Low Processing Efficiency Research Articles

Research Progress in the Construction of Delirium Risk Warning Model for ICU Patients Based on Decision Tree: A Review of the Literature

Intensive Care Unit (ICU) delirium is a cerebral syndrome characterized by acute disturbance of consciousness, with an incidence of 38%-87%. The occurrence of delirium can lead to prolonged hospital stay, accidental extubation rate, mortality and other adverse consequences. Therefore, early identification of delirium and active correction of reversible causes appear to be particularly important. At present, the risk prediction models for delirium in ICU constructed at home and abroad mainly use logistic regression to build delirium risk prediction models for patients admitted to ICU≥24h. However, studies have found that as many as 25% of critically ill patients will develop delirium within 24h of admission to ICU. Therefore, it is particularly important to construct a delirium early warning model for patients entering ICU24h. Logistic regression model has low processing efficiency for non-linear and interactive data, and can not intuitively show the importance of each variable in the predicted result. As a non-parametric statistical method, decision tree can overcome the disadvantages of Logistic regression model and build a better prediction model. Therefore, this study used 24h after admission to ICU as the segmentation point to build a decision tree model for predicting early and late delirium in ICU patients, forming a corresponding risk level system, and compared it with similar delirium models to verify the predictive value of the decision tree model for early and late delirium in ICU patients, providing a basis for the formulation of further intervention and nursing plans. Thereby reducing the incidence of ICU delirium.

Fatigue Performance of Ti-6Al-4V Processed by Wire-Arc Directed Energy Deposition

AbstractTi-6Al-4V has a wide range of applications, but long lead times and low-efficiency processing of the material leads to limitations. Through additive manufacturing, such as wire-arc directed energy deposition, higher processing efficiency, and lower lead times are possible. To fully realize the benefits, an important parameter for application is the fatigue performance, which needs to be better documented and performance shortcomings improved. Currently, available results on fatigue performance of wire-arc directed energy deposition of Ti-6Al-4V are limited. Therefore, wire-arc directed energy deposition of Ti-6Al-4V was used with the following approach. Samples were characterized using scanning electron microscopy and optical light microscopy, and mechanically tested for tensile and fatigue performance. Minimal pore density and a fine α microstructure within coarsened epitaxial columnar β-grains was observed. Additionally, elemental burn-off and oxygen contamination was assessed, showing a loss of 0.2 wt.% aluminum during processing and no oxygen pick-up. Compared to other cold metal transfer-based wire-arc directed energy deposition results available in the literature, the results present significant improvements. Fractography indicated mixed fracture modes, which are likely due to the macro-zones of α having varying orientations. Our work provides an advancement in fatigue performance and processing, further showing the potential of the technology.

DC-SoC: Optimizing a Blockchain Data Dissemination Model Based on Density Clustering and Social Mechanisms

Due to its partially decentralized and highly scalable features, the consortium blockchain has currently overtaken other blockchain technologies as the one most frequently used and studied across various industries. However, performance issues such as low transaction efficiency and redundant communication processes continue to hinder the development of consortium blockchains. In the Hyperledger Fabric consortium blockchain system, transaction efficiency is largely influenced by the consensus protocol and broadcast protocol. This paper introduces a novel consortium blockchain network model, DC-SoC, focused on optimizing broadcast protocols. By incorporating the concept of density clustering, a stable propagation structure is established for the blockchain network, thus optimizing data dissemination in the Gossip protocol. Additionally, the concept of social networks is integrated, using trustworthiness scores and economic incentives to evaluate node security. The experimental results demonstrate that when DC-SoC is applied in a large-scale consortium blockchain environment, it significantly improves communication performance between nodes and ensures transmission reliability.

