Showing papers by "University of Tabriz published in 2016"

Temperature-Responsive Smart Nanocarriers for Delivery Of Therapeutic Agents: Applications and Recent Advances

Abstract: Smart drug delivery systems (DDSs) have attracted the attention of many scientists, as carriers that can be stimulated by changes in environmental parameters such as temperature, pH, light, electromagnetic fields, mechanical forces, etc. These smart nanocarriers can release their cargo on demand when their target is reached and the stimulus is applied. Using the techniques of nanotechnology, these nanocarriers can be tailored to be target-specific, and exhibit delayed or controlled release of drugs. Temperature-responsive nanocarriers are one of most important groups of smart nanoparticles (NPs) that have been investigated during the past decades. Temperature can either act as an external stimulus when heat is applied from the outside, or can be internal when pathological lesions have a naturally elevated termperature. A low critical solution temperature (LCST) is a special feature of some polymeric materials, and most of the temperature-responsive nanocarriers have been designed based on this feature. In...

Generalized Structure for a Single Phase Switched-Capacitor Multilevel Inverter Using a New Multiple DC Link Producer With Reduced Number of Switches

Abstract: In this paper, initially a new dc/dc converter is proposed which can produce boosted multiple dc link voltages by using the novel switched-capacitor converter (SCC) and with reduced number of switches. In the proposed SCC, voltage of all capacitors is charged by binary asymmetrical pattern as self-balancing and without using any auxiliary circuits. The proposed SCC will boost the input dc power supply voltage without transformer by switching the capacitors in series and in parallel. Next, a new single phase switched-capacitor multilevel inverter (SCMLI) topology which uses the proposed SCC units as virtual dc links have been proposed. The proposed topologies reduce the number of power switches, diodes, isolated dc power supplies, size, and the cost of the system in comparison with conventional similar topologies. For example, by contribution of proposed SCMLI structure, 49 and 137 output voltage levels are made by only 14 and18 power switches and 3 and 4 isolated dc power supplies, respectively. To confirm the performance of proposed topology, various simulation results by PSCAD/EMTDC software and experimental tests are given.

A New Cascaded Switched-Capacitor Multilevel Inverter Based on Improved Series–Parallel Conversion With Less Number of Components

Abstract: The aim of this paper is to present a new structure for switched-capacitor multilevel inverters (SCMLIs) which can generate a great number of voltage levels with optimum number of components for both symmetric and asymmetric values of dc-voltage sources. The proposed topology consists of a new switched-capacitor dc/dc converter (SCC) that has boost ability and can charge capacitors as self-balancing by using the proposed binary asymmetrical algorithm and series–parallel conversion of power supply. The proposed SCC unit is used in new configuration as a submultilevel inverter (SMLI) and then, these proposed SMLIs are cascaded together and create a new cascaded multilevel inverter (MLI) topology that is able to increase the number of output voltage levels remarkably without using any full H-bridge cell and also can pass the reverse current for inductive loads. In this case, two half-bridge modules besides two additional switches are employed in each of SMLI units instead of using a full H-bridge cell that contribute to reduce the number of involved components in the current path, value of blocked voltage, the variety of isolated dc-voltage sources, and as a result, the overall cost by less number of switches in comparison with other presented topologies. The validity of the proposed SCMLI has been carried out by several simulation and experimental results.

Drought Stress in Plants: Causes, Consequences, and Tolerance

Abstract: Drought (water stress) is one of the most important environmental stresses and occurs for several reasons, including low rainfall, salinity, high and low temperatures, and high intensity of light, among others. Drought stress is a multidimensional stress and causes changes in the physiological, morphological, biochemical, and molecular traits in plants. Many plants have improved their resistance mechanisms to tolerate drought stress, but these mechanisms are varied and depend on the plant species. Typically, mechanisms involved in plant tolerance to drought follow a general plan: maintaining cell homeostasis in water-deficit situations, which is possible by increasing the water inlet to the cells. Drought avoidance is other common drought resistance mechanism in annual plants. With this mechanism, escape from stress conditions is the main strategy for plant growth under drought conditions.

Fungal Planet description sheets: 469-557

Abstract: Novel species of fungi described in this study include those from various countries as follows: Australia: Apiognomonia lasiopetali on Lasiopetalum sp., Blastacervulus eucalyptorum on Eucalyptus adesmophloia, Bullanockia australis (incl. Bullanockia gen. nov.) on Kingia australis, Caliciopsis eucalypti on Eucalyptus marginata, Celerioriella petrophiles on Petrophile teretifolia, Coleophoma xanthosiae on Xanthosia rotundifolia, Coniothyrium hakeae on Hakea sp., Diatrypella banksiae on Banksia formosa, Disculoides corymbiae on Corymbia calophylla, Elsinoe eelemani on Melaleuca alternifolia, Elsinoe eucalyptigena on Eucalyptus kingsmillii, Elsinoe preissianae on Eucalyptus preissiana, Eucasphaeria rustici on Eucalyptus creta, Hyweljonesia queenslandica (incl. Hyweljonesia gen. nov.) on the cocoon of an unidentified microlepidoptera, Mycodiella eucalypti (incl. Mycodiella gen. nov.) on Eucalyptus diversicolor, Myrtapenidiella sporadicae on Eucalyptus sporadica, Neocrinula xanthorrhoeae (incl. Neocrinula gen. nov.) on Xanthorrhoea sp., Ophiocordyceps nooreniae on dead ant, Phaeosphaeriopsis agavacearum on Agave sp., Phlogicylindrium mokarei on Eucalyptus sp., Phyllosticta acaciigena on Acacia suaveolens, Pleurophoma acaciae on Acacia glaucoptera, Pyrenochaeta hakeae on Hakea sp., Readeriella lehmannii on Eucalyptus lehmannii, Saccharata banksiae on Banksia grandis, Saccharata daviesiae on Daviesia pachyphylla, Saccharata eucalyptorum on Eucalyptus bigalerita, Saccharata hakeae on Hakea baxteri, Saccharata hakeicola on Hakea victoria, Saccharata lambertiae on Lambertia ericifolia, Saccharata petrophiles on Petrophile sp., Saccharata petrophilicola on Petrophile fastigiata, Sphaerellopsis hakeae on Hakea sp., and Teichospora kingiae on Kingia australis. Brazil: Adautomilanezia caesalpiniae (incl. Adautomilanezia gen. nov.) on Caesalpina echinata, Arthrophiala arthrospora (incl. Arthrophiala gen. nov.) on Sagittaria montevidensis, Diaporthe caatingaensis (endophyte from Tacinga inamoena), Geastrum ishikawae on sandy soil, Geastrum pusillipilosum on soil, Gymnopus pygmaeus on dead leaves and sticks, Inonotus hymenonitens on decayed angiosperm trunk, Pyricularia urashimae on Urochloa brizantha, and Synnemellisia aurantia on Passiflora edulis. Chile: Tubulicrinis australis on Lophosoria quadripinnata. France: Cercophora squamulosa from submerged wood, and Scedosporium cereisporum from fluids of a wastewater treatment plant. Hawaii: Beltraniella acaciae, Dactylaria acaciae, Rhexodenticula acaciae, Rubikia evansii and Torula acaciae (all on Acacia koa). India: Lepidoderma echinosporum on dead semi-woody stems, and Rhodocybe rubrobrunnea from soil. Iran: Talaromyces kabodanensis from hypersaline soil. La Reunion: Neocordana musarum from leaves of Musa sp. Malaysia: Anungitea eucalyptigena on Eucalyptus grandis × pellita, Camptomeriphila leucaenae (incl. Camptomeriphila gen. nov.) on Leucaena leucocephala, Castanediella communis on Eucalyptus pellita, Eucalyptostroma eucalypti (incl. Eucalyptostroma gen. nov.) on Eucalyptus pellita, Melanconiella syzygii on Syzygium sp., Mycophilomyces periconiae (incl. Mycophilomyces gen. nov.) as hyperparasite on Periconia on leaves of Albizia falcataria, Synnemadiella eucalypti (incl. Synnemadiella gen. nov.) on Eucalyptus pellita, and Teichospora nephelii on Nephelium lappaceum. Mexico: Aspergillus bicephalus from soil. New Zealand: Aplosporella sophorae on Sophora microphylla, Libertasomyces platani on Platanus sp., Neothyronectria sophorae (incl. Neothyronectria gen. nov.) on Sophora microphylla, Parastagonospora phoenicicola on Phoenix canariensis, Phaeoacremonium pseudopanacis on Pseudopanax crassifolius, Phlyctema phoenicis on Phoenix canariensis, and Pseudoascochyta novae-zelandiae on Cordyline australis. Panama: Chalara panamensis from needle litter of Pinus cf. caribaea. South Africa: Exophiala eucalypti on leaves of Eucalyptus sp., Fantasmomyces hyalinus (incl. Fantasmomyces gen. nov.) on Acacia exuvialis, Paracladophialophora carceris (incl. Paracladophialophora gen. nov.) on Aloe sp., and Umthunziomyces hagahagensis (incl. Umthunziomyces gen. nov.) on Mimusops caffra. Spain: Clavaria griseobrunnea on bare ground in Pteridium aquilinum field, Cyathus ibericus on small fallen branches of Pinus halepensis, Gyroporus pseudolacteus in humus of Pinus pinaster, and Pseudoascochyta pratensis (incl. Pseudoascochyta gen. nov.) from soil. Thailand: Neoascochyta adenii on Adenium obesum, and Ochroconis capsici on Capsicum annuum. UK: Fusicolla melogrammae from dead stromata of Melogramma campylosporum on bark of Carpinus betulus. Uruguay: Myrmecridium pulvericola from house dust. USA: Neoscolecobasidium agapanthi (incl. Neoscolecobasidium gen. nov.) on Agapanthus sp., Polyscytalum purgamentum on leaf litter, Pseudopithomyces diversisporus from human toenail, Saksenaea trapezispora from knee wound of a soldier, and Sirococcus quercus from Quercus sp. Morphological and culture characteristics along with DNA barcodes are provided.

