Islamic Azad University South Tehran Branch

Culture is a way for organizations to learn environmental factors. There are many definitions for culture. “Issue of” difference” with the leader of the director, including material that is much discussed in current and most experts believe that leadership is something different from the management

Brain tumor localization and segmentation from magnetic resonance imaging (MRI) are hard and important tasks for several applications in the field of medical analysis. As each brain imaging modality gives unique and key details related to each part of the tumor, many recent approaches used four modalities T1, T1c, T2, and FLAIR. Although many of them obtained a promising segmentation result on the BRATS 2018 dataset, they suffer from a complex structure that needs more time to train and test. So, in this paper, to obtain a flexible and effective brain tumor segmentation system, first, we propose a preprocessing approach to work only on a small part of the image rather than the whole part of the image. This method leads to a decrease in computing time and overcomes the overfitting problems in a Cascade Deep Learning model. In the second step, as we are dealing with a smaller part of brain images in each slice, a simple and efficient Cascade Convolutional Neural Network (C-ConvNet/C-CNN) is proposed. This C-CNN model mines both local and global features in two different routes. Also, to improve the brain tumor segmentation accuracy compared with the state-of-the-art models, a novel Distance-Wise Attention (DWA) mechanism is introduced. The DWA mechanism considers the effect of the center location of the tumor and the brain inside the model. Comprehensive experiments are conducted on the BRATS 2018 dataset and show that the proposed model obtains competitive results: the proposed method achieves a mean whole tumor, enhancing tumor, and tumor core dice scores of 0.9203, 0.9113 and 0.8726 respectively. Other quantitative and qualitative assessments are presented and discussed.

Coronary artery disease (CAD) is the leading cause of death worldwide and is commonly caused by a constellation of risk factors called the metabolic syndrome. We characterized a family with autosomal dominant early CAD, features of the metabolic syndrome (hyperlipidemia, hypertension, and diabetes), and osteoporosis. These traits showed genetic linkage to a short segment of chromosome 12p, in which we identified a missense mutation in LRP6, which encodes a co-receptor in the Wnt signaling pathway. The mutation, which substitutes cysteine for arginine at a highly conserved residue of an epidermal growth factor-like domain, impairs Wnt signaling in vitro. These results link a single gene defect in Wnt signaling to CAD and multiple cardiovascular risk factors.

A Confounder is a variable whose presence affects the variables being studied so that the results do not reflect the actual relationship. There are various ways to exclude or control confounding variables including Randomization, Restriction and Matching. But all these methods are applicable at the time of study design. When experimental designs are premature, impractical, or impossible, researchers must rely on statistical methods to adjust for potentially confounding effects. These Statistical models (especially regression models) are flexible to eliminate the effects of confounders.

This paper presents an empirical investigation to rank different factors influencing on maintenance strategies on Iranian oil terminals' company. The study determines four main factors, production quality, reliability, cost and safety. Using fuzzy analytical process, the study determines various factors associated with each main factor and ranks them by performing pairwise comparisons. The results indicate that reliability ranks first (0.255), followed by production quality (0.252), cost (0.25) and safety (0.244). In terms of reliability, the best utilization of resources is number one priority followed by increase access to maintenance tools, reduction in production interruption are among the most important issues. In terms of production quality, reduction in system failure as well as reworks is the most important factors followed by customer satisfaction and defects. In terms of cost items, ease of access to accessories and consulting are important factors followed by necessary software, hardware and training programs. Finally, in terms of safety factors, external, internal and employee services are the most important issues, which are needed to be considered.

Developed by OpenAI, ChatGPT (Conditional Generative Pre-trained Transformer) is an artificial intelligence technology that is fine-tuned using supervised machine learning and reinforcement learning techniques, allowing a computer to generate natural language conversation fully autonomously. ChatGPT is built on the transformer architecture and trained on millions of conversations from various sources. The system combines the power of pre-trained deep learning models with a programmability layer to provide a strong base for generating natural language conversations. In this study, after reviewing the existing literature, we examine the applications, opportunities, and threats of ChatGPT in 10 main domains, providing detailed examples for the business and industry as well as education. We also conducted an experimental study, checking the effectiveness and comparing the performances of GPT-3.5 and GPT-4, and found that the latter performs significantly better. Despite its exceptional ability to generate natural-sounding responses, the authors believe that ChatGPT does not possess the same level of understanding, empathy, and creativity as a human and cannot fully replace them in most situations.

Development of biologically inspired green synthesis of silver nanoparticles has attracted considerable worldwide attention in matter of medical science and disease treatment. Herein, the green synthesis of silver nanomaterials using organic green sources has been evaluated and discussed. These kinds of materials are widely used for treatment of antibiotic-resistant bacteria, cancer and etc due to their elegant properties compared with other chemical ways and drugs. Moreover, the outcome of green-based approaches were compared with chemical procedures and obtained data were examined via various analyses including UV-visible spectroscopy, scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDX), transmission electron microscope (TEM), atomic force microscopy (AFM) and Fourier transforms infrared spectroscopy (FT-IR). In this study, variety of green methods were investigated to present a summary of recent achievements toward highlighting biocompatible nanoparticles, all of which can reduce the toxicity of nanoparticles, make them eco-friendly, reduce their side effects and decrease the production cost. The nature of these biological organisms also affect the structure, shape, size and morphology of synthesized nanoparticles.

from the Indus Valley. This process was likely stimulated at the onset of the current geological age, ~4.2 thousand years ago, by a widespread multicentury drought. In contrast to genome-wide admixture, mitochondrial DNA stasis supports that this introgression was male-driven, suggesting that selection of arid-adapted zebu bulls enhanced herd survival. This human-mediated migration of zebu-derived genetics has continued through millennia, altering tropical herding on each continent.

Microgrids with different technologies in distributed generations (DGs), different control facilities and power electronic interfaces require proper management and operation strategies. In these strategies, in order to reach the optimum scheduling, the stochastic nature of some decision variables should be considered. Subsequently, it will lead to a decrease in the forced load curtailment and an increase in the economic efficiency from the perspective of both the maingrid and the microgrid owner. In this study, the availability of dispatchable DGs, energy storage, renewable energy sources (RESs) and the maingrid as well as the power generation of RESs and load are studied through their uncertainty natures. For dealing with these uncertainties, stochastic variables computation module is designed which generates several scenarios by Monte Carlo simulation at each hour. The microgrid operation is optimised in uncertainty environment through a linear two‐stage stochastic model. The stochastic scheduling model which is solved by mixed‐integer linear programming is compared with a deterministic model through three different cases in presence of demand response on a sample microgrid. The results explicitly show benefits of the proposed stochastic model since it provides accuracy in scheduling and decreases the operation cost.

Definition of motivation is the following “Powering people to achieve high levels of performance and overcoming barriers in order to change”. Motivation is the driver of guidance, control and persistence in human behavior. What strengthens a person's behavior? What guides such behaviors or conducts then in a certain direction? What enhanced or maintained the behavior? It is called motivation. On the importance of motivation, researches have shown that employees with high job motivation show, greater commitment to their job; on the other hand Workers who feel more commitment even when things are not moving forward according to the procedure, minimize the impact of this problem.

A new approach to control, stabilization and disturbance rejection of attitude subsystem of quadrotor is presented in this article. Analytical method is used to tune conventional structure of PID controller. SISO approach is implemented for control structure to achieve desired objectives. The performance of the designed control structure is evaluated through time domain factors such as overshoot, settling time and integral error index, and robustness. A comparison is done between designed controller and back-step controller applied to main model of quadrotor. The results of simulation show the effectiveness of designed control scheme.

