Buried Target Imaging: A Comparative Study

A wide variety of qualitative methods have been proposed for microwave imaging. It is difficult to select only one of these methods based on a priori information and measurement equipment to achieve a reliable reconstruction. Various arrangements for antennas to be used in, for instance, have been proposed which have direct impacts on the complexity of inverse methods as well as the quality of output images. In this study, four qualitative methods of the linear sampling method (LSM), time reversal (TR), diffraction tomography (DT), and back-projection (BP) have been reviewed in a 2D scenario; the performance of the methods is compared within the same framework of a multi-static configuration. The goal is to compare their resolutions and determine their advantages and drawbacks. It is shown that LSM provides the best azimuth resolution but the worst range resolution. It is almost invariant to dielectric contrast and is appropriate for a wide range of dielectric contrasts and relatively large objects. It is also shown that at relatively low dielectric contrasts, TR images are most similar to the true object, show fewer artifacts, and offer high immunity to noise. While suffering from more artifacts due to the presence of some ghost images, DT offers the best range resolution. The results also show that BP has the worst azimuth resolution when reconstructing deeply-buried targets, although its implementation is straightforward and not computationally complex.     

Characterization and microstructure study of low‐density polyethylene by Fourier transform infrared spectroscopy and temperature rising elution fractionation

Infrared spectroscopy is a powerful technique for studying the microstructure and determining the short‐chain branch distribution of polyethylene. In this work, the types and amounts of short‐chain branches in low‐density polyethylene were investigated with Fourier transform infrared spectroscopy, and a new and simple method for the determination of butyl short branches was discovered. The amount of each unsaturated species in low‐density polyethylene was also determined with Fourier transform infrared after the bromination of samples. Furthermore, the resin was fractionated by preparative temperature rising elution fractionation, and the branch distribution and melting endotherm of each fraction were analyzed with attenuated total reflectance/Fourier transform infrared and differential scanning calorimetry. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

A potential trackable bone filler: Preparation and characterization

This study reported the synthesis of fluorescent hydroxyapatite/alginate/carbon quantum dots (HA/Alg/CQDs) nanocomposites via the co-precipitation technique. The N-doped CQDs as a new class of fluorescent materials were prepared by the citric acid pyrolysis method, with an average size around 4 nm. Physical, chemical, and optical properties of the synthesized nanocomposites were investigated by X-ray diffraction (XRD), Fourier-transformed infrared spectroscopy (FTIR), atomic force microscopy (AFM), field-emission scanning electron microscopy (FESEM), UV–visible spectroscopy, and photoluminescence (PL) spectroscopy, respectively. The PL spectroscopy data verified the favorable in vitro luminescent emission of the HA/Alg/CQDs nanocomposites in comparison with HA/Alg and HA samples. The XRD patterns of the prepared samples confirmed the formation of crystalline HA in all composites, possessing a Ca/P ratio around 1.5 as obtained by EDX elemental analysis. The FESEM analysis exhibited HA nanoplates that homogeneously distributed throughout the alginate matrix. Therefore, the synthesized nanocomposites could be regarded as potential trackable drug carriers for hard tissue engineering applications.     

Protein Kinase C as a Therapeutic Target in Non-Small Cell Lung Cancer

Driver-directed therapeutics have revolutionized cancer treatment, presenting similar or better efficacy compared to traditional chemotherapy and substantially improving quality of life. Despite significant advances, targeted therapy is greatly limited by resistance acquisition, which emerges in nearly all patients receiving treatment. As a result, identifying the molecular modulators of resistance is of great interest. Recent work has implicated protein kinase C (PKC) isozymes as mediators of drug resistance in non-small cell lung cancer (NSCLC). Importantly, previous findings on PKC have implicated this family of enzymes in both tumor-promotive and tumor-suppressive biology in various tissues. Here, we review the biological role of PKC isozymes in NSCLC through extensive analysis of cell-line-based studies to better understand the rationale for PKC inhibition. PKC isoforms α, ε, η, ι, ζ upregulation has been reported in lung cancer, and overexpression correlates with worse prognosis in NSCLC patients. Most importantly, PKC isozymes have been established as mediators of resistance to tyrosine kinase inhibitors in NSCLC. Unfortunately, however, PKC-directed therapeutics have yielded unsatisfactory results, likely due to a lack of specific evaluation for PKC. To achieve satisfactory results in clinical trials, predictive biomarkers of PKC activity must be established and screened for prior to patient enrollment. Furthermore, tandem inhibition of PKC and molecular drivers may be a potential therapeutic strategy to prevent the emergence of resistance in NSCLC.     

