Low Q2Q^2 proton structure function, using gluon and pseudoscalar meson clouds in the constituent quark framework

The idea of the meson cloud approach in the chiral quark model has been extended to include gluon cloud in order to achieve the parton densities in the nucleon, based on the constitute quark framework. The splitting function of the quark to the quark-meson and quark-gluon at low $Q^2$ value are used to obtain parton densities in the constituent quark. The phenomenological constituent model is employed to extract the parton distributions in the proton at low $Q^2$ value. Since we have access to the parton densities at low $Q^2$, we are able to obtain $F_{2}(x,Q^2)$ structure function at low $Q^2$ value. The result is in good agreement with available experimental data and some theoretical models. To confirm the validity of our calculations, the fraction of total momentum of proton which is carried by gluon at high $Q^2$ and also the Gottfried sum rule are computed. The results are in good agreement with what are expected.Comment: 13 pages, 3 figure

Desmoplastic fibroma of the jaws: A case series and review of literature

Desmoplastic fibroma (DF) is a benign, locally aggressive neoplasm that rarely occurs in the facial skeleton. It usually presents during the first three decades of life. Due to its aggressiveness and high recurrence rate, early diagnosis is imperative, and complete surgical removal of the lesion is the treatment of choice. Herein, we present three cases of DF namely a 2 year-old girl with a mandibular DF, a 9 year-old boy with a maxillary lesion and a 1.5-year old boy with a mandibular DF. Complete clinicopathological information, treatment plan and long-term follow-up of patients are discussed. Histopathologic features of 3 cases revealed non-capsulated spindle cell tumor with fascicular or swirling patterns in incisional biopsy. Immunohistochemical staining was performed to make a definitive diagnosis. Strongly positive nuclear immunoreactivity for β-catenin confirmed the diagnosis of desmoplastic fibroma in 3 cases. Segmental mandibulectomy, partial maxillectomy and hemimandibulectomy were done for the cases. There was no recurrence in our reported cases after 8 and 11 months and 3 years follow up, respectively. It is noteworthy that despite the aggressive nature of DF, young patients often respond well to wide resection treatment. © 2020, Iranian Society of Pathology. All rights reserved

Facile Design of Superparamagnetic Core-Shell EDC-Ascorbate-Fe3O4 Nanocomposites for Targeted Delivery of Doxorubicin to Triple Negative Breast Tumor by Fenton Reaction

Triple negative breast cancer (TNBC) phenotype accounts for its significant resistance to chemotherapy and other therapeutic procedures. So, the establishment of better and effective therapeutic procedures has become a challenge during recent years. Doxorubicin is a potent chemotherapeutic candidate but its prominent side effects can be subsided via its combination with nanocarriers. So, the present study was aimed to design ascorbic acid modified biopolymeric EDC/NHS-modified magnetic nanoparticles (MNP@MNP@AA-EDC/NHS-DOX for doxorubicin drug delivery to the triple negative breast cancers cell lines of MDA-MB-231, MDA-MB-468 and HCC1937. Monodisperse Fe3O4 MNPs were prepared by chemical co-precipitation method. According to the SEM and DLS results, MNP@AA-EDC/NHS-DOX, MNPs@AA, MNP@AA-MNP@AA-EDC/NHS and MNP@AA-EDC/NHS-DOX had average particle diameter of 53, 79 and 95 nm, respectively. While, XRD analysis showed that the MNP material had the strongest Fe crystal peak, while surface modified MNP@AA-EDC/NHS-DOX did not alter the characteristic properties of MNPs. VSM magnetization analysis revealed that MNP@AA-EDC/NHS-DOX exhibited sufficient paramagnetic potential in the presence of external magnetic field. The TG analysis showed that thermal decomposition capacity of present nanocomposites was: MNPs > MNP@AA-EDC/NHS > AA-MNPs > MNP@AA-EDC/NHS-DOX. AA-modified MNPs did not completely lose their thermal stability as compared to other modifications. Alamar blue analysis revealed that the bare MNPs did have non-significant cytotoxicity in MDA-MB-231, MDA-MB-468 and HCC1937 cell lines (p > 0.001). While, MNP@AA-EDC/NHS-DOX at 0.1, 1.0 and 10 μg/mL DOX concentrations showed significantly lowered cell survival percentages as compared to the free DOX regimens after 24 and 72h. While, HCC1937 cell line had the most accumulation of free (1.42 > 0.93 > 0.9 pg DOX/cell) and conjugated DOX (2.64 > 2.2 > 1.91 pg DOX/cell) after 6 h of incubation period as compared to MDA-MB-468 and MDA-MB-231, respectively (* p < 0.05). Present results provide a new insight into the design of paramagnetic targeted drug delivery nanocomposite system to overcome the obstacles and side effects of conventional chemotherapeutic agents

Polarized Deeply Inelastic Scattering (DIS) Structure Functions for Nucleons and Nuclei

We extract parton distribution functions (PDFs) and structure functions from recent experimental data of polarized lepton-DIS on nucleons at next-to-leading order (NLO) Quantum Chromodynamics. We apply the Jacobi polynomial method to the DGLAP evolution as this is numerically efficient. Having determined the polarized proton and neutron spin structure, we extend this analysis to describe 3He and 3H polarized structure functions, as well as various sum rules. We compare our results with other analyses from the literature.Comment: LaTeX, 12 pages, 11 figures, 6 tables. Update to match published versio

