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Angiogenesis is the growth of blood vessels from the existing vasculature. The field of angiogenesis has grown enormously in the past 30 years, with only 40 papers published in 1980 and nearly 6000 in 2010. Why has there been this explosive growth in angiogenesis research? Angiogenic therapies provide a potential to conquer cancer, heart diseases, and more than 70 of life's most threatening medical conditions. The lives of at least 1 billion people worldwide could be improved with angiogenic therapy, according to the Angiogenesis Foundation. In this little book, we provide a simple approach to understand the essential elements of the angiogenic process, we critique the most powerful angiogenesis assays that are used to discover proangiogenic and antiangiogenic substances, and we provide an in-depth physiological perspective on how angiogenesis is regulated in normal, healthy tissues of the human body. All tissues of the body require a continuous supply of oxygen to burn metabolic substrates that are needed for energy. Oxygen is conducted to these tissues by blood capillaries: more capillaries can improve tissue oxygenation and thus enhance energy production; fewer capillaries can lead to hypoxia and even anoxia in the tissues. This means that angiogenic therapies designed to control the growth and regression of blood capillaries can be used to improve the survival of poorly perfused tissues that are essential to the body (heart, brain, skeletal muscle, etc.) and to rid the body of unwanted tissues (tumors).
Neovascularization. --- Neovascularization, Physiologic. --- Neovascularization, Pathologic. --- angiogenesis --- angiogenic assays --- oxygen --- hypoxia --- hyperoxia --- homeostasis --- angiogenic growth factors --- vascular endothelial growth factor (VEGF) --- microcirculation --- autoregulation --- endothelial cells --- adenosine --- feedback regulation --- lymphatics --- lymphangiogenesis
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The Special Issue "Fiber Optic Sensors in Chemical and Biological Applications” gathers recent original papers. The subjects of the papers cover a broad range of optical fiber chemical sensors and biosensors applied for regulation in bioreactors, to novel concepts of intrinsic optical fiber sensors.
fiber optic sensor --- gold nanoparticles --- localized surface plasmon resonance --- mercury --- ppb --- refractive index sensor --- gas sensor --- hollow-core photonic crystal fiber --- Mach–Zehnder interferometer --- whole-cell biosensor --- bioluminescent bioreporter --- optical fiber biosensor --- toluene --- Pseudomonas putida TVA8 --- Escherichia coli 652T7 --- fiber optics --- long period grating --- fiber optical sensors --- refractive index --- chemical sensing --- mercapto compound --- yeast cultivation --- feedback regulation --- glucose detection --- optical biosensor --- laser-induced plasma spectroscopy --- microchip laser --- hair analysis --- OFDR type DAS --- phase fading solution --- high SNR --- real-time events detection --- ammonia detection --- layer-by-layer --- U-bent optical fiber --- porphyrin --- poly(styrene sulfonate) --- diazo resin --- photocrosslinking
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Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems.
digital filter --- finite field algebra --- conversion device --- module --- memory device --- residue --- feedback regulation --- digital signal analysis --- control efficacy --- residue number system --- redundant residue number system --- modular division --- fraction --- algorithm --- mathematical models of digital signal processing --- digital filtering --- maximum correntropy --- impulsive noise --- sparse channel estimation --- discrete wavelet transform --- medical imaging --- 3D image processing --- quantization noise --- harmonic wavelets --- classification --- kNN-algorithm --- deep neural networks --- machine learning --- Fourier transform --- short-time Fourier transform --- wavelet transform --- spectrogram --- confusion matrix --- ROC curve --- 3D model --- prosthetic design --- orientation --- positioning --- reconstruction --- speech enhancement --- adaptive filter --- microphone array --- sub-band processing --- filter bank --- posture classification --- skeleton detection --- motion capture --- exercise classification --- virtual rehabilitation --- wood defect --- CNN --- ELM --- genetic algorithm --- detection
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Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems.
Information technology industries --- digital filter --- finite field algebra --- conversion device --- module --- memory device --- residue --- feedback regulation --- digital signal analysis --- control efficacy --- residue number system --- redundant residue number system --- modular division --- fraction --- algorithm --- mathematical models of digital signal processing --- digital filtering --- maximum correntropy --- impulsive noise --- sparse channel estimation --- discrete wavelet transform --- medical imaging --- 3D image processing --- quantization noise --- harmonic wavelets --- classification --- kNN-algorithm --- deep neural networks --- machine learning --- Fourier transform --- short-time Fourier transform --- wavelet transform --- spectrogram --- confusion matrix --- ROC curve --- 3D model --- prosthetic design --- orientation --- positioning --- reconstruction --- speech enhancement --- adaptive filter --- microphone array --- sub-band processing --- filter bank --- posture classification --- skeleton detection --- motion capture --- exercise classification --- virtual rehabilitation --- wood defect --- CNN --- ELM --- genetic algorithm --- detection --- digital filter --- finite field algebra --- conversion device --- module --- memory device --- residue --- feedback regulation --- digital signal analysis --- control efficacy --- residue number system --- redundant residue number system --- modular division --- fraction --- algorithm --- mathematical models of digital signal processing --- digital filtering --- maximum correntropy --- impulsive noise --- sparse channel estimation --- discrete wavelet transform --- medical imaging --- 3D image processing --- quantization noise --- harmonic wavelets --- classification --- kNN-algorithm --- deep neural networks --- machine learning --- Fourier transform --- short-time Fourier transform --- wavelet transform --- spectrogram --- confusion matrix --- ROC curve --- 3D model --- prosthetic design --- orientation --- positioning --- reconstruction --- speech enhancement --- adaptive filter --- microphone array --- sub-band processing --- filter bank --- posture classification --- skeleton detection --- motion capture --- exercise classification --- virtual rehabilitation --- wood defect --- CNN --- ELM --- genetic algorithm --- detection
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The Special Issue "Fiber Optic Sensors in Chemical and Biological Applications” gathers recent original papers. The subjects of the papers cover a broad range of optical fiber chemical sensors and biosensors applied for regulation in bioreactors, to novel concepts of intrinsic optical fiber sensors.
Research & information: general --- Biology, life sciences --- fiber optic sensor --- gold nanoparticles --- localized surface plasmon resonance --- mercury --- ppb --- refractive index sensor --- gas sensor --- hollow-core photonic crystal fiber --- Mach–Zehnder interferometer --- whole-cell biosensor --- bioluminescent bioreporter --- optical fiber biosensor --- toluene --- Pseudomonas putida TVA8 --- Escherichia coli 652T7 --- fiber optics --- long period grating --- fiber optical sensors --- refractive index --- chemical sensing --- mercapto compound --- yeast cultivation --- feedback regulation --- glucose detection --- optical biosensor --- laser-induced plasma spectroscopy --- microchip laser --- hair analysis --- OFDR type DAS --- phase fading solution --- high SNR --- real-time events detection --- ammonia detection --- layer-by-layer --- U-bent optical fiber --- porphyrin --- poly(styrene sulfonate) --- diazo resin --- photocrosslinking --- fiber optic sensor --- gold nanoparticles --- localized surface plasmon resonance --- mercury --- ppb --- refractive index sensor --- gas sensor --- hollow-core photonic crystal fiber --- Mach–Zehnder interferometer --- whole-cell biosensor --- bioluminescent bioreporter --- optical fiber biosensor --- toluene --- Pseudomonas putida TVA8 --- Escherichia coli 652T7 --- fiber optics --- long period grating --- fiber optical sensors --- refractive index --- chemical sensing --- mercapto compound --- yeast cultivation --- feedback regulation --- glucose detection --- optical biosensor --- laser-induced plasma spectroscopy --- microchip laser --- hair analysis --- OFDR type DAS --- phase fading solution --- high SNR --- real-time events detection --- ammonia detection --- layer-by-layer --- U-bent optical fiber --- porphyrin --- poly(styrene sulfonate) --- diazo resin --- photocrosslinking
Choose an application
Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems.
Information technology industries --- digital filter --- finite field algebra --- conversion device --- module --- memory device --- residue --- feedback regulation --- digital signal analysis --- control efficacy --- residue number system --- redundant residue number system --- modular division --- fraction --- algorithm --- mathematical models of digital signal processing --- digital filtering --- maximum correntropy --- impulsive noise --- sparse channel estimation --- discrete wavelet transform --- medical imaging --- 3D image processing --- quantization noise --- harmonic wavelets --- classification --- kNN-algorithm --- deep neural networks --- machine learning --- Fourier transform --- short-time Fourier transform --- wavelet transform --- spectrogram --- confusion matrix --- ROC curve --- 3D model --- prosthetic design --- orientation --- positioning --- reconstruction --- speech enhancement --- adaptive filter --- microphone array --- sub-band processing --- filter bank --- posture classification --- skeleton detection --- motion capture --- exercise classification --- virtual rehabilitation --- wood defect --- CNN --- ELM --- genetic algorithm --- detection
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