Payame Noor University

Purpose Partial least squares structural equation modeling (PLS-SEM) has attracted much attention from both methodological and applied researchers in various disciplines – also in hospitality management research. As PLS-SEM is relatively new compared to other multivariate analysis techniques, there are still numerous open questions and uncertainties in its application. This study aims to address this important issue by offering guidance regarding its use in contexts with which researchers struggle. Design/methodology/approach The authors examine the most prominent questions and answers posed in a well-known PLS-SEM discussion forum. The authors do so by using a text analysis technique to identify the most salient topics. Findings The data analysis identifies three salient PLS-SEM topics (i.e. bootstrapping and significance testing, higher-order constructs and moderation). Research limitations/implications The results allow us to address the PLS-SEM community’s main methodological issues. The authors discuss each area separately and provide explanations and guidelines. Practical implications The guidelines on the most important PLS-SEM topics provide decision-making and application aids. In this way, the authors make a decisive contribution to clarifying ambiguities when applying the PLS-SEM method in hospitality management research and other disciplines. Originality/value There has as yet been no systematic analysis of this kind in the field of PLS-SEM; the authors, therefore, present the first research results. The findings and recommendations provide guidance for PLS-SEM applications in hospitality research and practice.

The aim of this study is to identify important factors influencing organizational readiness to deal with the crisis in business organizations. The study designs a questionnaire in Likert scale and distributes it among some experts who work for Mapna company in Iran. The study uses the method developed by Why some companies emerge stronger and better from a crisis: 7 essential lessons for surviving disaster. AMACOM Div American Mgmt Assn.], which investigates the effects of four factors including job satisfaction, increase in income, cost reduction and change in strategies on crisis management. Using Pearson correlation ratio, the study has confirmed a positive and meaningful relationship between crisis management and three factors including increase in income, cost reduction and change in strategies. However, the study did not find any evidence to support the relationship between job satisfaction and crisis management.

Liposomes provide an established basis for the sustainable development of different commercial products for treatment of medical diseases by the smart delivery of drugs. The industrial applications include the use of liposomes as drug delivery vehicles in medicine, adjuvants in vaccination, signal enhancers/carriers in medical diagnostics and analytical biochemistry, solubilizers for various ingredients as well as support matrices for various ingredients and penetration enhancers in cosmetics. In this review, we summarize the main applications and liposome-based commercial products that are currently used in the medical field.

Hypoxia is a common feature of solid tumors, and develops because of the rapid growth of the tumor that outstrips the oxygen supply, and impaired blood flow due to the formation of abnormal blood vessels supplying the tumor. It has been reported that tumor hypoxia can: activate angiogenesis, thereby enhancing invasiveness and risk of metastasis; increase survival of tumor, as well as suppress anti-tumor immunity and hamper the therapeutic response. Hypoxia mediates these effects by several potential mechanisms: altering gene expression, the activation of oncogenes, inactivation of suppressor genes, reducing genomic stability and clonal selection. We have reviewed the effects of hypoxia on tumor biology and the possible strategiesto manage the hypoxic tumor microenvironment (TME), highlighting the potential use of cancer stem cells in tumor treatment.

A solar cell is an electronic device which directly converts sunlight into electricity. Light shining on the solar cell produces both a current and a voltage to generate electric power. This process requires firstly, a material in which the absorption of light raises an electron to a higher energy state, and secondly, the movement of this higher energy electron from the solar cell into an external circuit. The electron then dissipates its energy in the external circuit and returns to the solar cell. A variety of materials and processes can potentially satisfy the requirements for photovoltaic energy conversion, but in practice nearly all photovoltaic energy conversion uses semiconductor materials in the form of a p-n junction. With regard to the development of sustainable energy, such as solar energy, in this article we will Study types of solar cells and their applications

Among the most challenging problems that human beings appear to face are depleting energy sources and increasing environmental pollutions. Heterogeneous photocatalytic processes are the most rewarding technology to generate renewable energy and degrade environmental pollutants. In these processes, semiconductors are used as photocatalysts. ZnO is a widely used photocatalyst, because of its strong oxidation ability, cost effectiveness, non-toxicity, versatility in synthesis, abundance in nature, and ease of crystallization. However, pure ZnO has some drawbacks, due to its wide band gap, poor solar-light utilization, and rapid recombination of the photoinduced charge carriers. Modification of ZnO using different strategies including coupling with narrow band gap semiconductors, noble metal deposition, surface sensitization by organic dyes, and elemental doping can easily address these shortcomings. In addition, separation of photocatalysts from the treated systems limits their broad applications. Incorporation of photocatalysts in magnetic materials will help their recycling using external magnetic field. This combination leads to a new generation of photocatalysts, known as magnetically separable photocatalysts. The present review provides helpful insights into preparation of magnetically separable photocatalysts based on ZnO and their applications for degradations of different pollutants.

The nature of stock market movement has always been ambiguous for investors because of various influential factors. This study aims to significantly reduce the risk of trend prediction with machine learning and deep learning algorithms. Four stock market groups, namely diversified financials, petroleum, non-metallic minerals and basic metals from Tehran stock exchange, are chosen for experimental evaluations. This study compares nine machine learning models (Decision Tree, Random Forest, Adaptive Boosting (Adaboost), eXtreme Gradient Boosting (XGBoost), Support Vector Classifier (SVC), Naïve Bayes, K-Nearest Neighbors (KNN), Logistic Regression and Artificial Neural Network (ANN)) and two powerful deep learning methods (Recurrent Neural Network (RNN) and Long short-term memory (LSTM). Ten technical indicators from ten years of historical data are our input values, and two ways are supposed for employing them. Firstly, calculating the indicators by stock trading values as continuous data, and secondly converting indicators to binary data before using. Each prediction model is evaluated by three metrics based on the input ways. The evaluation results indicate that for the continuous data, RNN and LSTM outperform other prediction models with a considerable difference. Also, results show that in the binary data evaluation, those deep learning methods are the best; however, the difference becomes less because of the noticeable improvement of models' performance in the second way.

The main characteristics of mobile learning (m-learning) are recognized as the potential for learning process to be personalized, spontaneous, informal and ubiquitous. Although learning through mobile phones may take longer time compared to computers, the learners feel a greater sense of freedom of time and place, so that they can take the advantage of spare time to learn a second language when and where they are.

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTArylglyoxals in Synthesis of Heterocyclic CompoundsBagher Eftekhari-Sis*†, Maryam Zirak‡, and Ali Akbari†View Author Information† Department of Chemistry, Faculty of Science, University of Maragheh, Golshahr, P.O. Box. 55181-83111, Maragheh, Iran‡ Department of Chemistry, Payame Noor University, P.O. Box 19395-3697, Tehran, Iran*E-mail: [email protected]; [email protected]Cite this: Chem. Rev. 2013, 113, 5, 2958–3043Publication Date (Web):January 25, 2013Publication History Received28 April 2012Published online25 January 2013Published inissue 8 May 2013https://pubs.acs.org/doi/10.1021/cr300176ghttps://doi.org/10.1021/cr300176greview-articleACS PublicationsCopyright © 2013 American Chemical SocietyRequest reuse permissionsArticle Views16863Altmetric-Citations309LEARN 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:Addition reactions,Condensation,Cyclization,Heterocyclic compounds,Reaction products Get e-Alerts

We review the paradigm of quintom cosmology. This scenario is motivated by the observational indications that the equation-of-state of dark energy across the cosmological constant boundary is mildly favored, although the data are still far from being conclusive. As a theoretical setup we introduce a no-go theorem existing in quintom cosmology, and based on it we discuss the conditions for the equation-of-state of dark energy realizing the quintom scenario. The simplest quintom model can be achieved by introducing two scalar fields with one being quintessence and the other phantom. Based on the double-field quintom model we perform a detailed analysis of dark energy perturbations and we discuss their effects on current observations. This type of scenario usually suffers from a manifest problem due to the existence of a ghost degree-of-freedom, and thus we review various alternative realizations of the quintom paradigm. The developments in particle physics and string theory provide potential clues indicating that a quintom scenario may be obtained from scalar systems with higher derivative terms, as well as from non-scalar systems. Additionally, we construct a quintom realization in the framework of braneworld cosmology, where the cosmic acceleration and the phantom divide crossing result from the combined effects of the field evolution on the brane and the competition between four- and five-dimensional gravity. Finally, we study the outsets and fates of a universe in quintom cosmology. In a scenario with null energy condition violation one may obtain a bouncing solution at early times and therefore avoid the Big Bang singularity. Furthermore, if this occurs periodically, we obtain a realization of an oscillating universe. Lastly, we comment on several open issues in quintom cosmology and their connection to future investigations.

The prediction of stock groups values has always been attractive and challenging for shareholders due to its inherent dynamics, non-linearity, and complex nature. This paper concentrates on the future prediction of stock market groups. Four groups named diversified financials, petroleum, non-metallic minerals, and basic metals from Tehran stock exchange were chosen for experimental evaluations. Data were collected for the groups based on 10 years of historical records. The value predictions are created for 1, 2, 5, 10, 15, 20, and 30 days in advance. Various machine learning algorithms were utilized for prediction of future values of stock market groups. We employed decision tree, bagging, random forest, adaptive boosting (Adaboost), gradient boosting, and eXtreme gradient boosting (XGBoost), and artificial neural networks (ANN), recurrent neural network (RNN) and long short-term memory (LSTM). Ten technical indicators were selected as the inputs into each of the prediction models. Finally, the results of the predictions were presented for each technique based on four metrics. Among all algorithms used in this paper, LSTM shows more accurate results with the highest model fitting ability. In addition, for tree-based models, there is often an intense competition between Adaboost, Gradient Boosting, and XGBoost.

Due to the vast and inappropriate use of the antibiotics, microorganisms have begun to develop resistance to the commonly used antimicrobial agents. So therefore, development of the new and effective antimicrobial agents seems to be necessary. According to some recent reports, carbon-based nanomaterials such as fullerenes, carbon nanotubes (CNTs) (especially single-walled carbon nanotubes (SWCNTs)) and graphene oxide (GO) nanoparticles show potent antimicrobial properties. In present review, we have briefly summarized the antimicrobial activity of carbon-based nanoparticles together with their mechanism of action. Reviewed literature show that the size of carbon nanoparticles plays an important role in the inactivation of the microorganisms. As major mechanism, direct contact of microorganisms with carbon nanostructures seriously affects their cellular membrane integrity, metabolic processes and morphology. The antimicrobial activity of carbon-based nanostructures may interestingly be investigated in the near future owing to their high surface/volume ratio, large inner volume and other unique chemical and physical properties. In addition, application of functionalized carbon nanomaterials as carriers for the ordinary antibiotics possibly will decrease the associated resistance, enhance their bioavailability and provide their targeted delivery.

BACKGROUND: Nickel ferrite, a kind of soft magnetic materials is one of the most attracting class of materials due to its interesting and important properties and has many technical applications, such as in catalysis, sensors and so on. In this paper the synthesis of NiFe2O4 nanoparticles by the hydrothermal method is reported and the inhibition of surfactant (Glycerol or Sodium dodecyl sulfate) on the particles growth is investigated. METHODS: For investigation of the inhibition effect of surfactant on NiFe2O4 particles growth, the samples were prepared in presence of Glycerol and Sodium dodecyl sulfate. The X-ray powder diffraction (XRD), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR), vibrating sample magnetometer (VSM) and inductively coupled plasma atomic emission spectrometer (ICP-AES) techniques were used to characterize the samples. RESULTS: The results of XRD and ICP-AES show that the products were pure NiFe2O4 and also nanoparticles grow with increasing the temperature, while surfactant prevents the particle growth under the same condition. The average particle size was determined from the Scherrer's equation and TEM micrographs and found to be in the range of 50-60 nm that decreased up to 10-15 nm in presence of surfactant. The FT-IR results show two absorption bands near to 603 and 490 cm-1 for the tetrahedral and octahedral sites respectively. Furthermore, the saturated magnetization and coercivity of NiFe2O4 nanoparticles were in the range of 39.60 emu/g and 15.67 Qe that decreased for samples prepared in presence of surfactant. As well as, the nanoparticles exhibited a superparamagnetic behavior at room temperature. CONCLUSIONS: Nanosized nickel ferrite particles were synthesized with and without surfactant assisted hydrothermal methods. The results show that with increasing of temperature, the crystallinity of nanoparticles is increased. In the presence of surfactants, the crystallinity of NiFe2O4 nanoparticles decreased in comparison with surfactant- free prepared samples. All of the nickel ferrite nanoparticles were superparamagnetic at room temperature. GRAPHICAL

The impacts of climate change on agriculture are still shadowed with uncertainty. However, climate change is expected to adversely affect Iran's agricultural practices through changes in precipitation, temperature and carbon dioxide fertilization. Therefore, adaptation of this sector to the increasing weather events is imperative. This study is aimed to document the likely impacts of climate change on Iran's agriculture and the current adaptation efforts made by government and farmers. The review of literature shows that changes in rainfall and water endowments will have significant impacts on crop yield, crops' water requirements and income and welfare of farm families. The extent of the changes in yield depends on the crop type, assumptions related to the CO2 fertilization effect, climate scenarios and adaptation abilities. On adaptation, the government's efforts have been distinguished in the improving agricultural productivity and irrigation development based on current technology, developing new technologies and policy reforms. Farmers' adaptive responses have also been identified. Some conclusions and recommendations are offered to increase the adaptive capacity of farmers and reduce negative impacts of climate change.