Electrospinnng is one of the most conventional methods for producing nano fibers in different forms, such as core-shell hollow and porous nanofibers. These forms open new windows on innovative applications for nanofibers like ultra filtration, fuel cells, membranes, tissue engineering, catalysis and drug delivery or release and nanofluidics and hydrogen storage. In the presented paper, developments in the electrospinning method toward fabrication of core-shell, and hollow and porous nanofibers are presented. Different spinnerets like coaxial and side by side are considered. Furthermore, experienced methods for producing these novel fibers, such as Nonsolvent-Induced Phase Separation (NIPS) and phase separation, are described. It is concluded that there is rapid development and achievement in the improvement of nanofibers for new applications, and electrospinning has become a forerunner in this field.

This paper proposes a novel high step-up nonisolated single switch dc-dc converter suitable for regulating dc bus in various microsources especially for photovoltaic (PV) sources. Quadratic boost and switched-capacitor technique are used as primary and secondary circuits, respectively. A coupled inductor is applied to make a connection between them, so a high dc voltage gain is achieved. High efficiency is yield where voltage stress on active switch is alleviated by clamped capacitor; consequently, smaller R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DS(ON)</sub> for power switch is required. On the other hand, input current of the proposed converter is continued, hence stress on the input source is reduced. The operating principles and steady-state analyses are discussed in detail for both continuous and discontinuous conduction modes. Also, the boundary condition is computed. To verify the performance of the proposed converter and theoretical calculations, a 250-W prototype converter is implemented with an input voltage of 24 V and an output voltage of 400 V designed especially for PV sources in continuous conduction mode operation. Finally, simulation results are confirmed by experimental results; maximum efficiency is occurred at 150 W and full-load efficiency is 92.96%.

In this article, we examine the role of environmental quality and economic growth in the determination of health expenditure in the Middle East and North Africa region (MENA) countries for the period 1995–2014 using Autoregressive Distributed Lag (ARDL) method to explore the estimating the impacts of economic growth and environmental quality on heath expenditure. The results show that health expenditure, income, CO2 and PM10 emissions are a cointegrated panel. While long-run elasticities show that income and CO2 and PM10 emissions have statistically significant positive effects on health expenditure. The results show that the income elasticity is inelastic, that health expenditure is not more sensitive to income and the adjustment to changes in income in MENA countries.

Abstract Internet of Things (IoT) creates a world where smart objects and services interacting autonomously. Taking into account the dynamic-heterogeneous characteristic of interconnected devices in IoT, demand for a trust model to guarantee security, authentication, authorization, and confidentiality of connected things, regardless of their functionality, is imperative. However, as far as we know, against the centrality of trust-based recommendation mechanisms in the IoT environment, there is no ambient study for investigating its techniques. In this paper, we present a systematic literature review (SLR) of trust based IoT recommendation techniques so far. Detailed classifications based on extracted parameters as well as investigation existing techniques in three different IoT layers put forth. Moreover, the advantages, disadvantages and open issues of each approach are introduced that can expand more frontier in obtaining accurate IoT recommendation in the future.

Purpose The purpose of this study is to provide reliable and valid constructs of total quality management (TQM) and a measurement instrument in the context of Iranian manufacturing small to medium‐ sized enterprises (SMEs) and to examine the effects of these seven TQM criteria, namely: leadership, process management, supplier, customer focus, employee management, communication and quality information system (QIS) and tools and techniques on the organizational performance of the Iranian manufacturing SMEs. Design/methodology/approach In order to search the impact of TQM practices on Iranian manufacturing SMEs a questionnaire was developed and distributed to quality managers of 65 Iranian manufacturing SMEs, resulting in a response rate of 81.5 percent. In particular, hypotheses were developed to evaluate the impact of TQM implementation on the organizational performance of the manufacturing SMEs. Findings Statistical analysis revealed that a number of significant relationships between TQM practices and organizational performance of the manufacturing SMEs. The result found that leadership plays an important role in enhancing organizational performance of the Iranian manufacturing SMEs; however, these organizations encounter some obstacles in fully utilizing some TQM criteria, namely tools and techniques and suppliers. Research limitations/implications The sample is restricted to only a single region and manufacturing, so it would be strongly recommended that data be gathered from various parts of Iran including both manufacturing and service industries. As the data in this study were collected from top managers of organizations on the basis of their subjective evaluations, objective performance indicators should also be employed in the analysis. Originality/value This study has the potential to enhance the understanding of TQM practices impact on organizational performance of the Iranian manufacturing SMEs amongst researches and practitioners. Also the research adds knowledge in the field of quality management within the context of developing countries and gives a particular focus on the Iran manufacturing SMEs; as a review of literature, has identified no studies that have undertaken a comprehensive analysis of TQM practices and organizational performance of manufacturing SMEs in the Iranian context.

