Digital Shoreline Analysis System improvement for uncertain data detection in measurements.

Digital Shoreline Analysis System (DSAS) is the most frequently used coastal engineering system for shoreline change quantification. Factors like human and system errors, wrong perception of the shoreline changes, and non-exact data sources may cause errors in the measured data. Detection and modification of such data can increase the accuracy of results. At present, the DSAS tool lacks this capability, so this research aimed to present a new module for DSAS to detect uncertain data in shoreline change rate measurements. The module's basis for detecting uncertain data is to use statistical methods: adjusted boxplot, Grubbs' test, standard deviation tests, median test, modified Z-score test, and voting method. The module's performance was evaluated based on a data set obtained through Qeshm Island shoreline change quantification in Iran. The details of these methods, the prepared module, the case study, and the shoreline change measurement statistical methods were discussed in this study. The results showed the acceptable output of this module in detecting uncertain data.

Comparison of three hybrid models to simulate land use changes: a case study in Qeshm Island, Iran.

Land use change simulation is an important issue for its role in predicting future trends and providing implications for sustainable land management. Hybrid models have become a recognized strategy to inform decision-makers, but further attempts are needed to warrant the reliability of their projected results. In view of this, three hybrid models, including the cellular automata-Markov chain-artificial neural network, cellular automata-Markov chain-logistic regression, and Markov chain-artificial neural network, were applied to simulate land use change on the largest island in Iran, Qeshm Island. The Figure of Merit (FOM) was used to measure the modeling accuracy of the simulations, with the FOMs for the three models 6.7, 5.1, and 4.5, respectively. Consequently, the cellular automata-Markov chain-artificial neural network most precisely simulates land use change on Qeshm Island and is, thus, used to simulate land use change until 2026. The simulation shows that the incremental trend of the built-up class will continue in the coming years. Meanwhile, the areas of valuable ecosystems, such as mangroves, tend to decrease. Despite the protection plans for mangroves, these areas require more attention and conservation planning. This study demonstrates a referential example to select the proper land use models for informing planning and management in similar coastal zones.

Modeling land cover change dynamic using a hybrid model approach in Qeshm Island, Southern Iran.

Multiple factors including natural and human-induced ones lead to land cover change in the landscape. Therefore, identifying the pattern of land cover change can help inform land-use management and prevent associated issues which can affect the natural resources of the landscape. The aim of this study is to assess land cover change in the Qeshm Island in southern Iran by combining the resulting outputs of multiple modeling methods, cellular automata (CA), Markov chains, and artificial neural networks (ANN) based on land cover maps for the years 1996, 2006, and 2016 that have been extracted from satellite imagery (Landsat 5, 7, and 8). In order to evaluate the accuracy of modeling, the Kappa coefficient was calculated to be 0.8. Then, land cover changes for 2025 were predicted by a hybrid model (CA-Markov-ANN). The results indicate that the classes of built-up areas, vegetation, and mangrove forests have changed more significantly from 1996 to 2016 compared with other classes. Land cover maps generated in this study showed that built-up areas have grown significantly in recent decades due to the region's growing population and development of ports, commercial, and industrial areas. Due to the climate change, the land area covering vegetation has decreased dramatically. The size of the mangrove forests has increased over the time period of the study (1996-2025). The findings of this study can inform land-use planning decisions by providing them with a comprehensive overview of land cover conditions in the future.

Aureobasidium mangrovei sp. nov., an ascomycetous species recovered from Hara protected forests in the Persian Gulf, Iran.

A new ascomycetous black yeast-like species was recovered from healthy plant (Avicennia marina) of Hara protected mangrove forests at Qeshm Island, Iran. Morphological, physiological analysis as well as a molecular analysis of the internal transcribed spacer (ITS) and partial large ribosomal subunit (D1/D2 domains) confirmed the placement of this strain in the genus Aureobasidium and based on considerable sequence divergence, distinguishable cardinal growth temperatures and salt tolerance a new species Aureobasidium mangrovei sp. nov. is proposed. However, the type strain micro-morphologically is not clearly distinguishable from other members of the genus. The type strain, Aureobasidium mangrovei was preserved in a metabolically inactive state at the Iranian Biological Resource Centre, Tehran, Iran as IBRC-M 30265T and the ex-type culture is deposited in the CBS yeast collection of the Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands as CBS 142205T. The GenBank accession numbers for the nucleotide sequences of the large subunit ribosomal DNA and ITS region are KY089084 and KY089085, respectively. The MycoBank number of the new species is MB 823444.

First report of Lophomonas infection in a patient with AML-2 from Qeshm Island, Persian Gulf, southern Iran.

