Optimization of a natural gas SI engine employing EGR strategy using a two-zone combustion model

Natural gas has been recently used as an alternative to conventional fuels in order to satisfy some environmental and economical concerns. In this study, a natural gas spark-ignition engine employing cooled exhaust gas recirculation (EGR) strategy in a high pressure inlet condition was optimized. Both engine compression ratio and start of combustion timing were optimized in order to obtain the lowest fuel consumption accompanied with high power and low emissions. That was achieved numerically by developing a computer simulation of the four-stroke spark-ignition natural gas engine. A two-zone combustion model was developed to simulate the in-cylinder conditions during combustion. A kinetic model based on the extended Zeldovich mechanism was also developed in order to predict NO emission. In addition, a knocking model was incorporated with the two-zone combustion model in order to predict any auto-ignition that might occur. It was found that the value of the compression ratio at which the minimum fuel consumption occurs varies with the engine speed. A minimum fuel consumption of about 200 g/kW h was achieved at an engine speed of 1500 rpm, inlet conditions of 200 kPa and 333 K, and a compression ratio of about 12. Also, it was found that cooled EGR can significantly reduce NO emission at high compression ratio conditions. NO emission decreased by about 28% when EGR was increased from 20% at compression ratio of 10 to 27% at compression of 12 at the same engine speed of 3000 rpm.     

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10⁻⁶). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.     

An Eco-Friendly Approach to the Control of Pathogenic Microbes and Anopheles stephensi Malarial Vector Using Magnesium Oxide Nanoparticles (Mg-NPs) Fabricated by Penicillium chrysogenum

The discovery of eco-friendly, rapid, and cost-effective compounds to control diseases caused by microbes and insects are the main challenges. Herein, the magnesium oxide nanoparticles (MgO-NPs) are successfully fabricated by harnessing the metabolites secreted by Penicillium chrysogenum. The fabricated MgO-NPs were characterized using UV-Vis, XRD, TEM, DLS, EDX, FT-IR, and XPS analyses. Data showed the successful formation of crystallographic, spherical, well-dispersed MgO-NPs with sizes of 7–40 nm at a maximum wavelength of 250 nm. The EDX analysis confirms the presence of Mg and O ions as the main components with weight percentages of 13.62% and 7.76%, respectively. The activity of MgO-NPs as an antimicrobial agent was investigated against pathogens Staphylococcus aureus, Bacillus subtilis, Pseudomonas aeruginosa, Escherichia coli, and Candida albicans, and exhibited zone of inhibitions of 12.0 ± 0.0, 12.7 ± 0.9, 23.3 ± 0.8, 17.7 ± 1.6, and 14.7 ± 0.6 mm respectively, at 200 µg mL⁻¹. The activity is decreased by decreasing the MgO-NPs concentration. The biogenic MgO-NPs exhibit high efficacy against different larvae instar and pupa of Anopheles stephensi, with LC50 values of 12.5–15.5 ppm for I–IV larvae instar and 16.5 ppm for the pupa. Additionally, 5 mg/cm² of MgO-NPs showed the highest protection percentages against adults of Anopheles stephensi, with values of 100% for 150 min and 67.6% ± 1.4% for 210 min.     

Synthesis and characterization of chitosan-coated magnetite nanoparticles using a modified wet method for drug delivery applications

Abstract

Immobilizing various chemical functionalities on the surfaces of magnetite nanoparticles extends these applications without affecting the overall magnetic properties of the coated nanoparticles. In this study, magnetite nanoparticles have been prepared in the presence of chitosan using a simple modified wet method. Composition, morphology and magnetic properties of the chitosan-coated nanoparticles were investigated. Results showed the formation of coating with various thicknesses on the surfaces of the superparamagnetic nanoparticles. This in turn reduced the magnetization of the nanoparticles to some extent. The least particle size obtained in the presence of chitosan was 10?nm.     

On the inhomogeneous hydration kinetics and stiffness evolution of HNBR‐MgO reactive elastomer composites

Swellable elastomers are widely used in oilfield industry for sealing and zonal isolation applications. These materials need to sustain a large amount of external load after swelling. A newly developed reactive hydrogenated nitrile butadiene rubber (HNBR) based elastomer composite with magnesium oxide (MgO) as filler can swell and stiffen when exposed to water, which makes it ideal for oil field applications. However, both the filler hydration and the stiffness evolution inside this composite material are observed to be highly inhomogeneous even for samples on the length scale of millimeters. To understand this coupled diffusion‐hydration process is critical for applications of these materials with larger length scales. In this work, the hydration kinetics and stiffness evolution of the HNBR‐MgO composite are quantitatively studied on microscopic level. The extent of MgO hydration along the thickness of the sample are measured at the different stage of swelling. These results are used to determine the diffusion coefficient of water inside the composite. The diffusivity increases orders of magnitude after the filler hydration. In addition, the modulus change is non‐proportional to the degree of filler hydration as demonstrated by instrumented grid indentation on the hydrated composites. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43420.     

An Indexing Method for Answering Queries on Moving Objects

We consider the problem of indexing a set of objects moving in d-dimensional spaces along linear trajectories. A simple external-memory indexing scheme is proposed to efficiently answer general range queries. The following are examples of the queries that can be answered by the proposed method: report all moving objects that will (i) pass between two given points within a specified time interval; (ii) become within a given distance from some or all of a given set of other moving objects. Our scheme is based on mapping the objects to a dual space, where queries about moving objects are transformed into polyhedral queries concerning their speeds and initial locations. We then present a simple method for answering such polyhedral queries, based on partitioning the space into disjoint regions and using a B+-tree to index the points in each region. By appropriately selecting the boundaries of each region, we guarantee an average search time that matches a known lower bound for the problem. Specifically, for a fixed d, if the coordinates of a given set of N points are statistically independent, the proposed technique answers polyhedral queries, on the average, in O((N/B)^1−1/d⋅(log _B N)^1/d+K/B) I/O's using O(N/B) space, where B is the block size, and K is the number of reported points. Our approach is novel in that, while it provides a theoretical upper bound on the average query time, it avoids the use of complicated data structures, making it an effective candidate for practical applications. The proposed index is also dynamic in the sense that it allows object insertion and deletion in an amortized update cost of log _B(N) I/O's. Experimental results are presented to show the superiority of the proposed index over other methods based on R-trees. recommend Ahmed Elmagarmid     

Fatigue Life Evaluation of Concrete Bridge Deck Slabs Reinforced with Glass FRP Composite Bars

Since bridge deck slabs directly sustain repeated moving wheel loads, they are one of the most bridge elements susceptible to fatigue failure. Recently, glass fiber-reinforced polymer (FRP) composites have been widely used as internal reinforcement for concrete bridge deck slabs as they are less expensive compared to the other kinds of FRPs (carbon and aramid). However, there is still a lack of information on the performance of FRP–reinforced concrete elements subjected to cyclic fatigue loading. This research is designed to investigate the fatigue behavior and fatigue life of concrete bridge deck slabs reinforced with glass FRP bars. A total of five full-scale deck slabs were constructed and tested under concentrated cyclic loading until failure. Different reinforcement types (steel and glass FRP), ratios, and configurations were used. Different schemes of cyclic loading (accelerated variable amplitude fatigue loading) were applied. Results are presented in terms of deflections, strains in concrete and FRP bars, and crack widths at different levels of cyclic loading. The results showed the superior fatigue performance and longer fatigue life of concrete bridge deck slabs reinforced with glass FRP composite bars.     

Structured literature image finder: Parsing text and figures in biomedical literature

The SLIF project combines text-mining and image processing to extract structured information from biomedical literature.SLIF extracts images and their captions from published papers. The captions are automatically parsed for relevant biological entities (protein and cell type names), while the images are classified according to their type (e.g., micrograph or gel). Fluorescence microscopy images are further processed and classified according to the depicted subcellular localization.The results of this process can be queried online using either a user-friendly web-interface or an XML-based web-service. As an alternative to the targeted query paradigm, SLIF also supports browsing the collection based on latent topic models which are derived from both the annotated text and the image data.The SLIF web application, as well as labeled datasets used for training system components, is publicly available at http://slif.cbi.cmu.edu.     

Fast computation of spatial selections and joins using graphics hardware

Spatial database operations are typically performed in two steps. In the filtering step, indexes and the minimum bounding rectangles (MBRs) of the objects are used to quickly determine a set of candidate objects. In the refinement step, the actual geometries of the objects are retrieved and compared to the query geometry or each other. Because of the complexity of the computational geometry algorithms involved, the CPU cost of the refinement step is usually the dominant cost of the operation for complex geometries such as polygons. Although many run-time and pre-processing-based heuristics have been proposed to alleviate this problem, the CPU cost still remains the bottleneck. In this paper, we propose a novel approach to address this problem using the efficient rendering and searching capabilities of modern graphics hardware. This approach does not require expensive pre-processing of the data or changes to existing storage and index structures, and is applicable to both intersection and distance predicates. We evaluate this approach by comparing the performance with leading software solutions. The results show that by combining hardware and software methods, the overall computational cost can be reduced substantially for both spatial selections and joins. We integrated this hardware/software co-processing technique into a popular database to evaluate its performance in the presence of indexes, pre-processing and other proprietary optimizations. Extensive experimentation with real-world data sets show that the hardware-accelerated technique not only outperforms the run-time software solutions but also performs as well if not better than pre-processing-assisted techniques.