The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

Complex-valued regular functions that are normalized in the open unit disk are vastly studied. The current study introduces a new fractional integrodifferential (non-linear) operator. Based on the pre-Schwarzian derivative, certain appropriate stipulations on the parameters included in this con-structed operator to be univalent and bounded are investigated and determined.

The present study was set to investigate the potential association between the level of Interleukin-6 (IL-6), as a key component of the pro-inflammatory response, with different thalassemia’s biological and clinical features. For this purpose, one hundred fifty blood samples were collected from 100 beta-thalassemia patients, who attended the Genetic Hematology Centre at Ibn Al- Baladi Hospital in Baghdad, Iraq, and 50 healthy subjects who were employed as a control group. IL-6 levels were estimated using an ELISA Kit, whereas other thalassemia-related clinical features (such as HbA, HbF, ferritin, blood transfusions, splenectomy status, and the history of frequent infection) were additionally assessed. The results of the present s

The study of the language through the prophetic curriculum in general and the semantics in particular through the books of Professor Abdul Salam Yassin, may God have mercy on him and the most distinctive linguistic phenomena, and then study semantics and the most prominent methods that reveal the emotions dominated by this study to indicate the semantics of religious terms In this research we try to dive into the sea of ​​significance to know the relationship between the words and their connotations, and to monitor aspects of semantic development, although we have left non-essential words in order to avoid lengthening. N or three and sometimes Aguetsarna on one example we thought it was enough to clarify the meaning.

Objective: Many studies focused on clinical cases such as ovariohysterectomy of bitches and scarcely mentioned the histological features. The present study describes the cytoarchitecture characteristics of a local dog’s mature adult reproductive tract. Materials and Methods: Sixteen samples of uterus and cervix were obtained from local breed bitches to conduct this study. The organs were processed according to routine histopathological protocol and stained with hematoxylin and eosin, Masson’s trichrome, and combined Alcian blue (2.5 pH) and PAS (AB-PAS) stains. Results: The mature endometrium formed numerous short epithelial folds and epithelial crypts composed of mucous cells and cuboidal cells. The core of the endometrium is c

The present study was conducted to estimate the incidence, clinical findings, cytological and histopathological characteristics of spontaneously occurring skin neoplasms in dogs. A total of 40 grossly suspected cases of cutaneous and subcutaneous tumors were gathered during the period from July 2016 to August 2018 from male and female dogs in Baghdad city. Dogs with skin neoplasia revealed various clinical signs, and their ages were older than 5 years to 15 years. German shepherd 30% followed by Terrier dogs 25% were more influenced than other breeds. Concerning tumor features, the majority of neoplasms had solitary lesion 70%, regular shapes 65% with black color 55%. The tumors frequently occurred on fore-limbs and abdomen, and 80% of them

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc