s. farzaneh

 Among abiotic stress factors, drought is one of the most detrimental factors in arid and semiarid regions, causing a significant decrease in plant growth and yield in most species, including crops. Under drought conditions, morphological, physiological, and biochemical characteristics are negatively affected. The detrimental impact of water scarcity may be mitigated through the utilization of plant growth-promoting rhizobacteria (PGPR) and nanoparticles (NPs) like nano iron-silicon oxide. PGPR species such as Azospirillum and Pseudomonas have been found to enhance hormonal balance, maintain nutrient levels, improve plant growth characteristics, and ultimately boost yield. Additionally, the application of NPs aids in enhancing plant growth under stressful conditions by facilitating water retention, fortifying membrane integrity, and enhancing nutrient and water uptake. Consequently, it is plausible that the combined application of PGPR and NPs could enhance triticale yield even in conditions of water limitation.

An experiment as factorial split-plot was conducted based on randomized complete block design with three replications at the research farm of the Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili in 2021. Different irrigation regimes in three levels (full irrigation as control, irrigation withholding at 50% of booting and heading stages as severe and moderate water limitation respectively (BBCH 43 and 55 codes respectively) were assigned to the main plots and the combination of bio fertilizers application in four levels (no application as control, application of Azospirilum, Pseudomonas, both application Azospirilum and Pseudomonas) and nanoparticles foliar application at four levels (foliar application with water as control, nano iron oxide foliar application (1 g.L-1), nano silicon oxide (50 mg.L-1), both application nano iron-silicon oxide) were assigned to the subplots. Psedomunas and Azospirilum were isolated from the rhizospheres of wheat by the Research Institute of Soil and Water, Tehran, Iran. For inoculation seeds were coated with gum Arabic as an adhesive and rolled into the suspension of bacteria until uniformly coated. The strains and cell densities of microorganisms used as PGPR in this experiment were 1×108 colony forming units (CFU). In each plot, there were five rows with two m long. In each experimental plot, two beside rows and 0.5 m from the beginning and end of planting lines were removed as margin, and measurements were done on three rows in the middle lines. The used nano silicon-iron oxide had an average particle size of less than 30 nm and the special surface of particles was more than 30 m2.g-1. They were product of Nanomaterial US Research which was provided by Pishgaman Nanomaterials Company of Iran. Nano silicon oxide and nano silicon oxide powder added to deionized water and was placed on ultrasonic equipment (100 W and 40 kHz) on a shaker for better solution. Foliar application of nano silicon-iron oxide was done in two stages of period growth BBCH 21 and 30 codes respectively. In this study, dry matter remobilization, volume and root dry weight, leaf area index (LAI), and grain yield of triticale were investigated. Analysis of variance and mean comparisons were performed using SAS ver 9.1. The main effects and interactions were tested using the least significant difference (LSD) test at the 0.05 probability level.

 The results showed that remobilization from the stem (22.75%) and total dry matter remobilization (21.36%) and contribution of these processes in grain yield (58.29 and 56.24% respectively) decreased in both application of PGPR and nano iron-silicon oxide foliar application under irrigation withholding at booting stage in compared to no application of bio-fertilizers and nanoparticles. Also, the application of PGPR and nanoparticles under irrigation withholding in the booting stage increased the root volume (44.68%), current photosynthesis (48.63), the contribution of photosynthesis contribution in grain yield (15.63%), LAI (32.82%), and grain yield in compared to no application of PGPR and nanoparticles under irrigation withholding at booting stage.

Based on the results of this study, it seems that the application of both PGPR and nanoparticles can be a suitable management factor to increase the grain yield of triticale under water-limited conditions.

