DUA-MQTT: A Distributed High-Availability Message Communication Model for the Industrial Internet of Things.

With the rapid development of the Industrial Internet of Things (IIoT), the scale of industrial equipment has expanded, leading to an increasing diversity of communication protocols and a significant rise in data transmission volume within industrial networks. Traditional communication systems, constrained by concurrency and throughput limitations, struggle to meet the demands of massive data transmission. To address this issue, this paper proposes a distributed high-availability message communication model for IIoT (DUA-MQTT) based on the OPC UA architecture.

Synthesis of Upconversion Nanoparticles with Manipulable Crystal Phase, Size Specification, and Morphological Features.

Rare earth-doped upconversion nanomaterials are one of the luminescent materials that have received extensive attention in recent years and have important applications in fields such as biomedicine, optoelectronic devices, and security inspection. In this study, for NaYF:Yb,Er upconversion nanoparticles, the effects of experimental parameters such as reaction temperature, reaction time, and the content of surfactants on their crystal phase, size, and morphology were systematically investigated. By adjusting the experimental parameters, the size of the hexagonal phase upconversion nanoparticles can be effectively controlled within the range of 18-71 nm.

The electricity purchasing and selling strategy of load aggregators participating in China's dual-tier electricity market considering inter-provincial subsidies.

To promote the optimal allocation of electricity resources, this paper designs a trading framework for small and medium-sized adjustable electricity users to participate in China's dual-tier electricity market through load aggregators, proposes an inter-provincial transaction correction subsidy coefficient, and analyzes the purchase cost and risk at multiple time and space scales. Combining user demand response and preference behavior, a purchase and sale electricity decision-making model is constructed to achieve revenue maximization and risk control. The experimental results show that the spot purchase strategy proposed in this paper faces relatively low market risks.

NiFe-LDH as a bifunctional electrocatalyst for efficient water and seawater electrolysis: enhanced oxygen evolution and hydrogen evolution reactions.

Water electrolysis for hydrogen production has garnered significant attention due to its high efficiency, environmental friendliness, and abundant resource availability. Developing cost-effective, efficient, and stable materials for water electrolysis is crucial. This study investigates NiFe-LDH, a highly efficient electrocatalyst for the oxygen evolution reaction (OER) in alkaline electrolytes and a bifunctional electrocatalyst for alkaline seawater electrolysis.

Wind Turbine Blade Defect Recognition Method Based on Large-Vision-Model Transfer Learning.

Timely and accurate detection of wind turbine blade surface defects is crucial for ensuring operational safety and improving maintenance efficiency with respect to large-scale wind farms. However, existing methods often suffer from poor generalization, background interference, and inadequate real-time performance. To overcome these limitations, we developed an end-to-end defect recognition framework, structured as a three-stage process: blade localization using YOLOv5, robust feature extraction via the large vision model DINOv2, and defect classification using a Stochastic Configuration Network (SCN).

Impact of micro- and nanoplastics on gastrointestinal diseases: Recent advances.

Micro- and nanoplastics (MNPs) are ubiquitous contaminants increasingly recognized for their potential to adversely affect gastrointestinal (GI) health. This review provides a comprehensive overview regarding the impact of MNPs exposure on GI diseases, especially their toxicological mechanisms, such as oxidative stress, inflammation, apoptosis, gut microbiota dysbiosis, and intestinal barrier dysfunction. Excessive reactive oxygen species production and persistent GI inflammation triggered by MNPs exposure drive epithelial cell apoptosis and compromise the intestinal barrier.

The analysis of learning investment effect for artificial intelligence English translation model based on deep neural network.

With the rapid development of multimodal learning technologies, this work proposes a Future-Aware Multimodal Consistency Translation (FACT) model. This model incorporates future information guidance and multimodal consistency modeling to improve translation quality and enhance language learning efficiency. The model innovatively integrates target future contextual information with a multimodal consistency loss function, effectively capturing the interaction between text and visual information to optimize translation performance.

Novel laser-driven fast pyrolysis of biomass: Insights into biochar characteristics and applications.

Biomass pyrolysis is a promising technology for producing biochar, but conventional methods often lack precise control over heating rates and real-time monitoring, particularly in fast pyrolysis. A novel laser-driven fast pyrolysis (LFP) system was developed, achieving ultrafast heating rates (100°C/s) and enabling non-contact temperature measurement through infrared thermometry. Experiments were conducted using poplar wood as feedstock, with heating rates of 10°C/s and 100°C/s, spanning temperatures from 400°C to 700°C.

