Recording microscale variations in snowpack layering using near-infrared photography

AbstractDeposition of snow from precipitation and wind events creates layering within seasonal snowpacks. The thickness and horizontal continuity of layers within seasonal snowpacks can be highly variable, due to snow blowing around topography and vegetation, and this has important implications for hydrology, remote sensing and avalanche forecasting. In this paper, we present practical field and post-processing protocols for recording lateral variations in snow stratigraphy using near-infrared (NIR) photography. A Fuji S9100 digital camera, modified to be sensitive to NIR wavelengths, was mounted on a rail system that allowed for rapid imaging of a 10 m long snow trench excavated on the north side of Toolik Lake, Alaska (68°38′ N, 149°36′ W). Post-processing of the images included removal of lens distortion and vignetting. A tape measure running along the base of the trench provided known locations (control points) that permitted scaling and georeferencing. Snow layer heights estimated from the NIR images compared well with manual stratigraphic measurements made at 0.2 m intervals along the trench (n = 357, R2 = 0.97). Considerably greater stratigraphic detail was captured by the NIR images than in the manually recorded profiles. NIR imaging of snow trenches using the described protocols is an efficient tool for quantifying continuous microscale variations in snow layers and associated properties.

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The Role of NIR Fluorescence in MDR Cancer Treatment: From Targeted Imaging to Phototherapy

Current Medicinal Chemistry ◽

10.2174/0929867326666190627123719 ◽

2020 ◽

Vol 27 (33) ◽

pp. 5510-5529

Author(s):

Zengtao Wang ◽

Qingqing Meng ◽

Shaoshun Li

Keyword(s):

Cancer Treatment ◽

Near Infrared ◽

Combined Therapy ◽

Efflux Pumps ◽

Cross Resistance ◽

Great Promise ◽

Drug Efflux ◽

Nir Dyes ◽

Nir Imaging ◽

Drug Efflux Pumps

Background: Multidrug Resistance (MDR) is defined as a cross-resistance of cancer cells to various chemotherapeutics and has been demonstrated to correlate with drug efflux pumps. Visualization of drug efflux pumps is useful to pre-select patients who may be insensitive to chemotherapy, thus preventing patients from unnecessary treatment. Near-Infrared (NIR) imaging is an attractive approach to monitoring MDR due to its low tissue autofluorescence and deep tissue penetration. Molecular NIR imaging of MDR cancers requires stable probes targeting biomarkers with high specificity and affinity. Objective: This article aims to provide a concise review of novel NIR probes and their applications in MDR cancer treatment. Results: Recently, extensive research has been performed to develop novel NIR probes and several strategies display great promise. These strategies include chemical conjugation between NIR dyes and ligands targeting MDR-associated biomarkers, native NIR dyes with inherent targeting ability, activatable NIR probes as well as NIR dyes loaded nanoparticles. Moreover, NIR probes have been widely employed for photothermal and photodynamic therapy in cancer treatment, which combine with other modalities to overcome MDR. With the rapid advancing of nanotechnology, various nanoparticles are incorporated with NIR dyes to provide multifunctional platforms for controlled drug delivery and combined therapy to combat MDR. The construction of these probes for MDR cancers targeted NIR imaging and phototherapy will be discussed. Multimodal nanoscale platform which integrates MDR monitoring and combined therapy will also be encompassed. Conclusion: We believe these NIR probes project a promising approach for diagnosis and therapy of MDR cancers, thus holding great potential to reach clinical settings in cancer treatment.

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Performance Evaluation of Dorsal Vein Network of Hand Imaging Using Relative Total Variation-Based Regularization for Smoothing Technique in a Miniaturized Vein Imaging System: A Pilot Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18041548 ◽

2021 ◽

Vol 18 (4) ◽

pp. 1548 ◽

Cited By ~ 1

Author(s):

Kyuseok Kim ◽

Hyun-Woo Jeong ◽

Youngjin Lee

Keyword(s):

