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By leveraging metamaterials and compressive imaging, a low-profile aperture capable of microwave imaging without lenses, moving parts, or phase shifters is demonstrated. This designer aperture allows image compression to be performed on the physical hardware layer rather than in the postprocessing stage, thus averting the detector, storage, and transmission costs associated with full diffraction-limited sampling of a scene. A guided-wave metamaterial aperture is used to perform compressive image reconstruction at 10 frames per second of two-dimensional (range and angle) sparse still and video scenes at K-band (18 to 26 gigahertz) frequencies, using frequency diversity to avoid mechanical scanning. Image acquisition is accomplished with a 40:1 compression ratio.

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays 'Fernandez') plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable.

Designing, fabricating, and integrating arrays of nanodevices into a functional system are the key to transferring nanoscale science into applicable nanotechnology. We report large-array three-dimensional (3D) circuitry integration of piezotronic transistors based on vertical zinc oxide nanowires as an active taxel-addressable pressure/force sensor matrix for tactile imaging. Using the piezoelectric polarization charges created at a metal-semiconductor interface under strain to gate/modulate the transport process of local charge carriers, we designed independently addressable two-terminal transistor arrays, which convert mechanical stimuli applied to the devices into local electronic controlling signals. The device matrix can achieve shape-adaptive high-resolution tactile imaging and self-powered, multidimensional active sensing. The 3D piezotronic transistor array may have applications in human-electronics interfacing, smart skin, and micro-and nanoelectromechanical systems.

Fear memories guide adaptive behavior in contexts associated with aversive events. The hippocampus forms a neural representation of the context that predicts aversive events. Representations of context incorporate multisensory features of the environment, but must somehow exclude sensory features of the aversive event itself. We investigated this selectivity using cell type–specific imaging and inactivation in hippocampal area CA1 of behaving mice. Aversive stimuli activated CA1 dendrite-targeting interneurons via cholinergic input, leading to inhibition of pyramidal cell distal dendrites receiving aversive sensory excitation from the entorhinal cortex. Inactivating dendrite-targeting interneurons during aversive stimuli increased CA1 pyramidal cell population responses and prevented fear learning. We propose subcortical activation of dendritic inhibition as a mechanism for exclusion of aversive stimuli from hippocampal contextual representations during fear learning.

Objective To determine whether ultrasound imaging can reduce the risk of failed lumbar punctures or epidural catheterisations, when compared with standard palpation methods, and whether ultrasound imaging can reduce traumatic procedures, insertion attempts, and needle redirections.Design Systematic review and meta-analysis of randomised controlled trials.Data sources Ovid Medline, Embase, and Cochrane Central Register of Controlled Trials up to May 2012, without restriction by language or publication status.Review methods Randomised trials that compared ultrasound imaging with standard methods (no imaging) in the performance of a lumbar puncture or epidural catheterisation were identified.Results 14 studies with a total of 1334 patients were included (674 patients assigned to the ultrasound group, 660 to the control group). Five studies evaluated lumbar punctures and nine evaluated epidural catheterisations. Six of 624 procedures conducted in the ultrasound group failed; 44 of 610 procedures in the control group failed. Ultrasound imaging reduced the risk of failed procedures (risk ratio 0.21 (95% confidence interval 0.10 to 0.43), P<0.001). Risk reduction was similar when subgroup analysis was performed for lumbar punctures (risk ratio 0.19 (0.07 to 0.56), P=0.002) or epidural catheterisations (0.23 (0.09 to 0.60), P=0.003). Ultrasound imaging also significantly reduced the risk of traumatic procedures (risk ratio 0.27 (0.11 to 0.67), P=0.005), the number of insertion attempts (mean difference −0.44 (−0.64 to −0.24), P<0.001), and the number of needle redirections (mean difference −1.00 (−1.24 to −0.75), P<0.001).Conclusions Ultrasound imaging can reduce the risk of failed or traumatic lumbar punctures and epidural catheterisations, as well as the number of needle insertions and redirections. Ultrasound may be a useful adjunct for these procedures.

Cellular metabolites are detected within living cells by fluorescent RNA-based ligand-binding sensors. Genetically encoded sensors are powerful tools for imaging intracellular metabolites and signaling molecules. However, developing sensors is challenging because they require proteins that undergo conformational changes upon binding the desired target molecule. We describe an approach for generating fluorescent sensors based on Spinach, an RNA sequence that binds and activates the fluorescence of a small-molecule fluorophore. We show that these sensors can detect a variety of different small molecules in vitro and in living cells. These RNAs constitute a versatile approach for fluorescence imaging of small molecules and have the potential to detect essentially any cellular biomolecule.

