A transdermal drug delivery system (TDDS) is characterized by the application of medications onto the skin's surface to deliver drugs at a controlled and predefined rate through the skin. Spanlastics, an elastic nanovesicle capable of transporting various pharmacological substances, shows promise as a drug delivery carrier. It offers numerous advantages over traditional vesicular systems applied topically, including enhanced stability, flexibility in penetration, and improved targeting capabilities. This study aims to develop meloxicam (MX)-loaded spanlastics gel as skin delivery carriers and to look into the effects of formulation factors like Tween80, Brij 35, and carbopol concentration on the properties of spanlastics gel, like pH, drug

Objective: The purpose of this study was to determine the association between caries related microorganisms in children’s saliva, such as Streptococcus mutans and lactobacilli, and their demographic factors. Methods: This study involved a sample of 135, both sexes with an age range between 3 and 10 years. Unstimulated saliva was obtained and diluted in normal saline. Saliva was then placed in selective media. Salivaris agar was used for mutans streptococci while Rogosa agar for lactobacilli. After incubation, Streptococcus mutans counting of CFU (colony forming units) with morphology characterization and numbers of CFU per milliliter of saliva for lactobacilli. Demographic factors information was collected using a questionnaire.

In Nathaniel Hawthorn's The Scarlet Letter, love and hate appear as independent powers that consume their holders. In this novel, Nathaniel Hawthorn presents a picture of the Puritans which shows an important part of American history. The Scarlet Letter outlines the American's brief moment of theocracy and extreme social order. Hawthorn is one of the first American writers to explore the hidden motivations of his characters. The Puritans wanted to establish an ideal community in America that can act as a model of influence for what they saw as a corrupted civil and religious order in England. This sense of mission is the core of their religious and social identity. That is why they required a strict moral regulation. The research tackles th

The concept of decolonization of trauma has intrigued researchers for years due to its prolonged effect on personal and cultural levels. The process of intellectual decolonization involves defensive survival mechanisms, such as cultural rituals using traditional practices, nostalgic dialogues that idealize memories and recollections, and conversations about identity to navigate postcolonial trauma displacement. Symbolic connections evoke strong emotional responses, bridging the gap between the characters‘ physical dislocation and their imaginary homeland. Cocooning identity represents a space where a multidimensional self emerges—one that holds the victim of trauma, the survivor who endures, and the narrator, who constructs an idealized

Cultural and identity scars have been engraved in the body of ethnic minority of Muslims in America due to the bloody attacks of 9/11. These events have created thus traumatic experiences on the party who witnessed the events at close and the people on whom the blame is conclusively directed, Muslim Americans. For Americans, the attacks resulted in a proud reassertion of the national virtue and communal integrity from which Muslim Americans were excluded. This reassertion is accompanied for Muslims by a reconstruction of a cultural identity away from their origin homeland and under pressures and prejudices that made the process of reconstruction to be severely challenging. Accordingly, the challenge needed to be portrayed to overcome the d

This study aims to conduct an exhaustive comparison between the performance of human translators and artificial intelligence-powered machine translation systems, specifically examining the top three systems: Spider-AI, Metacate, and DeepL. A variety of texts from distinct categories were evaluated to gain a profound understanding of the qualitative differences, as well as the strengths and weaknesses, between human and machine translations. The results demonstrated that human translation significantly outperforms machine translation, with larger gaps in literary texts and texts characterized by high linguistic complexity. However, the performance of machine translation systems, particularly DeepL, has improved and in some contexts

This study was aimed to evaluate atotal phenolic content, antibacterial activity, and antioxidant activity of M. communis callus extracts were evaluated. Callus induction in general Murashige and Skoog (MS) media is completed by the Benzil adenine's unique knowledge of callus formation. A well diffusion experiment was used to examine antibacterial interest in Staphylococcus aureus, Escherichia coli, Klebsiella pneumonia, and Pseudomonas aeruginosa. The DPPH radical scavenging activity test was used to measure antioxidant activity. FTIR and HPLC have been used to pinpoint the presence of polyphenol compounds in calluses. The total phenol content of plant leaves extract (0.1, 0.5, and 1) mg/ml was 42.12, 94.08, and 189 mg of Gallic ac

An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu