Photoinduced Deoxygenative C2 Arylation of Quinoline N-oxides with Phenylhydrazines to 2-Arylquinolines over Porous Tubular Graphitic Carbon Nitride Semiconductor Photocatalyst.

The photo-induced deoxygenative C2 arylation of quinoline N-oxides to 2-arylquinolines is achieved over a heterogeneous porous tubular graphitic carbon nitride (PTCN) catalyst with phenylhydrazines as arylation reagent. A wide range of quinoline N-oxides can be efficiently transformed into their corresponding 2-arylquinolines under visible light irradiation. Moreover, PTCN catalyst is easily separated and could be reused several times without loss to its original activity.

A highly-selective biomimetic potassium channel.

Reproducing the outstanding selectivity achieved by biological ion channels in artificial channel systems can revolutionize applications ranging from membrane filtration to single-molecule sensing technologies, but achieving this goal remains a challenge. Herein, inspired by the selectivity filter structure of the KcsA potassium channel, we propose a design of biomimetic potassium nanochannels by functionalizing the wall of carbon nanotubes with an array of arranged carbonyl oxygen atoms. Our extensive molecular dynamics simulations show that the biomimetic nanochannel exhibits a high K permeation rate along with a high K/Na selectivity ratio.

Tailoring Single-Atom Coordination Environments in Carbon Nanofibers via Flash Heating for Highly Efficient Bifunctional Oxygen Electrocatalysis.

The rational design of carbon-supported transition metal single-atom catalysts necessitates precise atomic positioning within the precursor. However, structural collapse during pyrolysis can occlude single atoms, posing significant challenges in controlling both their utilization and coordination environment. Herein, we present a surface atom adsorption-flash heating (FH) strategy, which ensures that the pre-designed carbon nanofiber structure remains intact during heating, preventing unforeseen collapse effects and enabling the formation of metal atoms in nano-environments with either tetra-nitrogen or penta-nitrogen coordination at different flash heating temperatures.

FLAT: Fusing layer representations for more efficient transfer learning in NLP.

Parameter efficient transfer learning (PETL) methods provide an efficient alternative for fine-tuning. However, typical PETL methods inject the same structures to all Pre-trained Language Model (PLM) layers and only use the final hidden states for downstream tasks, regardless of the knowledge diversity across PLM layers. Additionally, the backpropagation path of existing PETL methods still passes through the frozen PLM during training, which is computational and memory inefficient.

Personalized optimization strategy for electrode array layout in TTFields of glioblastoma.

Tumor treating fields (TTFields) is a novel therapeutic approach for the treatment of glioblastoma. The electric field intensity is a critical factor in the therapeutic efficacy of TTFields, as stronger electric field can more effectively impede the proliferation and survival of tumor cells. In this study, we aimed to improve the therapeutic effectiveness of TTFields by optimizing the position of electrode arrays, resulting in an increased electric field intensity at the tumor.

NCME-Net: Nuclear cataract mask encoder network for intelligent grading using self-supervised learning from anterior segment photographs.

Cataracts are a leading cause of blindness worldwide, making accurate diagnosis and effective surgical planning critical. However, grading the severity of the lens nucleus is challenging because deep learning (DL) models pretrained using ImageNet perform poorly when applied directly to medical data due to the limited availability of labeled medical images and high interclass similarity. Self-supervised pretraining offers a solution by circumventing the need for cost-intensive data annotations and bridging domain disparities.

MixImages: An Urban Perception AI Method Based on Polarization Multimodalities.

Intelligent urban perception is one of the hot topics. Most previous urban perception models based on semantic segmentation mainly used RGB images as unimodal inputs. However, in natural urban scenes, the interplay of light and shadow often leads to confused RGB features, which diminish the model's perception ability.

Associations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging.

People affected by psychotic, depressive and developmental disorders are at a higher risk for alcohol and tobacco use. However, the further associations between alcohol/tobacco use and symptoms/cognition in these disorders remain unexplored. We identified multimodal brain networks involving alcohol use (n = 707) and tobacco use (n = 281) via supervised multimodal fusion and evaluated if these networks affected symptoms and cognition in people with psychotic (schizophrenia/schizoaffective disorder/bipolar, n = 178/134/143), depressive (major depressive disorder, n = 260) and developmental (autism spectrum disorder/attention deficit hyperactivity disorder, n = 421/346) disorders.

