In the present study, the ballast waters from 24 ships arriving at Shahid Rajaee Port in Bandar Abbas, Hormozgan Province, Iran, were studied in two warm and cold seasons (summer 2017 and winter 2018). The zooplankton sampling was conducted under the MEPC 173(58) method, by bucket and using a 50-micron mesh to filter 300 liters of ballast water. In total, 57 zooplankton species, belonging to 8 phyla, 11 classes, 15 orders, and 35 families were identified in the sampled ballast water, among which the Arthropoda phylum with 16 families and 23 species recorded the highest number of species The highest and lowest density among the studied samples belonged to the Tintinnopsis gracilis species from the Codonellidae family (11. 4%) and Calanopia elliptic species from the Pontellida family (0. 04%), respectively. The results of the Pearson correlation test showed that there was a negative correlation between the measured pH parameter and the frequency of zooplankton (p<0. 01). There was also a positive correlation between EC and Shannon diversity index (p<0. 05). (PCA) test results showed that EC, temperature, salinity, and TDS factors had the most impact in stations with the highest number of species and abundance of zooplankton. The results of the cluster diagram showed the highest similarity between winter at the Western Indian Ocean (WW) and summer at the Western Indian Ocean (WS) at the level of 54%, and the lowest similarity between the winters at the Northwestern Indian Ocean (NW) at the level of 24% with other regions. All the studies species in the ballast waters of the Persian Gulf had been identified and reported by previous studies but certainly requires continuous monitoring management of the ballast water, and supervising their discharge into the marine environment.

Background: Eating disorders have become increasingly prevalent over the years,the age at which they appear has decreased, and they can lead to serious illness or death. Therefore, the number of studies on the matter has increased. Eating disorders like anorexia nervosa (AN) and bulimia nervosa (BN) are affected by many factors including mental illnesses that can have serious physical and psychological consequences. Accordingly, the present study aimed to compare the clinical and metabolic features of patients with AN and BN and identify potential biomarkers for distinguishing between the two disorders. Methods: Clinical data of 41 participants who sought treatment for eating disorders between 2012 and 2022, including 29 AN patients and 12 BN patients, were obtained from NPIstanbul Brain Hospital in Istanbul, Turkey. The study included the clinical variables of both outpatient and inpatient treatments. Principal component analysis ((PCA)) was utilized to gain insights into differentiating AN and BN patients based on clinical characteristics, while machine learning techniques were applied to identify eating disorders. Findings: The study found that thyroid hormone levels in patients with AN and BN were influenced by non-thyroidal illness syndrome (NTIS), which could be attributed to various factors, including psychiatric disorders, substance abuse, and medication use. Lipid profile comparisons revealed higher triglyceride levels in the BN group (P<0. 05), indicating increased triglyceride synthesis and storage as an energy source. Liver function tests showed lower levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) in BN patients (P<0. 05), while higher prolactin levels (P<0. 05) suggested an altered hypothalamicpituitary-gonadal axis. Imbalances in minerals such as calcium and magnesium (P<0. 05) were observed in individuals with eating disorders. (PCA) effectively differentiated AN and BN patients based on clinical features, and the Naïve Bayes (NB) model showed promising results in identifying eating disorders. Conclusion: The findings of the study provide important insights into AN and BN patients’ clinical features and may help guide future research and treatment strategies for these conditions.

Background and Objective: Increasing industrial activities associated with the production of pollutants, including heavy metals, is one of the main causes of water and soil pollution. Mineral activities are one of the human activities that cause pollution of the natural resources such as soil. Method: In this study, the zoning concentration of copper as soil contamination around Meyduk copper mine was investigated. The direction samples were taken according to the situation of surrounding villages. Systematic sampling of 360 samples had been collected through the directions. Measuring the concentration of sample was done using atomic absorption method in the laboratory. To indicate the degree of soil pollution with heavy metals, Muller’ s geoaccumulation index was used. Finally, in order to estimate the normal concentration of Cu and pollution of soil, Kriging method was used. Results: Results showed that the maximum amount of Cu concentration is 697. 5 mg/kg and the minimum is 6. 35 mg/kg. The Cu concentration trend in direction D was more than direction M due to the direction of local dominant wind. Discussion and Conclusion: By receding from location of mine, the overall trend of Cu concentration decreased. This indicated the role of mine activities on soil pollution.

The problem with waste plastic is that it decomposes after hundreds of years which causes its accumulation on the land. The waste plastic is used in the production of Polymer-Coated Aggregate ((PCA)) material that is eventually used in the construction of commercial roads. The roads made from (PCA) material are more efficient and are of greater strength as compared to normal roads. Through previous extensive experimental work, it is concluded that the addition of 12% of plastic in the total mixture provides the optimum results. The chosen process for the research to make (PCA) is the dry process, which follows by heating the aggregate stone to a certain temperature and on the other hand melting the (PCA) and coating over the aggregate. This research is mainly based on the fabrication of a machine that eventually produces (PCA). The process of production of (PCA) material includes pre-heating of crushed aggregate, shredding of plastics, melting and coating of plastics, heating bitumen, adding hot molten bitumen, and uniform mixing. The aggregate tests began with each batch sample from the machine to validate the working and product quality of the fabricated mixer. The mean of Marshall stability value, flow value, and % air void are 2651.893kN, 17, and 2.642% respectively. Whereas the mean aggregate crushing and impact value obtained is 9.778 and 7.627. The mean value of specific gravity obtained is 2.569. The produced (PCA) material has a low water absorption capability is 0.573. The Los Angeles abrasion test, 9.652 is the mean abrasion value observed. The mean value of the stripping test obtained is 0.197%, which shows that there is almost negligible stripping of bitumen from the surface of (PCA).  It can be concluded that the fabricated rotary mixer gives us an adequate (PCA) product with suitable enhancement of binding properties for the pavement of roads.