LandSat Satellite ETM+ image have been analyzed to detect the different depths of regions inside the Tigris river in order to detect the regions that need to remove sedimentation in Baghdad in Iraq Country. The scene consisted of six bands (without the thermal band), It was captured in March ٢٠٠١. The variance in depth is determined by applying the rationing technique on the bands ٣ and ٥. GIS ٩. ١ program is used to apply the rationing technique and determined the results.

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

Background: Recent implant surgical approach aims to cause less trauma, invasiveness and pain as much as possible and to reduce patient and surgeon discomfort, time of surgery and time needed for functional implant loading. Flapless surgical techniques considered recently as one of the most popular techniques that may achieve these aims especially enhancing osseointegration and subsequently implant stability within less time than the traditional flapped surgical technique. So this study aimed to make a comparison between flapped and flapless surgical techniques in resulted implant stability according to resonance frequency analysis RFA and in duration of surgical operation. Materials and methods: A total of 26 patients with 41 implants (o

Background: Lowering the amount of iodinated contrast material and tube voltage may increase pulmonary artery opacification and thrombus identification without compromising picture quality.

Objectives: To explore the efficiency of using lower tube voltage and a lower contrast medium dose for conducting computed tomography for pulmonary angiography (CTPA) aiming to increase its accuracy in detecting pulmonary thromboembolism (PTE).

Subjects and Methods:100 patients scheduled for CTPA with a preoperative diagnosis of PTE were grouped into two: group A, (50 patients) got 1 mL/kg at 120 kV and group B, (50 patients) received 0.5 mL/kg at 80 kV.The tec

In this work, the possibility of a multiwavelength mode-locked fiber laser generation based on Four-Wave Mixing (FWM) induced by Fe2O3-SiO2 nanocomposite material is investigated for the first time. A multiwavelength mode-locked pulses fiber laser are generated from Ytterbium–doped fiber laser (YDFL) due to the combined action of high nonlinear absorption and high refractive coefficients of Fe2O3-SiO2 nanocomposite incorporated inside YDFL ring cavity. Up to more than 20 lasing lines in the 1040–1070 nm band with an equally lines separation of ~0.6 nm have been observed by just simple variation of passive modulation of the state of the polarization and the pump power altogether. Moreover, a passively mode-locked operation of YDFL laser

This is the first record of a new species of cyanobacteria Westiellopsis akinetica in the Iraqi environment, Samples were collected on June 2013 and the existence of it was not documented before. We isolated and purified this species ten years ago in Iraq, but we couldn't identify accurately based on all taxonomic handbooks. This is due to the species features being different from the other documented species in the available taxonomic lectures. It resembled many species by morphological characteristics such as Fischerella muscicola, Fischerella thermalis, Westiellopsis biateralis SA16. Westiellopsis interrupta, Westiellopsis persica SA33, Westiellopsis prolifica and Symphyonema bifilamentata. Describing a new species of the Westiellops

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte