Investigation Anthropogenic Impacts and Climate Factors on Drying up of Urmia Lake using Water Budget and Drought Analysis

The water level of Urmia Lake, the largest inland lake in Iran with maximum water surface area of about 6000 km², has been shrinking for the last two decades. Although a number of study have been performed to determine drought condition and coastline changes of Urmia Lake, there has not been a detailed study to distinguish anthropogenic effects from climate impacts on the drying of Urmia Lake. In this study, water budget of Urmia Lake and the intensity of drought in the basin were analyzed in the period from 1985 to 2010 and a new hypothesis is proposed to quantify anthropogenic and climate impacts in reducing the volume of Urmia Lake. The results of this study indicate that human impacts on the Lake and its basin are more important than climate factors. Though previous studies assumed that ground water output from Urmia Lake is negligible, the results of this study show the presence of significant groundwater seepage from Urmia Lake. Major changes in the variables that reduced the water level of Urmia Lake were observed since 1998. Anthropogenic impacts and climate factors have roughly 80% and 20% effects on the drying up of Urmia Lake, respectively. Hence, the first step to recover Urmia Lake could be the revision of management surface water, operation of dams and groundwater resources. The second step could be the review and classification of agricultural products grown in the region in terms of water consumption and teach local people the best practice methods for irrigation.     

Uncertainty in a nested relational database model

Some database models have already been developed to deal with complex values but they have constrains that data stored is precise and queries are crisp. However, as many researchers have pointed out, there is a need to present, manipulate, and query complex and uncertain data of various non-traditional database applications such as oceanography, multimedia, meteorology, office automation systems, engineering designs, expert database systems and geographic information systems. In this paper, we present a logical database model, which is an extension of a nested relational data model (also known as an NF² data model), for representing and manipulating complex and uncertain data in databases. We also introduce a possible physical representation of such complex and uncertain values in databases and describe the query processing of the model that we discuss here.     

Platinum Nanoparticles Supported on Ionic Liquid‐Modified Magnetic Nanoparticles: Selective Hydrogenation Catalysts

A method for supporting platinum nanoparticles on magnetite nanoparticles is described. The method requires modification of the surface of the magnetic nanoparticles with ionic liquid groups. Before modification, the magnetic nanoparticles are not stable and easily aggregate and, after modification, the magnetite nanoparticles become highly stable and soluble in polar or non‐polar organic solvents depending on the alkyl group of the linked ionic liquids. The supporting of platinum nanoparticles on the modified magnetic nanoparticles was achieved by adsorbing platinum salts (K₂PtCl₄) on the surface of the magnetite nanoparticles via ion exchange with the linked ionic liquid groups and then reducing them by hydrazine. The supported platinum nanoparticles were applied in the catalytic hydrogenation of alkynes in which cis‐alkenes were selectively produced, and in the hydrogenation of α,β‐unsaturated aldehydes where the allyl alcohols were obtained as the exclusive products. The new catalyst can be easily separated from the reaction mixtures by applying an external magnetic field and recycled.     

Properties of Electrodeposited CoFeNi/Cu Superlattices: The Effect of CoFeNi and Cu Layers Thicknesses

CoFeNi/Cu superlattices were grown on Ti substrate by electrodeposition as a function of the ferromagnetic and non-magnetic layer thicknesses. In order to examine the effect of the Cu layer thickness on the film properties, the Cu layer thickness was changed from 0.5 to 6 nm, while the CoFeNi layer thickness was kept constant at 4 nm. Also, for the CoFeNi layer effect, the CoFeNi layer thickness was changed from 2 to 15 nm, while the Cu layer thickness was fixed at 4 nm. The structural analysis studied by X-ray diffraction indicated that the superlattices have face-centered-cubic structure. Magnetic characteristics were investigated by vibrating sample magnetometer. From the hysteresis curves, the coercivity and the saturation magnetization were determined. It was found that the easy-axis of the films is parallel to the film plane. Magnetoresistance measurements were made by the Van der Pauw method at the room temperature with magnetic fields up to ±12 kOe. All superlattices exhibited giant magnetoresistance (GMR). As the ferromagnetic layer thickness increased up to 4 nm, the GMR value increases up to 22 % and then decreases. The superlattices saturated at the lower magnetic layers with increasing ferromagnetic layer thickness. The maximum GMR value was obtained to be 22 % for a superlattice with 375[CoFeNi(4 nm)/Cu(4 nm)].     

