Showing papers by "Islamic Azad University published in 2015"

Heavy Metal Stress and Some Mechanisms of Plant Defense Response

Abstract: Unprecedented bioaccumulation and biomagnification of heavy metals (HMs) in the environment have become a dilemma for all living organisms including plants. HMs at toxic levels have the capability to interact with several vital cellular biomolecules such as nuclear proteins and DNA, leading to excessive augmentation of reactive oxygen species (ROS). This would inflict serious morphological, metabolic, and physiological anomalies in plants ranging from chlorosis of shoot to lipid peroxidation and protein degradation. In response, plants are equipped with a repertoire of mechanisms to counteract heavy metal (HM) toxicity. The key elements of these are chelating metals by forming phytochelatins (PCs) or metallothioneins (MTs) metal complex at the intra- and intercellular level, which is followed by the removal of HM ions from sensitive sites or vacuolar sequestration of ligand-metal complex. Nonenzymatically synthesized compounds such as proline (Pro) are able to strengthen metal-detoxification capacity of intracellular antioxidant enzymes. Another important additive component of plant defense system is symbiotic association with arbuscular mycorrhizal (AM) fungi. AM can effectively immobilize HMs and reduce their uptake by host plants via binding metal ions to hyphal cell wall and excreting several extracellular biomolecules. Additionally, AM fungi can enhance activities of antioxidant defense machinery of plants.

Observation of the rare B-s(0)->mu(+)mu(-) decay from the combined analysis of CMS and LHCb data

Abstract: The standard model of particle physics describes the fundamental particles and their interactions via the strong, electromagnetic and weak forces. It provides precise predictions for measurable quantities that can be tested experimentally. The probabilities, or branching fractions, of the strange B meson (B-s(0)) and the B-0 meson decaying into two oppositely charged muons (mu(+) and mu(-)) are especially interesting because of their sensitivity to theories that extend the standard model. The standard model predicts that the B-s(0)->mu(+)mu(-) and B-0 ->mu(+)mu(-) decays are very rare, with about four of the former occurring for every billion B-s(0) mesons produced, and one of the latter occurring for every ten billion B-0 mesons(1). A difference in the observed branching fractions with respect to the predictions of the standard model would provide a direction in which the standard model should be extended. Before the Large Hadron Collider (LHC) at CERN2 started operating, no evidence for either decay mode had been found. Upper limits on the branching fractions were an order of magnitude above the standard model predictions. The CMS (Compact Muon Solenoid) and LHCb(Large Hadron Collider beauty) collaborations have performed a joint analysis of the data from proton-proton collisions that they collected in 2011 at a centre-of-mass energy of seven teraelectronvolts and in 2012 at eight teraelectronvolts. Here we report the first observation of the B-s(0)->mu(+)mu(-) decay, with a statistical significance exceeding six standard deviations, and the best measurement so far of its branching fraction. Furthermore, we obtained evidence for the B-0 ->mu(+)mu(-) decay with a statistical significance of three standard deviations. Both measurements are statistically compatible with standard model predictions and allow stringent constraints to be placed on theories beyond the standard model. The LHC experiments will resume taking data in 2015, recording proton-proton collisions at a centre-of-mass energy of 13 teraelectronvolts, which will approximately double the production rates of B-s(0) and B-0 mesons and lead to further improvements in the precision of these crucial tests of the standard model.

Monolayer and multilayer adsorption isotherm models for sorption from aqueous media

Abstract: Industrial wastewater polluted with various contaminants, including heavy metals, dyes, etc., endangers human health and the environment. Various separation techniques have been developed for the removal of pollutants from aqueous solutions. Adsorption process has drawn considerable attention due to its simplicity of design, high removal efficiency, even at dilute concentration, and economical aspect. We reviewed the most common two, three, four, and five parameter adsorption isotherm models corresponding to monolayer and multilayer adsorption on the basis of parameters that can be used for exploring novel adsorbents. Thermodynamic assumptions of the models give information about the surface properties, capacity of the adsorbent and adsorption mechanism. Seven error functions were investigated to evaluate the fitness quality of isotherm models with the experimental equilibrium data.

Theoretical Study on the Al-Doped ZnO Nanoclusters for CO Chemical Sensors

Abstract: Experimental work has already demonstrated that Al-doped ZnO nanostructures exhibit a higher response than the pure ZnO sample to CO gas and can detect it at sub-ppm concentrations. In this work, using density functional theory calculations (at B3LYP, M06-L, and B97D levels), we studied the effect of Al-doping on the sensing properties of a ZnO nanocluster. We investigated several doping and adsorption possibilities. This study explains the electrical behavior that has been obtained from the ZnO nanostructures upon the CO adsorption. There is a relationship between the HOMO–LUMO energy gap (Eg) and the resistivity of the ZnO nanostructure. If a Zn atom of the ZnO nanocluster is replaced by an Al atom, a CO molecule can be adsorbed from its C-head on the doped site with ΔG of −5.0 kcal/mol at room temperature. In contrast to the pristine cluster, Al-doped ZnO cluster can detect CO molecules due to a significant decrease in the Eg and thereby in the resistivity. We also found that the Eg decreases by increa...

Alcohol-Related Risk of Suicidal Ideation, Suicide Attempt, and Completed Suicide: A Meta-Analysis

Abstract: BACKGROUND: Several original studies have investigated the effect of alcohol use disorder (AUD) on suicidal thought and behavior, but there are serious discrepancies across the studies. Thus, a systematic assessment of the association between AUD and suicide is required. METHODS: We searched PubMed, Web of Science, and Scopus until February 2015. We also searched the Psycinfo web site and journals and contacted authors. We included observational (cohort, case-control, and cross-sectional) studies addressing the association between AUD and suicide. The exposure of interest was AUD. The primary outcomes were suicidal ideation, suicide attempt, and completed suicide. We assessed heterogeneity using Q-test and I2 statistic. We explored publication bias using the Egger's and Begg's tests and funnel plot. We meta-analyzed the data with the random-effects models. For each outcome we calculated the overall odds ratio (OR) or risk ratio (RR) with 95% confidence intervals (CI). RESULTS: We included 31 out of 8548 retrieved studies, with 420,732 participants. There was a significant association between AUD and suicidal ideation (OR=1.86; 95% CI: 1.38, 2.35), suicide attempt (OR=3.13; 95% CI: 2.45, 3.81); and completed suicide (OR=2.59; 95% CI: 1.95, 3.23 and RR=1.74; 95% CI: 1.26, 2.21). There was a significant heterogeneity among the studies, but little concern to the presence of publication bias. CONCLUSIONS: There is sufficient evidence that AUD significantly increases the risk of suicidal ideation, suicide attempt, and completed suicide. Therefore, AUD can be considered an important predictor of suicide and a great source of premature death. Language: en

Benign and malignant breast tumors classification based on region growing and CNN segmentation

Abstract: CNN templates are generated using a genetic algorithm to segment mammograms.An adaptive threshold is computed in region growing process by using ANN and intensity features.In tumor classification, CNN produces better results than region growing.MLP produces the highest classification accuracy among other classifiers.Results on DDSM images are more appropriate than those of MIAS. Breast cancer is regarded as one of the most frequent mortality causes among women. As early detection of breast cancer increases the survival chance, creation of a system to diagnose suspicious masses in mammograms is important. In this paper, two automated methods are presented to diagnose mass types of benign and malignant in mammograms. In the first proposed method, segmentation is done using an automated region growing whose threshold is obtained by a trained artificial neural network (ANN). In the second proposed method, segmentation is performed by a cellular neural network (CNN) whose parameters are determined by a genetic algorithm (GA). Intensity, textural, and shape features are extracted from segmented tumors. GA is used to select appropriate features from the set of extracted features. In the next stage, ANNs are used to classify the mammograms as benign or malignant. To evaluate the performance of the proposed methods different classifiers (such as random forest, naive Bayes, SVM, and KNN) are used. Results of the proposed techniques performed on MIAS and DDSM databases are promising. The obtained sensitivity, specificity, and accuracy rates are 96.87%, 95.94%, and 96.47%, respectively.

Nanoparticles Biosynthesized by Fungi and Yeast: A Review of Their Preparation, Properties, and Medical Applications.

