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Abstract The current research aimed to study and measure the solubility of omeprazole (used to treat and reduce stomach acid) for the first time in pure subcritical and ethanol-modified water. These tests have been performed in the 25–130 °C temperature range and constant pressure of 20 bar with the use of 0–10% ethanol weight as the cosolvent. The solubility of omeprazole in subcritical water ranged from 0.0697 × 10–4 to 5.843 × 10–4 mol fraction at temperatures from 25 to 130 °C, respectively. The highest solubility was obtained at 130 °C with a 10% ethanol weight as the cosolvent, which is indicative of a significant trend of improvement in omeprazole solubility with the increase in temperature and the use of ethanol cosolvent in various weight percentages. The solubility experimental data obtained were fitted using the semi-experimental and modified Apelblat linear model, and the findings revealed an excellent correlation between the experimental data and the data received from the linear and modified Apelblat model. Also, at the 25–130 °C temperature range, no degradation, phase transition, or other changes in the structure and physical state of the drug were observed.

Abstract Humans have utilized plants for various purposes, including sustenance and medical treatment for millennia. Researchers have extensively investigated medicinal plants’ potential in drug development, spurred by their rich array of chemical compounds. Curcumin, a valuable bioactive compound, is extracted from Turmeric, known by the scientific name Curcuma Longa L. Notably, curcumin boasts potent antioxidant and anti-inflammatory properties, making it a promising candidate for treating cancer and other microbial diseases. Therefore, the simulation study of the extraction of this important medicinal compound by water, which is a green solvent, was carried out. This study employed molecular dynamics simulation for the first time to explore the extraction of Curcuma Longa L. extract using subcritical water. The simulations were carried out at constant pressure and different temperatures, using the Compass force field in the Lammps simulation package. The findings revealed an increase in the amount of Curcuma longa extract with rising temperature, indicating a weakening of hydrogen bonds in water molecules. Water lost its polar state with increasing temperature and became a suitable non-polar solvent for extracting non-polar compounds. The average absolute relative deviation (AARD) for calculated and simulated density data was 6.45%.

Abstract In this work, microcapsules were developed by the complex coacervation of sodium caseinate and pectin as a carrier for saffron extract. Parameters such as Zeta potential, dynamic light scattering, and microscopic techniques were investigated for their influence on the formation of these complexes. Furthermore, Fourier transform infrared (FTIR) analysis confirmed the reaction mechanism between the protein and tannic acid or saffron extract. The study revealed that core/shell and protein/polysaccharide (Pr/Ps) ratios play a role in the encapsulation efficiency (EE) and loading capacity (LC) of saffron extract, with EE and LC ranging from 48.36 to 89.38% and 1.14 to 5.55%, respectively. Thermal gravimetric analysis revealed that the degradation temperature of saffron increased significantly with microencapsulation. The use of tannic acid for hardening the microcapsules led to an increase in size from 13 μm to 27 μm. Rheological findings indicated that shear-thinning behavior in the coacervates, with cross-linking, has a minor effect on the interconnected elastic gel structures. However, cross-linking improved the microcapsules' thermal and structural properties. The increase in polymer chain length due to cross-linking and the presence of the guest molecule (saffron extract) resulted in higher rheological moduli, reflecting enhanced entanglements and correlating well with the thermal, structural, and microstructural properties of the coacervates. Kinetic release studies showed a slower release in the gastric phase compared to the intestinal phase, with the Ritger–Peppas model effectively describing saffron extract release, highlighting a dominant swelling and dissolution release mechanism. Therefore, the NaCas/HMP coacervate wall materials made saffron stable in the gastric stage and sustainably release. It in the intestinal stage, promoting excellent absorption of saffron in simulated digestion. Graphical Abstract

Determining the creep function of viscoelastic pipes is one of the challenges of modeling these pipes to calibrate or determine defects. The present research aims to determine the creep function of viscoelastic pipes using transient flow pressure in the time and frequency domains. For this purpose, the proposed method is first implemented using a numerical example. The numerical part investigated the effect of signal sample size, the number of Kelvin-Voigt (K-V) elements, repeatability, and decision variables. Then, using an experimental test, the desired methodology has been evaluated. In this research, the K-V mechanical model was used to define the creep function, and its parameters, including elastic pressure wave speed, retardation times, and creep complaint coefficients, were calibrated. The results showed that using pressure signals in both time and frequency domains provides stable results for the investigated pipeline. Examining the effect of signal size showed that the creep function can be estimated with reasonable accuracy in the time domain with a few initial cycles. Also, 14.33 dimensionless frequency for a simple reservoir-pipe-valve system can provide accurate results in the frequency domain. The results of this research can be used as a suitable pre-processing to reduce the dimensions of inputs in models based on artificial intelligence.

Forecasting short-term water demands is one of the most critical needs of operating companies of urban water distribution networks. Water demands have a time series nature, and various factors affect their variations and patterns, which make it difficult to forecast. In this study, we first implemented a hybrid model of convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to forecast urban water demand. These models include a combination of CNN with simple RNN (CNN-Simple RNN), CNN with the gate recurrent unit (CNN-GRU), and CNN with the long short-term memory (CNN-LSTM). Then, we increased the number of CNN channels to achieve higher accuracy. The accuracy of the models increased with the number of CNN channels up to four. The evaluation metrics show that the CNN-GRU model is superior to other models. Ultimately, the four-channel CNN-GRU model demonstrated the highest accuracy, achieving a mean absolute percentage error (MAPE) of 1.65% for a 24-h forecasting horizon. The effects of the forecast horizon on the accuracy of the results were also investigated. The results show that the MAPE for a 1-h forecast horizon is 1.06% in four-channel CNN-GRU, and its value decreases with the amount of the forecast horizon. HIGHLIGHTS Time series analysis of water demand using hybrid deep learning models can be a suitable option for short-term forecasting.; Hybrid deep neural networks integrate the advantages of the two classic models of convolutional neural networks (CNNs) and recurrent neural networks (RNNs).; The combination of CNN and RNNs can simultaneously extract the appropriate features by CNN and learn the long dependency between data by RNNs.;

In this study CO2 absorption into aqueous droplets of N-methyl-diethanolamine (MDEA) in water-in-oil (w/o) and oil-in-water (o/w) emulsions were investigated in batch-stirred reactor at 298 K and different CO2 partial pressure in the range of 0.1-0.5 bar. The effects of the aqueous phase concentration, emulsion type, CO2 partial pressure and the amount of piperazine as a promoter on absorption percentage and loading amount of CO2 (mole of absorbed CO2/mole of amines) were studied. All microemulsion samples were prepared by titration method. The CO2 loading amounts of all experiments were calculated and the results showed that water in oil samples have better absorption performance and higher CO2 loading values. The loading values in samples were improved in both emulsion types with increasing CO2 partial pressure. The results also showed that in water-in-oil samples with different concentrations of piperazine or MDEA, CO2 absorption and loading improves with increasing amine concentration.

Abstract Forecasting precipitation is a crucial input to hydrological models and hydrological event management. Accurate forecasts minimize the impact of extreme events on communities and infrastructure by providing timely and reliable information. In this study, six artificial intelligent hybrid models are developed to predict daily rainfall in urban areas by combining the firefly optimization algorithm (FA), invasive weed optimization algorithm (IWO), genetic particle swarm optimization algorithm (GAPSO), neural network (ANN), group method of data handling (GMDH), and wavelet transformation. Optimization algorithms increase forecasting accuracy by controlling all stages. A variety of criteria are used for validating the models, including correlation coefficient (R), root-mean-square error (RMSE), mean absolute error (MAE), critical success index (CSI), probability of detection (POD), and false alarm ratio (FAR). The proposed models are also evaluated in an urban area in Ahvaz, Iran. The GAPSO-Wavelet-ANN model is superior to other models for predicting daily rainfall, with an RMSE of 1.42 mm and an R of 0.9715.

Abstract Proton exchange membrane fuel cells (PEMFC) have received a lot of interest and use metal–organic frameworks (MOF)/polymer nanocomposite membranes. Zeolite imidazole framework-90 (ZIF-90) was employed as an addition in the sulfonated poly (1, 4-phenylene ether-ether-sulfone) (SPEES) matrix in order to investigate the proton conductivity in a novel nanocomposite membrane made of SPEES/ ZIF. The high porosity, free surface, and presence of the aldehyde group in the ZIF-90 nanostructure have a substantial impact on enhancing the mechanical, chemical, thermal, and proton conductivity capabilities of the SPEES/ZIF-90 nanocomposite membranes. The results indicate that the utilization of SPEES/ZIF-90 nanocomposite membranes with 3wt% ZIF-90 resulted in enhanced proton conductivity of up to 160 mS/cm at 90 °C and 98% relative humidity (RH). This is a significant improvement compared to the SPEES membrane which exhibited a proton conductivity of 55 mS/cm under the same conditions, indicating a 1.9-fold increase in performance. Furthermore, the SPEES/ZIF-90/3 membrane exhibited a remarkable 79% improvement in maximum power density, achieving a value of 0.52 W/cm2 at 0.5 V and 98% RH, which is 79% higher than that of the pristine SPEES membrane.

Abstract Traditional solvent extraction (SX) procedures limit metal separation and purification, which consist of the organic and aqueous phases. Because differences in metal ion solvation lead to distinct distribution properties, non-aqueous solvent extraction (NASX) considerably expands the scope of solvent extraction by replacing the aqueous phase with alternate polar solvents. In this study, an experimental design approach used non-aqueous solvent extraction to extract cobalt from zinc plant residue. The aqueous phase comprises ethylene glycol (EG), LiCl and metal ions. In kerosene, D2EHPA, Cyanex272, Cyanex301, and Cyanex302 extractants were used as a less polar organic phase. Various factors were investigated to see how they affected extraction, including solvent type, extractant type and phase ratio, pH, Co(II) concentration, and temperature. The results revealed that at a concentration of 0.05 M, the Cyanex301 extractant could achieve the requisite extraction efficiency in kerosene. The optimal conditions were chosen as the concentration of Cyanex 301 (0.05 M), the concentration of cobalt (833 ppm), the pH (3.5), and the percent of EG (80%). As a result, during the leaching process, these systems are advised for extracting and separating a combination of various metal ions.

To analyze transient flows, continuity and momentum equations must be solved. Due to the non-linear friction term in the momentum equation, numerical methods such as method of characteristics (MOC) are used to analyze the problem in thetime domain. Although numerical methods are easy to use, but they are numerically expensive and time-consuming, especially for advanced applications of transient analysis, e.g., real-time evaluations and fault detection algorithms, including inverse problem solutions. To cope with mentioned problems, an approximate analytical solution should be investigated, which is not required high computational time. To this end, the nonlinear equations should be linearized. Thus, the focus of this paper is to investigate the linearization methods. Therefore, four different linearization methods are applied and the resultingequations of each method in different RPV systems are solved. The efficiency of each method is compared with the results obtained from the numerical analysis of nonlinear governing equations. The results show that linearized water hammerequations provide reasonable results in early pressure wave cycles. The obtained results show that the coefficient of determination (R2) of the linearized models changes from 0.92 to 0.99. Also, by comparing the results of linearization modelswith each other, the linearized momentum equation in the time domain by replacing the mean velocity instead of the instantaneous velocity is the most accurate model which R2 is 0.999452.

Abstract Background The electrostatic interactions between polysaccharides and proteins are an interesting field in the complex coacervation. PH and mixing ratio have major effect on the complexation and the coacervates structure. Hence, it is necessary to find the optimum pH and mixing ratio of the coacervates as well as understanding the thermal, mechanical, and structural characterization of the coacervates. Thus, structural changes of the complexes of sodium caseinate (NaCas) and high methoxyl pectin as a function of pH (2.00–7.00), biopolymer ratios (1:1, 2:1, 4:1, and 8:1), and total biopolymer concentration (0.1, 0.2, and 0.4% w/v) were evaluated by light scattering and ζ-potential measurements. The phase separation behavior of the NaCas/HMP coacervate and its kinetics turbidity were also investigated via monitoring the turbidity profiles. Moreover, the thermal, rheological and structural behavior of the coacervates was evaluated at the selected pH values. Results The highest turbidity, particle size, and viscosity were achieved at pHmax = 3.30 and formation or dissociation around the pHmax was confirmed by particle size and FTIR. The optimum condition for the coacervation of NaCas and HMP was obtained at ratio 4:1 and 0.4% w/v. Thermal and mechanical stability of the NaCas/HMP coacervates was improved at pH 3.30. By increasing the total concentration of biopolymers, the NaCas/pectin ratio shifted to higher pH values. Furthermore, the maximum coacervate yield was achieved at 39.8% w/w at a ratio of 4:1 of NaCas/HMP and a total biopolymer concentration of 0.4% w/v. Conclusion Phase separation behavior of the coacervates exhibited the optimum pH in coacervation between NaCas and HMP. Furthermore, the rheological, thermal and structural stability of the coacervates were improved in comparison with the single biopolymers. Graphical Abstract

Background: Immune cells and their secreted cytokines are known as the first barrier against pathogens. Leishmania major as an intracellular protozoan produces anti-inflammatory cytokines that lead to proliferation and survival of the parasite in the macrophages. miRNAs are small non-coding RNA molecules that regulate mRNAs expression. We aimed to investigate the relationship between the expression of TGF-β and a bioinformatically candidate miRNA, in leishmaniasis as a model of TGF-β overexpression. Methods: The miRNAs that target TGF-β -3´UTR were predicted and scored by bioinformatic tools. After cloning of TGF-β-3'UTR in psi-CHECK TM- 2 vector, targeting validation was confirmed using Luciferase assay. After miRNA mimic transfection, the expression of miR-27a, TGF-β, as well as Nitric Oxide concentration was evaluated. Results: miR-27a received the highest score for targeting TGF-β in bioinformatic predictions. Luciferase assay confirmed that miR-27a is targeting TGF-β-3'UTR, since miR-27a transfection decreased the luciferase activity. After miRNA transfection, TGF-β expression and Nitric Oxide concentration were declined in L. major infected macrophages. Conclusion: Bioinformatic prediction, luciferase assay, and miRNA transfection results showed that miR-27a targets TGF-β. Since miRNA and cytokine-base therapies are developing in infectious diseases, finding and validating miRNAs targeting regulatory cytokines can be a novel strategy for controlling and treating leishmaniasis.

To examine the genetic diversity of Leishmania major, 100 Giemsa-stained positive slides were collected from endemic foci of Iran (Northeast, Central, and Southwest provinces) over two consecutive years during 2019-2021. The Leishmania ITS-rDNA gene was amplified and Leishmania sp. was recognized by PCR-RFLP and sequencing. In addition, 178 registered ITS-rDNA sequences from other geographical regions of Iran were retrieved from GenBank, including different host species (human, sandfly and rodent). A total of 40 new haplotypes were discovered using the ITS-rDNA sequence analysis. IR29 (20.6%) and IR34 (61%) were the two most common haplotypes, represented by a star-like feature in the overall population. Analysis of the molecular variance test revealed low genetic diversity of L. major in human cases (Haplotype diversity; 0.341), rodent (Hd; 0.387) and sandfly (Hd; 0.390) sequences. The lowest genetic diversity of L. major was observed in Southwest/Southeast Iran (Hd: 0.104-0.286). The statistically Fst value indicated that L. major is not genetically differentiated between geographic regions of Iran, except for the Northeast-Southwest (Fst: 0.29055) and Central-Southwest (Fst: 0.30294) population pairs. The current study as the first investigation discloses new perspectives for further evaluation in the identification local transmission paradigms and initiating effective prevention strategies.

Giardia duodenalis is a cryptic protozoan, which has eight assemblages (A-H). Assemblages A and B are the main genotypes reported from humans with probable anthroponotic and zoonotic transmission. The current study aimed to characterize G. duodenalis assemblages in tuberculosis (TB) patients and healthy subjects using multilocus genotyping (MLG). Thirty Giardia-positive stool samples, which were obtained from TB patients and healthy subjects were included in the study. After total DNA extraction, three β-giardin (bg), triosephosphate isomerase (tpi), glutamate dehydrogenase (gdh) genes were amplified and sequenced. Obtained sequences were compared to the GenBank database to characterize assemblages. Phylogenetic analysis using Maximum Likelihood (ML) and Tamura 3-parameter was performed for each gene. From 30 Giardia-positive subjects, 17 (57%) and 13 (43%) were from healthy and TB-infected subjects, respectively. There was no significant co-existence of Giardia and tuberculosis (P-value = 0.051). In addition, 14 (46.7%) and 16 (53.3%) of Giardia isolates were from asymptomatic and symptomatic subjects, respectively. PCR amplification was successful in 25 single samples (83.3%) consisted of 20 for tpi, 15 for bg, and 13 for gdh genes. Accordingly, 13/25 (52%) and 8/25 (32%) belonged to assemblage A and assemblages B, respectively, whereas 4/25 (16%) were either assemblage A or B with different genes at the same time. Significant correlation between assemblages and TB, age, and symptoms was not seen. The phylogenetic analyses represented no separation based on TB and gastrointestinal symptoms. Assemblage A was the predominant genotype in samples. The high frequency of assemblage AII indicated importance of anthroponotic transmission of Giardia in both healthy and TB patients. In addition, considering the exclusive reports of sub-assemblage AIII in wild ruminants, the presence of AIII in the current study have to be carefully interpreted. The inconsistency between the assemblage results of either bg or gdh loci with tpi gene signifies the insufficiency of single gene analysis and the necessity for MLG in molecular epidemiology of G. duodenalis.

Abstract Background Blastocystis sp. is an anaerobic intestinal protozoan parasite of humans and a wide range of animals worldwide. In the current study the correlation between the cysteine protease activity of clinical samples of Blastocystis sp. ST1–3 and 6 with the levels of pro-inflammatory cytokines was evaluated. Methods Stool samples were collected from subjects with or without clinical symptoms. All samples were cultivated in DMEM medium. The bacteria were eliminated or reduced in Blastocystis sp. positive samples subtypes 1–3 and 6 by a variety of antibiotics and consecutive sub-cultures. To prepare parasite lysate, 1 × 105 Blastocystis sp. from each isolate were harvested and lysed using freeze-thaw. Protease activity of each isolate was measured and the gene expression of pro-inflammatory biomarkers in HT-29 cell line sensed by isolates was investigated using quantitative Real-time PCR. Results Protease activity assay showed inter- and intra-subtype variations among subtypes regarding the presence of symptoms, while the protease activity of symptomatic isolates was higher than asymptomatic isolates. The highest and lowest levels of protease activity were seen in ST6 and ST2, respectively. However, patterns of the expression of pro-inflammatory biomarkers in HT-29 cell line was different regarding the presence of symptoms and time points. There was no significant correlation between protease activity of different subtypes with the expression levels of pro-inflammatory biomarkers. Conclusions Our study indicated a higher protease activity among isolates from symptomatic compared to asymptomatic subjects, suggesting functional role for proteases in clinical symptoms due to Blastocystis sp. The lack of correlation between the levels of expression of pro-inflammatory biomarkers with subtypes regarding the presence of clinical symptoms proposes the importance of host-related factors in presentation of clinical symptoms.

Flood impact assessment in a river system is done with the help of flood routing and this process helps to determine the status of sensitive points of the route in terms of flood entry and the resulting risks for urban and rural areas. For flood routing, a hydrodynamic numerical model should be implemented and this model needs upstream and downstream boundaries. In some cases, the upstream boundary, which is usually a hydrograph, is not available due to the lack of facilities and it is necessary to be generated for numerical model implementation. The purpose of this study is to present an integrated method comprising an optimization model and a hydrodynamic numerical model for flood modeling in order to determine the upstream hydrograph using the measured downstream hydrograph along a river. The routing procedure consists of three steps: (1) generating a hypothetical upstream hydrograph using the genetic algorithm method; (2) hydrodynamic modeling using a numerical simulation model for flood routing according to the hypothetical hydrograph, which is generated in the first step; (3) comparing the calculated and observed hydrograph in the downstream by using a fitness function. This recommended procedure was named the Reverse Flood Routing Method (RFRM) and was then applied to Karun River, the largest river in Iran. Comparison of the final generated upstream hydrograph by the RFRM model with the corresponding measured hydrograph at the upstream boundary (here Ahvaz hydrometric station was assumed as an ungauged river location) shows the high accuracy of the recommended model in this study.

Today, water desalination methods are of great importance in solving the freshwater crisis in the world, so that in recent years, the world's water desalination capacity has increased dramatically. Among them, the reverse osmosis membrane technology has been the most popular and the most commonly used. There are problems such as high energy consumption, high operating costs, and fouling in this method. The objective of this paper was to use reverse and forward osmosis membrane methods simultaneously in a hybrid reverse-forward osmosis setting, which enabled us to take advantage of the benefits of forward osmosis such as not being dependent on high hydraulic pressure, lower cost and less membrane fouling compared to reverse osmosis. Another objective of the study was to evaluate the permeate water production efficiency of desalination with this hybrid method. It is expected that using the hybrid method will reduce the required pressure for conducting reverse osmosis process to achieve a specified permeate flux, because it reduces cost and energy. An HRFO laboratory pilot with a capacity of 50 m3/day was designed and set up in the Hydraulic Lab of Shahid Chamran University of Ahvaz for running hybrid experiments. The design of the pilot was such that it could operate in both reverse osmosis and HRFO. HRFO experiments were carried out at pressures of 4.5 to 10.5 bar for Ahvaz urban water as feed solution, as well as NaCl as draw solution with a concentration of 2000 to 10000 mg/L via the experimental HRFO plant. It was found that adding the forward osmosis to reverse osmosis at the best situation (lowest pressure and highest concentration of draw solution) can increase the permeate water production efficiency of desalination by 55.12%. The best hybridization degree of these two methods was determined to be 64.5% for reverse osmosis and 35.5% for forward osmosis.

