Annulation and Substitution Reactions Mediated by Cobalt and Scandium Complexes, Respectively

The following dissertation work is generally divided into five main chapters. Besides chapter one (Background) and chapter five (conclusion and future work) Content in chapter two and three have been published in Organometallics and RSC Advances in 2018 and 2020, respectively. Chapter one is a short background of chemistry of ethers and Pauson-Khand reaction. Chapter two mainly focuses on the substitution reactions catalyzed by Scandium and Dimethylaminoprydine for the synthesis of unsymmetrical ethers. In terms of step and atom economy, substitution reactions using catalysts for the synthesis of asymmetrical ethers has been great deal of interest among all research groups. So, we have reported catalytic activation of alcohols using scandium triflate and dimethyl aminopyridine (DMAP) as the ligand for the synthesis of secondary and tertiary alcohols. In chapter four and five the development of the PKR has been reported. Using nitrous oxide as the promoter and arylboronic acid in the reactions enabled us to synthesize new molecular structure from the precursors which have not been reported before in the reaction

Auditor Choice in a Non-Big Market: Evidence on the Role of Ownership Structure

ABSTRACT The operation of both state and private auditors following audit privatization in the Iranian audit market has provided a unique laboratory to investigate auditor choice, whereas prior research studied such issues by comparing Big versus non-Big audit firms. This paper provides empirical evidence concerning the effect of ownership structure (non-state ownership versus state ownership) on auditor choice (private audit firms) based on data from firms listed on the Tehran Stock Exchange between 2002 and 2007. This study finds that compared with state owned enterprises, non-state owned firms are more likely to choose private audit firms. Such a pattern of auditor choice can be explained by the 'auditor-client alignment' argument and the lack of 'collusion incentive'

Changes of hormones (T3, T4 and cortisol) and ions (Na+ , Cl, K+ ) during smoltification in Salmo trutta caspius Kessler 1877

Salmo trutta caspius is an important and economic fish in the Caspian Sea has several morphological and physiological changes during smoltification. In this study, Hormonal (T3, T4 & Cortisol) and ionic (Na+ , Cl & K+ ) changes in the serum were determined during the period of smoltification in 5, 10, 15 & 20g of hatchery reared salmo trutta caspius in different seasons (spring, summer, autumn & winter). Hormones were measured by Eliza and Radio Immuno Assay, Na+ and K+ using flame photometer, Cl by colorimeter. T3 and T4 were quite high in spring, especially in the juvenile of 20g. Cortisol was quite low in spring and summer in all of weight groups. Ionic changes showed no significant differences with weight, but it was significantly different among seasons. This result suggests that analyzing the plasma thyroid hormones and ionic provide useful information about the optimal time of transferring Caspian Sea trout from fresh water to sea water. It is concluded that the juvenile fish of 20g shows a better smoltification process in the spring

\u3cem\u3eIn vitro\u3c/em\u3e Effect of Graphene Structures as an Osteoinductive Factor in Bone Tissue Engineering: A Systematic Review

Graphene and its derivatives have been well‐known as influential factors in differentiating stem/progenitor cells toward the osteoblastic lineage. However, there have been many controversies in the literature regarding the parameters effect on bone regeneration, including graphene concentration, size, type, dimension, hydrophilicity, functionalization, and composition. This study attempts to produce a comprehensive review regarding the given parameters and their effects on stimulating cell behaviors such as proliferation, viability, attachment and osteogenic differentiation. In this study, a systematic search of MEDLINE database was conducted for in vitro studies on the use of graphene and its derivatives for bone tissue engineering from January 2000 to February 2018, organized according to the PRISMA statement. According to reviewed articles, different graphene derivative, including graphene, graphene oxide (GO) and reduced graphene oxide (RGO) with mass ratio ≤1.5 wt % for all and concentration up to 50 μg/mL for graphene and GO, and 60 μg/mL for RGO, are considered to be safe for most cell types. However, these concentrations highly depend on the types of cells. It was discovered that graphene with lateral size less than 5 µm, along with GO and RGO with lateral dimension less than 1 µm decrease cell viability. In addition, the three‐dimensional structure of graphene can promote cell‐cell interaction, migration and proliferation. When graphene and its derivatives are incorporated with metals, polymers, and minerals, they frequently show promoted mechanical properties and bioactivity. Last, graphene and its derivatives have been found to increase the surface roughness and porosity, which can highly enhance cell adhesion and differentiation

Identification of vitellogenin gene expression patterns in liver and ovary of Rutilus frisii kutum exposed to genistein and β-sitosterol

The vitellogenin gene expression can be altered by some estrogenic plant compounds like Genistein and β-sitosterol. Therefore, the measurement of vitellogenin gene expression can be used as an indicator to determine their effect on reproductive performance of aquatic animals. In order to evaluate the effects of genistein and β-sitosterol on the expression of vitellogenin gene in the liver and ovary of Rutilus frisii Kutum, the fish were separately exposed to 3 levels of genistein and beta-sitosterol (500, 50 and 10 ng/L). After 21 days, the RNA extracted and expression of vitellogenin gene in both the liver and ovary was investigated by Real-time PCR. The results showed the level of vitellogenin gene expression in fish exposed to genistein was higher in liver than control and β-sitosterol treatment. This difference was not observed in the ovarian tissue. Because the main site of vitellogenin synthesis expressed liver and it was controlled by endogenous estrogen (E2), so, it seems phytoesterogenic compound such as genistein has been able to increase the relative expression of this gene in fish Exposed to 500 mg/L

Improving the performance of mechanical stirring in biogas plant by computational fluid dynamics (CFD)

Stirring of material in biogas plant needs to be done to provide desirable contact between microorganisms and substrate which can improve digestion process. In the present study, computational fluid dynamics (CFD) was used to determine a suitable mechanical stirrer for biogas plant and simulate the flow pattern. In order to select optimum design of impeller, three types of impeller including six-blade turbine, four-blade turbine and six-flat-blade disc turbine were evaluated. Simulations were undertaken utilizing Fluent 15.0 software with a multiple reference frame approach via standard k-ε turbulence model under steady-state conditions. According to the simulation results, six-blade turbine impeller is more appropriate than the two other impellers. The results further indicated that, this type of stirrer offers suitable mixing both at the center and on the lateral walls of the reactor, reducing dead spaces and improving mass and heat transfers inside the reactor

Integrating Experimental and Computational Approaches to Optimize 3D Bioprinting of Cancer Cells

A key feature distinguishing 3D bioprinting from other 3D cell culture techniques is its precise control over created structures. This property allows for the high-resolution fabrication of biomimetic structures with controlled structural and mechanical properties such as porosity, permeability, and stiffness. However, for bioprinting to be successful, a comprehensive understanding of cell behavior is essential, yet challenging. This includes the survivability of cells throughout the printing process, their interactions with the printed structures, and their responses to environmental cues after printing. There are numerous variables in bioprinting which influence the cell behavior, so bioprinting quality during and after the procedure. Thus, to achieve desirable results, it is necessary to consider and optimize these influential variables. So far, these optimizations have been accomplished primarily through trial and error and replicating several experiments, a procedure that is not only time-consuming but also costly. This issue motivated the development of computational techniques in the bioprinting process to more precisely predict and elucidate cells’ function within 3D printed structures during and after printing. During printing, we developed predictive machine learning models to determine the effect of different variables such as cell type, bioink formulation, printing settings parameters, and crosslinking condition on cell viability in extrusion-based bioprinting. To do this, we first created a dataset of these parameters for gelatin and alginate-based bioinks and the corresponding cell viability by integrating data obtained in our laboratory and those derived from the literature. Then, we developed regression and classification neural networks to predict cell viability based on these bioprinting variables. Compared to models that have been developed so far, the performance of our models was superior and showed great prediction results. The study further demonstrated that among the variables investigated in bioprinting, cell type, printing pressure, and crosslinker concentration, respectively, had the most significant impact on the survival of cells. Additionally, we introduced a new optimization strategy that employs the Bayesian optimization model based on the developed regression neural network to determine the optimal combination of the selected bioprinting parameters for maximizing cell viability and eliminating trial-and-error experiments. In our study, this strategy enabled us to identify the optimal crosslinking parameters, within a specified range, including those not previously explored, resulting in optimum cell viability. Finally, we experimentally validated the optimization model's performance. After printing, we developed a cellular automata model for the first time to predict and elucidate the post-printing cell behavior within the 3D bioprinted construct. To improve our model, we bioprinted a 3D construct using cell-laden hydrogel and evaluated cellular functions, including viability and proliferation, in 11 days. The results showed that our model successfully simulated the 3D bioprinted structure and captured in-vitro observations. The proposed model is beneficial for demonstrating complex cellular systems, including cellular proliferation, movement, cell interactions with the environment (e.g., extracellular microenvironment and neighboring cells), and cell aggregation within the scaffold. We also demonstrated that this computational model could predict post-printing biological functions for different initial cell numbers in bioink and different bioink formulations with gelatin and alginate without replicating several in-vitro measurements. Taken all together, this thesis introduces novel bioprinting process design strategies by presenting mathematical and computational frameworks for both during and after bioprinting. We believe such frameworks will substantially impact 3D bioprinting's future application and inspire researchers to further realize how computational methods might be utilized to advance in-vitro 3D bioprinting research

