In recent years, considerable efforts have been done to better understand the peculiar emission properties of upconverting materials due to their widespread applications in different and important technological fields such as upconversion-based photoactivated cancer therapies, photoactivated drug-delivery, magnetic resonance imaging contrast agents, bioimaging.
Despite limitations of the system, it is an advance toward sampling the full particle-size spectrum of loose sediment available for entrainment with the overall goal to better understand the mechanisms of dust emission and their variability.
Research is needed to better understand the impacts of future emissions pathways, climate change impacts on concentrations of fine particles and gases, how changing weather patterns could influence the frequency and severity of episodes of poor air quality, population sensitivity, and how these factors might interact.
In order to better understand the origin of these characteristic emission peaks, we perform a Fourier analysis of an ensemble of individual emission spectra.
To better understand the levels of excitation and emission collection efficiencies required for ITE imaging we carried out quantitative tissue autofluorescence imaging using optics analogous to what we envision in future microendoscope or laparoscope optics (0.7 NA Olympus microprobe lens with a 3.2 mm diameter tip – Fig. 1A).
In an effort to better understand the social drivers of CO2 emissions the Global Carbon Project of the Earth Systems Science Partnership has established an Urban and Regional Carbon Management (URCM) initiative, which calls for carbon research and management at multiple scales [3].
Clearly, a research priority for the future must be to better understand the dynamics of forest carbon emissions in landscapes undergoing rapid land use change, including fragmentation, regrowth, deforestation, and degradation processes.
In an effort to better understand the social drivers of CO2 emissions the Global Carbon Project of the Earth Systems Science Partnership has established an Urban and Regional Carbon Management (URCM) initiative, which calls for carbon research and management at multiple scales [ 3].
The present study explored the milk metabolome by gas chromatography-mass spectrometry (milk volatile metabolites) and nuclear magnetic resonance (milk nonvolatile metabolites) to better understand the biological pathways involved in CH4 emission in dairy cattle.
To better understand the dynamics of the Er3+-related emission, the time evolution of the 1,535-nm 1,535-nm band analyzed at different excitation wavelengthas 266 and 488 nm. Figure 3 shows the obeenned results together with manalyzedntropy method (MEM) atalysis expressedifferentform of α. Figurexcitationvolution of the 1,535-nm band.
