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Abstract In the design and optimisation of marine wireless communication and navigation systems, a thorough investigation of radio wave propagation characteristics under atmospheric ducting conditions is essential. The authors aim to enhance the efficiency of radio wave propagation loss prediction in marine atmospheric ducting environments, proposing a prediction model based on Fast Reordered‐Alternate Direction Decomposition (FR‐ADD). By approximating the diffraction term into three independent components, exploiting the commutative properties of the Fourier transform to reduce the spatial dimensions, and incorporating a rapid algorithm for the parabolic equation, the model optimises the stepping process and significantly improves computational efficiency. Simulation experiments demonstrate that, in the long‐distance and complex marine ducting environments, the model not only maintains prediction accuracy but also substantially reduces computational load and prediction time, effectively realising over‐the‐horizon propagation prediction. In the experiment of radio wave propagation characteristics in the Yellow and Bohai Seas, the simulation data from the FR‐ADD model showed significant correlation with actual measurements and simulations from the AREPS software, confirming the method's efficiency and practicality.

This paper adds an organizational dimension to the body of literature on international student mobility. Existing studies examine push/pull factors and student motivations, neglecting that students' motivations and demands are not necessarily spontaneous, but can be shaped by external forces. Drawing on interview, archival and observation data collected on four leading cram schools that prepare students for the TOEFL/GRE, IELTS and SAT in China, I argue that cram schools not only coach students on test preparation and "how to study abroad," but they also adopt organizational framing to instill in students "why to study abroad." Leading cram schools have played an integral role in promoting a certain organizational framing as the dominant approach of a niche market in a given era. During the 1990s, when the TOEFL/GRE niche market was rapidly expanding, the market leader in this niche promoted self-help and nationalism as dominant discourses. Self-help discourse frames overseas study and test preparation not as means, but as the ends of students' lives: going beyond one's limit and making one's life complete. Nationalist discourse depicts overseas study as a detour to build a stronger China after learning from the West. After 2000, however, new organizational framing picked up momentum in the new niche markets of IELTS and SAT. Targeting urban middle-class consumers, market leaders in these new niches increasingly framed studying abroad as a springboard for immigration, a channel for becoming global elites and an opportunity for status improvement for the entire family. My article bridges literature on transnational higher education with studies on supplementary education.

The performance of metal sites in terms of their formation, evolution, and deactivation is strongly influenced by the properties of the supports during catalysis. Nanomaterials offer a tailorable size, shape, and composition, along with a large surface area, a high fraction of surface atoms, and unique electronic properties, thereby significantly improving the efficiency, selectivity, stability, and versatility of catalytic processes. In the direct dehydrogenation of propane (PDH) reactions, the activity, selectivity, and durability of catalysts face challenges due to the high reaction temperature and harsh atmosphere that accompanies the presence of reducible reactants. Herein, bimetallic platinum–zinc (PtZn) sites were synthesized on various silica nanomaterials to investigate the correlation between the nanoscale properties of silica and PDH performance. Among the supports being explored, including amorphous SiO2 particles, mesoporous SBA-15, microporous silicate-1, and mesoporous MCM-41, MCM-41 stood out due to its distinctive advantages, including a large specific surface area, well-portioned pore size and distribution, and an appropriate amount and strength of acidic sites. Operating at a temperature of 600 °C, the catalyst exhibited a notable propene production rate of approximately 37.3 mmol·gcat–1·h–1. This performance was coupled with an outstanding initial conversion (39.2%) and selectivity (97.7%) during the PDH reaction. The characterization results highlighted the exceptional dispersion of the PtZn sites on the MCM-41 support, showing remarkable resistance to coking and sintering throughout the reaction. These attributes exceeded those observed in other silica supports. [ABSTRACT FROM AUTHOR]

BACKGROUND: Atherosclerotic renal artery stenosis (ARAS) is a common disease in the elderly population. OBJECTIVE: The aim was to develop a contrast-enhanced ultrasound (CEUS)-based model for predicting post-angioplasty improvement in hypertension in patients with severe ARAS. METHODS: Thirty-five patients with severe ARAS (⩾ 70%) were included in this study, and 42 renal arteries received percutaneous transluminal renal arterial stenting. An optimal integral formula was developed from pre-interventional color-coded duplex sonography (CCDS) and CEUS parameters using least absolute shrinkage and selection operator (LASSO) regression and receiver operating characteristic (ROC) curve analysis. A model for predicting short-term hypertension improvement was established using the integral formula and clinical risk factors. Bootstrapping was used for internal validation. RESULTS: Two integral formulas, LASSO.CCDS and LASSO.CEUS, were established. ROC curves of the two integral formulas showed that LASSO.CEUS was the better formula for predicting hypertension improvement (AUC 0.816, specificity 78.6%). Univariate and multivariate regression analyses showed that duration of hypertension (OR 0.841, P = 0.027), diabetes (OR = 0.019, P = 0.010), and LASSO.CEUS (OR 7.641, P = 0.052) were predictors of short-term hypertension improvement after interventional therapy. Using LASSO.CEUS combined with clinical risk factors, the following prediction model was established: logit (short-term improvement in hypertension) = 1.879–0.173 × hypertension duration – 3.961 × diabetes + 2.034 × LASSO.CEUS (AUC 0.939). CONCLUSIONS: The model established using CEUS parameters and clinical risk factors could predict hypertension improvement after interventional therapy, but further research and verification are needed. [ABSTRACT FROM AUTHOR]

This paper reviewed the clinical data of 15 children undergoing allogeneic hematopoietic stem cell transplantation (HSCT) for Fanconi anemia. All the children received comprehensive nursing measures including overall environmental protection, infection prevention, safety protection, psychological counseling and health education based on their disease characteristics and disease progression. Allogeneic hematopoietic stem cell transplantation was successfully performed in 15 children with Fankone anemia. After transplantation, the mean time of neutrophil engraftment was (11. 67±1. 67) d, time of transferred out of laminar flow room was (13. 33±1. 49) d. (本文回顾了科室科收治的行异基因造血干细胞移植术治疗的范可尼贫血患儿15例的临床资料。结合患儿的疾病特点与病情进展, 为患儿实施全环境保护、预防感染、安全防护、心理疏导和健康教育。15例范可尼贫血患儿成功进行异基因造血干细胞移植, 于移植后平均(11. 67±1. 67)d中性粒细胞开始重建, 平均(13. 33±1. 49)d转出层流室。)

The formed morphology during phase separation is crucial for determining the properties of the resulting product, e.g., a functional membrane. However, an accurate morphology prediction is challenging due to the inherent complexity of molecular interactions. In this study, the phase separation of a two-dimensional model polymer solution is investigated. The spinodal decomposition during the formation of polymer-rich domains is described by the Cahn–Hilliard equation incorporating the Flory–Huggins free energy description between the polymer and solvent. We circumvent the heavy burden of precise morphology prediction through two aspects. First, we systematically analyze the degree of impact of the parameters (initial polymer volume fraction, polymer mobility, degree of polymerization, surface tension parameter, and Flory–Huggins interaction parameter) in a phase-separating system on morphological evolution characterized by geometrical fingerprints to determine the most influential factor. The sensitivity analysis provides an estimate for the error tolerance of each parameter in determining the transition time, the spinodal decomposition length, and the domain growth rate. Secondly, we devise a set of physics-informed neural networks (PINN) comprising two coupled feedforward neural networks to represent the phase-field equations and inversely discover the value of the embedded parameter for a given morphological evolution. Among the five parameters considered, the polymer–solvent affinity is key in determining the phase transition time and the growth law of the polymer-rich domains. We demonstrate that the unknown parameter can be accurately determined by renormalizing the PINN-predicted parameter by the change of characteristic domain size in time. Our results suggest that certain degrees of error are tolerable and do not significantly affect the morphology properties during the domain growth. Moreover, reliable inverse prediction of the unknown parameter can be pursued by merely two separate snapshots during morphological evolution. The latter largely reduces the computational load in the standard data-driven predictive methods, and the approach may prove beneficial to the inverse design for specific needs. [ABSTRACT FROM AUTHOR]