A New General Multilevel Converter Topology Based on Cascaded Connection of Submultilevel Units With Reduced Switching Components, DC Sources, and Blocked Voltage by Switches

Abstract: A new cascade topology for multilevel converter is introduced in this paper which comprises series connection of several submultilevel units. To determine the magnitudes of the dc sources, two new methods are described. The proposed topology is optimized to generate any levels with minimum number of components and peak voltage on switches. The presented topology can be used in high-voltage applications due to using the switches with low voltage rating. To indicate the merits of the proposed structure, comparison studies are provided with other topologies in terms of the number of elements and peak voltage on switches. The comparison results prove that the presented cascade multilevel converter requires fewer components. Moreover, it is shown that the total peak voltage on switches in the proposed topology is less than other structures. Experimental work is presented to demonstrate the performance of the presented multilevel converter.

A comparative study of artificial neural network (MLP, RBF) and support vector machine models for river flow prediction

Abstract: This study investigates the applicability of multilayer perceptron (MLP), radial basis function (RBF) and support vector machine (SVM) models for prediction of river flow time series. Monthly river flow time series for period of 1989–2011 of Safakhaneh, Santeh and Polanian hydrometric stations from Zarrinehrud River located in north-western Iran were used. To obtain the best input–output mapping, different input combinations of antecedent monthly river flow and a time index were evaluated. The models results were compared using root mean square errors and the correlation coefficient. A comparison of models indicates that MLP and RBF models predicted better than SVM model for monthly river flow time series. Also the results showed that including a time index within the inputs of the models increases their performance significantly. In addition, the reliability of the models prediction was calculated by an uncertainty estimation. The results indicate that the uncertainty in the SVM model was less than those in the RBF and MLP models for predicting monthly river flow.

