Magnetic Field/Ultrasound-Responsive FeO Microbubbles for Targeted Mechanical/Catalytic Removal of Bacterial Biofilms.

Conventional antibiotics are limited by drug resistance, poor penetration, and inadequate targeting in the treatment of bacterial biofilm-associated infections. Microbubble-based ultrasound (US)-responsive drug delivery systems can disrupt biofilm structures and enhance antibiotic penetration through cavitation effects. However, currently developed US-responsive microbubbles still depend on antibiotics and lack targeting capability.

Bio-Inspired P-type TeSeO Synaptic Transistor Based on Multispectral Sensing for Neuromorphic Visual Multilevel Nociceptor.

The development of neuromorphic color vision has significant research implications in the fields of machine vision and artificial intelligence. By mimicking the processing mechanisms of energy-efficient biological visual systems, it offers a unique potential for real-time color environment perception and dynamic adaptability. This paper reports on a multispectral color sensing synaptic device based on a novel p-type TeSeO transistor, applied to a neuromorphic visual multilevel nociceptor.

Highly efficient ferroelectric capacitor reservoir computing through the study of its nonlinear polarization dynamics.

In this work, we aim to unveil the general correlations between the performance of a physical reservoir computing (RC) system and the inherent nonlinear dynamics of the adopted device. Taking the metal-ferroelectric-metal (MFM) capacitor, one of the most popular candidate devices for compute-in-memory (CIM) technology, as the computational platform, we construct a nonlinear dynamical model of polarization in the ferroelectric layer. We then design the physical RC utilizing a single and/or an array of MFM capacitors by analyzing the model's stability and feasible dynamical cases.

Why they take the risk to perform a direct left turn at intersections: A data-driven framework for cyclist violation modeling.

Bicycle crashes at intersection areas are posed a worrying traffic safety issue, and one of the main reasons for bicycle crashes is failing to avoid conflicts with motor vehicles and other bicycles. Clearly, cyclists are more exposed to risk if they perform a direct left turn (DLT) being mixed with left-turning vehicle under a left-turn phase. Owing to the lack of exposure data, the detection of DLT event and the mechanism behind the risky riding behavior have yet to be discovered.

Uniaxial tensile strain impact on 1T-NbS monolayers as cathode material for lithium-sulfur batteries.

The application of lithium-sulfur (Li-S) batteries as efficient energy storage systems is hindered by the polysulfide shuttle and expansion effects. To overcome these obstacles, we employed density functional theory (DFT) to explore the 1T-NbS monolayer as a cathode material for Li-S batteries, particularly focusing on the effects of uniaxial tensile strain. Our results indicate that the pristine 1T-NbS monolayer presents a balanced adsorption affinity for LiPSs, thereby mitigating the shuttle effect.

Hepatoid adenocarcinoma of the stomach: discrimination from conventional gastric adenocarcinoma with a computed tomography-based radiomics nomogram.

Background: Previous studies found it difficult to differentiate hepatoid adenocarcinoma of the stomach (HAS) from conventional gastric adenocarcinoma (CGA). We aimed to assess the efficacy of a computed tomography (CT)-based radiomics nomogram in identifying HAS.

Methods: Portal phase CT images were collected from 59 patients with HAS and 122 patients with CGA.

CRISPR/Cas13a Trans-Cleavage and Catalytic Hairpin Assembly Cascaded Signal Amplification Powered SERS Aptasensor for Ultrasensitive Detection of Gastric Cancer-Derived Exosomes.

Cancer-derived exosomes carry a large number of specific molecular profiles from cancer cells and have emerged as ideal biomarkers for early cancer diagnosis. Accurate detection of ultralow-abundance exosomes in complex biological samples remains a great challenge. Herein, a novel SERS aptasensor powered by cascaded signal amplification of CRISPR/Cas13a -cleavage and catalytic hairpin assembly (CHA) was proposed for ultrasensitive detection of gastric cancer-derived exosomes, which included hairpin-structured recognition aptamers (MUC1-apt), cascaded signal amplification (i.

Coordinating Multi-Agent Reinforcement Learning via Dual Collaborative Constraints.

Many real-world multi-agent tasks exhibit a nearly decomposable structure, where interactions among agents within the same interaction set are strong while interactions between different sets are relatively weak. Efficiently modeling the nearly decomposable structure and leveraging it to coordinate agents can enhance the learning efficiency of multi-agent reinforcement learning algorithms for cooperative tasks, while existing works typically fail. To overcome this limitation, this paper proposes a novel algorithm named Dual Collaborative Constraints (DCC) that identifies the interaction sets as subtasks and achieves both intra-subtask and inter-subtask coordination.

Design, dynamic modeling and testing of a novel MR damper for cable-stayed climbing robots under wind loads.

To increase the adaptability of bridge construction equipment in high-altitude settings, this study examines a magnetorheological (MR) damper designed for cable-stayed climbing robots. Initially, a novel damper incorporating a spring-MR fluid combination and three magnetic circuit units is developed. A robot-cable-wind coupling dynamic model is subsequently formulated via Hamilton's principle, based on force analysis.

Model-free distributed state estimation with local measurements.

In this paper, the state estimation problem of physical plants with unknown system dynamic is revisited from the perspective of limited output information measurement, which corresponds to those with characteristics of high-dimensional, wide-area coverage and scatter. Given this fact, a network of sensors are used to carry out the measurement with each one accessing only partial outputs of the targeted systems and a novel model-free state estimation approach, named distributed stochastic variational inference state estimation, is proposed. The key idea of this method is to compensate for the impacts of local output measurements by adding nearest-neighbor rule-based information interaction among estimators to complete the state estimation.

