Fluorescence Lifetime Imaging of Triplet-Triplet Annihilation Upconversion for Quantitative Mapping of Environmental Stimuli.

Photon upconversion via triplet-triplet annihilation (TTA-UC) is a promising technology for environmentally responsive sensing, characterized by delayed fluorescence and anti-Stokes shifts. However, it faces quantification challenges due to intensity-based detection limitations, such as fluorophore concentration, excitation source instability, and environmental scattering. To address these issues, we report a time-resolved fluorescence strategy that exploits the intrinsic delayed fluorescence lifetime of TTA-UC systems as a robust, concentration-independent parameter for the quantitative spatiotemporal mapping of environmental stimuli.

Integrated decision-control for social robot autonomous navigation considering nonlinear dynamics model.

Reinforcement learning (RL) has demonstrated significant potential in social robot autonomous navigation, yet existing research lacks in-depth discussion on the feasibility of navigation strategies. Therefore, this paper proposes an Integrated Decision-Control Framework for Social Robot Autonomous Navigation (IDC-SRAN), which accounts for the nonlinearity of social robot model and ensures the feasibility of decision-control strategy. Initially, inverse reinforcement learning (IRL) is employed to tackle the challenge of designing pedestrian walking reward.

Engineering oxygen vacancy-enriched S-scheme ZnIO(OH)/BiOIO heterojunction architectures for enhanced charge separation and photocatalytic efficiency.

Tetracycline (TC), a commonly used antibiotic, is often classified under pharmaceuticals and personal care products (PPCPs), and its extensive use poses significant risks including ecotoxicity, antimicrobial resistance (AMR), and gut microbiota imbalance, among others. The composite photocatalyst ZCZIH/BIO (ZnCO/ZnIO(OH)/BiOIO) with S-scheme heterojunction was fabricated through a simplified two-stage hydrothermal approach for the degradation of TC in aqueous environment. The optimal photocatalyst showed excellent photocatalytic performance for TC degradation, achieving a reaction rate constant of around 8.

Quaternized-PAF Architecture Mediated Proton Channels to Enhance Ultra-Robust Operation for 200 °C Proton Exchange Membrane Fuel Cells.

In optimizing the trade-off between power density and phosphoric acid (PA) retention in PA-doped polybenzimidazole (PA-PBI) membrane for improving performance of high-temperature proton exchange membrane fuel cells (HT-PEMFCs), the self-reinforcing network of interfacial interactions of the HT-PEMs has to be deeply investigated. In this paper, a breakthrough strategy employing a quaternary ammonium (QA)-functionalized porous aromatic framework (QPAF-225) to synergistically integrate with sulfonated poly[2,2'-(p-oxydiphenylene)-5,5'-bibenzimidazole] (SOPBI) to form the robust HT-PEM is successfully developed. The ionic interactions between the cationic QA moieties and anionic sulfonic acid groups can establish a self-reinforcing proton-conductive network, while the high-density basic sites in QPAF-225 act as the PA reservoirs and can mitigate the leakage.

Recyclable G-quadruplex-driven hydrogel electrolyte for interface-compatible sustainable supercapacitors.

Sustainable hydrogel-based supercapacitors are emerging as promising options for safe and green energy storage solutions, but suffer from low energy density and non-recyclability. Herein, a G-quadruplex-driven hydrogel electrolyte with recyclability and ion channels is successfully designed and applied to construct interface-compatible sustainable supercapacitors. The G-quadruplex-driven supramolecular network with ion channels not only enables hydrogel electrolytes to achieve high ionic conductivity, but also imparts thermally activated reversible regulation of network structure for the construction of interface-compatible supercapacitors.

Improved MPC for trajectory planning of self-driving cars.

To tackle the challenges associated with lane changes in diverse driving environments, this study introduces an Improved Model Predictive Control (IMPC) approach that integrates vehicle state and driving context to execute maneuvers effectively. Initially, a simplified model is established, incorporating vehicle position, velocity, and driving conditions. Subsequently, a Sigmoid function is utilized to restrict vehicle movements, while Finite State Machine (FSM) decision-making selects appropriate maneuvers in real time according to changing driving conditions.

Evaluating sports complex sustainable supply chains: A prospective assessment technique method of moments quantile regression research.

The growing emphasis on sustainability in supply chain management has raised critical concerns about its implementation in complex ecosystems such as sports stadiums. This study investigates the economic and environmental dimensions of sustainable supply chains within sports complexes, employing the Method of Moments Quantile Regression (MMQR) technique to provide a nuanced analysis of key variables influencing sustainability outcomes from 2008 to 2022. By integrating Corporate Environmentalism (CE), Population Density (PD), Economic Complexity Ratio, and Workforce Readiness Ratio with Gross Domestic Product (GDP) differentiation metrics, the research identifies significant conditional and non-linear relationships.

