Bu-Ali Sina University

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTBis- and Trisindolylmethanes (BIMs and TIMs)†Morteza Shiri*‡, Mohammad Ali Zolfigol§, Hendrik Gerhardus Kruger⊥, and Zahra Tanbakouchian‡View Author Information Department of Chemistry, College of Science, Alzahra University, Vanak, 1993891176, Tehran, Iran, Faculty of Chemistry, Bu-Ali Sina University, 6517838683, Hamedan, Iran, School of Chemistry, University of KwaZulu-Natal, Durban 4001, South Africa†This paper is dedicated to Prof. Dr. Junes Ipaktschi on occasion of his 70th birthday.* To whom correspondence should be addressed. Fax: +98 21 88041344. E-mail: [email protected]‡Alzahra University.§Bu-Ali Sina University.⊥University of KwaZulu-Natal.Cite this: Chem. Rev. 2010, 110, 4, 2250–2293Publication Date (Web):December 30, 2009Publication History Received18 May 2009Published online30 December 2009Published inissue 14 April 2010https://pubs.acs.org/doi/10.1021/cr900195ahttps://doi.org/10.1021/cr900195areview-articleACS PublicationsCopyright © 2009 American Chemical SocietyRequest reuse permissionsArticle Views7054Altmetric-Citations509LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Aldehydes,Anions,Catalysts,Indoles,Reaction products Get e-Alerts

Abstract Fluorescence excitation‐emission matrix (EEM) measurements are useful in fields such as food science, analytical chemistry, biochemistry and environmental science. EEMs contain information which can be modeled using the parallel factor analysis (PARAFAC) model but the data analysis is often complicated due to both Rayleigh and Raman scattering. There are several established ways to deal with scattering effects. However, all of these methods have associated problems. This paper develops a new method for handling scattering using interpolation in the areas affected by first‐ and second‐order Rayleigh and Raman scatter in such a way that the interfering signal is, at best, removed. The suggested method is fast and requires no additional input other than specifying the scattering region. The results of the proposed method were compared with those obtained from common alternative approaches used for preprocessing fluorescence data before analysis with PARAFAC and were shown to be equally good for various types of EEM data. The main advantage of the interpolation method is in its lack of additional metaparameters, its algorithmic speed and subsequent speed‐up of PARAFAC modeling. It also allows for using EEM data in software not able to handle missing data. Copyright © 2007 John Wiley & Sons, Ltd.

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.

The pseudo-second-order (PSO) kinetic model has become among the most popular ways to fit rate data for adsorption of metal ions, dyes, and other compounds from aqueous solution onto cellulose-based materials. This review first considers published evidence regarding the validity of the mechanistic assumptions underlying application of the PSO model to adsorption kinetics. A literal interpretation of the model requires an assumption that different adsorption sites on a solid substrate randomly collide with each other during a rate-limiting mechanistic step. Because of problems revealed by the literature regarding the usual assumptions associated with the PSO model, this review also considers how else to account for good fits of adsorption data to the PSO model. Studies have shown that adsorption behavior that fits the PSO model well often can be explained by diffusion-based mechanisms. Hypothetical data generated using the assumption of pseudo-first-order rate behavior has been shown to fit the PSO model very well. In light of published evidence, adsorption kinetics of cellulosic materials is expected to mainly depend on diffusion-limited processes, as affected by heterogeneous distributions of pore sizes and continual partitioning of solute species between a dissolved state and a fixed state of adsorption.

In this research, temporal trends of reference evapotranspiration (ET0) values were investigated in arid regions of Iran. For this purpose, meteorological observations collected from 11 high quality meteorological sites over a 41-year period (1965–2005) were used and statistically significant ET0 trends in the monthly, seasonal and annual time basis were detected using nonparametric Mann-Kendall (MK) and Spearman’s Rho (SR) tests at the 5% significant level. To eliminate the effect of serial correlation on the test results, the Trend Free Pre-Whitening (TFPW) approach was applied. The results of this study indicated that the ET0 trends for some cities were increasing (positive) however, for some sites, they showed decreasing (negative) trends. The most number of significant ET0 trends on a monthly time scale occurred at Birjand but no significant trend was observed at the Bandarabbas, Sabzevar and Semnan sites. On the annual time scale, Mashhad revealed the highest positive trend (7.5 mm per year). On the other hand, Esfahan showed the highest decreasing (negative) ET0 trend of about −6.38 mm per year. In general, the performances and abilities of the MK and SR tests were consistent at the verified significant level.

