Tandem near-infrared organic photodiodes (OPDs) for future application in artificial retinal implants (Conference Presentation)

2018 ◽  
Author(s):  
Giulio Simone ◽  
Dario Di Carlo ◽  
Stefan Meskers ◽  
René Janssen ◽  
Gerwin Gelinck
Keyword(s):  
Near Infrared ◽  
Future Application ◽  
Retinal Implants

scholarly journals Near-Infrared Tandem Organic Photodiodes for Future Application in Artificial Retinal Implants

2018 ◽  
Vol 30 (51) ◽  
pp. 1804678 ◽  
Author(s):  
Giulio Simone ◽  
Dario Di Carlo Rasi ◽  
Xander de Vries ◽  
Gaël H. L. Heintges ◽  
Stefan C. J. Meskers ◽  
...  
Keyword(s):  
Near Infrared ◽  
Future Application ◽  
Retinal Implants

scholarly journals Optical Mapping-Validated Machine Learning Improves Atrial Fibrillation Driver Detection by Multi-Electrode Mapping

2020 ◽  
Vol 13 (10) ◽  
Author(s):  
Alexander M. Zolotarev ◽  
Brian J. Hansen ◽  
Ekaterina A. Ivanova ◽  
Katelynn M. Helfrich ◽  
Ning Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Atrial Fibrillation ◽  
Near Infrared ◽  
Fourier Spectrum ◽  
Optical Mapping ◽  
Binary Classification ◽  
Future Application ◽  
Data Set ◽  
Frequency Spectra

Background: Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypothesized that application of machine learning to electrogram frequency spectra may accurately automate driver detection by MEM and add some objectivity to the interpretation of MEM findings. Methods: Temporally and spatially stable single AF drivers were mapped simultaneously in explanted human atria (n=11) by subsurface near-infrared optical mapping (NIOM; 0.3 mm 2 resolution) and 64-electrode MEM (higher density or lower density with 3 and 9 mm 2 resolution, respectively). Unipolar MEM and NIOM recordings were processed by Fourier transform analysis into 28 407 total Fourier spectra. Thirty-five features for machine learning were extracted from each Fourier spectrum. Results: Targeted driver ablation and NIOM activation maps efficiently defined the center and periphery of AF driver preferential tracks and provided validated annotations for driver versus nondriver electrodes in MEM arrays. Compared with analysis of single electrogram frequency features, averaging the features from each of the 8 neighboring electrodes, significantly improved classification of AF driver electrograms. The classification metrics increased when less strict annotation, including driver periphery electrodes, were added to driver center annotation. Notably, f1-score for the binary classification of higher-density catheter data set was significantly higher than that of lower-density catheter (0.81±0.02 versus 0.66±0.04, P <0.05). The trained algorithm correctly highlighted 86% of driver regions with higher density but only 80% with lower-density MEM arrays (81% for lower-density+higher-density arrays together). Conclusions: The machine learning model pretrained on Fourier spectrum features allows efficient classification of electrograms recordings as AF driver or nondriver compared with the NIOM gold-standard. Future application of NIOM-validated machine learning approach may improve the accuracy of AF driver detection for targeted ablation treatment in patients.

scholarly journals The principles, practices and some future applications of near infrared spectroscopy for predicting the nutritive value of foods for animals and humans

1997 ◽  
Vol 10 (1) ◽  
pp. 83-114 ◽  
Author(s):  
D. I. Givens ◽  
J. L. De Boever ◽  
E. R. Deaville
Keyword(s):  
Egg Production ◽  
Nutritive Value ◽  
Near Infrared ◽  
Starch Content ◽  
Animal Health ◽  
Nir Spectroscopy ◽  
Vital Role ◽  
Future Application ◽  
Current Application ◽  
The Future

AbstractThe current application and future potential of near infrared (NIR) spectroscopy in the evaluation of foods for domesticated animals and humans is enormous. Where used, NIR spectroscopy has revolutionized the analysis and nutritional evaluation of animal feeds and human foods by providing a rapid means of examination. The availability of accurate and rapid methods of evaluation is becoming increasingly important to meet the nutritional requirements of animals for meat, milk, wool and egg production. This is essential for efficient and economic animal production, to maintain animal health and to minimize environmental impact. Accurate evaluation methods are also needed in relation to national and international legislation that regulates the circulation, trade and inspection of foods and feeds, aids effective functioning of the market and guards the safety of animals and humans. The aim of this review is to outline the theory and principles of NIR spectroscopy and to focus primarily on its application in the field of animal nutrition. The vital role NIR spectroscopy is playing in the prediction of biologically meaningful feed characteristics, including data derived in vivo, is demonstrated particularly through its application to forage evaluation, but also in the examination of raw materials and compound feeds. While the applications of NIR spectroscopy to different foods and drinks are extensive, this review gives an overview only of selected reported applications including its use for predicting nutritive value (mainly water, protein, fat, sucrose and starch content), monitoring food processing and for food authentication. The review provides clear evidence that the future application of NIR spectroscopy will undoubtedly increase, playing a vital role in the authentication of the quality and origin of foods and feeds and enabling the complex methods of feed evaluation required in the future to be put into widespread use.

PREPARATION AND PHOTOLUMINESCENCE PROPERTIES OFNdVO4NANOTUBES IN AAO TEMPLATE

2009 ◽  
Vol 23 (22) ◽  
pp. 2647-2653 ◽  
Author(s):  
XIAO-NIU PENG ◽  
XIAN ZHANG ◽  
LIAO YU ◽  
LI ZHOU
Keyword(s):  
Electron Microscopy ◽  
Near Infrared ◽  
Light Emission ◽  
Sol Gel ◽  
Visible Region ◽  
Infrared Region ◽  
Future Application ◽  
Aao Template ◽  
Anodized Aluminum ◽  
Transmission Electron

Porous anodized aluminum oxide (AAO) template was combined with sol-gel method in this work for the fabrication of high-ordered NdVO4nanotube arrays. The diameter, length, and wall thickness of the nanotubes can be adjusted conveniently. The sample was characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), X-ray diffraction (XRD), absorption spectra, and photoluminescence spectra. The results show that these uniformly distributed, high-ordered, and parallel nanotubes have great light emission in both the visible region and near-infrared region due to their corresponding energy level transitions. With this method, future application of rare-earth hollow nanostructures will be widely extended.

scholarly journals The Role of Solar Energy (UV-VIS-NIR) as an Assistant for Sulfide Minerals Leaching and Its Potential Application for Metal Extraction

Minerals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 828
Author(s):  
Orlando Yepsen ◽  
Eugenia Araneda ◽  
Rodrigo Yepsen ◽  
Humberto Estay
Keyword(s):  
Energy Consumption ◽  
Solar Energy ◽  
Potential Application ◽  
Near Infrared ◽  
Renewable Energy Sources ◽  
Sulfide Minerals ◽  
Metal Extraction ◽  
Future Application ◽  
Processing Route

The mining industry is facing emerging challenges as a result of the increase in energy consumption and environmental demands. These facts have promoted the use of renewable energy sources, such as wind, geothermal and, mainly, solar energy. This paper discusses the role of solar energy (UV-VIS-NIR) in leaching processes, evaluating its potential application in metal extraction from sulfide minerals, based on photochemical mechanisms that promote the regeneration of ferric iron or the so called ferrous iron cycling. The present paper discusses the possibility that ultraviolet, visible light and near infrared irradiation (e.g., sunlight provided) can assist the leaching processes in two main ways: by the oxidation of sulfide minerals through in-situ generated Fenton-like reactions, and by the photochemical activation of semiconductor minerals that contain transition metals (Fe, Cu, and Cr, among others). Thus, this paper provides theoretical support to move towards the future application of photoleaching, which consist of a leaching process assisted by UV, VIS, and NIR irradiation. This technology can be considered a promising mineral processing route, using direct photochemical solar energy that can reduce the energy consumption (electricity, fuels) and the environmental impact, opening an opportunity for an alternative method of metal extraction from sulfide ores.

scholarly journals Recent advances in near-infrared II imaging technology for biological detection

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Nan-nan Zhang ◽  
Chen-ying Lu ◽  
Min-jiang Chen ◽  
Xiao-ling Xu ◽  
Gao-feng Shu ◽  
...  
Keyword(s):  
Optical Imaging ◽  
Near Infrared ◽  
Early Stage ◽  
Signal To Noise Ratio ◽  
Stokes Shift ◽  
Biological Tissues ◽  
Dynamic Monitoring ◽  
Future Application ◽  
High Signal ◽  
Imaging Technology

AbstractMolecular imaging technology enables us to observe the physiological or pathological processes in living tissue at the molecular level to accurately diagnose diseases at an early stage. Optical imaging can be employed to achieve the dynamic monitoring of tissue and pathological processes and has promising applications in biomedicine. The traditional first near-infrared (NIR-I) window (NIR-I, range from 700 to 900 nm) imaging technique has been available for more than two decades and has been extensively utilized in clinical diagnosis, treatment and scientific research. Compared with NIR-I, the second NIR window optical imaging (NIR-II, range from 1000 to 1700 nm) technology has low autofluorescence, a high signal-to-noise ratio, a high tissue penetration depth and a large Stokes shift. Recently, this technology has attracted significant attention and has also become a heavily researched topic in biomedicine. In this study, the optical characteristics of different fluorescence nanoprobes and the latest reports regarding the application of NIR-II nanoprobes in different biological tissues will be described. Furthermore, the existing problems and future application perspectives of NIR-II optical imaging probes will also be discussed.

scholarly journals Predicting plant available phosphorus using infrared spectroscopy with consideration for future mobile sensing applications in precision farming

2019 ◽  
Vol 21 (4) ◽  
pp. 737-761 ◽  
Author(s):  
Stefan Pätzold ◽  
Matthias Leenen ◽  
Peter Frizen ◽  
Tobias Heggemann ◽  
Peter Wagner ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Near Infrared ◽  
Model Performance ◽  
Precision Farming ◽  
Future Application ◽  
Available Phosphorus ◽  
Agricultural Practice ◽  
Mir Spectroscopy ◽  
Sensing Applications ◽  
Rapid Discrimination

Abstract Phosphorus (P) fertilisation recommendations rely primarily on soil content of plant available P (Pavl) that vary spatially within farm fields. Spatially optimized P fertilisation for precision farming requires reliable, rapid and non-invasive Pavl determination. This laboratory study aimed to test and to compare visible-near infrared (Vis–NIR) and mid-infrared (MIR) spectroscopy for Pavl prediction with emphasis on future application in precision agriculture. After calibration with the conventional calcium acetate lactate (CAL) extraction method, limitations of Vis–NIRS and MIRS to predict Pavl were evaluated in loess topsoil samples from different fields at six localities. Overall calibration with 477 (Vis–NIRS) and 586 (MIRS) samples yielded satisfactory model performance (R2 0.70 and 0.72; RPD 1.8 and 1.9, respectively). Local Vis–NIRS models yielded better results with R2 up to 0.93 and RPD up to 3.8. For MIRS, results were comparable. However, an overall model to predict Pavl on independent test data partly failed. Sampling date, pre-crop harvest residues and fertilising regime affected model transferability. Varying transferability could partly be explained after deriving the cellulose absorption index from the Vis–NIR spectra. In 62 (Vis–NIRS) and 67% (MIRS) of all samples, prediction matched the correct Pavl content class. Rapid discrimination between high, optimal and low P classes could be carried out on many samples from single fields thus marking an improvement over the common practice. However, Pavl determination by means of IR spectroscopy is not yet satisfactory for determination of precision fertilizer dosage. For introduction into agricultural practice, a standardized sampling protocol is recommended to help achieve reliable spectroscopic Pavl prediction.

Construction of a near-infrared responsive upconversion nanoplatform against hypoxic tumors via NO-enhanced photodynamic therapy

Nanoscale ◽  
2020 ◽  
Vol 12 (14) ◽  
pp. 7875-7887 ◽  
Author(s):  
Ying Lan ◽  
Xiaohui Zhu ◽  
Ming Tang ◽  
Yihan Wu ◽  
Jing Zhang ◽  
...  
Keyword(s):  
Photodynamic Therapy ◽  
Near Infrared ◽  
Upconversion Nanoparticles

A near-infrared (NIR) activated theranostic nanoplatform based on upconversion nanoparticles (UCNPs) is developed in order to overcome the hypoxia-associated resistance in photodynamic therapy by photo-release of NO upon NIR illumination.

A nitroreductase-activatable near-infrared theranostic photosensitizer for photodynamic therapy under mild hypoxia

2020 ◽  
Vol 56 (43) ◽  
pp. 5819-5822
Author(s):  
Jing Zheng ◽  
Yongzhuo Liu ◽  
Fengling Song ◽  
Long Jiao ◽  
Yingnan Wu ◽  
...  
Keyword(s):  
Photodynamic Therapy ◽  
Triplet State ◽  
Near Infrared ◽  
Mild Hypoxia

In this study, a near-infrared (NIR) theranostic photosensitizer was developed based on a heptamethine aminocyanine dye with a long-lived triplet state.

Fluorescent proteins for in vivo imaging, where's the biliverdin?

2020 ◽  
Vol 48 (6) ◽  
pp. 2657-2667
Author(s):  
Felipe Montecinos-Franjola ◽  
John Y. Lin ◽  
Erik A. Rodriguez
Keyword(s):  
Hydrogen Peroxide ◽  
In Vivo Imaging ◽  
Near Infrared ◽  
Fluorescent Protein ◽  
Fluorescent Proteins ◽  
Fluorescent Imaging ◽  
Infrared Light ◽  
Red Fluorescent Protein ◽  
Color Palette

Noninvasive fluorescent imaging requires far-red and near-infrared fluorescent proteins for deeper imaging. Near-infrared light penetrates biological tissue with blood vessels due to low absorbance, scattering, and reflection of light and has a greater signal-to-noise due to less autofluorescence. Far-red and near-infrared fluorescent proteins absorb light &gt;600 nm to expand the color palette for imaging multiple biosensors and noninvasive in vivo imaging. The ideal fluorescent proteins are bright, photobleach minimally, express well in the desired cells, do not oligomerize, and generate or incorporate exogenous fluorophores efficiently. Coral-derived red fluorescent proteins require oxygen for fluorophore formation and release two hydrogen peroxide molecules. New fluorescent proteins based on phytochrome and phycobiliproteins use biliverdin IXα as fluorophores, do not require oxygen for maturation to image anaerobic organisms and tumor core, and do not generate hydrogen peroxide. The small Ultra-Red Fluorescent Protein (smURFP) was evolved from a cyanobacterial phycobiliprotein to covalently attach biliverdin as an exogenous fluorophore. The small Ultra-Red Fluorescent Protein is biophysically as bright as the enhanced green fluorescent protein, is exceptionally photostable, used for biosensor development, and visible in living mice. Novel applications of smURFP include in vitro protein diagnostics with attomolar (10−18 M) sensitivity, encapsulation in viral particles, and fluorescent protein nanoparticles. However, the availability of biliverdin limits the fluorescence of biliverdin-attaching fluorescent proteins; hence, extra biliverdin is needed to enhance brightness. New methods for improved biliverdin bioavailability are necessary to develop improved bright far-red and near-infrared fluorescent proteins for noninvasive imaging in vivo.

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