Mass nonlinear dynamic analysis is unavoidable in many fields of earthquake and structural engineering, such as incremental dynamic analysis, probabilistic performance-based design, and optimization approaches. Using simplified models with fewer degrees of freedom instead of detailed original models to a great extent reduces the computational cost and prevents extremely time-consuming analysis. Among different simplified models for steel moment frames, stick models (such as shear beam models) only use the global story stiffness to estimate the original model responses, which do not consider the structural configuration. The stick models are only suitable for obtaining the general responses of the structure, such as global and interstory drift. However, simplified frame models are the more accurate simplified models that consider the details of the original frame, such as beam and column elements, nonlinear plastic hinge springs, and joint rotations. Substitute Frame is one of these models, which is a one-bay frame that predicts the structural responses for concrete and steel moment frames with very high accuracy. The purpose of this research is to develop a substitute frame model for steel moment frames with unequal bay lengths. For this purpose, the beam stiffness and nonlinear behavior of rotational springs were modified based on linear and nonlinear structural analysis approaches and the proposed model is called Modified Substitute Frame. In the following, to evaluate the accuracy of the proposed model, three types of 12-story buildings with unequal bay lengths were designed using ASCE7-16 and AISC 341-16 criteria and subjected to three different ground motion data sets, i.e., far field, near field with pulse and without pulse ground motions. The nonlinear time history analysis results showed that the Modified Substitute Frame predicts the original frame responses with very high accuracy. Moreover, the Modified Substitute Frame prediction was more precise than the Improved FishBone model which was recently presented for moment frames with unequal bay lengths.

Salinity stands as a significant environmental stressor that profoundly curtails the growth and yield of crop plants. This adversity also extends to the impairment of pigments and plastids, leading to diminished chlorophyll indices, rates, and grain-filling durations. To counteract the deleterious impact of such stressors on plant growth, a spectrum of strategies has been devised. Prominent among these strategies are plant growth-promoting rhizobacteria, exemplified by azospirillum, and the utilization of nanoparticles like zinc and silicon. These factors play a pivotal role in elevating yield outcomes. Zinc's pivotal involvement spans protein metabolism, photosynthetic activities, and diverse physiological traits within plants. Particularly noteworthy is its contribution to rectifying zinc deficiency, a particularly critical concern in plants cultivated in high-pH soils. Notably, recent research has illuminated the potential of applying minute quantities of micronutrients, notably zinc via foliar spraying, in bolstering plant resilience against salt stress. Likewise, silicon emerges as a supplemental micronutrient that imparts heightened resistance to environmental stresses, fostering increased resilience within biological systems. Therefore, this study aimed to evaluate the effects of application of plant growth-promoting rhizobacteria and nanoparticles (zinc and silicon) on the yield, photosynthetic pigments, and filling components of triticale grain under salt stress.

This experiment was conducted as factorial based on a randomized complete block design with three replications in greenhouse research of the Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili in 2022. Factors experimental included salinity at three levels (no salinity as control, application of 60, 120 mM salinity) by NaCl, application of PGPR at two levels (no inoculation as control and seed inoculation with Azospirillium), and foliar application of nanoparticles at four levels (foliar application with water as control, foliar application of 0.8 g.L-1 nano zinc oxide, foliar application 50 mg.L-1 nano silicon, foliar application both of nano zinc oxide (0.4 g.L-1) and nano silicon (25 mg.L-1). The strains and cell densities of microorganisms used as PGPR in this experiment were 1×107 bacteria per milliliter (107 cfu.ml−1). A two-part linear model was used to quantify the grain-filling parameters. In this study, grain dry weight and number were used to calculate the average grain weight for each sample. Total duration of grain filling was determined for each treatment combination by fitting a bilinear model:    GW =where GW is the grain dry weight; a, the GW-intercept; b, the slope of grain weight indicating grain filling rate; t, the days after earring; and t0, physiological maturity. The effective grain filling period (EGFD) was calculated from the following equation:EGFD = the highest grain weight (g)/rate of grain filling (g day-1).