Immunocompromised patients are frequently more susceptible to pathogens such as protozoa. For the first time, we report a case of pulmonary lophomoniasis in a known case of acute myeloid leukaemia (AML-2) from Qeshm Island, Persian Gulf, southern Iran. Diagnosis of lophomoniasis was confirmed using microscopy and molecular examinations of bronchoalveolar lavage fluid. She was completely treated with metronidazole (500 mg three times a day for 3 weeks). We conclude that immunocompromised patients with unjustified respiratory disorders should be screened for Lophomonas infection.

A Study of Female Genital Mutilation of African-Descent Iranians in Qeshm Island.

Background: This article investigates the practice of female genital mutilation (FGM) as a long-held custom in Qeshm Island, which makes many African-descended women face different physical and psychological health problems. Objective: To investigate the prevalence of female genital mutilation in Qeshm Island and the traditional mode of thinking of Afro-Iranian people of the Island about this practice. Methods: This study is based on the descriptive analysis method. The questions of the study are (a) Why female genital mutilation is still practiced in Qeshm Island; (b) What are the mental and physical effects of female genital mutilation on women; and (c) How government or NGOs are fighting against this tradition. The results: This article has found out that female genital mutilation resulted in many lifelong diseases and sexual degradation in African-descended women of Qeshm Island. This article also illustrates that the best way to combat this wrong tradition is to inform people by gradual training without any insult to their beliefs. Conclusion: This study reveals the prevalence of a false tradition and the necessity of behavioral change. In doing so, the government and NGOs' strong actions and attracting the support of the community elders are also needed.

Multivariate curve resolution of organic pollution patterns in mangrove forest sediment from Qeshm Island and Khamir Port-Persian Gulf, Iran.

Straight-chain alkanes (n-alkanes) have been proposed as biomarkers to assess petroleum pollution sources in marine environments. In this work, three sampling sites were selected along Iranian-protected mangrove forests in the Persian Gulf. Sample sites were chosen to represent different compositions and sources of n-alkanes in surface sediments (0-5 cm) from different locations in the Khamir Port, in the middle part of the Gulf, and in the Qeshm Island. Samples were analyzed by gas chromatography-mass spectrometry (GC-MS), and the obtained n-alkanes concentrations were analyzed by principal component analysis (PCA) and multivariate curve resolution alternating least squares (MCR-ALS) to deduce their possible sources and distribution patterns. Results revealed that n-alkanes have a dominant biogenic source in marginal Qeshm Island stations, which changed from biogenic to petrogenic sources in the Khamir Port areas. Sediment samples from the Khamir Port showed the significant presence of oil pollution due to transportation. These samples are being exposed to basic Persian Gulf currents entering from the Hormuz Strait causing oil pollution spread over the entire Gulf area. Sediment samples of the Middle Part stations located between two other sites show a combined condition of the two previous sections, with petrogenic and biogenic contributions. The present study demonstrates that the Hara Protected Area was already contaminated by background oil pollution as a result of continuous oil spills and war conflicts in the Persian Gulf.Additionally, the MCR-ALS method is shown to be a powerful chemometric tool for the investigation, resolution, identification, and description of pollution patterns distributed over a particular geographical area and environmental compartment. They can be used as well as parameters like unresolved to resolved ratio (U/R), pristane to phytane (Pr/Ph), n-C17/Pr, n-C18/Ph, and unresolved complex mixture (UCM) to assess petroleum pollution sources in the sediments.

Antifungal and antibacterial activity of Haliclona sp. from the Persian Gulf, Iran.

In this study, antifungal and antibacterial activities of diethyl ether, methanol and aqueous extracts of Haliclona sp. were assessed (in vitro). The antibacterial activity of the extracts was determined by broth dilution methods against clinical Gram-negative bacteria: Escherichia coli, Pseudomonas aeruginosa and Gram-positive bacteria: Staphylococcus aureus aureus, Bacillus subtilis spizizenii. The antifungal activity of the extracts was determined by using a broth microdilution test against clinical fungi Candida albicans and Aspergillus fumigatus. Our results showed diethyl ether extract of Haliclona sp. was active on Gram-positive bacteria. In addition, methanol extract in comparison with diethyl ether extract had better activity against C. albicans (MIC: 0.75 mg/mL, MFC: 1.5mg/mL) and A. fumigatus (MIC: 2mg/mL, MFC: 3mg/mL). Aqueous extract had neither antifungal nor antibacterial activities. Based our results, Haliclona sp. can be considered as a source of novel antibiotic and antifungal.