The ability of companies in determining suitable financial policies to make investment opportunities is one of the most principal factors for the companies' growth and progression. Adopting a debt policy or a capital structure is considered as a momentous decision that influences the companies' value. This paper is aimed to investigate the probable relationship between debt policies (including Current Debt, Non-Current Debt, and Total Debt) and performance of Tehran Stock Exchange Companies. The regression model is applied to investigate the relationship between the performance indicators and debt ratios. In this research, financial performance indicators are considered as Gross Margin Profit, Return on Assets (ROA), Tobin's Q Ratio, and Debt Ratios (Current Debt, Non-Current Debt, and Total Debt). "size" and "growth rate" are considered as control variables. Results show that an increase in current debts, non-current debts, and total debts has a negative influence on the corporate performance. It was also found that companies that merely attempt to create assets through debts, without any attention to the company size and other important factors, are not able to have an excellent performance.

The paper's aim is that how the electronic system is able to transmit the message and is considered as an advertising tool, influencing factors on consumer's behavioral response should be identified in order to use this media desirably, effectively, and utilize the e-advertising advantages to satisfy consumers' needs. This is a research an applied research and a descriptive one with field studies. There are some casual relationships among the research variables. A questionnaire is used to collect data. This study aims to designing, validating, and evaluating a model which explains the influence of e-advertising on consumer behavior as well as providing strengths and weaknesses of the model and suggesting solutions to enhance strengths and converting weaknesses to strengths. In this paper, capabilities of internet advertising are examined in a form of 14 content and communicate motives via a leading process (cognition, affection, and attitude) on consumer's behavioral response (image and mentality, intention and desire, testing, purchasing and consuming) as "an e-advertising model" in Tehran Refah Chain Stores. Results show a suitability of the fitted structural model. The above mentioned company, however, should improve its website's capability in content and communicate motives. In this way, internet advertisings of Refah Chain Store's are able to have a desirable effectiveness in order to lead the consumer behavior.

Latest innovations in Internet of Things (IoT) technologies as well as the new paradigms in Artificial Intelligence systems are opening up opportunities to create smart computing infrastructures for the Healthcare Facility Management. However, the current scenario of hospital buildings maintenance management is strongly characterized by slow, redundant, and not integrated processes, which lead to loss of money, resources, and time. On the other hand, lack of data and information in as-built digital models considerably limits the potential of Building Information Modelling in Facility Maintenance Management. Consequently, optimization of data collection process and management is required. In this light, this paper presents a review of embedding AI (Artificial Intelligence) in BIM-IoT integration for the process of healthcare Facility Maintenance Management (FMM) in order to conquer the current challenges. The first challenge in front of integrating IoT– BIM, is the lack of information; the second challenge is BIM’s sematic information that has not been able to display indoor conditions’ elements which should be reconsidered; and the third challenge is the data size which is stored in systems as well as the eligibility of individuals to apply the related data. Additionally, some emerging trends in IoT are reviewed such as the combination of Machine Learning and Artificial Intelligence in order to exploit their advantages and complement their limitations, which enable new promising IoT applications.