Image-Driven Hybrid Structural Analysis Based on Continuum Point Cloud Method with Boundary Capturing Technique.

Conventional approaches for the structural health monitoring of infrastructures often rely on physical sensors or targets attached to structural members, which require considerable preparation, maintenance, and operational effort, including continuous on-site adjustments. This paper presents an image-driven hybrid structural analysis technique that combines digital image processing (DIP) and regression analysis with a continuum point cloud method (CPCM) built on a particle-based strong formulation. Polynomial regressions capture the boundary shape change due to the structural loading and precisely identify the edge and corner coordinates of the deformed structure.

Evolution of Liver Resection for Hepatocellular Carcinoma: Change Point Analysis of Textbook Outcome over Twenty Years.

: The aim of this study was to comprehensively analyze the evolution in textbook outcome (TO) achievement after liver resection for hepatocellular carcinoma (HCC) over two decades at a single tertiary referral center. : All consecutive liver resections for HCC at Seoul National University Bundang Hospital from 2003 to 2022 were analyzed. The included 1334 patients were divided into four groups by time intervals identified through change point analysis.

Exoskeleton Robot Training in Two Patients with an Electrical Burn and Septic Arthritis: A Case Report.

Septic arthritis (SA) are rare in patients with burns, but delayed treatment can result in irreversible joint destruction. Early diagnosis and immediate treatment are necessary to prevent joint destruction. Robot training in patients with musculoskeletal diseases and burns, can improve joint range of motion (ROM), muscle strength, and lower extremity function.

Etchant-Free Dry-Developable Extreme Ultraviolet Photoresist Materials Utilizing N-Heterocyclic Carbene-Metal Complexes.

Extreme ultraviolet (EUV) lithography has enabled significant reductions in device dimensions but is often limited by capillary force-driven pattern collapse in conventional wet processes. Recent dry-development approaches, while promising, frequently require toxic etchants or specialized equipment, limiting their broader applicability and highlighting the need for more sustainable, cost-effective alternatives. In this study, highly reactive, etchant-free dry-developable EUV photoresists using N-heterocyclic carbene (NHC)-based metal-ligand complexes, achieving half-saturation at EUV doses of 8.

Artificial intelligence-enhanced comprehensive assessment of the aortic valve stenosis continuum in echocardiography.

Background: Transthoracic echocardiography (TTE) is the primary modality for diagnosing aortic stenosis (AS), yet it requires skilled operators and can be resource-intensive. We developed and validated an artificial intelligence (AI)-based system for evaluating AS that is effective in both resource-limited and advanced settings.

Methods: We created a dual-pathway AI system for AS evaluation using a nationwide echocardiographic dataset (developmental dataset, n = 8427): 1) a deep learning (DL)-based AS continuum assessment algorithm using limited 2D TTE videos, and 2) automating conventional AS evaluation.