Prediction and Analysis of Borosilicate Glass Surface Deformation Induced by Flame Jet

To address the issues of low processing efficiency, poor forming accuracy, and internal damage in glass material processing, this study proposes the use of flame jet forming. However, the mechanism of flame jet processing requires further elucidation. This research investigates the relationship between the indentation morphology on the glass surface and the inlet velocity of the flame jet. A theoretical model was established through mathematical analysis to reflect this relationship. The model’s accuracy was validated using numerical simulation methods. By comparing experimental data with theoretical model results, surface tension was incorporated, and the model was iteratively optimized using MATLAB R2024a. The final optimized model demonstrated an absolute error range of 0.009 to 0.069 mm. This study confirms the feasibility of flame jet processing and enriches the understanding of its mechanism, providing a novel, efficient, and precise method for processing glass materials.

A Force Control Method Integrating Human Skills for Complex Surface Finishing

Force control is one of the core modules for surface finishing such as grinding, polishing and sanding. However, the current force control methods based on human skills lack in-depth analysis of data patterns or are only applicable to flat surfaces. In addition, surface finishing is mainly performed by hand, resulting in low processing efficiency and poor product consistency. Therefore, this paper proposes a force control method that incorporates human skills to achieve relatively accurate force skill transfer and complex surface finishing. Firstly, human skills consisting of the force skill and the motion skill are learned. The force skill is used to generate the desired force. Then, a series of discrete poses are obtained based on human demonstration and combined with the motion skill to generate the desired trajectory. Finally, a computed-torque impedance control method is proposed to achieve relatively accurate force skill transfer and complex surface finishing by incorporating the desired trajectory and the desired force. The experiments are conducted on a platform composed of a 7-DOF collaborative robot manipulator from Franka Emika and a complex violin surface. The results demonstrate that the proposed force control method can achieve relatively accurate force skill transfer and improve the surface quality of the workpiece.

Force rheological polishing of polycrystalline magnesium aluminate spinel using agglomerated diamond abrasive

The high hardness and polycrystalline structure of polycrystalline magnesium aluminate spinel (PMAS) present significant challenges in achieving high-precision processing, particularly during polishing. Issues such as low processing efficiency and grain effects can compromise processing accuracy, surface quality, and optical performance. To address these challenges and enhance both polishing efficiency and surface quality, this study employed agglomerated diamond (AD) abrasives and single crystal diamond (SCD) abrasives in force rheological polishing (FRP). The experimental results revealed that the lowest surface roughness (Sa) and optimal selective material removal were achieved using 25 μm AD abrasives, particularly those agglomerated with 0.2 μm SCD abrasives. This approach reduced Sa from 146.1 nm to 4.6 nm, peak-to-valley height difference (Sz) from 1329 nm to 69.3 nm and achieved a material removal rate (MRR) of 228.8 nm/min. Conversely, polishing with 1 μm SCD abrasives resulted in poorer selective material removal, with Sz decreasing from 1265.1 nm to 280.9 nm and Sa decreasing from 138.3 nm to 27.6 nm, although it exhibited the highest MRR of 323.64 nm/min. The superior polishing results obtained with AD abrasives, compared to SCD abrasives of the same size, can be attributed to the polycrystalline-like structure of AD abrasives, which exhibit more micro cutting edges. Additionally, the surface and subsurface damage after polishing with AD abrasives was analyzed. The results indicated that material removal of PMAS using AD abrasives was effective in FRP, resulting in minimal lattice distortion. This study provides both theoretical and experimental foundations for polishing PMAS using larger-sized AD abrasives in FRP.

Selective ion channel adsorbents facilitate efficient and low environmental impact extraction of liquid lithium resources

As lithium is the cornerstone of green energy development, it is crucial to realize a low environmental impact and efficient lithium extraction process. Ion-sieve adsorption is the most widely used method to extract liquid lithium resources, but this method is only efficient under alkaline conditions for H+ and Mg2+ competing adsorption. Conventional methods are often accompanied by the consumption of quantities of alkali, the generation of solid waste, and the acidification of liquid lithium resources. To address these issues, a selective ion-channel adsorbent was constructed. The composition comprises an ion sieve adsorbent and an organic carrier with a zwitterionic quaternary ammonium base group. This group storages OH-in situ, hinders H+ diffusion, slows down Mg2+ diffusion, and accelerates Li+ diffusion by relying on the difference in binding energies, which reduces the competing adsorption and avoids acidification and solid waste generation. The saturated adsorption capacity (21.38mg/g) and selectivity of the adsorbent are 4.7 and 24 times higher than that of conventional ion-sieve adsorbent under neutral conditions respectively. The dosage of alkali is 1/256 of the traditional method, the effluent remains neutral and no solid waste is generated. This study presents an environmental and effective adsorbent for lithium extraction.

