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Rockville, MD, United States

Wicks G.G.,Applied Research LLC | Hill W.D.,Georgia Regents University | Weinberger P.M.,Georgia Regents University
International Journal of Applied Glass Science | Year: 2016

Tiny bubbles or glass microspheres/microcapsules are used in our society today in many ways. The microspheres can be solid or hollow and represent particles that are generally in the range of 0.1-100 μm. Solid and hollow microspheres have significantly different densities, properties, and capabilities and are commercially available. Special morphologies, formulations, and compositions can also be achieved by a variety of techniques in the laboratory. One of the most interesting morphologies of these tiny bubbles, are porous wall hollow glass microspheres, which are glass micro-balloons in which through-wall porosity was induced in the thin outer shells and controlled, on a scale of 10-100 nm. This unique porosity can be used to fill the microspheres with a variety of cargos of various contents that can later be released on demand. For medical applications, an interdisciplinary team investigated these tiny bubbles, as part of a new series of composites or medical cocktails. The microspheres are key components in the composites and can be used alone or mixed in various amounts and ratios, with a variety of contents, outer coatings, and/or biocompatible matrices, resulting in a wide range of medical cocktails designed and tailored for various applications. © 2016 American Ceramic Society and Wiley Periodicals, Inc. Source


Li H.,CAS South China Botanical Garden | Fu S.,CAS South China Botanical Garden | Zhao H.,Applied Research LLC | Xia H.,CAS South China Botanical Garden
Soil Science and Plant Nutrition | Year: 2010

The magnitude, temporal, and spatial patterns of nitrous oxide (N2O) fluxes in plantations are still largely unknown; however, they are crucial for our understanding and management of global greenhouse gas emissions. The objective of this study was to determine the effects of forest management practices, such as the understory removal and nitrogen (N)-fixing species (Cassia alata [C. alata]) seeding, on soil N2O fluxes in four forest plantations in southern China. Fluxes of N2O were measured in a Eucalyptus urophylla plantation (EUp), an Acacia crassicarpa plantation (ACp), 10 native species-mixed plantation (Tp), and 30 native species-mixed plantation (THp) by a static chamber method from June 2007 to May 2008 in Guangdong province, China. Four forest management treatments, including understory removal and replacement with C. alata (UR+CA), understory removal only (UR), C. alata seeding only (CA), and (4) control without any disturbances (CK), were applied in the four forest plantations. The results showed that N2O fluxes were higher under UR treatment as compared to CK in EUp (16.9 μg m-2 h-1), ACp (16.3 μg m-2 h-1), Tp (14.4 μg m-2 h-1), and THp (14.4 μg m-2 h-1) during the study period. Soil N2O fluxes under CA treatment tended to be enhanced in EUp (18.1 μg m-2 h-1), ACp (18.3 μg m-2 h-1), Tp (19 μg m-2 h-1), and THp (16.6 μg m-2 h-1), having higher values in CA than in CK. There were positive relationships between N2O fluxes and soil temperature (P < 0.01), soil moisture (P < 0.01), and nitrate (NO3)-N concentrations (P < 0.05). Our results indicated that soil NO3-N, soil temperature, and moisture are the primary controlling variables for soil N2O fluxes. The present study improved our understanding of soil N2O fluxes in forest plantations under different management practices. © 2010 Japanese Society of Soil Science and Plant Nutrition. Source


Herrmann H.C.,University of Pennsylvania | Baxter S.,Applied Research LLC | Ruiz C.E.,New Hill | Feldman T.E.,Evanston Hospital | Hijazi Z.M.,Rush Center for Congenital and Structural Heart Disease
Catheterization and Cardiovascular Interventions | Year: 2010

