Polymer-MOF Network Enabling Ultrathin Coating for Post-Combustion Carbon Capture.

Permeance-selectivity trade-off and high temperature resilience are key challenges in development of membranes for post-combustion carbon capture. While mixed matrix membranes (MMMs) consisting of polymers and metal-organic frameworks (MOFs) offer the potential to address the challenges, they are limited by the low loading of MOFs in the thin film layer. Herein, we propose an inverse synthesis strategy to form polymer-MOF networks by copolymerizing monomers with functionalized UiO-66 nanoparticles.

PodGPT: An audio-augmented large language model for research and education.

The proliferation of scientific podcasts has generated an extensive repository of audio content, rich in specialized terminology, diverse topics, and expert dialogues. Here, we introduce a computational framework designed to enhance large language models (LLMs) by leveraging this informational content from publicly accessible podcast data across science, technology, engineering, mathematics and medical (STEMM) disciplines. This dataset, comprising over 3, 700 hours of audio content, was transcribed to generate over 42 million text tokens.

MedSyn: Text-Guided Anatomy-Aware Synthesis of High-Fidelity 3-D CT Images.

This paper introduces an innovative methodology for producing high-quality 3D lung CT images guided by textual information. While diffusion-based generative models are increasingly used in medical imaging, current state-of-the-art approaches are limited to low-resolution outputs and underutilize radiology reports' abundant information. The radiology reports can enhance the generation process by providing additional guidance and offering fine-grained control over the synthesis of images.

Electrospun transparent nanofibers as a next generation face filtration media: A review.

The development of fascinating materials with functional properties has revolutionized the humankind with materials comfort, stopped the spreading of diseases, relieving the environmental pollution pressure, economized government research funds, and prolonged their serving life. The outbreak of Coronavirus Disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has triggered great global public health concern. Face masks are crucial tools to impede the spreading of SARS-CoV-2 from human to human.

GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-Resolved EEG Motor Imagery Signals.

Toward the development of effective and efficient brain-computer interface (BCI) systems, precise decoding of brain activity measured by an electroencephalogram (EEG) is highly demanded. Traditional works classify EEG signals without considering the topological relationship among electrodes. However, neuroscience research has increasingly emphasized network patterns of brain dynamics.

Deep Feature Mining the Attention-Based Bidirectional Long Short Term Memory Graph Convolutional Neural Network for Human Motor Imagery Recognition.

Recognition accuracy and response time are both critically essential ahead of building the practical electroencephalography (EEG)-based brain-computer interface (BCI). However, recent approaches have compromised either the classification accuracy or the responding time. This paper presents a novel deep learning approach designed toward both remarkably accurate and responsive motor imagery (MI) recognition based on scalp EEG.

Polydopamine Microsphere-Incorporated Electrospun Fibers as Novel Adsorbents for Dual-Responsive Adsorption of Methylene Blue.

The usually inconvenient detection and uneasy recycling of polydopamine (PDA) with sphere morphology as an adsorbent restrict its actual applications in wastewater purification. Thus, novel composite fibers were fabricated via the electrospinning technique by integrating polydopamine microspheres (PDA-MPs) with pH/temperature dual-responsive copolymers. The insoluble fraction of the fabricated composite fibers can be maintained to a value above 89% after being immersed in aqueous solutions with different pH values.

thermal fabrication of copper sulfide-polymer hybrid nanostructures for tunable plasmon resonance.

Here, a novel strategy for fabricating plasmonic-polymer hybrid nanostructures the thermal synthesis of copper sulfide (CuS) nanocrystals within poly(-vinyl caprolactam)-based microgels is presented. In particular, the carboxyl groups inside the microgels enriched Cu ions electrostatic interaction, which further facilitated the nucleation inside the microgel matrix. The increase in nanocrystals' sizes with more added precursors indicated nanocrystals' continuous growth.

A novel approach of decoding EEG four-class motor imagery tasks via scout ESI and CNN.

Objective: To develop and implement a novel approach which combines the technique of scout EEG source imaging (ESI) with convolutional neural network (CNN) for the classification of motor imagery (MI) tasks.

Approach: The technique of ESI uses a boundary element method (BEM) and weighted minimum norm estimation (WMNE) to solve the EEG forward and inverse problems, respectively. Ten scouts are then created within the motor cortex to select the region of interest (ROI).

β-Cyclodextrin modified electrospinning fibers with good regeneration for efficient temperature-enhanced adsorption of crystal violet.

Novel β-cyclodextrin modified fibers with highly insoluble infraction and temperature enhanced adsorption performance were fabricated via electrospinning technology and followed thermo-crosslinking. The fabricated fibers were characterized by FT-IR, H NMR, TGA and SEM. In the fibers, β-CD was crosslinked with methacrylic acid (MAA) units to maintain morphologies of fibers and further be utilized for the adsorption of Crystal Violet through complex and electrostatic interaction.