Diseño de un seguro de ingresos de toda la granja para cultivos agrícolas en la provincia de Zanjan de Irán

[EN] The purpose of this article is to design and empirically evaluate the Whole Farm Insurance (WFI) over the conventional insurance programs in Zanjan province of Iran. Historical farm-level and county-level data were used to estimate yield and price density functions. Both parametric and non-parametric methods were applied for predicting the future values and the PQH simulation method was utilized to calculate premium rates. Results revealed that loss ratios of the WFI are lower for farmers who insured more than one crop. Additionally, utilizing WFI reduces premiums. Moreover, premiums obtained from nonparametric method are relatively lower compared to the parametric approach.[ES] El propósito de este artículo es diseñar y evaluar empíricamente el Seguro Agrario Integral (SAI) con respecto a los programas de seguros convencionales en la provincia de Zanjan de Irán. Se usaron datos históricos a nivel de explotación y de comarca para estimar las funciones de rendimiento y de densidad de precios. Se aplicaron métodos paramétricos y no paramétricos para predecir los valores futuros y se utilizó el método de simulación SAI para calcular las tasas de primas. Los resultados revelaron que los índices de pérdida del SAI son más bajos para los agricultores que aseguraron más de un cultivo. Además, la utilización del SAI reduce las primas. Las primas obtenidas del método no paramétrico son relativamente más bajas en comparación con el enfoque paramétrico.Ghahremanzadeh, M.; Mohammadrezaei, R.; Dashti, G.; Ainollahi, M. (2018). Designing a whole-farm revenue insurance for agricultural crops in Zanjan province of Iran. Economía Agraria y Recursos Naturales - Agricultural and Resource Economics. 17(2):29-53. doi:10.7201/earn.2017.02.02SWORD295317

Controlador híbrido robusto basado en red neuronal fuzzy de intervalo tipo 2 y modo deslizante de alto orden para robots manipuladores

Industrial arms should be able to perform their duties in environments where unpredictable conditions and perturbations are present. In this paper, controlling a robotic manipulator is intended under significant external perturbations and parametric uncertainties. Type-2 fuzzy logic is an appropriate choice in the face of uncertain environments, for various reasons, including utilizing fuzzy membership functions. Also, using the neural network (NN) can increase robustness of the controller. Although neural network does not basically need to build its type-2 fuzzy rules, the initial rules based on sliding surface of higher order sliding mode controller (HOSMC) can improve the system's performance. In addition, self-regulation feature of the controller, which is based on the existence of the neural network in the central type-2 fuzzy controller block, increases the robustness of the method even more. Effective performance of the proposed controller (IT2FNN-HOSMC) is shown under various perturbations in numerical simulations.Los brazos industriale deben poder realizar sus tareas en entornos donde existen condiciones y perturbaciones impredecibles. En este artículo, el control de un manipulador robótico está bajo perturbaciones externas significativas e incertidumbres paramétricas. La lógica difusa de tipo 2 es una opción adecuada frente a entornos inciertos, por varias razones, incluida la utilización de funciones de membresía difusas. Además, el uso de la red neuronal (NN) puede aumentar la robustez del controlador. Aunque la red neuronal no necesita básicamente construir sus reglas difusas tipo 2, las reglas iniciales basadas en la superficie deslizante del controlador de modo deslizante de orden superior (HOSMC) pueden mejorar el rendimiento del sistema. Además, la función de autorregulación del controlador, que se basa en la existencia de la red neuronal en el bloque central del controlador difuso tipo 2, aumenta aún más la robustez del método. El rendimiento efectivo del controlador propuesto (IT2FNN-HOSMC) se muestra bajo varias perturbaciones en simulaciones numéricas

Internet of Things (IoT) and the Energy Sector

Integration of renewable energy and optimization of energy use are key enablers of sustainable energy transitions and mitigating climate change. Modern technologies such the Internet of Things (IoT) offer a wide number of applications in the energy sector, i.e, in energy supply, transmission and distribution, and demand. IoT can be employed for improving energy efficiency, increasing the share of renewable energy, and reducing environmental impacts of the energy use. This paper reviews the existing literature on the application of IoT in in energy systems, in general, and in the context of smart grids particularly. Furthermore, we discuss enabling technologies of IoT, including cloud computing and different platforms for data analysis. Furthermore, we review challenges of deploying IoT in the energy sector, including privacy and security, with some solutions to these challenges such as blockchain technology. This survey provides energy policy-makers, energy economists, and managers with an overview of the role of IoT in optimization of energy systems.Peer reviewe