Background: Osteoporosis is a skeletal defect manifested by a reduction of bone strength as a result of reduced bone mass to the extent that there is a higher risk of fracture even on minor trauma. Hysterectomy in a premenopausal woman is a well known cause of ovarian failure resulting in an increased risk of osteoporosis.

Objective : To clarify bisphosphonate's preventive effect on osteopenia and osteoporosis in premenopausal women after hysterectomy.

Type of the study: Cross –sectional study.

Method:  84 premenopausal females post hysterectomy aged between 40 – 50 years, were enrolled in this randomized controlled double blinded trail a

Background: The vertical distance between the upper and lower incisal edge of the central incisors when the mouth is opened as wide as possible is called maximum mouth opening (MMO). Any pathological change in the masticatory system had a direct effect on the maximal mouth opening. The aim of this study was to evaluate the relationship between the maximum bite force and the maximum mouth opening among group of children. Materials and methods: Four hundred children of both genders were included in this study, their age ranged from eight to ten years. Anterior and posterior (right, left) bite force were measured using bite force sensor. Maximum mouth opening was evaluated by electronic digital caliper. Data was statistically analyzed

Background: Patients with decompensated cirrhosis are often given therapeutic and prophylactic drugs. Polypharmacy raises both the likelihood of prescription errors and the complications associated with drugs. Clinical pharmacists are excellent at recognizing, addressing, and preventing clinically significant drug-related problems.

Objectives: Identification types of pharmacist interventions to address drug-related problems in patients with decompensated cirrhosis and assess the acceptance/implementation of these recommendations. And identify patient factors associated with accepting pharmacist recommend

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach