Introduction and purpose: Despite recent efforts to identify microplastics in the aquatic environment worldwide, identifying the various sources of its release remains a challenging task. Understanding and identifying the different sources of aquatic pollution and the processes affecting them is essential for a comprehensive description of the quality of water resources. The aim of this study is therefore to introduce statistical methods to determine the sources of microplastics in aquatic environments. Methods: This review article first identifies the pathways of microplastic entry into the aquatic environment, followed by an examination of four commonly used Multivariate statistical methods: Principal Component analysis (PCA), Cluster analysis (CA), Hierarchical Cluster analysis (HCA) and Positive Matrix Factorization (PMF). Results: Multivariate statistical analysis can be used to determine different variables such as size, shape, color, and density of microplastics. It can also determine the sources of microplastics (domestic wastewater, industrial effluents, agricultural activities, surface runoff, air currents, etc.). It also identifies which variables have the greatest impact on pollution and suggests the best solutions to reduce pollution. Conclusion: the study of pollution based on Multivariate statistical analysis can provide important information on the main sources of microplastic pollution and the relative contribution of different sources in the aquatic environment, which can help to improve environmental management and reduce pollution.

In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of statistical energy analysis. Correct estimation of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the statistical energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound estimation.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

Q-mode hierarchical cluster (HCA) and principal component analysis (PCA) were simultaneously applied to groundwater hydrochemical data from the three times in 2004: June, September, and December, along the Ain Azel aquifer, Algeria, to extract principal factors corresponding to the different sources of variation in the hydrochemistry, with the objective of defining the main controls on the hydrochemistry at the aquifer scale. Hydrochemical data for 54 groundwater samples were subjected to Q-mode hierarchical cluster and principal component analysis. The study finds, from Q-mode HCA that there are three main hydrochemical facies namely the less saline water (group 1: Ca-Mg-HCO3), mixed water (group 2: Mg-Ca-HCO3-Cl) and blended water (group 3: Mg-Ca-Cl-HCO3). In principal component analysis, the first 4 factors explain 72.14% of the total variance, their loadings allowing the interpretation of hydrochemical processes that take place in the area. The results of this study clearly demonstrate the usefulness of Multivariate statistical analysis in hydrochemical.

In this paper we construct a modeling for detection of banks which are experiencing serious problems. Sample and variable set of the study contains 30 banks of Iran during 2006-2014 and their financial ratios. Well known Multivariate statistical technique (principal component analysis) was used to explore the basic financial characteristics of the banks, and discriminant Logit and Probit models were estimated based on these characteristics. Results suggest that the model can be used as an analytical decision support tool in both on-site and off-site bank monitoring system to detect the banks which are experiencing serious problems.

In this research work, Intra-species karyotypic diversity for 17 populations of Silybum marianum from different geographical regions of Iran along with one population from Hungary were investigated. To prepare the appropriate chromosomal specimen, one and a half centimeters of root tip were isolated, after using fixation of pre-treatment, the picture were taken from the karyotypes which prepared and the chromosome base number of all of them was x = 17, therefore the number of chromosomes obtained 2n = 34. In terms of karyotypic symmetry indices DRL, S%, TF%, A1 and A2, there were significant differences between ecotypes at probability level of 1%, which indicates that there were genetic diversity between the studied ecotypes. Regarding these results, the Ramhormoz ecotype and then the Shushtar ecotype were considered as the most asymmetric and most advanced ecotypes and the ecotype of Najaf-Abad and ecotype of Karaj-2 were considered as the most symmetrical and incomplete ecotypes. Based on the cluster analysis, the karyotypic characters of the populations were divided into three groups. The greatest difference was observed between the two Ramhormoz and Najafabad ecotypes. To determine the contribution of each karyotypic trait in the creation of diversity among ecotypes, factor analysis was carried out and the first, second and third factors accounted for more than 87% of the variation among the populations. The results of karyotypic analysis showed that there is a high karyotypic variation among Silybum marianum ecotypes in Iran, so that they can be used in breeding programs and widening genetic diversity in gene pools.

