Integrated reservoir rock typing in carbonate reservoirs is a significant step in reservoir modelling. The key purpose of this study is the identification of integrated rock types in the Sarvak Formation of an Iranian oilfield. In this study, electrofacies (EFAC) analysis of the Sarvak reservoir was done in detail to determine the reservoir quality and rock types of the Sarvak Formation in the studied field. The core data and conventional petrophysical logs were used for rock typing. Some petrophysical logs such as porosity, sonic, neutron, density, and Photo electric factor were applied as input data for electrofacies analysis. Multi-Resolution Graph-Based Clustering was used among six approaches, resulting in four electrofacies af

Abstract The avulsion of the flexor digitorum profundus, also known as the jersey finger, is a well-known injury that can be treated surgically. It has been classified into four types, among them type IV which involves tendon avulsion from an associated bony fragment with subsequent retraction to the palm or proximal interphalangeal joint is very rare. We present a case of type IV injury in a 45-year-old man with a pulling-on injury. The repair followed a pull-out technique (reinserting the tendon into the avulsed fragment); the entire reduction was tied over a button on the dorsal aspect of the nail and was augmented with a volar plate. The case was reported due to its rarity. We found that early surgical management of this problem greatly

This research considers a proposed mechanism relying on frictional interactions between the grasped object and the gripper, thus attaining a case of self-locking condition for a tendon type robotic gripper. A mathematical model was derived for this proposed mechanism, upon which a special purpose apparatus was fabricated and tested. Both results, theoretically and experimentally, are in good agreement, showing that the weight of the grasped object played a major role in attaining the self-locking condition.

Gallstone disease is one of the most common complications among diabetic patients especially type 2 DM. Till now, there is no specific and certain factor that explain the incidence of gallstones among type 2 diabetic patients and many risk factors are taken collectively to estimate its intensity and severity compared to non diabetic counter parts. This clinical study was designed to evaluate and report the incidence and severity of gallstones among type 2 diabetics and non diabetics regarding certain factors. 20 diabetic females and 20 diabetic males were collected as patients′ group and have had gallstones while 20 females and 20 males who have had gallstones without diabetes mellitus type 2 were collected as controls′ group

BACKGROUND: The primary cause of blindness in diabetics is diabetic retinopathy (DR), the most common microvascular complication of diabetes, and visual impairment. Visfatin is an adipocytokine that aids in insulin activity during gestational diabetes and pregnancy.

AIM: This study aimed to estimate serum visfatin levels in DR, proliferative (PDR), non-proliferative (NPDR), and healthy subjects (HS).

MATERIALS AND METHODS: A 120-patient case-control study with a history of T2DM for more than 5 years as well as 30 healthy subjects enrolled in the study. Patients group divided into three sub-groups, DM, PDR, and NPDR. Visfatin levels w

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff