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bsj-7825
Predict the Laser Power and Recovery Period in Treatment by Endovenous Laser Ablation (EVLA)
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            Eight patients (3 male and 5 female) were treated in this study by Endovenous Laser Ablation (EVLA); Mathematical models are proposed to estimate the applied laser power and to assess the recovery period. The estimations of the applied laser power and recovery period in these models will be depended mainly on the diameter of the incompetent vein.  In addition, Excel Program was utilized to find the proposed models.  A 1470 nm diode laser up to 15W continuous power (CW) was used in the treatment of venous ulcers by EVLA procedure. Following up by duplex ultrasound was started in the 1st week after the first session until the vein is completely closed. The present study concluded that the relationship both between the applied laser power and recovery period with diameter is directly linear. The mathematical results obtained from the two mathematical proposals are consistent with the clinical results

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Publication Date
Sun Dec 20 2020
Journal Name
Journal Of Global Pharma Technology
Synthesis, Characterization, Antibacterial and Antifungal Activity of Some Bis (1, 3, 4-oxadiazole) Polymer
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Pyridine-2, 6-dicarbohydrazide comp (2) was synthesized from ethanolic solution of diethyl pyridine-2, 6- dicarboxylate comp (1) with excess of hydrazine hydrate. Newly five polymers (P1-P5) were synthesized from reaction of pyridine-2, 6-dicarbohydrazide comp (2) with five different di carboxylic acid in the presence of poly phosphoric acid (PPA). The antibacterial activity of the synthesized polymers was screened against some gram positive and gram negative bacteria. Antifungal activity of these polymers was evaluated in vitro against some yeast like fungi such as albicans (candida albicans). Polymers P3, P4 and P5 exhibited highest antibacterial and antifungal against all microorganisms under test.

Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Network Self-Fault Management Based on Multi-Intelligent Agents and Windows Management Instrumentation (WMI)
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This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

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Publication Date
Wed Jul 01 2026
Journal Name
South African Journal Of Chemical Engineering
Enhancement of water-based drilling fluid using novel composite of silica and alumina nanoparticles
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One of the most recent research areas in subsurface applications, including well drilling, is the use of eco-friendly and sustainably synthesized nanoparticles to improve drilling fluid efficiency. Typically, Shale formations present significant challenges to traditional drilling fluids, including fluid infiltration and shale swelling, which jeopardize wellbore stability. Although water-based drilling fluids (WBM) are environmentally preferred, their performance often requires enhancement through advanced additives. This study thus examines the synthesis of silica (SiO₂) and alumina (Al₂O₃) nanoparticles (NPs) using sustainable methods, employing Iraqi bentonite for silica and recycled aluminum scrap for alumina, to improve WBM effici

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Publication Date
Tue May 12 2026
Journal Name
Geomatics
Semantic Mapping of Urban Mobile Mapping LiDAR Using Panoramic OCR and Geometric Back-Projection
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This paper presents a deterministic system that combines textual semantic data from panoramic images with LiDAR point clouds in a mobile mapping setup. Urban scenes often include textual elements, such as signs and business names, that provide key details typically missing from LiDAR-based urban digital twins. The presented method uses deep learning-based OCR to extract text from street panoramas and then categorizes it into urban types using a rule-based classifier. Text regions are geometrically projected into the LiDAR environment by converting image coordinates into viewing rays that intersect LiDAR surfaces, such as facades. Data from multiple panoramas are merged with confidence-weighted spatial clustering to produce consisten

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Publication Date
Tue May 13 2025
Journal Name
Journal Of Robotics And Control (jrc)
Bipedal Robots: A Systematic Review of Dynamical Models, Balance Control Strategies, and Locomotion Methods
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Bipedal robots, designed to replicate human locomotion, face significant balance challenges due to instability and high degrees of freedom. This study examines dynamical models, balance control strategies, and locomotion methodologies. Dynamical models are categorized into simplified, centroidal dynamics, and whole-body dynamics models. Simplified models, such as the Linear Inverted Pendulum Model (LIPM), approximate the robot as a point mass at the Center of Mass (CoM) but neglect upper-body dynamics and complex terrain interactions. Centroidal dynamics models incorporate CoM motion, contact forces, and angular momentum for improved disturbance rejection but require extensive computational resources. Whole-body models achieve high

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Publication Date
Fri Apr 01 2022
Journal Name
Dental Hypotheses
Evaluation of Friction and Surface Characteristics of Two Types of Self-Ligating Bracket Gate
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Introduction:

Frictional forces generation during orthodontic treatment with fixed appliances impedes appropriate tooth movement; hence, research is ongoing to explore “frictionless” techniques. This in vitro study compares Damon Q and Pactive self-ligating metallic brackets in terms of friction and surface characteristics of the bracket gates when using CuNiTi archwires during leveling and alignment stage and examines the effects of aging conditions on frictional force generation.

Methods:

A total of 108 metallic s

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Publication Date
Fri Dec 02 2022
Journal Name
International Journal Of Corrosion And Scale Inhibition
Anticorrosion, antimicrobial and antioxidant study of ZnO nanoparticles synthesized from Punica granatum (Pomegranate) extract
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Metal and metal oxide NPs have shown to be perfectly synthesized by using plant extracts with high efficiency, low cost and low toxicity. Our goal was to synthesize ZnO NPs by using an extract of pomegranate seeds and investigate the anticorrosion, antimicrobial and antioxidant properties of the synthesized ZnO NPs. The results have shown that the use of pomegranate in the green synthesis of ZnO NPs gave a good yield, with a low cost and non-toxic approach. The electrophoretic deposition (EPD) was used to coat stainless steel (S.S) by synthesized ZnO NPs in an alcoholic solution at room temperature producing a good coating against corrosion. The corrosion properties were investigated in a saline solution and a temperature range of (293–32

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Publication Date
Tue Feb 21 2023
Journal Name
International Journal Of Operational Research
Aggregate production planning of Abu Ghraib Dairy factories based on forecasting and goal programming
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Publication Date
Tue Jun 24 2025
Journal Name
Baghdad Science Journal
Accelerating Face Mask Detection Training Model Based on Multi-GPUs and Multi-core CPU
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Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

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Publication Date
Thu Oct 03 2024
Journal Name
Pharmacia
Synthesis and preliminary antimicrobial evaluation of new 7-amino-4-methyl-coumarin thiazolidinone conjugates
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Abstract As a part of our ongoing project on the design and synthesis of new 4-thiazolidinone derivatives with antimicrobial activity, four new 4-thiazolidinone derivatives carrying bromo, nitro, methyl, and chloro groups on the benzene ring were synthesized by starting with the 7-amino-4-methylcoumarin moiety, linking coumarin with various phenyl isothiocynate to form the thiourea group, and then cyclizing the derivatives, characterized by IR and 1HNMR, and assayed in vitro for their antimicrobial activity against Gram positive and Gram negative bacteria and fungi. Overall, 2-(4-methyl-2-oxo-2H-chromen-3-yl)-3-(4-nitrophenyl) thiazolidin-4-one to be the most powerful individuals in the series. Based on the observed data, it can be sta

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