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Development of the Karun Macroinvertebrate Tolerance Index (KMTI) for semi-arid mountainous streams in Iran
Nanometric CrN/CrAlN and CrN/ZrN multilayer physical vapor deposited coatings on 316L stainless steel as bipolar plate for proton exchange membrane fuel cells
Nanometric CrN/CrAlN and CrN/ZrN multilayer physical vapor deposited coatings on 316L stainless steel as bipolar plate for proton exchange membrane fuel cells
Application of the most competent knowledge-driven integration method for deposit-scale studies
Electrophoretic deposition of chitosan reinforced baghdadite ceramic nano-particles on the stainless steel 316L substrate to improve biological and physical characteristics
Electrophoretic deposition of chitosan reinforced baghdadite ceramic nano-particles on the stainless steel 316L substrate to improve biological and physical characteristics
Electrophoretic deposition of chitosan reinforced baghdadite ceramic nano-particles on the stainless steel 316L substrate to improve biological and physical characteristics
Evaluation of Resistance to Abamectin in the Populations of Tuta absoluta (Lepidoptera: Gelechiidae), Collected from Isfahan Province, Iran
Predicting habitat suitability for the endangered species Hedysarum criniferum Boiss. using a fuzzy model in the semi-arid zone in Iran
Predicting habitat suitability for the endangered species Hedysarum criniferum Boiss. using a fuzzy model in the semi-arid zone in Iran
Predicting habitat suitability for the endangered species Hedysarum criniferum Boiss. using a fuzzy model in the semi-arid zone in Iran
Predicting habitat suitability for the endangered species Hedysarum criniferum Boiss. using a fuzzy model in the semi-arid zone in Iran
Phylogenetic Analysis of Phaeosphaeria Species Using Mating Type Genes and Distribution of Mating Types in Iran
Effects of different sources and spatial resolutions of environmental covariates on predicting soil organic carbon using machine learning in a semi-arid region of Iran
Effects of different sources and spatial resolutions of environmental covariates on predicting soil organic carbon using machine learning in a semi-arid region of Iran