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

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

This research utilized natural asphalt (NA) deposits from sulfur springs in western Iraq. Laboratory tests were conducted to evaluate the performance of an asphalt mixture incorporating NA and verify its suitability for local pavement applications. To achieve this, a combination of two types of NA, namely soft SNA and hard HNA, was blended to create a binder known as Type HSNA. The resulting HSNA exhibited a penetration grade that adhered to Iraqi specifications. Various percentages of NA (20%, 40%, 60%, and 80%) were added to petroleum asphalt. The findings revealed enhanced physical properties of HSNA, which also satisfied the requirements outlined in the Iraqi specifications for asphalt cement.

Consequently, HS

Levan is an exopolysaccharide produced by various microorganisms and has a variety of applications. In this research, the aim was to demonstrate the biological activity of levan which produced from B. phenoliresistens KX139300. These were done via study the antioxidant, anti-inflammatory, anticancer and antileishmanial activities in vitro. The antioxidant levan was shown 80.9% activity at 1250 µg/mL concentration. The efficient anti-inflammatory activity of 88% protein inhibition was noticed with levan concentration at 35 µg/mL. The cytotoxic activity of levan at 2500 µg/mL concentration showed a maximum cytotoxic effect on L20B cell line and promastigotes of Leishmani tropica. Levan has dose-dependent anticancer and antileishman

Concrete filled steel tube (CFST) columns are being popular in civil engineering due to their superior structural characteristics. This paper investigates enhancement in axial behavior of CFST columns by adding steel fibers to plain concrete that infill steel tubes. Four specimens were prepared: two square columns (100*100 mm) and two circular columns (100 mm in diameter). All columns were 60 cm in length. Plain concrete mix and concrete reinforced with steel fibers were used to infill steel tube columns. Ultimate axial load capacity, ductility and failure mode are discussed in this study. The results showed that the ultimate axial load capacity of CFST columns reinforced with steel fibers increased by 28% and 20 % for circular and square c

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

The research aims for the study about Ibn Tulun's personal and scientific biography to the
scholar, scientist and historian Ibn Tulun Shams Id- Din Mohammad Ibn Ali al-Dimashqi al-
Salihi (953 A.H. / 1546 A.D.) Ibn Tulun was a prominent Muslim historian in Blad al-
Sham.
At the first deals with Ibn Tulun's personal biography, author's name, Lineage, and
nickname, his nativity; his upbringing, and edification, his moral character, Finally, his death.
As to Ibn Tulun's scientific biography, at the first deals with his initiation into education
and learning , sheds light on his tutors and his authorities , scientific stations and travels , his
scholarly status , and Ibn Tulun's alumni or his students .

 Avascular necrosis have always presented great challenges to orthopedic surgeons and patients, remain in many ways today the unsolved dilemma. Varieties of non-vascularized bone grafting techniques preceded by core decompression have been proposed with varying degrees of success. O bb j ee cc t i vv ee ss : The aim of this study is to review the the value of core decompression and non-vascularized tibial bone strip graft treatment for early stages of non-traumatic osteonecrosis stage II & III according to stein burg staging . M ee t hh oo dd ss : prospectively reviewed 26 patients (32 hips) with osteonecrosis of the femoral head between June 2006 and December 2013 at Imam Ali hospital in Sader city & Al-Wasity teaching hosp