Accelerated Proton Transfer in Asymmetric Active Units for Sustainable Acidic Oxygen Evolution Reaction.

The poor durability of Ru-based catalysts limits the practical application in proton exchange membrane water electrolysis (PEMWE). Here, we report that the asymmetric active units in RuMO (M = Sb, In, and Sn) binary solid solution oxides are constructed by introducing acid-resistant p-block metal sites, breaking the activity and stability limitations of RuO in acidic oxygen evolution reaction (OER). Constructing highly asymmetric Ru-O-Sb units with a strong electron delocalization effect significantly shortens the spatial distance between Ru and Sb sites, improving the bonding strength of the overall structure.

Metal-Organic Framework with Dual Excitation Pathways as Efficient Bifunctional Catalyst for Photo-assisted Li-O Batteries.

Li-O batteries (LOBs) have sparked significant interest due to their fascinating high theoretical energy density. However, the large overpotential for the formation and oxidation of LiO during charge and discharge process seriously hinders the further development and application of LOBs. In this work, metal-organic frameworks (MOFs) with different metal clusters (Fe, Ti, Zr) are successfully synthesized, and they are employed as the photoelectrodes for the photo-assisted LOBs.

Encapsulation of Sn Sub-Nanoclusters in Multichannel Carbon Matrix for High-Performance Potassium-Ion Batteries.

Sub-nanoclusters with ultra-small particle sizes are particularly significant to create advanced energy storage materials. Herein, Sn sub-nanoclusters encapsulated in nitrogen-doped multichannel carbon matrix (denoted as Sn-SCs@MCNF) are designed by a facile and controllable route as flexible anode for high-performance potassium ion batteries (PIBs). The uniformly dispersed Sn sub-nanoclusters in multichannel carbon matrix can be precisely identified, which ensure us to clarify the size influence on the electrochemical performance.

Constructing MXene-based mixed-dimensional structure with multiple interfaces to optimize dielectric-magnetic synergistic effect for effective electromagnetic wave absorption.

Exploring efficient microwave absorbing materials (MAMs) which could convert electromagnetic (EM) energy into thermal energy represents an approbatory vision to reducing EM radiation and interference. Designing of mixed-dimensional structure with multiple interfaces represents the available target to investigate an ideal MAMs, which maximizes the superiority of mixed-dimensional structure in electromagnetic wave absorption (EMWA). Herein, we take full advantage of multiple interfaces engineering of MXene for optimizing the impedance matching to improve EMWA, MXene-based mixed-dimensional structure was designed by incorporating three-dimensional FeC@Carbon layers coated zero-dimensional FeO nanoparticles (NPs) supported two-dimensional MXene nanosheets (MXene/FeO@FeC@Carbon, MFC).

Musical tension is affected by metrical structure dynamically and hierarchically.

As the basis of musical emotions, dynamic tension experience is felt by listeners as music unfolds over time. The effects of musical harmonic and melodic structures on tension have been widely investigated, however, the potential roles of metrical structures in tension perception remain largely unexplored. This experiment examined how different metrical structures affect tension experience and explored the underlying neural activities.

The nexus between foreign direct investment, economic progress, and quality of institutions in fostering sustainable energy efficiency: Evidence from BRICS economies.

This paper analyzes the relationship between Foreign Direct Investment (FDI), economic growth, and institutional quality to maintain sustainable energy efficiency in BRICS. The objective of our study is to decompose which elements collectively impact the uptake of sustainable energy practices. A comprehensive dataset and an advanced econometric model Data Envelopment Analysis (DEA) are employed to investigate the dynamics at play.

Design and simulation of a compact polarization beam splitter based on dual-core photonic crystal fiber with elliptical gold layer.

