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The authors previously reported discovery of narrow, thermal emission bands from symmetrically patterned features etched into silicon wafers. In this paper, we report further results that show the measured absorption peaks for such patterned surfaces match theoretical calculations of the complete electrodynamic problem solved using the Transfer Matrix Method (TMM).
Along with scientific applications, Geostationary imagery is often used to learn about weather patterns through true color visualizations. NOAA/NASA's GOES-R series of satellites uses the advanced baseline imager with 16-bands which, unlike previous generations, does not include the green wavelength (500-565 nm) and hence cannot directly generate true color images. However, Himawari, Japan's geostationary satellite, uses a similar 16-band advanced Himawari imager that does include a green band (but missing cirrus). In this work, we show how transfer learning with convolutional neural networks can be applied across satellites to generate "virtual sensors". We apply this approach to generate a green band for GOES-16 and present near true color images.
This paper examines the effect that solar differential rotation would have on a hypothetical large-scale equatorial dipole field. The evolving large-scale field pattern is expressed as a series of non-axisymmetric moments. As time increases, power is transferred to progressively higher order moments. In the 27d rotating coordinate system, each moment undergoes a small retrograde drift which remains nearly uniform until that mode begins to fade. The synodic rotation periods of the first few moments are comparable to the observed 28.5d period of the sun's large-scale field near sunspot maximum. Differential rotation may be the source of this 28.5d period, but the eruption of new flux is necessary to keep the pattern going.
Focal-plane arrays of semiconductor quantum-dot infrared photodetectors (QDIPs) are being developed as superior alternatives to prior infrared imagers, including imagers based on HgCdTe devices and, especially, those based on quantum-well infrared photodetectors (QWIPs). HgCdTe devices and arrays thereof are difficult to fabricate and operate, and they exhibit large nonunformities and high 1/f (where f signifies frequency) noise. QWIPs are easier to fabricate and operate, can be made nearly uniform, and exhibit lower 1/f noise, but they exhibit larger dark currents, and their quantization only along the growth direction prevents them from absorbing photons at normal incidence, thereby limiting their quantum efficiencies. Like QWIPs, QDIPs offer the advantages of greater ease of operation, greater uniformity, and lower 1/f noise, but without the disadvantages: QDIPs exhibit lower dark currents, and quantum efficiencies of QDIPs are greater because the three-dimensional quantization of QDIPs is favorable to the absorption of photons at normal or oblique incidence. Moreover, QDIPs can be operated at higher temperatures (around 200 K) than are required for operation of QWIPs. The main problem in the development of QDIP imagers is to fabricate quantum dots with the requisite uniformity of size and spacing. A promising approach to be tested soon involves the use of electron-beam lithography to define the locations and sizes of quantum dots. A photoresist-covered GaAs substrate would be exposed to the beam generated by an advanced, high-precision electron beam apparatus. The exposure pattern would consist of spots typically having a diameter of 4 nm and typically spaced 20 nm apart. The exposed photoresist would be developed by either a high-contrast or a low-contrast method. In the high-contrast method, the spots would be etched in such a way as to form steep-wall holes all the way down to the substrate. The holes would be wider than the electron beam spots perhaps as wide as 15 to 20 nm, but may be sufficient to control the growth of the quantum dots. In the low-contrast method, the resist would be etched in such a way as to form dimples, the shapes of which would mimic the electron-beam density profile. Then by use of a transfer etching process that etches the substrate faster than it etches the resist, either the pattern of holes or a pattern comprising the narrow, lowest portions of the dimples would be imparted to the substrate. Having been thus patterned, the substrate would be cleaned. The resulting holes or dimples in the substrate would serve as nucleation sites for the growth of quantum dots of controlled size in the following steps. The substrate would be cleaned, then placed in a molecular-beam-epitaxy (MBE) chamber, where native oxide would be thermally desorbed and the quantum dots would be grown.
Carbonate and organic matter deposited during the latest Paleocene thermal maximum is characterized by a remarkable -2.5% excursion in delta 13C that occurred over approximately 10(4) yr and returned to near initial values in an exponential pattern over approximately 2 x 10(5) yr. It has been hypothesized that this excursion signifies transfer of 1.4 to 2.8 x 10(18) g of CH4 from oceanic hydrates to the combined ocean-atmosphere inorganic carbon reservoir. A scenario with 1.12 x 10(18) g of CH4 is numerically simulated here within the framework of the present-day global carbon cycle to test the plausibility of the hypothesis. We find that (1) the delta 13C of the deep ocean, shallow ocean, and atmosphere decreases by -2.3% over 10(4) yr and returns to initial values in an exponential pattern over approximately 2 x 10(5) yr; (2) the depth of the lysocline shoals by up to 400 m over 10(4) yr, and this rise is most pronounced in one ocean region; and (3) global surface temperature increases by approximately 2 degrees C over 10(4) yr and returns to initial values over approximately 2 x 10(6) yr. The first effect is quantitatively consistent with the geologic record; the latter two effects are qualitatively consistent with observations. Thus, significant CH4 release from oceanic hydrates is a plausible explanation for observed carbon cycle perturbations during the thermal maximum. This conclusion is of broad interest because the flux of CH4 invoked during the maximum is of similar magnitude to that released to the atmosphere from present-day anthropogenic CH4 sources.
A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.
Here, nanopatterning for the fabrication of optical metasurfaces entails a need for high-resolution approaches like electron beam lithography that cannot be readily scaled beyond prototyping demonstrations. Block copolymer thin film self-assembly offers an attractive alternative for producing periodic nanopatterns across large areas, yet the pattern feature sizes are fixed by the polymer molecular weight and composition. Here, a general strategy is reported that overcomes the limitation of fixed feature size by treating the copolymer thin film as a hierarchical resist, in which the nanoscale pattern motif is defined by self-assembly. Feature sizes can then be tuned by thermal reflow controlled locally by irradiative crosslinking or chemical alteration using lithographic ultraviolet light or electron beam exposure. Using blends of polystyrene-block-poly(methylmethacrylate) (PS-b-PMMA) with PS and PMMA homopolymer, we demonstrate both self-assembled PS grating and hexagonal hole patterns; exposure-controlled reflow is then used to reduce hole diameter by as much as 50% or increase PS grating linewidth by more than 180%. Transferring these nanopatterns, or their inverse obtained by a lift-off approach, into silicon yields structural colors that may be prescriptively controlled based on nanoscale feature size. Furthermore, patterned exposure enables area-selective feature size control, yielding uniform structural color patterns across centimeter square areas. Electron beam lithography is also used to show that the lithographic resolution of this selective-area control can be extended to the nanoscale dimensions of the self-assembled features. The exposure-controlled reflow approach demonstrated here takes a pivotal step towards fabricating complex, hierarchical optical metasurfaces using scalable self-assembly methods.
We have selected square subareas (110 km on a side) from coastal zone color scanner (CZCS) and advanced very high resolution radiometer (AVHRR) images for 1981 in the California Current region off northern California for which we could identify sequences of cloud-free data over periods of days to weeks. We applied a two-dimensional fast Fourier transformation to images after median filtering, (x, y) plane removal, and cosine tapering. We formed autospectra and coherence spectra as functions of a scalar wavenumber. Coherence estimates between pairs of images were plotted against time separation between images for several wide wavenumber bands to provide a temporal lagged coherence function. The temporal rate of loss of correlation (decorrelation time scale) in surface patterns provides a measure of the rate of pattern change or evolution as a function of spatial dimension. We found that patterns evolved (or lost correlation) approximately twice as rapidly in upwelling jets as in the 'quieter' regions between jets. The rapid evolution of pigment patterns (lifetime of about 1 week or less for scales of 50-100 km) ought to hinder biomass transfer to zooplankton predators compared with phytoplankton patches that persist for longer times. We found no significant differences between the statistics of CZCS and AVHRR images (spectral shape or rate of decorrelation). In addition, in two of the three areas studied, the peak correlation between AVHRR and CZCS images from the same area occurred at zero lag, indicating that the patterns evolved simutaneously. In the third area, maximum coherence between thermal and pigment patterns occurred when pigment images lagged thermal images by 1-2 days, mirroring the expected lag of high pigment behind low temperatures (and high nutrients) in recently upwelled water. We conclude that in dynamic areas such as coastal upwelling systems, the phytoplankton cells (identified by pigment color patterns) behave largely as passive scalars at the mesoscale and that growth, death, and sinking of phytoplankton collectively play at most a mariginal role in determining the spectral statistics of the pigment patterns.