Numerical analysis of choked converging nozzle flows with surface roughness and heat flux conditions

Choked converging nozzle flow and heat transfer characteristics are numerically investigated by means of a recent computational model that integrates the axisymmetric continuity, state, momentum and energy equations. To predict the combined effects of nozzle geometry, friction and heat transfer rates, analyses are conducted with sufficiently wide ranges of covergence half angle, surface roughness and heat flux conditions. Numerical findings show that inlet Mach and Nusselt numbers decrease up to 23.1% and 15.8% with surface heat flux and by 15.13% and 4.8% due to surface roughness. Considering each convergence half angle case individually results in a linear relation between nozzle discharge coefficients and exit Reynolds numbers with similar slopes. Heat flux implementation, by decreasing the shear stress values, lowers the risks due to wear hazards at upstream sections of flow walls; however the final 10% downstream nozzle portion is determined to be quite critical, where shear stress attains the highest magnitudes. Heat transfer rates are seen to increase in the streamwise direction up to 2.7 times; however high convergence half angles, heat flux and surface roughness conditions lower inlet Nusselt numbers by 70%, 15.8% and 4.8% respectively.     

ROC analysis of ultrasound tissue characterization classifiers for breast cancer diagnosis

Breast cancer diagnosis through ultrasound tissue characterization was studied using receiver operating characteristic (ROC) analysis of combinations of acoustic features, patient age, and radiological findings. A feature fusion method was devised that operates even if only partial diagnostic data are available. The ROC methodology uses ordinal dominance theory and bootstrap resampling to evaluate A(z) and confidence intervals in simple as well as paired data analyses. The combined diagnostic feature had an A(z) of 0.96 with a confidence interval of at a significance level of 0.05. The combined features show statistically significant improvement over prebiopsy radiological findings. These results indicate that ultrasound tissue characterization, in combination with patient record and clinical findings, may greatly reduce the need to perform biopsies of benign breast lesions.     

LLVMVF: A Generic Approach for Verification of Multicore Software

Proliferation of multicore hardware boosted the need for verification of multicore software that is running on these hardware. Multicore software demands new verification techniques different from the ones used for sequential software. Many optimized compiler frameworks are arising to address the complexities of multicore software. Among these compilers, Low Level Virtual Machine (LLVM) is especially gaining popularity because i) has a universal front-end that allows to read in many different input languages, ii) aggressive optimizations to improve code performance and quality, and iii) a well-defined intermediate bytecode representation, called LLVM IR, that allows a unified intermediate representation. In this work, we present a novel framework, called LLVM Verification Framework (LLVMVF), implemented in a purely functional language for verification of multicore software. To our knowledge, this is the first verification framework using the LLVM bytecode representation for multicore software. We present an SMT-based Bounded Model Checker backend of LLVMVF and perform initial experiments on multicore software using Pthreads library. Furthermore, we compare our results with an existing multicore software verification tool.     

Electrodeposited Co–Ni Films: Electrolyte pH—Property Relationships

The effect of electrolyte pH on structural, magnetic, and magnetoresistive properties of Co–Ni films was studied. The films were deposited on a titanium substrate from the electrolytes with 4.10±0.05, 3.14±0.05, and 2.14±0.05 pH values. The Co–Ni system exhibited anomalous codeposition. Structural analysis indicated that the films had (220) preferential oriented face-centered cubic structure and their surface became smoother as the electrolyte pH decreased. The compositional and magnetic analysis revealed that an increase of the Co content in the films resulted in an increase in saturation magnetization and coercivity. Magnetoresistance curves indicated that the films show anisotropic magnetoresistance. Longitudinal and transversal magnetoresistances were found to be the highest values of 8 % and 7 %, respectively, for the film deposited at a low electrolyte pH. The variation of the Co:Ni ratio in deposits caused by the change of the electrolyte pH has a considerable effect on the properties of the films.