High-Voltage and Ultralow-Temperature Lithium Metal Batteries Achieved by Methyl Acetate-Based Locally High-Concentration Electrolyte.

The instability of the cathode/electrolyte interface and the increased difficulty of lithium-ion desolvation at low temperatures significantly limit the development of rechargeable lithium metal batteries (LMBs). In this work, a local high-concentration electrolyte based on methyl acetate was prepared using the diluent 1,1,2,2-tetrafluoroethyl 2,2,3,3-tetrafluoropropyl ether. Theoretical calculations and experimental results show that optimizing the solvent structure of the electrolyte by adjusting the lithium salt concentration and adding a diluent facilitates the desolvation process of Li.

Bubble-Templated Assembly of Ceramic Nanofibrous Aerogels: Effects of Fiber Content on Microstructure, Mechanical Properties, and Thermal Insulation Performance.

Lightweight ceramic nanofibrous aerogels with elastic 3D networks show a strong potential for thermal insulation. As the main structural units, nanofibers play a key role in determining the aerogel integrity and performance. In this study, a ceramic nanofibrous aerogel was prepared via a bubble-templated assembly strategy.

A multi-task learning model for global soil moisture prediction based on adaptive weight allocation.

Global soil moisture is crucial for multiple disciplines such as earth science and agricultural science. Therefore, there are many studies on how to improve the prediction accuracy of soil moisture, especially the rapid development of deep learning in recent years, which has greatly improved data-driven models. This paper proposes an adaptive weight long short-term memory (AW-LSTM) model based on dynamic weight allocation, which dynamically optimizes the model by calculating the correlation coefficient [Formula: see text] between tasks.

Sodium alginate-enhanced MXene multifunctional hydrogel: Dual temperature-strain response and recyclability.

Conductive hydrogels are valued for their flexibility and sensitivity for flexible wearable sensors, but they typically focus on strain sensing and lack features such as fast temperature response. In addition, discarded sensors can cause environmental problems. Based on this, we developed a novel GBM hydrogel using NIPAAm, AM, PDA@BN, MXene, and SA to achieve dual response to temperature and strain as well as reuse after disposal.

Biomimetic Construction of Robust and Multifunctional-Integrated Superhydrophobic Coatings on Steel Structures via a One-Step Spraying Technique.

Nowadays, the contradictions between ideal fire resistance and adequate surface functionality are increasingly highlighted for conventional coatings of steel structures in actual applications. In this context, the introduction of multifunctional coatings has become one of the effective and practical avenues to solve the crucial problem of steel materials. In this paper, superhydrophobic coatings inspired by nature were successfully prepared on steel structures by a simple one-step spraying method, which consisted of a mixture of silicone resin (SR), poly(dimethylsiloxane) (PDMS), diatomaceous earth (DE), titanium dioxide (TiO), and modified ammonium polyphosphate (MAPP).

CuO/BiCuO Heterostructured Electrocatalyst for the Efficient Reduction of Nitrate to Ammonia.

The electrochemical reduction of nitrate to ammonia (NH) not only provides an effective approach to balance the perturbed nitrogen cycle for addressing environmental issues but also provides a potential technology for green NH synthesis. However, the process is limited by the produced intermediate-nitrite that tends to accumulate on cathode surfaces and multiple competing reactions. Herein, CuO/BiCuO-450 heterostructures are reported as efficient electrocatalysts for the nitrate reduction reaction with extraordinary catalytic activities and selectivities for NH production.

Heterogeneous Graph Contrastive Learning with Graph Diffusion for Drug Repositioning.

Drug repositioning, which identifies novel therapeutic applications for existing drugs, offers a cost-effective alternative to traditional drug development. However, effectively capturing the complex relationships between drugs and diseases remains challenging. We present HGCL-DR, a novel heterogeneous graph contrastive learning framework for drug repositioning that effectively integrates global and local feature representations through three key components.

Deep Learning-Assisted 3D Pressure Sensors for Control of Unmanned Aerial Vehicles.

Accurately and reliably detecting and recognizing human body movements in real time, relaying appropriate commands to the machine, have substantial implications for virtual reality, remote control, and robotics applications. Nonetheless, most contemporary wearable analysis and control systems attain action recognition by setting sensor thresholds. In routine usage, the stringent trigger conditions facilitate inadvertent contact, resulting in a poorer user experience.

A Hybrid CBiGRUPE Model for Accurate Grinding Wheel Wear Prediction.

