Models for hydrologic design of evapotranspiration landfill covers

The technology used in landfill covers is changing, and an alternative cover called the evapotranspiration (ET) landfill cover is coming into use. Important design requirements are prescribed by Federal rules and regulations for conventional landfill covers but not for ET landfill covers. There is no accepted hydrologic model for ET landfill cover design. This paper describes ET cover requirements and design issues, and assesses the accuracy of the EPIC and HELP hydrologic models when used for hydrologic design of ET covers. We tested the models against high-quality field measurements available from lysimeters maintained by the Agricultural Research Service of the U.S. Department of Agriculture at Coshocton, Ohio, and Bushland, Texas. The HELP model produced substantial errors in estimating hydrologic variables. The EPIC model estimated ET and deep percolation with errors less than 7% and 5%, respectively, and accurately matched extreme events with an error of less than 2% of precipitation. The EPIC model is suitable for use in hydrologic design of ET landfill covers.     

Electric field tuning of plasmonic response of nanodot array in liquid crystal matrix

In this work we demonstrate the feasibility of electric-field tuning of the plasmonic spectrum of a novel gold nanodot array in a liquid crystal matrix. As opposed to previously reported microscopically observed near-field spectral tuning of individual gold nanoparticles, this system exhibits macroscopic far-field spectral tuning. The nanodot-liquid crystal matrix also displays strong anisotropic absorption characteristics, which can be effectively described as a collective ensemble within a composite matrix in the lateral dimension and a group of noninteracting individual particles in the normal direction. The effective medium model and the Mie theory are employed to describe the experimental results.     

Biosynthetic precursors of fungal pyrrolizidines, the loline alkaloids

Loline alkaloids are saturated pyrrolizidines with a substituted 1-amino group and an oxygen bridge between C2 and C7, and are insecticidal metabolites of plant-symbiotic fungi (endophytes). Cultures of the endophyte, Neotyphodium uncinatum, incorporated labeled L-proline and L-homoserine into the 1-aminopyrrolizidine, N-formylloline. The A-ring carbons C1-C3 and the N1 were derived from L-homoserine; the B-ring carbons C5-C8 and the ring nitrogen were derived from L-proline. Incorporation of both deuterium atoms from L-[4,4-(2H2)]homoserine and feeding tests with labeled L-methionine indicated that L-homoserine incorporation was not achieved via aspartyl semialdehyde or S-adenosylmethionine, but probably involved a highly novel N--C bond-forming gamma-substitution reaction.     

A tool to visualize and evaluate data obtained by liquid chromatography-electrospray ionization-mass spectrometry

We present a software tool for visualizing data obtained from analyzing complex peptide mixtures by liquid chromatography (LC) electrospray ionization (ESI) mass spectrometry (MS). The data are represented as a two-dimensional density plot. For experiments employing collision-induced dissociation (CID), links are embedded in the image to the CID spectra and the corresponding peptide sequences that are represented by the respective feature. The image provides an intuitive method to evaluate sample quality and the performance of an LC-ESI-MS system and can be used to optimize experimental conditions. Local patterns of the image can also be used to identify chemical contaminants and specific peptide features. Therefore, this software tool may have broad application in MS-based proteomics.     

Grain Size and Wettability of TiO2/SiO2 Photocatalytic Composite Thin Films

The uniform transparent TiO2/SiO2 photocatalytic composite thin films are prepared by sol-gel method on the soda lime glass substrates, and characterized by UV-visible spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), BET surface area, FTIR spectroscopy and X-ray photoelectron spectroscopy (XPS). It was found that the addition of SiO2 to TiO2 thin films can suppress the grain growth of TiO2 crystal, increase the hydroxyl content on the surface of TiO2 films, lower the contact angle for water on TiO2 films and enhance the hydrophilic property of TiO2 films. The super-hydrophilic TiO2/SiO2 photocatalytic composite thin films with the contact angle of 0-° are obtained by the addition of 10%-20% SiO2 in mole fraction.     

全球第一套以德士古煤气化技术建设的联合循环发电装置Tampa电力公司Polk电站的运行状况

叙述了美国Ｔａｍｐａ电力公司２５０ＭＷ的大型煤气化联合循环发电（ＩＧＣＣ）商业化电站（Ｐｏｌｋ电站）自商业化运行以来德士古煤气化（ＴＧＰ）装置的运行情况、设备和技术特点,对中国采用ＴＧＰ技术的厂家有一定的借鉴参考价值,希望对国内ＩＧＣＣ技术的应用有积极的推进作用。     

Experimental Determination of Mg Activities in Fe-Mg Solutions

The thermodynamics of magnesium in liquid iron was determined at 1823 K (1550 °C). For this purpose, liquid iron was equilibrated with Ag-Mg alloys in a semienclosed molybdenum vessel. From the partition of magnesium between iron and silver, the activity coefficient of Mg and the self-interaction parameter e_\textMg^\textMg \varepsilon_{\text{Mg}}^{\text{Mg}} were determined.     

Synthesis of biocompatible, mesoporous Fe(3)O(4) nano/microspheres with large surface area for magnetic resonance imaging and therapeutic applications

This article reports the fabrication of mesoporous Fe(3)O(4) nano/microspheres with a high surface area value (163 m(2)/g, Brunauer-Emmett-Teller) and demonstrates their use for drug loading, release, and magnetic resonance imaging (MRI). These monodispersed, mesoporous Fe(3)O(4) nano/microspheres with controllable average sizes ranging from 50 to 200 nm were synthesized using a Fe(3)O(4)/poly(acrylic acid) hybrid sphere template and subsequent silica shell formation and removal. We found that the SiO(2) coating is a crucial step for the successful synthesis of uniform mesoporous Fe(3)O(4) nano/microspheres. The as-synthesized mesoporous Fe(3)O(4) nanospheres show a high magnetic saturation value (M(s) = 48.6 emu/g) and could be used as MRI contrast agents (r(2) = 36.3 s(-1) mM(-1)). Trypan blue exclusion and MTT assay (see Supporting Information ) cytotoxicity analyses of the nanospheres based on HepG2 and MDCK cells showed that the products were biocompatible, with a lower toxicity than lipofectamine (positive control). Hydrophilic ibuprofen and hydrophobic zinc(II) phthalocyanine drug loading into mesoporous Fe(3)O(4) nanospheres and selected release experiments were successfully achieved. The potential use of mesoporous Fe(3)O(4) nanospheres in biomedical applications, in light of the nano/microspheres' efficient drug loading and release, MRI, and low cytotoxicity, has been demonstrated. It is envisaged that mesoporous Fe(3)O(4) nanospheres can be used as drug carriers and MRI contrast agents for the reticuloendothelial system; they can also be delivered locally, such as via a selective catheter.     

Medical Diagnosis Using Machine Learning: A Statistical Review

Decision making in case of medical diagnosis is a complicated process. A large number of overlapping structures and cases, and distractions, tiredness, and limitations with the human visual system can lead to inappropriate diagnosis. Machine learning (ML) methods have been employed to assist clinicians in overcoming these limitations and in making informed and correct decisions in disease diagnosis. Many academic papers involving the use of machine learning for disease diagnosis have been increasingly getting published. Hence, to determine the use of ML to improve the diagnosis in varied medical disciplines, a systematic review is conducted in this study. To carry out the review, six different databases are selected. Inclusion and exclusion criteria are employed to limit the research. Further, the eligible articles are classified depending on publication year, authors, type of articles, research objective, inputs and outputs, problem and research gaps, and findings and results. Then the selected articles are analyzed to show the impact of ML methods in improving the disease diagnosis. The findings of this study show the most used ML methods and the most common diseases that are focused on by researchers. It also shows the increase in use of machine learning for disease diagnosis over the years. These results will help in focusing on those areas which are neglected and also to determine various ways in which ML methods could be employed to achieve desirable results.     

Denoising Medical Images Using Deep Learning in IoT Environment

Medical Resonance Imaging (MRI) is a noninvasive, nonradioactive, and meticulous diagnostic modality capability in the field of medical imaging. However, the efficiency of MR image reconstruction is affected by its bulky image sets and slow process implementation. Therefore, to obtain a high-quality reconstructed image we presented a sparse aware noise removal technique that uses convolution neural network (SANR_CNN) for eliminating noise and improving the MR image reconstruction quality. The proposed noise removal or denoising technique adopts a fast CNN architecture that aids in training larger datasets with improved quality, and SARN algorithm is used for building a dictionary learning technique for denoising large image datasets. The proposed SANR_CNN model also preserves the details and edges in the image during reconstruction. An experiment was conducted to analyze the performance of SANR_CNN in a few existing models in regard with peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mean squared error (MSE). The proposed SANR_CNN model achieved higher PSNR, SSIM, and MSE efficiency than the other noise removal techniques. The proposed architecture also provides transmission of these denoised medical images through secured IoT architecture.