Next-to-Leading order approximation of polarized valon and parton distributions

Polarized parton distributions and structure functions of the nucleon are analyzed in the improved valon model. The valon representation provides a model to represent hadrons in terms of quarks, providing a unified description of bound state and scattering properties of hadrons. Polarized valon distributions are seen to play an important role in describing the spin dependence of parton distributions in the leading order (LO) and next-to-leading order (NLO) approximations. In the polarized case, a convolution integral is derived in the framework of the valon model. The Polarized valon distribution in a proton and the polarized parton distributions inside the valon are necessary to obtain the polarized parton distributions in a proton. Bernstein polynomial averages are used to extract the unknown parameters of the polarized valon distributions by fitting to the available experimental data. The predictions for the NLO calculations of the polarized parton distributions and proton structure functions are compared with the LO approximation. It is shown that the results of the calculations for the proton structure function, $xg_1^p$, and its first moment, $\Gamma_{1}^p$, are in good agreement with the experimental data for a range of values of $Q^{2}$. Finally the spin contribution of the valons to the proton is calculated.Comment: 22 pages, 7 figures. Published in Journal of High Energy Physics (JHEP

An improved dandelion optimizer algorithm for spam detection next-generation email filtering system

Spam emails have become a pervasive issue in recent years, as internet users receive increasing amounts of unwanted or fake emails. To combat this issue, automatic spam detection methods have been proposed, which aim to classify emails into spam and non-spam categories. Machine learning techniques have been utilized for this task with considerable success. In this paper, we introduce a novel approach to spam email detection by presenting significant advancements to the Dandelion Optimizer (DO) algorithm. DO is a relatively new nature-inspired optimization algorithm inspired by the flight of dandelion seeds. While DO shows promise, it faces challenges, especially in high-dimensional problems such as feature selection for spam detection. Our primary contributions focus on enhancing the DO algorithm. Firstly, we introduce a new local search algorithm based on flipping (LSAF), designed to improve DO's ability to find the best solutions. Secondly, we propose a reduction equation that streamlines the population size during algorithm execution, reducing computational complexity. To showcase the effectiveness of our modified DO algorithm, which we refer to as Improved DO (IDO), we conduct a comprehensive evaluation using the Spam base dataset from the UCI repository. However, we emphasize that our primary objective is to advance the DO algorithm, with spam email detection serving as a case study application. Comparative analysis against several popular algorithms, including Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Generalized Normal Distribution Optimization (GNDO), Chimp Optimization Algorithm (ChOA), Grasshopper Optimization Algorithm (GOA), Ant Lion Optimizer (ALO), and Dragonfly Algorithm (DA), demonstrates the superior performance of our proposed IDO algorithm. It excels in accuracy, fitness, and the number of selected features, among other metrics. Our results clearly indicate that IDO overcomes the local optima problem commonly associated with the standard DO algorithm, owing to the incorporation of LSAF and the reduction equation methods. In summary, our paper underscores the significant advancement made in the form of the IDO al-gorithm, which represents a promising approach for solving high-dimensional optimization prob-lems, with a keen focus on practical applications in real-world systems. While we employ spam email detection as a case study, our primary contribution lies in the improved DO algorithm, which is efficient, accurate, and outperforms several state-of-the-art algorithms in various metrics. This work opens avenues for enhancing optimization techniques and their applications in machine learning

A Scalable Feature Selection and Opinion Miner Using Whale Optimization Algorithm

Due to the fast-growing volume of text documents and reviews in recent years, current analyzing techniques are not competent enough to meet the users' needs. Using feature selection techniques not only support to understand data better but also lead to higher speed and also accuracy. In this article, the Whale Optimization algorithm is considered and applied to the search for the optimum subset of features. As known, F-measure is a metric based on precision and recall that is very popular in comparing classifiers. For the evaluation and comparison of the experimental results, PART, random tree, random forest, and RBF network classification algorithms have been applied to the different number of features. Experimental results show that the random forest has the best accuracy on 500 features. Keywords: Feature selection, Whale Optimization algorithm, Selecting optimal, Classification algorith

Specialized Plant Metabolism Characteristics and Impact on Target Molecule Biotechnological Production.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI linkPlant secondary metabolism evolved in the context of highly organized and differentiated cells and tissues, featuring massive chemical complexity operating under tight environmental, developmental and genetic control. Biotechnological demand for natural products has been continuously increasing because of their significant value and new applications, mainly as pharmaceuticals. Aseptic production systems of plant secondary metabolites have improved considerably, constituting an attractive tool for increased, stable and large-scale supply of valuable molecules. Surprisingly, to date, only a few examples including taxol, shikonin, berberine and artemisinin have emerged as success cases of commercial production using this strategy. The present review focuses on the main characteristics of plant specialized metabolism and their implications for current strategies used to produce secondary compounds in axenic cultivation systems. The search for consonance between plant secondary metabolism unique features and various in vitro culture systems, including cell, tissue, organ, and engineered cultures, as well as heterologous expression in microbial platforms, is discussed. Data to date strongly suggest that attaining full potential of these biotechnology production strategies requires being able to take advantage of plant specialized metabolism singularities for improved target molecule yields and for bypassing inherent difficulties in its rational manipulation

A new approach to calculate the gluon polarization

We derive the Leading-Order master equation to extract the polarized gluon distribution G(x;Q^2) = x \deltag(x;Q^2) from polarized proton structure function, g1p(x;Q^2). By using a Laplace-transform technique, we solve the master equation and derive the polarized gluon distribution inside the proton. The test of accuracy which are based on our calculations with two different methods confirms that we achieve to the correct solution for the polarized gluon distribution. We show that accurate experimental knowledge of g1p(x;Q^2) in a region of Bjorken x and Q^2, is all that is needed to determine the polarized gluon distribution in that region. Therefore, to determine the gluon polarization \deltag /g,we only need to have accurate experimental data on un-polarized and polarized structure functions (F2p (x;Q^2) and g1p(x;Q^2)).Comment: 12 pages, 5 figure