BACKGROUND: This meta-analysis addressed the association between substance use disorder (SUD) and suicide outcomes based on current evidence. METHODS: We searched PubMed, Web of Science and Scopus until May 2015. We also searched the reference lists of included studies and Psycinfo website. We included observational (cohort, case-control, cross-sectional) studies addressing the association between SUD and suicide. Our outcomes of interest were suicide ideation, suicide attempt and suicide death. For each outcome, we calculated the odds ratio (OR) or risk ratio (RR) with 95% confidence intervals (CI) based on the random-effects model. RESULTS: = 82.7%, 7 studies). CONCLUSIONS: Based on current evidence, there is a strong association between SUD and suicide outcomes. However, evidence based on long-term prospective cohort studies is limited and needs further investigation. Moreover, further evidence is required to assess and compare the association between suicide outcomes and different types of illicit drugs, dose-response relationship and the way they are used.

Due to global climate change, abiotic stresses are affecting plant growth, productivity, and the quality of cultivated crops. Stressful conditions disrupt physiological activities and suppress defensive mechanisms, resulting in stress-sensitive plants. Consequently, plants implement various endogenous strategies, including plant hormone biosynthesis (e.g., abscisic acid, jasmonic acid, salicylic acid, brassinosteroids, indole-3-acetic acid, cytokinins, ethylene, gibberellic acid, and strigolactones) to withstand stress conditions. Combined or single abiotic stress disrupts the normal transportation of solutes, causes electron leakage, and triggers reactive oxygen species (ROS) production, creating oxidative stress in plants. Several enzymatic and non-enzymatic defense systems marshal a plant's antioxidant defenses. While stress responses and the protective role of the antioxidant defense system have been well-documented in recent investigations, the interrelationships among plant hormones, plant neurotransmitters (NTs, such as serotonin, melatonin, dopamine, acetylcholine, and γ-aminobutyric acid), and antioxidant defenses are not well explained. Thus, this review discusses recent advances in plant hormones, transgenic and metabolic developments, and the potential interaction of plant hormones with NTs in plant stress response and tolerance mechanisms. Furthermore, we discuss current challenges and future directions (transgenic breeding and genome editing) for metabolic improvement in plants using modern molecular tools. The interaction of plant hormones and NTs involved in regulating antioxidant defense systems, molecular hormone networks, and abiotic-induced oxidative stress tolerance in plants are also discussed.

The plasma electrolytic oxidation (PEO) procedure is utilized in order to amend the surface properties of Mg and its alloys. This procedure creates a ceramic coating on the surface applying high-voltage. The presence of deep pores and porosities in the surface that affect the corrosion resistance of the coatings is one of the PEO procedure limitations. One of the useful methods to decrease porosities of coating and improve its final properties is changing electrolyte conditions based on the presence of micro- and nanoparticles. The present paper reviews the mechanisms of particle adsorption and composition in PEO thin films in addition to the effect of particle addition on the microstructure, composition and corrosion behavior of coatings that were applied on magnesium alloys.

This paper presents a framework to tackle combinatorial optimization problems using neural networks and reinforcement learning. We focus on the traveling salesman problem (TSP) and train a recurrent network that, given a set of city coordinates, predicts a distribution over different city permutations. Using negative tour length as the reward signal, we optimize the parameters of the recurrent network using a policy gradient method. We compare learning the network parameters on a set of training graphs against learning them on individual test graphs. Despite the computational expense, without much engineering and heuristic designing, Neural Combinatorial Optimization achieves close to optimal results on 2D Euclidean graphs with up to 100 nodes. Applied to the KnapSack, another NP-hard problem, the same method obtains optimal solutions for instances with up to 200 items.

