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Multi-objective optimization of the design parameters in longitudinal corrugated tubes to improve crashworthiness performance
Multi-objective optimization of the design parameters in longitudinal corrugated tubes to improve crashworthiness performance
Risk analysis of inflow to the Zayandehrud Dam under historical and future scenarios using reliability, resiliency, and vulnerability indicators: a comparative study of the runoff risk index and runoff risk ranking methods
Risk analysis of inflow to the Zayandehrud Dam under historical and future scenarios using reliability, resiliency, and vulnerability indicators: a comparative study of the runoff risk index and runoff risk ranking methods
Changes in Morphological, Physiological and Phytochemical Traits of Different Dill (Anethum graveolens L.) Cultivars as Affected by Light-Emitting Diodes
Changes in Morphological, Physiological and Phytochemical Traits of Different Dill (Anethum graveolens L.) Cultivars as Affected by Light-Emitting Diodes
Changes in Morphological, Physiological and Phytochemical Traits of Different Dill (Anethum graveolens L.) Cultivars as Affected by Light-Emitting Diodes
Genetic and Phenotypic Characterization of Botrytis Populations from Economic and Wild Host Plants in Iran
A machine learning-based framework for estimating fragility parameters in RC/MR frames considering seismic, structural, and site attributes
Assessment of environmental and health risks of potentially toxic elements associated with desert dust particles affected by industrial activities in Isfahan metropolitan
Assessment of environmental and health risks of potentially toxic elements associated with desert dust particles affected by industrial activities in Isfahan metropolitan
Lysophospholipid Supplementation in Broiler Breeders' Diet Benefits Offspring's Productive Performance, Blood Parameters, and Hepatic ?-Oxidation Genes
Using visible and near infrared spectroscopy and machine learning for estimating total petroleum hydrocarbons in contaminated soils
Using visible and near infrared spectroscopy and machine learning for estimating total petroleum hydrocarbons in contaminated soils
Using visible and near infrared spectroscopy and machine learning for estimating total petroleum hydrocarbons in contaminated soils