Inverse design of promising electrocatalysts for CO reduction via generative models and bird swarm algorithm.

Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties.

Targeting extracellular matrix components to attenuate microglia neuroinflammation: A study of fibulin-2 and CSPGs in a model of multiple sclerosis.

The extracellular matrix (ECM) plays an important role in the central nervous system (CNS), shaping tissue structure and functions as well as contributing to the pathology of chronic diseases such as multiple sclerosis (MS). ECM components, including fibulin-2 (FBLN2) and chondroitin sulfate proteoglycans (CSPGs), may impact neuroinflammation and remyelination. We investigated the capacity of FBLN2 to modulate immune responses and evaluated its interaction with CSPGs in experimental autoimmune encephalomyelitis (EAE), a common model for MS.

A Resource-Efficient Multi-Entropy Fusion Method and Its Application for EEG-Based Emotion Recognition.

Emotion recognition is an advanced technology for understanding human behavior and psychological states, with extensive applications for mental health monitoring, human-computer interaction, and affective computing. Based on electroencephalography (EEG), the biomedical signals naturally generated by the brain, this work proposes a resource-efficient multi-entropy fusion method for classifying emotional states. First, Discrete Wavelet Transform (DWT) is applied to extract five brain rhythms, i.

Erbium: key to simultaneously achieving superior temperature-stability and high magnetic properties in 2 : 17-type permanent magnets.

To address the demands of rapidly advancing precision instruments requiring higher efficiency and miniaturization, permanent magnets must exhibit exceptional energy density, temperature stability, high magnetic energy product [()], and adequate coercivity (). Herein, we design rare earth Er-based magnets (2 : 17-type Er-magnets) with a composition of (Er, Sm)(Co, Fe, Cu, Zr). Erbium-based compounds (ErCo) offer a unique combination of temperature compensation and high saturation magnetization compared to other heavy rare earth elements, resulting in 2 : 17-type Er-magnets with superior temperature stability in and ().

Types and cost of wellness services provided by a neighborhood-based academic nursing center.

Background: Despite increased insurance coverage since 2010, racial and ethnic minorities in the United States still receive less medical care than White counterparts. The Johns Hopkins School of Nursing's Center for Community Programs, Innovation, and Scholarship (COMPASS Center) provides free wellness services, aiming to address healthcare disparities in the neighborhoods.

Objective: To delineate the types and cost of wellness services provided by the COMPASS Center.