Multidimensional Engineering Strategies for Transition Metal Selenide Electrocatalysts in Water Electrolysis with Performance Optimization Mechanisms and Future Perspectives.

Hydrogen energy, as a carbon-neutral, high-energy-density renewable clean energy source, is recognized as an ideal alternative to fossil fuels. Although water electrolysis has emerged as a core technology for hydrogen production, its advancement remains constrained by the exorbitant cost, scarcity, and inadequate stability of precious metal catalysts. Transition metal selenides (TMSes) has emerged as promising electrocatalytic materials due to their combined advantages of low cost, tunable electronic structures, and intrinsic activity comparable to noble metals.

Study on structural dynamic response of offshore wind turbine under floating ice load.

The structural dynamic characteristics of offshore wind turbines are directly related to the operational safety and equipment reliability of these turbines in service. However, due to the complex working conditions, a single load analysis fails to accurately reflect the structural dynamic characteristics during actual operation. In this study, we focus on the 5 MW offshore wind turbines and establish a three-dimensional turbulent flow field model at sea using the Kaimal wind speed spectrum.

Optimal control of PVC polymerization process with set values based on TD3 algorithm.

Aiming at the various time frames between the operation computing and the base loop computing of the PVC polymerization process, as well as the difficulty in establishing the nonlinear model of the operation layer, this paper presents a data-based run-level control method combining iterative lifting technique and the TD3 algorithm. Aiming at the problem of different time scales of the two-layer structure, the iterative boosting technique is used to boost the cycle of the basic level of circulation to the cycle of the operation layer, and substitute the closed-loop basic loop system into the operational layer model; then the operation layer model is augmented and generalized, and general control objects that use the set values of the cyclic layer as input values, and with the operation index as the output value, are obtained. Based on the synchronized updating of the value function and the control strategy, the online strategy iteration algorithm is implemented using a model-free method based on TD3 neural network.

Capacity configuration optimization of electricity heat hydrogen regional integrated energy system considering supply-demand uncertainties.

Rationally configuring the capacity of the electricity heat hydrogen regional integrated energy system is conducive to improving its economy and energy utilization efficiency. In view of the dual effects of the uncertainties of energy supply and demand in system configuration on power supply reliability and wind power consumption, a min-max-min two-stage robust optimization configuration model aiming at the minimum sum of system investment and operating cost is established for achieving an optimal capacity configuration of multi-vector technologies involved in it. On the basis of typical scenarios, a box-type uncertainty set independent of a probability distribution is used to describe the uncertainty of wind power and demand and the robustness constraint is formed.

Capacity optimization configuration and multi-dimensional value evaluation of integrated energy system with power-to-hydrogen.

The research on the value evaluation system of power-to-hydrogen (P2H) equipment configuration in integrated energy systems is of great value for optimizing resource allocation, improving energy utilization efficiency, and promoting clean energy technology development. However, there is no comprehensive evaluation system for evaluating P2H equipment configuration in integrated energy systems. Therefore, a multi-dimensional value evaluation system is proposed to realize the thorough evaluation of P2H equipment with different capacity configurations in the integrated energy system.

First-principles prediction of intrinsic ferrovalley properties in Janus rare-earth PrXY (X ≠ Y = Cl, Br, I) monolayers.

In this work, using first-principles calculations, we predict a promising class of two-dimensional ferromagnetic semiconductors, namely Janus PrXY (X ≠ Y = Cl, Br, I) monolayers. Through first-principles calculations, we found that PrXY monolayers have excellent dynamic and thermal stability, and their band structures, influenced by magnetic exchange and spin-orbital coupling, exhibit significant valley polarization. Between and - valleys, the Berry curvature values are opposite to each other, resulting in the anomalous valley Hall effect.

Effects of air pollution on the development and progression of digestive diseases: an umbrella review of systematic reviews and meta-analyses.

Air pollution, especially particulate matter (PM), is one of the most common risk factors for global burden of disease. However, its effect on the risk of digestive diseases is unclear. Herein, we attempt to explore this issue by reviewing the existing evidence from published meta-analyses.

Development of Zn-CoS@Ni(OH) Heterostructured Nanosheets for High-Performance Supercapacitors.

With the increasing societal demand for sustainable and renewable energy, supercapacitors have become research hotspots. Transition metal oxides, due to their high capacitance and abundant resources, are the preferred electrode materials. However, their poor conductivity and volume changes limit performance enhancement.

