Development and precision evaluation of a robotic system for oral implant surgery using personalized digital guides and optical spatial positioning technology.

Oral implant surgery demands a high level of precision and expertise, making the integration of robotic assistance an optimal solution. This study introduces an innovative dental implant robotic system designed to enhance accuracy during cavity preparation by combining robotic technology, optical spatial positioning, and personalized digital implant guides. The system employs an EC66 six-degree-of-freedom robotic arm, integrated with digital implant guides and optical navigation technology.

Chiral Molecular Rotors Based on Mixed (Phthalocyaninato)(Porphyrinato) Rare-Earth Triple-Decker Complexes.

The effective control over the rotary motions of molecular rotors still remains an enormous challenge. Herein, mixed (phthalocyaninato)(porphyrinato) rare-earth triple-decker complexes ()-/()- and ()-/()- have been designed and investigated as a new type of molecular rotors with a phthalocyanine ligand as the rotator and a strapped bisporphyrin ligand as the stator. The rotational rates and thermodynamic parameters of the rotors were determined through variable-temperature H NMR experiments, revealing a higher rotational rate and a reduced rotational barrier for ()-, in comparison to those of ()-.

Leveraging industry 4.0 technologies and industrial symbiosis: Advancing circular economy practices in BRICS economies.

In addressing the dynamics of a circular economy (CE), Industry 4.0 technologies (IN4.0T) and Industrial Symbiosis (IS) necessitate meticulous management strategies to optimize their advantageous impacts on circular practices.

Preparation and Properties of Low-Exothermic Polyurethanes Doped with Modified Hydrated Salt Phase Change Materials.

In this study, fumed silica (FS) was used as a support material and infused with the hydrated salt sodium hydrogen phosphate dodecahydrate (DHPD) to create shape-stabilized constant phase change materials (CPCMs). These CPCMs were integrated into a polyurethane matrix as a functional filler, resulting in low-exothermic polyurethane composite foams (CPCM-RPUFs) that demonstrate thermoregulation and flame-retardant properties. Recent findings show that CPCM-RPUF excels in thermal stability compared to pure polyurethane, with a melt phase transition enthalpy of 115.

Artificial Proton Channel Membrane with Self-Amplified Selectivity for Simultaneous Waste Acid Recovery and Power Generation.

Proton channels have both high permeability and selectivity, a property that remains unparalleled by artificial materials yet is highly demanded in many applications, including acid recovery and power generation. This work takes inspiration from the structure and surface chemistry of biological proton channels and presents a method to construct covalent organic framework (COF) membranes consisting of high-performance artificial proton channels. The membrane was purposefully rendered amorphous, which eliminates most of the nanoscale pores and induces high steric hindrance to ions.

Prediction of Soil Pollution Risk Based on Machine Learning and SHAP Interpretable Models in the Nansi Lake, China.

To assess and predict the Nansi Lake soil pollution risk, we evaluate the soil environmental quality in the Nansi Lake region using machine learning techniques, combined with the SHapley Additive exPlanations (SHAP) model for interpretability. The primary objective was to predict the level of soil pollution caused by heavy metals, incorporating the traditional Pollution Load Index (PLI) and Potential Ecological Risk Index (PERI) methods. Through the integration of statistical characteristics, PLI, and PERI evaluations, a new assessment method was created, categorizing soil pollution into "Class0-no risk", "Class1-low risk", and "Class2-high risk".

Intelligent Systems for Inorganic Nanomaterial Synthesis.

Inorganic nanomaterials are pivotal foundational materials driving traditional industries' transformation and emerging sectors' evolution. However, their industrial application is hindered by the limitations of conventional synthesis methods, including poor batch stability, scaling challenges, and complex quality control requirements. This review systematically examines strategies for constructing automated synthesis systems to enhance the production efficiency of inorganic nanomaterials.

Experimental and numerical studies on fluid flow through fractured rock masses based on an enhanced three-dimensional discrete fracture network model.

Fluid flow through rock fracture networks was experimentally and numerically studied based on an enhanced discrete fracture network (DFN) model that explicitly characterizes 3D void geometry within rough-walled fracture. Fluid flow tests under different hydraulic gradients J were conducted on a series of DFN samples created by a 3D printer. Meanwhile, numerical simulations were performed based on the enhanced DFN model solving the NS equations and conventional DFN model solving the Reynolds equation, respectively.

Influence of discrete fracture network on the performance of enhanced geothermal system considering thermal-hydraulic-mechanical multi-physical field coupling.

