Search Results (14)

Infrared remote sensing images are often degraded by blur and stripe noise caused by satellite attitude variations, optical distortions, and electronic interference, which significantly compromise image quality and target detection performance. Existing joint deblurring and destriping methods tend to over-smooth image edges and textures, failing to effectively preserve high-frequency details and sometimes misclassifying ringing artifacts as stripes. This paper proposes a variational framework for simultaneous deblurring and destriping of infrared remote sensing images. By leveraging an adaptive structure tensor model, the method exploits the sparsity and directionality of stripe noise, thereby enhancing edge and detail preservation. During blur kernel estimation, a fidelity term orthogonal to the stripe direction is introduced to suppress noise and residual stripes. In the image restoration stage, a WCOB (Non-blind restoration based on Wiener-Cosine composite filtering) model is proposed to effectively mitigate ringing artifacts and visual distortions. The overall optimization problem is efficiently solved using the alternating direction method of multipliers (ADMM). Extensive experiments on real infrared remote sensing datasets demonstrate that the proposed method achieves superior denoising and restoration performance, exhibiting strong robustness and practical applicability. Full article

Flywheel energy storage systems play an important role in frequency regulation and power quality control within modern power grids, yet the fault signals generated by defects in their rolling bearings are typically indistinct, making direct diagnosis difficult. Raw noisy signals often yield unsatisfactory diagnostic performance when directly processed by neural networks. Although MOMEDA (Multipoint Optimal Minimum Entropy Deconvolution Adjusted) can effectively extract impulsive fault components, its performance is highly dependent on the selected fault period and filter length. To address these issues, this paper proposes an improved fault diagnosis method that integrates MOMEDA-based periodic extraction with a neural network classifier. The Artificial Fish Swarm Algorithm (AFSA) is employed to adaptively determine the key parameters of MOMEDA using multi-point kurtosis as the optimization objective, and the optimized parameters are used to enhance impulsive fault features. The filtered signals are then converted into image representations and fed into a ResNet-18 network (a compact 18-layer deep convolutional neural network from the residual network family) to achieve intelligent identification and classification of bearing faults. Experimental results demonstrate that the proposed method can effectively extract and diagnose bearing fault signals. Full article

The Debye model and its modified forms are widely applied to interpret relaxation polarization processes in dielectric media. However, these models generally require prior assumptions regarding the number of polarization branches, which makes it difficult to construct an equivalent circuit model that accurately reflects the real relaxation characteristics. In this work, frequency-domain dielectric spectra of oil–paper insulation samples with different moisture contents were measured and analyzed. A distributed Debye model considering the probabilistic distribution of relaxation branches was established, and the corresponding relaxation time distribution was obtained using discretization and regularization techniques. Based on this, an accurate moisture condition assessment method for oil–paper-insulated bushings is proposed. The results indicate that, with increasing moisture content, both the real and imaginary parts of the complex capacitance increase significantly in the low-frequency region, while remaining nearly constant at high frequencies. Meanwhile, the peak of the imaginary part shifts toward higher frequencies. By applying the proposed discretization and regularization method to the measured dielectric spectra, the relaxation time distribution function can be accurately derived. As the moisture content increases, the relaxation time constant corresponding to the third relaxation peak gradually decreases. The constructed assessment model exhibits high accuracy, with a maximum error below 2.66%. Full article

Bamboo fiber is a prime green fiber due to its renewability, biodegradability, and high specific strength. Bamboo-fiber-reinforced epoxy (BFRE) composites have seen extensive use and shown great promise for natural biofiber-reinforced friction materials. Inspired by the decussated fiber alignment of bovine enamel, this study investigated how fiber orientation influences the tribological properties of BFRE composites. Specifically, the proportion of fibers oriented vertically to the surface was varied at seven levels: 0%, 25%, 33%, 50%, 67%, 75%, and 100%. The tribological performance was assessed through wear reciprocating testing and microscopic morphological characterization techniques. Results indicate that the bio-inspired fiber decussation can reduce the wear loss of the BFRE composites. Among all bio-inspired BFRE composites, BFRE composites with 67% vertical fibers achieve the best wear resistance. The vertical fibers in the BFRE composites can withstand pressure to provide a “compression–rebound” effect, while the parallel fibers can resist shear stress. The decussated structure inhibits crack initiation and propagation during wear and promotes transfer film formation, reducing wear loss. The findings expand understanding of the correlation between the bovine-tooth-like decussated structure and its tribological mechanisms, thereby offering essential guidance for the biomimetic design of high-performance BFRE composites for friction material application. Full article

High-power lithium-ion batteries impose stringent requirements on output power. Tetramethylene sulfone (TMS), serving as a novel electrolyte additive, effectively enhances the stability of electrolytes under high-voltage conditions due to its high flash point and high dielectric constant, thereby boosting the output performance of lithium-ion batteries. In this work, we selected lithium hexafluorophosphate (LiPF₆) as the lithium salt, using a solvent carrier consisting of a mixture of ethylene carbonate (EC), dimethyl carbonate (DMC), and ethyl methyl carbonate (EMC). TMS was added as an additive to create a novel high-power electrolyte system. We prepared five electrolytes with different TMS concentrations and conducted in-depth investigations into their impacts on the performance of lithium-ion batteries. The findings indicate that the electrolytes with TMS ratios of 2 wt% and 5 wt% demonstrated good synergistic cathode–anode stability in the NCM//soft carbon system, and the electrolyte with a 5 wt% TMS ratio demonstrated the most significant improvement in the overall performance of the full battery. Full article

In this study, a methodology using probabilistic distribution techniques to determine the parameters of the soil’s effective internal friction angle ($\phi ’$) was proposed. The method was grounded in quantitative survey information extracted from geotechnical reports. Extensive equivalent samples were estimated using Markov chain Monte Carlo (MCMC) simulations and probability density functions ($PDFs$). The effective internal friction angle ($\phi ’$) of silty clay layers was probabilistically characterized using the plasticity index ($P_I$), in situ static cone penetration test ($q_c$), and standard penetration test ($N_{SPT}$). A systematic quantitative analysis integrated prior information from different sources was systematically integrated with sampling data. By establishing a Bayesian framework that incorporated the regression relationship and uncertainties associated with the effective internal friction angle ($\phi ’$), the model ensured balance and symmetry in the treatment of prior information and observed data. The model was then transformed into equivalent sample values based on three models, reflecting the symmetrical consideration of different data sources. Further considerations involved correcting the three different analysis methods. A comparison of equivalent sample values with the mean values of the sampling data, along with the parameter optimization updates, was performed by combining the three models. Using three sets of sampling data, a linear relationship model for the new soil parameters was derived. The analysis results demonstrated that the proposed method could obtain equivalent samples for the effective internal friction angle. Full article

The actions of the retinoic acid nuclear receptor gamma (RARγ) agonist, palovarotene, on pre-existing osteochondromas were investigated using a mouse multiple osteochondroma model. This approach was based on the knowledge that patients often present to the clinic after realizing the existence of osteochondroma masses, and the findings from preclinical investigations are the effects of drugs on the initial formation of osteochondromas. Systemic administration of palovarotene, with increased doses (from 1.76 to 4.0 mg/kg) over time, fully inhibited tumor growth, keeping the tumor size (0.31 ± 0.049 mm³) similar to the initial size (0.27 ± 0.031 mm³, p = 0.66) while the control group tumor grew (1.03 ± 0.23 mm³, p = 0.023 to the drug-treated group). Nanoparticle (NP)-based local delivery of the RARγ agonist also inhibited the growth of osteochondromas at an early stage (Control: 0.52 ± 0.11 mm³; NP: 0.26 ± 0.10, p = 0.008). Transcriptome analysis revealed that the osteoarthritis pathway was activated in cultured chondrocytes treated with palovarotene (Z-score = 2.29), with the upregulation of matrix catabolic genes and the downregulation of matrix anabolic genes, consistent with the histology of palovarotene-treated osteochondromas. A reporter assay performed in cultured chondrocytes demonstrated that the Stat3 pathway, but not the Stat1/2 pathway, was stimulated by RARγ agonists. The activation of Stat3 by palovarotene was confirmed using immunoblotting and immunohistochemistry. These findings suggest that palovarotene treatment is effective against pre-existing osteochondromas and that the Stat3 pathway is involved in the antitumor actions of palovarotene. Full article