Background and purpose: Increasing population and urbanization density and as a result increasing impermeable levels, led to an increase in the volume of urban runoff. Applying simulation models is a suitable way to know the amount of runoff quality parameters. This study aims at evaluating the quality of urban runoff in Shushtar city using storm water management model (SWMM). Materials and Methods: Two given rainfall events in 1395 for calibration and validation of the model were considered. The parameters related to the first rainfall event were measured at the outlet of the urban drainage system. Quantitative and qualitative calibration of the model was performed using the first rainfall and model validation was performed using the second rainfall. Results: In the hydraulic calibration, mean values of impermeability, slope, catchment width and manning coefficient were estimated to be 50%, 75%, 25 m and 0.013, respectively. In the qualitative calibration, the coefficients of the Build-up equations for TSS, COD and Zn were equal to 95-25, 48-1, 1- 0.09, respectively. The coefficients of Wash-off equations for TSS, COD and Zn were estimated 0.21- 0.8, 0.2-0.8 and 0.19-0.78, respectively. Conclusion: The results showed that the accurate calibration of the model enhances the ability of the model to estimate the quantitative and qualitative parameters in future rainfall events for the study area. According to the results, the modeling is a powerful tool that can be very useful to improve runoff management.

The inverse transient analysis (ITA) method is amongst the successful leak detection methods in water distribution networks. However, determining the unknown leakage parameters such as number, location, and area of leakages is computationally time-consuming and costly due to applying metaheuristic algorithms, like the genetic algorithm (GA). This study aimed to present a novel approach to resolve this issue in order to enhance the accuracy and speed of the ITA method while maintaining its computational structure. In this research, surrogate models were incorporated in the optimization process of the ITA method. Mimicking the behavior of the objective function, surrogate models attempt to represent the most similar behavior at a low computational cost. In this regard, a new optimization algorithm based on the Kriging surrogate model, called GA-Kriging was proposed. In this algorithm, according to the structural characteristics of the Kriging surrogate model, an EI index was presented to modify the offspring selection scheme in GA. In order to evaluate the GA-Kriging algorithm and compare its performance with the conventional GA, a reference water distribution network was considered for leak detection. The accuracy and computational efficiency of the results in the GA-Kriging algorithm were 52% and 75% higher than those of the conventional GA, respectively. The present study concluded that appropriate incorporation of surrogate models in the optimization process can make the computations more intelligent, reduce repeated computations and, ultimately, increase computational efficiency.

The Reverse Osmosis (RO) input parameters have key roles in mass transport and performance indicators. Several studies can be found in open literature. However, an experimental research on evaluating the brackish water RO input parameters influence on the performance metrics with justifying the interference between them via a robust model has not been addressed yet. This paper aims to design, construct, and experimentally evaluate the performance of a 50 m3/d RO pilot-plant to desalinate brackish water in Shahid Chamran University of Ahvaz, Iran. Water samples with various salinity ranging from 1000 to 5000 ppm were fed to a semi-permeable membrane under variable operating pressures from 5 to 13 bar. By evaluating permeate flux and brine flowrate, permeate and brine salinities, membrane water recovery, and salt rejection, some logical relations were derived. The results indicated that the performance of an RO unit is largely dependent on feed pressure and feed salinity. At a fixed feed concentration, an almost linear relationship was found to relate feed pressure and both permeate and brine flowrates. Statistically, it was found that 13 bar feed pressure results in a maximum salt rejection of 98.8% at a minimum permeate concentration of 12 ppm. Moreover, 73.3% reduction in permeate salinity and 30.8% increase in brine salinity are reported when feed pressure increases from 5 to 13 bar. Finally, it is concluded that the water transport coefficient is a function of feed pressure, salinity, and temperature, which is experimentally estimated to be 2.8552 L/(m2 h bar).

The rapid population growth and urban development have notably influenced the role of water distribution networks (WDNs) compared to the past. This issue encourages operators to adopt new smart tools to better system management. Such a smart system is expected to play an effective role in both crisis and normal services. For fire extinguishing services, a WDN needs to be well-equipped to supply the fire flow efficiently. In this sense, WDNs are required not only modern fire-fighting equipment but also a systematic program to satisfy the fire demand in the right place at the right time. This paper aims at introducing a pre-processing (not real-time) approach for smart pressure management using the regulation of control valves. The problem is formulated as a mathematical programing in which the reliability measure is maximized and the valve opening positions are decision variables. Using a self-adaptive Genetic Algorithm coupled with EPANET, the problem is solved. The proposed algorithm is applied to a case study from the literature and produces the optimum pattern for regulation of valves. Such results can be an appropriate guide for operators to practically maneuver valves in fire situation. The case study manifests that by applying the model the reliability of system can be increased up to 40.7%.

The accuracy of leak detection and calibration of pipe networks by means of the inverse transient analysis (ITA) is highly affected by the number and location of the measurement sites. This study introduces a conceptual decision-making model, the Decision Table Method (DTM), for the measurement site design of pipe networks with the aim of inverse transient analysis. Through the Decision Table Method, near optimum measurement sites are decided based on two criteria of the maximum sensitivity of measurement sites and the maximum diversity of sensitivity with respect to unknown parameters of leak areas and friction factors. The main advantage of DTM is that even in case of large networks, calculation of the Hessian matrix and the utilization of any optimization algorithm is not required. To evaluate the efficiency and applicability of the method, it is applied on two pipe networks of small and large size from the literature and the results are compared with the previous methods. Accordingly, the DTM is found reliable as well as easy to understand and implement.

Today, pipe systems are the most common facilities to convey various fluids from one place to another. In such facilities faults like leaks lead to advert consequences such as economic losses and social health threats. The fact that early detection of leaks can play a prominent role in reducing the amount of these undesired impacts has absorbed noticeable attention from researchers to this field of study. This paper presents a literature review on major aspects of hydraulic transient-based leak detection in pipe systems over the past three decades. The value of the present study is that an extensive database of peer-reviewed publications is brought together under a meticulous survey. It describes the trends, status and pinpoints the areas with a need for further investigation in the future. Uniquely, it contains information for over 95 publications in a tabular form, presenting domain type, analysis approach, optimization technique, topographic complexity of the case study, leak unknowns and validation approach.

Hydraulic analysis of pipe networks is generally done considering certain values for independent parameters of the system such as roughness of pipes, nodal demands, etc. Such analysis would inevitably lead to certain hydraulic responses of the system, i.e. nodal pressures, etc. This is while, inherent uncertainties associated with independent parameters as expected stresses, spread over the system and result in hydraulic stress in nodal pressure heads as dependent uncertainties. Using optimization tools, this study presents a reliable approach based on interval analysis to deal with these uncertain hydraulic stresses. In the proposed approach, the optimization problem is formulated in a manner that the nodal demands, roughness of pipes and water levels in elevated tanks would be the decision variables while extreme nodal pressures for unknown intervals are explored as the objectives functions. The large number of junctions in the case of real pipe networks, leads to inefficient iterative use of single objective optimization engine. In order to this problem, this study exploits a many-objective approach with an appropriate performance. Applying the proposed approach on a real pipe network shows that ±15% variation in nodal demands and pipes’ roughness in addition to ±1m in water levels might produce hydraulic stress in pressure heads from -13.7% to +10.2% with regard to the crisp values. In such a condition, it is possible for 125 junctions out of 128, to fail in satisfying the minimum required pressure head. It is demonstrated that the proposed approach has acceptable accuracy for analyzing hydraulic stress in real water distribution networks.

Although oral drug delivery is the best choice, many pharmaceutical drugs such as anticancer have aromatic structure and so low solubility in water and biological fluid, which reduce the amount and rate of adsorption of these drugs and hence limits on their use in treatment. Nanoscience with unique characteristics has eliminated many of these problems. As with the use of nanoscale drug carries, many properties of drug such as solubility and half-life of the drug can be improved. Graphene and graphene oxide (GO) sheets have promising candidates to advance drug delivery platforms due to its two-dimensional structure, high chemical surface area, high chemical and physical stability, lower toxicity, and biocompatibility. One of the aims of designing drug delivery platform is to increase the effectiveness of the drug by focusing on the target tissue. Among the various type of magnetic nanoparticles, superparamagnetic iron oxide nanoparticles SPION due to its excellent magnetic properties, biocompatibility, biodegradability, and mobility in targeted area using external magnetic field, attracted a lot of attention. In the current study, we benefited from the use of graphene oxide Functionalized with γ-cyclodextrins, as carrier for SN38 and superparamagnetic iron oxide, which result shows covalent attachment of active drug molecule (SN38) to cyclodextrin-graphene oxide, increase the solubility of the drug and increase local temperature and hyperthermia following laser irradiation with a wavelength at 808 nm

To evaluate a pipe network performance, both steady and unsteady flow conditions are required to be accurately analyzed in the system. For this purpose, mathematical models are developed and utilized. Calibration of parameters with dynamic effects like the steady and unsteady friction loss factors as well as pipe wave speed is crucial to the simulation models. A common approach for calibration of pipe networks under unsteady flow is the Inverse Transient Analysis (ITA) method. This study introduces a model for hydraulic analysis of unsteady flow in pressurized pipes using the numerical Method of Characteristics (MOC). To each calibration parameter a correction factor is specified. Then, a nonlinear optimization problem is developed with the aim of minimizing the discrepancy between the calculated and measured transient pressure heads at the measurement sites. The decision variables are the correction factors multiplied by the pipe wave speeds, steady friction factors and unsteady friction loss components. In this Article, the proposed model applied to an experimental system set up in the Technical University of Lisbon. By defining the genetic algorithm to minimize the objective function, after 30 generations error rate was reduced from 140 m to 92.15 meters. The results, increasing the accuracy of modeling showed as much as 33%.

Molecular analysis of antifolate resistance-associated genes—dihydrofolate reductase (dhfr) and dihydropteroate synthetase (dhps) of Plasmodium vivax is important in predicting the emergence of drug resistance to sulphadoxine-pyrimethamine (SP). The present study aimed to determine the polymorphism of dhfr and dhps genes in P. vivax field isolates. Samples from 80 microscopically diagnosed vivax malaria cases were collected from endemic areas of malaria in Hormozgan Province of Iran, from June 2010 to November 2015. The two sets of codons at position 33, 57, 58, 117, 173 of dhfr and 382, 383, and 553 of dhps genes were analysed by direct sequencing of PCR products. The majority of the isolates (70%) harboured a wild-type allele for P. vivax dhfr (Pvdhfr) and P. vivax dhps (Pvdhps). Mutations were detected in three codons of Pvdhfr (P33L, S58R and S117N) and single codon in Pvdhps (A383G). Novel mutations that have not been identified previously at codon 459 (D459A) of Pvdhps were also observed. The high prevalence of point mutation as well as the rising triple mutation of Pvdhfr and Pvdhps genotypes necessitate change in programmes and guidelines to eliminate P. vivax in future.

Background: We aimed to investigate the effect of miR-15a mimic and inhibitor of miR-155 expression on apoptosis induction in macrophages infected with Iranian strain of Leishmania major in-vitro and in-vivo. Methods: RAW 264.7 cells were infected with L. major promastigotes (MRHO/IR/75/ER), and then were treated with miRNAs. For in-vivo experiment, BALB/c mice were inoculated with L. major promastigotes, and then they were treated with miRNAs. For evaluation of miRNA therapeutic effect, in-vitro and in-vivo studies were performed using quantitative Real-time PCR, Flow cytometry, lesion size measurement, and Limiting Dilution Assay (LDA). This study was performed in Shahid Beheshti University of Medical Sciences in 2019. Results: In-vitro results of flow cytometry showed that using miR-15a mimic, miR-155 inhibitor or both of them increased apoptosis of macrophages. In in-vivo, size of lesion increased during experiment in control groups (P

Background: Cutaneous Leishmaniasis (CL) is an emerging uncontrollable and neglected infectious disease worldwide including Iran. The aim of this study was to investigate the expression profile of apoptosis- related miRNA and its target gene in macrophages. Methods: This study was carried out in the Department of Medical Parasitology and Mycology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran from January 2016 to November 2018. Applying literature reviews, bioinformatics software, and microarray expression analysis, we selected miRNA-24-3p interfering in apoptosis pathway. The expression profile of this miRNA and target gene were investigated in Leishmania major (MRHO/IR/75/ER)-infected primary and RAW 264.7 macrophages (IBRC-C10072) compared with non-infected macrophages (control group) using quantitative Real-time PCR. Results: Results of bioinformatics analysis showed that miR-24-3p as anti-apoptotic miRNA inhibits pro-apoptotic genes (Caspases 3 and 7). Microarray expression data presented in Gene Expression Omnibus (GEO) revealed a significant difference in the expression level of selected miRNA and its target gene between two groups. QRT-PCR results showed that the expression of miR-24-3p was upregulated in L. major infectioned macrophages that approved the results of bioinformatics and microarray analysis. Conclusion: Parasite can alter miRNAs expression pattern in the host cells to establish infection and its survival. Alteration in miRNAs levels likely plays an important role in regulating macrophage functions following L. major infection. These results could highlight current understanding and new insights concerning the gene expression in macrophages during leishmaniasis and will help to development of novel strategies for control and treatment of CL.

Background: Cystic echinococcosis can cause severe disease and probable death in humans. Epitopes of its antigens play a key role in the sensitivity and specificity of immunodiagnostic tests. Methods: Epitope prediction software programs predict the most antigenic linear B-cell epitopes of AgB (8 kD), Ag5, and Ag95. Six such epitopes were predicted and connected by “Gly-Ser” linker and synthesized. The purity of the concentrated recombinant multi-epitope protein was assessed by 15% SDS-PAGE. Overall, 186 serum samples were collected from the Loghman Hakim Hospital and different laboratories, Tehran, Iran, from July 2016 to February 2017. Patients infected with hepatic hydatid cysts, patients infected by other parasites and viruses, and healthy individuals were used to detect the anti-CE IgG using recombinant multi-epitope protein. Results: Forty-one samples out of 43 cases of hydatidosis were diagnosed correctly as positive, and two were negative. In addition, six negative cases of healthy individual group were diagnosed as positive and negative with rMEP-ELISA and the commercial kit, respectively. Therefore, these six samples were considered as false positive using our method. In addition, a diagnostic sensitivity of 95.3% (95% CI, 84.19% to 99.43%) and a specificity of 95.0% (95% CI, 89.43% to 98.14%) were obtained using optimum cutoff value (0.20). The sensitivity and specificity of the commercial kit was 100%. Conclusion: Our findings showed high diagnostic accuracy of the ELISA test using the developed recombinant protein, which encourages the use of this recombinant multi-epitope protein for rapid serological diagnosis of hydatidosis.

Plastic pipes are widely used in pressurized water systems. The analysis of transient flow and estimation of maximum and minimum pressure wave propagation in pipeline and pipe networks is required for design and practice of piping systems, pumping stations, and dam water conveyance tunnels. The viscoelastic properties of the polyethylene pipes have significant effect on the estimation of pressure wave speed and attenuation in transient flow. The use of polymeric pipes such as polyethylene and polyvinyl chloride has recently increased due to their technical and economic advantages over steel and concrete pipes. Due to viscoelastic behavior, polymeric pipes have a significant impact on transient flows (Pezzinga, 2002). In a fast transient flow event like water hammer, viscoelastic properties of polymeric materials cause a residual stress in the pipe wall. These deformations will not return to their original state immediately after unloading (Covas, 2003). This viscoelastic behavior also affects the intensity, shape, and dampening of pressure oscillation in transient flows. Covas (2003) developed a numerical model to simulate the viscoelastic behavior of the pipe wall in transient flow events. In this study, the results of a linear viscoelastic model were compared with experimental results in the presence and absence of unsteady friction loss. Soares et al., (2008) also considered transient flow in PVC pipes, and their results were in good agreement with those obtained by Ramos et al. (2004). Evangelista et al., (2015) studied water hammer phenomenon in a Y-shaped system both experimentally and numerically. According to their results, the linear viscoelastic model was able to simulate the water hammer phenomenon in this system. The present research deals with the introduction and simulation of dynamic effects, including unsteady friction and pipe-wall viscoelastic in transient flows in polymeric pipes that widely used in water works. Accordingly, the governing equations are rewritten and manipulated for considering the unsteady friction and viscoelastic properties. The equations are then solved using the method of characteristics coupled with the finite difference method. Appling the inverse transient analysis method and with the aid of a genetic algorithm, the unknown parameters are determined. Steady state friction coefficients have to be estimated based on steady state data and other unknown parameters were calibrated based on the transient flow.

Leakage in water transmission systems and distribution networks in addition to waste of water and energy, can cause a declined water quality due to exposure to contaminants at low pressure conditions as well as damages to roads, buildings, and infrastructures. Therefore and due to its negative impacts on economics, environmental, and social safety, determination and control of leakage is one of the most important and complex topics in water supply systems engineering. The current research investigated transient-based techniques for leak detection in Polyethylene water pipe systems. For this purpose, firstly an inverse transient analysis (ITA) tool was developed, and then for testing and validating this model, extensive experiments were carried out at Hydraulic Laboratory of Shahid Chamran University of Ahvaz to collect the necessary data. A selected set of data corresponding to two leak locations with different sizes was used to assess the ITA method. Results indicated that the leak location can be accurately pinpointed using a sample size equal to one period (T=4L/a) of the collected pressure in ITA. The error for estimation of the location for a significant leak was between 0.17% and 2.17% of the pipe length. Also, using two periods (2T) of the pressure signal, the uncertainties in leak quantity estimation were satisfactory, as less than 23% of the real leak quantity. Additionally, the comparison between the observed data and the numerical results in different conditions indicated that the hydraulic model estimated the transient pressure accurately by just incorporating the pipe wall viscoelasticity into the model.

Objective (s): SN38 is the prominent and effective anticancer drug for treating various types of human cancers such as colorectal, ovarian and lung cancers. SN38 is highly toxic, and due to its poor solubility in aqueous media, and low stability and hydrolysis at physiological pH, it has not been used as an anti-cancer drug. To overcome these problems, SN38 was conjugated with new nanocarriers in order to efficiently deliver it into cancer cells.Materials and Methods: we report the synthesis of nanocarriers based on covalent attachment of graphene oxide with β-cyclodextrin and coordinated with superparamagnetic iron oxide nanoparticles for SN38 loading and delivery. Using SPION-functionalized graphene oxide provides magnetic properties and local hyperthermia due to laser irradiation at 808 nm. Structures were characterized by using FT-IR spectroscopy and the size and morphology of the nanoparticles were determined using Malvern Zetasizer and FE-SEM, respectively. Results: The prepared nanoplatform was not significantly toxic to HT-29 cells. However, the developed graphene oxide-based nanocarrier containing SPION and SN38 was used to improve the chemotherapy through photothermal and photodynamic therapy. The optimal laser wavelength (808 nm) for PTT is consistent with that of IR-808 for PDT and the β-CD-GO-EDTA-Fe3O4-SN38 indicated synergistic effects of both drugs and SPION.Conclusion: Biocompatible nanocarrier based on functionalized graphene oxide (β-CD-GO-EDTA-Fe3O4-SN38) demonstrated strong synergistic cytotoxic activity. The new formulation has a great potential as chemo-photothermal-photodynamic therapy agents in synergistic phototherapy.

In this research, photocatalytic degradation method for COD(CHEMICAL OXYGEN DEMAND Value) removal has been introduced to treatment of petrochemical industries wastewater as an adaptable method and effective parameters in the process performance have been investigated. Therewith, by using commercial photocatalyst of titanium dioxide and empirical measurement of COD parameter, decrease percentage of this parameter of photocatalytic process during 90 minutes investigated via DOE&ANN method. To carry out experiments,A photocatalytic reactor with agitator used which UV-C lamps submerged within photocatalyst solution in the wastewater sample. Results of experiments at optimized conditions indicated that two models is in a good agreement with the consequences. These results demonstrated that photocatalyst concentration increase in the neutral pH state to optimized amount of 0.84 grams per liter under unlimited conditions and 2 grams per liter under limited conditions, causes removal increase of COD to 93 and 77 percent, respectively(from 180 to 90 and 294 respectively).

The chance of developing lung cancer is increased through being exposed to cigarette smoke illustrated by studies. It is vital to understand the development of particular histologic-type cancers regarding the deposition of carcinogenic particles, which are present in human airway. In this paper, the mass transfer and deposition of cigarette smoke, inside the human airway, are investigated applying the finite element method. The mass transfer and depositions of four types of critical cigarette smoke, namely 1, 3-butadiene, acrolein, acetaldehyde and carbon monoxide (CO), in a complete human-airway model (from mouth to B3 generation), under inhalation conditions, have been simulated. In this study, concentration distribution in inhalation is evaluated. The vapour deposition was modelled with 30 and 80 L.min-1 volumetric flow rates. Therefore, a two-dimensional model of human airway from the mouth to generation B3 was reconstructed. Then, for simulating the mass transfers and deposition fraction, the low-Reynolds-number (LRN) k–ω turbulence equation was used.

