Kordagan 1:100,000 sheet is located in the northern Lut structural block and in South Khorasan province. In this area, mineralogy is mainly a vein controlled by fault structures with a northwest-southeast trend. In order to improve the results of the exploration, three solutions were used. To eliminate interfering elements and obtain clean factors in the multivariate statistical technique of stepwise factor analysis (SFA) was used. In addition to eliminate ineffective elements in the calculations, the elements that were not related to vein-type copper mineralization were also excluded. Finally, using the GMPI method, the obtained anomalies were intense. During the exploratorion operations in the Kordgan region, 836 stream sediment and 30 duplicate samples were taken. The samples were analyzed by ICP method by the Geological Survey and Mineral Exploration of Iran. Through the SFA in three step, the elements Ag, Ni and Cd were omitted from factor analysis calculations. In the next step, the elements Co, Cr, Fe, Mn, Sc, Ti, V, Zn, Sr, and W, which did not correspond to vein-type copper mineralization, were removed and factor analysis was prformed again. The results classified the elements into three factors, which were integrated and classified by GMPI method. Based on the results, eight favorable exploration areas were detected. These area was entirely compatible with the former investigation and also faults and favorable geological units for veins reserves such as Andesite and Andesitic tuff with Eocene age. It seems that the applied methods, by using multi-elemental geochemical signatures and integrating them appropriately, can identify and deduce anomalies consistent with other exploratory evidence.

Qalikouh area is located 35 km southwest of Aligudarz city, Lorestan province, SW of Iran. The area is located in the central part of the Zagros Geological Zone. The oil shales of the area are located in the Upper Triassic and Lower Jurassic of Sargalu and Garau Formations. The Sargalu Formation contains a series of shale, carbonate and clays. Garau Formation includes oil shale horizons with different thicknesses, ammonite shales and black cherty layer. In order to investigate the enrichment ratio and relationship between elements and organic matter, 53 samples of oil shale from Garau and Sargalu formations were selected. The samples were analyzed by XRD, XRF, ICP-MS and Rock-Eval analyzer. Data processing was performed using factor analysis, fractal modeling, stepwise factor analysis and principal component analysis. The data show that Sargalu Formation with average TOC = 13.27% and Garau Formation with average TOC = 18.13%, have high content of organic matter in central and NW of the area. Cconcentration-number fractal modeling showed that the Co, Mo, Ni, Pb and U have significant anomalies. The stepwise factor analysis (SFA) method showed a significant correlation between the anomalous elements and TOC. Geochemical maps showed that the anomalies are located for Co and Pb in the center and SE, for Mo, Ni in the NW and center, for V and REE in the NW, and for U in central part of the area.

The aim of this study was to separate the different mineralized zones consisting of supergene enrichment and hypogene zones in Milloieh porphyry Cu deposit (SE Iran) based on subsurface data and using the Staged Factor Analysis (SFA) and Concentration-Number (C-N) fractal modelling. Results obtained by SFA indicate that Cu and Mo were situated in a factor as F2-2 which was modelled by the C-N fractal method for separation of the mineralized zones. The supergene enrichment zone derived via the SFA and C-N fractal analysis contains 0.86% for Cu and 5.3 ppm for Mo. Moreover, the hypogene zone obtained by this modelling has Cu and Mo average values of 0.59% and 1.88 ppm, respectively. These mineralized zones were correlated with mineralographical data obtained by the polished section microscopic studies which indicate that the obtained zones based on the SFA and C-N fractal model are consistent with the geological and mineralization data.

To analyze the value of quantitative parameters of Computed Tomograph (CT) abdominal fat in predicting postoperative intestinal obstruction for gastric cancer. A retrospective analysis was conducted on 120 gastric cancer patients treated between January 2017 and December 2021. These patients were divided into two groups: an observation group with postoperative intestinal obstruction (28 patients) and a control group without (92 patients). CT scans were used to measure the Subcutaneous Fat Area (SFA) and Visceral Fat Area(VFA), calculate the SFA-VFA difference, and the VFA/SFA ratio. The receiver operating curve (ROC) was employed to evaluate the predictive efficacy of these CT measurements. The observation group exhibited significantly lower VFA and SFA compared to the control group (P < 0.05), while the differences in VFA/SFA ratio and SFA-VFA were not statistically significant. The area under the ROC curve (AUC) for the combined VFA and SFA in predicting postoperative intestinal obstruction was 0.902, with a 95% confidence interval of 0.859 to 0.956. This combined measure showed higher sensitivity (96.02%) and comparable specificity (85.24%) than single measurements. Logistic regression analysis identified diabetes, malnutrition, C-Reactive Protein (CRP) levels, VFA, and SFA as risk factors for postoperative intestinal obstruction (P < 0.05). The combined quantitative assessment of VFA and SFA using abdominal CT improves the sensitivity of predicting postoperative intestinal obstruction in gastric cancer patients. This complication is multifactorial, emphasizing the importance of a comprehensive approach in the clinical evaluation and management of these patients.

Seismic facies analysis (SFA) aims to classify similar seismic traces based on amplitude, phase,frequency, and other seismic attributes. SFA has proven useful in interpreting seismic data, allowing significant information on subsurface geological structures to be extracted. While facies analysis has been widely investigated through unsupervised-classification-based studies, there are few cases associated with supervised classification methods. In this study, we follow supervised classification scheme under classifiers, the support vector classifier (SVC), and multilayer perceptrons (MLP) to provide an opportunity for directly assessing the feasibility of different classifiers. Before choosing classifier, we evaluate extracted seismic attributes using forward feature selection (FFS) and backward feature selection (BFS) methods for logical SFA. The analyses are examined with data from an oil field in Iran, and the results are discussed in detail. The numerical relative errors associated with these two classifiers as a proxy for the robustness of SFA confirm reliable interpretations. The higher performance of SVC comparing to MLP classifier for SFA is proved in two validation steps. The results also demonstrate the power and flexibility of SVC compared with MLP for SFA.