Large Scale Reservoirs System Operation Optimization: the Interior Search Algorithm (ISA) Approach

Reservoirs are built to provide a powerful tool to control and manage surface water resources in order to cover inconsistency between water resources and demands. Due to finite available water and the increasing demands for water especially in arid and semi-arid regions like Iran, reservoirs must be optimally operated in order to use water in the most efficient way. This study applies the Interior Search Algorithm (ISA) to solve large scale reservoirs system operation optimization problems. The ISA is a meta-heuristic algorithm inspired from a systematic methodology of architecture process and mirror work utilized by Persian designers for decoration. Unlike other meta-heuristic algorithms, the ISA just have one parameter to tune which is a great advantage. In this study the parameter of the ISA tuned automatically using a linear equation. A real-world one-reservoir operation problem (i.e. Karun-4) and two large scale benchmark problems (i.e. four-reservoir and ten-reservoir operation problem) were employed to show the effectiveness of the ISA. The results shows the high ability of the ISA to solve reservoirs system operation problems as it achieved solutions 99.97, 99.99 and 99.95 % of global optimum for Karun-4 reservoir, four-reservoir and ten-reservoir system operation problems, respectively. These results are the best results reported so far in the studied problems. Comparing results of the ISA with those of non-linear programming (NLP), linear programming (LP), genetic algorithm (GA) and other meta-heuristic algorithms indicates fast convergence to global optimum. Considering the results, it can be stated that the ISA is a powerful tool to optimize complex large scale reservoir system operation problems.     

Optimal Inter-Basin Water Allocation Using Crisp and Fuzzy Shapley Games

In recent years, uneven distribution of available water resources as well as increasing water demands and overexploiting the water resources have brought severe need for transferring water from basins having sufficient water to basins facing water shortages. Therefore, optimal allocation of shared water resources in water transfer projects, considering the utilities of different stakeholders, physical limitations of the system and socioeconomic criteria is an important task. In this paper, a new methodology based on crisp and fuzzy Shapley games is developed for optimal allocation of inter-basin water resources. In the proposed methodology, initial water allocations are obtained using an optimization model considering an equity criterion. In the second step, the stakeholders form crisp coalitions to increase the total net benefit of the system as well as their own benefits and a crisp Shapley Value game is used to reallocate the benefits produced in the crisp coalitions. Lastly, to provide maximum total net benefit, fuzzy coalitions are constituted and the participation rates of water users to fuzzy coalitions are optimized. Then, the total net benefit is reallocated to water users in a rational and equitable way using Fuzzy Shapley Value game. The effectiveness of this method is examined by applying it to a large scale case study of water transfer from the Karoon river basin in southern Iran to the Rafsanjan plain in central Iran.     

Optimizing the Runoff Estimation with HEC-HMS Model Using Spatial Evapotranspiration by the SEBS Model

Most of the commonly used hydrological models do not account for the actual evapotranspiration (ETa) as a key contributor to water loss in semi-arid/arid regions. In this study, the HEC-HMS (Hydrologic Engineering Center Hydrologic Modeling System) model was calibrated, modified, and its performance in simulating runoff resulting from short-duration rainfall events was evaluated. The model modifications included integrating spatially distributed ETa, calculated using the surface energy balance system (SEBS), into the model. Evaluating the model’s performance in simulating runoff showed that the default HEC-HMS model underestimated the runoff with root mean squared error (RMSE) of 0.14 m³/s (R²?=?0.92) while incorporating SEBS ETa into the model reduced RMSE to 0.01 m³/s (R²?=?0.99). The integration of HECHMS and SEBS resulted in smaller and more realistic latent heat flux estimates translated into a lower water loss rate and a higher magnitude of runoff simulated by the HECHMS model. The difference between runoff simulations using the default and modified model translated into an average of 95,000 m³ runoff per rainfall event (equal to seasonal water requirement of ten-hectare winter wheat) that could be planned and triggered for agricultural purposes, flood harvesting, and groundwater recharge in the region. The effect of ETa on the simulated runoff volume is expected to be more pronounced during high evaporative demand periods, longer rainfall events, and larger catchments. The outcome of this study signifies the importance of implementing accurate estimates of evapotranspiration into a hydrological model.

     

Performance Assessment of a Coupled Particle Swarm Optimization and Network Flow Programming Model for Optimum Water Allocation

Water resources allocation problems are mainly categorized in two classes of simulation and optimization. In most cases, optimization problems due to the number of variables, constraints and nonlinear feasible search space are known as a challenging subject in the literature. In this research, by coupling particle swarm optimization (PSO) algorithm and a network flow programming (NFP) based river basin simulation model, a PSO-NFP hybrid structure is constructed for optimum water allocation planning. In the PSO-NFP model, the NFP core roles as the fast inner simulation engine for finding optimum values for a large number of water discharges in the network links (rivers and canals) and nodes (reservoirs and demands) while the heuristic PSO algorithm forms the outer optimization cover to search for the optimum values of reservoirs capacities and their storage priorities. In order to assess the performance of the PSO-NFP model, three hypothetical test problems are defined, and their equivalent nonlinear mathematical programs are developed in LINGO and the results are compared. Finally, the PSO-NFP model is applied in solving a real river basin water allocation problem. Results indicate that the applied method of coupling PSO and NFP has an efficient ability for handling river basin-scale water resources optimization problems.     

A Multi-Model Nonstationary Rainfall-Runoff Modeling Framework: Analysis and Toolbox

Water Resources Management - We present a framework and toolbox for multi-model (one at a time) nonstationary modeling of rainfall-runoff (RR) transformation. The designed time-varying nature of...     

Environmental damage costs in Iran by the energy sector

On the basis of the energy supply and demand, this paper assesses the environmental damage from air pollution in Iran using the Extern-E study that has extended over 10 years and is still in progress in the European Union (EU) commission. Damage costs were transferred from Western European practice to the conditions of Iran by scaling according to GDP per capital measured in PPP terms.