Image Quality ◽

Total Variation ◽

Near Infrared ◽

Imaging System ◽

Histogram Equalization ◽

Evaluation Performance ◽

Visual Evaluation ◽

Évaluation Performance ◽

Nir Imaging ◽

Relative Total Variation

Vein puncture is commonly used for blood sampling, and accurately locating the blood vessel is an important challenge in the field of diagnostic tests. Imaging systems based on near-infrared (NIR) light are widely used for accurate human vein puncture. In particular, segmentation of a region of interest using the obtained NIR image is an important field, and research for improving the image quality by removing noise and enhancing the image contrast is being widely conducted. In this paper, we propose an effective model in which the relative total variation (RTV) regularization algorithm and contrast-limited adaptive histogram equalization (CLAHE) are combined, whereby some major edge information can be better preserved. In our previous study, we developed a miniaturized NIR imaging system using light with a wavelength of 720–1100 nm. We evaluated the usefulness of the proposed algorithm by applying it to images acquired by the developed NIR imaging system. Compared with the conventional algorithm, when the proposed method was applied to the NIR image, the visual evaluation performance and quantitative evaluation performance were enhanced. In particular, when the proposed algorithm was applied, the coefficient of variation was improved by a factor of 15.77 compared with the basic image. The main advantages of our algorithm are the high noise reduction efficiency, which is beneficial for reducing the amount of undesirable information, and better contrast. In conclusion, the applicability and usefulness of the algorithm combining the RTV approach and CLAHE for NIR images were demonstrated, and the proposed model can achieve a high image quality.

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Development of a Novel SNAP-Epitope Tag/Near-Infrared Imaging Assay to Quantify G Protein-Coupled Receptor Degradation in Human Cells

SLAS DISCOVERY Advancing Life Sciences ◽

10.1177/2472555220979793 ◽

2021 ◽

pp. 247255522097979

Author(s):

Kyung-Soon Lee ◽

Edelmar Navaluna ◽

Nicole M. Marsh ◽

Eric M. Janezic ◽

Chris Hague

Keyword(s):

G Protein ◽

Adrenergic Receptor ◽

Near Infrared ◽

Human Cells ◽

Receptor Subtypes ◽

G Protein Coupled Receptor ◽

Functional Responses ◽

Epitope Tag ◽

Nir Imaging ◽

G Protein Coupled

We have developed a novel reporter assay that leverages SNAP-epitope tag/near-infrared (NIR) imaging technology to monitor G protein-coupled receptor (GPCR) degradation in human cell lines. N-terminal SNAP-tagged GPCRs were subcloned and expressed in human embryonic kidney (HEK) 293 cells and then subjected to 24 h of cycloheximide (CHX)-chase degradation assays to quantify receptor degradation half-lives ( t1/2) using LICOR NIR imaging–polyacrylamide gel electrophoresis (PAGE) analysis. Thus far, we have used this method to quantify t1/2 for all nine adrenergic (ADRA1A, ADRA1B, ADRA1D, ADRA2A, ADRA2B, ADRA2C, ADRB1, ADRB2, ADRB3), five somatostatin (SSTR1, SSTR2, SSTR3, SSTR4, SSTR5), four chemokine (CXCR1, CXCR2, CXCR3, CXCR5), and three 5-HT2 (5HT2A, 5HT2B, 5HT2C) receptor subtypes. SNAP-GPCR-CHX degradation t1/2 values ranged from 0.52 h (ADRA1D) to 5.5 h (SSTR3). On the contrary, both the SNAP-tag alone and SNAP-tagged and endogenous β-actin were resistant to degradation with CHX treatment. Treatment with the proteasome inhibitor bortezomib produced significant but variable increases in SNAP-GPCR protein expression levels, indicating that SNAP-GPCR degradation primarily occurs through the proteasome. Remarkably, endogenous β2-adrenergic receptor/ADRB2 dynamic mass redistribution functional responses to norepinephrine were significantly decreased following CHX treatment, with a time course equivalent to that observed with the SNAP-ADRB2 degradation assay. We subsequently adapted this assay into a 96-well glass-bottom plate format to facilitate high-throughput GPCR degradation screening. t1/2 values quantified for the α1-adrenergic receptor subtypes (ADRA1A, ADRA1B, ADR1D) using the 96-well-plate format correlated with t1/2 values quantified using NIR-PAGE imaging analysis. In summary, this novel assay permits precise quantitative analysis of GPCR degradation in human cells and can be readily adapted to quantify degradation for any membrane protein of interest.