Abstract Sustainable use of soil resources can be assessed from management‐induced changes in soil properties from long‐term experiments. Such data are scanty, especially with regard to changes in soil physical properties. Therefore, soil physical and chemical analyses were performed 28 yr after initiating a crop rotation‐tillage experiment on a well‐drained Wooster silt loam soil (fine‐loamy, mixed, mesic Typic Fragiudalf) at Wooster, OH. All combinations of three rotations (continuous corn [CC; Zea mays L.]; corn and soybean [ Glycine max (L.) Merr.] in a 2‐yr rotation [CS]; and corn, oat [ Avena sativa L.], and meadow in a 3‐yr rotation [COM]) and of three tillage treatments (no‐tillage [NT]; chisel plow [CP]; and moldboard plow [MP]) were maintained on the same plots for the entire length of study. All crops were grown every year. Soil properties studied for the 0‐ to 15‐cm layer were: structural stability of aggregates, bulk density, total porosity, penetration resistance, organic C, pH, cation‐exchange capacity (CEC), and exchangeable K, Ca and Mg. Mean bulk densities measured prior to tillage treatments and planting were 1.18, 1.24, and 1.28 Mg m −3 for CC, CS, and COM rotations, respectively. The lowest bulk density was observed for the CC‐NT combination. Total aggregation in CS was 26.9% greater than CC and 111.2% greater than COM. With tillage treatments, aggregation was in the order of NT>CP>MP. Rotation treatments had no effect on aggregate size. In accord with bulk density, the relative magnitude of organic C content was 100, 85, and 63 for CC, CS, and COM rotations, respectively.

This paper examined the efficiency of multivariate linear regression (MLR) and artificial neural network (ANN) models in prediction of two major water quality parameters in a wastewater treatment plant. Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) as well as indirect indicators of organic matters are representative parameters for sewer water quality. Performance of the ANN models was evaluated using coefficient of correlation (r), root mean square error (RMSE) and bias values. The computed values of BOD and COD by model, ANN method and regression analysis were in close agreement with their respective measured values. Results showed that the ANN performance model was better than the MLR model. Comparative indices of the optimized ANN with input values of temperature (T), pH, total suspended solid (TSS) and total suspended (TS) for prediction of BOD was RMSE = 25.1 mg/L, r = 0.83 and for prediction of COD was RMSE = 49.4 mg/L, r = 0.81. It was found that the ANN model could be employed successfully in estimating the BOD and COD in the inlet of wastewater biochemical treatment plants. Moreover, sensitive examination results showed that pH parameter have more effect on BOD and COD predicting to another parameters. Also, both implemented models have predicted BOD better than COD.

An anodic oxidation process with graphite anode coated with lead dioxide (G/β-PbO2) was optimized for the degradation of methylene blue (MB) and the treatment of real textile wastewater. The G/β-PbO2 anode was prepared by the electrochemical precipitation method. The scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), and X-ray diffraction (XRD) analyses confirmed the successful coating of graphite substrate with the β-PbO2 film. The effect of four independent variables including pH, reaction time, current density, and electrolyte concentration of Na2SO4 on the performance of the electrochemical oxidation system was modeled by using a complete central composite design and was then optimized by genetic algorithm method. The accuracy of the proposed quadratic model by CCD was confirmed with p-value <0.0001 and adj-R2 > 0.9. The optimum conditions for solution pH, reaction time, current density, and Na2SO4 electrolyte concentration were obtained to be 5.75, 50 min, 10 mA/cm2, and 78.8 mg/L, respectively. In these conditions, the experimental removal efficiencies of MB using G/β-PbO2 and graphite anodes were 96.2% and 68.3%, respectively. The electrochemical removal of MB using both G/β-PbO2 and graphite anodes well followed the pseudo-first-order reaction (R2 > 0.9). Cyclohexane, cyclohexa-2,5-dien-1-ylium, and N-(sec-butyl) aniline were the most abundant intermediates identified by LC-MS analysis. However, the complete mineralization of MB was achieved in 60 min. The optimized anodic oxidation process successfully improved the biodegradability of real textile wastewater (BOD/COD>0.4).

