Nitrogen (N) is a key growth and yield-limiting factor in cultivated rice areas. This study has been conducted to evaluate the effects of different conditions of N application on rice yield and yield components (Shiroudi cultivar) in Babol (Mazandaran, Iran) during the 2015- 2016 season. A factorial experiment executed of a Randomized Complete Block Design (RCBD) used in three iterations. In the first factor, treatments were four N amounts (including 50, 90, 130, and 170 kg N ha-1), while in the second factor, the treatments consisted of four different fertilizer splitting methods, including T1:70 % at the basal stage + 30 % at the maximum tillering stage, T2:1/3 at the basal stage + 1/3 at the maximum tillering stage + 1/3 at the panicle initiation, T3: 25 % at the basal stage + 50 % at the maximum tillering stage + 25 % at the panicle initiation, and T4: 25 % at the basal stage + 25 % at the maximum tillering stage + 50 % at the panicle initiation. The results illustrate only the number of panicles (m2) which was significantly impacted by the year (at the CI of 0.99). Different levels of N had effects on the panicle length, the percentage of filled grain (PFG), whole grain in a plant, and yield (at the CI of 0.95). The panicle length, the PFG, and yield were also significantly affected by different methods of N splitting (at the P-v of 0.01). The interaction of N amount × N splitting had a significant effect on the panicle length, the PFG, and yield (at the CI of 0.95). In general, the most significant impact on the panicle length, the number of panicles (m2), the whole plant's grain, and yield observed after using 130 kg N ha-1. Besides, T3 showed the most notable effect on all the studied indices except for the panicle length.
In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of ho
... Show MoreRM Abbas, AA Abdulhameed, AI Salahaldin, International Conference on Geotechnical Engineering, 2010
This study focused on extracting the outer membrane nanovesicles (OMVs) from Escherichia coli BE2 (EC- OMVs) by ultracentrifugation, and the yield was 2.3mg/ml. This was followed by purification with gel filtration chromatography using Sephadex G-150, which was 2mg/ml. The morphology and size of purified EC-OMVs were confirmed by transmission electron microscopy (TEM) at 40-200 nm. The nature of functional groups in the vesicle vesicle was determined by Fourier transforms infrared spectroscopy (FT-IR) analysis. The antitumor activity of EC-OMVs was conducted in vitro by MTT assay in human ovarian (OV33) cancer cell line at 24,48 and 96hrs. The cytotoxicity test showed high susceptibility to the vesicles in ovarian compared to normal
... Show MoreAim: To evaluate the side effects of Tamsulosin hydrochloride in fertility of experimental rats. Materials and methods: three groups of mice were used. First and second groups were injected [intraperitoneal (I.P.)] daily for 42 with 8 and 16 µg /kg mouse body weight (kg.b.wt) of Tamsulosin hydrochloride, respectively. Third group was injected with PBS (control). Several biological and histopathological studies were conducted on rat groups. Results: Significant decrease in number, motility and viability of epididymal sperm post injection with 16 µg /kg.b.wt, while injection with 8 µg /kg.b.wt reduced significantly, percentage of viability of sperm as compared with the control group. High percentage of abnormal sperm was observed in mice t
... Show MoreBiometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in
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