From β-Carotene to Retinoids: A Review of Microbial Production of Vitamin A.

Vitamin A (retinoids) is crucial for human health, with significant demand across the food, pharmaceutical, and animal feed industries. Currently, the market primarily relies on chemical synthesis and natural extraction methods, which face challenges such as low synthesis efficiency and complex extraction processes. Advances in synthetic biology have enabled vitamin A biosynthesis using microbial cell factories, offering a promising and sustainable solution to meet the increasing market demands. This review introduces the key enzymes involved in the biosynthesis of vitamin A from β-carotene, evaluates achievements in vitamin A production using various microbial hosts, and summarizes strategies for optimizing vitamin A biosynthesis. Additionally, we outline the remaining challenges and propose future directions for the biotechnological production of vitamin A.

Insights into the role of electrochemical stimulation on sulfur-driven biodegradation of antibiotics in wastewater treatment

The presence of antibiotics in wastewater poses significant threat to our ecosystems and health. Traditional biological wastewater treatment technologies have several limitations in treating antibiotic-contaminated wastewaters, such as low removal efficiency and poor process resilience. Here, a novel electrochemical-coupled sulfur-mediated biological system was developed for treating wastewater co-contaminated with several antibiotics (e.g., ciprofloxacin (CIP), sulfamethoxazole (SMX), chloramphenicol (CAP)). Superior removal of CIP, SMX, and CAP with efficiencies ranging from 40.6 ± 2.6 % to 98.4 ± 1.6 % was achieved at high concentrations of 1000 μg/L in the electrochemical-coupled sulfur-mediated biological system, whereas the efficiencies ranged from 30.4 ± 2.3 % to 98.2 ± 1.4 % in the control system (without electrochemical stimulation). The biodegradation rates of CIP, SMX, and CAP increased by 1.5∼1.9-folds under electrochemical stimulation compared to the control. The insights into the role of electrochemical stimulation for multiple antibiotics biodegradation enhancement was elucidated through a combination of metagenomic and electrochemical analyses. Results showed that sustained electrochemical stimulation significantly enriched the sulfate-reducing and electroactive bacteria (e.g., Desulfobulbus, Longilinea, and Lentimicrobiumin on biocathode and Geobactor on bioanode), and boosted the secretion of electron transport mediators (e.g., cytochrome c and extracellular polymeric substances), which facilitated the microbial extracellular electron transfer processes and subsequent antibiotics removal in the sulfur-mediated biological system. Furthermore, under electrochemical stimulation, functional genes associated with sulfur and carbon metabolism and electron transfer were more abundant, and the microbial metabolic processes were enhanced, contributing to antibiotics biodegradation. Our study for the first time demonstrated that the synergistic effects of electrochemical-coupled sulfur-mediated biological system was capable of overcoming the limitations of conventional biological treatment processes. This study shed light on the mechanism of enhanced antibiotics biodegradation via electrochemical stimulation, which could be employed in sulfur-mediated bioprocess for treating antibiotic-contaminated wastewaters.

A Fish Target Identification and Counting Method Based on DIDSON Sonar and YOLOv5 Model

In order to more accurately and quickly identify and count underwater fish targets, and to address the issues of excessive reliance on manual processes and low processing efficiency in the identification and counting of fish targets using sonar data, a method based on DIDSON and YOLOv5 for fish target identification and counting is proposed. This study is based on YOLOv5, which trains a recognition model by identifying fish targets in each frame of DIDSON images and uses the DeepSort algorithm to track and count fish targets. Field data collection was conducted at Chenhang Reservoir in Shanghai, and this method was used to process and verify the results. The accuracy of random sampling was 83.56%, and the average accuracy of survey line detection was 84.28%. Compared with the traditional method of using Echoview to process sonar data, the YOLOv5 based method replaces the step that requires manual participation, significantly reducing the time required for data processing while maintaining the same accuracy, providing faster and more effective technical support for monitoring and managing fish populations.