Full consideration of the performance and efficiency of hospital costs necessitates the application of economic analysis techniques. The aim of this study was to assess the efficiency of hospitals in Kermanshah University of Medical Sciences through Stochastic Frontier Analysis (SFA) method. The performance of Kermanshah hospitals (n=7) was assessed and analyzed by Stochastic Frontier Analysis (SFA) method during 2005-2011. Inpatient admission was considered as the output variable, while the number of medical doctors, nursing staff other personnel, active beds and outpatient admission were considered as the input variables. Frontier 4.1 software was used to analyze the data. Based on the results of performance evaluation using Cobb-Douglas production function, the mean efficiency score of the hospitals in the SFA method was 0.63. Also, the efficiency capacity in these hospitals could be promoted up to 37 percent. Based on the results of Stochastic Frontier Analysis, downsizing the manpower in hospitals plays a major role in reducing hospital costs and improving their performance. Finally, it is necessary to investigate the effect of factors such as quality of service and patient satisfaction on hospital performance.

This study evaluated the effects of coating of soybean meal (SMB) with the fat enriched in saturated fatty acid (SFA) and zeolite on rumen degradable dry matter (RDDM), rumen degradable protein (RDP) and intestinal digestibility of protein. Treatments were (1) SBM, (2) SBM protected with 40% SFA, (3) SBM protected with 38% SFA and 2% zeolite, (4) SBM protected with 50% SFA, (5) SBM protected with 48% SFA and 2% zeolite. To obtain the RDP fraction, samples were ruminally incubated for 16 h. The intestinal digestibility of crude protein was performed by three-step in vitro procedure. The results showed that SBM protecting with SFA reduced protein solubility compared with untreated SBM (P=0.002). The RDDM and RDP were decreased (P<0.05) with increasing fat level in the product. Using 2 % zeolite significantly decreased (P<0.05) RDP. There were no significant differences between SBM and SBM protected treatments in intestinal digestibility. It was concluded that protection of SBM with SFA decreased of RDDM and RDP, while RDP values showed more decrease with the inclusion of zeolite in the fat matrix.

Escherichia coli (E. coli) is a major cause of urinary tract infection in children and women. Several virulence factors have been detected in uropathogenic Escherichia coli strains. P، S and Afa fimbria are the most important factors which are coding by pap، sfa and afa genes، respectively. This study aimed to determine the presence and prevalence of fimbrial virulence genes in Escherichia coli isolates from patients with urinary tract infection in Rafsanjan city، Iran. In this study، 145 urine samples were cultured for identification of Escherichia coli. The isolates were examined via standard biochemical tests. DNA extracts from the confirmed isolates were examined to determine papEF، afaBC and sfa / focDE genes using multiplex-polymerase chain reaction (PCR) method. Among the cultured samples، 122 Escherichia coli isolates were determined. Virulence genes genotyping of isolates showed that 38. 50% of the isolates were possessed at least one of the three virulence genes. The papEF gene was the most prevalent (18. 85%) and prevalences of sfa/focDE and afaBC were 2. 45% and 0. 81%، respectively. Twenty isolates (16. 39%) contained both papEF and sfa/focDE genes. The results of this study in comparison with other researchers showed that papEF gene is in the high frequency، and then، afaBC and sfa/focDE fimbrial genes.

The main endeavor in this paper is to study on 32 fundamental Iranian dams and investigating efficiency scores and also ranks of placed powerhouse on them by using data envelopment analysis and stochastic frontier analysis methods in 1393. Applying copula technique in the stochastic frontier analysis is an advantage to our study between similar activities. EMS and MATLAB programs have been used to evaluate efficiency of centers by any models. To have a unique result, we use the average of scores by four models in any center and it is seen that Sefidroud has been selected the best efficient center and also Taleghan is in the last order. Also for comparing results of the mentioned four models, we use correlations which are based on ranks of the hydroelectricity centers in every model. The minimum compatibility is between results of BCC and SFA-Clayton models which is 63.86% and the maximum compatibility is between results of standard SFA and SFA-Clayton models which is 99.41%. Meanwhile compatibility between results of CCR and BCC models is 72.10%.

The main goal of this paper is to identify the factors affecting the efficiency of banking industry in Iran. Towards this ends, two methods namely, Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) have been employed to investigate the issue in detail. The data needed for this study covers the period of 1002to 1002and are compiled from balance sheets of commercial banks, specialized banks and also from private banks. The results obtained by the application of DEA method indicate that in terms of economic, allocation, and technical consideration, the average efficiency of banking sectors has been in the order of 265, 775and 715, respectively. In the SFA method, the overall average efficiency of banking system is estimated tobe around %45. the results of our model and its coefficient estimates indicate that the efficiency of banking industry is inversely related to the size of the banks, its overall assets and concentration index while factors such as number of bank branches, its skilled and educated labor force, loan to asset ratio, ratio of credit risk to asset, and e-banking index have a positive impact on efficiency index of banking industry.Promotion of efficiency in the banking sectors can be ensured only when the non viable banks are taking over by acquisition or merging practices.