Saqez–Sardasht Goldfield,North Sanandaj-Sirjan Zone,Iran:A Tectono-Metallogenic Synthesis

The Sanandaj–Sirjan Zone(SSZ),as the metamorphic-magmatic core of the Zagros Orogen in southwestern Iran,contains several styles of gold deposit of Phanerozoic age.The northern SSZ includes an ENE-trending goldfield belt.This area that encompasses the main orogenic gold deposits,e.g.,Qolqoleh,Kervian,Qabaqhlujeh,and the Barika VMS goldfield,was chosen for this research to study the spatial and temporal relationships between gold mineralization and orogenic phases.Regarding the rock unit variations,metamorphism,magmatism and the settings of the structures,the study area is divided into four distinct tectonic blocks,separated by three main NW-trending thrust faults(suture lines)including,from NE to SW,the Tamugheh,the Ebrahim Hesar and the Zagros main thrust(ZMT)faults.The area between the Tamugheh and Ebrahim Hesar faults is a tectonized/uplifted basement of accretionary wedge-originated thrust slivers,hosting the above orogenic gold mineralizations.The other area between the here termed Ebrahim Hesar fault and the ZMT is an island-arc basin,proposed here as the Sardasht–Barika zone,including the only recognized massive sulfide gold district all over the SSZ,named Barika.The Barika goldfield was metamorphosed,deformed and enriched due to the islandarc collision to the Arabian continent,before the closure of Neotethys on the eastern flank.

Frequency of E.coli pathotypes in acute diarrhea of children and its related factorsat Beassat hospital,Sanandaj

Objective:Diarrhea is a leading cause of morbidity and mortality among children in developing countries.The bacterial pathogen most commonly associated with childhood diarrhea is Escherichia coli.A one-year prospective study was carried out in Sanandaj to determine the prevalence and roles of the different E.coli pathotypes in children less than five years of age with acute diarrhea.Methods:Rectal swab were collected prospectively from children with acute diarrhea and transported to the Department of Microbiology,School of Medicine, KUMS,Sanandaj during 2008.The study was approved by the institutional ethics committee.Results:During this study period,rectal swabs were investigated from a total of 466 children 1 to 144 months of age(mean, 29.97 months±S.D) with diarrhea.Among the children,191(41%,191/466) were girls,and 275 (59%,275/466) were boys.The age-specific incidence rates of acute diarrhea among children 13-24 and 1 - 12 months of age were 37.37%(37/99) and 26.26%(26/99),respectively,during the study period.A total of 99 strains of E.coli were detected.EPEC 59(59.59%) and EIEC 22(22.22%),were the most commonly found Escherichia coli strains detected in stools from children.Disk diffusion testing showed E.coli strains resistance to tetracycline(89.89%),chloramphenicol(88.88%),Ampicillin(79.79%),Amoxicillin (75.75%) and Ceficime(75.75%).Among risk factors like age,sex,haemoglubin,fathers and mothers education,food and weight of children only mother's education was significant(P =0.018).Conclusion: In most of the clinical laboratories in Iran,E.coli does not considered as an etiologic agent responsible for diarrhea. Results in this study revealed that E.coli should be considered as an etiologic agent causing acute diarrhea among children.We therefore,recommend the routine isolation and identification of E.coli strains in all the clinical laboratories in Sanandaj.Guidelines for appropriate use of antibiotics in Sanandaj need updating.

Genotyping of E. coli Isolated from Urinary Tract Infection Patients Containing B-Lactamase Resistance Gene CTX-M Group 1 in Sanandaj Medical Health Centers

