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A new solution framework for the task of network dismantling is recently developed, based on a two-scale bipartite factor-graph representation of the original graph where local structures are abstracted as factor nodes. This technique leads to advancement of extant dismantling algorithms, among which the belief-propagation decimation (BPD) algorithm has an efficient counterpart (factor BPD, i.e., FBPD) on the factor graph, building upon a mean-field spin-glass theory developed for the underlying long-loop feedback vertex set (FVS) problem. In this paper, I (1) demonstrate the advantage as well as disadvantage of the new factor-graph approach, and investigate the varying choice of factors, (2) show that the method can be supported by an alternative microscopic picture, and the two distinct spin-glass theories derive equivalent outcomes, whose analytical results serve as lower bounds for the FVS size on random regular factor graphs, besides (3) an extra mathematical lower bound from the result on random regular (original) graphs. Performances of graph/factor-graph algorithms are compared on various real networks. It shows empirically and analytically that the factor-graph approach does not interfere with what we could achieve without applying this technique; the new approach does a good job where traditional algorithms may perform poorly.

A bstract We study reflected entropy as a mixed state correlation measure in black hole evaporation. As a measure for bipartite mixed states, reflected entropy can be computed between black hole and radiation, radiation and radiation, and even black hole and black hole. We compute reflected entropy curves in three different models: 3-side wormhole model, End-of-the-World (EOW) brane model in three dimensions and two-dimensional eternal black hole plus CFT model. For 3-side wormhole model, we find that reflected entropy is dual to island cross section. The reflected entropy between radiation and black hole increases at early time and then decreases to zero, similar to Page curve, but with a later transition time. The reflected entropy between radiation and radiation first increases and then saturates. For the EOW brane model, similar behaviors of reflected entropy are found. We propose a quantum extremal surface for reflected entropy, which we call quantum extremal cross section. In the eternal black hole plus CFT model, we find a generalized formula for reflected entropy with island cross section as its area term by considering the right half as the canonical purification of the left. Interestingly, the reflected entropy curve between the left black hole and the left radiation is nothing but the Page curve. We also find that reflected entropy between the left black hole and the right black hole decreases and goes to zero at late time. The reflected entropy between radiation and radiation increases at early time and saturates at late time.

Microstrain and the associated propagation of structural defects from the surface to the bulk are significant challenges in developing high energy, long life energy storage systems. However, the origins and impact of microstrain during the material synthesis remain poorly understood. In this study, we conducted real time, in situ microstrain screening during the synthesis of layered oxide cathode materials using multiscale synchrotron X-ray diffraction and microscopy techniques. Our findings reveal that the spatial distribution of transition metals within individual precursor particles critically influences nanoscale phase transformations, local charge heterogeneity, and the accumulation of microstrain. This unexpected dominance of transition metals results in a counterintuitive outward propagation of defect nucleation and growth. These insights provide a pathway for a more rational synthesis approach to minimize microstrain and crystallographic defects, enhancing the structural stability of battery materials. This work marks an essential step toward synthesis-by-design of defect-free materials for energy storage systems.

The dynamics of wind-generated water waves in the principal stage of the Phillips theory (Phillips, J. Fluid Mech., vol. 2, 1957, pp. 417–445) is investigated by a combined numerical and analytical approach. We perform a number of high-resolution direct numerical simulation (DNS) of turbulent wind over initially calm water to capture the multistage generation of water waves. Detailed analyses are conducted to evaluate the Phillips theory in both physical space and wavenumber space. Numerical evidence is obtained for the existence of a principal stage when the surface elevation variance grows linearly with time. We further propose a random sweeping turbulence pressure–wave interaction model by introducing the random sweeping hypothesis of air pressure fluctuations to the Phillips theory, and obtain an asymptotic solution of the mean square of surface wave elevations over time. This asymptotic analysis captures the temporal oscillations of surface elevation variance in the principal stage, which is also confirmed by our DNS results. The wavenumber spectrum of surface wave elevations is analysed using a time-dependent norm to elucidate the role of the resonance mechanism on wave generation. In physical space, we use the random sweeping turbulence pressure–wave interaction model to obtain a quantitative prediction of the growth rate of surface elevation variance in the principal stage, which is found to agree with the DNS results better than the original Phillips model.

Abstract Background: Cancer patterns in China are becoming similar to those in the United States (US). Comparing the recent cancer profiles, trends, and determinants in China and the US can provide useful reference data. Methods: This study used open-source data. We used GLOBOCAN 2022 cancer estimates and United Nations population estimates to calculate cancer cases and deaths in both countries during 2024. Data on cancer incidence and mortality trends were obtained from the Surveillance, Epidemiology, and End Results (SEER) program and National Centre for Health Statistics in the US and cancer registry reports of the National Cancer Center (NCC) of China. Data from the Global Burden of Disease study (GBD) and a decomposition approach were used to estimate the contributions of four determinants to the change in cancer deaths. Results: In 2024, there are an estimated 3,246,625 and 2,510,597 new cancer cases and 1,699,066 and 640,038 cancer deaths in China and the US, respectively. The highest estimated cancer cases are lung cancer in China and breast cancer in the US. The age-standardized incidence rates of lung and colorectal cancer in the US, and stomach, liver, and esophageal cancer in China have decreased, but the incidence rates of liver cancer in the US and colorectal cancer, prostate cancer in men, and cervical cancer in women in China have increased. Increases in the adult population size and population aging are main reasons for the increase in cancer deaths; case fatality rates are a main reason for the decrease in cancer deaths in both countries. Conclusions: China has made progress in cancer control but lags the US. Considering the transformation in China’s pattern of cancers epidemiology, it is imperative to develop stronger policies by adopting the cancer prevention and control strategies used in the US to address population aging and curb growing cancer trends.

A bstract Defect extremal surface is defined by extremizing the Ryu-Takayanagi formula corrected by the quantum defect theory. This is interesting when the AdS bulk contains a defect brane (or string). We introduce a defect extremal surface formula for reflected entropy, which is a mixed state generalization of entanglement entropy measure. Based on a decomposition procedure of an AdS bulk with a brane, we demonstrate the equivalence between defect extremal surface formula and island formula for reflected entropy in AdS 3 /BCFT 2 . We also compute the evolution of reflected entropy in evaporating black hole model and find that defect extremal surface formula agrees with island formula.

Technological advancements, particularly in the field of artificial intelligence (AI) have played an increasingly important role in transforming education. More recently, ground-breaking AI applications like ChatGPT have demonstrated the potential to bring radical changes to the educational landscape due to their capability to understand complex questions, generate plausible responses and human-like writing, and assist with the completion of complex tasks. However, ChatGPT has limitations in the quality of its output, such as the inclusion of inaccurate, fabricated and biased information and the lack of critical thinking and in-depth understanding. The combinations of these capabilities and limitations along with external factors (e.g., the growing demand for personalized learning support, the irresponsible and unethical use of AI) presents a range of opportunities and challenges to the potential use of ChatGPT in education. This paper presents a thorough SWOT (strength, weakness, opportunity, threat) analysis of ChatGPT, based on which we propose how ChatGPT can be properly integrated into teaching and learning practice to harness its potential in education.

The high volatility of the price of cobalt and the geopolitical limitations of cobalt mining have made the elimination of Co a pressing need for the automotive industry 1 . Owing to their high energy density and low-cost advantages, high-Ni and low-Co or Co-free (zero-Co) layered cathodes have become the most promising cathodes for next-generation lithium-ion batteries 2 , 3 . However, current high-Ni cathode materials, without exception, suffer severely from their intrinsic thermal and chemo-mechanical instabilities and insufficient cycle life. Here, by using a new compositionally complex (high-entropy) doping strategy, we successfully fabricate a high-Ni, zero-Co layered cathode that has extremely high thermal and cycling stability. Combining X-ray diffraction, transmission electron microscopy and nanotomography, we find that the cathode exhibits nearly zero volumetric change over a wide electrochemical window, resulting in greatly reduced lattice defects and local strain-induced cracks. In-situ heating experiments reveal that the thermal stability of the new cathode is significantly improved, reaching the level of the ultra-stable NMC-532. Owing to the considerably increased thermal stability and the zero volumetric change, it exhibits greatly improved capacity retention. This work, by resolving the long-standing safety and stability concerns for high-Ni, zero-Co cathode materials, offers a commercially viable cathode for safe, long-life lithium-ion batteries and a universal strategy for suppressing strain and phase transformation in intercalation electrodes. A compositionally complex (high-entropy) doping strategy is proposed to fabricate zero-strain high-Ni and Co-free layered cathodes with superior structural and mechanical stabilities and long cycle life.

Using text analysis techniques to identify the research topics of the literature in the field of cybersecurity allows us to sort out the evolution of their research topics and reveal their evolution trends. The paper takes the literature from the Web of Science in the field of cybersecurity research from 2003 to 2022 as its research subject, dividing it into ten stages. It then integrates LDA and Word2vec methods for topic recognition and topic evolution analysis. The combined LDA2vec model can better reflect the correlation and evolution patterns between adjacent stage topics, thereby accurately identifying topic features and constructing topic evolution paths. Furthermore, to comprehensively evaluate the effectiveness of the LDA model in topic evolution analysis, this paper introduces the Dynamic Topic Model (DTM) for comparative analysis. The results indicate that the LDA model demonstrates higher applicability and clarity in topic extraction and evolution path depiction. In the aspect of topic content evolution, research topics within the field of cybersecurity exhibit characteristics of complexity and diversity, with some topics even displaying notable instances of backtracking. Meanwhile, within the realm of cybersecurity, there exists a dynamic equilibrium between technological developments and security threats.

Quantum network is a promising platform for many ground-breaking applications that lie beyond the capability of its classical counterparts. Efficient entanglement generation on quantum networks with relatively limited resources such as quantum memories is essential to fully realize the network’s capabilities, the solution to which calls for delicate network design and is currently at the primitive stage. In this study we propose an effective routing scheme to enable automatic responses for multiple requests of entanglement generation between source-terminal stations on a quantum lattice network with finite edge capacities. Multiple connection paths are exploited for each connection request while entanglement fidelity is ensured for each path by performing entanglement purification. The routing scheme is highly modularized with a flexible nature, embedding quantum operations within the algorithmic workflow, whose performance is evaluated from multiple perspectives. In particular, three algorithms are proposed and compared for the scheduling of capacity allocation on the edges of quantum network. Embodying the ideas of proportional share and progressive filling that have been well-studied in classical routing problems, we design another scheduling algorithm, the propagatory update method, which in certain aspects overrides the two algorithms based on classical heuristics in scheduling performances. The general solution scheme paves the road for effective design of efficient routing and flow control protocols on applicational quantum networks.