The long-term circulation of cold water within the deep heat reservoir in enhanced geothermal system (EGS) involves dynamic evolution of thermal-hydraulic-mechanical (THM) fields. The characteristics of discrete fracture network (DFN) in the reservoir also affect the thermal performance of EGS. In this paper, the influence of the DFN on the performance of EGS considering THM multi-physical field couple was numerically investigated.

Trajectory prediction via proposal guided transformer with out way attention.

The accurate prediction of the behavior of surrounding agents is crucial for the safe operation of autonomous vehicles. Currently, the dominant approach involves manually defining rules, which often fail to cover all potential scenarios. To address the rigidity and challenges of generalizing these rules to real-world driving contexts, we introduce a novel attention mechanism called "Out Way Attention".

A new fault diagnosis method for reciprocating piston pump based on feature fusion of CNN and transformer encoder.

Reciprocating piston pump is an important power equipment in coal mine production, so the research on condition monitoring and fault diagnosis of reciprocating piston pump is of great significance. It is challenging to extract fault information from monitoring data due to the complex underground environment and serious noise. The existing methods have the problems of insensitive feature extraction and low diagnostic accuracy.

Electrochemiluminescence and fluorescence dual-mode monitoring of aflatoxin B1 production based on single Ru-MOF particles and FITC luminophores.

Herein, an electrochemiluminescence (ECL) and fluorescence (FL) dual-mode imaging biosensing platform was developed for onsite and dynamic monitoring of aflatoxin B1 (AFB1) production in the corn molding process. Zinc metal organic framework structures encapsulated with Ru(bpy) (Ru-MOF) were employed as ECL signal probes for single particle imaging with stable luminescent intensity and high emission efficiency. Fluorescein Isothiocyanate (FITC) luminophores, served as fluorescent probes, were conjugated with AFB1 aptamer modified on the electrode surface, which enabled the observation of green luminescent spots in FL mode.

Enhanced nitrogen removal in constructed wetlands filled with iron-carbon substrates: Reexploring unique roles of iron-cycling and electroactive microorganisms.

Bacteria involved in iron cycle and electroactivity are commonly found in intensified constructed wetlands (CWs) with iron-carbon substrates. However, their roles in nitrogen (N) removal remain unclear. Here, two types of CWs with different filling modes (separate and mixed) of sponge iron and biochar substrates under micro-oxygen regulation (2 h/d, 60 mL min) were constructed for nitrogen removal for 240 days.

Semantic and relation aware neural network model for bi-class multi-relational heterogeneous graphs.

This paper constructs three bi-class multi-relational heterogeneous graphs based on real-world data, and it proposes a semantic and relation aware neural network model (SRA-BMHN) designed for bi-class multi-relational heterogeneous graphs. SRA-BMHN consists of two core modules: first, the semantic-aware module, which integrates diverse relational semantic information using a non-linear mapping function and attention mechanism tailored to specific relationship semantics; second, the relation-aware module, which employs a hierarchical bipartite subgraph aggregation strategy. This module first divides the bi-class multi-relational heterogeneous graphs into multiple bipartite subgraphs based on different edge relationship types and captures the topological information within them.

Analysis of the Wetting Behavior and Kinetic Mechanism of Non-Ionic Surfactants on the Micro Interface of Coal: A Case Study.

This study addresses the issue of varying the wetting effects of surfactants in coal dust control. Utilizing low-field nuclear magnetic resonance (LF-NMR) experiments and molecular dynamics (MD) simulations, it reveals the microscopic wetting mechanism of nonionic surfactant fatty alcohol polyoxyethylene ether (JFCS) on different coal ranks. The results indicate that JFCS can reduce the attractive forces between molecules on the coal surface, promoting the diffusion of water molecules at the coal interface.

Plasma-Induced Wrinkle-Crack Dual Structure for Robust Directional Strain Sensing in Dynamic Motion Perception.

Flexible multi-directional sensors hold vast potential for complex application scenarios, yet creating sensitive, stable, and linear strain sensors capable of flexibly detecting multi-directional strain remains a significant challenge. Here, a plasma-induced wrinkle-crack dual structure is introduced for multi-directional force detection of high-reliability flexible strain sensors. By combining pre-stretching and oxidative plasma bombardment, a multi-layer structure exhibits film stress engineering with varying elastic moduli established on the surface of the elastomer.

Dual-Filter Cross Attention and Onion Pooling Network for Enhanced Few-Shot Medical Image Segmentation.

Few-shot learning has demonstrated remarkable performance in medical image segmentation. However, existing few-shot medical image segmentation (FSMIS) models often struggle to fully utilize query image information, leading to prototype bias and limited generalization ability. To address these issues, we propose the dual-filter cross attention and onion pooling network (DCOP-Net) for FSMIS.

An Enhanced, Real-Time, Low-Cost GNSS/INS Integrated Navigation Algorithm and Its Platform Design.

The integration of the global navigation satellite system (GNSS) and the inertial navigation system (INS) is a well-established method for achieving accurate positioning, especially in applications involving unmanned aerial vehicles (UAVs). UAVs are increasingly used across various fields, yet they face challenges such as the need for real-time processing and the impact of low-quality measurements from cost-effective devices. To address these challenges, we propose a velocity-constrained, enhanced, real-time, low-cost, GNSS/INS integrated navigation algorithm and design an algorithmic platform based on the open-source software KF_GINS.

Self-Adaptive Gyroscope-Structured Hybrid Triboelectric-Electromagnetic Buoy System for Real-Time Ocean Currents Monitoring.

With the rapid development of Internet of Things (IoT) technology, sensors have become the most important nodes for information exchange in the IoT. However, ensuring stable power supply and network communication of a plethora of distributed sensing nodes has become the key technical bottleneck that restricts the development of marine IoT. Herein, a self-adaptive gyroscope-structured hybrid triboelectric-electromagnetic nanogenerator (SAG-HTENG) is designed for omnidirectional wave energy harvesting.

Psychological mechanisms of healthy lifestyle and academic burnout: a moderated mediation model.

Objective: Academic burnout is a prevalent phenomenon among college students. According to the Conservation of Resources Theory, when there is an imbalance between invested resources and expected returns, individuals may suffer from academic or job burnout. If an individual has sufficient resources, these resources may relieve the negative problem.

Preparation of nanofiber membrane based on recycled keratin from chicken eggshell and its preliminary application in membrane distillation.

The inner eggshell membrane (ESM) sanctions the unfettered conveyance of air across the membrane, ensuring the air provision for embryonic development. As such, the electrostatic spinning technique was availed to fabricate large-scale and flat-sheet 'artificial' eggshell membranes by extracting keratin from waste egg membranes. Keratin within eggshell membranes was initially extracted the chemical reduction method.

Wheat bran supplementation improved polystyrene degradation efficiency of Zophobas atratus larvae by alleviating intestinal injury caused by polystyrene-intake.

Wheat bran supplementation significantly improves the polystyrene consumption capacity of Zophobas atratus larvae. However, the underlying mechanism remains unclear, limiting further advancements in degradation efficiency. This study seeks to clarify the mechanism by analyzing intestinal morphology, gut microbiota structure, gene transcription, and targeted metabolites.

An enhanced lightweight model for apple leaf disease detection in complex orchard environments.

Automated detection of apple leaf diseases is crucial for predicting and preventing losses and for enhancing apple yields. However, in complex natural environments, factors such as light variations, shading from branches and leaves, and overlapping disease spots often result in reduced accuracy in detecting apple diseases. To address the challenges of detecting small-target diseases on apple leaves in complex backgrounds and difficulty in mobile deployment, we propose an enhanced lightweight model, ELM-YOLOv8n.

Synthesis of core/shell cobalt-doped rutile TiO nanorods for MB degradation under visible light.

Although TiO has been widely applied in many fields, the design and preparation of one-dimensional rutile TiO nanomaterials for high-efficiency photocatalysis under visible light remain challenging. Herein, uniform Co-doped rutile TiO nanorods with selective adsorption and photocatalytic activity for methylene blue (MB) have been developed a one-pot molten salt flux method. Compared to pure rutile TiO nanorods, the Co-doped rutile TiO nanorods exhibited an obvious core/shell structure with smaller inner crystal face spacing ( = 0.

Silico-oxygen bonding integrated with nano-size pore enrichment enables sustainable low-oxidant-consumption Fenton-like chemistry.

Key bottlenecks of the persulfate-based advanced oxidation processes (AOPs) are the high dosage of persulfate and the secondary pollution of sulfate ion. In this work, a sustainable strategy involving the transformation of diatomite into a water purification catalyst consisting of nano-size pore enrichment and silico-oxygen bonding (Si/C@BD) was proposed. Results indicated that the pollutants with electron-donating groups can be quickly degraded by the Si/C@BD via amplified electron transfer process (ETP) under very low peroxymonosulfate (PMS) usage.