Abstract This study investigated the removal of Cd2+, Cu2+, Ni2+, and Pb2+ from aqueous solutions using nanoparticle sorbents (TiO2, MgO, and Al2O3) with a range of experimental approaches. The maximum uptake values (sum of four metals) with multiple component solutions were 594.9, 114.6, and 49.4 mg g−1, for MgO, Al2O3, and TiO2, respectively. The sorption equilibrium isotherms were described using the Freundlich and Langmuir models. The best interpretation for experiment data was given by the Freundlich model for Cd2+, Cu2+, and Ni2+ in single- and multiple-component solutions. A first-order kinetic model adequately described the experimental data using MgO, Al2O3, and TiO2. SEM-EDX both before and after metal sorption and soil solution saturation indices (SI) in MgO nanoparticles indicated that the main sorption mechanism for heavy metals was attributable to adsorption and precipitation, whereas heavy metal sorption by TiO2 and Al2O3 adsorbents was due to adsorption. These nanoparticles may potentially be used as efficient sorbents for heavy metal removal from aqueous solutions. MgO nanoparticles were the most promising sorbents because of their high metal uptake. Keywords: Aqueous solutionsHeavy metalsNanoparticlesRemoval Notes a Data calculated from the XRD pattern according to the Scherrer equation. b Data from TEM analysis. *mg g−1 min−1. **(mg g−1)−1. a mg g−1.

The homotopy analysis method is employed to examine free convective heat and mass transfer in a steady two-dimensional magnetohydrodynamic fluid flow over a stretching vertical surface in porous medium. In this study thermal radiation and non-uniform magnetic field are taken into consideration. The two-dimensional boundary-layer governing partial differential equations are derived with considering Boussinesq and boundary-layer approximations, and the ordinary differential nonlinear forms of momentum, energy and concentration equations, obtained by the similarity solution, are solved analytically in the presence of buoyancy forces. The effects of different involved parameters such as magnetic field parameter, suction parameter, Prandtl number, buoyancy parameter, Schmidt number, Biot number and radiation parameter on velocity, temperature and concentration profiles are plotted and discussed in the paper.

The pseudo-second-order (PSO) kinetic model has become among the most popular ways to fit rate data for adsorption of metal ions, dyes, and other compounds from aqueous solution onto cellulose-based materials. This review first considers published evidence regarding the validity of the mechanistic assumptions underlying application of the PSO model to adsorption kinetics. A literal interpretation of the model requires an assumption that different adsorption sites on a solid substrate randomly collide with each other during a rate-limiting mechanistic step. Because of problems revealed by the literature regarding the usual assumptions associated with the PSO model, this review also considers how else to account for good fits of adsorption data to the PSO model. Studies have shown that adsorption behavior that fits the PSO model well often can be explained by diffusion-based mechanisms. Hypothetical data generated using the assumption of pseudo-first-order rate behavior has been shown to fit the PSO model very well. In light of published evidence, adsorption kinetics of cellulosic materials is expected to mainly depend on diffusionlimited processes, as affected by heterogeneous distributions of pore sizes and continual partitioning of solute species between a dissolved state and a fixed state of adsorption.