The results showed that application of Azospirillium and foliar application of nano zinc-silicon oxide under no salinity increased chlorophyll a (38.42%), chlorophyll b (41.76%), total chlorophyll (39.39%), carotenoids (53.99%), root weight (62.61%), grain filling rate (16.37%), grain filling period and effective grain filling period (21.28 and 29.78%) and grain yield (47.23%) in compared to no application of Azospirillium and nanoparticles under 120 mM salinity. Application of Azospirillium and foliar application nano zinc-silicon oxide under 60 mM salinity also increased chlorophyll a (31.4%), chlorophyll b (34.35%), total chlorophyll (32%), carotenoids (45.68%), root weight (57.14%), grain filling rate (15.21%), grain filling period and effective grain filling period (21.29 and 28.16%) and grain yield (35.67%) in compared to the application of Azospirillium and nanoparticles under 120 mM salinity. According to this study, application of Azospirillium and nanoparticles (zinc and silicon) can increase yield of triticale grain under salinity stress such as no salinity due to the improvement of photosynthetic pigments content and grain filling components.

In arid and semi-arid regions, drought stress as the main factor and salinity stress as a secondary factor decreases plant growth and yield. Water limitation can damage pigments and plastids, and reduce chlorophyll index, rate, and grain filling period. Several strategies have been developed to decrease the toxic effects caused by environmental stresses on plant growth. Among them, the use of bio-fertilizers such as plant growth-promoting rhizobacteria (PGPR) and also nanoparticles such as nano iron-silicon oxide plays a very important role in yield improvement. Inoculation of plants with native suitable microorganisms may decrease the deleterious effects of environmental stresses and increase stress tolerance of plants by a variety of mechanisms, including synthesis of phytohormones such as auxins, cytokinin, and gibberellins, solubilization of minerals like phosphorus, production of siderophores and increase in nutrient uptake, N2 fixation. It seems that application of nanoparticles and biofertilizers can improve triticale yield under water limitation conditions.

To study the effects of bio-fertilizers and nano silicon-iron oxide on the quantitative yield and grain-filling components of triticale under water limitation conditions, a factorial experiment was conducted based on randomized complete block design with three replications at the research farm of the faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili during 2021. The experimental factors included irrigation in three levels (full irrigation as control, irrigation withholding at 50% of the heading stage based on codes 43 of the BBCH scale; irrigation withholding at 50% of the booting stage based on codes 55 of the BBCH scale), as severe and moderate water limitation respectively, application of biofertilizers in four levels (no application of biofertilizers as control, application of Azospirilum, Pseudomonas, both application Azospirilum and Pseudomonas) and nanoparticles foliar application at four levels (foliar application with water as control, nano iron oxide foliar application, nano silicon, both foliar application nano iron-silicon oxide). The strains and cell densities of microorganisms used as PGPR in this experiment were 108 bacteria per milliliter (108 cfu.ml−1). A two-part linear model was used to quantify the grain-filling parameters. In this study, anthocyanin, flag leaf protein, chlorophyll index, grain filling components, and yield of triticale were investigated. Chlorophyll Index was calculated by a chlorophyll meter (SPAD-502; Konica Minolta Sensing, Inc., Japan). Grain dry weight and number were used to calculate the average grain weight for each sample. The total duration of grain filling was determined for each treatment combination by fitting a bilinear model: 
Where GW is the grain dry weight; a, the GW-intercept; b, the slope of grain weight indicating grain filling rate; t, the days after earring; and t0, physiological maturity. The effective grain filling period (EGFD) was calculated from the following equation:EGFD = the highest grain weight (g)/rate of grain filling (g day-1).

The results showed that the both application of biofertilizers and foliar application of nano iron-silicon oxide in full irrigation, increased maximum grain weight (56.07%), grain filling period, and Effective grain filling period (22.29 and 48.43% respectively), chlorophyll index (45.11%) and flag leaf protein (64.75%), plant height (49.31%), number of grains per spike (70.58%), spike length (53.75%), 1000 grains weight (64.9%) and grain yield (43.28%) in compared to no application of biofertilizers and no foliar application under severe water limitation. Severe water limitation increased the content of anthocyanin, but the application of biofertilizers and foliar application of nano silicon-iron oxide decreased its content.

Based on the results of this study, it seems that application of both applications of Azospirilum and Pseudomonas and foliar application of nano iron-silicon oxide can be applied as a proper method for increasing grain yield of triticale under water limitation conditions.

