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Quantum communication has made great breakthroughs in recent years. Because of its characteristics for strict information security transmission and high speed, it has received attention from related research fields around the world. This paper briefly reviews the progress in the field of quantum computing and communication. The basic functions of quantum mechanics related to the quantum communication are first introduced, including qubit, logic gates, postulates, polarization and quantum entanglement. Then the applications of quantum communication are discussed including teleportation, cryptography and quantum networks. Finally, advantages and disadvantages for the current applications are analyzed and the challenges remained in the current research are demonstrated.

Background As the global aging issue grows, dementia, particularly Alzheimer’s disease (AD), has become a major public health challenge for everyone. This study utilizes the Global Burden of Disease (GBD) database to analyze trends in the epidemiology of AD and other dementias from 1990 to 2021 and to predict future burdens to 2040. Methods We examined global, regional, and national data on AD and other dementias, focusing on incidence, prevalence, and Disability-Adjusted Life Years (DALYs). Joinpoint regression analysis was employed to identify significant changes in trends over time. The effects of age, period, and birth cohort on the risk of AD and other dementias were analyzed. Additionally, the impact of aging, population growth, and epidemiological changes on DALYs was assessed across different Socio-demographic Index (SDI) quintiles. Results The global burden of AD and other dementias has significantly increased, with the highest incidence, prevalence, and DALYs observed in East Asia. A notable increase in prevalence was observed in females over 65 years compared to males. Joinpoint regression analysis revealed substantial changes in trends in 1995, 2005, 2011, and 2019, with a noticeable acceleration post-2011, especially after 2019. Age was a significant risk factor, with a sharp increase in risk after 60 years of age. Epidemiological changes had a minor impact globally but varied by region and gender. Bayesian age-period-cohort modeling predicts sustained growth through 2040, with age-standardized incidence and prevalence rates projected to reach 144.85 and 821.80 per 100,000 respectively, driven predominantly by aging populations in high SDI regions and demographic expansion in low SDI regions. Conclusions The global burden of AD and other dementias is escalating, with a pronounced increase expected by 2040. This study highlights the need for targeted interventions, particularly in regions with higher burdens and among older populations. The findings underscore the importance of considering SDI, age, and gender when planning public health strategies to address the growing challenge of AD and other dementias.

Sustainable gardens have emerged as innovative models of urban tourism that integrate ecological aesthetics, participatory design, and community well-being. This study explores how tourists’ perceived value influences revisit intention and introduces two experiential moderators—narrative transportation and empowerment capability—to uncover the underlying psychological and participatory mechanisms that drive behavioral intention. A mixed-methods approach was employed, combining grounded theory interviews to develop the conceptual framework with a large-scale survey analyzed using structural equation modeling (SmartPLS). The results demonstrate that perceived value positively affects revisit intention through tourist satisfaction, while narrative transportation and empowerment capability significantly strengthen these relationships by enhancing emotional immersion and participatory engagement. These findings advance sustainable tourism theory by highlighting the dual-path moderating effects of storytelling and empowerment in shaping visitor behavior. Practically, the study provides actionable insights for sustainable garden management, emphasizing the importance of immersive narratives and participatory empowerment in fostering long-term tourist loyalty and sustainable destination development.

This paper offers a thorough analysis of Ctrip’s position in the tourism market, focusing on optimizing its marketing strategies to enhance its market presence. It begins by outlining the tourism industry’s background and the pivotal role of online travel agencies like Ctrip in simplifying travel experiences. The literature review highlights current marketing practices and consumer behavior, identifying key gaps that shape the study’s research questions and framework. The findings reveal that Ctrip faces significant challenges due to digital transformation, intense competition, and increasingly selective consumers. The paper discusses these challenges’ implications for both Ctrip and the broader market, offering strategic recommendations to address them. Key strategies include leveraging emerging technologies, enhancing competitive differentiation, and improving customer retention. The insights provided aim not only to secure Ctrip’s future success but also to offer guidance for other industry players navigating similar challenges. The key terms in this study include tourism market, marketing strategy, Ctrip, optimization, and analysis.

Physics informed neural network (PINN) demonstrates powerful capabilities in solving forward and inverse problems of nonlinear partial differential equations (NLPDEs) through combining data-driven and physical constraints. In this paper, two PINN methods that adopt tanh and sine as activation functions, respectively, are used to study data-driven solutions and parameter estimations of a family of high order KdV equations. Compared to the standard PINN with the tanh activation function, the PINN framework using the sine activation function can effectively learn the single soliton solution, double soliton solution, periodic traveling wave solution, and kink solution of the proposed equations with higher precision. The PINN framework using the sine activation function shows better performance in parameter estimation. In addition, the experiments show that the complexity of the equation influences the accuracy and efficiency of the PINN method. The outcomes of this study are poised to enhance the application of deep learning techniques in solving solutions and modeling of higher-order NLPDEs.

Large-scale pretrained language models (LLMs), such as ChatGPT and GPT4, have shown strong abilities in multilingual translation, without being explicitly trained on parallel corpora. It is intriguing how the LLMs obtain their ability to carry out translation instructions for different languages. In this paper, we present a detailed analysis by finetuning a multilingual pretrained language model, XGLM-7.5B, to perform multilingual translation following given instructions. Firstly, we show that multilingual LLMs have stronger translation abilities than previously demonstrated. For a certain language, the translation performance depends on its similarity to English and the amount of data used in the pretraining phase. Secondly, we find that LLMs’ ability to carry out translation instructions relies on the understanding of translation instructions and the alignment among different languages. With multilingual finetuning with translation instructions, LLMs could learn to perform the translation task well even for those language pairs unseen during the instruction tuning phase.

Van der Waals encapsulation of two-dimensional materials in hexagonal boron nitride (hBN) stacks is a promising way to create ultrahigh-performance electronic devices 1 – 4 . However, contemporary approaches for achieving van der Waals encapsulation, which involve artificial layer stacking using mechanical transfer techniques, are difficult to control, prone to contamination and unscalable. Here we report the transfer-free direct growth of high-quality graphene nanoribbons (GNRs) in hBN stacks. The as-grown embedded GNRs exhibit highly desirable features being ultralong (up to 0.25 mm), ultranarrow (<5 nm) and homochiral with zigzag edges. Our atomistic simulations show that the mechanism underlying the embedded growth involves ultralow GNR friction when sliding between AA′-stacked hBN layers. Using the grown structures, we demonstrate the transfer-free fabrication of embedded GNR field-effect devices that exhibit excellent performance at room temperature with mobilities of up to 4,600 cm 2  V –1  s –1 and on–off ratios of up to 10 6 . This paves the way for the bottom-up fabrication of high-performance electronic devices based on embedded layered materials. A strategy for the transfer-free direct growth of ultralong, high-quality graphene nanoribbons, which have desirable electronic properties, between layers of a boron nitride insulator is reported.

Classical nucleation theory predicts that two-dimensional islands on a surface must reach a critical size before they continue to grow; below that size, they dissolve. Chen et al. used phage display to select for short peptides that would bind to molybdenum disulfide (MoS 2 ) (see the Perspective by Kahr and Ward). Hexagonal arrays of these peptides grew epitaxially as dimers but without a size barrier—the critical nuclei size was zero. Although two-dimensional arrays formed, growth occurred one row at time. Classical nucleation theory indeed predicts the absence of a barrier for such one-dimensional growth. Science , this issue p. 1135 ; see also p. 1111 The barrier-free, row-by-row assembly of peptides on a MoS 2 surface confirms a prediction of classical nucleation theory. Assembly of two-dimensional (2D) molecular arrays on surfaces produces a wide range of architectural motifs exhibiting unique properties, but little attention has been given to the mechanism by which they nucleate. Using peptides selected for their binding affinity to molybdenum disulfide, we investigated nucleation of 2D arrays by molecularly resolved in situ atomic force microscopy and compared our results to molecular dynamics simulations. The arrays assembled one row at a time, and the nuclei were ordered from the earliest stages and formed without a free energy barrier or a critical size. The results verify long-standing but unproven predictions of classical nucleation theory in one dimension while revealing key interactions underlying 2D assembly.

Plant mitochondrial genomes (mitogenomes) are a valuable source of genetic information for a better understanding of phylogenetic relationships. However, no mitogenome of any species in the genus of Photinia has been reported. In this study, using NGS sequencing, we reported the mitogenome assembly and annotation of Photinia serratifolia , which is 473,579 bp in length, contains 38 protein-coding genes, 23 tRNAs, and 6 rRNAs, with 61 genes have no introns. The rps2 and rps11 genes are missing in the P. serratifolia mitogenome. Although there are more editing sites (488) in the P. serratifolia mitogenome than in most angiosperms, fewer editing types were found in the P. serratifolia mitogenome, showing a clear bias in RNA-editing. Phylogenetic analysis based on the mitogenomes of P. serratifolia and 8 other taxa of the Rosaceae family reflected the exact evolutionary and taxonomic status of P. serratifolia . However, Ka/Ks analysis revealed that 72.69% of the protein-coding genes in the P. serratifolia mitogenome had undergone negative selections, reflecting the importance of those genes in the P. serratifolia mitogenome. Collectively, these results will provide valuable information for the evolution of P. serratifolia and provide insight into the evolutionary relationships within Photinia and the Rosaceae family.

Vanadium dioxide (VO 2 ) exhibits an insulator-to-metal transition accompanied by a structural transition near room temperature. This transition can be triggered by an ultrafast laser pulse. Exotic transient states, such as a metallic state without structural transition, were also proposed. These unique characteristics let VO 2 have great potential in thermal switchable devices and photonic applications. Although great efforts have been made, the atomic pathway during the photoinduced phase transition is still not clear. Here, we synthesize freestanding quasi-single-crystal VO 2 films and examine their photoinduced structural phase transition with mega-electron-volt ultrafast electron diffraction. Leveraging the high signal-to-noise ratio and high temporal resolution, we observe that the disappearance of vanadium dimers and zigzag chains does not coincide with the transformation of crystal symmetry. After photoexcitation, the initial structure is strongly modified within 200 femtoseconds, resulting in a transient monoclinic structure without vanadium dimers and zigzag chains. Then, it continues to evolve to the final tetragonal structure in approximately 5 picoseconds. In addition, only one laser fluence threshold instead of two thresholds suggested in polycrystalline samples is observed in our quasi-single-crystal samples. Our findings provide essential information for a comprehensive understanding of the photoinduced ultrafast phase transition in VO 2 . The atomic pathway in the photoinduced ultrafast structural phase transition of VO 2 has been a controversial problem for a long time. Here the authors, using MeV ultrafast electron diffraction, show that the melting of V-V dimers and the transformation of crystal symmetry are two processes with different timescales.