The earthquakes in Makran and Oman sea and the historical Tsunamies such as one that happened on 27 November 1945 in Makran coast are main reasons for insecurity because of Tsunamie's wave affected in the mentioned area. Also the geophysical interpretation supports this fact. Because of various seismic in this region; it is divided into two areas in this research.The data of earthquakes were used in the current century and historical earthquakes to estimate the Gutenberg–Rishter parameters and the earthquake cycle (recurrence intervals).The distribution of seismic energy released have been drown and analysed. By depth information, slop state of deposit has been analysed and the speed of Tsunami in different places in comparison with different depths of Oman sea has been evaluated. Landslide possibility and height of Tsunamie's wave have been compared in different coast of the Oman sea.

This research attempts to assess the history of tsunami occurrences and potential for tsunami generation at the southern coasts of Iran bordering the Indian Ocean by providing a list of historical tsunamis in this region and also, modeling of phases of tsunami generation and propagation. After the December 2004 mega-tsunami in the Indian Ocean, wide efforts were devoted to assess hazard of tsunami, and to develop tsunami warning and mitigation systems in the region. To assess the hazard of tsunami in any particular region, the compilation of historical records of tsunami is always the first primary task. Such a list may lead to useful information about the return period of tsunami events, and most vulnerable coastlines to the impact of possible tsunami. Regarding this fact, in the framework of this study, the first list of Makran historical tsunamis is provided. The Makran zone is located offshore Iran and Pakistan and any tsunami in this region would affect coastlines of Iran, Pakistan, Oman, and India. The last major tsunami in this region was produced following the occurrence of an 8.1 magnitude earthquake which took the lives of at least 4000 people all over the Makran coasts. Also, in this research, the potential for tsunami generation in the Makran subduction zone is quantitatively estimated through modeling of tsunami generation phase. In this regard, based on Mansinha and Smylie (1971) formulas a computer program has been developed to predict the ocean floor deformation due to the occurrence of underwater earthquakes in subduction zones. After the verification of model results, it has been employed to predict possible ocean floor deformation after the occurrence of underwater earthquake in the Makran subduction zone. Tsunami generation analysis shows that the risk of tsunami generation from Makran subduction zone can be classified into three main categories, as follows: (1) very little risk for tsunami generation in the case of occurrence of an earthquake having magnitude up to 7; (2) little to medium risk (Magnitude ranging 7 to 7.5); and (3) high risk (Magnitude greater than 7.5). In the next section of the paper, the tsunami propagation in the Makran zone was modeled. The results of tsunami propagation indicate that in the case of tsunami production in this region, the first tsunami waves will hit the nearest shoreline within 15 to 20 minutes. Finally, considering tsunami hazard assessment performed in this paper, the necessity for the development of a tsunami warning system in southern coasts of Iran was emphasized and its components and orderly sequences of tasks are proposed.

Today, the world has reached a new nature with advances in science. The Internet of Things is a technology that can connect all objects in different fields through the Internet. Some unforeseen event that destroys economic, social and physical capabilities and inflicts human and financial losses is known as a natural disaster, such as a tsunami. IoT-based tsunami forecasting system is an IoT smart device that acts as a tsunami alert and monitoring system and has the ability to communicate via the Internet. Therefore, it is necessary to conduct studies and research in the field of tsunami management with the approach of minimizing financial and human losses. In this study, first the tsunami is described and some IoT applications for tsunami detection are introduced, then the challenges of IoT-based algorithms used for the tsunami warning system are pointed out. It is hoped that tsunamis will be predicted early in the not-too-distant future and that tsunami detection, crisis management will be reduced using the Internet of Things.

In this research, based on the long wave theory, a computer program has been developed to predict propagation pattern and Tsunami travel times for the Iranian southern shorelines. As there is a high risk of Tsunami at the southern coasts of Iran, it is necessary to develop a Tsunami warning system for this region. In this regard, predicting the Tsunami propagation pattern and calculating its travel times are among the most basic information required to develop a Tsunami warning system. In this context, after verification of the developed model, it was exploited for the Iranian southern coastlines. The results indicate that in the case of Tsunami production in this region, the first Tsunami waves will hit the nearest shoreline within 15 minutes. Such a short arrival time necessitates adoption of a Tsunami warning system which should be able to produce warnings within 15 minutes. Results and methods presented in this paper can be employed to develop a database of Tsunami travel times for the Iranian southern coasts, which is the most basic information required to develop a Tsunami warning system.

After the 26 December 2004 mega-tsunami in the Indonesia coastlines, wide efforts were devoted to assess the hazard of tsunami, and to develop tsunami warning systems in the Indian Ocean basin. Based on these efforts, two main tsunamigenic sources that can trigger tsunami-generating earthquakes in the Indian Ocean basin have been identified as the Indonesian subduction zone in the east and the Makran subduction zone (MSZ) in the north of the Indian Ocean. MSZ is located off the southern coasts of Iran and Pakistan in the northwestern Indian Ocean and any possible tsunami from this zone has the potential to affect Iran, Oman, Pakistan, and India. The last major historical earthquake and tsunami in the MSZ occurred on 28 November 1945 killing more than 4,000 people along the Makran coast. Therefore, considering the hazard of tsunami in southern coasts of Iran bordering the Indian Ocean, in this study the potential for tsunami generation in this region has been investigated using modeling of tsunami generation phase. In this regard, a computer program based on Mansinha and Smylie (1971) formula has been developed to predict the seafloor deformation due to underwater earthquake occurrence. The results obtained here show that the risk of tsunami generation from MSZ can be classified into three main categories, as follows: (1) very little risk for tsunami generation in the case of occurrence of an earthquake having magnitude up to 7;(2) little to medium risk (Magnitude ranging 7 to 7.5);and (3) high risk (Magnitude greater than 7.5). At the end of the paper, considering the results of our tsunami hazard assessment, the necessity for development of a tsunami warning system for southern coasts of Iran is emphasized and the structure, components, and mechanism of such a system is presented.

Oral hygiene entails cleaning the teeth and the oral cavity to prevent gingival diseases, periodontitis, and halitosis. Oral hygiene measures are necessary and inevitable for everyone throughout life. Halitosis is a medical and social problem in all communities. 1 Halitosis is defined as a malodor that mainly originates from the oral cavity, which might occur when an individual has poor oral hygiene. 2 One reason for toothbrushing is to avoid oral malodor during social interactions, indicating the importance of observing oral hygiene measures. 3 Wearing a mask is mandatory during the COVID-19 pandemic to prevent the spread of the virus through respiratory droplets, negating the commitment to observe oral hygiene measures during social interactions. 4 Therefore, it results in a decrease in the observation of individual oral hygiene measures. This increases the severity or the odds of developing periodontal disease. In addition, wearing a mask and drinking no liquids at the workplace increase oral mucosal dryness, exacerbating periodontal diseases. 5, 6 Another factor that exacerbates periodontal diseases or results in the recurrence of periodontal diseases is that the treated patients do not attend periodontal maintenance sessions...