In order to study the effects of nanoparticles and biofertilizers on chlorophyll fluorescence indices and some physiological traits of triticale (Triticosecale Wittmack) under salinity stress, a factorial experiment was conducted based on a randomized complete block design with three replications in the research greenhouse of Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardebili in 2021. Experimental factors included salinity (non-saline control, 35, and 70 mM NaCl), application of biofertilizers (PGPR) (biofertilizers-free control, application of Azospirilum, Pseudomonas, combined application Azospirilum and Pseudomonas) and nanoparticles foliar application (foliar application with water as control, nano iron oxide foliar application, nano silicon, combined foliar application of nano iron-silicon oxide). The results showed that both application of PGPR and foliar application of nanoparticles under non-saline condition increased quantum yield (64%), maximum fluorescence (69%), variable fluorescence (175%), chlorophyll index (48.1%), leaf nitrogen content (35.3%), leaf relative water content (49.7%) and stomatal conductance (81.4%) and grain yield per plant (44.5%) in comparison with biofertilizers-free and nanoparticles foliar application under 70 mM salt condition. Maximum of minimum fluorescence (178) and electrical conductivity (126) were obtained at the highest salinity level, i.e. 70 mM NaCl. Based on the results of this study, it seems that application of bio fertilizers and nanoparticles foliar application may improve the grain yield of triticale under salinity stress.

In recent years, dynamic analysis has been considered as an appropriate tool in the earthquake engineering field. On the other hand, the number of analyzes required in the research and design field has grown. So, in some fields of research with a probabilistic approach, resilience or optimization, requires extensive nonlinear dynamic analyses. Performing such a mass analysis has a very high computational cost and requires a lot of analysis time. One of the practical solutions to this problem is the use of simplified models that significantly reduce the total analysis time with appropriate and acceptable accuracy compared to the detailed model. In this research, in order to determine the collapse margin ratio of structures, three 8-,12-, and 20- story buildings have been considered. By performing the incremental dynamic analysis (IDA) on the detailed model and the substitute frame model, their collapse intensities and collapse margin ratio have been calculated. The results show that the substitute frame model determines the collapse margin ratio with an error rate of 3%, and also reduces the analysis time by an average of 2/5%.

Nowadays, geodetic networks have a significant contribution in safety during constructing and operation in urban constructions. They could prevent a terrible disaster by detecting and alarming any displacement in important        constructions. The detection of unstable and stable points is an essential part in computing displacement in geodetic network, because misdetection leads to datum defect in geodetic network. Then, the detected displacement will be questionable. In order to detecting stable and unstable points usually two important methods are used:A. General  stability test in geodetic networks, B. Minimizing the norm of displacement vectors. The main goal of this paper is the comparison between two mentioned methods and  assessing their advantage and disadvantage.