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change presents four general circulation models under the SRES emission scenarios of A2 and B1. The take-home message of these documents is the expected change in the atmospheric temperature, which undoubtedly would affect the hydrology of watersheds. These warnings dictate the necessity of prediction of the future change in the flow of rivers and the vulnerability of the people who depend on them for their water supplies. Results indicated that the average temperature variations are from -0.13 to 0.96°C and 0.72 to 1.85°C for 2016-2038 and 2039-2061 periods, respectively. Furthermore, the average monthly rainfall variations in the baseline period in comparison to the observed period (1988-2010) are from -3.5 to 182% and -20.7 to 123 % for those two periods, respectively. The daily rainfall- runoff simulation using the IHACRES model yielded the R2 of 0.684 and 0.635 for the calibration and validation stages, respectively. Overall, the mean volume of annual runoff into the Doroodzan Reservoir would decrease by 8.4 and 28.15 % as compared with the baseline period for the 2016-2038 and 2039-2061, respectively. Furthermore, the most decrease in the mean volume of monthly runoff of the basin in comparison with the baseline period has been predicted for November to be 42.34 and 54.13 % for those two periods, respectively.

Transient flows naturally occur in piping systems due to operation exigencies. It is, therefore, essential to analyze water distribution networks under transient flow conditions in an attempt to enhance their reliability. The accuracy of such an analysis highly depends on such input parameters as pipe wall roughness, wave speed, and unsteady friction loss coefficients. As these parameters vary from system to system and in different flow conditions, they cannot be definitively determined in practice. Generally, the parameters are determined by engineering judgments and trial-and-error estimations. For complex pipe networks, this can be very burdensome and time-consuming. Moreover, there are great numbers of dynamic parameters in water supply networks and their interactions are so complicated that it is extremely difficult to explicitly determine the role of each one in the system responses observed. This calls for mathematical simulation models to predict systems responses accurately. In this study, an inverse transient analysis model is introduced for the calibration of input parameters. A reverse method based on a series of measurements and computations was used for the solution of the calibration problem and efforts were made to reduce the value of the objective function by finding the optimum solution. However, the model introduced in this work differs from other similar ones in that inverse transient analysis models are often used in the time-domain while the current work uses the transfer matrix method to analyze the system in the frequency-domain. The frequency analysis of a pipe network not only provides a deep insight into the system performance but also speeds up the simulation and optimization computations. Finally, the model is applied to a lab-scale pipe network from the Technical University of Lisbon as a reference model. The parameters with dynamic effects are calibrated and compared with available data obtained from massive experimental observations and numerical trial-and-errors in the time domain. Results indicate not only that the model is adequately simple and faster than its counterpart model in the time domain but that it is capable of successfully calibrating the network with results in good agreement with observed data.

Background:intestinal parasitic infection is one of the most prevalent health problems in developing countries. This study was conducted to determine the prevalence of intestinal parasitic infection and its correlation with socio-demographic parameters in Haji-abad, 2015.MaterialsandMethods:This cross-sectional descriptive study was conducted on 635 samples. After completing questionnaires, stool samples were assessed macroscopically, and microscopically using direct slide smear with saline and lugol, formalin-ether concentration, Ziehl-Neelsen staining to track Cryptosporidium species and Trichrome staining for the samples suspected to amoeba and other indeterminate cases. PCR using specific primers was conducted for Entamoebahistolytica/E. dispar suspected samples. The results were analyzed using SPSSver.16 software.Results:Of total 635 samples, 198 cases (31.2%) were infected by at least one intestinal parasite. The most common parasites in this area were: Blastocystis sp. (105, 16.5%), Endolimax nana (43, 6.8%), Entamoeba coli (32, 5.0%), Giardia lamblia (31, 4.9%), and Iodamoeba butschlii (11, 1.7%). Enterobius vermicularis (1, 0.2%) was the only detected helminthic infection. Regarding socio-demographic variables, age, residence, sampling month, and job showed a significant correlation with IPIs (p-value=0.031, 0.019, 0.014, 0.012; respectively). None of nine microscopically suspected E. histolytica/E. dispar cases were confirmed by molecular investigations (PCR method) and were considered as E. coli.Conclusion:In agreement with previous studies, helminthes infections show a dramatic decline compare to protozoa in this study. The relatively high incidence of intestinal protozoan infections in studies performed in Iran supports strategies for pre­venting the transmission and expansion of these parasites as a priority.

In this study, the photocatalytic method was used for treating the spent caustic in the wastewater of Olefin units used in petrochemical industries which contain large amounts of total dissolved solids (TDS). By using the synthetic photocatalyst of suspended titanium dioxide and measuring the chemical oxygen demand (COD) which was reduced in the photocatalyst (lbc) process, the values of COD were modeled and evaluated by means of the Box-Behnken (BBD) and the artificial neural network (ANN) using experimental tests in a double-cylindrical-shell photo reactor. According to the applied calculations, it was found that the artificial neural network was a more suitable method than the experimental design in modeling and forecasting the amount of COD removal. The modeling employed in this research showed that increasing the concentration of the photocatalyst in a state of neutral pH enhanced the COD removal up to the optimal amount of 1.31 g/L without restrictions and 2 g/L with restrictions at the rate of 81% and 79%, respectively. In addition, the study of the parameter effects including oxidizer amount, aeration rate, pH, and the amount of loaded catalyst indicated that all factors except pH had a positive effect on the model; furthermore, if the interactions were neglected, the COD removal efficiency would increase by increasing each of these factors (except pH). In addition, there was no interaction between the aeration and the concentration of the photocatalyst, and the acidic pH was more suitable at low concentrations of the photocatalyst. Besides that, by increasing the pH, the efficiency of removal was reduced when the oxidant was at its low level. The results showed that photolysis and adsorption adoptions had a very small effect on the efficiency of the removal of COD compared to the photocatalyst adoptions, and it was insignificant. In addition, the photocatalytic method had an acceptable capacity for removing the phenol in the wastewater sample, whereas it was inefficient in reducing the sulfide solution in the wastewater.

In this study, photocatalytic treatment was used to treat spent caustic wastewater of olefin petrochemical plants which is one of industrial wastewater with high total dissolved solids (TDS). For this purpose, by using the synthetic photocatalyst of the suspended TiO2 Doped Nitrogen(N-TiO2)and measuring the parameter of the chemical oxygen demand (COD), this parameter decrease percentage in the Photocatalyst process has been modeled and evaluated by means of Box-Behnken (BBD) design of experiment (DOE) in a double-cylindrical-shell photo-reactor. Modeling of this research showed that increasing the concentration of photocatalyst in a state of neutral pH, lead to enhance the COD removal till the optimal amount of 0.64 g/L without restrictions and 2 g/L with restrictions in the rate of 96% and 90%, respectively. In addition, the study of the parameters’ effects including oxidizer amount, aeration rate, pH and the amount of loaded catalyst indicate that all factors except pH have been had positive effect on the model and if the interactions are neglected, the COD removal efficiency will increase by increasing each of these factors (except pH).

