
Verlag: Trans Tech Publications

Sonstiges, Englisch, Band Volume 42, 106 Seiten, Format (B × H): 125 mm x 142 mm, Gewicht: 200 g

Reihe: Journal of Biomimetics, Biomaterials and Biomedical Engineering

The 42nd volume of "Journal of Biomimetics, Biomaterials and Biomedical Engineering" contains papers that present to readers with the latest results of scientific research and engineering decisions in the fields of the biomechanics, utilization of modern biomaterials for implantation and in tissue engineering, biochemical methods and methods of processing the medical images for the early cancer diagnostic in the current medical practice. We hope that this volume will be useful for many researchers and engineers involved in different branches of modern biomedicine.

Autoren/Hrsg.

Nandyala, Sooraj Hussain

Fachgebiete

• Technische Wissenschaften Technik Allgemein Bionik, Biomimetik
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde Materialwissenschaft: Biomaterialien, Nanomaterialien, Kohlenstoff
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik

Inhaltsverzeichnis

Assessment of Muscles Fatigue during 400-Meters Running Strategies Based on the Surface EMG SignalsCollagen-Chitosan- Glycerol-HPMC Composite as Cornea Artificial CandidateThe Effects of Biodegradation on the Cytocompatibility of Bioresorbable Fe-Based Scaffolds: A ReviewUsing Chitosan Besides Nano Hydroxyapatite and Fluorohydroxyapatite Boost Dental Pulp Stem Cell Proliferation
In Vitro Nucleic Acid Hybridization for the Identification of High-Risk Human Papillomavirus (HPV) in Cervical Clinical SpecimensPortable and Rapid In Vivo Imaging of Tissue Oxygenation Changes Induced by Skin Perfusion PressureSegmented and Non-Segmented Skin Lesions Classification Using Transfer Learning and Adaptive Moment Learning Rate Technique Using Pretrained Convolutional Neural NetworkClassification of Mammograms Using Texture and CNN Based Extracted Features