Introduction: Long-term clinical evaluation of dental implants and their surrounding structures is of utmost importance to acquire knowledge about reasons for implant success and failure.However, accurate and reproducible results are difficult to obtain. The aim of the present study was to examine bone height around endosseous implants on digital conventional radiographs (DCR) and direct digital subtraction images (DSI) prior to loading.Materials and methods: In this experimental study, bone height around 10 implants in 6 patients was assessed by 2 observers. Standardized digital radiographs were obtained just a week and 3 months postoperatively and subtracted by means of EMAGO software. Then the observers evaluated bone height on DCRs and DSIs. MINITAB software and paired t-test were used for statistical analysis (a=0.05).Results: Comparative evaluation of bone height indicated significantly higher values on DCR than on DSI (p value=0.002). The observers also had statistically significant variability in this assessment (p value=0.00003).Conclusion: DSI demonstrated lower values of linear measurement of bone height around endosseous implants compared with DCR. Interobserver variability should be considered when comparing values from follow-up studies.

With the introduction of Bitcoin in 2008, a revolution was created in coins, which led to the presentation of a wide range of digital currencies and drew the attention of all financial market participants to the digital currency market. In the meantime, some beginner investors bought and sold them imitating professional investors and caused a herd behavior. The purpose of this study is to investigate herd behavior in the digital currency market. Considering the important role of herd behavior in the digital currency market and its effect on the price of cryptocurrencies, this study focuses on mass behavior in digital currency markets, because this herd behavior causes the direction of the market to change, so for the trader and investors, it is important for what reasons this herd behavior occurs. Bitcoin has been the largest cryptocurrency invested over the past decade, and mass phenomena in cryptocurrency markets are largely attributed to its price volatility. The data analysis method is linear regression, and the statistical population is currently the top 500 cryptocurrencies based on the project. In this research, the sample of top 200 cryptocurrencies based on their market value in the digital currency market, which have the greatest impact on the market and cause herd behavior in the digital currency market is selected. The method of collecting data is the library method, by checking the Coin Market Cap website and Latin articles. Cross-sectional absolute standard deviation (CSAD) is used to test the research hypotheses. The results of the research show that the intensity of herd behavior in the bull market is higher than in the bear market, and there is also herd behavior in the cryptocurrency bull market. The contribution of this research is to help traders and investors in the financial markets, in their decisions. This research can be of great help to traders and investors when deciding to enter and exit bull and bear markets.

In recent years, digital currencies have attracted many investors. Bitcoin is one of those digital currencies that are considered to be trading more than other currencies. A review of Bitcoin prices is indicative of fluctuations in this market, which increases probability of existing bubble. In this regard, using the monthly data for the period from 08/2013 to 01/2018, the bubble of this market and the single or multiple type of bubbles were investigated. The method used in this study is A recursive unit root test, which was used in the form of SADF, RADF and GSADF tests. Based on the RADF test, there were four bubble periods (March 2015-April 2015, Decembar 2015-March 2016, July 2016-January 2017, September 2017-not disappeared) that had single structures. Based on the SADF test, there was a continuous long bubble period (August 2016-not disappeared), which has a single structure and has not yet exploded. Finally, based on the GSADF test, there were three bubble periods (March 2015-May 2015, Decembar 2015-March 2016, July 2016-not disappeared), that two first bubbles have same structure (March 2015-May 2015, Decembar 2015-March 2016) and the third one has multiple structure (July 2016-not disappeared).

Directive 790/2019 on Copyright and Related Rights in the Digital Single Market is the latest regulation in the field of intellectual property law to be adopted and recently implemented in the European region. These regulations are based on a new legal regime that introduces certain components in the field of intellectual property. In this regime, data mining and educational use in the form of limitations or exceptions with a narrow domain in the context of the digital environment and the right to news is provided for press publishers, in addition to online sharing service providers are required to fulfill obligations to filter works. Right holders will also have the authority to modify their contracts and exercise the right to withdraw literary and artistic works. The important question is what the components of the new system are. And what assessment can be made of the nature of the regulations? The present paper concludes with a descriptive-analytical method that in the new regime, a liability-based regime has been established for the basis of specific legal entities in order to establish limitations and exceptions and control the use of works in parallel with the implementation of some intellectual property law provisions. It could soon serve as a model for other countries regulations, although the added value of new exceptions will not be widespread in the consumer community.

Digital marketing serves as a tool for accessing real estate properties aligned with sustainable development goals, and the use of up-to-date technologies in this sector is a key driver of success for digital marketing in the sustainable real estate industry. Therefore, it is essential to consider the technological dimension along with other dimensions in real estate evaluation models consistent with sustainable development objectives. Accordingly, the present study was designed with the aim of explaining the criteria influencing the sustainable digital real estate market. The research employed a mixed-methods approach (qualitative–quantitative). In the qualitative phase, the thematic analysis technique was applied, while in the quantitative phase, the path analysis technique was used to identify the criteria affecting the sustainable digital real estate market. The qualitative research population consisted of all articles, scientific reports, and theses related to factors influencing the sustainable digital real estate market. The quantitative research population comprised experts and specialists in sustainable digital marketing and the digital real estate market. The sampling method in the qualitative phase was the snowball technique, classified as a non-probability and theoretical sampling method, whereas in the quantitative phase, a simple random stratified sampling method was employed. Due to the unknown size of the statistical population, the sample size was determined to be approximately 380 individuals based on Morgan’s table. The data collection tools consisted of note-taking in the qualitative phase and a researcher-made questionnaire aligned with the study objective in the quantitative phase. Data were gathered through interviews. Data analysis was conducted by the researcher using SPSS software, version 23, as needed. Based on the results, the formation of a digital real estate market significantly leads to the development of variables such as customer–seller–real estate agent interactions, enhancement of customer awareness regarding properties, environmental justice, and economic growth through reduced advertising costs, ultimately resulting in the creation of an optimal real estate market.

Background & Aim: The majority of carious lesions are not well-defined radiolucencies. Approximately 40% demineralization is required for radiographic detection of a lesion. The actual depth of penetration of carious lesion is deeper than may be detected radiographically. However, digital subtraction images permit to detect 1-5% decrease of mineral mass per unit volume. The goal of the present study was to evaluate the accuracy of digital subtraction radiography in the detection of dental demineralization in vitro.Methods & Materials: This study was based on observational-diagnostic method which was done on 30 extracted human teeth, categorized in two groups A and B, each having 15 members. In each of teeth, one approximal enamel demineralization lesion was induced using an acidified system (PH=4.8). Direct digital radiography were obtained under standardized condition of teeth before demineralization. After 7 days, the teeth of group B and after 42 days, group A removed from acid and new radiographs were taken. The images of the 7th and 42nd days were subtracted from the baseline radiograph (before creation of the lesion). Then teeth were histologically evaluated. Direct digital and subtraction images were interpreted by three observers to detect presence or absence of the lesion, then the diagnostic accuracy of both methods was determined.Results: After 7 days, the sensitivity, specificity, accuracy, positive predictive value and negative predictive value for incipient lesions in direct digital radiography were 0%, 80%, 40%, 0% and 44% respectively and in digital subtraction radiography were 66.7%, 86.7%, 76.7%, 83.4% and 72.3% respectively. However after 42 days the sensitivity, specificity and accuracy of both methods were 100%.Conclusion: Digital subtraction radiography has a fairly acceptable accuracy in detection ofthe incipient proximal lesions in comparison with DDR. For moderate proximal lesions DSR has the same accuracy as DDR.