Maximum power point tracking in fuel cells an AI controller based on metaheuristic optimisation.

The increasing concern about global warming and the depletion of fossil fuel reserves has led to a growing interest in alternative energy sources, particularly fuel cells (FCs). These green energy sources convert chemical energy into electrical energy, offering advantages such as quick initiation, high power density, and efficient operation at low temperatures. However, the performance of FCs is influenced by changes in operating temperature, and optimal efficiency is achieved by operating them at their maximum power point (MPP).

Clinical Profiles and Survival Outcomes of Patients With Relapsed Ovarian Cancer: A Single-Center Study.

Background Ovarian cancer is the third most prevalent form of cancer among women in India. The majority of patients are diagnosed at an advanced stage. Many women with late-stage ovarian cancer experience a recurrence and need subsequent treatment, even after initial therapy.

Predictors of Mortality for Upper Extremity Penetrating Vascular Injuries (UEPVI).

Objectives: Our objective was to determine risk factors and operative outcomes for patients with upper extremity penetrating vascular injuries(UEPVI).

Methods: A retrospective review was performed of all adult UEPVI patients presenting to a level I trauma center between 1986 and 2019. Statistical analyses were performed to determine the independent predictors of mortality and hospital length of stay(LOS) among patients who underwent operative repair.

Prevalence and Impact of Cytomegalovirus Primary Infection and Reactivation on Graft Function in Post-Renal Transplant Recipients.

Introduction Cytomegalovirus (CMV) is often associated with mortality and significant morbidity following renal transplantation leading to graft rejection or dysfunction. Primary CMV infection refers to the first detection of the virus in a person who has no prior evidence of CMV exposure before transplantation. CMV has a unique property called latency.

Advances in diagnosis and prognosis of bacteraemia, bloodstream infection, and sepsis using machine learning: A comprehensive living literature review.

Background: Blood-related infections are a significant concern in healthcare. They can lead to serious medical complications and even death if not promptly diagnosed and treated. Throughout time, medical research has sought to identify clinical factors and strategies to improve the management of these conditions.