The Great Observatories All-Sky LIRG Survey (GOALS20) combines data from NASA’sSpitzer Space Telescope, Chandra X-Ray Observatory, Hubble Space Telescope(HST), andGalaxy Evolution Explorer(GALEX) observatories, together with ground-based data, into a comprehensive imaging and spectroscopic survey of over 200 low-redshift ( z < 0.088 z < 0.088 ), Luminous Infrared Galaxies (LIRGs). The LIRGs are a complete subset of theIRASRevised Bright Galaxy Sample (RBGS), which comprises 629 extragalactic objects with 60 μm flux densities above 5.24 Jy, and Galactic latitudes above five degrees. The LIRGs targeted in GOALS span the full range of nuclear spectral types defined via traditional optical line-ratio diagrams (type-1 and type-2 AGN, LINERs, and starbursts) as well as interaction stages (major mergers, minor mergers, and isolated galaxies). They provide an unbiased picture of the processes responsible for enhanced infrared emission in galaxies in the local Universe. As an example of the analytic power of the multiwavelength GOALS data set, we presentSpitzer, Chandra, HST,andGALEXimages and spectra for the interacting system VV 340 (IRAS F14547 + 2449 F 14547 + 2449 ). TheSpitzerMIPS imaging data indicates that between 80–95% of the total far-infrared emission (or about5 × 1011 L ⊙ 5 × 10 11     L ⊙ ) originates in VV 340 north. While theSpitzerIRAC colors of VV 340 north and south are consistent with star-forming galaxies, both theSpitzerIRS andChandraACIS data indicate the presence of an AGN in VV 340 north. The observed line fluxes, without correction for extinction, imply that the AGN accounts for less than 10%–20% of the observed infrared emission. The X-ray data are consistent with a heavily absorbed ( N H ≥1024 cm-2 N H ≥ 10 24     cm - 2 ) AGN. The GALEX far and near-UV fluxes imply a extremely large infrared “excess” (IRX) for the system (FIR/Ffuv ∼ 81 F IR / F fuv ∼ 81 ) which is well above the correlation seen in starburst galaxies. Most of this excess is driven by VV 340 N, which has an IR excess of nearly 400. The VV 340 system seems to be comprised of two very different galaxies: an infrared luminous edge-on galaxy (VV 340 north) that dominates the long-wavelength emission from the system, which hosts a buried AGN; and a face-on starburst (VV 340 south) that dominates the short-wavelength emission.

To mount an immune response, lymphocytes must recirculate between the blood and lymph nodes, recognize antigens upon contact with specialized presenting cells, proliferate to expand a small number of clonally relevant lymphocytes, differentiate to antibody-producing plasma cells or effector T cells, exit from lymph nodes, migrate to tissues, and engage in host-protective activities. All of these processes involve motility and cellular interactions—events that were hidden from view until recently. Introduced to immunology by three papers in this journal in 2002, in vivo live-cell imaging studies are revealing the behavior of cells mediating adaptive and innate immunity in diverse tissue environments, providing quantitative measurement of cellular motility, interactions, and response dynamics. Here, we review themes emerging from such studies and speculate on the future of immunoimaging.

Positron emission tomography (PET) and magnetic resonance imaging (MRI) are widely used in vivo imaging technologies with both clinical and biomedical research applications. The strengths of MRI include high-resolution, high-contrast morphologic imaging of soft tissues; the ability to image physiologic parameters such as diffusion and changes in oxygenation level resulting from neuronal stimulation; and the measurement of metabolites using chemical shift imaging. PET images the distribution of biologically targeted radiotracers with high sensitivity, but images generally lack anatomic context and are of lower spatial resolution. Integration of these technologies permits the acquisition of temporally correlated data showing the distribution of PET radiotracers and MRI contrast agents or MR-detectable metabolites, with registration to the underlying anatomy. An MRI-compatible PET scanner has been built for biomedical research applications that allows data from both modalities to be acquired simultaneously. Experiments demonstrate no effect of the MRI system on the spatial resolution of the PET system and <10% reduction in the fraction of radioactive decay events detected by the PET scanner inside the MRI. The signal-to-noise ratio and uniformity of the MR images, with the exception of one particular pulse sequence, were little affected by the presence of the PET scanner. In vivo simultaneous PET and MRI studies were performed in mice. Proof-of-principle in vivo MR spectroscopy and functional MRI experiments were also demonstrated with the combined scanner.

The area of offline handwritten text recognition(OHTR) has been widely researched in the last decades, but it stills an important research problem. The OHTR system has an objective to transform a document image into text data. Compared with online handwriting recognition, the dynamic information about the writing trajectories in OHTR is not available. Many advancements have been proposed in the literature, most notably the application of deep learning methods to OHTR. In this paper, we introduced how this problem has been handled in the past few decades, analyze the latest advancements and the potential directions for future research in this field.