Water-soluble gums (hydrocolloids) are used for various applications as coating agents, packaging films, texture modifiers, thickeners, stabilizers and emulsifiers. Edible coatings are mostly used to increase food products appearance and extending shelf life of the fruits. Several studies have been carried out showing the potential use of natural gums such as chitosan, alginate, xanthan, gellan, mesquite, psyllium, basil seed, guar, tragacanth and arabic gums in edible coatings formulation and improving their properties. This review summarized the characterization of new biodegradable edible coatings based on natural gums on quality and shelf-life of apple, papaya, carrot, guava, plum, mango, apricot, banana, orange, mushroom and tomato. The edible coatings fabricated from natural gums could provide some benefits such as extended shelf life, delaying ripening, decrease the rate of respiration, biocompatibility and environmentally friendly, economically affordable, good mass transfer barrier characteristics, carriers of foods additives such as antioxidants, vitamins and antimicrobial compounds. The addition of 20% glycerol (w/w) to edible coatings solutions containing 1% gum was sufficient to achieve the high reduction of the fruits and vegetables weight loss.

Abstract Evaluation of soil physical properties was conducted on soil sampled in 1990 from long‐term tillage experiments established in 1962 on silt loam soils at Wooster and South Charleston, OH. Tillage treatments included: moldboard plowing (MP), chisel plowing (CP), and no‐till (NT). No‐till treatments had significantly ( P = 0.05) more organic C accompanied by a similar increase of cation‐exchange capacity (CEC) in the 0‐ to 15‐cm layer in both sites than other tillage methods. High bulk density and penetration resistance were measured in the traffic zone (TZ) compared with the row zone (RZ) in the top 15 cm under NT treatments. The mean hydraulic conductivity in NT plots was 12 times more than CP and MP for TZ and 15 times more for RZ. The aggregation percentage and mean weight diameter (MWD) were significantly ( P = 0.05) more in NT compared with other treatments in both zones and sites. The available water‐holding capacity (AWC) was in the order of NT &gt; CP &gt; MP, with significant differences among treatments. The mean AWC in NT plots was 24% more than CP and 23% more than MP for RZ, and 8% more than CP and 11% more than MP for TZ.

Silica sulfuric acid and silica chloride, two silica based solid acids have been used for various organic functional group transformations either as reagent or as catalyst. All reactions have been carried out under mild and heterogeneous conditions. These reagents were used for C-C, C-N, and C-O bond formation and cleavage and also deprotection of different protecting groups. Silica sulfuric acid was recycled in many cases, and reused. Silica chloride has been used as a starting material for preparation of some new silica based reagents with special properties. Keywords: multicomponent reactions (MCRs), 2,3-Dihydroquinazolinone derivatives, carbon-oxygen bonds, oxidation reactions, Nitrosation, Silica Chloride

We establish a new connection between value and policy based reinforcement learning (RL) based on a relationship between softmax temporal value consistency and policy optimality under entropy regularization. Specifically, we show that softmax consistent action values correspond to optimal entropy regularized policy probabilities along any action sequence, regardless of provenance. From this observation, we develop a new RL algorithm, Path Consistency Learning (PCL), that minimizes a notion of soft consistency error along multi-step action sequences extracted from both on- and off-policy traces. We examine the behavior of PCL in different scenarios and show that PCL can be interpreted as generalizing both actor-critic and Q-learning algorithms. We subsequently deepen the relationship by showing how a single model can be used to represent both a policy and the corresponding softmax state values, eliminating the need for a separate critic. The experimental evaluation demonstrates that PCL significantly outperforms strong actor-critic and Q-learning baselines across several benchmarks.

The demand for fossil fuels is increasing because of globalization and rising energy demands. As a result, many nations are exploring alternative energy sources, and hydrogen is an efficient and practical alternative fuel. In the transportation industry, the development of hydrogen-powered cars aims to maximize fuel efficiency and significantly reduce exhaust gas emission and concentration. The impact of using hydrogen as a supplementary fuel for spark ignition (SI) and compression ignition (CI) engines on engine performance and gas emissions was investigated in this study. By adding hydrogen as a fuel in internal combustion engines, the torque, power, and brake thermal efficiency of the engines decrease, while their brake-specific fuel consumption increase. This study suggests that using hydrogen will reduce the emissions of CO, UHC, CO2, and soot; however, NOx emission is expected to increase. Due to the reduction of environmental pollutants for most engines and the related environmental benefits, hydrogen fuel is a clean and sustainable energy source, and its use should be expanded.