Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak

Acute lymphoblastic leukemia (ALL) is a cancer of the blood and bone marrow (spongy tissue in the center of bone). In ALL, too many bone marrow stem cells develop into a type of white blood cell called lymphocytes. These abnormal lymphocytes are not able to fight infection very well. The aim of this study was to investigate possible links between E3 SUMO-Protein Ligase NSE2 [NSMCE2] and increase DNA damage in the childhood patients with Acute lymphoblastic leukemia (ALL). Laboratory investigations including hemoglobin(Hb) ,white blood cell (WBC) , serum total protein , albumin ,globulin , in addition to serum total antioxidant activity (TAA) , Advanced oxidation protein products(AOPP) and E3 SUMO-Protein Ligase NSE2[NSMCE2]. Blood samples

Abstract

The purpose of our study was to develop Dabigatran Etexilate loaded nanostructured lipid carriers (DE-NLCs) using Glyceryl monostearate and Oleic acid as lipid matrix, and to estimate the potential of the developed delivery system to improve oral absorption of low bioavailability drug, different Oleic acid ratios effect on particle size, zeta potential, entrapment efficiency and loading capacity were studied, the optimized DE-NLCs shows a particle size within the nanorange, the zeta potential (ZP) was 33.81±0.73mV with drug entrapment efficiency (EE%) of  92.42±2.31% and a loading capacity (DL%) of 7.69±0.17%. about 92% of drug was released in 24hr in a controlled manner, the ex-vivo intestinal p

Cryptosporidiosis is mainly cause a persistent diarrhea in immune compromised patients, BALB/c mice have been suppressed by dexamethasone, tissue Th1, Th2 and Th17 cytokines concentrations in the ileum were significantly diminished in both infected and immunosuppressed mice. Level of IFN-g, TNF-a, IL-12, IL-6, IL-17A was increased in level, IL-4 didn’t increases, in both ileal and spleen tissue. Levels of above cytokines were examined in spleen in order to follow the proliferation of CD4+ T-cell during C. parvum infection.

The objective of this research paper is two-fold. The first is a precise reading of the theoretical underpinnings of each of the strategic approaches: "Market approach" for (M. Porter), and the alternative resource-based approach (R B V), advocates for the idea that the two approaches are complementary. Secondly, we will discuss the possibility of combining the two competitive strategies: cost leadership and differentiation. Finally, we propose a consensual approach that we call "dual domination". 

Autoría: Muwafaq Obayes Khudhair. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a