Renewable energies are well-known as one of the most important energy resources not only due to limited other energy resources, but also due to environmental problems associated with air pollutants and greenhouse gas emissions. Renewable energy project selection is a multi actors and sophisticated problem because it is a need to incorporate social, economic, technological, and environmental considerations. Multi criteria decision making (MCDM) methods are powerful tools to evaluate and rank the alternatives among a pool of alternatives and select the best one. COPRAS (COmplex PRoportional ASsessment) is an MCDM technique which determines the best alternative by calculating the ratio to the ideal solution and the negative ideal solution. On the other hand, analytical hierarchy process (AHP) is widely used in order to calculate the importance weights of evaluation criteria. In this paper an integrated COPRAS-AHP methodology is proposed to select the best renewable energy project. In order to validate the output of the proposed model, the model is compared with five MCDM tools. The results of this paper demonstrate the capability and effectiveness of the proposed model in selecting the most appropriate renewable energy option among the existing alternatives.

The study discussed the synthesis of silica sol using the sol-gel method, doped with two different amounts of Cu nanoparticles. Cotton fabric samples were impregnated by the prepared sols and then dried and cured. To block hydroxyl groups, some samples were also treated with hexadecyltrimethoxysilane. The average particle size of colloidal silica nanoparticles were measured by the particle size analyzer. The morphology, roughness, and hydrophobic properties of the surface fabricated on cotton samples were analyzed and compared via the scanning electron microscopy, the transmission electron microscopy, the scanning probe microscopy, with static water contact angle (SWC), and water shedding angle measurements. Furthermore, the antibacterial efficiency of samples was quantitatively evaluated using AATCC 100 method. The addition of 0.5% (wt/wt) Cu into silica sol caused the silica nanoparticles to agglomerate in more grape-like clusters on cotton fabrics. Such fabricated surface revealed the highest value of SWC (155° for a 10-μl droplet) due to air trapping capability of its inclined structure. However, the presence of higher amounts of Cu nanoparticles (2% wt/wt) in silica sol resulted in the most slippery smooth surface on cotton fabrics. All fabricated surfaces containing Cu nanoparticles showed the perfect antibacterial activity against both of gram-negative and gram-positive bacteria.

Abstract In this paper, numerical algorithms for solving “fuzzy ordinary differential equations” are considered. A scheme based on the Taylor method of order p is discussed in detail and this is followed by a complete error analysis. The algorithm is illustrated by solving some linear and nonlinear fuzzy Cauchy problems.

ABSTRACT Many polymeric materials have been developed and introduced for bone regeneration. Especially, their nanofibrous forms are mostly applied for artificial extracellular matrices. Polymeric materials in their nanofibrous form show some potent properties such as high surface‐to‐volume ratio, tunable porosity, and ease of surface functionalization. Benefiting from the properties of their main polymer and additives, they can provide new opportunities for cell seeding, proliferation, and new 3D‐tissue formation. This article focuses on most cited polymeric nanofibrous scaffolds fabricated by electrospinning and recent achievements. They were divided into two main categories: natural (collagen, silk, keratin, gelatin, chitosan, and alginate) and synthetic (e.g., polycaprolactone, polylactic acid, and polyglycolic acid) polymers. The role of several additives like hydroxyapatite, bone morphogenetic proteins (BMPs), tricalcium phosphate, and collagen type I in improving the adhesion, differentiation, and tissue formation of stem cells were discussed. Finally, the osteogenic capacity and ability of nanofibrous scaffolds to support the growth of clinically relevant bone tissue were briefly studied. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133 , 42883.