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In this study, a thermal–phase–mechanical coupled numerical model was presented for the prediction of the distribution of temperature, phase and residual stress of 42CrMo steel during two-track laser hardening process. Austenite and tempering transformation were simulated based on the isoconversional method. K-M equation was used to calculate the fraction of martensite. Residual stress was calculated considering the thermal strain, transformation strain and transformation plasticity. The accuracy of the numerical model was verified according to the comparison with experimental results. The stress distribution of two-track laser hardening process was studied according to numerical simulation results. And the effect of the second track on the residual stress produced by the first track in two-track laser hardening was also analyzed by using this numerical model.

This article reviews plant-derived exosome-like nanoparticles (ELNs), and highlights their potential in regenerative medicine. Various extraction techniques, including ultracentrifugation and ultrafiltration, and their impact on ELN purity and yield were discussed. Characterization methods such as microscopy and particle analysis are found to play crucial roles in defining ELN properties. This review is focused on exploring the therapeutic potential of ELNs in tissue repair, immune regulation, and antioxidant activities. Further research and optimization methods for extraction of ELNs to realize clinical potential applications are necessary. [ABSTRACT FROM AUTHOR]

Alveolar bone defects are often irregular in shape and can severely affect patients' physical and psychological well-being, posing significant challenges in treatment, particularly in cases complicated by systemic diseases. This study presents a shape-adaptive hydrogel with sequential antibacterial and osteogenic functions designed to repair irregular bone defects associated with osteoporosis. Naringin, an estrogen analogue, was conjugated to the hydrogel via disulfide bonds and then uniformly mixed with nano-hydroxyapatite (nano-HAP) to create microspheres. These microspheres were uniformly dispersed within the naringin-loaded hydrogel, forming an injectable and photocurable suspension. Upon implantation, naringin is rapidly released due to diffusion along the concentration gradient and initial hydrogel degradation, providing antibacterial effects and preventing infection. As bone repair progresses, the hydrogel undergoes further degradation and the disulfide bonds break, so that naringin is continuously released, which enhances osteoblast differentiation and inhibits osteoclast differentiation. Material characterization confirmed the presence of disulfide bonds and the sustained release profile of naringin. Both in vitro and in vivo experiments demonstrated the hydrogel's excellent biocompatibility and its effectiveness in repairing regular mandibular defects as well as irregular alveolar bone defects associated with osteoporosis. This hydrogel provides a promising strategy for the development of advanced biomaterials tailored to the complex requirements of irregular bone defect repair under osteoporotic conditions. [ABSTRACT FROM AUTHOR]

Background: Dementia is a growing public health issue. Non-drug interventions targeting individuals before the onset of overt cognitive decline may be effective. Subjective cognitive decline (SCD) is present in > 50% of older adults and associated with progression to dementia. Here, we tested the compliance and effectiveness of a Multidomain Lifestyle Intervention Program using the mini-program, Cognitive Evergreenland, (MLIP-CE), based on the Health Action Process Approach model to support home-based intervention in older adults with SCD. Methods: Cognitive Evergreenland was designed to improve cognitive reserve and maintain brain function in people at high risk of dementia and included: cognitive stimulation, cognitive training, health education, vascular risk monitoring, social support, and functional assessment, among other features. This was an exploratory trial designed to examine participant compliance with the mobile lifestyle intervention and its effectiveness, as well as changes in health-related indicators and cognitive function of older adults with SCD from baseline to 12 and 24 weeks post-intervention. Results: The retention rate for MLIP-CE was 90.2% (37/41). Mean participant age was 70.93 ± 6.91 years, 73.2% of participants were female, and mean Montreal Cognitive Assessment score was 24.51 ± 2.87. Throughout the 24 weeks of the prescribed intervention, app usage remained consistently high, with over 92% of participants using the mini-program at least once a week and successfully completing corresponding health management tasks. In terms of average usage, cognitive training emerged as the most frequently used functional module (95.73%), closely followed by health education (95.02%). The health behavior levels of older adults with SCD, measured in terms of ability, opportunity, and motivation, were significantly increased relative to baseline (p < 0.001). Regarding cognitive function, Mini-Mental State Examination scores were significantly improved post-intervention, with a moderate effect size (Hedges' g = 0.60). Conclusions: These findings suggest that MLIP-CE, which was designed based on a theoretical framework, has potential for implementation, and support ongoing research into use of MLIP-CE for individuals at high risk of SCD or other dementia conditions. Trial registration: The trial was prospectively registered at the Chinese Clinical Trials Registry with the registration number ChiCTR2200058665 on 13 April 2022. [ABSTRACT FROM AUTHOR]

A strategy was proposed for the synthesis of Mo2C/C composite as an efficient electrocatalyst through electrospinning and calcination. PVP and PAN were utilized as electrospinning precursors for comparative analysis. Morphological characterization revealed that an electrospinning solution with the viscosity in the range of 2–5 mPa·S was conducive to the formation of spherical morphology. Under calcination at nitrogen atmosphere, as-electrospun Mo@PVP-1 and Mo@PAN-1 samples transformed into Mo2C/C with bead-like structure at 900 and 800 °C, respectively. Compared to PVP, PAN exhibited greater resistance to deformation at elevated temperature, resulting in better-dispersed spherical Mo2C/C composite. The synthesized Mo2C/C exhibited good electrocatalytic activity for hydrogen evolution reaction. The Tafel slopes of Mo2C/C prepared from Mo@PVP-1-900 and Mo@PAN-1-800 were 75.85 and 164.7 mV·dec−1, respectively. This work contributes to the understanding of synthetic process of spherical Mo2C/C composites through electrospinning, providing an effective way to improve material performance. Mo2C/C composites were synthesized by calcination with different polymer solutions (PAN and PVP) by electrostatic spraying, and their performance as catalysts was tested. [ABSTRACT FROM AUTHOR]

