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.     

A new optimization method based on cellular automata for VVER-1000 nuclear reactor loading pattern

This paper presents a new and innovative optimization technique, which uses cellular automata for solving multi-objective optimization problems. Due to its ability in simulating the local information while taking neighboring effects into account, the cellular automata technique is a powerful tool for optimization. The fuel-loading pattern in nuclear reactor cores is a major optimization problem. Due to the immensity of the search space in fuel management optimization problems, finding the optimum solution requires a huge amount of calculations in the classical method. The cellular automata models, based on local information, can reduce the computations significantly. In this study, reducing the power peaking factor, while increasing the initial excess reactivity inside the reactor core of VVER-1000, which are two apparently contradictory objectives, are considered as the objective functions. The result is an optimum configuration, which is in agreement with the pattern proposed by the designer. In order to gain confidence in the reliability of this method, the aforementioned problem was also solved using neural network and simulated annealing, and the results and procedures were compared.     

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.

     

The Impact of Sub-Millisecond Damage Fixation Kinetics on the In Vitro Sparing Effect at Ultra-High Dose Rate in UNIVERSE

The impact of the exact temporal pulse structure on the potential cell and tissue sparing of ultra-high dose-rate irradiation applied in FLASH studies has gained increasing attention. A previous version of our biophysical mechanistic model (UNIVERSE: UNIfied and VERSatile bio response Engine), based on the oxygen depletion hypothesis, has been extended in this work by considering oxygen-dependent damage fixation dynamics on the sub-milliseconds scale and introducing an explicit implementation of the temporal pulse structure. The model successfully reproduces in vitro experimental data on the fast kinetics of the oxygen effect in irradiated mammalian cells. The implemented changes result in a reduction in the assumed amount of oxygen depletion. Furthermore, its increase towards conventional dose-rates is parameterized based on experimental data from the literature. A recalculation of previous benchmarks shows that the model retains its predictive power, while the assumed amount of depleted oxygen approaches measured values. The updated UNIVERSE could be used to investigate the impact of different combinations of pulse structure parameters (e.g., dose per pulse, pulse frequency, number of pulses, etc.), thereby aiding the optimization of potential clinical application and the development of suitable accelerators.     

Thermodynamic analysis of a tri-generation system based on micro-gas turbine with a steam ejector refrigeration system

In the present work, performance of new configuration of Micro-gas turbine cogeneration and tri-generation systems, with a steam ejector refrigeration system and Heat recovery Steam Generator (HRSG) are studied. A micro-gas turbine cycle produces 200 KW power and exhaust gases of this micro-gas turbine are recovered in an HRSG. The main part of saturated steam in HRSG is used through a steam ejector refrigeration system to produce cooling in summer. In winter, this part of saturated steam is used to produce heating. In the first part of this paper, performance evaluation of this system with respect to Energy Utilization Factor (EUF), Fuel Energy Saving Ratio (FESR), thermal efficiency, pinch point temperature difference, net power to evaporator cooling load and power to heat ratio is carried out. It has been shown that by using the present cogeneration system, one can save fuel consumption from about 23% in summer up to 33% in winter in comparison with separate generation of heating, cooling and electricity.     

Numerical simulation of steady natural convection heat transfer in a 3-dimensional single-ended tube subjected to a nanofluid

In this paper, 3-dimensional numerical simulation of steady natural convective flow and heat transfer are studied in a single-ended tube with non-uniform heat input. Apart from some other applications, it serves as a simplified model of the single-ended evacuated solar tube of a water-in-glass evacuated tube solar water heater. It is assumed that the sealed end of tube to be adiabatic and also the tube opening to be subjected to copper–water nanofluid. Governing equations are derived based on the conceptual model in the cylindrical coordinate system. The governing equations have been then approximated by means of a fully implicit finite volume control method (FVM), using SIMPLE algorithm on the collocated arrangement. The study has been carried out for solid volume fraction 0 ≤ φ ≤ 0.05 and maximum heat flux 100 ≤ q_m ≤ 700. Considering that the driven flow in the tube is influenced by the dimensions and the inclination angle of the solar tube, the flow patterns and temperature distributions are presented on different cross sectional planes and longitudinal sections, when the tube is positioned at different orientations.     

Seismic soil–structure interaction analysis of wind turbines in frequency domain

In this paper, the seismic behavior of wind turbines sitting on a finite flexible soil layer is investigated in three‐dimensional space. A numerical algorithm formulated in frequency domain is proposed in order to simulate the dynamic soil–structure interaction (SSI). The wind turbine is discretized using finite element method (FEM) while, the underlying soil is represented by complex dynamic stiffness functions based on cone models. A parametric study consisting of 24 ground motions and three soil profiles is carried out, and different response quantities of the wind tower model are calculated and presented in the paper. The free‐field ground motions are estimated based on an equivalent linear approach using SHAKE2000 computer software. Transfer functions for total acceleration of the wind tower are obtained under the considered soil profiles and the modal frequencies of the coupled wind turbine–soil foundation are estimated. It is shown that the response quantities such as displacement, rotation, acceleration, base shear and moment are significantly affected by SSI, although the effect of SSI on the fundamental frequencies of the wind tower is insignificant. The moment and shear force distribution along the height of the tower is highly influenced as the soil stiffness decreases. The change in seismic demand distribution along the tower height because of SSI is not addressed by simplified design approached and should be carefully considered in seismic design of wind towers. Copyright © 2016 John Wiley & Sons, Ltd.     

Nonlinear soil‐pile interaction for offshore wind turbines

The current work presents a parametric study, which involves different generalized nonlinear mechanical formulations with different damping characteristics to account for the interaction between a monopile‐supported offshore wind turbine and the surrounding soil. The novelty of the study lies in the fact that recently developed nonlinear mechanical models used so far for the simulation of high‐damping rubber isolators are introduced to describe the nonlinear hysteretic soil behavior. More specifically, the first generalized mechanical model consists of a combination of elastoplastic and trilinear elastic elements (labeled as model 3), while the second model consists of trilinear hysteretic models connected in parallel with trilinear elastic springs and hysteretic dampers used to ensure that the unloading stiffness will be as close as possible to the initial stiffness of the system (labeled as model 4). These newly developed models are compared with well‐known models within the industry, namely, a model that comprises elastoplastic elements (labeled as model 1) and a model that comprises trilinear elastic springs (labeled as model 2). All these models provide exactly the same effective stiffness, but on the other hand different levels of damping are involved in each one of them. The goal of the present work is 3‐fold, introducing novel mechanical models for the simulation of soil behavior, to investigate the effect of different soil damping levels in the response of offshore wind turbines and to highlight the limitations of the commonly used models within the industry. To this end, the differences between the response due to different levels of damping characteristics and modeling approaches are shown, highlighting the importance of soil damping in the overall response of the system.     

Numerical modeling of the hydraulic blade pitch actuator in a spar‐type floating wind turbine considering fault conditions and their effects on global dynamic responses

This paper deals with numerical modeling of the hydraulic blade pitch actuator and its effect on the dynamic responses of a floating spar‐type wind turbine under valve fault conditions. A spar‐type floating wind turbine concept is modeled and simulated using an aero‐hydro‐servo‐elastic simulation tool (Simo‐Riflex [SR]). Because the blade pitch system has the highest failure rate, a numerical model of the hydraulic blade pitch actuator with/without valve faults is developed and linked to SR to study the effects of faults on global responses of the spar‐type floating wind turbine for different faults, fault magnitudes, and environmental conditions. The consequence of valve faults in the pitch actuator is that the blade cannot be pitched to the desired angle, so there may be a delay in the response due to excessive friction and the wrong voltage, or slit lock may cause runaway blade pitch. A short circuit may cause the blade to get stuck at a particular pitch angle. These faults contribute to rotor imbalance, which result in different effects on the turbine structure and the platform motions. The proposed method for combining global and hydraulic actuator models is demonstrated in case studies with stochastic wind and wave conditions and different types of valve faults.     

A comparative study of landslide susceptibility maps produced using support vector machine with different kernel functions and entropy data mining models in China

Bulletin of Engineering Geology and the Environment - The main objective of the current study is to apply a random forest (RF) data-driven model and prioritization of landslide conditioning factors...