Abstract: In the field of nanotechnology, the use of various biological units instead of toxic chemicals for the reduction and stabilization of nanoparticles, has received extensive attention. Among the many possible bio resources, biologically active products from fungi and yeast represent excellent scaffolds for this purpose. Since fungi and yeast are very effective secretors of extracellular enzymes and number of species grow fast and therefore culturing and keeping them in the laboratory are very simple. They are able to produce metal nanoparticles and nanostructure via reducing enzyme intracellularly or extracellularly. The focus of this review is the application of fungi and yeast in the green synthesis of inorganic nanoparticles. Meanwhile the domain of biosynthesized nanoparticles is somewhat novel; the innovative uses in nano medicine in different areas including the delivery of drug, cancer therapy, antibacterial, biosensors, and MRI and medical imaging are reviewed. The proposed signaling pathways of nanoparticles induced apoptosis in cancerous cells and anti-angiogenesis effects also are reviewed. In this article, we provide a short summary of the present study universally on the utilization of eukaryotes like yeast and fungi in the biosynthesis of nanoparticles (NPs) and their uses.

Worldwide evidence of a unimodal relationship between productivity and plant species richness

Abstract: The search for predictions of species diversity across environmental gradients has challenged ecologists for decades The humped-back model (HBM) suggests that plant diversity peaks at intermediate productivity; at low productivity few species can tolerate the environmental stresses, and at high productivity a few highly competitive species dominate Over time the HBM has become increasingly controversial, and recent studies claim to have refuted it Here, by using data from coordinated surveys conducted throughout grasslands worldwide and comprising a wide range of site productivities, we provide evidence in support of the HBM pattern at both global and regional extents The relationships described here provide a foundation for further research into the local, landscape, and historical factors that maintain biodiversity

Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at √s = 8 TeV

Abstract: A description is provided of the performance of the CMS detector for photon reconstruction and identification in proton-proton collisions at a centre-of-mass energy of 8 TeV at the CERN LHC. Details are given on the reconstruction of photons from energy deposits in the electromagnetic calorimeter (ECAL) and the extraction of photon energy estimates. The reconstruction of electron tracks from photons that convert to electrons in the CMS tracker is also described, as is the optimization of the photon energy reconstruction and its accurate modelling in simulation, in the analysis of the Higgs boson decay into two photons. In the barrel section of the ECAL, an energy resolution of about 1% is achieved for unconverted or late-converting photons from H→γγ decays. Different photon identification methods are discussed and their corresponding selection efficiencies in data are compared with those found in simulated events.

Search for a Higgs boson in the mass range from 145 to 1000 GeV decaying to a pair of W or Z bosons

Abstract: A search for a heavy Higgs boson in the H to WW and H to ZZ decay channels is reported. The search is based upon proton-proton collision data samples corresponding to an integrated luminosity of up to 5.1 inverse femtobarns at sqrt(s)=7 TeV and up to 19.7 inverse femtobarns at sqrt(s)=8 TeV, recorded by the CMS experiment at the CERN LHC. Several final states of the H to WW and H to ZZ decays are analyzed. The combined upper limit at the 95% confidence level on the product of the cross section and branching fraction exclude a Higgs boson with standard model-like couplings and decays in the range 145 < m[H] < 1000 GeV. We also interpret the results in the context of an electroweak singlet extension of the standard model.

Green synthesis of palladium nanoparticles using Hippophae rhamnoides Linn leaf extract and their catalytic activity for the Suzuki–Miyaura coupling in water

Abstract: During this study, we report the green synthesis of palladium nanoparticles using Hippophae rhamnoides Linn leaf extract and their application as heterogeneous catalysts for the Suzuki–Miyaura coupling in water. The synthesized nanoparticles are characterized by XRD, SEM, TEM and UV–vis techniques. This method has the advantages of high yields, simple methodology, and elimination of ligand, organic solvent and homogeneous catalysts and easy work-up. Furthermore, the catalyst exhibits high catalytic activity, superior cycling stability and excellent substrate applicability.