WO3, due to its intrinsic property as an acidic oxide, is a promising candidate as gas sensing material towards toxic gases such as trimethylamine (TEA). In order to further improve the performance of WO3-based gas sensors, a preparation method is provided in this study to synthesize nanostructured WO3 with WS2 as precursor via in-situ oxidation procedure. During preparation, a chemical oxidation treatment was conducted on WS2 by immersing it in different oxidizing solutions, respectively, such as KMnO4, HNO3 and H2O2. Then followed by thermal oxidation treatment at 350 °C, various nanostructured WO3 were successfully prepared. Based on the characterization results, it was found out that the chemical oxidants had different impact on the morphology and structure of the as-prepared WO3. Gas sensing properties of the WO3 sensors were evaluated in the presence of various volatile organic compounds. It was discovered that the WO3-P sensor with KMnO4 as oxidizing agent shows great improvement of TEA sensing performance compared to the pristine WO3 sensor, including higher sensing response, shorter recovery time and enhanced selectivity. The sensitization mechanism of WO3-P could be attributed to its nano-scale grain size, open structure constructed by nanosheets and more favorable crystal structure. [ABSTRACT FROM AUTHOR]

In forest monitoring networks, the computational capabilities of sensors cannot meet the latency requirements for complex tasks, and the limited battery capacity of these sensors hinders the long-term execution of monitoring tasks. Mobile edge computing (MEC) acts as an effective solution for this issue by offloading tasks to edge servers, significantly reducing both task latency and energy consumption. However, the computational capacity of MEC servers and the bandwidth in the system are limited, and the communication environment in forested areas is complex. To simulate the complexity of the forest communication environment, we incorporate empirical path loss and multipath fading into the calculation of signal transmission rates. The computational offloading problem is then converted into a minimum-cost optimization problem with multiple constraints related to energy consumption and latency, which we formulate as an NP-hard problem. We propose a dung beetle optimization (DBO) strategy for computational offloading, enhancing it with an improved circle chaotic mapping, a dimension decomposition strategy, and Cauchy disturbance. This algorithm has the beauty of symmetry in the search range, and the symmetrical features can comprehensively search for existing solutions. Experimental results demonstrate that the improved dung beetle optimization algorithm (IDBO) achieves better convergence, lower complexity, and superior optimization outcomes compared to local offloading strategies and other metaheuristic algorithms, confirming the effectiveness of the proposed algorithm and ensuring the service quality of the forest monitoring network. [ABSTRACT FROM AUTHOR]

This study analysed how income disparity affects citizens' public service satisfaction. Using the data of the Chinese General Social Survey from 2013 to 2015, we found that income disparity can reduce citizens' satisfaction with public service. Through a series of robustness tests, the findings of this paper remain robust. Mechanism analysis indicates that material aspirations are the main pathway through which income disparity affects citizens' satisfaction with public services. We also found that the effect of income disparity on citizens' satisfaction with public services is more pronounced in the samples of non-residents, urban residents and higher-income groups. [ABSTRACT FROM AUTHOR]

[Objective] In order to study the local load transfer mechanism and mechanical properties of tunnel lining reinforced with corrugated steel plate lining. [Method] The tunnel lining unit was regarded as a beam unit, and a bending performance test of concrete beam reinforced with corrugated steel plate was carried out. Establish a corresponding three-dimensional refined finite element model, verify the model through test results, and analyze the load transfer mechanism. [Result] Research results show that compared with unreinforced beams, the ultimate load of beams reinforced with corrugated steel plates is increased by 30% to 41%, and the ultimate load increases with the increase in the number of anchor bolts. The relative slip between the corrugated steel plate and the concrete structure decreases as the number of anchor bolts increases. At the initial stage of loading, the corrugated steel plate is in the neutral layer position, and the strain is basically zero; after reaching the cracking load, the entire corrugated steel plate peak is in a compressive state, while the corrugated steel plate trough is always in a tensile state.[Conclusion] Finally, through the finite element software analysis, the failure mode of the specimen and the load-strain of the corrugated steel plate are verified. The simulation results are in good agreement with the experimental results. [ABSTRACT FROM AUTHOR]

High-resolution remote sensing imagery comprises spatial structure features of multispectral bands varying in scale, color, and shape. These heterogeneous geographical features introduce grave challenges to the fine segmentation required for classification applications in remote sensing imagery, where direct application of traditional image classification models fails to deliver optimal results. To overcome these challenges, a multispectral, multi-label model, MMDL-Net, has been developed. This model is integrated with the multi-label BigEarthNet dataset, primarily employed for land cover classification research in remote sensing imagery, with each image composed of 13 spectral bands and spatial resolutions of 10 m, 20 m, and 60 m. To effectively utilize the information across these bands, a multispectral stacking module has been introduced to concatenate this spectral information. To proficiently process three distinct large-scale remote sensing image datasets, a multi-label classification module has been incorporated for training and inference. To better learn and represent the intricate features within the images, a twin-number residual structure has been proposed. The results demonstrate that the MMDL-Net model achieves a top accuracy of 83.52% and an F1 score of 77.97%, surpassing other deep learning models and conventional methods, thereby exhibiting exceptional performance in the task of multispectral multi-label classification of remote sensing imagery. [ABSTRACT FROM AUTHOR]