Vegetable oil blending: A review of physicochemical, nutritional and health effects

Abstract: Background Oils and fats have many functions in food product preparation. Quality, stability and nutritional features of oils are the most important factors in food technology. There is no pure oil with good functional and nutritional properties and appropriate oxidative stability. Therefore, vegetable oils are modified using different methods to enhance their commercial applications and to improve their nutritional quality. Modification methods are hydrogenation, interesterification, fractionation and blending. Scope and approach Trans isomers of fatty acids formed during hydrogenation are known to have negative effects on health. Interesterification needs special equipment and is more expensive. Fractionation is also applicable only for some fats/oils. Blending should not have any adverse effects on health attributes. Blending vegetable fats/oils with different compositions and properties is one of the simplest methods to create new specific products with desired textural, oxidative and nutritional properties which lead to improved industrial applications. Key findings and conclusions This paper is a brief review of recent publications on the positive advantages of blending vegetable oils with different properties to obtain new oil mixtures. There are many researches on oil blending, and results show that oil blending is widely used in food industry to produce blended oils with improved stability and nutritional characteristics at an affordable price. In the future, there are also many economical and health reasons for the production of new oil blends using new and conventional oil sources to be introduced to the market.

Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River, Iran

Abstract: The accuracy of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels of northwest Iran’s Aji-Chay River was assessed. The models were calibrated, validated and tested using different subsets of monthly records (October 1983 to September 2011) of individual solute (Ca2+, Mg2+, Na+, SO4 2− and Cl−) concentrations (input parameters, meq L−1), and electrical conductivity-based salinity levels (output parameter, µS cm−1), collected by the East Azarbaijan regional water authority. Based on the statistical criteria of coefficient of determination (R2), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency coefficient (NSC) and threshold statistics (TS) the ANFIS model was found to outperform the ANN model. To develop coupled wavelet-AI models, the original observed data series was decomposed into sub-time series using Daubechies, Symlet or Haar mother wavelets of different lengths (order), each implemented at three levels. To predict salinity input parameter series were used as input variables in different wavelet order/level-AI model combinations. Hybrid wavelet-ANFIS (R2 = 0.9967, NRMSE = 2.9 × 10−5 and NSC = 0.9951) and wavelet-ANN (R2 = 0.996, NRMSE = 3.77 × 10−5 and NSC = 0.9946) models implementing the db4 mother wavelet decomposition outperformed the ANFIS (R2 = 0.9954, NRMSE = 3.77 × 10−5 and NSC = 0.9914) and ANN (R2 = 0.9936, NRMSE = 3.99 × 10−5 and NSC = 0.9903) models.

A new combination of artificial neural network and K-nearest neighbors models to predict blast-induced ground vibration and air-overpressure

Abstract: Blasting operation is widely used method for rock excavation in mining and civil works. Ground vibration and air-overpressure (AOp) are two of the most detrimental effects induced by blasting. So, evaluation and prediction of ground vibration and AOp are essential. This paper presents a new combination of artificial neural network (ANN) and K-nearest neighbors (KNN) models to predict blast-induced ground vibration and AOp. Here, this combination is abbreviated using ANN-KNN. To indicate performance of the ANN-KNN model in predicting ground vibration and AOp, a pre-developed ANN as well as two empirical equations, presented by United States Bureau of Mines (USBM), were developed. To construct the mentioned models, maximum charge per delay (MC) and distance between blast face and monitoring station (D) were set as input parameters, whereas AOp and peak particle velocity (PPV), as a vibration index, were considered as output parameters. A database consisting of 75 datasets, obtained from the Shur river dam, Iran, was utilized to develop the mentioned models. In terms of using three performance indices, namely coefficient correlation (R2), root mean square error and variance account for, the superiority of the ANN-KNN model was proved in comparison with the ANN and USBM equations.