The present study dealt with the morphological, anatomical,trichomespollen grains,and ecological characteristics of Caroxylon jordanicola (EigAkhani & Roalson (Amaranthaceae) in Al-Tar Caves, Karbala, Iraq which belongs to the Amaranthaceae family. The results of the present study demonstrated that There are distinctive characteristics of the studied species distinguish it from other species and facilitate its diagnosis. The sample was diagnosed using the taxonomic keys of the Iraqi flora and the flora of neighboring countriesIn addition to some available research. The results of the morphological and anatomical features investigation provide really significant taxonomical value to distinguish the species. The results that showe

A new Ni(II) nanostructured chelating system (DHN) was introduced for selective optical heavy-metal ion sensing in an aqueous medium. The cooperative chelating system comprising 8-hydroxyquinoline (8-HQ) and dimethylglyoxime (DMG) has been developed for the first time in association with fibre optic sensing for selective optical heavy-metal ion sensing in an aqueous medium. The Ni(II) nanocompound fluoresces upon 578 nm excitation, showing a highly sensitive optical response with a linear calibration curve in the range 0–100 ng/mL. The regression equation of the calibration curve is y = 0.0035x + 0.9990, which indicates very good linearity, implying R2 = 0.999 with high sensitivity (calibration slope of 0.0035) and low baseline noise (bla

The current paper investigates the effect of cut-out design parameters on load-bearing capacity and buckling behaviour of steel cylindrical shell using a nonlinear finite element analysis in modelling cylinder buckling under longitudinal compressive load. The effect of four geometry design parameters: shell diameter to thickness ratio, cut-out location, orientation, and size were investigated in this study. To enhance the prediction of buckling behaviour, both geometrical and material nonlinearities were considered. An ANSYS APDL code was written and tested by verifying its validity through comparison with former buckling study. The results showed that changing the cut-out location from mid-height of the cylindrical shell towards a

Identifying the total number of fruits on trees has long been of interest in agricultural crop estimation work. Yield prediction of fruits in practical environment is one of the hard and significant tasks to obtain better results in crop management system to achieve more productivity with regard to moderate cost. Utilized color vision in machine vision system to identify citrus fruits, and estimated yield information of the citrus grove in-real time. Fruit recognition algorithms based on color features to estimate the number of fruit. In the current research work, some low complexity and efficient image analysis approach was proposed to count yield fruits image in the natural scene. Semi automatic segmentation and yield calculation of fruit

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti