Background: Thymus vulgaris is a plant rich in essential oils acclaimed for the management of oxidative stress and inflammation in the organs. Meanwhile, the heavy metal lead is widely distributed in nature and continued exposure to lead acetate causes reduced fertility.Objectives: The present study aimed to investigate the effects of T. vulgaris on ovarian and uterine structural and functional characteristics in female rats exposed to lead acetate. Methods: Three groups of 18 mature Wistar albino female rats (Rattus norvegicus), 15 weeks old and weighing between 200 and 210 g, were established and handled for 60 days as follows: Group A (control group) received 0.5 mL of distilled water (DW) daily; group B received 5 mg/kg body weight (BW

In the last decades, using mineral admixture in concrete became very necessary to improve concrete properties and reduce CO₂ emissions associated with the cement production process. Subsequently, more sustainable concrete can be obtained.  Ternary blended cement containing two different types of mineral admixture can achieve ambitious steps in this trend. In this research, the synergic effects of mineral admixtures in ternary blended cement and its effects on concrete fresh properties, strength, durability, and efficiency factors of mineral admixture in ternary blended cement, were reviewed. The main conclusion reached after reviewing many literature pieces is that the concrete with ternary blended cement

Fumonisin B1 (FB1) is a mycotoxin produced in some grains (mainly corn) by Fusarium species. Due to a structural similarity between FB1 and sphinganine, sphingolipids metabolism is inhibited. Such inhibition plays a critical role in cell to cell singling and structure of lipoprotein; therefore FB1 has been suggested to have a relationship with human and animal cancer. This research is planned to study the effect of FB1 on male mice at two doses (20 and 30 µg/ ml) on the expression of TGF-β1 and p16 in liver cells. Three groups of Swiss albino male mice; each group was orally administrated with FB1 toxin as the following: normal saline (control group); 20 and 30 µg/ ml. All groups were sacrificed after two weeks of oral manage

The Phenomenon of Euphemism in the Translon Activity Euphemism is the replacement of a harsh word with a less harsh or more acceptable   one.   Most   languages   are   affected   by   ideological,   cultural, social,   or   religious   perspectives   which   in   turn   would   reflect   different linguistic levels. On such a basis, translation is affected by its medium,i.e. language, and consequently what is acceptably expressed by a nation may   not  be  acceptable by another.   In   this paper, we try   to  

Background: Chronic obstructive pulmonary disease (COPD) is a progressive airflow limitation that is preventable but not curable. It is associated with persistent symptoms that cause a considerable burden on individual productivity at work, and daily activities, and reduced quality of life, also burdening the healthcare system and society. Objectives: The study aims to measure the burden of COPD on patients in terms of daily activities and work productivity. It also seeks to investigate some inflammatory biomarkers' levels and their correlation with selected outcomes. Patients and Methods: A cross-sectional study on 120 stable COPD patients who were diagnosed and treated according to the GOLD guidelines at Kirkuk General Hospital's

Recently, a new secure steganography algorithm has been proposed, namely, the secure Block Permutation Image Steganography (BPIS) algorithm. The new algorithm consists of five main steps, these are: convert the secret message to a binary sequence, divide the binary sequence into blocks, permute each block using a key-based randomly generated permutation, concatenate the permuted blocks forming a permuted binary sequence, and then utilize a plane-based Least-Significant-Bit (LSB) approach to embed the permuted binary sequence into BMP image file format. The performance of algorithm was given a preliminary evaluation through estimating the PSNR (Peak Signal-to-Noise Ratio) of the stego image for limited number of experiments comprised hiding

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th