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Snow fracture in relation to slab avalanche release: critical state for the onset of crack propagation

The Cryosphere ◽

10.5194/tc-11-217-2017 ◽

2017 ◽

Vol 11 (1) ◽

pp. 217-228 ◽

Cited By ~ 30

Author(s):

Johan Gaume ◽

Alec van Herwijnen ◽

Guillaume Chambon ◽

Nander Wever ◽

Jürg Schweizer

Keyword(s):

Crack Propagation ◽

Slope Angle ◽

Critical Length ◽

Snow Layer ◽

Critical Crack ◽

Critical Crack Length ◽

New Model ◽

Avalanche Forecasting ◽

Weak Layer ◽

Recent Developments

Abstract. The failure of a weak snow layer buried below cohesive slab layers is a necessary, but insufficient, condition for the release of a dry-snow slab avalanche. The size of the crack in the weak layer must also exceed a critical length to propagate across a slope. In contrast to pioneering shear-based approaches, recent developments account for weak layer collapse and allow for better explaining typical observations of remote triggering from low-angle terrain. However, these new models predict a critical length for crack propagation that is almost independent of slope angle, a rather surprising and counterintuitive result. Based on discrete element simulations we propose a new analytical expression for the critical crack length. This new model reconciles past approaches by considering for the first time the complex interplay between slab elasticity and the mechanical behavior of the weak layer including its structural collapse. The crack begins to propagate when the stress induced by slab loading and deformation at the crack tip exceeds the limit given by the failure envelope of the weak layer. The model can reproduce crack propagation on low-angle terrain and the decrease in critical length with increasing slope angle as modeled in numerical experiments. The good agreement of our new model with extensive field data and the ease of implementation in the snow cover model SNOWPACK opens a promising prospect for improving avalanche forecasting.

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A Comparison of Near-Infrared Imaging and Computerized Tomography Scan for Detecting Maxillary Sinusitis

Annals of Otology Rhinology & Laryngology ◽

10.1177/00034894211060623 ◽

2021 ◽

pp. 000348942110606

Author(s):

Mehdi Abouzari ◽

Brooke Sarna ◽

Joon You ◽

Adwight Risbud ◽

Kotaro Tsutsumi ◽

...

Keyword(s):

Maxillary Sinus ◽

Computerized Tomography ◽

Sensitivity And Specificity ◽

Near Infrared ◽

Maxillary Sinusitis ◽

Tertiary Care ◽

Pixel Intensity ◽

Sinus Disease ◽

Nir Imaging ◽

Average Pixel Intensity

Objective: To investigate the use of near-infrared (NIR) imaging as a tool for outpatient clinicians to quickly and accurately assess for maxillary sinusitis and to characterize its accuracy compared to computerized tomography (CT) scan. Methods: In a prospective investigational study, NIR and CT images from 65 patients who presented to a tertiary care rhinology clinic were compared to determine the sensitivity and specificity of NIR as an imaging modality. Results: The sensitivity and specificity of NIR imaging in distinguishing normal versus maxillary sinus disease was found to be 90% and 84%, normal versus mild maxillary sinus disease to be 76% and 91%, and mild versus severe maxillary sinus disease to be 96% and 81%, respectively. The average pixel intensity was also calculated and compared to the modified Lund-Mackay scores from CT scans to assess the ability of NIR imaging to stratify the severity of maxillary sinus disease. Average pixel intensity over a region of interest was significantly different ( P < .001) between normal, mild, and severe disease, as well as when comparing normal versus mild ( P < .001, 95% CI 42.22-105.39), normal versus severe ( P < .001, 95% CI 119.43-174.14), and mild versus severe ( P < .001, 95% CI 41.39-104.56) maxillary sinus disease. Conclusion: Based on this data, NIR shows promise as a tool for identifying patients with potential maxillary sinus disease as well as providing information on severity of disease that may guide administration of appropriate treatments.

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Imaging of β-amyloid plaques by near infrared fluorescent tracers: a new frontier for chemical neuroscience

Chemical Society Reviews ◽

10.1039/c4cs00337c ◽

2015 ◽

Vol 44 (7) ◽

pp. 1807-1819 ◽

Cited By ~ 96

Author(s):

Matteo Staderini ◽

María Antonia Martín ◽

Maria Laura Bolognesi ◽

J. Carlos Menéndez

Keyword(s):

Near Infrared ◽

Amyloid Plaques ◽

Fluorescent Tracers ◽

Non Invasive ◽

Nir Imaging ◽

New Frontier ◽

Invasive Method ◽

Β Amyloid

Near infrared (NIR) imaging is a promising and non-invasive method to visualize amyloid plaquesin vivo.

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LAND COVER CLASSIFICATION ALOS AVNIR DATA USING IKONOS AS REFERENCE

International Journal of Remote Sensing and Earth Sciences (IJReSES) ◽

10.30536/j.ijreses.2012.v9.a1822 ◽

2012 ◽

Vol 9 (1) ◽

Author(s):

Bambang Trisakti ◽

Dini Oktaviana Ambarwati

Keyword(s):

Land Cover ◽

Near Infrared ◽

Good Accuracy ◽

Confusion Matrix ◽

Principal Component ◽

Land Cover Classification ◽

Accuracy Evaluation ◽

Post Processing ◽

Classification Result ◽

Training Samples

Abstract. Advanced Land Observation Satellite (ALOS) is a Japanese satellite equipped with 3 sensors i.e., PRISM, AVNIR, and PALSAR. The Advanced Visible and Near Infrared Radiometer (AVNIR) provides multi spectral sensors ranging from Visible to Near Infrared to observe land and coastal zones. It has 10 meter spatial resolution, which can be used to map land cover with a scale of 1:25000. The purpose of this research was to determineclassification for land cover mapping using ALOS AVNIR data. Training samples were collected for 11 land cover classes from Bromo volcano by visually referring to very high resolution data of IKONOS panchromatic data. The training samples were divided into samples for classification input and samples for accuracy evaluation. Principal component analysis (PCA) was conducted for AVNIR data, and the generated PCA bands were classified using Maximum Likehood Enhanced Neighbor method. The classification result was filtered and re-classed into 8 classes. Misclassifications were evaluated and corrected in the post processing stage. The accuracy of classifications results, before and after post processing, were evaluated using confusion matrix method. The result showed that Maximum Likelihood Enhanced Neighbor classifier with post processing can produce land cover classification result of AVNIR data with good accuracy (total accuracy 94% and kappa statistic 0.92). ALOS AVNIR has been proven as a potential satellite data to map land cover in the study area with good accuracy.

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X-Ray and Near-Infrared Spectroscopy of Dim X-Ray Point Sources Constituting the Galactic Ridge X-Ray Emission

Acta Polytechnica CTU Proceedings ◽

10.14311/app.2014.01.0222 ◽

2014 ◽

Vol 1 (1) ◽

pp. 222-226

Author(s):

Kumiko Morihana ◽

Masahiro Tsujimoto ◽

Ken Ebisawa

Keyword(s):

Near Infrared ◽

Cataclysmic Variables ◽

Point Sources ◽

X Ray ◽

Nir Imaging ◽

Group A ◽

Field L ◽

Imaging And Spectroscopy ◽

Group B ◽

Thermal Sources

We present the results of X-ray and Near-Infrared observations of the Galactic Ridge X-ray Emission (GRXE). We extracted 2,002 X-ray point sources in the Chandra Bulge Field (l =0°.113, b = 1°.424) down to ~10-14.8 ergscm-2s-1 in 2-8 keV band with the longest observation (900 ks) of the GRXE. Based on X-ray brightness and hardness, we classied the X-ray point sources into three groups: A (hard), B (soft and broad spectrum), and C (soft and peaked spectrum). In order to know populations of the X-ray point sources, we carried out NIR imaging and spectroscopy observation. We identied 11% of X-ray point sources with NIR and extracted NIR spectra for some of them. Based on X-ray and NIR properties, we concluded that non-thermal sources in the group A are mostly active galactic nuclei and the thermal sources are mostly white dwarf binaries such as cataclysmic variables (CVs) and Pre-CVs. We concluded that the group B and C sources are X-ray active stars in flare and quiescence, respectively.

