Study of food products containing gluten by using the method of polymerase chain reaction

The results of studies on the detection of gluten in the 7 products, members of the group of gluten-free, used for patients with celiac disease. Used the method of polymerase chain reaction detection in real time (by method of polymerase chain reaction) using a test system SureFood Allergen Gluten. With this method, fully meets the requirements of the Codex Alimentarius Commission, confirmed the compliance of the investigated food gluten-free category, used for patients with celiac disease.     

Preparation and utilization of microporous molecularly imprinted polymer for sustained release of tetracycline

A polyacrylate tetracycline (TC) selective microporous molecularly imprinted polymer was prepared in three different porogenic solvents (chloroform, acetonitrile, and methanol) via precipitation polymerization, using methacrylic acid monomer, ethylene glycol dimethacrylate crosslinker, and TC as template. In all three solvents this method produced microporous particles in the scale range (200–400 nm), simply, quickly, cleanly, and in good yield. The effect of polarity of porogenic solvents on binding capacity was investigated. The imprinted polymer prepared in chloroform gave much higher binding capacity (K_D = 198.6) for TC than the polymers prepared in acetonitrile (K_D = 133.2) or methanol (K_D = 104.7). The selectivity of imprinted polymers was evaluated by rebinding other structurally similar compounds. The results clearly indicated that the imprinted acrylate polymer exhibits an excellent selectivity toward TC, and has better ability to control the release of TC than the non‐imprinted polymer.© 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Reducing Data Cache Susceptibility to Soft Errors

Data caches are a fundamental component of most modern microprocessors. They provide for efficient read/write access to data memory. Errors occurring in the data cache can corrupt data values or state, and can easily propagate throughout the memory hierarchy. One of the main threats to data cache reliability is soft (transient, nonreproducible) errors. These errors can occur more often than hard (permanent) errors, and most often arise from single event upsets (SEUs) caused by strikes from energetic particles such as neutrons and alpha particles. Many protection techniques exist for data caches; the most common are ECC (error correcting codes) and parity. These protection techniques detect all single bit errors and, in the case of ECC, correct them. To make proper design decisions about which protection technique to use, accurate design-time modeling of cache reliability is crucial. In addition, as caches increase in storage capacity, another important goal is to reduce the failure rate of a cache, to limit disruption to normal system operation. In this paper, we present our modeling approach for assessing the impact of soft errors using architectural simulators. We also describe a new technique for reducing the vulnerability of data caches: refetching. By selectively refetching cache lines from the ECC-protected L2 cache, we can significantly reduce the vulnerability of the L1 data cache. We discuss and present results for two different algorithms that perform selective refetch. Experimental results show that we can obtain an 85 percent decrease in vulnerability when running the SPEC2K benchmark suite while only experiencing a slight decrease in performance. Our results demonstrate that selective refetch can cost-effectivety decrease the error rate of an L1 data cache     

Mapping mineralogical alteration using principal‐component analysis and matched filter processing in the Takab area,north‐west Iran,from ASTER data

The Takab area, located in north‐west Iran, is an important gold mineralized region with a long history of gold mining. The gold is associated with toxic metals/metalloids. In this study, Advanced Space Borne Thermal Emission and Reflection Radiometer data are evaluated for mapping gold and base‐metal mineralization through alteration mapping. Two different methods are used for argillic and silicic alteration mapping: selective principal‐component analysis and matched filter processing (MF). Running a selective principal‐component analysis using the main spectral characteristics of key alteration minerals enhanced the altered areas in PC2. MF using spectral library and laboratory spectra of the study area samples gave similar results. However, MF, using the image reference spectra from principal component (PC) images, produced the best results and indicated the advantage of using image spectra rather than library spectra in spectral mapping techniques. It seems that argillic alteration is more effective than silicic alteration for exploration purposes. It is suggested that alteration mapping can also be used to delineate areas contaminated by potentially toxic metals.     

Using Local Popularity of Web Resources for Geo-Ranking of Search Engine Results

Search engines retrieve and rank Web pages which are not only relevant to a query but also important or popular for the users. This popularity has been studied by analysis of the links between Web resources. Link-based page ranking models such as PageRank and HITS assign a global weight to each page regardless of its location. This popularity measurement has shown successful on general search engines. However unlike general search engines, location-based search engines should retrieve and rank higher the pages which are more popular locally. The best results for a location-based query are those which are not only relevant to the topic but also popular with or cited by local users. Current ranking models are often less effective for these queries since they are unable to estimate the local popularity. We offer a model for calculating the local popularity of Web resources using back link locations. Our model automatically assigns correct locations to the links and content and uses them to calculate new geo-rank scores for each page. The experiments show more accurate geo-ranking of search engine results when this model is used for processing location-based queries.     

Prediction of influence parameters on the hot rolling process using finite element method and neural network

In the present investigation, a hot rolling process of AA5083 aluminum alloy is simulated using the finite element method. The temperature distribution in the roll and the slab, the stress, strain and strain rate fields, are extracted throughout a steady-state analysis of the process. The main hypotheses adopted in the formulation are: the thermo-viscoplastic behavior of the material expressed by Perzyna constitutive equation and rolling under plane-deformation conditions. The main variables that characterize the rolling process, such as the geometry of the slab, load, rolling speed, percentage of thickness reduction, initial thickness of the slab and friction coefficient, have been expressed in a parametric form giving a good flexibility to the model. The convergence of the results has been evaluated using experimental and theoretical data available in the literature. Since the FE simulation of the process is a time-consuming procedure, an artificial neural network (ANN) has been designed based on the back propagation method. The outputs of the FE simulation of the problem are used for training the network and then, the network is employed for prediction of the behavior of the slab during the hot rolling process.     

Combined grain refining and modification of conventional and rheo-cast A356 Al–Si alloy

This paper describes a comprehensive study on the combined addition of Ti–B grain refiner and Sr modifier elements to A356 Al–Si alloy. Using different qualitative and quantitative techniques in conventional and semi-solid metal castings, it is shown that, while the refiner and modifier elements affect respectively the nucleation and eutectic reactions, the combined addition not only replicates both individual element effects but also gives the added bonus of better globularity in the semi-solid metal process. A new innovative concept is introduced for fluidity measurement by using the magnitude of remaining liquid in the form of drainage, which is increased by combined treatment.     

Synthesis,recognition and evaluation of molecularly imprinted polymer nanoparticle using miniemulsion polymerization for controlled release and analysis of risperidone in human plasma samples

We prepared high selective imprinted nanoparticle polymers by a miniemulsion polymerization technique, using risperidone as the template, MAA as the functional monomers, and TRIM as the cross-linker in acetonitrile as solvent. The morphology of the nanoparticles determined by scanning electron microscopy (SEM) images and drug release, binding properties and dynamic light scattering (DLS) of molecularly imprinted polymers (MIPs) were studied. Controlled release of risperidone from nanoparticles was investigated through in 1% wt sodium dodecyl sulfate aqueous solution and by measuring the absorbance by HPLC-UV. The results showed that the imprinted nanoparticles exhibited a higher binding level and slower release rate than non-imprinted nanoparticles, which contributed to interaction of risperidone with imprinted cavities within nanoparticles. Furthermore, the results from HPLC showed good precision (5% for 50.0 μg L^?1) and recoveries (between 86–91) using MIP from human plasma samples.     

Best of Both Worlds: Synergistically Derived Material Properties via Additive Manufacturing of Nanocomposites

With an exponential rise in the popularity and availability of additive manufacturing (AM), a large focus has been directed toward research in this topic's movement, while trying to distinguish themselves from similar works by simply adding nanomaterials to their process. Though nanomaterials can add impressive properties to nanocomposites (NCs), there are expansive amounts of opportunities that are left unexplored by simply combining AM with NCs without discovering synergistic effects and novel emerging material properties that are not possible by each of these alone. Cooperative, evolving properties of NCs in AM can be investigated at the processing, morphological, and architectural levels. Each of these categories are studied as a function of the amplifying relationship between nanomaterials and AM, with each showing the systematically selected material and method to advance the material performance, explore emergent properties, as well as improve the AM process itself. Innovative, advanced materials are key to faster development cycles in disruptive technologies for bioengineering, defense, and transportation sectors. This is only possible by focusing on synergism and amplification within additive manufacturing of nanocomposites.