Nowadays, with the growing use of AFM (Atomic Force Microscope) nanorobots in the fabrication of nanostructures, research in this area has been proliferated. The major limiting of manipulation process is the lack of real-time observation. Computer simulations have been widely applied to improve the feasibility of the process. The existing 2D strategies are incapable of presenting the feasibility of the process. Therefore, 3D simulations of effective forces during the manipulation process and the control mechanism of the process have been presented in this research, where the effective parameters are investigated. To evaluate the validity of the presented results, a FEM simulation is proposed. It is observed that the two sets of results (the analytical method and the finite element approach) have adequate correlation, while the discrepancy which is in an acceptable range, is due to the different solving technique of the finite element method. By applying the presented models, it is now possible to accurately predict the effective forces for fabricating the nanostructures.

Purpose: The aim of this study is to report a successful management of a sever nonspecific chronic low back pain relating to visceral stiffness and altered respiratory pattern. Clinical Findings: A 33-year-old female with nonspecific low back pain, with abnormal visceral stiffness, pain in the right abdominal side, pain and tenderness in areas of pelvic and respiratory diaphragms and inability in diaphragmatic breathing. Pain severity was reported as 10 based on VAS. MRI findings showed intervertebral disc protrusion at L5-S1 level. Diagnosis: Pain derived from visceral spasms. Management: Four sessions of visceral manipulation with diaphragmatic breathing exercises and general stretching exercises. Results: At the end of 1st session, the pain severity was improved for 80%, at the end of 2nd session the patient was able to perform perfect diaphragmatic breathing and pain severity was reported 3 based on Visual Analogue Scale (VAS). After 3rd session, pain was felt only at the time of wake up.

Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature selection is a common approach to tackle this issue by choosing prominent features. Multi-label feature selection is an NP-hard approach, and so far, some swarm intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.

Managers accomplish earning management through real earning manipulation and accrual earning manipulation. Accomplishment of both options of earnings management has relative restrictions and relative costs. The problem is whether earning management choices accomplish simultaneously or one option accomplished before another. Therefore, the aim objective of this paper is to determine the substitutive relation between earning management choices (i.e. real earning management and accrual management). For hypothesis test in this study, data for 117 listed companies on Tehran Stock Exchange for period of 1380–1388 is used. To test research hypotheses, Hausman test and multiple regression model approach is applied. The results of this research indicate a substitutive relation between accrual earning management and real earning management. Also the results indicate that managers determine real earning management before accrual earning management.

ObjectiveFinding and choosing healthy food products is one of the main challenges that consumers face when buying these types of products. In recent years, different types of diseases such as obesity and overweight, and cardiovascular diseases have become prevalent in different societies. The appropriate choice and consumption of healthy food products can have an effective role in preventing these types of diseases. Nutrition labels are among the visual labels that can help consumers in finding and choosing healthy food items and increasing consumers’ health. Previous studies have shown that motivational mechanisms can influence attention to nutrition labels. One of these motivational mechanisms is creating a fit between the regulatory focus and the purchasing strategy of consumers. According to Regulatory Focus Theory, individuals have either a promotion (achieving positive events) or a prevention (avoiding negative events) focus. Accordingly, Regulatory Fit Theory indicates that creating a fit between the regulatory focus and the strategy towards obtaining a specific goal can increase motivation and encourage one to pursue the related goal. This study investigates the effect of a regulatory fit between the regulatory focus and purchasing strategy on consumers' visual attention to nutrition labels. In other words, the study aims to examine the simultaneous effect of regulatory focus and the goal of healthy food purchasing by aligning these two factors with each other. The study is novel because no studies to date have investigated the effect of a regulatory fit between an individual's regulatory focus and purchasing strategy on the level of visual attention to nutrition labels. In this research, this issue is investigated for the first time using a lab experiment with the eye-tracking technique. MethodologyThis study is quantitative and uses a laboratory experiment. It has a 2 × 2 factorial design with two independent variables, including regulatory focus (2 levels: promotion or prevention) and purchasing strategy (2 levels: trying to buy healthy food products or avoiding buying unhealthy food products). In total, 67 individuals participated in the study. At first, they read and signed their consent forms. After that, they were randomly assigned to one of the four experimental conditions, including two fit and two non-fit conditions. Then, participants’ regulatory focus and purchasing strategies were manipulated using standard techniques in the related literature. After that, participants went through an online shopping experience in which they had to select products based on their assigned purchasing strategies related to the level of product healthiness (promotion versus prevention purchasing strategy). During this online shopping, their eye movements were tracked using a screen-based eye-tracking device. Finally, participants answered a set of demographic questions. Data were collected in the Business Research Laboratory at the Faculty of Management, the University of Tehran, and were analyzed using the Univariate Analysis of Variance (ANOVA) in SPSS software. Visual attention was measured by five measures (time to first fixation, fixation duration, fixation count, visit duration, and visit count). FindingsIn the regulatory fit conditions, including the two conditions of prevention—avoiding buying unhealthy food products—and promotion—trying to buy healthy food products—visual attention to nutrition labels increased. Regulatory fit is influential in visual attention and increases consumers' focus on nutrition labels. ConclusionBy creating a fit between regulatory focus and purchasing strategy, we can increase visual attention to nutrition labels and improve the rate of healthy food purchasing.

Public confidence in the fairness of stock markets increases their efficiency and liquidity. Manipulating stock market destroys its coherence and decreases public confidence about the authenticity of the market. manipulation of market leads to false and nominal prices and creates misleading appearance of market activity trend.To support the capital market investors, legal systems principally banned manipulation of stock market and have set penalty.Elements of market manipulation crime and prescribed penalties are different in different legal systems with the approval of stock market law in 2005 and according to Article 46 of this law, manipulation of stock market was considered a crime and its punishment was determined.