Abstract Quantifying the relative influence of factors and processes controlling riverine ecosystem function is essential to predicting future conditions under global change. Dissolved organic matter (DOM) is a fundamental component of riverine ecosystems that fuels microbial food webs, influences nutrient and light availability, and represents a significant carbon flux globally. The heterogeneous nature of DOM molecular composition and its propensity for interaction (i.e., functional diversity) can characterize riverine ecosystem function across spatiotemporal scales. To investigate fundamental drivers of DOM diversity, we collected seasonal water samples from 42 nested locations within five watersheds spanning multiple watershed sizes (~ 5 to 30,000 km 2 ) across the United States. Patterns in DOM molecular richness, aromaticity, relative abundance of N-containing formulas, and putative biochemical transformations derived from high-resolution mass spectrometry were assessed across gradients of explanatory variables associated with watershed characteristics (e.g., watershed area, water residence time, land cover). We found that putative biochemical transformations were more strongly related to explanatory variables across watersheds than common bulk DOM parameters and that watershed area, surface water residence time and derived Damköhler numbers representing DOM reactivity timescales were strong predictors of DOM diversity. The data also indicate that catchment-specific land cover factors can significantly influence DOM diversity in diverging directions. Overall, the results highlight the importance of considering water residence time and land cover when interpreting longitudinal patterns in DOM chemistry and the continued challenge of identifying generalizable drivers that are transferable across watershed and regional scales for application in Earth system models. This work also introduces a Findable Accessible Interoperable Reusable (FAIR) dataset (> 300 samples) to the community for future syntheses.
Fluvial networks integrate and transport constituents from terrestrial and aquatic ecosystems. To date, most research on water quality dynamics has focused on process understanding at individual streams and, as a result, there is a lack of studies analyzing how small-scale, physical and biogeochemical drivers scale across fluvial networks. We performed tracer tests in five stream orders of the Jemez River continuum in New Mexico, USA, to quantify reach-scale hyporheic exchange during two different seasonal periods to address: how do hyporheic zone contributions to riverine processing change with space and time? And does the spatiotemporal variability of hyporheic exchange scale across fluvial networks? Combining conservative (i.e., bromide) and reactive (i.e., resazurin) tracer analyses with solute transport modeling, we found a dominance of reaction-limited transport conditions in space (for all stream orders) and time (two contrasting flow regimes). Moreover, we found a trend toward more reaction-limited conditions with increasing discharge across all stream orders. While our studied fluvial network did not consistently follow the expectations of decreasing hyporheic exchange contributions with increasing stream order, as it has been previously suggested from modeling studies, we found that processing rate coefficients and Damköhler numbers consistently decreased along the continuum with increasing discharge. Our findings suggest that knowledge transferability of hyporheic zone processing along fluvial networks may be possible if the scaling patterns that we found hold true in other catchments. Thus, more research on scaling patterns along fluvial networks is highly needed.
The effect of the atmosphere on remote image interpretation and transfer was studied under laboratory conditions. Indoor laboratory measurements were made of the reflection patterns of typical natural surfaces using a dual channel polarizing radiometer. Outdoor ground measurements of these same surfaces were compared to indoor ones to validate the findings. From these data attempts were made to construct an atmospheric remote sensing model that could predict spectral intensity characteristics of the remote image as seen by a particular sensor given the spatial orientation of the sensor, the atmospheric conditions, the time of day, and the type of surface being viewed.
The effects of g-jitter on nonencapsulated and encapsulated liquid bridges were investigated numerically, using fluid characteristics and parameters from three fluid systems: a silicone oil bridge, a methanol bridge, and a silicon melt. Results showed that complex flow patterns can arise in g-jitter environment which significantly modify the heat-transfer characteristics of the system. It was found that the nonencapsulated liquid bridges and float zone melts were dominated by surface-tension driven convection, with very little impact on the flows by residual and g-jitter accelerations. Zone encapsulation resulted in a sizeable drop in the maximum fluid velocities. The g-jitter computations on the encapsulated float zones resulted in significant augmentation of the maximum velocities and heat transfer, with the silicon melt being the least sensitive to g-jitter acceleration.
Early reflection patterns calculated from a room design program were filtered with measured head-related transfer functions (HRTFs) within a 'hypothetical auralization system.' With reference to a particular set of room/listener/sound source configurations, the system is shown to produce both perceptible and imperceptible results. The results of this exploratory analysis are illuminating for future design considerations of HRTF-based auralization systems.
Transient spin-up and spin-down flows inside of spacecraft fuel tanks need to be analyzed in order to properly design spacecraft control systems. Knowledge of the characteristics of angular momentum transfer to and from the fuel is used to size the de-spin mechanism that places the spacecraft in a controllable in-orbit state. In previous studies, several analytical models of the spin-up process were developed. However, none have accurately predicted all of the flow dynamics. Several studies have also been conducted using Navier-Stokes based methods. These approaches have been much more successful at simulating the dynamic processes in a cylindrical container, but have not addressed the issue of momentum transfer. In the current study, the spin-up and spin-down of a fuel tank filled with gaseous xenon has been investigated using a three-dimensional unsteady Navier-Stokes code. Primary interests have been concentrated on the spin-up/spin-down time constants and the initial torque imparted on the system. Additional focus was given to the relationship between the dominant flow dynamics and the trends in momentum transfer. Through the simulation of both a cylindrical and a spherical tank, it was revealed that the transfer of angular momentum is nonlinear at early times and tends toward a linear pattern at later times. Further investigation suggests that the nonlinear spin up is controlled by the turbulent transport of momentum, while the linear phase is controlled by a Coriolis driven (Ekman) flow along the outer wall. These results indicate that the spinup and spin-down processes occur more quickly in tanks with curved surfaces than those with defined top, bottom, and side walls. The results also provide insights for the design of spacecraft de-spin mechanisms.
With an estimated global flash rate of 46 lightning per second, a significant amount of lightning nitrogen oxides (LNOx) are produced within the climate system. In turn, LNOx affect the concentrations of ozone (O 3 , an important greenhouse gas) as well as the very reactive hydroxyl radicals (OH, that affect all greenhouse gases). Thus, space-based estimation of LNOx is highly sought [Koshak 2017; Koshak et al. (2015)]. Total lightning channel length, L , is a proxy for the total flash energy (and hence LNOx production). Geostationary lightning mappers provide cloud-top 2D views of the diffuse (i.e., blurry) optical images of lightning, thereby making it difficult to determine L (and other channel features). Transient Boltzmann radiative transfer modeling is applied here to investigate the dependence of the spatio-temporal pattern of cloud-top lightning optical emissions on L and other channel characteristics (e.g., orientation, propagation direction, amplitude, location, ...).
Mitochondria are essential components of eukaryotic cells, responsible for ATP production through oxidative phosphorylation. Despite their biological importance, unique challenges have hindered the adoption of automated mitochondrial genome (mitogenome) annotation methods, obstructing mitochondrial comparative genomics in a broad evolutionary context. Using Fungi as a study system and a Joint Genome Institute (JGI) annotated high-quality reference set, we observed broad patterns of mitochondrial evolution across the kingdom. We found that the median fungal mitogenome size is 58 kb and identified exceptionally large examples over 1 Mb in Pezizomycetes. All 14 expected oxidative phosphorylation protein-coding genes, plus rps3, were generally conserved. We found evidence of major evolutionary transitions within the Ascomycota, including the transfer of mitochondrially encoded atp8 and atp9 to the nuclear genomes across the Pezizomycotina and shifts in mitogenome tRNA patterns across the kingdom. We found substantial concordance between mitochondrial and nuclear evolution, enabling us to document 3131 total fungal mitogenomes from JGI-derived metagenomic datasets. We also identified 6467 total undeclared mitogenomes embedded in Genbank fungal nuclear assemblies. We provide interactive tools for mitogenome analysis through the JGI MycoCosm platform. Collectively, this work generated nearly 10 000 new fungal mitogenome annotations, providing a foundation and resources for future exploration of comparative fungal mitogenomics.
The prediction of the complete flow field in a turbine passage is an extremely difficult task due to the complex three dimensional pattern which contains separation and attachment lines, a saddle point and horseshoe vortex. Whereas, in principle such a problem can be solved using full Navier-Stokes equations, in reality methods based on a Navier-Stokes solution procedure encounter difficulty in accurately predicting surface quantities (e.g., heat transfer) due to grid limitations imposed by the speed and size of the existing computers. On the other hand the overall problem is strongly three dimensional and too complex to be analyzed by the current design methods based on inviscid and/or viscous strip theories. Thus there is a strong need for enhancing the current prediction techniques through inclusion of 3-D viscous effects. A potentially simple and cost effective way to achieve this is to use a prediction method based on three dimensional boundary layer (3-DBL) theory. The major objective of this program is to assess the applicability of such a 3-DBL approach for the prediction of heat loads, boundary layer growth, pressure losses and streamline skewing in critical areas of a turbine passage. A brief discussion of the physical problem addressed here along with the overall approach is presented.
Kinetic energy of the near storm environment was analyzed by meso beta scale data. It was found that horizontal winds in the 400 to 150 mb layer strengthen rapidly north of the developing convection. Peak values then decrease such that the maximum disappears 6 h later. Southeast of the storms, wind speeds above 300 mb decrease nearly 50% during the 3 h period of most intense thunderstorm activity. When the convection dissipates, wind patterns return to prestorm conditions. The mesoscale storm environment of AVE-SESAME 5 is characterized by large values of cross contour generation of kinetic energy, transfers of energy to nonresolvable scales of motion, and horizontal flux divergence. These processes are maximized within the upper troposphere and are greatest during times of strongest convection. It is shown that patterns agree with observed weather features. The southeast area of the network is examined to determine causes for vertical wind variations.