Earth dams are constructed mainly from soil. A homogenous earth dam is composed of only one material. The seepage through such dams is quite high. Upstream impervious blanket is one of the methods used to control seepage through the dam foundations. Bennet's method is one of the commonly used methods to design an impervious upstream blanket. Design charts are developed relating the length of blanket, total reservoir head, total base width of the dam (excluding downstream drainage), the coefficient of permeability of the blanket material, blanket thickness, foundation thickness, and coefficient of permeability of the foundation soil, based on the equations governing the Bennet's method for a homogenous earth dam with a blanket of uniform

Artificial intelligence has quickly invaded the realms of both creative and information-based writing, raising new questions about human originality, authorship and style. Despite its ability to produce writings that are coherent and stylistically varied, there are still concerns over the uniqueness and cultural neutrality of AI programs such as ChatGPT. This review covers significant recent advancements with artificial intelligence applications in both the literary and non-literary fields. It analyzes 35 recent studies contrasting authorship and creativity, or stylistic considerations and impressions, between human and AI texts. These studies range from poetic and fictional writing through essay, news article and academic publicati

Background: Diabetic mellitus (DM) is a collection of metabolic disorder identified by hyperglycemia. The heterogeneous etiology includes defects either in insulin secretion, or in insulin action, or the both. In addition to the distraction in carbohydrate, fat and protein metabolism. Inflammatory reaction that caused by many pro-inflammatory cytokines play a central role in the pathogenicity of T2DM, these cytokines can enhance insulin resistance which led to impaired glucose homeostasis. Subjects: The study included 75 patients (38 males and 37 females) suffering from T2DM with age mean ± SE 52.30 ± 1.60, and 70 individuals as healthy controls (35 males and 35 females) with age mean ± SE 48.88 ± 0.64. Evaluation of immunological marke

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

This investigation provides a comprehensive anatomical, histological, and endocrine profile of the thyroid gland in adult guinea fowls (Numida meleagris), a species for which detailed morphological data remain scarce in avian literature. A total of ten clinically healthy specimens, representing both sexes, were subjected to morphometric analysis of their thyroid glands, including lobar dimensions and weight. Anatomical dissection revealed that the glands are bilaterally positioned at the thoracic inlet, symmetrically located near the carotid arteries. Histological examinations—conducted using Hematoxylin and Eosin and Masson\'s trichrome stains—demonstrated the presence of structurally uniform follicles surrounded by a highly vasculariz

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The study objective was to summarize and evaluate the literature from the last decade about the cost of illness (COI) of diabetic retinopathy (DR) and diabetic macular edema (DME) through a systematic review.