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Red pandas
\"Developed by literacy experts for students in kindergarten through grade three, this book introduces red pandas to young readers through leveled text and related photos\"-- Provided by publisher.
Book
Automated analysis of microplastics based on vibrational spectroscopy: are we measuring the same metrics?
Abstract The traditional manual analysis of microplastics has been criticized for its labor-intensive, inaccurate identification of small microplastics, and the lack of uniformity. There are already three automated analysis strategies for microplastics based on vibrational spectroscopy: laser direct infrared (LDIR)–based particle analysis, Raman-based particle analysis, and focal plane array-Fourier transform infrared (FPA-FTIR) imaging. We compared their performances in terms of quantification, detection limit, size measurement, and material identification accuracy and speed by analyzing the same standard and environmental samples. LDIR-based particle analysis provides the fastest analysis speed, but potentially questionable material identification and quantification results. The number of particles smaller than 60 μm recognized by LDIR-based particle analysis is much less than that recognized by Raman-based particle analysis. Misidentification could occur due to the narrow tuning range from 1800 to 975 cm−1 and dispersive artifact distortion of infrared spectra collected in reflection mode. Raman-based particle analysis has a submicrometer detection limit but should be cautiously used in the automated analysis of microplastics in environmental samples because of the strong fluorescence interference. FPA-FTIR imaging provides relatively reliable quantification and material identification for microplastics in environmental samples greater than 20 μm but might provide an imprecise description of the particle shapes. Optical photothermal infrared (O-PTIR) spectroscopy can detect submicron-sized environmental microplastics (0.5–5 μm) intermingled with a substantial amount of biological matrix; the resulting spectra are searchable in infrared databases without the influence of fluorescence interference, but the process would need to be fully automated.
Journal Article
Detection of stellar light from quasar host galaxies at redshifts above 6
The detection of starlight from the host galaxies of quasars during the reionization epoch (
z
> 6) has been elusive, even with deep Hubble Space Telescope observations
1
,
2
. The current highest redshift quasar host detected
3
, at
z
= 4.5, required the magnifying effect of a foreground lensing galaxy. Low-luminosity quasars
4
–
6
from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP)
7
mitigate the challenge of detecting their underlying, previously undetected host galaxies. Here we report rest-frame optical images and spectroscopy of two HSC-SSP quasars at
z
> 6 with the JWST. Using near-infrared camera imaging at 3.6 and 1.5 μm and subtracting the light from the unresolved quasars, we find that the host galaxies are massive (stellar masses of 13 × and 3.4 × 10
10
M
☉
, respectively), compact and disc-like. Near-infrared spectroscopy at medium resolution shows stellar absorption lines in the more massive quasar, confirming the detection of the host. Velocity-broadened gas in the vicinity of these quasars enables measurements of their black hole masses (1.4 × 10
9
and 2.0 × 10
8
M
☉
, respectively). Their location in the black hole mass–stellar mass plane is consistent with the distribution at low redshift, suggesting that the relation between black holes and their host galaxies was already in place less than a billion years after the Big Bang.
Images and spectroscopy obtained by the JWST from two HSC-SSP quasars show massive, compact and disc-like galaxies, indicating that the relation between black holes and their host galaxies was in place less than a billion years after the Big Bang.
Journal Article
Characterization of connective tissues using near-infrared spectroscopy and imaging
Near-infrared (NIR) spectroscopy is a powerful analytical method for rapid, non-destructive and label-free assessment of biological materials. Compared to mid-infrared spectroscopy, NIR spectroscopy excels in penetration depth, allowing intact biological tissue assessment, albeit at the cost of reduced molecular specificity. Furthermore, it is relatively safe compared to Raman spectroscopy, with no risk of laser-induced photothermal damage. A typical NIR spectroscopy workflow for biological tissue characterization involves sample preparation, spectral acquisition, pre-processing and analysis. The resulting spectrum embeds intrinsic information on the tissue’s biomolecular, structural and functional properties. Here we demonstrate the analytical power of NIR spectroscopy for exploratory and diagnostic applications by providing instructions for acquiring NIR spectra, maps and images in biological tissues. By adapting and extending this protocol from the demonstrated application in connective tissues to other biological tissues, we expect that a typical NIR spectroscopic study can be performed by a non-specialist user to characterize biological tissues in basic research or clinical settings. We also describe how to use this protocol for exploratory study on connective tissues, including differentiating among ligament types, non-destructively monitoring changes in matrix formation during engineered cartilage development, mapping articular cartilage proteoglycan content across bovine patella and spectral imaging across the depth-wise zones of articular cartilage and subchondral bone. Depending on acquisition mode and experiment objectives, a typical exploratory study can be completed within 6 h, including sample preparation and data analysis.
This protocol describes how to perform near-infrared spectroscopy and imaging of connective tissues. Detailed guidelines are provided for sample preparation, spectral acquisition and data pre-processing and analysis, with example applications.
Journal Article
Red-eyed tree frog
\"Introduces facts about red-eyed tree frogs, including physical features, habitat, life cycle, food, and threats to these rainforest creatures. Photos, captions, and keywords supplement the narrative of this informational text.\"-- Provided by publisher.
Book
A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology
This year marks the 20th anniversary of functional near-infrared spectroscopy and imaging (fNIRS/fNIRI). As the vast majority of commercial instruments developed until now are based on continuous wave technology, the aim of this publication is to review the current state of instrumentation and methodology of continuous wave fNIRI. For this purpose we provide an overview of the commercially available instruments and address instrumental aspects such as light sources, detectors and sensor arrangements. Methodological aspects, algorithms to calculate the concentrations of oxy- and deoxyhemoglobin and approaches for data analysis are also reviewed.
From the single-location measurements of the early years, instrumentation has progressed to imaging initially in two dimensions (topography) and then three (tomography). The methods of analysis have also changed tremendously, from the simple modified Beer-Lambert law to sophisticated image reconstruction and data analysis methods used today. Due to these advances, fNIRI has become a modality that is widely used in neuroscience research and several manufacturers provide commercial instrumentation. It seems likely that fNIRI will become a clinical tool in the foreseeable future, which will enable diagnosis in single subjects.
•Comprehensive review on continuous wave functional near infrared imaging•Overview of currently available commercial near infrared imaging instrumentation•Review of technical aspects such as light sources, detectors and sensor arrangements•Review of methodological aspects, algorithms, and data analysis and its tool boxes
Journal Article
Red foxes
Did you know that red fox kits have blue eyes at first? They turn gold over time. Find out more in Red Foxes, a Little Backyard Animals book.
Book
Depth Sensitivity and Source-Detector Separations for Near Infrared Spectroscopy Based on the Colin27 Brain Template
Understanding the spatial and depth sensitivity of non-invasive near-infrared spectroscopy (NIRS) measurements to brain tissue-i.e., near-infrared neuromonitoring (NIN) - is essential for designing experiments as well as interpreting research findings. However, a thorough characterization of such sensitivity in realistic head models has remained unavailable. In this study, we conducted 3,555 Monte Carlo (MC) simulations to densely cover the scalp of a well-characterized, adult male template brain (Colin27). We sought to evaluate: (i) the spatial sensitivity profile of NIRS to brain tissue as a function of source-detector separation, (ii) the NIRS sensitivity to brain tissue as a function of depth in this realistic and complex head model, and (iii) the effect of NIRS instrument sensitivity on detecting brain activation. We found that increasing the source-detector (SD) separation from 20 to 65 mm provides monotonic increases in sensitivity to brain tissue. For every 10 mm increase in SD separation (up to ~45 mm), sensitivity to gray matter increased an additional 4%. Our analyses also demonstrate that sensitivity in depth (S) decreases exponentially, with a \"rule-of-thumb\" formula S=0.75*0.85(depth). Thus, while the depth sensitivity of NIRS is not strictly limited, NIN signals in adult humans are strongly biased towards the outermost 10-15 mm of intracranial space. These general results, along with the detailed quantitation of sensitivity estimates around the head, can provide detailed guidance for interpreting the likely sources of NIRS signals, as well as help NIRS investigators design and plan better NIRS experiments, head probes and instruments.
Journal Article