For the polarization multiplexing requirements in all-optical networks, this work presents a compact all-fiber polarization beam splitter (PBS) based on dual-core photonic crystal fiber (PCF) and an elliptical gold layer. Numerical analysis using the finite element method (FEM) demonstrates that the mode modulation effect of the central gold layer effectively reduces the dimensions of the proposed PBS. By determining reasonable structural parameters of the proposed PCF, the coupling length ratio (CLR) between X- and Y-polarized super-modes can approach 2, achieving a minimal device length of 0.

Lag projective synchronization of discrete-time fractional-order quaternion-valued neural networks with time delays.

This paper deals with the lag projective synchronization (LPS) problem for a class of discrete-time fractional-order quaternion-valued neural networks(DTFO QVNNs) systems with time delays. Firstly, a DTFOQVNNs system with time delay is constructed. Secondly, linear and adaptive feedback controllers with sign function are designed respectively.

Numerical simulation of the transition flight aerodynamics of cross-shaped quad-tiltrotor UAV.

In order to enhance the stability of the tilt transition process, a new configuration of Quad-Tiltrotor UAV was presented in this paper. Firstly, numerical simulation was used to calculate and analyze the aerodynamic interaction between the front rotor/fuselage/rear rotor during the transition state mode. The calculation model of the isolated rotor, front-rear rotor, front rotor-fuselage, and front rotor-rear rotor-fuselage combination states are established.

Multi-scale design of MWCNT/glass fiber/balsa wood composite multilayer stealth structure with wide broadband absorption and excellent mechanical properties.

In unmanned aircraft applications, electromagnetic wave (EMW) absorbers suffer from defects in narrow absorption bands and poor mechanical properties. To solve the problems, a lightweight multilayer stealth structure with wide broadband absorption performance and excellent mechanical properties was designed and prepared by adjusting microscopically the number of multi-walled carbon nanotubes (MWCNT) and modulating macroscopically the thickness-matching relationship of the structure to promote the absorption of EMW synergistically. Under the MWCNT of 30 wt% and the depletion layer with the thickness of 0.

Integrated MUSIC array for high-precision damage diagnosis in complex composite structures.

Guided Wave (GW)-based Multiple Signal Classification (MUSIC) damage imaging presents several advantages, such as high resolution, which makes it a promising technique for localizing damage in composite structures. However, the application of this technology in aircraft is confronted with various challenges. The variability in performance of MUSIC array sensors is attributed to material and manufacturing process dispersion.

Error-controlled adaptive machining of aeronautical cabin structures by laser triangulation on-machine measurement.

Laser Triangulation On-Machine Measurement (LTOMM) is being implemented increasingly to inspect aeronautical components accurately and efficiently, with its enhanced application in adaptive machining. This work proposes an error compensation and controlling method for measuring the typical features of steps, holes, and freeform surfaces to improve accuracy. Then, the global path to inspect the cabin's structures is planned by introducing optimization algorithms, thus providing an appropriate sequence to shorten the traveling length.

Multiple cognition associated multimodal brain networks in major depressive disorder.

Major depressive disorder frequently leads to cognitive impairments, significantly affecting patients' quality of life. However, the neurobiological mechanisms underlying cognitive deficits remain unclear. This study aimed to explore multimodal imaging biomarkers associated with cognitive function in major depressive disorder.

Novel 4D-printed multi-stable metamaterials: programmability of force-displacement behaviour and deformation sequence.

The unique properties of metamaterials are determined by the configuration and spatial arrangement of artificially designed unit structures. However, the configuration and mechanical properties of conventional metamaterials are challenging to reverse and adjust. Based on curved beams, two types of novel three-dimensional (3D) multi-stable metamaterials with reconfigurable deformation and tunable mechanical properties are designed and fabricated using a four-dimensional (4D) printing method.

Rapid Mental Workload Detection of Air Traffic Controllers with Three EEG Sensors.

Air traffic controllers' mental workload significantly impacts their operational efficiency and safety. Detecting their mental workload rapidly and accurately is crucial for preventing aviation accidents. This study introduces a mental workload detection model for controllers based on power spectrum features related to gamma waves.