Background: Minimal information is available on the number and type of procedures being performed for structural and valvular heart disease, the physicians who perform these procedures, and on the training requirements for this emerging field. Methods: Surveys were performed using an online survey of members of the Society of Cardiac Angiography and Interventions (SCAI), including its Council on Structural Heart Disease and the Congenital Heart Disease Committee. The responses of 107 US-based interventional cardiologists were analyzed. A second questionnaire of a purposive sample of 10 training directors of US interventional cardiology programs was also performed. Results: Although many procedures (e.g., transseptal puncture, PFO, and ASD closure) are commonly performed by most respondents, others are limited to a significant minority of respondents (e.g., alcohol septal ablation, transcatheter valve repair, and implantation). In addition, the number of procedures performed varies greatly as does the training directors' estimate of the number necessary to gain proficiency. There is no single method being used to gain the requisite skills. A number of factors that limit the more widespread growth of this field were identified. Conclusions: The field of intervention for structural and valvular heart disease is new, growing rapidly, and will require a core knowledge base and new didactic methods. The cardiovascular community will be challenged to devise new training standards and credentialing approaches to serve interventionalists interested in this field. © 2010 Wiley-Liss, Inc. Source


Grant
Agency: Department of Defense | Branch: Air Force | Program: STTR | Phase: Phase I | Award Amount: 150.00K | Year: 2015

ABSTRACT: Our main objective in this project is to propose a novel Structured Sparse Priors for Target Recognition (SSPTR) system and to demonstrate that discriminative applications such as data clustering or target detection, tracking, and classification can be solved effectively and directly on the compressed measurement domain without the need to recover the original data. Our proposed sparse-representation discriminative algorithms have, at worst, the same level of complexity as popular sparse recovery algorithms in CS signal reconstruction while yielding comparable clustering/detection/classification accuracy as state-of-the-art discriminative strategies applying on original data. Here the crucial observation is that a test sample can be reasonably approximated as a linear combination of training samples belonging to the same class, with no contributions from training samples of other classes. Therefore, the sparse code which is often recovered via either basis pursuit or matching pursuit naturally encodes discriminative information that is crucial to classification tasks. In other words, the semantic (label) information of the signal of interest is directly captured in and instantaneously available from the sparse representation. Moreover, we also propose to further improve our baseline sparse-representation-based classification approach by the development of a novel unifying robust discriminative framework based on sparse representations directly on the collected measurements via context-aware and observable data-adaptive dictionaries and available domain-knowledge priors.; BENEFIT: Target/pattern detection, classification, and recognition applications will benefit more by incorporating such class-specific discriminative information than merely by conventional sparse signal recovery followed by a conventional classification strategy. Hence, we focus on maximizing the discriminability within the sparse recovery process by enforcing meaningful adaptive class-specific priors/constraints directly in the data measurement domain along with adaptive sparse representations in the measurement space explicitly for the purpose of image understanding and classification. ???Our proposed system can be used for missile seekers and other military surveillance and reconnaissance applications. We expect our software will have a unit price of $300 per device. With an estimated sales of over 20,000 units in the next decade, the military market potential results in more than 6 million dollars in the next decade. ????Besides military applications, ARLLCs technology will have many users in the commercial world. For example, border patrol, security monitoring in buildings and parking lots, coastal patrol, urban development monitoring, vegetation monitoring, hurricane damage assessment, and many others can benefit from our technology. We expect the commercial market size will be at least 20 million dollars over the next decade. ?


Grant
Agency: National Aeronautics and Space Administration | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 125.00K | Year: 2014

Some target signatures of interest in drought monitoring, flooding assessment, fire damage assessment, coastal changes, urban changes, etc. may need to be tracked periodically. In a typical change detection application, a hyperspectral image collected in an earlier visit may need to be compared with later images collected using different imagers with different viewing geometries, illumination, ground sampling distance (GSD), spectral sampling, signal-to-noise ratio (SNR), and atmospheric conditions. We propose a novel framework that can deal with all of the above challenges. We first propose to apply techniques such as flat-field to obtain the reflectance signature (fire damage signature, for example) from the target radiance signatures in a given hyperspectral image. The target reflectance signature is then saved in a target reflectance signature library for future use. After that, to detect targets (fire damage, for instance) in new images, we will expand a hyperspectral image processing system developed by the Johns Hopkins University/Applied Physics Lab (JHU/APL).

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