A digital resource copyright protection scheme based on blockchain cross-chain technology

With the expansion of the digital publishing industry, copyright infringement of digital resources has become increasingly rampant. Blockchain technology offers a promising solution for copyright protection of digital resources. However, existing copyright protection methods based on single-chain or consortium blockchains have disadvantages such as low system processing efficiency, poor scalability, and a lack of alignment with real-world business needs. To address the current challenges of blockchain technology in the field of copyright protection and establish a more effective solution for protecting digital resource copyrights, while also expanding the application of blockchain cross-chain technology and promoting its development, leveraging blockchain cross-chain theory, technology, and methods, a digital resource copyright protection scheme based on blockchain cross-chain technology was constructed. It outlines detailed processes for copyright registration, resource transactions, copyright modifications, and copyright enforcement. Furthermore, this copyright protection scheme was analyzed. The findings indicated that the blockchain cross-chain technology is suitable for digital resource copyright protection. The proposed copyright protection scheme can allow various stakeholders to better fulfill their roles, in addition to enhancing the overall maintainability and scalability of the blockchain system.

Building Electrochemical Roadmaps for Decarbonization in the Specialty Chemical Sector

Greenhouse gas emissions from the chemical manufacturing industry are enormous, by some estimates they amount to 5% percent of the global total.1,2 Moreover, chemical manufacturing is widely considered as a “difficult-to-decarbonize” sector due to the deeply entrenched reliance on crude-based hydrocarbons as fuels and feedstocks.3 The ultimate goal of eliminating anthropogenic greenhouse gas emissions, clearly demands a wholesale reconsideration of energy and material flows in chemical manufacturing.One area of research that has gained momentum in the past decade is the use of electrochemistry to perform organic redox reactions. These types of electrosynthetic transformations provide a straightforward means to electrify chemical manufacturing, thereby decreasing the global warming impact as the carbon intensity of grid electricity diminishes with continued adoption of low-carbon power sources. Further improvements are achievable through decarbonization of material inputs, e.g., by replacing problematic redox reagents like methane-derived hydrogen or fuming nitric acid with reactive hydrogen and oxygen intermediates generated at electrodes via water electrolysis.Despite these promising advances, interest in organic electrosynthesis to date has mainly focused on the production of commodity chemicals (e.g., CO2 reuse, ammonia electrosynthesis) at the expense of specialty chemical synthesis. This focus is well justified based on the possible impact of major breakthroughs on global emissions, but it constitutes missed opportunities to drive broad adoption of electrosynthesis across the chemical industry. To address this knowledge gap, our lab has undertaken a collaborative research effort with a global specialty chemical manufacturer to explore opportunities to decarbonize through electrification strategies involving electrosynthetic reaction schemes.This presentation will detail our recent work on a holistic “scoping study” to estimate the potential for reducing the global warming emissions profiles for a representative set of specialty chemicals through the adoption of electrosynthetic methods. First, we mapped the supply chain for 12 specific chemicals (chosen for their relevance to the specialty industry and significant global warming potential from current production methods) in terms of all reactive processes required to generate these compounds from petrochemical feedstocks. Next, we searched for literature reports detailing electrosynthetic pathways to generate each intermediate species along the manufacturing supply chain. The relevant electrochemical reactions were broadly classifiable as (a) generating alternatives to petrochemical feedstocks; (b) direct replacement of an existing chemical redox reaction with an electrochemical reaction; or (c) intensified approaches that use electrochemistry to reduce the total number of reactive process steps required. Finally, we benchmarked the potential for reduced greenhouse gas emissions for electrosynthetic schemes compared to the incumbent technologies based on a set of simplifying assumptions that involve calculating baseline emissions intensities as a function of the thermodynamic minimum energy input and the carbon intensity of the electric power supply, and further applying generic “efficiency factors” to account for all emissions in excess of this thermodynamic minimum. The results of this analysis suggest remarkable opportunities to develop electrosynthetic schemes for a handful of reactions for which global warming emissions could be reduced even in the most conservative scenarios of low process efficiency and high carbon intensity of the input power.This presentation will also cover the hurdles we have identified in the development of modular and continuously operated electrosynthetic reactors, as well as what we have learned in addressing these challenges.References(1) Saygin, D.; Gielen, D. Zero-Emission Pathway for the Global Chemical and Petrochemical Sector. Energies 2021, 14 (13), 3772. https://doi.org/10.3390/en14133772.(2) Gabrielli, P.; Rosa, L.; Gazzani, M.; Meys, R.; Bardow, A.; Mazzotti, M.; Sansavini, G. Net-Zero Emissions Chemical Industry in a World of Limited Resources. One Earth 2023, 6 (6), 682–704. https://doi.org/10.1016/j.oneear.2023.05.006.(3) Gross, S. The Challenge of Decarbonizing Heavy Industry, 2021. https://www.brookings.edu/wp-content/uploads/2021/06/FP_20210623_industrial_gross_v2.pdf.

Sewage sludge management and enhanced energy recovery using anaerobic digestion: an insight.

Sewage sludge (SS) is a potential source of bioenergy, yet its management is a global concern. Anaerobic digestion (AD) is applied to effectively valorize SS by reclaiming energy in the form of methane. However, the complex floc structure of SS hinders hydrolysis during AD process, thus resulting in lower process efficiency. To overcome the rate-limiting hydrolysis, various pre-treatment methods have been developed to enhance AD efficiency. This review aims to provide insights into recent advancements in pre-treatment technologies, including mechanical, chemical, thermal, and biological methods. Each technology was critically evaluated and compared, and its relative worth was summarized based on full-scale applicability, along with economic benefits, AD performance improvements, and impact on digested sludge. The paper illuminates the readers about existing research gaps, and the future research needed for successful implementation of these approaches at full scale.

Experimental sticking coefficients of CO and N_2 on sub-micrometric cosmic grain analogs

Measuring the sticking coefficient of molecules pertinent to astrochemistry - such as CO - on substrates that mimic interstellar dust grains is crucial for the comprehensive understanding of gas-grain chemical processes. Although astrochemical models assume a sticking coefficient of 1, recent laboratory experiments on H2O and CO2 have revealed significantly lower values when measured on small grain analogs. As the effect of grain size on molecular adsorption has been largely ignored to date, further experiments are needed to determine the accretion rates of species known to freeze out on dust grains. Our aim is to determine the sticking coefficients of CO and N2 on sub-micrometric silicate and carbon grains. By quantifying realistic sticking coefficients on these dust grain analogs, we can improve the accuracy of astrochemists' predictions of molecular abundances as affected by gas-grain interactions. The molecules of interest were added to various substrates at 10 K in an ultra-high vacuum. The amount of adsorbate that stuck to the substrate was quantified using X-ray photoelectron spectroscopy. These quantities were compared to a reference with a sticking coefficient of 1, allowing the deduction of the sticking coefficient for each substrate. The average sticking coefficients of CO and N2 on grain analogs are 0.17 for CO and 0.14 for N2 on olivine powder, and 0.05 for CO and 0.07 on N2 on soot, instead of the presumed 1. This is in line with the low values previously reported for H2O and CO2 These laboratory results indicate that CO and N2 in addition to H2O and CO2 also exhibit a low sticking coefficient on dust grain analogs. It is thus necessary to reconsider the interactions between gaseous species and dust particles as a low-efficiency process. This reduction in accretion and reaction rates has important implications for how we understand astrochemistry.

The Research Progress of Magnesium Alloy Building Formwork.

Building formwork is a kind of temporary supporting structure consumable material used in the construction field. In recent years, building formwork has gradually developed to become lighter, more environmentally friendly, and have higher performance. This sets higher requirements for the materials used to make building formwork. There is an urgent need to find a lighter and more durable material for building formwork. Magnesium alloys possess the advantages of low density, high alkali resistance, and high strength. As a building formwork material, it can reduce the weight of formwork and improve its durability. Therefore, a magnesium alloy is considered a material with high potential for building formwork. Currently, magnesium alloy building formwork has attracted the attention of many companies and research and development institutions, with preliminary research applications and good feedback on usage effects. It is highly possible to obtain the opportunity to put it into market application. However, to be applied on a large scale, there are still some important problems that need to be solved. These problems fall into three main areas, including the relatively low processing efficiency of magnesium alloy materials, the unstable price of magnesium alloys, and the fact that the formwork is easily corroded during storage. Firstly, at present, the main processing methods for magnesium alloy building formwork are casting and extrusion, and the production efficiency of both methods needs to be improved. Secondly, high-performance magnesium alloy materials are usually more expensive, which is not conducive to the large-scale application of the formwork. The price of magnesium alloys has fluctuated greatly in recent years, which increases the difficulty of promoting magnesium alloy building formwork. Thirdly, in the atmosphere, the oxide film on the surface of the magnesium alloy cannot play an effective role in corrosion resistance. So, surface treatment is necessary for magnesium alloy building formwork. Among the various surface treatment methods for magnesium alloys, the chemical conversion method has the advantages of being easy to operate, cost-effective, and having good corrosion resistance. It may be a very suitable protective method for large-scale applications of magnesium alloy building formwork and possesses excellent potential for application. The future of magnesium alloy building formwork will focus on new low-cost materials, high-efficiency processing technology, and low-cost green anti-corrosion technology. With in-depth research and the maturation of technology, magnesium alloy formwork is expected to play a more important role in the construction industry.

Design of Automatic Seaming Machine for Fire Air Ducts with 3D Model and Its Experiment

The fire air duct is one of the important components of the ventilation system in large buildings, which is is a unit system for ventilation and smoke exhaust. The ventilation system is a customized system with a wide range of applications and a high demand, resulting in the use of multiple sizes and specifications of fire air ducts. At the same time, fire air ducts are generally made of thin galvanized iron sheets, which have poor rigidity and are prone to deformation. For the two above-mentioned reasons, the seaming process of the fire air duct is currently mainly completed by manual tapping, resulting in low processing efficiency, high labor intensity, and high cost. Therefore, it is necessary to design an automated equipment that can complete the fire air duct seaming process. Firstly, a 3D model for automatic seaming machine for fire air ducts to demonstrate the working principle and a double head positioning and clamping mechanism is proposed to improve the pipe rigidity; Secondly, to adapt to most specifications for rectangular fire air ducts, a system was designed that utilizes the two right angle ends of the stitching edge for positioning and clamping without many special toolings. Thirdly, a set of automatic seaming prototype has been manufactured based on the above design ideas. The experimental results on the prototype show that the fire air duct automatic stitching machine can seam a fire air duct within 1 minute. Compared with manual processing, the processing efficiency is improved by more than 80%.

High‐Temperature Semiconductor CuO/SiC‐Based Catalyst for Artificial Photosynthesis

AbstractArtificial photosynthesis can convert CO2 and H2O into hydrocarbons via solar energy. However, the extremely low process efficiency is a major obstacle to this application. The photocatalyst is considered to be the key factor to raise the overall solar energy conversion efficiency. Much research focused on co‐catalysts, but less attention has been paid on the high‐temperature semiconductor. Herein, a strategy is proposed involving high‐temperature semiconductor to design target photocatalyst dealing with the artificial photosynthesis at high temperature. Based upon this strategy, a CuO/SiC catalyst with single atom characteristic was designed, prepared and the activity of CO2 photoreduction with H2O was tested in a high temperature environment. Above 150 °C, the catalyst activity was boosted and unprecedented performance values were attained. Under the irradiation condition delivered by a 1000 W Xe light and at 350 °C, the obtained yields of CH4, C2H4, and C2H6 were 2041.4 μmol ⋅ g−1, 15.2 μmol ⋅ g−1, and 63.6 μmol ⋅ g−1, respectively. The overall CO2 conversion reached 24.6 % and the maximum solar energy conversion efficiency was 2.3 % without any sacrificed agents. This strategy will be helpful to overcome the current limitations for the industrialization of artificial photosynthesis and accelerate the related research on photothermal catalysis.