To reveal the integrative biochemical networks of wheat leaves in response to water deficient conditions, proteomics and metabolomics were applied to two spring-wheat cultivars (Bahar, drought-susceptible; Kavir, drought-tolerant). Drought stress induced detrimental effects on Bahar leaf proteome, resulting in a severe decrease of total protein content, with impairments mainly in photosynthetic proteins and in enzymes involved in sugar and nitrogen metabolism, as well as in the capacity of detoxifying harmful molecules. On the contrary, only minor perturbations were observed at the protein level in Kavir stressed leaves. Metabolome analysis indicated amino acids, organic acids, and sugars as the main metabolites changed in abundance upon water deficiency. In particular, Bahar cv showed increased levels in proline, methionine, arginine, lysine, aromatic and branched chain amino acids. Tryptophan accumulation via shikimate pathway seems to sustain auxin production (indoleacrylic acid), whereas glutamate reduction is reasonably linked to polyamine (spermine) synthesis. Kavir metabolome was affected by drought stress to a less extent with only two pathways significantly changed, one of them being purine metabolism. These results comprehensively provide a framework for better understanding the mechanisms that govern plant cell response to drought stress, with insights into molecules that can be used for crop improvement projects.

Introduction. Depression is one of the four major diseases in the world and is the most common cause of disability from diseases. The aim of this study is to estimate the prevalence of depression among Iranian university students using meta-analysis method. Materials and Methods. Keyword depression was searched in electronic databases such as PubMed, Scopus, MAGIran, Medlib, and SID. Data was analyzed using meta-analysis (random-effects model). Heterogeneity of studies was assessed using the I (2) index. Data was analyzed using STATA software Ver.10. Results. In 35 studies conducted in Iran from 1995 to 2012 with sample size of 9743, prevalence of depression in the university students was estimated to be 33% (95% CI: 32-34). The prevalence of depression among boys was estimated to be 28% (95% CI: 26-30), among girls 23% (95% CI: 22-24), single students 39% (95% CI: 37-41), and married students 20% (95% CI: 17-24). Metaregression model showed that the trend of depression among Iranian students was flat. Conclusions. On the whole, depression is common in university students with no preponderance between males and females and in single students is higher than married ones.

The purpose of this study was to investigate the effects of inquiry-based learning method on students’ academic achievement in sciences lesson. A total of 40 fifth grade students from two different classes were involved in the study. They were selected through purposive sampling method. The group which was assigned as experimental group was instructed through inquiry-based learning method whereas the other group was traditionally instructed. This experimental study lasted eight weeks. To determine the effectiveness of inquiry-based learning method over traditional instruction, an achievement test about sciences which consisted of 30 items was administered as pre-test and post-test to students both in the experimental and control groups. For the statistical analysis, Analysis of Covariance (ANCOVA) was used. The results showed that students who were instructed through inquiry-based learning were achieved higher score than the ones which were instructed through the traditional method.

A highly sensitive electrocatalytic sensor was designed and fabricated by the incorporation of NiO dope Pt nanostructure hybrid (NiO-Pt-H) as conductive mediator, bis (1,10 phenanthroline) (1,10-phenanthroline-5,6-dione) nickel(II) hexafluorophosphate (B,1,10,P,1,10, PDNiPF6), and electrocatalyst into carbon paste electrode (CPE) matrix for the determination of cysteamine. The NiO-Pt-H was synthesized by one-pot synthesis strategy and characterized by XRD, elemental mapping analysis (MAP), and FESEM methods. The characterization data, which confirmed good purity and spherical shape with a diameter of ⁓ 30.64 nm for the synthesized NiO-Pt-H. NiO-Pt-H/B,1,10, P,1,10, PDNiPF6/CPE, showed an excellent catalytic activity and was used as a powerful tool for the determination of cysteamine in the presence of serotonin. The NiO-Pt-H/B,1,10, P,1,10, PDNiPF6/CPE was able to solve the overlap problem of the two drug signals and was used for the determination of cysteamine and serotonin in concentration ranges of 0.003-200 µM and 0.5-260 µM with detection limits of 0.5 nM and 0.1 µM, using square wave voltammetric method, respectively. The NiO-Pt-H/B,1,10,P,1,10,PDNiPF6/CPE showed a high-performance ability for the determination of cysteamine and serotonin in the drug and pharmaceutical serum samples with the recovery data of 98.1-103.06%.

In this Letter we consider a correspondence between the holographic dark energy density and Chaplygin gas energy density in FRW universe. Then we reconstruct the potential and the dynamics of the scalar field which describe the Chaplygin cosmology.

Motivation and attitude provide primary impetus to initiate learning language 2 (hereafter L2) and later the driving force to sustain the long and often tedious learning process. Lack of attention to these factors can lead to inefficiencies in learning L2. The research question lying behind this study is: Is there any effective and efficient relationship between language learning and motivation and attitude? This article intends to achieve a main purpose: to provide an overview of recent advances in research on motivation and attitude to learn L2. It provides some implications for better language learning too. In this paper authors have concentrated on descriptive and analytical approaches in order to clarify the role of attitude and motivation in language learning. Authors have achieved practical and tangible findings and have clarified that designing and implementation of various techniques can change student's attitude positively toward L2 learning. Systematic and academic application of “motivation and attitude” issues in language learning classes is very important and can make language courses more interesting.