Global Positioning System (GPS) receivers in gravimetric satellites continuously measure valuable information about 3D satellite position. However، the velocity of satellites، which has important applications in the satellite geodesy such as gravity field recovery، cannot be directly measured. These data are used in the energy integral method or other methods based on the Earth gravity field motion equation to determine the velocity or acceleration of satellite. In this study، the velocity vector is computed using the numerical differentiation and the Kalman filtering for the Gravity Recovery And Climate Experiment (GRACE) twin satellites. The Numerical results show that the Kalman filtering yields more accurate results than numerical differentiation when they are compared with the intersatellite range-rate measurements. In the wake of the New Gravity Satellite era due to the launch of ChAllenging Minisatellite Payload (CHAMP)، GRACE and GOCE، processing methods of enormously large orbit data has become the focus of the geodetic interest. The input data are different from earlier times as they contain some millions of continuous position data per satellite per year. The huge number of data arises from continuous observation from these satellites to the GPS system. This can be done due to the much higher altitude of the GPS satellites (20،000 km) compared to that of the gravity satellites (between 250 and 500 km). The latter is often referred to as Low Earth Orbiter، i. e. LEO. The GPS-LEO constellation as described above in technical terms is called High-Low Satellite to Satellite Tracking (High-Low SST). Thus some million position-data of the LEOs are the basis of the global gravity field determination techniques. The concept behind the Solutions is that satellites are in free-fall in the gravity field of the Earth. After modeling and removing all further force sources (e. g. gravitation of the Sun and the Moon and other planets، direct and indirect tides، surface forces (atmospheric drag، solar radiation pressure)) the remaining orbit is a trajectory in space، which is governed purely by the gravity field of the Earth. Therefore، the task is only to determine the force behind the motion. Conservation laws can be applied for satellites successfully. The Newton’s equation of law states the conservation of forces in a closed system. Applying it for a satellite requires information of the acceleration along the orbit. In this article the velocity vector is derived as a part of the unknown vector in Kalman filter algorithm. Kalman filter is a well-known mathematical tool، which gives the answer to the most frequent engineering question: how can we get the best estimate of the system state from the noisy measurements? The Kalman filter is a data processing algorithm that estimates the state of a system from noisy measurements using least-squares. It gives the optimal system state estimate together with a measure of how precise is the state estimate compared to true state. The Kalman filter performs optimal solution for a linear process with uncorrelated، white، zero mean Gaussian process and measurement disturbances. The Kalman filter is a “one-step back recursive filter”، meaning that there is no need to store past measurements for the purpose of computing the present time. We assume that the discrete random kinematic process to be estimated can be modeled with two main Kalman filter equations: Process equation Measurement equation Where x is the system state vector، A is the state transition matrix and W is the process noise. From this discrete time linear formation of the Kalman filter، the discrete time nonlinear formation of the Extended Kalman Filter is based. For the state space model for the Extended Kalman Filter (EKF)، the above linear equations are replaced by one nonlinear function: In this study، the velocity vector is computed using numerical differentiation and the Kalman filtering for the GRACE twin satellites. The numerical analysis shows that the Extended Kalman filtering yields the optimal solution. The comparison is performed based on the intersatellite range-rate measurements.

In order to investigate the competition effect and yield of two soybean cultivars in pure stand and intercropping systems, a factorial experiment based on randomized complete block design with three replications was conducted in field, 22 kilometers from Gorgon-Sari in 2002. Factors were: soybean cultivars Pershing and Williams with three densities (40, 50 and 60 plants m-2) and six levels of planting patterns of Pershing-Williams(0:100, 20:80, 40:60, 60:40, 80:20, 100:0). The competition models of reverse productivity for Willims and Pershing in pure stand was Cayera equation and for intercropping were Shenozoki and Cayera equations. The reverse productivity of single plant in pure stand in both cultivars had a linear relationship with plant density. The results showed that productivity of Williams single plant was equal to 1.2385 of Pershing and the single plant productivity of Pershing was equal to 0.9212 of Willims. The intracultivar competition in Willims was more than intercultivar competition, while in Pershing it was vice versa. The differences between inverse productivity of single plant of Williams in pure cultivation and intercropping was very low. But in Pershing this difference was relatively high, which shows that Willims cultivar is more competitive than Pershing. The highest yield was obtained at the ratio of 40:60 with 50 plantsm-2 and land equivalent ratio of 1.21.

In order to examine drought tolerance of cotton genotypes at seedling growth stage, an experiment was conducted in greenhouse using 40 cotton genotypes and three drought levels (-1, -4 and -8 bars) in factorial arrangement with 3 replications and a randomized complete block design. Matric potentials were created based on soil moisture release curve. Percentage emergence, emergence rate, leaf number, leaf area, total dry weight (root and shoot) and root/ shoot ratio were evaluated as affected by metric potentials. Results showed that all traits, except root/ shoot ratio, were decreased with increase in drought stress. Among the measured traits, leaf area was more sensitive and decreased greatly. Drought stress increased root/ shoot ratio, so that the greatest values were obtained at-8 bar. Overall, the genotypes Bulgar 433, Tabeladila and N.O.200 at emergence stage and the genotypes Siokra, Barbadens, Bulgar 433 and Tabeladila at seedling growth stage were the most tolerant, while the genotypes Narabry and Sahel at emergence stage and Narabry, N.O. 259 and Delta pine at seedling growth stage were the most sensive genotypes.