Experimental Study on the Effects of Washing Time, Washing Temperature, and Particle Size on the Combustion and Ash Formation Characteristics of Rice Husk.

There are many problems in the direct combustion of biomass, such as low combustion efficiency and easy slagging. In this paper, rice husk (RH) was taken as the research object, and the effects of different washing pretreatment conditions (washing time (WTI), washing temperature (WTE), and particle size) on the combustion characteristics and ash formation characteristics were discussed. The results show that the combustion characteristics of RH were significantly coupling-affected by the WTE and WTI, and the comprehensive characteristics of volatile release were significantly coupling-affected by the particle size and WTI.

The Effect of Ultrasonic Vibration on the 3D Printing Fabrication and Grinding Performance of Structured CBN Grinding Wheel.

The abrasives of traditional grinding wheels are usually randomly arranged on the substrate, reducing the number of effective abrasive grains involved in the machining during the grinding process. However, there are some problems such as uneven distribution of chip storage space, high grinding temperature, and easy surface burn. In trying to address this issue, an ultrasonic vibration 3D printing method is introduced to fabricate the structured CBN (Cubic Boron Nitride) grinding wheel.

Rational Design of V-ZnCoO Nanowires on Nickel Foam: Achieving Superior Capacitance and Mechanical Resilience.

The structural characteristics of electrode materials play a crucial role in their potential applications. Therefore, designing the material's structure rationally is one of the most effective methods to achieve high-performance electrodes. In this study, V-ZnCoO nanowires were synthesized on nickel foam using a simple hydrothermal method, and the prepared V-ZnCoO-2 electrode material exhibited a specific capacitance of 1621 C g.

Optimizing the Ratio of Metallic and Single-Atom Co in CoNC via Annealing Temperature Modulation for Enhanced Bifunctional Oxygen Evolution Reaction/Oxygen Reduction Reaction Activity.

Developing low-cost, efficient alternatives to catalysts for bifunctional oxygen electrode catalysis in the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is critical for advancing the practical applications of alkaline fuel cells. In this study, Co particles and single atoms co-loaded on nitrogen-doped carbon (CoNC) were synthesized via pyrolysis of a CN and cobalt nitrate mixture at varying temperatures (900, 950, and 1000 °C). The pyrolysis temperature and precursor ratios were found to significantly influence the ORR/OER performance of the resulting catalysts.

A Discrete Brain Storm Optimization Algorithm for Hybrid Flowshop Scheduling Problems with Batch Production at Last Stage in the Steelmaking-Refining-Continuous Casting Process.

The iron and steel industry is energy-intensive due to the large volume of steel produced and its high-temperature and high-weight characteristics, sensors such as high-temperature application sensors can be utilized to collect production data and support the process control and optimization. Steelmaking-refining-continuous casting (SRCC) is a bottleneck in the iron and steel production process. SRCC scheduling problems are worldwide problems and NP-hard.

LFformer: An improved Transformer model for wind power prediction.

Wind power forecasting has complex nonlinear features and behavioral patterns across time scales, which is a severe test for traditional forecasting techniques. To address the multi-scale problem in wind power forecasting, this paper innovatively proposes an ultra-short-term forecasting model LFformer based on Legendre-Fourier, which firstly focuses on the important information in the input sequences by using the encoder-decoder architecture, and then scales the range of the original data with the Devlin normalization method, and then utilizes the Legendre polynomials to The data sequence is projected into a bounded dimensional space, the historical data is compressed using feature representation, then feature selection is performed using the low-rank approximation method of Fourier Transform, the prediction is inputted into the multilayer perceptron through the multi-scale mixing mechanism, and finally the results are outputted after back-normalization. The experimental results show that compared with the existing prediction methods, the model realizes the improvement of prediction accuracy and stability, especially in the ultra-short-term prediction scenario, with obvious advantages.

The long-term transformation of Fe-As coprecipitates at room temperature under oxic conditions: New insights for the fate and the speciation of As.

The long-term stability of Fe-As coprecipitates, a typically hydrometallurgical or naturally produced As-bearing wastes in tailings or in other environments, is critical to evaluating the As risk caused by them. A wide pH range, different Fe/As molar ratios, reaction media, and neutralization reagents were considered in order to find the mechanisms controlling the fate of As during the 1640 days of transformation at 25 °C. The results indicated that at pH 4 and 12, As continuously released from the solid phase.