CTX-M-producing bacteria are known as a resistant source against oxyimino-cephalosporin such as cefotaxime and ceftazidime;although laboratory diagnosis of this gene has not been properly defined. The aims of this study are determining the rates of prevalence of CTX-M and CTX-M group 1 in the Escherichia coli (E. coli) obtained from urinary tract infections (UTI), and also determining their genetic relationship in the city of Sanandaj. In current study, 180 E. coli strains isolated from urinary tract infections were used. Sensitivity to common antibiotics was studied by the disc diffusion method. Phenotypic detection of isolated ESBL-producing starins was done by the combination disc test. CTX-M and CTX-M1 genes were detected using the PCR method and finally, the possible clonal relationship between isolates was determined using the REP-PCR method. 89 samples were ESBL-positive. The PCR assay used for detecting the CTX-M gene, showed that 48 samples out of 180 samples (26.66%) contained that gene;also among these 48 samples, 23 (12.77%) had CTX-M group 1. Based on the REP-PCR assay, 48 genotypes among 48 samples were CTX-M-positive. Results from the REP-PCR assay indicated that the clonal propagation theory of one epidemic strain of Escherichia coli is not apply, i.e. all CTX-M-producing species are not originated from one single strain and the gene is spread between different isolates. Therefore, hospitals and their employees must be more hygiene and, proper disposal of hospital waste can help to prevent the spread of different resistances.

Path-Based Clustering Algorithm with High Scalability Using the Combined Behavior of Evolutionary Algorithms

Path-based clustering algorithms typically generate clusters by optimizing a benchmark function.Most optimiza-tion methods in clustering algorithms often offer solutions close to the general optimal value.This study achieves the global optimum value for the criterion function in a shorter time using the minimax distance,Maximum Spanning Tree“MST”,and meta-heuristic algorithms,including Genetic Algorithm“GA”and Particle Swarm Optimization“PSO”.The Fast Path-based Clustering“FPC”algorithm proposed in this paper can find cluster centers correctly in most datasets and quickly perform clustering operations.The FPC does this operation using MST,the minimax distance,and a new hybrid meta-heuristic algorithm in a few rounds of algorithm iterations.This algorithm can achieve the global optimal value,and the main clustering process of the algorithm has a computational complexity of O�k2×n�.However,due to the complexity of the minimum distance algorithm,the total computational complexity is O�n2�.Experimental results of FPC on synthetic datasets with arbitrary shapes demonstrate that the algorithm is resistant to noise and outliers and can correctly identify clusters of varying sizes and numbers.In addition,the FPC requires the number of clusters as the only parameter to perform the clustering process.A comparative analysis of FPC and other clustering algorithms in this domain indicates that FPC exhibits superior speed,stability,and performance.

Applications of Soft Computing Methods in Backbreak Assessment in Surface Mines: A Comprehensive Review

Geo-engineering problems are known for their complexity and high uncertainty levels,requiring precise defini-tions,past experiences,logical reasoning,mathematical analysis,and practical insight to address them effectively.Soft Computing(SC)methods have gained popularity in engineering disciplines such as mining and civil engineering due to computer hardware and machine learning advancements.Unlike traditional hard computing approaches,SC models use soft values and fuzzy sets to navigate uncertain environments.This study focuses on the application of SC methods to predict backbreak,a common issue in blasting operations within mining and civil projects.Backbreak,which refers to the unintended fracturing of rock beyond the desired blast perimeter,can significantly impact project timelines and costs.This study aims to explore how SC methods can be effectively employed to anticipate and mitigate the undesirable consequences of blasting operations,specifically focusing on backbreak prediction.The research explores the complexities of backbreak prediction and highlights the potential benefits of utilizing SC methods to address this challenging issue in geo-engineering projects.

Mineral Chemistry,Trace Elements,Isotopic Analysis and Zircon U-Pb Dating in the Hesar Pluton,Northern UDMA,Iran:Implications for Pre-Collisional Magma Mixing

The Hesar pluton in the northern Urumieh-Dokhtar magmatic arc hosts numerous mafic-microgranular enclaves(MMEs).Whole rock geochemistry,mineral chemistry,zircon U-Pb and Sr-Nd isotopes were measured.It is suggested that the rocks are metaluminous(A/CNK=1.32-1.45),subduction-related I-type calc-alkaline gabbro to diorite with similar mineral assemblages and geochemical signatures.The host rocks yielded an U-Pb crystallization age of 37.3±0.4 Ma for gabbro-diorite.MMEs have relatively low SiO_(2) contents(52.9-56.6 wt%)and high Mg^(#)(49.8-58.7),probably reflecting a mantle-derived origin.Chondrite-and mantle-normalized trace element patterns are characterized by LREE and LILE enrichment,HREE and HFSE depletion with slight negative Eu anomalies(Eu/Eu^(*)=0.86-1.03).The host rocks yield(^(87)Sr/^(86)Sr)_(i) ratios of 0.70492-0.70510,positive ε_(Nd)(t)values of+1.55-+2.06 and T_(DM2)of 707-736 Ma,which is consistent with the associated mafic microgranular enclaves((^(87)Sr/^(86)Sr)_(i)=0.705014,ε_(Nd)(t)=+1.75,T_(DM2)=729 Ma).All data suggest magma-mixing for enclave and host rock formation,showing a complete equilibration between mixed-mafic and felsic magmas,followed by rapid diffusion.The T_(DM1)(Nd)and T_(DM2)(Nd)model ages and U-Pb dating indicate that the host pluton was produced by partial melting of the lower continental crust and subsequent mixing with injected lithospheric mantlederived magmas in a pre-collisional setting of Arabian-Eurasian plates.Clinopyroxene composition indicates a crystallization temperature of~1000℃ and a depth of~9 km.

Nurses'attitude toward patients'safety climate during COVID-19 pandemic:a cross-sectional study

Objective:Patient safety is a fundamental factor in improving the quality of care provided in hospitals.Therefore,it is considered a significant parameter by all healthcare organizations around the world.The present study was conducted to investigate the attitude of nurses toward the patient safety climate during the Coronavirus Disease 2019(COVID-19)pandemic in the southeast of Iran.Methods:This is a cross-sectional descriptive study.Among all the nurses working in one of the hospitals in the southeast of Iran,171 nurses participated in the study through convenience sampling methods.The survey was conducted between June 1 and July 30,2020.A 2-part questionnaire including demographic information and an assessment of nurses'attitudes toward patients'safety climate was used for data collection in 2021.The content validity of the scale is(0.77)and reliability was re-calculated and confirmed by the present study with Cronbach's alpha(α=0.9).Data were analyzed by SPSS 20(IBM Corporation,Armonk,New York,United States)using descriptive and analytical statistical tests.Results:The mean score of safety climates was 3.2±5.20(out of 5 scores).The results showed that among all dimensions of the safety climate,only the education dimension was statistically significant between males and females(P<0.001).Also,there was a significant relationship between the overall average of the safety climate and its dimensions according to the people's position only in the dimension of supervisors'attitude(P<0.01)and burnout(P<0.01).Additionally,a significant correlation between the education level and the overall score of safety climate(P<0.01),as well as the supervisor's attitude dimension(P<0.01),was observed.Conclusions:The results showed that the safety climate was at a relatively favorable level.Considering the impact of nurses'attitudes on the safety climate of patients,its improvement seems necessary.It is recommended to design training courses and educate nurses in order to promote a patients safety climate in hospitals.

Investigation of factors affecting rural drinking water consumption using intelligent hybrid models

Identifying the factors affecting drinking water consumption is essential to the rational management of water resources and effective environment protection. In this study, the effects of the factors on rural drinking water demand were studied using the adaptive neuro-fuzzy inference system (ANFIS) and hybrid models, such as the ANFIS-genetic algorithm (GA), ANFIS-particle swarm optimization (PSO), and support vector machine (SVM)-simulated annealing (SA). The rural areas of Hamadan Province in Iran were selected for the case study. Five drinking water consumption factors were selected for the assessment according to the literature, data availability, and the characteristics of the study area (such as precipitation, relative humidity, temperature, the number of subscribers, and water price). The results showed that the standard errors of ANFIS, ANFIS-GA, ANFIS-PSO, and SVM-SA were 0.669, 0.619, 0.705, and 0.578, respectively. Therefore, the hybrid model SVM-SA outperformed other models. The sensitivity analysis showed that of the parameters affecting drinking water consumption, the number of subscribers significantly affected the water consumption rate, while the average temperature was the least significant factor. Water price was a factor that could be easily controlled, but it was always one of the least effective parameters due to the low water fee.

Rapid, accurate and serotype independent pipeline for in silico epitope mapping of SARS-CoV-2 antigens: a combined machine learning and Chou’s pseudo amino acid composition method

Here,a new integrated machine learning and Chou’s pseudo amino acid composition method has been proposed for in silico epitope mapping of severe acute respiratorysyndrome-like coronavirus antigens.For this,a training dataset including 266 linear B-cell epitopes,1,267 T-cell epitopes and 1,280 non-epitopes were prepared.The epitope sequences were then converted to numerical vectors using Chou’s pseudo amino acid composition method.The vectors were then introduced to the support vector machine,random forest,artificial neural network,and K-nearest neighbor algorithms for the classification process.The algorithm with the highest performance was selected for the epitope mapping procedure.Based on the obtained results,the random forest algorithm was the most accurate classifier with an accuracy of 0.934 followed by K-nearest neighbor,artificial neural network,and support vector machine respectively.Furthermore,the efficacies of predicted epitopes by the trained random forest algorithm were assessed through their antigenicity potential as well as affinity to human B cell receptor and MHC-I/II alleles using the VaxiJen score and molecular docking,respectively.It was also clear that the predicted epitopes especially the B-cell epitopes had high antigenicity potentials and good affinities to the protein targets.According to the results,the suggested method can be considered for developing specific epitope predictor software as well as an accelerator pipeline for designing serotype independent vaccine against the virus.

Wettability alteration and oil recovery by spontaneous imbibition of smart water and surfactants into carbonates

Naturally fractured carbonate reservoirs have very low oil recovery efficiency owing to their wettability and tightness of matrix.However,smart water can enhance oil recovery by changing the wettability of the carbonate rock surface from oilwet to water-wet,and the addition of surfactants can also change surface wettability.In the present study,the effects of a solution of modified seawater with some surfactants,namely C12 TAB,SDS,and TritonX-100(TX-100),on the wettability of carbonate rock were investigated through contact angle measurements.Oil recovery was studied using spontaneous imbibition tests at 25,70,and 90°C,followed by thermal gravity analysis to measure the amount of adsorbed material on the carbonate surface.The results indicated that Ca2+,Mg2+,and SO42-.ions may alter the carbonate rock wettability from oil-wet to water-wet,with further water wettability obtained at higher concentrations of the ions in modified seawater.Removal of NaCl from the imbibing fluid resulted in a reduced contact angle and significantly enhanced oil recovery.Low oil recoveries were obtained with modified seawater at 25 and 70°C,but once the temperature was increased to 90°C,the oil recovery in the spontaneous imbibition experiment increased dramatically.Application of smart water with C12 TAB surfactant at 0.1 wt%changed the contact angle from 161°to 52°and enhanced oil recovery to 72%,while the presence of the anionic surfactant SDS at 0.1 wt%in the smart water increased oil recovery to 64.5%.The TGA analysis results indicated that the adsorbed materials on the carbonate surface were minimal for the solution containing seawater with C12 TAB at 0.1 wt%(SW+CTAB(0.1 wt%)).Based on the experimental results,a mechanism was proposed for wettability alteration of carbonate rocks using smart water with SDS and C12 TAB surfactants.

Effects of Persian turpentine tree litter and slope aspect on soil chemical properties in a Zagros forest,Iran

For analyzing the effects of forest litter and slope aspect on soil properties eight soil samples were collected at a depth of 0–10 cm near(i.e.,beneath the crown)and away from(i.e.,not influenced by crown)five Persian turpentine trees each on a north and a south slope at the same elevation in a Zagros forest,Iran.The litter beneath tree crowns and slope exposure were found to have significant interactive effects on C,N,P,K,and electrical conductivity of the soils,however,Ca,Mg and the soil pH were not significantly influenced by these factors.The soil beneath the crowns was enriched in cations compared to more distal positions.Generally,Persian turpentine trees have positive impacts on soil properties in the forest.Degrading or killing these trees by sap extraction,extreme grazing,cutting,fire and expansion of agriculture will lead to significant losses in soil fertility and increases in soil erosion.

Effect of land-use changes on chemical and physical properties of soil in western Iran(Zagros oak forests)

The consequence of land-use change from forest to agriculture and other uses has become one of the world’s greatest concerns.The soil,one of the most important components of forests and containing all the required plant nutrients as soluble ions,is highly impacted by these changes.Because vast areas of the Zagros forests in western Iran have changed in use during the last few decades,the present study investigated the effects of landuse changes of forest area to agriculture,orchard,and agroforestry on soil chemical and physical properties.Soil was sampled at four land-use areas:less-disturbed forest areas(control)and agricultural,orchard,and agroforestry areas.Among each of the two forest-use areas(agroforestry and orchard),we selected five trees with similar-sized crowns and sampled under each tree crown at 0-15 and>15-30 cm depths.Five soil samples also were taken in agriculture area at each depth.The findings indicated that during land-use changes,soil sand particles decreased,and clay and silt particles of soil increased,resulting in a fine soil texture.Moreover,the amount of nitrogen(N),phosphorus(P),organic carbon(OC),and electrical conductivity(EC)of soil decreased at both depths due to the decrease in organic matter.Soil pH and magnesium(Mg)level rose during land-use change at both depths except at agricultural sites.Soil potassium(K)content decreased during agricultural use due to the elimination of tree cover.The level of K decreased only at the depth of 0-15 cm because of K dependency on parent materials.Generally,most soil nutrients were affected by plant removal in the conversion.Forest and agricultural soil are distinguishable by their properties,while land-uses such as agroforestry-orchard separated from the others.Soil nutrients were severely affected by the decrease and elimination of tree cover,plowing,and continuous harvesting,resulting in a decline in soil quality and fertility.

Diversity of woody plant species and their relationship to physiographic factors in central Zagros forests (Case study： Perc forest, Khorramabad, Iran)

Topography is the most factor that has the greatest impact of all factor that affect the distribution. To study the diversity of trees and shrub species in the Perc forest situated in Khorramabad, Lorestan, 140 circular plots of 1200 m2 in a grid of 300 m × 250 m were surveyed, using a systematic random sampling method. In each plot, the Margalef richness index, Shannon-Wiener diversity index, Hill＇s N1 and Simpson indices and the evenness index of Simpson and Smith-Wilson were calculated and ordered on the basis of different classes of elevation, exposition and slope. The results indicated that slope did not have any significant effect on the indices. Exposition and elevation classes significant impacted the richness and diversity indices, but did not influence evenness. In general, the highest plant diversity was observed for slopes less than 15 %, northern aspects, without geographical direction, and elevations of 2100-2200 m. This information can be very useful in achieving the goals for sustainable management of forests. In addition to greater protection for regions with high diversity and reforestation （compatible species） in degraded area, we can help increase diversity in forests.

Antibacterial effect and physicochemical properties of essential oil of Zataria multiflora Boiss

ObjectiveTo evaluate the antibacterial effect and physicochemical properties of essential oil of Zataria multiflora Boiss.MethodsAntibacterial activity of essential oil of Zataria multiflora Boiss was assessed by agar disc diffusion and minimal inhibitory concentration(MIC) was tested by E test.ResultsThe essential oil of Zataria multiflora Boiss was effective on pathogenic bacteria particularly Staphylococcus aureus (S. aureus). The MIC values of the target cultures ranged from 0.39 mg/mL to 1.56 mg/mL. The physicochemical properties like effects of pH, temperature, detergents, and enzymes on the activity of essential oil from Zataria multiflora Boiss were also determined. The essential oil was quite stable to temperature as tested against S. aureus and Escherichia coli (E. coli). The essential oil was very stable over a wide range of pH. The antibacterial activity of essential oil was insensitive to various protein-denaturing detergents (Such as Tween 80, Tween 20, Triton 100, etc.) and enzymes (namely proteinase K, trypsin, lipase, and lysosyme).ConclusionsA potential use of the essential oil from Zataria multiflora Boiss is suggested. More studies including further purification, mass spectra, nuclear magnetic resonance (NMR) and evaluation of toxicity are needed for confirmation of this suggestion.

p-Toluenesulfonyl chloride as a new and effective catalyst for acetylation and formylation of hydroxyl compounds under mild conditions

The catalytic application of p-toluenesulfonyl chloride for efficient acetylation of various types of alcohols and phenols with acetic anhydride in solvent-free conditions is reported.Also structurally diverse alcohols were formylated using formic acid based on the use of catalytic amount of p-toluenesulfonyl chloride under solvent-free condition.The reactions were carried out in short reaction time and in good to excellent yields at room temperature.

ADDITIVE MAPS ON SOME OPERATOR ALGEBRAS BEHAVING LIKE(α, β)-DERIVATIONS OR GENERALIZED(α, β)-DERIVATIONS AT ZERO-PRODUCT ELEMENTS

Let A be a subalgebra of B（X） containing the identity operator I and an idempotent P. Suppose that α,β： A →A are ring epimorphisms and there exists some nest N on 2（ such that α（P）（X） and β（P）（X） are non-trivial elements of N. Let A contain all rank one operators in AlgN and δ ： A→ B（X） be an additive mapping. It is shown that, if δ is （α, β）-derivable at zero point, then there exists an additive （α, β）-derivation τ ： A →β（X） such that δ（A） =τ（A） ＋ α（A）δ（I） for all A∈A. It is also shown that if δ is generalized （α,β）-derivable at zero point, then δ is an additive generalized （α, β）-derivation. Moreover, by use of this result, the additive maps （generalized） （α,β）-derivable at zero point on several nest algebras, are also characterized.

Deep learning neural networks for spatially explicit prediction of flash flood probability

Flood probability maps are essential for a range of applications,including land use planning and developing mitigation strategies and early warning systems.This study describes the potential application of two architectures of deep learning neural networks,namely convolutional neural networks(CNN)and recurrent neural networks(RNN),for spatially explicit prediction and mapping of flash flood probability.To develop and validate the predictive models,a geospatial database that contained records for the historical flood events and geo-environmental characteristics of the Golestan Province in northern Iran was constructed.The step-wise weight assessment ratio analysis(SWARA)was employed to investigate the spatial interplay between floods and different influencing factors.The CNN and RNN models were trained using the SWARA weights and validated using the receiver operating characteristics technique.The results showed that the CNN model(AUC=0.832,RMSE=0.144)performed slightly better than the RNN model(AUC=0.814,RMSE=0.181)in predicting future floods.Further,these models demonstrated an improved prediction of floods compared to previous studies that used different models in the same study area.This study showed that the spatially explicit deep learning neural network models are successful in capturing the heterogeneity of spatial patterns of flood probability in the Golestan Province,and the resulting probability maps can be used for the development of mitigation plans in response to the future floods.The general policy implication of our study suggests that design,implementation,and verification of flood early warning systems should be directed to approximately 40%of the land area characterized by high and very susceptibility to flooding.

Effect of trapezoidal collars as a scour countermeasure around wing-wall abutments

Local scour around bridge abutments is a widespread problem that can result in structural failure. Collars can be used as a countermeasure to reduce the scour depth. In this study, the temporal scour development around a wing-wall abutment was investigated with and without collars. The tests were carried out under clear-water conditions for different abutment lengths, with collars of different sizes placed at the bed level. When no collar was used in the experiments, 70% of the maximum scour depth occurred in less than 2 h. However, when a collar with a width greater than the length of the abutment was used, no scour was observed for up to 200 min from the beginning of the experiments. The results show that an increase in the collar width not only led to a lag time for the onset of scouring but also reduced the maximum scour depth. Moreover, an increased collar width led to a better performance in mitigating scouring around smaller abutments. Generally, the scour depth decreased by 9%-37% with different collar widths.

Exact Solutions of the Dirac Equation for an Electron in a Magnetic Field with Shape Invariant Method

Based on the shape invariance property we obtain exact solutions oI the Dirac equation for an electron moving in the presence of a certain varying magnetic field, then we also show its non-relativistic limit.

Introduce a Novel PCA Method for Intuitionistic Fuzzy Sets Based on Cross Entropy

In this paper, a new method for Principal Component Analysis in intuitionistic fuzzy situations has been proposed. This approach is based on cross entropy as an information index. This new method is a useful method for data reduction for situations in which data are not exact. The inexactness in the situations assumed here is due to fuzziness and missing data information, so that we have two functions (membership and non-membership). Thus, method proposed here is suitable for Atanasov’s Intuitionistic Fuzzy Sets (A-IFSs) in which we have an uncertainty due to a mixture of fuzziness and missing data information. For the demonstration of the application of the method, we have used an example and have presented a conclusion.