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Background: To observe the effects of the minimally invasive removal of an intracerebral hematoma on the glutamate concentration, blood-brain barrier (BBB) permeability and brain water content in the brain tissue surrounding the hematoma and to provide a theoretical basis for minimally invasive removal of intracerebral hematomas. Methods: Thirty rabbits (2.8-3.4 kg body weight) were selected to establish a model of intracerebral hemorrhage, and they were randomly divided into a model control group and a minimally invasive group after the model was prepared successfully. The intracerebral hematoma was evacuated by stereotactic procedures in minimally invasive group 6 h after the model was established. The glutamate content, the permeability of the BBB and the brain water content in perihematomal brain tissues were determined and compared between the two groups. Results: The glutamate content, the permeability of the BBB and the brain water content in the perihematomal brain tissues were significantly decreased compared to the model control group 1, 3, and 7 days after the minimally invasive removal of the intracerebral hematoma. Conclusions: Minimally invasive surgery for removal of an intracerebral hematoma could significantly reduce the glutamate content, BBB permeability and the brain water content in perihematomal brain tissues. [ABSTRACT FROM AUTHOR]

The Atmospheric Infrared Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI), together with the future Cross-track Infrared Sounder, will provide long-term hyperspectral measurements of the earth and its atmosphere at ∼10 km spatial resolution. Quantifying the radiometric difference between AIRS and IASI is crucial for creating fundamental climate data records and establishing the space-based infrared calibration standard. Since AIRS and IASI have different local equator crossing times, a direct comparison of these two instruments over the tropical regions is not feasible. Using the Geostationary Operational Environmental Satellite (GOES) imagers as transfer radiometers, this study compares AIRS and IASI over warm scenes in the tropical regions for a time period of 16 months. The double differences between AIRS and IASI radiance biases relative to the GOES-11 and -12 imagers are used to quantify the radiance differences between AIRS and IASI within the GOES imager spectral channels. The results indicate that, at the 95% confidence level, the mean values of the IASI − AIRS brightness temperature differences for warm scenes are very small, that is, −0.0641 ± 0.0074 K, −0.0432 ± 0.0114 K, and −0.0095 ± 0.0151 K for the GOES-11 6.7-, 10.7-, and 12.0- μm channels, respectively, and −0.0490 ± 0.0100 K, −0.0419 ± 0.0224 K, and −0.0884 ± 0.0160 K for the GOES-12 6.5-, 10.7-, and 13.3- μm channels, respectively. The brightness temperature biases between AIRS and IASI within the GOES imager spectral range are less than 0.1 K although the AIRS measurements are slightly warmer than those of IASI. [ABSTRACT FROM AUTHOR]

The calibrated radiances from geostationary water vapor channels play an important role for weather forecasting, data assimilation, and climate studies. Therefore, better understanding the data quality for radiance measurements and independently assessing their onboard calibrations become increasingly more important. In this study, the Infrared Atmospheric Sounding Interferometer (IASI) hyperspectral measurements on the polar-orbiting Meteorological Operation-A (MetOp-A) satellite are used to assess the calibration accuracy of water vapor channels on the Geostationary Operational Environmental Satellite-11 (GOES-11) and GOES-12 imagers with one year of data. The near-simultaneous nadir observations with homogeneous scenes from IASI and GOES imagers are spatially collocated. The IASI spectra are convolved with the GOES imager spectral response functions (SRFs) to compare with GOES imager observations. Assuming that IASI is well calibrated and can be used as an on-orbit radiometric reference standard, then the GOES imager water vapor channels have an overall relative calibration bias to IASI of better than 0.3 K (with a standard deviation of ∼0.2 K) at the brightness temperature (BT) range of 240–260 K, which meets the design specification (1.0-K calibration accuracy for infrared channels). This study further demonstrates the technique of using hyperspectral radiance measurements in a polar-orbiting satellite to accurately assess broadband radiometer calibration of the GOES imager, which also provides an effective way for monitoring sensor performance over time. In addition, the potential of using the intercalibration results to integrate and merge data from different observing systems involving both IASI and different GOES imagers to create consistent, seamless global products is explored. The method presented here can potentially be applied to other instruments on both polar-orbiting and geostationary satellites for generating long-term time series. [ABSTRACT FROM AUTHOR]

The High-Resolution Infrared Radiation Sounder (HIRS) has been carried on NOAA satellites for more than two decades, and the HIRS data have been widely used for geophysical retrievals, climate studies, and radiance assimilation for numerical weather prediction models. However, given the legacy of the filter-wheel radiometer originally designed in the 1970s, the HIRS measurement accuracy is neither well documented nor well understood, despite the importance of this information for data users, instrument manufacturers, and calibration scientists. The advent of hyperspectral sounders, such as the Atmospheric Infrared Sounder (AIRS), and intersatellite calibration techniques makes it possible to independently assess the accuracy of the HIRS radiances. This study independently assesses the data quality and calibration accuracy of HIRS by comparing the radiances between HIRS on NOAA-16 and AIRS on Aqua with simultaneous nadir overpass (SNO) observations for the year 2004. The results suggest that the HIRS radiometric bias relative to the AIRS-convolved HIRS radiance is on the order of ∼0.5 K, except channel 16, which has a bias of 0.8 K. For all eight spectrally overlapped channels, the observations by HIRS are warmer than the corresponding AIRS-convolved HIRS channel. Other than channel 16, the biases are temperature dependent. The root causes of the bias can be traced to a combination of the HIRS blackbody emissivity, nonlinearity, and spectral uncertainties. This study further demonstrates the utility of high-spectral-resolution radiance measurements for high-accuracy assessments of broadband radiometer calibration with the SNO observations. [ABSTRACT FROM AUTHOR]

In the low doping limit, a high Tc cuprate preserves a two band structure. O2p electrons are itinerant, Cu3d electrons are localized. Therefore the two component model is suitable to describe nuclear spin relaxation at copper sites. In addition to the Korringa process, the hyperfine interaction between nuclear spins and local electron spins is considered, which gives rise to the anomalous relaxation rate 1/T1 = a + bT. The decrease of the susceptibility near Tc, as shown by the Knight shift measurements, can be attributed to the ordering of local spins and the pairing of the uncompensated spins created by holes at the oxygen sites. [ABSTRACT FROM AUTHOR]

In this fifth of a series of papers describing the extended-time high cloud observation program from the University of Utah Facility for Atmospheric Remote Sensing, the structural properties of cirrus clouds over Salt Lake City, Utah, are examined. Wavelet analysis is applied to a 10-yr record of cirrus cloud ruby (0.694 μm) lidar backscatter data as a function of cloud height in order to study the presence of periodic cloud structures, such as the signatures of Kelvin–Helmholtz instabilities, cirrus mammata, and uncinus cells (all with length scales of ∼1–10 km), as well as mesoscale cloud organizations generally believed to be induced by gravity waves. About 8.4% of the data display structures after passing a 95% confidence level test, but an 80% confidence level, which seems better able to resolve structures spread over long periods, yields 16.4%. The amount of identified cloud structures does not change significantly with length scale from 0.2 to 200 km, although the frequency of mesoscale cloud structures tends to increase as length scales increase. The middle-to-lower portion of cirrus clouds contains the most identified cloud structures, which seems related to the mesoscale organization of fall streaks from cloud-top-generating cells. The variability of cirrus cloud optical depth τ (defined by the standard deviation over mean τ) derived from a combined lidar and infrared radiometer (LIRAD) analysis is shown to be largely independent of τ. Because visual examination of the lidar displays also indicates that few cirrus layers can be considered horizontally homogeneous over our typical 3-h lidar data collection period, the authors conclude that the clouds in their sample are inherently inhomogeneous even though most cirrus structures are not revealed as periodic by wavelet analysis. [ABSTRACT FROM AUTHOR]

The authors improve the traditional genetic algorithm, and combine the new method named RAGA (Real coded based accelerating Genetic Algorithm) with PPE. (Projection Pursuit Evaluation) model. The HAGA-PPE model own optimize several parameters at one time. Based on this method, the authors built up a new evaluating model. Through applying the new model to evaluate the country energy of Pingtan County, the authors gained the good results. Thus, the authors provide a new method and thought for readers who engage in researching country energy planing. [ABSTRACT FROM AUTHOR]

Summary: High-throughput RNA sequencing (RNA-seq) is rapidly emerging as a major quantitative transcriptome profiling platform. Here, we present DEGseq, an R package to identify differentially expressed genes or isoforms for RNA-seq data from different samples. In this package, we integrated three existing methods, and introduced two novel methods based on MA-plot to detect and visualize gene expression difference. [ABSTRACT FROM PUBLISHER]

Metallothionein (MT) genes are valuable genetic materials for developing metal bioremediation tools. Currently, a limited number of prokaryotic MTs have been experimentally identified, which necessitates the expansion of bacterial MT diversity. In this study, we conducted a metagenomics-guided analysis for the discovery of potential bacterial MT genes from the soil microbiome. More specifically, we combined resistance gene enrichment through diversity loss, metagenomic mining with a dedicated MT database, evolutionary trace analysis, DNA chemical synthesis, and functional genomic validation to identify novel MTs. Results showed that Cu stress induced a compositional change in the soil microbiome, with an enrichment of metal-resistant bacteria in soils with higher Cu concentrations. Shotgun metagenomic sequencing was performed to obtain the gene pool of environmental DNA (eDNA), which was subjected to a local BLAST search against an MT database for detecting putative MT genes. Evolutional trace analysis led to the identification of 27 potential MTs with conserved cysteine/histidine motifs different from those of known prokaryotic MTs. Following chemical synthesis of these 27 potential MT genes and heterologous expression in Escherichia coli, six of them were found to improve the hosts' growth substantially and enhanced the hosts' sorption of Cu, Cd, and Zn, among which MT5 led to a 13.7-fold increase in Cd accumulation. Furthermore, four of them restored Cu and/or Cd resistance in two metal-sensitive E. coli strains. [ABSTRACT FROM AUTHOR]

We report the photoassisted activation of selected C-H bonds in individual molecules adsorbed on metal surfaces within the junction of a scanning tunneling microscope. Photons can couple to the C-H bond activation of specific hydrocarbons through a resonant photoassisted tunneling process. The molecule to be activated can be selected by positioning the tip with subangstrom resolution. Furthermore, structural tomography of the molecule and its dissociation products are imaged at different heights by the inelastic tunneling probe. The demonstration of single bond dissociation induced by resonant photoassisted tunneling electrons implies the attainment of atomic scale spatial resolution for bond-selected photochemistry. [ABSTRACT FROM AUTHOR]