Plasticizer Design Principle of "Like Dissolves Like": Semiconductor Fluid Plasticized Stretchable Fully π-Conjugated Polymers Films for Uniform Large-Area and Flexible Deep-Blue Polymer Light-Emitting Diodes.

Physical blending of fully π-conjugated polymers (FπCPs) is an effective strategy to achieve intrinsically stretchable films for the fabrication of flexible optoelectronic devices, but easily causes phase separation, nonuniform morphology and uncontrollable photo-electronic processing. This may cause low efficiency, unstable and nonuniform emission, and poor color purity, which are undesirable for deep-blue flexible polymer light-emitting diodes (FPLEDs). Herein, a "Like Dissolves Like" design principle to prepare semiconductor fluid plasticizers (SFPs) is established and intrinsically stretchable FπCPs films via external plasticization for high-performance deep-blue FPLEDs are developed.

Application of 3D-printed resin guides for the removal of molar fiber posts.

Objective: To evaluate the digital guide technique for removing fiber posts from molars and compare it with the conventional microscope-assisted ultrasound method.

Methods: Two mandibular dentition models, each comprising six extracted molars, were prepared. Two thick and straight canals distributed separately in the distal and mesial roots of each molar were selected for placing the fiber posts.

Anatase/TiO(B) homojunction nanosheets with a gold cocatalyst for direct photocatalytic coupling of methane to ethane.

An anatase/TiO(B) homojunction loaded with Au nanoparticles was synthesized, achieving a CH yield rate of 170 μmol g h in a flow photoreactor. The homojunction reduces TiO(B)'s strong oxidative ability, offering a more moderate environment for methane dehydrogenation, while Au aids in charge mitigation and methyl radical coupling. The catalyst highlights homojunction engineering and a ternary synergistic effect in photocatalytic CH coupling.

High-Performance Circularly Polarized Phosphorescence by Confining Isolated Chromophores with Chiral Counterions.

Organic room-temperature phosphorescence (RTP) featuring circularly polarized luminescence (CPL) is highly valuable in chiroptoelectronics, but the trade-off issue between luminescence efficiency (Φ) and dissymmetry factor (g) is still challenging to be solved. Here, chiroptical ionic crystals (R/S-DNP) are constructed through ionization-induced assembly, in which isolated chromophore of carboxylic anion is tightly confined by the surrounding chiral counterions. The long-range ordered and chiral counterions with asymmetric stacking are closely connected with isolated chromophores for molecular assembly via high-density electrostatic interactions, thus enabling the simultaneous realization of excellent single-molecule RTP emission and efficient chirality transfer.

Distributed dynamic scheduling algorithm of target coverage for wireless sensor networks with hybrid energy harvesting system.

The integration of energy harvesting techniques has the potential to significantly prolong target monitoring in wireless sensor networks (WSNs). However, the stochastic nature of hybrid solar-wind energy arrivals poses a significant challenge to optimizing energy utilization for target coverage. To address this issue, we propose a dynamic and distributed node scheduling algorithm based on Lyapunov optimization for hybrid energy-harvesting WSNs (HEH-WSNs).

Two fitness inference schemes compared using allele frequencies from 1068 391 sequences sampled in the UK during the COVID-19 pandemic.

Throughout the course of the SARS-CoV-2 pandemic, genetic variation has contributed to the spread and persistence of the virus. For example, various mutations have allowed SARS-CoV-2 to escape antibody neutralization or to bind more strongly to the receptors that it uses to enter human cells. Here, we compared two methods that estimate the fitness effects of viral mutations using the abundant sequence data gathered over the course of the pandemic.

Nanobiohybrid Extracellular Vesicle Nanoreactor with Improving Metabolical Activity for Biocatalytic Therapy.

Extracellular vesicles (EVs) hosting enzymatic activities that function as independent metabolic units are attractive natural biocatalytic platforms. However, directly using these metabolically active nanoreactors for effective biocatalytic applications remains challenging, mainly due to their constrained catalytic capabilities. Here, we construct an EV-templated nanobiohybrid system by engineering an EV surface with a photoresponsive zeolitic imidazolate framework (ZIF).

Understanding the Relationship Between Trait Mindfulness and Perceived Stress: The Serial Multiple Mediating Roles of Basic Psychological Needs Satisfaction and Psychological Flexibility.

Although research suggests that trait mindfulness has been negatively associated with perceived stress, an integrative examination of the underlying mechanisms is lacking. Consequently, the purpose of this study was to establish an integrative model within Monitor and Acceptance Theory (MAT). This model examined the relationship between trait mindfulness and perceived stress by assessing two important psychological resources: basic psychological needs satisfaction (BPNS) and psychological flexibility.

Correction: How do ecosystem service functions affect ecological health? Evidence from the Yangtze River Economic Belt in China.

Correction for 'How do ecosystem service functions affect ecological health? Evidence from the Yangtze River Economic Belt in China' by Wei Wang , , 2024, https://doi.org/10.1039/D4EM00296B.

Investigations of the interactions between ZnO nanorods and H with O NMR spectroscopy.

The interactions between ZnO nanorods and H at different temperatures are revealed with O solid-state NMR spectroscopy in combination with a variety of different characterization methods. These results should enable further understanding of the adsorption properties of H on ZnO nanocrystalline or related nanomaterials.

DeepBP: Ensemble deep learning strategy for bioactive peptide prediction.

Background: Bioactive peptides are important bioactive molecules composed of short-chain amino acids that play various crucial roles in the body, such as regulating physiological processes and promoting immune responses and antibacterial effects. Due to their significance, bioactive peptides have broad application potential in drug development, food science, and biotechnology. Among them, understanding their biological mechanisms will contribute to new ideas for drug discovery and disease treatment.