Background: Knowledge about the prevalence and distribution of pathologies in a particular location is important when a differential diagnosis is being formulated. The aim of this study was to describe the prevalence and the clinicopathological features of odontogenic cysts and tumors affecting the maxilla and to discuss the unusual presentation of those lesions within maxillary sinus.

Materials and Methods: A multicenter retrospective analysis was performed on pathology archives of patients who were diagnosed with maxillary odontogenic cysts and tumors from 2010 to 2020. Data were collected with respect to age, gender and location.

Result: A total of 384 cases was identified, 320 (83.3%) cases were diagnosed as odontogenic

An encryption system needs unpredictability and randomness property to maintain information security during transmission and storage. Although chaotic maps have this property, they have limitations such as low Lyapunov exponents, low sensitivity and limited chaotic regions. The paper presents a new improved skewed tent map to address these problems. The improved skew tent map (ISTM) increases the sensitivity to initial conditions and control parameters. It has uniform distribution of output sequences. The programs for ISTM chaotic behavior were implemented in MATLAB R2023b. The novel ISTM produces a binary sequence, with high degree of complexity and good randomness properties. The performance of the ISTM generator shows effective s

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Micro-perforated panel (MPP) absorber is increasingly gaining popularity as an alternative sound absorber in buildings compared to the well-known synthetic porous materials. A single MPP has a typical feature of a Helmholtz resonator with a high amplitude of absorption but a narrow absorption frequency bandwidth. To improve the bandwidth, a single MPP can be cascaded with another single MPP to form a double-layer MPP. This paper proposes the introduction of inhomogeneous perforation in the double-layer MPP system (DL-iMPP) to enhance the absorption bandwidth of a double-layer MPP. Mathematical models are proposed using the equivalent electrical circuit model and are validated with experiments with good agreement. It is revealed that the DL-

Increasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off permeab

The study explored applications of artificial intelligence and its dialectical relationship with international human rights law of individuals, which requires assessing the effects of this technology on human rights and freedoms. The problem of privacy of humanity, as AI technologies can control human rights and freedoms, while monitoring potential violations in this context. The study use of documentary research and qualitative lens to analyze the data. In conclusion, unawareness of the use of AI may impose significant hurdles on future generations and may infringe on human rights across all sectors of society. The government should mandate obligations for artificial intelligence businesses concerning education, health, human right