Professor Svetlana Mojsov and Professor Carlos Kenig, among other eminent figures, were selected to win the 48th session of the PrizeRiyadh, Saudi Arabia, Jan. 07, 2026 (GLOBE NEWSWIRE) -- Professor S ...

The course provides an introduction to the theoretical basis for linear partial differential equations, focusing on elliptic equations and eigenvalue problems. The techniques and methods developed are ...

Fruchter, G. (2026) Opportunism in Supply Chain Recommendations: A Dynamic Optimization Approach. Modern Economy, 17, 26-38.

PDF files have become ubiquitous in our multi-platform world. This convenient file format makes it possible to view and share documents across various devices using various operating systems and ...

Solving partial differential equations (PDEs) is a required step in the simulation of natural and engineering systems. The associated computational costs significantly increase when exploring various ...

Objective To assess the benefit of arthroscopic partial meniscectomy (APM) in adults with a meniscal tear and knee pain in three defined populations (taking account of the comparison intervention): (A ...

Introduction Each year, millions of people experience recurrent diverticulitis episodes. Elective sigmoid colon resection reduces the risk of recurrence, but The American Society of Colon and Rectal ...

Abstract: This paper proposes a novel non-iterative method to solve power system differential algebraic equations (DAEs) using the differential transformation, which is a mathematical tool able to ...

Face-to-Face class that meets on designated campus. Students are expected to attend all class meetings on the days and times shown in schedule. Students who do not attend a class meeting by the end of ...

Abstract: This paper presents a review of advanced architectures based on the partial power processing concept, whose main objective is to achieve a reduction of the power processed by the converter.

This repo is the official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network" by Longxiang Jiang, Liyuan Wang, Xinkun Chu, Yonghao Xiao, and Hao Zhang ...