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Abstract Harmonics and electromagnetic interference (EMI) pose serious threats to the safety and efficiency of grid‐tied inverters. Although the inductor‐capacitor‐inductor (LCL) filter offers commendable harmonic suppression, it does not sufficiently mitigate leakage current and EMI caused by high‐frequency pulse‐width modulation (PWM). This paper examines the use of a symmetrical LCL filter to reduce the AC side leakage current in grid‐tied inverters. The symmetrical structure bolsters the conducted EMI suppression capability of the LCL filter. A magnetic integration scheme for symmetric LCL filters is introduced, and through thoughtful structural design, it achieves filter inductance integration on the EIE magnetic core. An experimental platform, equipped with a high‐frequency SiC‐MOSFET voltage source inverter with a 600 W output, is utilized. The LCL filter, symmetric LCL filter, and magnetic integrated symmetric LCL filter are contrasted, proving the effectiveness and feasibility of the proposed scheme. Furthermore, the experimental results demonstrate that the proposed magnetic integration scheme significantly reduces the filter's volume and weight, thereby enhancing the power density of the grid‐tied inverter system.

Abstract Purpose To investigate the value of CT urography (CTU) indicators in the quantitative differential diagnosis of bladder urothelial carcinoma (BUC) and inverted papilloma of the bladder (IPB). Material and methods The clinical and preoperative CTU imaging data of continuous 103 patients with histologically confirmed BUC or IPB were retrospectively analyzed. The imaging data included 6 qualitative indicators and 7 quantitative measures. The recorded clinical information and imaging features were subjected to univariate and multivariate logistic regression analysis to find independent risk factors for BUC, and a combined multi-indicator prediction model was constructed, and the prediction model was visualized using nomogram. ROC curve analysis was used to calculate and compare the predictive efficacy of independent risk factors and nomogram. Results Junction smoothness, maximum longitudinal diameter, tumor-wall interface and arterial reinforcement rate were independent risk factors for distinguishing BUC from IPB. The AUC of the combined model was 0.934 (sensitivity = 0.808, specificity = 0.920, accuracy = 0.835), and its diagnostic efficiency was higher than that of junction smoothness (AUC=0.667, sensitivity = 0.654, specificity = 0.680, accuracy = 0.660), maximum longitudinal diameter (AUC=0.757, sensitivity = 0.833, specificity = 0.604, accuracy = 0.786), tumor-wall interface (AUC=0.888, sensitivity = 0.755, specificity = 0.808, accuracy = 0.816) and Arterial reinforcement rate (AUC=0.786, sensitivity = 0.936, specificity = 0.640, accuracy = 0.864). Conclusion Above qualitative and quantitative indicators based on CTU and the combination of them may be helpful to the differential diagnosis of BUC and IPB, thus better assisting in clinical decision-making. Key points 1. Bladder urothelial carcinoma (BUC) and inverted papilloma of the bladder (IPB) exhibit similar clinical symptoms and imaging presentations. 2. The diagnostic value of CT urography (CTU) in distinguishing between BUC and IPB has not been documented. 3. BUC and IPB differ in lesion size, growth pattern and blood supply. 4. The diagnostic efficiency is optimized by integrating multiple independent risk factors into the prediction model.

Language transfer or crosslinguistic influence (CLI), referring to the influence of an L1 on the learning of an L2, is a significant aspect of Second Language Acquisition (SLA). Much work in this area is data-driven, and consequently, large L2 corpora have been constructed for use in CLI analyses. The field of Natural Language Processing, and in particular the specific task of Grammatical Error Correction (GEC), also has corpora that can be of use in these kinds of analyses. In this paper, we take the FCE corpus, a popular dataset of English as a Second Language (ESL) learner texts used for Grammatical Error Correction model training, and use it to analyse the relationship between the distributions of errors and the first languages of the ESL learners. We carry out a detailed analysis of three error types, and demonstrate that the errors made by ESL learners have a statistically significant relationship with linguistic characteristics of their first languages, suggesting the existence of both positive and negative transfer. The analysis aligns with results from the SLA literature, and validates the use of GEC corpora for use in CLI analysis.

Abstract Background Circular RNAs are highly stable regulatory RNAs that have been increasingly associated with tumorigenesis and progression. However, the role of many circRNAs in triple-negative breast cancer (TNBC) and the related mechanisms have not been elucidated. Methods In this study, we screened circRNAs with significant expression differences in the RNA sequencing datasets of TNBC and normal breast tissues and then detected the expression level of circRPPH1 by qRT‒PCR. The biological role of circRPPH1 in TNBC was then verified by in vivo and in vitro experiments. Mechanistically, we verified the regulatory effects between circRPPH1 and ZNF460 and between circRPPH1 and miR-326 by chromatin immunoprecipitation (ChIP), fluorescence in situ hybridization assay, dual luciferase reporter gene assay and RNA pull-down assay. In addition, to determine the expression of associated proteins, we performed immunohistochemistry, immunofluorescence, and western blotting. Results The upregulation of circRPPH1 in TNBC was positively linked with a poor prognosis. Additionally, both in vivo and in vitro, circRPPH1 promoted the biologically malignant behavior of TNBC cells. Additionally, circRPPH1 may function as a molecular sponge for miR-326 to control integrin subunit alpha 5 (ITGA5) expression and activate the focal adhesion kinase (FAK)/PI3K/AKT pathway. Conclusion Our research showed that ZNF460 could promote circRPPH1 expression and that the circRPPH1/miR-326/ITGA5 axis could activate the FAK/PI3K/AKT pathway to promote the progression of TNBC. Therefore, circRPPH1 can be used as a therapeutic or diagnostic target for TNBC.

Rare-earth-metal-based materials have emerged as frontrunners in the quest for high-performance hydrogen storage solutions, offering a paradigm shift in clean energy technologies. This comprehensive review delves into the cutting-edge advancements, challenges, and future prospects of these materials, providing a roadmap for their development and implementation. By elucidating the fundamental principles, synthesis methods, characterization techniques, and performance enhancement strategies, we unveil the immense potential of rare-earth metals in revolutionizing hydrogen storage. The unique electronic structure and hydrogen affinity of these elements enable diverse storage mechanisms, including chemisorption, physisorption, and hydride formation. Through rational design, nanostructuring, surface modification, and catalytic doping, the hydrogen storage capacity, kinetics, and thermodynamics of rare-earth-metal-based materials can be significantly enhanced. However, challenges such as cost, scalability, and long-term stability need to be addressed for their widespread adoption. This review not only presents a critical analysis of the state-of-the-art but also highlights the opportunities for multidisciplinary research and innovation. By harnessing the synergies between materials science, nanotechnology, and computational modeling, rare-earth-metal-based hydrogen storage materials are poised to accelerate the transition towards a sustainable hydrogen economy, ushering in a new era of clean energy solutions.

The control of soft surrounding rock stability has always been a hot academic issue. Soft rock has poor stability and low strength, and the deformation of a soft rock tunnel becomes more serious after it is affected by water for a long time. In this paper, the Jintong Coal Mine is taken as the research object, and nondestructive immersion experiments are used to study the change in mechanical properties of rock after being affected by water. The FLAC numerical model is used to analyze the stress evolution characteristics of the surrounding rock after being affected by water, and the results of the study show that the water absorption of siltstone is always higher than that of coarse-grained sandstone, and the uniaxial compressive strength of siltstone and coarse-grained sandstone decreases by 54.59% and 67.99%, respectively, under a state of saturated water compared with that under a state of dryness. Influenced by a T-shaped surface, the maximum principal stress concentration area occurs in the rock layer below the T-shaped surface and outside the joint. Concentrations of maximum shear stress occur within the “T” channel. Vertical stress concentration zones occur at the higher ground level and the bottom of the slope. The maximum shear stress of the roof fluctuates before the face reaches the surface of the “1” section, and continues to increase with and continues to increase with the distance of the face. After entering below the surface of the “1” section, the maximum shear stress of the roof increases rapidly, and the influence range is about 24 m. The maximum shear stress distribution plays a dominant role in the stability of the surrounding rocks of the two roadways. We analyze the principle of high-strength economic support, propose a “four-in-one” surrounding rock control technology based on “controlled hydrophobicity, structural adjustment, district management, and gradient control”, and propose a surrounding rock control scheme of district management. The measured data on site show that the roadway surrounding the rock is reasonably controlled. This provides a reference for the stable control of the surrounding rock of the roadway under similar conditions.

Hydrogen storage materials play a pivotal role in the development of a sustainable hydrogen economy. However, the discovery and optimization of high-performance storage materials remain a significant challenge due to the complex interplay of structural, thermodynamic and kinetic factors. Computational materials science has emerged as a powerful tool to accelerate the design and development of novel hydrogen storage materials by providing atomic-level insights into the storage mechanisms and guiding experimental efforts. In this comprehensive review, we discuss the recent advances in crystal structure prediction and performance assessment of hydrogen storage materials from a computational perspective. We highlight the applications of state-of-the-art computational methods, including density functional theory (DFT), molecular dynamics (MD) simulations, and machine learning (ML) techniques, in screening, evaluating, and optimizing storage materials. Special emphasis is placed on the prediction of stable crystal structures, assessment of thermodynamic and kinetic properties, and high-throughput screening of material space. Furthermore, we discuss the importance of multiscale modeling approaches that bridge different length and time scales, providing a holistic understanding of the storage processes. The synergistic integration of computational and experimental studies is also highlighted, with a focus on experimental validation and collaborative material discovery. Finally, we present an outlook on the future directions of computationally driven materials design for hydrogen storage applications, discussing the challenges, opportunities, and strategies for accelerating the development of high-performance storage materials. This review aims to provide a comprehensive and up-to-date account of the field, stimulating further research efforts to leverage computational methods to unlock the full potential of hydrogen storage materials.

Hydrogen energy, known for its high energy density, environmental friendliness, and renewability, stands out as a promising alternative to fossil fuels. However, its broader application is limited by the challenge of efficient and safe storage. In this context, solid-state hydrogen storage using nanomaterials has emerged as a viable solution to the drawbacks of traditional storage methods. This comprehensive review delves into the recent advancements in nanomaterials for solid-state hydrogen storage, elucidating the fundamental principles and mechanisms, highlighting significant material systems, and exploring the strategies of surface and interface engineering alongside catalytic enhancement. We also address the primary challenges and provide future perspectives on the development of nanomaterial-based hydrogen storage technologies. Key discussions include the role of nanomaterial size effects, surface modifications, nanocomposites, and nanocatalysts in optimizing storage performance.