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Norwegian hindcast archive (NORA3) – A validation of offshore wind resources in the North Sea and Norwegian Sea

10.5194/wes-2021-22 ◽

2021 ◽

Author(s):

Ida Marie Solbrekke ◽

Asgeir Sorteberg ◽

Hilde Haakenstad

Keyword(s):

Wind Power ◽

Power Production ◽

Offshore Wind ◽

Norwegian Sea ◽

Offshore Wind Power ◽

Wind Speeds ◽

The North ◽

The North Sea ◽

Wind Events ◽

Simulated Wind

Abstract. A new high-resolution (3 km) numerical mesoscale weather simulation spanning the period 2004–2018 is validated for offshore wind power purposes for the North Sea and Norwegian Sea. The NORwegian hindcast Archive (NORA3) was created by dynamical downscaling, forced with state-of-the-art hourly atmospheric reanalysis as boundary conditions. A validation of the simulated wind climatology has been carried out to determine the ability of NORA3 to act as a tool for planning future offshore wind power installations. Special emphasis is placed on evaluating offshore wind power-related metrics and the impact of simulated wind speed deviations on the estimated wind power and the related variability. The general conclusion of the validation is that the NORA3 data is rather well suited for wind power estimates, but gives slightly conservative estimates on the offshore wind metrics. Wind speeds are typically 5 % (0.5 ms−1) lower than observed wind speeds, giving an underestimation of offshore wind power of 10 %–20 % (equivalent to an underestimation of 3 percentage point in the capacity factor), for a selected turbine type and hub height. The model is biased towards lower wind power estimates because of overestimation of the frequency of low-speed wind events (< 10 ms−1) and underestimation of high-speed wind events (> 10 ms−1). The hourly wind speed and wind power variability are slightly underestimated in NORA3. However, the number of hours with zero power production (around 12 % of the time) is fairly well captured, while the duration of each of these events is slightly overestimated, leading to 25-year return values for zero-power duration being too high for four of the six sites. The model is relatively good at capturing spatial co-variability in hourly wind power production among the sites. However, the observed decorrelation length was estimated to be 432 km, whereas the model-based length was 19 % longer.

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Measurement of greenhouse gas emissions from Australian feedlot beef production using open-path spectroscopy and atmospheric dispersion modelling

Australian Journal of Experimental Agriculture ◽

10.1071/ea07244 ◽

2008 ◽

Vol 48 (2) ◽

pp. 244 ◽

Cited By ~ 38

Author(s):

Zoë Loh ◽

Deli Chen ◽

Mei Bai ◽

Travis Naylor ◽

David Griffith ◽

...

Keyword(s):

Greenhouse Gas ◽

Software Package ◽

Near Infrared ◽

Atmospheric Dispersion ◽

Gas Emissions ◽

The North ◽

Open Path ◽

Gas Fluxes ◽

Greenhouse Gas Fluxes ◽

Beef Feedlots

Feedlot production of beef cattle results in concentrated sources of gas emissions to the atmosphere. Reported here are the preliminary results of a micrometeorological study using open-path concentration measurements to determine whole-of-feedlot emissions of methane (CH4) and ammonia (NH3). Tunable near-infrared diode lasers were used to measure line-averaged (150–400 m) open-path concentrations of CH4 and NH3. A backward Lagrangian stochastic model of atmospheric dispersion and the software package WindTrax were used to estimate greenhouse gas fluxes from the measured concentrations. We studied typical Australian beef feedlots in the north (Queensland) and south (Victoria) of the continent. The data from a campaign during summer show a range of CH4 emissions from 146 g/animal.day in Victoria to 166 g/animal.day in Queensland and NH3 emissions from 125 g/animal.day in Victoria to 253 g/animal.day Queensland.

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