The tourism industry has undergone exponential transformation, reshaped by online travel agencies (OTAs), shifting consumer preferences, and technological advancements. Established OTAs like TripAdvisor and Travelocity face pressures to adapt their strategies to capitalize on these disruptive landscape changes. This research involves a comparative analysis examining the key challenges confronting TripAdvisor and Travelocity, with a focus on opportunities to leverage artificial intelligence (AI) in enhancing personalization and the traveler experience. The study utilizes publicly available data on the companies and academic literature on AI innovation diffusion. Findings reveal that while TripAdvisor has actively developed AI-based trip plan

Liposomal amphotericin B (Amph B) has been used effectively to treat leishmaniosis, in spite of its high toxicity appeared in some patients. In our study, Amph B was administered in Leishmania donovani that infected BALB/c male mice using different concentrations to evaluate its efficacy challenge against infection as well as its effect in modulating immunity of the host. We observed that low doses with short duration of Amph B as a therapy regime significantly enhanced the induction of Th1 cytokine (INF-γ), but suppressed Th2 cytokine (IL-10) production. Groups of mice infected with L. donovani and treated with Amph B showed clearly increasing in INF-γ level and reduction in IL-10 level in concentration (3, 4, 5 mg/ml/kg) with best resul

The research aims to shed light on the role of artificial intelligence in achieving Ambidexterity performance, as banks work to take advantage of modern technologies, artificial intelligence is an innovation that is expected to have a long-term impact, as well as banks can improve the quality of their services and analyze data to ensure that customers' future needs are understood. . The Bank of Baghdad and the Middle East Bank were chosen as a community for the study because they had a role in the economic development of the country as well as their active role in the banking market. A sample of department managers was highlighted in collecting data and extracting results based on the checklist, which is the main tool for the stu

War as a human phenomenon, has its own literature. Poetry is a major genre in this literature. This paper is an attempt to investigate and analyse some stylistic features in two selected, English and Arabic, war poems. These poems share the same theme.Both promote the principle of sacrificing one’s own life for the sake of homeland.  This paper limits itself to analyse, thecontent words, tenses, semantic grouping of vocabulary and foregrounding in the two poems. The areas of analysis show great similarities in distributing the general content words (nouns, verbs, adjectives, and adverbs). In the analysis of the semantic areas of each content word, these poems reveal some similarities and some differences in their frequency rates.

Cams are considered as one of the most important mechanical components that depends the contact action to do its job and suffer a lot of with drawbacks to be predicted and overcame in the design process. this work aims to investigate the induced cam contact and the maximum shear stress energy or (von misses) stresses during the course of action analytically using Hertz contact stress equation and the principal stress formulations to find the maximum stress value and its position beneath the contacting surfaces. The experimental investigation adopted two dimensions photoelastic technique to analyze cam stresses under a plane polarized light. The problem has been numerically simulated using Ansys software version 15 as FE

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

A large number of natural or synthetic dyes have been removed from both national and international lists of permitted food colors because of their mutagenic or carcinogenic activity. Therefore, this study aimed to use the Random Amplified Polymorphic DNA-Based Polymerase Chain Reaction (RAPD-PCR) assay as a feasible method to evaluate the ability of some food colors as genotoxin-induced DNA damage and mutations. Lactiplantibacillus plantarum was used as a bioindicator to determine the genotoxic effects by RAPD-PCR using M13 primer after treatment with some synthetic dyes currently used as food color additives, including Sunset Yellow, Carmoisine, and Tartrazine. Besides qualitative analysis, the bioinformatic GelJ software was used for clus