ALBERT

Description: Lithium-oxygen (Li-O2) batteries have the highest theoretical energy density of all the Li-based energy storage systems, but many challenges prevent them from practical use. A major obstacle is the sluggish performance of the air cathode, where both oxygen reduction (discharge) and oxygen evolution (charge) reactions occur. Recently there have been significant advances in the development of graphene-based air cathode materials with a large surface area and high catalytic activity for both oxygen reduction and evolution reactions. However, most studies reported so far have examined air cathodes with a limited areal mass loading rarely exceeding 1 mg/cm2. Despite the high gravimetric capacity values achieved, therefore, the actual (areal) capacities of those batteries were far from sufficient for practical applications. Here, we present the fabrication, performance, and mechanistic investigations of high mass loading (up to 10 mg/cm2) graphene-based air electrodes for high-performance Li-O2 batteries. Such air electrodes could be easily prepared within minutes under solvent-free and binder-free conditions by compression molding holey graphene because of the unique dry compressibility of this graphene structural derivative with in-plane holes. High mass loading Li-O2 batteries prepared in this manner exhibited excellent gravimetric capacity and thus ultrahigh areal capacity (as high as ~40 mAh/cm2). The batteries were also cycled at a high curtailing areal capacity (2 mAh/cm2), with ultrathick cathodes showing a better stability during cycling than thinner ones. Detailed postmortem analyses of the electrodes clearly revealed the battery failure mechanisms under both primary and secondary modes, which were the oxygen diffusion blockage and the catalytic site deactivation, respectively. The results strongly suggest that the dry-pressed holey graphene electrodes are a highly viable architectural platform for high capacity, high performance air cathodes in Li-O2 batteries of practical significance.

Description: The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

Description: During the last several years, a number of airborne and satellite hyperspectral sensors have been developed or improved for remote sensing applications. Imaging spectrometry allows the detection of materials, objects and regions in a particular scene with a high degree of accuracy. Hyperspectral data typically consist of hundreds of thousands of spectra, so the analysis of this information is a key issue. Mathematical morphology theory is a widely used nonlinear technique for image analysis and pattern recognition. Although it is especially well suited to segment binary or grayscale images with irregular and complex shapes, its application in the classification/segmentation of multispectral or hyperspectral images has been quite rare. In this paper, we discuss a new completely automated methodology to find endmembers in the hyperspectral data cube using mathematical morphology. The extension of classic morphology to the hyperspectral domain allows us to integrate spectral and spatial information in the analysis process. In Section 3, some basic concepts about mathematical morphology and the technical details of our algorithm are provided. In Section 4, the accuracy of the proposed method is tested by its application to real hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer. Some details about these data and reference results, obtained by well-known endmember extraction techniques, are provided in Section 2. Finally, in Section 5 we expose the main conclusions at which we have arrived.

Description: The presence of lysylpyridinoline (LP) as a nonreducible cross-link in appreciable quantities has primarily been limited to the mineralized tissues, bone and dentin. However, the results reported here show that LP is not only present in the hypertrophic cartilage of the tibiotarsus isolated from newly hatched broiler chicks, but it is approx. 4-fold as concentrated as hydroxylysylpyridinoline (HP). Bone and articular cartilage surrounding the hypertrophic cartilage do not contain measurable quantities of LP. Purified LP has a fluorescent scan similar to purified HP and literature values, confirming that we indeed were measuring LP. Also, the cartilage lesion produced by immature chondrocytes from birds with tibial dyschondroplasia had LP but the HP:LP ratio was 〉 1. Thus, the low HP:LP ratio could be a marker for hypertrophic cartilage in avians.

Description: The growth hormone (GH)-deficient dwarf rat was used to investigate recombinant human (rh) GH-induced bone formation and to determine whether rhGH facilitates simultaneous increases in bone formation and bone maturation during rapid growth. Twenty dwarf rats, 37 days of age, were randomly assigned to dwarf plus rhGH (GH; n = 10) and dwarf plus vehicle (n = 10) groups. The GH group received 1.25 mg rhGH/kg body wt two times daily for 14 days. Biochemical, morphological, and X-ray diffraction measurements were performed on the femur middiaphysis. rhGH stimulated new bone growth in the GH group, as demonstrated by significant increases (P 〈 0.05) in longitudinal bone length (6%), middiaphyseal cross-sectional area (20%), and the amount of newly accreted bone collagen (28%) in the total pool of middiaphyseal bone collagen. Cortical bone density, mean hydroxyapatite crystal size, and the calcium and collagen contents (microgram/mm3) were significantly smaller in the GH group (P 〈 0.05). Our findings suggest that the processes regulating new collagen accretion, bone collagen maturation, and mean hydroxyapatite crystal size may be independently regulated during rapid growth.

Description: The purpose of this study was to investigate the impact of recombinant human growth hormone (rhGH) on patella tendon (PT), medial collateral ligament (MCL), and lateral collateral ligament (LCL) on collagen growth and maturational changes in dwarf GH-deficient rats. Twenty male Lewis mutant dwarf rats, 37 days of age, were randomly assigned to Dwarf + rhGH (n = 10) and Dwarf + vehicle (n = 10) groups. The GH group received 1.25 mg rhGH/kg body wt twice daily for 14 days. rhGH administration stimulated dense fibrous connective tissue growth, as demonstrated by significant increases in hydroxyproline specific activity and significant decreases in the non-reducible hydroxylysylpyridinoline (HP) collagen cross-link contents. The increase in the accumulation of newly accreted collagen was 114, 67, and 117% for PT, MCL, and LCL, respectively, in 72 h. These findings suggest that a short course rhGH treatment can affect the rate of new collagen production. However, the maturation of the tendon and ligament tissues decreased 18-25% during the rapid accumulation of de novo collagen. We conclude that acute rhGH administration in a dwarf rat can up-regulate new collagen accretion in dense fibrous connective tissues, while causing a reduction in collagen maturation. Copyright 2002 Elsevier Science Ltd.

Description: We investigated the hypothesis that hindlimb unloading inhibits healing in fibrous connective tissue such as ligament. Male rats were assigned to 3- and 7-wk treatment groups with three subgroups each: sham control, ambulatory healing, and hindlimb-suspended healing. Ambulatory and suspended animals underwent surgical rupture of their medial collateral ligaments, whereas sham surgeries were performed on control animals. After 3 or 7 wk, mechanical and/or morphological properties were measured in ligament, muscle, and bone. During mechanical testing, most suspended ligaments failed in the scar region, indicating the greatest impairment was to ligament and not to bone-ligament insertion. Ligament testing revealed significant reductions in maximum force, ultimate stress, elastic modulus, and low-load properties in suspended animals. In addition, femoral mineral density, femoral strength, gastrocnemius mass, and tibialis anterior mass were significantly reduced. Microscopy revealed abnormal scar formation and cell distribution in suspended ligaments with extracellular matrix discontinuities and voids between misaligned, but well-formed, collagen fiber bundles. Hence, stress levels from ambulation appear unnecessary for formation of fiber bundles yet required for collagen to form structurally competent continuous fibers. Results support our hypothesis that hindlimb unloading impairs healing of fibrous connective tissue. In addition, this study provides compelling morphological evidence explaining the altered structure-function relationship in load-deprived healing connective tissue.

Description: Multilayer optics operated at normal incidence offer a powerful new technology for the study of the solar spectrum in the XUV. The spectra of most cosmic X-ray sources are strongly extinguished at wavelengths above 40 A due to absorption and scattering by interstellar grains. We describe a number of configurations which allow multilayer optics to be used at nonnormal angles of incidence in conjunction with grazing incidence optics to analyze the spectra of cosmic X-ray sources in the wavelength interval between 1.5 and 40 A. These optical configurations utilize both multilayer mirrors and gratings, and permit the efficient observation of extended sources using stigmatic spectrographs. The response of the instruments described to typical cosmic X-ray sources is also discussed.

Description: One of the basic requirements in engineering analysis is the development of a mathematical model describing the system. Frequently comparisons with test data are used as a measurement of the adequacy of the model. An attempt is typically made to update or improve the model to provide a test verified analysis tool. System identification provides a systematic procedure for accomplishing this task. The terms system identification, parameter estimation, and model correlation all refer to techniques that use test information to update or verify mathematical models. The goal of system identification is to improve the correlation of model predictions with measured test data, and produce accurate, predictive models. For nonmetallic structures the modeling task is often difficult due to uncertainties in the elastic constants. A finite element model of the shell was created, which included uncertain orthotropic elastic constants. A modal survey test was then performed on the shell. The resulting modal data, along with the finite element model of the shell, were used in a Bayes estimation algorithm. This permitted the use of covariance matrices to weight the confidence in the initial parameter values as well as confidence in the measured test data. The estimation procedure also employed the concept of successive linearization to obtain an approximate solution to the original nonlinear estimation problem.

Description: A refinement of the current ultrasonic elasticity technique was used to measure the orthotropic elastic properties of rat cortical bone as well as to quantify changes in elastic properties, density, and porosity of the dwarf rat cortex after a treatment with recombinant human growth hormone (rhGH). The ultrasonic elasticity technique was refined via optimized signal management of high-frequency wave propagation through cubic cortical specimens. Twenty dwarf rats (37 days old) were randomly assigned to two groups (10 rats each). The dwarf rat model (5-10% of normal GH) was given subcutaneous injections of either rhGH or saline over a 14-day treatment period. Density was measured using Archimedes technique. Porosity and other microstructural characteristics were also explored via scanning electron microscopy and image analysis. Statistical tests verified significant decreases in cortical orthotropic Young's (-26.7%) and shear (-16.7%) moduli and density (-2.42%) concomitant with an increase in porosity (+125%) after rhGH treatments to the dwarf model (p 〈 0.05). A change in material symmetry from orthotropy toward planar isotropy within the radial-circumferential plane after GH treatments was also noted. These results demonstrate some alteration in bone properties at this time interval. Structural implications of these changes throughout physiological loading regimens should be explored.