Driven by the wave of artificial intelligence, the educational practice and application of robots have become increasingly common. Despite extensive coverage in the literature on various aspects of educational robots, there are still unexplored avenues, particularly regarding robotic support, robotic personality, and challenges in their applications. This study presented a systematic review of high-quality empirical research on the use of physical robots in educational settings. A total of 92 relevant papers from the Web of Science database were analyzed. Employing the technological pedagogical content knowledge (TPCK) framework, we investigated research questions across seven components, including the learning domain, teaching strategy, robot types, learning results, problems with using robots, robotic support, and robotic personality. The findings revealed that robots are most prevalently employed in language learning applications. When opting for teaching strategies, educators tend to favor those that incorporate physical interaction. Concurrently, humanoid robots emerge as the preferred choice among many. These robots, in human–robot interaction scenarios, often exhibit an agreeable personality. In terms of evaluating learning results, cognitive aspects like thinking, creativity, self-regulation, and inquiry ability are especially emphasized. Such results are frequently influenced by the informational and emotional support provided by robots. Nonetheless, challenges encountered by teachers, learners, and robots in this process are not to be overlooked. The findings of this study contributed to future applications of robotics in education. Full article

Shijing 詩經 is the earliest collection of Chinese poems and songs traditionally considered to be compiled by Confucius. Scholarship on this collection deems the widespread wind imagery contained in it to be either a metaphor for males or a medium of emotional expression. However, the religious ideas involved in the sacrifices to the wind gods in early China, which are, in fact, deeply linked with the “wind” in Shijing, warrant further consideration. This article focuses on the relation between the “wind” in Shijing and the religious ideas involved in sacrificial rites (“ningfeng 寧風” and “difeng 禘風”) to the wind gods. Drawing upon the history of wind disasters and sacrifices to the wind gods in early China, this article suggests that the pieces entitled “Gufeng 谷風” (included in the Xiaoya 小雅 section) and “Herensi 何人斯” provide descriptions of “ningfeng” (appeasing unwanted wind). Moreover, it argues that the pieces entitled “Kaifeng 凱風” and “Tuoxi 蘀兮” depict a genial wind in connection with harvest, childbearing, and prosperity involved in “difeng”. Full article

Sasa argenteostriata (Regel) E.G. Camus is a gramineous plant with the potential for phytoremediation. In this study, we aimed to determine its tolerance to zinc stress and combined lead–zinc stress and the effect of zinc on its absorption and accumulation characteristics of lead. The results showed that S. argenteostriata had good tolerance to zinc stress, and S. argenteostriata was not significantly damaged when the zinc stress concentration was 600 mg/L. Under both zinc stress and combined lead–zinc stress, the root was the main organ that accumulated heavy metals in S. argenteostriata. The presence of zinc promoted the absorption of lead by the root of S. argenteostriata, and the lead content in the root under PZ1, PZ2, PZ3 and PZ4 treatments was 2.15, 4.31, 4.47 and 6.01 times that of PZ0 on the 20 days. In the combined lead–zinc stress treatments, the toxicity of heavy metals to S. argenteostriata was mainly caused by lead. Under high concentrations of combined lead–zinc stress (PZ4), the proportion of zinc in the leaf of S. argenteostriata on the 20 days increased, which was used as a tolerance strategy to alleviate the toxicity of lead. Full article

We present a new machine learning (ML) deep learning (DL) synthesis algorithm for the design of a microstrip meander line (MML) slow wave structure (SWS). Exact numerical simulation data are used in the training of our network as a form of supervised learning. The learning results show that the training mean squared error is as low as 5.23 × 10⁻² when using 900 sets of data. When the desired performance is reached, workable geometry parameters can be obtained by this algorithm. A D-band MML SWS with 20 GHz bandwidth at 160 GHz center frequency is then designed using the auto-design neural network (ADNN). A cold test shows that its phase velocity varies by 0.005 c, and the transmission rate of a 50-period SWS is greater than −5 dB with the reflectivity below −15 dB when the frequency is from 150 to 170 GHz. Particle-in-cell (PIC) simulation also illustrates that a maximum power of 3.2 W is reached at 160 GHz with 34.66 dB gain and output power greater than 1 W from 152 to 168 GHz. Full article

Cold storage and heat exposure are crucial components of tephritid fruit fly mass-rearing programs, as they influence the development and fitness traits of produced flies. This work investigated the effects of cold storage on the pupal developmental parameters and quality of Bactrocera dorsalis (Hendel) genetic sexing strain (GSS) adults. Furthermore, the impact of short-term thermal exposure on the fecundity of B. dorsalis (GSS) that also underwent pupal cold storage was examined. Our results show that pupal development time, emergence rate, partial emergence rate, flight ability and fecundity were significantly affected by low temperature and pupal age and their interaction. Pupal cold storage did not pose negative impacts on the mating competition and response to methyl eugenol (ME) in the males. In addition, compared with the adults that were subjected to the same pupal storage protocol (five-day-old pupae stored at 13 °C), adult exposure to 41 °C for 1 h showed significant reparative effects on fecundity. In summary, the cold storage procedure of B. dorsalis (GSS) pupae has the potential to improve the flexibility and efficiency of mass-rearing schedules. Furthermore, short-term thermal exposure showed reparative effects on the fecundity costs induced by pupal cold storage in B. dorsalis (GSS). Full article

In the natural host, most of the synonymous codons of a gene have been evolutionarily selected and related to protein expression and function. However, for the design of a new gene, most of the existing codon optimization tools select the high-frequency-usage codons and neglect the contribution of the low-frequency-usage codons (rare codons) to the expression of the target gene in the host. In this study, we developed the method Presyncodon, available in a web version, to predict the gene code from a protein sequence, using built-in evolutionary information on a specific expression host. The synonymous codon-usage pattern of a peptide was studied from three genomic datasets (Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae). Machine-learning models were constructed to predict a selection of synonymous codons (low- or high-frequency-usage codon) in a gene. This method could be easily and efficiently used to design new genes from protein sequences for optimal expression in three expression hosts (E. coli, B. subtilis, and S. cerevisiae). Presyncodon is free to academic and noncommercial users; accessible at http://www.mobioinfor.cn/presyncodon_www/index.html. Full article

Total antioxidant capacity of different varieties of strawberry (Ningfeng, Ningyu, Zijin 4, Toyonoka, Benihope, Sweet Charlie) in different developmental stages (including green unripe stages, half red stages, and red ripe stages) was investigated by oxygen radical absorbance capacity (ORAC) assay. In addition, effects of the antioxidant properties of strawberry stored at 4 °C or −18 °C for a period of five months were studied. The results showed that antioxidant capacity of strawberry changed based on tested part, developmental stage, variety, and time of collection. Calyces had significantly higher ORAC values compared with fruits. Strawberry fruits had higher ORAC values during the green unripe stages than the half red stages and red ripe stages. Strawberries got higher ORAC values during short-time storage, and then decreased during long-time storage. Samples stored at −18 °C exhibited higher antioxidant capacity than those stored at 4 °C, while vacuum treatment could further increase ORAC values. The results indicated the potential market role of strawberries as a functional food and could provide great value in preventing oxidation reaction in food processing and storage for the dietary industry. Full article