Effective cataract surgical and refractive error coverages in the state of Qatar.

Purpose: To evaluate the progress in Qatar's eye care since 2009, focusing on effective cataract surgical and refractive error coverages, leading to enhanced eye health strategies and action plans.

Methods: A modified Rapid Assessment of Avoidable Blindness (RAAB) survey was employed using multi-stage sampling in all persons 50 years and older in Qatar. The study focused on uncorrected refractive errors, cataract surgery coverage and effectiveness, and visual acuity assessment.

Metaheuristic optimized complex-valued dilated recurrent neural network for attack detection in internet of vehicular communications.

The Internet of Vehicles (IoV) is a specialized iteration of the Internet of Things (IoT) tailored to facilitate communication and connectivity among vehicles and their environment. It harnesses the power of advanced technologies such as cloud computing, wireless communication, and data analytics to seamlessly exchange real-time data among vehicles, road-side infrastructure, traffic management systems, and other entities. The primary objectives of this real-time data exchange include enhancing road safety, reducing traffic congestion, boosting traffic flow efficiency, and enriching the driving experience.

The Role of Intermittent Fasting on Metabolic Syndrome: A Systematic Review and Meta-Analysis.

Intermittent fasting has gained popularity as a dietary intervention to improve metabolic health. Metabolic syndrome may benefit from intermittent fasting by improving weight, cholesterol levels, blood pressure (BP), and glucose control. This study aims to assess the effects of intermittent fasting on weight, BMI, cholesterol levels, BP, and glucose in individuals with metabolic syndrome.

Assessment of Primary Healthcare Providers' Knowledge and Practices in Addressing Asymptomatic Hyperuricemia and Gout in the Asir Region of Saudi Arabia.

Introduction and aim Gout, the most common form of inflammatory arthritis, arises from hyperuricemia, a condition where elevated levels of uric acid lead to the deposition of monosodium urate (MSU) crystals in the joints. Nevertheless, it's important to note that not all cases of hyperuricemia result in gout. Methodology This cross-sectional study was conducted in the Asir region of Saudi Arabia, targeting primary healthcare physicians (PHPs) specializing in family medicine and general practice.

An Automatic-Segmentation- and Hyper-Parameter-Optimization-Based Artificial Rabbits Algorithm for Leaf Disease Classification.

In recent years, disease attacks have posed continuous threats to agriculture and caused substantial losses in the economy. Thus, early detection and classification could minimize the spread of disease and help to improve yield. Meanwhile, deep learning has emerged as the significant approach to detecting and classifying images.

Microservice Application Scheduling in Multi-Tiered Fog-Computing-Enabled IoT.

Fog computing extends mobile cloud computing facilities at the network edge, yielding low-latency application execution. To supplement cloud services, computationally intensive applications can be distributed on resource-constrained mobile devices by leveraging underutilized nearby resources to meet the latency and bandwidth requirements of application execution. Building upon this premise, it is necessary to investigate idle or underutilized resources that are present at the edge of the network.

Endoscopic Sleeve Gastroplasty in Those With a Body Mass Index of 27-30.

Introduction: Endoscopic sleeve gastroplasty (ESG) is safe and effective in patients with a body mass index (BMI) more than 30, with few cases reported in patients with overweight (BMI 27-30). However, evidence is lacking in the overweight group because the procedure is not currently performed routinely for such patients. In this study, we aim to evaluate the safety and efficacy of ESG in patients with a BMI between 27 and 30 who failed other weight loss modalities and/or had weight-related comorbidities.

Attention Aware Deep Learning Approaches for an Efficient Stress Classification Model.

In today's world, stress is a major factor for various diseases in modern societies which affects the day-to-day activities of human beings. The measurement of stress is a contributing factor for governments and societies that impacts the quality of daily lives. The strategy of stress monitoring systems requires an accurate stress classification technique which is identified via the reactions of the body to regulate itself to changes within the environment through mental and emotional responses.

Long-term outcomes of laparoscopic sleeve gastrectomy in those with class I obesity: safety, efficacy, and quality of life.

Background: Class I obesity carries significant morbidity and mortality risk similar to higher grades of obesity, and persons with class I obesity have a high risk of progression to class II and III obesity. While bariatric surgery has made strides in safety and efficacy, it remains inaccessible for persons with class I obesity (body mass index [BMI] of 30-35 kg/m).

Objectives: To assess safety, weight loss durability, co-morbidity resolution, and quality of life after laparoscopic sleeve gastrectomy (LSG) in persons with class I obesity.