Radiosynthesis and biodistribution of [^18F]-tetracosactide using a semi-automated [^18F]SFB production module

In order to prepare a specific melanocortin type 2 receptor (MC2R) ligand, b1-24-corticotrophin was pre-pared in one-step reaction with [18F] SFB and b-1-24-corticotrophin pharmaceutical solution (1 mg/mL, pH=6.5). [18F]SFB was prepared in a semi-automated module in two steps with an overall radiochemical yield of 47% to EOB (not-decay corrected) in 90 min. The 18F-labeled intermediates and 18F-labeled peptide was checked by RTLC and HPLC. The results show that the radiochemical purity is >95% and the yield to EOB (not-decay corrected) is 29% for final 18F-labeled peptide at optimized conditions. Preliminary in vivo studies in normal mice were performed to deter-mine biodistribution of the 18F-labeled peptide for 150 min. The results show that the major tracer uptake is consistent with the natural distribution of MC2R receptors in mammals. Testes/blood and testes/muscle ratios for 18F-labeled peptide at 150 min were 184 and 1.56, respectively, and adipocyte/blood and adipocyte/muscle ratios at 120 min were 221 and 142, respectively. The data support the specific receptor binding of the radiolabeled peptide as reported for MC2R receptor accumulation in adipocytes and testes and demonstrates the retention of biological activity of the pep-tide. This tracer can be used in detection of MC2R distribution in malignancies and sex organ diseases.     

Solving the stochastic support vector regression with probabilistic constraints by a high-performance neural network model

This paper offers a recurrent neural network to support vector machine (SVM) learning in stochastic support vector regression with probabilistic constraints. The SVM is first converted into an equivalent quadratic programming (QP) formulation in linear and nonlinear cases. An artificial neural network for SVM learning is then proposed. The presented neural network framework guarantees obtaining the optimal solution of the SVM problem. The existence and convergence of the trajectories of the network are studied. The Lyapunov stability for the considered neural network is also shown. The efficiency of the proposed method is shown by three illustrative examples.

     

Enhanced oil recovery from carbonate reservoirs by spontaneous imbibition of low salinity water

An experimental study was performed to investigate the impact of low salinity water on wettability alteration in carbonate core samples from southern Iranian reservoirs by spontaneous imbibition. In this paper, the effect of temperature, salinity, permeability and connate water were investigated by comparing the produced hydrocarbon curves. Contact angle measurements were taken to confirm the alteration of surface wettability of porous media. Oil recovery was enhanced by increasing the dilution ratio of sea water, and there existed an optimum dilution ratio at which the highest oil recovery was achieved. In addition, temperature had a very significant impact on oil recovery from carbonate rocks. Furthermore, oil recovery from a spontaneous imbibition process was directly proportional to the permeability of the core samples. The presence of connate water saturation inside the porous media facilitated oil production significantly. Also, the oil recovery from porous media was highly dependent on ion repulsion/attraction activity of the rock surface which directly impacts on the wettability conditions. Finally, the highest ion attraction percentage was measured for sodium while there was no significant change in pH for all experiments.     

Computer simulation of the optical properties of high-temperature cermet solar selective coatings

A computer simulation is developed to calculate the solar absorptance and thermal emittance of various configurations of cermet solar selective coatings. Special attention has been paid to those material combinations, which are commonly used in high-temperature solar thermal applications. Moreover, other material combinations such as two-, three- and four-cermet-layer structures as solar selective coatings have been theoretically analyzed by computer simulation using three distinct physical models of Ping Sheng, Maxwell–Garnett and Bruggeman. The novel case of two-cermet-layer structure with different cermet components has also been investigated. The results were optimized by allowing the program to manipulate the metal volume fraction and thickness of each layer and the results compared to choose the best possible configuration. The calculated results are within the range of 0.91–0.97 for solar absorptance and 0.02–0.07 for thermal emittance at room temperature.     

A novel algorithm to study the impact of the mismatch on analog building blocks: a case study in basic 35 nm CMOS amplifiers

In this paper, the context of modeling of the impact of mismatch and statistical variations on analogue circuit building blocks is emphasized. The aim is to develop a new algorithm which predicts the statistical behavior of important parameters of an amplifier including output resistance, voltage gain and trans-conductance. The relative error of standard deviation of statistical parameters will remain less than 5% compared with the most accurate Monte-Carlo (MC) simulations using atomistic library model-cards. In comparison with other models which are based on the normal distribution of parameters, the proposed model does not need this limiting presumption. On the other hand, the proposed algorithm is more efficient compared with time consuming MC atomistic simulations.     

Hybrid sonochemic urea-nitrate combustion preparation of CuO/ZnO/Al2O3 nanocatalyst used in fuel cell-grade hydrogen production from methanol: Effect of sonication and fuel/nitrate ratio

Fuel cell-grade hydrogen production has been studied via steam reforming of methanol (SRM) over a series of CuO/ZnO/Al₂O₃ nanocatalysts fabricated by the combustion method. The effect of sonication and urea/nitrate ratio on the characteristics and catalytic properties of the prepared catalysts has been investigated. The synthesized catalysts were characterized by x-ray diffraction (XRD), field emission scanning electron microscope (FESEM), Particle Size Distribution (PSD), energy dispersive x-ray (EDX), Brunauer-Emmett-Teller (BET) and FTIR analyses XRD patterns showed positive influence of urea/nitrate ratio on CuO and ZnO crystallite sizes. The ultrasonic mixing of primary gel compared with conventional mixing led to lower crystallite size. FESEM images showed that the sample mixed by sonication with a urea/nitrate ratio of 1 had more homogeneous morphology with narrow particle size distribution. EDX results proved the presence of all metals on the surface of the nanocatalysts and better consistence between the gel and surface composition of elements in samples prepared by sonication. Catalytic performance showed that sonication during the mixing of primary gel dramatically increased the methanol conversion. It was also proved that increasing the amount of urea led to lower catalytic activity. The ultrasound-treated nanocatalyst with urea/nitrate?=?1 was the best sample in terms of activity and selectivity. It was stable in the SRM for 1200?min without considerable change in methanol conversion and product selectivity.     

MRI and PET image fusion using structure tensor and dual ripplet-II transform

Multimedia Tools and Applications - Medical image fusion aims at preserving salient image features, reducing the redundancy, and increasing the interpretation quality of images in clinical...     

A fast algorithm for feature extraction of hyperspectral images using the first order statistics

Multimedia Tools and Applications - A new supervised feature extraction method appropriate for small sample size situations is proposed in this work. The proposed method is based on the first-order...     

A novel trust-based access control for social networks using fuzzy systems

World Wide Web - Social networks are constantly expanding and attracting more and more users. The users of these networks share plenty of information with their friends, many of which are...     

The application of internet of things in healthcare: a systematic literature review and classification

Universal Access in the Information Society - The Internet of Things (IoT) is an ecosystem that integrates physical objects, software and hardware to interact with each other. Aging of population,...