A Method for Preparing Surface Sub-Microstructures on Sapphire Surfaces Using Femtosecond Laser Processing Technology

Femtosecond laser processing technology is an advanced sub-micro-processing technique that enables the non-contact processing of various materials. This technology can be used to apply sub-micro structures for purposes such as hydrophilicity enhancement, optical transmittance improvement, and photonics detection. However, when it comes to processing micro/nanostructures on highly brittle materials using femtosecond lasers, there are challenges such as low processing efficiency, generation of debris, and microcracking. In this paper, we propose a method called the out-of-focus femtosecond laser direct writing technique combined with wet etching. This method offers simplicity, speed, and flexibility in preparing dense, large-area sub-microstructured surfaces on the brittle material sapphire. Our detailed investigation focuses on the impact of laser processing parameters (direct writing period, distance of focusing, direct writing speed, etc.) on the sub-microstructures of Al2O3 surfaces. The results demonstrate that this method successfully creates embedded sub-microstructures on the sapphire surface. The microholes, with a diameter of approximately 2.0 μm, contain sub-micro structures with a minimum width of 250 ± 20 nm. Additionally, we conducted experiments to assess the optical transmittance of sapphire nanostructures in the range of 350–1200 nm, which exhibited an average transmittance of approximately 77.0%. The water contact angle (CA) test yielded a result of 52 ± 2°, indicating an enhancement in the hydrophilicity of the sapphire nanostructures with only a slight reduction in optical transmittance. Our efficient fabrication of sub-microstructures on the sapphire surface of highly brittle materials offers a promising method for the production and application of brittle materials in the field of micro-optics.

Ultrasonic vibration cutting of advanced aerospace materials: a critical review of in-service functional performance

PurposeUnconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.Design/methodology/approachThe surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.FindingsTo address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.Originality/valueThis study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

Neural network big data fusion in remote sensing image processing technology

Abstract Remote sensing (RS) image processing has made significant progress in the past few years, but it still faces some problems such as the difficulty in processing large-scale RS image data, difficulty in recognizing complex background, and low accuracy and efficiency of processing. In order to improve the existing problems in RS image processing, this study dealt with ConvNext-convolutional neural network (CNN) and big data (BD) in parallel. Moreover, it combined the existing RS image processing with the high dimensional analysis of data and other technologies. In this process, the parallel processing of large data and high-dimensional data analysis technology improves the difficulty and low efficiency of large-scale RS image data processing in the preprocessing stage. The ConvNext-CNN optimizes the two modules of feature extraction and object detection in RS image processing, which improves the difficult problem of complex background recognition and improves the accuracy of RS image processing. At the same time, the performance of RS image processing technology after neural networks (NNs) and BD fusion and traditional RS image processing technology in many aspects are analyzed by experiments. In this study, traditional RS image processing and RS image processing combined with NN and BD were used to process 2,328 sample datasets. The image processing accuracy and recall rate of traditional RS image processing technology were 81 and 82%, respectively, and the F1 score was about 0.81 (F1 value is the reconciled average of accuracy and recall, a metric that combines accuracy and recall to evaluate the quality of the results, a higher F1 value indicates a better overall performance of the retrieval system). The accuracy rate and recall rate of RS image processing technology, which integrates NN and BD, were 97 and 98%, respectively, and its F1 score was about 0.97. After analyzing the process of these experiments and the final output results, it can be determined that the RS image processing technology combined with NN and BD can improve the problems of large-scale data processing difficulty, recognition difficulty under complex background, low processing accuracy and efficiency. In this study, the RS image processing technology combined with NN and BD has stronger adaptability with the help of NN and BD technology, and can adjust parameters and can be applied in more tasks.