Summary: In the present study the sample catchment basin approach has been used in addition to Multivariate statistical analysis over geochemical dataset collected in Kervian area in Iran. Sample catchment basin has reasonably detected the favorable zones in the present study and the proven Au mineralization has validated the results. Introduction: Stream sediment data application method has been widely used and accepted in exploration of different deposit types in mineral exploration industry and has shown its efficiency in this context. The sample catchment basin approach is a technique for processing of stream sediment data that is employed for removal of lithological impact from existing variation in chemical content of the samples. Methodology and Approaches: The target area covers 617 km2 in which 299 stream sediment samples were collected for chemical analysis. In addition, digitized 1:100000 geological and 1:50000 topographical maps were used for creation of sample catchment basins considering the sampling point positions. In order to remove the impact of background contribution to geochemistry of stream sediment by this technique the following procedure has been taken into account: 1- estimation of uni-element background concentration of element of interest for every lithology and then estimation of uni-element background value for every sample catchment basin 2- removal of the background concentration from measured concentration of element for each sample 3- dilution correction of residual values by taking the catchment area size into account 4- analysis of dilution correction values and delineating the anomalous basins. Results and Conclusions: The sample catchment basin method was employed and data processing was completed as mentioned above which resulted in delineation of anomalous Au values extended south-westerly. The results are compatible with known gold occurrences located in this part of the map. There are weak to moderate anomalous basins positioned south east and east of the known mineralization covered with the same sedimentary units as mineralization area that could be assumed promising. However, sample catchment basin has successfully highlighted the anomalous basins which were not detected through analysis of raw dataset. Employing this method has led to introduction of more areas for further prospecting, decreasing the chance of false negative anomaly. Comparison between processed dataset with the sample catchment basin approach and raw data set has demonstrated the superiority of the sample catchment basin approach.

Sulfur springs are distinguished from other groundwater sources by their specific therapeutic, thermal and hydrochemical properties. Golgir, Meydavood, Naft Sefid, pole Zal, Grasab JaOrdo, Mashrageh, Grab Behbahan, and Baba Ahmad Springs are low-temperature sulfur springs in Zagros area of Khuzestan. These springs have temperatures between 22 and 35 ° C and appear along with the Zagros thrust. By analyzing the hydrochemical data of sulfur springs on two periods (December 2017 and May 2018) and applying the hydrochemical methods, principal component analysis (PCA) and hierarchical clustering (AHC), it has been tried to identify the factors affecting the chemical quality of the springs. The first factor includes the electrical conductivity, Na, Cl, K, Ca, Mg, As and Cd variables, this factor is due to the interaction of aquifer and water materials, as well as high correlation between the main ions, arsenic, and cadmium indicates that these elements have a similar origin. The second factor includes the SO4, NO3, and S variables. According to the results of TOC analysis, this factor can be attributed to the influence of oil brines. Piper diagrams and hierarchical Q-mode clustering were used to classify the springs studied. The Piper diagram separated these springs into three groups and the hierarchical Q-mode clustering method, taking into account further parameters of sulfur springs in four groups.

In order to cytogenetic study were examined six genotypes of Achillea including, A. millefoliumand A. Santolina. In this study were done karyotype determination and determination of the traits contribution in variation. To provide appropriate examined samples, after gathering roots, 0.5 cm root tip was removed and then was carried out pre-treatment and fixation, respectively. After hydrolysis and squash were done imaging and finally were prepared karyotypes. In all genotypes basic chromosome number was x =9. Three genotypes Aligoodarz, Ardabil and Meshkinshar were diploid and Arak, Ilam and Estahban were tetraploid. Based on Stebbins method, Arak and Ilam were classified in Class 1A, Ardabil and Meshkinshar in Class 2A and Aligoodarz and Estahban in Class 1B, respectively. Mean comparisons revealed that the Estahban and Aligoodarz had the lowest and highest the value of the S, L and T respectively. In factor analysis, two factors were explained more than %90.92 of the variance. The first factor was explained %46.65 of variance and was correlated positively with the L/S and the L-S was correlated negatively with %F and the ratio S/L. Therefore, this factor was named as the arm chromosome ratio arm and Huziwara index. The second factor explained %44.27 of variance and was correlated positively with the S, L, T and %RL. Therefore, this factor was named as the chromosome or genome size. Cluster analysis was classified genotypes into two clusters. In statistical analysis employed software' s including, excel (2007), Photoshop (Adobe Photoshop CS2) and SPSS (PASW Statistics18).