Aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that regulates T cell function. The aim of this study was to investigate the effects of AhR ligands, 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), and 6-Formylindolo[3,2-b]carbazole (FICZ), on gut-associated microbiota and T cell responses during delayed-type hypersensitivity (DTH) reaction induced by methylated bovine serum albumin (mBSA) in a mouse model. Mice with DTH showed significant changes in gut microbiota including an increased abundance of Bacteroidetes and decreased Firmicutes at the phylum level. Also, there was a decrease in Clostridium cluster XIV and IV, which promo

       The study aimed to determine the extent of market knowledge in the companies researched, as if market knowledge is qualified to lead the companies researched to achieve marketing performance , for this purpose, formulated hypotheses of the study in three hypotheses, the first major hypothesis "there is a correlation with significance of market knowledge to improve the marketing performance  , "while the second major hypothesis, "there is a significant moral influence of market knowledge to improve the marketing performance  " these hypotheses targeting to determine the role played by market knowledge in the leadership of companies researched to achieve improvement in marketing perfor

The researcher tackles the most outstanding conditions of experimentation, the importance of the study lies in being helpful to the workers in the field of theatre in general and directors in particular which the conditions of experimentation that should be taken.The study aims at knowing the experimental basis which the director (Sami Abdulhamid) followed in the realization of this.The researcher tackles in the First inquiry the concept of experimentation and the second tackles the conditions of experimentation.In the methodology of study the researcher analyzed the show of the "Othello in the Kitchen" and comes up to the following: 1. the dhows has cone with the nature of the previous shows experienced the methods that were not familia

            The objective of this study is to measure the impact of financial development on economic growth in Iraq over the period (2004-2018) by applying a fully corrected square model (FMOLS) Whereas, a set of variables represented by (credit-to-private ratio of GDP, the ratio of money supply in the broad sense of GDP, percentage of bank deposits from GDP) were chosen as indicators for measuring financial development and GDP to measure economic growth.

Major tests have been carried out, such as the stability test (Unite Root Test), the integration test (Cointegration). Results of the study showed that there

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

This study evaluated yellow mealworm (Tenebrio molitor) larvae meal as an alternative animal-protein ingredient in diets for common carp (Cyprinus carpio) fingerlings. Two diets were compared for 60 days: a conventional fish-meal diet (T1; 32.09% crude protein) and a diet in which the animal-protein component was replaced weight-for-weight with T. molitor meal (T2; 23.88% crude protein). Each treatment was tested in duplicate tanks containing 28 fingerlings per tank, and growth was assessed over three consecutive 20-day phases. The initial mean body weight was 3.21 g. Weight gain differed significantly between treatments (p < 0.05), with the highest total value recorded in T2 (4.87 ± 0.47 g). The T2 diet produced a significantly higher fee

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to