Background: The present study aimed to assess the grouping of subtypes 1-3 and 6 of Blastocystis according to the size and generation time of the parasite among the symptomatic and asymptomatic subjects. Methods: Blastocystis subtypes1-3 and 6 isolated from symptomatic and asymptomatic subjects and were cultivated in DMEM medium. In order to assess inter- and intra-subtype variation in size, all the isolates were measured using morphometric criteria. Generation time was calculated using approximately 1×104 Blastocystis, which were cultivated in DMEM, every 24h for 4 days. Results: All subtypes had 5 to 185 μm diameter range. The smallest size was attributed to ST1, followed by ST6 and ST2. ST3 showed the most variable size and phenotypes compared with the other three subtypes. Furthermore, amoeboid forms and parasite clumping were only seen in ST3-S (symptomatic subjects). Generation time analysis showed that the number of ST1 isolated from symptomatic and asymptomatic subjects peaked higher than the other subtypes. Conclusion: This is the first study discussing inter-intra-size, phenotype and generation time variations among 4 common subtypes of Blastocystis. Accordingly, ST3 was largest subtype and showed most diversities in both size and phenotype, while ST1 was smallest subtype with lowest intra-subtype variation.

Aim: Fascioliasis is one of the most zoonotic diseases with global extension. As the epidemiological distribution of Fasciola may lead to various genetic patterns of the parasite, the aim of this study is to identify Fasciola hepatica based on spermatogenesis, and phylogenetic analysis using mitochondrial (nicotiamide adenine dinucleotide dehydrogenase subunit I [ND1] and cytochrome oxidase subunit I) gene marker. Materials and Methods: In this study, 90 F. hepatica collected from 30 cattle at slaughterhouse located in three different geographical locations in the North-East of Iran were evaluated based on spermatogenetic ability and internal transcribed spacer 1 gene restriction fragment length polymorphism pattern. Genetic diversity and phylogenetic relationship using mtDNA gene marker for the isolates from the North-East of Iran, and other countries were then analyzed. Results: Partial sequences of mtDNA showed eight haplotypes in both genes. The phylogenic analysis using neighbor joining as well as maximum likelihood methods showed similar topologies of trees. Pairwise fixation index between different F. hepatica populations calculated from the nucleotide data set of ND1 gene are statistically significant and show the genetic difference. Conclusion: F. hepatica found in this region of Iran has different genetic structures through the other Fasciola populations in the world.

This paper introduces a methodology for soil slope stability analysis based on optimization, limit equilibrium principles and method of slices. In this study, the slope stability analysis problem is transformed into a constrained nonlinear optimization problem. To solve that, a Self-Adaptive Genetic Algorithm (GA) is utilized. In this study, the slope stability safety factors are the objective functions, slip surface parameters are the decision variables and, the equilibrium equations are the problem constraints. The proposed model satisfies all conditions of the equilibrium completely. It is also applicable to problems with different soil layers, variable soil properties and including pore water pressure. The model is applied against a benchmark example and the results are compared with previous studies. Accordingly, it is found computationally efficient and reliable.

To derive optimal operation policies from multi-reservoir systems, applying the conflict multiple goals simultaneously is very important. In order to, this paper presents a multi-objective optimization-simulation model, which is consist of agriculture and minimum flow goals in a three dam water resources system. For this purpose, a discrete hedging rule with a non-dominated sorting genetic algorithm has been coupled to minimize the modified shortage index over a series of hydrological record of 48 years. The evaluation metrics are diversity metric and standard deviation, which obtained values of each are equal to 0.357 and 0.0111 respectively. The results show the efficient performance of this algorithm to obtain Pareto frontier. Also, multi-objective algorithms present a set of optimum solutions for users instead of a solution, thus it helps to make decision in supplying the conflict goals of agriculture and minimum flow in different and complicate operation conditions such as drought periods easily.

Background: The main aim of the present research was to develop the experimental meningo encephalitis due to Naegleria australiensis isolated from geothermal water sources in mice model, November 2017 in Iran. Methods: Naegleria australiensis was isolated from geothermal water sources in northern Iran. The number of amoebae was adjusted to be 1×104/ml amoebae. The experimental infection was done using 3 wk old male (BALB/c) mice. Seven animals were used for experimental amebic infection and one animal was selected for the control. Intranasal (IN) and intracerebral (IC) inoculation of amoebae were done. The mice were then monitored on daily observation and as soon as they present any brain involvement they sacrificed. The brain of all animals was then dislocated and passaged in non-nutrient agar. Results: One mouse out of seven infected mice were showed clinical symptoms of meningoencephalitis. Within few hours of culture of the brain, many vegetative forms of amoebae were detected in plate culture. The other infected animals and control mice showed no clinical symptoms until day 14. After 14 d all the animals sacrificed. The culture was negative up to one month. Conclusion: The lack of brain involvement of other animals in the present study could be due to animal immune system or it may be possible that the amoebae did not reach to olfactory bulb of nostrils.

Background: Vivax malaria is more prevalent in the malarious areas of Iran, which makes vaccine research a high priority. Serine Repeat Antigens (SERA) have essential role in the parasite life cycle and high expression profiles of PvSERA5 make it suitable vaccine candidates. This study aimed to evaluate the genetic diversity of C-terminal region of PvSERA5 in Iranian isolates of Plasmodium vivax in Sistan and Baluchistan. Methods: Totally, 49 blood samples were taken from symptomatic malaria patients in Sistan and Baluchistan Province in 2016. Mono-infection to P. vivax was confirmed by 18srRNA-Nested-PCR. Genomic DNA was extracted and C-terminal region of PvSERA5 was amplified by specific primers. PCR-products have been sequenced and analysis was done by using bioinformatics software, mainly DnaSP & MEGA5. Results: Genetic diversity was calculated 14.8% in C-terminal region of PvSERA5 in Iranian isolates, 19 different sequences and 4 haplotypes existed. The amount of Tajima’s D (0.3805) and ratio of non-synonymous to synonymous mutation (1.82) showed that C-terminal region of PvSERA5 is under positive natural selection; also intragenic recombination could interfere. Conclusion: Results could be helpful in any research, regarding this antigen as vaccine candidate in Iran or worldwide.

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Background: The fatal form of leishmaniasis is visceral form (VL), found in some of the countries in the world. Visceral leishmaniasis has been reported sporadically from all provinces in Iran, including Lorestan. This study aimed to characterize parasite species in DAT positive and some of the DAT negative human blood samples of Delfan district, Lorestan Province, central Iran. Methods: Blood samples were collected from different geographical areas of Delfan. Serum was used for DAT test and remained part of molecular study. DNA was extracted by using DNG-plus extracted kit (Cinagen, Iran). Poly­merase chain reaction amplification of Leishmania kDNA and PCR-RFLP of ITS1 was done to identify Leishmania species. Some amplicons were sequenced, submitted to GenBank and analyzed by BLASTn. Results: Expected band of kDNA for L. infantum (720bp) was amplified in 16 out of 186 (8.6%) samples which showed previously anti-Leishmania antibody at different titers or were negative serologically. Using BLASTn, 93% similarity with L. infantum has been shown. The rDNA-ITS1 was amplified only in 9 samples (4.7%). RFLP pattern was similar to what expected for L. infantum. Conclusion: A new emerging hypo-endemic focus, caused by L. infantum, is going to be established in Delphan District, Lorestan Province. Further studies on vector and reservoirs are necessary for the region and other parts of Lorestan Province.