In grinding machining, monitoring grinding wheel wear is essential for ensuring process quality wear and reducing production costs. This paper presents a hybrid CBiGRUPE model to predict grinding wheel wear, which integrates the advantages of convolutional neural networks (CNNs), bidirectional gated recurrent unit (BiGRU), and the Performer encoder. Time-domain features are extracted from the spindle motor current signals of a surface grinding machine.

Rapid Assembly of Block Copolymer Thin Films via Accelerating the Swelling Process During Solvent Annealing.

Block copolymer (BCP) lithography is widely regarded as a promising next-generation nanolithography technique. However, achieving rapid assembly with defect-free morphology remains a significant challenge for its practical application. In this study, we presented a facile and efficient solvent annealing method for fabricating well-ordered BCP thin films within minutes on both flat and topographically patterned substrates.

Facile synthesis of recyclable Mn-crosslinked chitosan schiff base composites as heterogeneous catalysts for selective oxidation of methyl phenyl sulfide with HO.

A novel manganese crosslinked chitosan composite (CS-Salen-Mn) was synthesized via Schiff base modification and coordination assembly. This composite showed excellent recyclability for heterogeneous catalytic oxidation. A Schiff base-modified chitosan (CS-Schiff) carrier was prepared via condensation of surface amines and salicylaldehyde, followed by coordination crosslinking with manganese acetate.

Regression analysis of a graphical proportional hazards model for informatively left-truncated current status data.

In survival analysis, researchers commonly focus on variable selection issues in real-world data, particularly when complex network structures exist among covariates. Additionally, due to factors such as data collection costs and delayed entry, real-world data often exhibit censoring and truncation phenomena.This paper addresses left-truncated current status data by employing a copula-based approach to model the relationship between censoring time and failure time.

High-throughput microanalysis of steel segregation using picosecond laser-induced breakdown spectroscopy.

Segregation monitoring plays an essential role in the quality control of steels, and laser-induced breakdown spectroscopy (LIBS) can be employed as a diagnostic tool in this process for elemental microanalysis. In this study, we constructed an ultrafast LIBS system employing a 1.2 kHz repetition-rate picosecond laser (ps-laser) to achieve high-throughput analysis of steel segregation with a spatial resolution of 1 μm.

Synergistic Interaction of Sulfonyl-Containing Sulfanilamide/Sulfamide To Enhance the Dielectric and Mechanical Properties of Polyurethane Materials.

High-performance dielectric materials have gained widespread attention, due to their great potential for various applications, such as flexible electronics and capacitive sensors. In this study, sulfamide (SA) and sulfanilamide (SAN), containing sulfonyl groups, were introduced into polyurethane (PU) as chain extenders. The polyurethane with the best performance was end-capped with 3-methylsulfonyl-1-propanol (3-MSP) to investigate the effects of the SAN/SA molar ratio and the capping agent on the microstructure, dielectric properties, and mechanical performance of the PU.

Impact of alkyl-substituted auxiliary acceptor positioning on dyes for DSSCs with Hagfeldt donor.

The introduction of an auxiliary acceptor into donor/acceptor dye systems is one of the most widely used strategies to enhance the light-harvesting properties of dye-sensitized solar cells. However, our understanding of the effects of these auxiliary acceptors remains limited. In this study, we utilize two organic dyes that differ in the positioning of the auxiliary acceptor to explore their impacts on several important factors associated with short-circuit current density and open-circuit photovoltage.

Deep Learning Image Compression Method Based On Efficient Channel-Time Attention Module.

Remote monitoring of transmission lines plays a vital role in ensuring the stable operation of power systems, especially in regions with weak or unstable network signals, where efficient data transmission and storage are essential. However, traditional image compression methods face significant limitations in both quality and efficiency when applied to high-resolution imagery in such scenarios.To address these challenges, this paper proposes a deep learning-based image compression approach incorporating an Efficient Channel-Temporal Attention Module (ETAM).

Analyzing the distribution of cell membrane receptors in real-time based on multiple molecule force spectroscopy.

Most cellular activities are predicated on ligand-receptor interactions at the cell membrane, the distribution and expression level of receptors on cell membrane exhibit significant variability. In this study, we introduce a new method to analyze the distribution of cell membrane receptors in real-time. Herein, the multiple molecule force spectroscopy (MMFS) was employed by using ligands functionalized microsphere on AFM (atomic force microscopy) tip cantilever.

Novel fluorescence and smartphone-assisted colorimetric sensing platform based on ionic liquid carbon dots for rapid detection of amylase in urine.

Changes in amylase (AMY) concentration in urine serve a vital function in monitoring human health. However, the development of non-destructive, sensitive, and real-time assays for AMY concentration still faces serious challenges. In this study, a novel fluorescence/smartphone imaging colorimetric dual-mode sensing platform based on ionic liquid carbon dots (IL-CDs) was designed for the first time for assessing AMY concentration in urine.