Groundwater qanat potential mapping using frequency ratio and Shannon’s entropy models in the Moghan watershed, Iran

Abstract: The purpose of current study is to produce groundwater qanat potential map using frequency ratio (FR) and Shannon's entropy (SE) models in the Moghan watershed, Khorasan Razavi Province, Iran. The qanat is basically a horizontal, interconnected series of underground tunnels that accumulate and deliver groundwater from a mountainous source district, along a water- bearing formation (aquifer), and to a settlement. A qanat locations map was prepared for study area in 2013 based on a topographical map at a 1:50,000-scale and extensive field surveys. 53 qanat locations were detected in the field surveys. 70 % (38 locations) of the qanat locations were used for groundwater potential mapping and 30 % (15 locations) were used for validation. Fourteen effective factors were considered in this investigation such as slope degree, slope aspect, altitude, topographic wetness index (TWI), stream power index (SPI), slope length (LS), plan curvature, profile curvature, distance to rivers, distance to faults, lithology, land use, drainage density, and fault density. Using the above conditioning factors, groundwater qanat potential map was generated implementing FR and SE models, and the results were plotted in ArcGIS. The predictive capability of frequency ratio and Shannon's entropy models were determined by the area under the relative operating characteristic curve. The area under the curve (AUC) for frequency ratio model was calculated as 0.8848. Also AUC for Shannon's entropy model was 0.9121, which depicts the excellence of this model in qanat occurrence potential estimation in the study area. So the Shannon's entropy model has higher AUC than the frequency ratio model. The produced groundwater qanat potential maps can assist planners and engineers in groundwater development plans and land use planning.

Simulation of copper-water nanofluid in a microchannel in slip flow regime using the lattice Boltzmann method

Abstract: Laminar forced convection heat transfer of water–Cu nanofluids in a microchannel was studied utilizing the lattice Boltzmann method (LBM). The entering flow was at a lower temperature compared to the microchannel walls. Simulations were performed for nanoparticle volume fractions of 0.00 to 0.04 and slip coefficient from 0.005 to 0.02. The model predictions were found to be in good agreement with earlier studies. The effects of wall slip velocity and temperature jump of the nanofluid were studied for the first time by using lattice Boltzmann method. Streamlines, isotherms, longitudinal variations of Nusselt number, slip velocity and temperature jump as well as velocity and temperature profiles for different cross sections were presented. The results indicate that LBM can be used to simulate forced convection for the nanofluid micro flows. Moreover, the effect of the temperature jump on the heat transfer rate is significant. Also, the results showed that decreasing the values of slip coefficient enhances the convective heat transfer coefficient and consequently the Nusselt number (Nu) but increases the wall slip velocity and temperature jump values.

Future of agricultural water management in Africa

Abstract: This paper aims to estimate ratio of area equipped for irrigation to cultivated area (AI) in Africa in 2035 and 2060 using studies of agricultural water management from 1962 to 2011. For this purpose, all necessary information was gathered from Food and Agriculture Organization of the United Nations (FAO) and their values were checked using The World Bank Group (WBG). Among all presented data in the FAO database, 10 indices were selected (due to more importance and more availability for all the regions in Africa). The selected indices were analysed for all seven regions in the study area and the amount of AI was estimated by three different scenarios and using other nine indices. The results show that changes of AI are 0.3% to 49.5% and 16.5% to 83.2% from 2011 to 2035 and 2060, respectively. Indian Ocean Islands has a better potential to increase AI in the future. A considerable note is the change of irrigation status in the future than the current status. In 2011, AI of Sudano-Sahelian is more than AI o...

A Generalized Voltage Droop Strategy for Control of Multiterminal DC Grids

Abstract: This paper proposes a generalized voltage droop (GVD) control strategy for dc voltage control and power sharing in voltage source converter (VSC)-based multiterminal dc (MTDC) grids The proposed GVD control is implemented at the primary level of a two-layer hierarchical control structure of the MTDC grid, and constitutes an alternative to the conventional voltage droop characteristics of voltage-regulating VSC stations, providing higher flexibility and, thus, controllability to these networks As a difference with other methods, the proposed GVD control strategy can be operated in three different control modes, including conventional voltage droop control, fixed active power control, and fixed dc voltage control, by adjusting the GVD characteristics of the voltage-regulating converters Such adjustment is carried out in the secondary layer of the hierarchical control structure The proposed strategy improves the control and power-sharing capabilities of the conventional voltage droop, and enhances its maneuverability The simulation results, obtained by employing a CIGRE B4 dc grid test system, demonstrate the efficiency of the proposed approach and its flexibility in active power sharing and power control as well as voltage control In these analysis, it will be also shown how the transitions between the operating modes of the GVD control does not give rise to active power oscillations in the MTDC grids