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bsj-5920
Approximate Analytical Solutions of Bright Optical Soliton for Nonlinear Schrödinger Equation of Power Law Nonlinearity
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This paper introduces the Multistep Modified Reduced Differential Transform Method (MMRDTM). It is applied to approximate the solution for Nonlinear Schrodinger Equations (NLSEs) of power law nonlinearity. The proposed method has some advantages. An analytical approximation can be generated in a fast converging series by applying the proposed approach. On top of that, the number of computed terms is also significantly reduced. Compared to the RDTM, the nonlinear term in this method is replaced by related Adomian polynomials prior to the implementation of a multistep approach. As a consequence, only a smaller number of NLSE computed terms are required in the attained approximation. Moreover, the approximation also converges rapidly over a wide time frame. Two examples are provided for showing the ability and advantages of the proposed method to approximate the solution of the power law nonlinearity of NLSEs. For pictorial representation, graphical inputs are included to represent the solution and show the precision as well as the validity of the MMRDTM.

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Publication Date
Fri Feb 05 2021
Journal Name
Scientific Reports
Green Nanotechnology of MGF-AuNPs for Immunomodulatory Intervention in Prostate Cancer Therapy
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Abstract<p>Men with castration-resistant prostate cancer (CRPC) face poor prognosis and increased risk of treatment-incurred adverse effects resulting in one of the highest mortalities among patient population globally. Immune cells act as double-edged sword depending on the tumor microenvironment, which leads to increased infiltration of pro-tumor (M2) macrophages. Development of new immunomodulatory therapeutic agents capable of targeting the tumor microenvironment, and hence orchestrating the differentiation of pro-tumor M2 macrophages to anti-tumor M1, would substantially improve treatment outcomes of CRPC patients. We report, herein, Mangiferin functionalized gold nanoparticles (MGF-AuNPs) and its</p> ... Show More
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Publication Date
Wed Jan 15 2025
Journal Name
Human Antibodies
State of type 2 diabetic Iraqi patients after hospitalization for COVID-19
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Background

The coronavirus-19 (COVID-19) pandemic, triggered by the severe acute respiratory syndrome coronavirus 2, has affected over 100 million people and killed around 2 million individuals. One of the most common chronic illnesses in the world is diabetes, which greatly raises the risk of hospitalization and death for COVID-19 patients.

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This study aims to analyze the novel coronavirus's general characteristics and shed light on COVID-19 and its management in diabetic individuals by measuring some metabolic and inflammatory factors in type 2 diabetic pa

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Publication Date
Wed Jun 27 2018
Journal Name
Journal Of The College Of Education For Women
The uses of Iraqi women for Facebook and innovation made from them
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The problem of research is to identify the uses of Iraqi women for Facebook and the motives of these uses and the innovations that have been achieved from them, in view of the increasing role-played by social networking sites in the lives of individuals in general and women in particular.The research seeks to identify the following: Identify the extent to which Iraqi women use Facebook and the usage motives and innovations achieved by the interviewees When they using Facebook. This study belongs to the descriptive studies that are interested in monitoring the characteristics of a particular phenomenon to identify its characteristics and characteristics.This study adopted the survey methodology to test the hypotheses of the study and how

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Publication Date
Tue Sep 09 2014
Journal Name
Iosr Journal Of Mathematics (iosr-jm)
An Efficient Shrinkage Estimator for the Parameters of Simple Linear Regression Model
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Publication Date
Tue Feb 24 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Local drug delivery systems for treating periodontal diseases (A review of literature)
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In this review of literature, the light will be concentrated on the local drugs delivery systems for treating the periodontal diseases. Principles, types, advantages and indications of each type will be discussed in this paper.

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Publication Date
Sat Sep 01 2018
Journal Name
King's College London
A novel sol-gel silica formulation for management of methadone hydrochloride abuse
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Introduction: Methadone hydrochloride (MDN) is an effective pharmacological substitution treatment for opioids dependence, adopted in different countries as methadone maintenance treatment (MMT) programmes. However, MDN can exacerbate the addiction problem if it is abused and injected intravenously, and the frequent visits to the MMT centres can reduce patient compliance. The overall aim of this study is to develop a novel extended-release capsule of MDN using the sol-gel silica (SGS) technique that has the potential to counteract medication-tampering techniques and associated health risks and reduce the frequent visits to MMT centres. Methods: For MDN recrystallisation, a closed container method (CCM) and hot-stage method (HSM) were conduc

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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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Publication Date
Wed May 01 2024
Journal Name
Journal Of Testing And Evaluation
Univariate and Multivariate Exploration of Resilient Modulus for Warm Mix Asphalt Mixtures
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This paper predicts the resilient modulus (Mr) for warm mix asphalt (WMA) mixtures prepared using aspha-min. Various predictor variables were analyzed, including asphalt cement types, asphalt contents, nominal maximum aggregate sizes (NMAS), filler content, test temperatures, and loading times. Univariate and multivariate analyses were conducted to examine the behavior of each predictor variable individually and collectively. Through univariate analysis, it was observed that Mr exhibited an inverse trend with asphalt cement grade, NMAS, test temperature, and load duration. Although Mr increased slightly with higher filler and asphalt content, the magnitude of this increase was minimal. Multivariate analysis revealed that the rate of change

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Information Technology Management
The impact of social commerce determinants on social capital for energy sectors
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This study investigates the constructs and related theories that drive social capital in energy sector from the intention perspectives. This research uses theories of 'social support' and 'planned behaviour' alongside satisfaction and perceived value to propose a research model that drives social capital for energy sectors in Malaysia. The model reveals that the Theories of Planned Behaviour (TPB) and Social Support Theory (SST) alongside satisfaction and perceived value factors promote social capital development in energy sectors. Using PLS-SEM to analyse data gathered from energy sector employees in Malaysia, this research demonstrates that social capital is present when there is trust and loyalty among the users and positively effects en

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Publication Date
Sun Dec 01 2024
Journal Name
Chilean Journal Of Statistics
A method of multi-dimensional variable selection for additive partial linear models.
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In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

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