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The idea of the out-of-time-order correlator (OTOC) has recently emerged in the study of both condensed matter systems and gravitational systems. It not only plays a key role in investigating the holographic duality between a strongly interacting quantum system and a gravitational system, it also diagnoses the chaotic behavior of many-body quantum systems and characterizes information scrambling. Based on OTOCs, three different concepts—quantum chaos, holographic duality, and information scrambling—are found to be intimately related to each other. Despite its theoretical importance, the experimental measurement of the OTOC is quite challenging, and thus far there is no experimental measurement of the OTOC for local operators. Here, we report the measurement of OTOCs of local operators for an Ising spin chain on a nuclear magnetic resonance quantum simulator. We observe that the OTOC behaves differently in the integrable and nonintegrable cases. Based on the recent discovered relationship between OTOCs and the growth of entanglement entropy in the many-body system, we extract the entanglement entropy from the measured OTOCs, which clearly shows that the information entropy oscillates in time for integrable models and scrambles for nonintgrable models. With the measured OTOCs, we also obtain the experimental result of the butterfly velocity, which measures the speed of correlation propagation. Our experiment paves a way for experimentally studying quantum chaos, holographic duality, and information scrambling in many-body quantum systems with quantum simulators.

Food waste is becoming more prevalent, and managing it is one of the most important issues in terms of food safety. In this study, functional proteins and bioactive peptides produced from the enzymatic digestion of black soldier fly ( Hermetia illucens L. , BSF) fed with food wastes were characterized and quantified using proteomics-based analysis. The results revealed approximately 78 peptides and 57 proteins, including 40S ribosomal protein S4, 60S ribosomal protein L8, ATP synthase subunit alpha, ribosomal protein S3, Histone H2A, NADP-glutamate dehydrogenase, Fumarate hydratase, RNA helicase, Chitin binding Peritrophin-A, Lectin C-type protein, etc. were found in BSF. Furthermore, functional analysis of the proteins revealed that the 60S ribosomal protein L5 (RpL5) in BSF interacted with a variety of ribosomal proteins and played a key role in the glycolytic process (AT14039p). Higher antioxidant activity was found in peptide sequences such as GYGFGGGAGCLSMDTGAHLNR, VVPSANRAMVGIVAGGGRIDKPILK, AGLQFPVGR, GFKDQIQDVFK, and GFKDQIQDVFK. It was concluded that the bioconversion of food wastes by BSF brought about the generation of a variety of functional proteins and bioactive peptides with strong antioxidant activity. However, more studies are required to exploit BSF's potential in the value addition of food wastes.

To investigate cervical cancer screening knowledge, attitudes, and practices among high-risk women in remote western China, and to identify socioeconomic and systemic barriers influencing screening participation. Additionally, to evaluate the comparative effectiveness of p16 staining versus p16/Ki-67 dual-staining immunocytochemistry in triaging women with cytological abnormalities or HPV-positive results, aiming to reduce unnecessary colposcopy referrals in resource-limited settings. This cross-sectional study enrolled 260 women (aged 20-65 years) with cytological abnormalities or HPV-positive results from two remote counties in Xinjiang Province (January-December 2023). Participants completed structured questionnaires assessing cervical cancer knowledge, screening attitudes, and healthcare access. Cervical specimens collected liquid-based cytology underwent parallel testing: conventional cytology, p16 staining, and p16/Ki-67 dual-staining, with all analyses performed by blinded pathologists. Among 260 high-risk women in Xinjiang, cervical cancer awareness (67.31%, 95% CI [61.50-72.90]) and screening rates (56.15%, 95% CI [50.23-62.17]) remained suboptimal. Multivariable analyses revealed significant disparities: college-educated women had 7.58-fold higher odds of awareness (95% CI [2.32-24.75]) compared to those with primary education, while public servants showed the strongest employment-based association (aOR = 11.23, 95% CI [2.64-47.83]). Mediation analysis demonstrated that health awareness fully mediated the effect of education (128.8% mediation) and nearly fully mediated the effect of employment (93.8%). Notably, 93.98% (95% CI [90.85-96.27]) expressed willingness to rescreen, and 82.95% (95% CI [78.33-86.84]) supported HPV vaccination. Biomarker analysis showed that p16/Ki-67 dual-staining positivity increased progressively with lesion severity (  < 0.001). This study reveals suboptimal cervical cancer knowledge and screening rates among women in Xinjiang, with socioeconomic disparities-particularly in education and employment-primarily mediated through health awareness. The findings support integrated interventions, including physician-led education, digital health communication for media-dependent populations, simplified visual materials for less-educated women, and active linkage to national screening programs for unemployed populations. High rescreening willingness and parental acceptance of HPV vaccination indicate strong potential for intervention. p16 staining and p16/Ki-67 dual-staining show promise for triage in resource-limited settings. These findings highlight the need for tailored strategies to enhance cervical cancer prevention in western China, with further research needed to address current limitations.

Bactrocera cucurbitae (Coquillett) is an important pest of cucurbit crops and certain vegetables in Asia, the Middle East, Africa and Hawaii. Most studies on B. cucurbitae have focussed on the effects of prolonged high temperature and very few have examined the effects of short-term exposures to high-temperature on behaviour. In this study, short-term of high-temperature treatments of 33°C, 37°C, 41°C and 45°C were maintained for 1-3hr, and long-term, variable high-temperature treatments were established that consisted of experienced one, two and three times high temperatures stages to 31°C, 33°C, 34°C, 35°C, 36°C, 37°C, 41°C and 45°C for 7hr. We compared the effects of the different high temperatures regimes changes treatments on the mating, oviposition and thermotactic taxis of the flies. The results showed that exposure to a 45°C/1hr treatment, delayed both initiation of mating and oviposition for 8 hr relative to the control but mating and was observed 41 times and oviposition 47 times. By comparison, in the control, mating commenced immediately and was observed 38.3 times and oviposition was observed 41.3 times. Under the other treatments, all the indices for the flies declined with the increase in temperature and duration of exposure. Results showed that 1hr of exposure to 45°C significantly stimulated mating, oviposition and thermotactic behaviour of the flies. These results could improve our understanding of the mechanisms responsible for the population dynamics of B. cucurbitae during the high-temperature season.

Inspired by the concept of “potential energy” in physics, we propose a new indicator to measure the “direction” of interdisciplinary knowledge diffusion named “disciplinary potential energy” (DPE). We also used the Shannon entropy to measure the “diversity” of interdisciplinary knowledge diffusion. In memory of Professor Zeyuan Liu, a pioneer in the field of science of science (SoS) in China, we measured the direction and diversity of his interdisciplinary knowledge diffusion, based on his 371 publications and subsequent citations in the China National Knowledge Infrastructure (CNKI) database, and 236 journal articles and subsequent citations in the Chinese Social Science Citation Index (CSSCI) database, respectively. The findings are (1) the newly proposed indicator that has advantages over previous interdisciplinary indicators characterizing the relative location of each discipline in the knowledge flow, through both direct and indirect citations; (2) particular importance was attached to Liu's contributions to management science (focusing on SoS) and philosophy (focusing on philosophy of science and technology) because of the “reverse-flow” of his knowledge from “net-inflow” disciplines to “net-outflow” disciplines, although his contributions covered at least four disciplines, namely management science, economics (focusing on technical economics), philosophy, and engineering; and (3) Liu's research has had ever-increasing influence on management science over the past decade, while his interdisciplinary citation influence decreased in economics, philosophy and engineering. This study not only demonstrates how extensive Liu's knowledge contributions have been to Chinese academia. We also shed light on the methodology to measure interdisciplinary knowledge diffusion.

Background and aims Rhizosphere microorganisms play a critical role in plant growth, particularly in degraded lands. However, the characteristics of rhizosphere microbial communities, assembly mechanisms, and their influencing factors in Pinus elliottii plantations on sandy lands in the Poyang Lake Basin, China, remain unclear. Methods We investigated the composition of bulk soil and rhizosphere microbial communities in P. elliottii plantations by Illumina Miseq sequencing. Community assembly and cross-domain network analyses were used to reveal the microbial community assembly mechanisms and co-occurrence patterns, and to identify the main biotic and abiotic factors influencing them. Results The P. elliottii rhizosphere was significantly enriched with Burkholderia-Caballeronia-Paraburkholderia . The composition of the fungal community did not exhibit significant differences between compartments. The P. elliottii rhizosphere had a notably simplified bacterial-fungal co-occurrence network, with keystone microorganisms potentially exerting significant roles in plantation establishment and soil nitrogen and phosphorus cycling. Bacterial community assembly was governed by both deterministic and stochastic processes, whereas fungal communities were dominated by stochastic processes. A significant correlation was detected between bacterial communities and fungal richness. Differences in fungal richness were significantly correlated with the rhizosphere bacterial community beta-Nearest Taxon Index, whereby a larger difference in fungal richness between samples led to a higher percentage of variable selection in the process of rhizosphere bacterial community assembly. Conclusion This study highlights the strong association between P. elliottii and Burkholderia-Caballeronia-Paraburkholderia and underscores the significant role of fungal richness in the bacterial community assembly in the rhizosphere of P. elliottii in sandy soils.

The quantum imaginary time evolution is a powerful algorithm for preparing the ground and thermal states on near-term quantum devices. However, algorithmic errors induced by Trotterization and local approximation severely hinder its performance. Here we propose a deep reinforcement learning-based method to steer the evolution and mitigate these errors. In our scheme, the well-trained agent can find the subtle evolution path where most algorithmic errors cancel out, enhancing the fidelity significantly. We verified the method’s validity with the transverse-field Ising model and the Sherrington-Kirkpatrick model. Numerical calculations and experiments on a nuclear magnetic resonance quantum computer illustrate the efficacy. The philosophy of our method, eliminating errors with errors, sheds light on error reduction on near-term quantum devices. Quantum imaginary time evolution – a common technique in theoretical studies to prepare ground states of quantum systems – comes with the uneasy requirement to implement non-unitary time evolution in the lab, and while recent solution has been proposed it carries leftover errors. The present work implements reinforcement learning to mitigate such errors in a physics-informed way, demonstrating the efficiency of AI-enhanced algorithms on a quantum computer.

Quantum query complexity is pivotal in the analysis of quantum algorithms, encompassing well-known examples like search and period-finding algorithms. These algorithms typically involve a sequence of unitary operations and oracle calls dependent on an input variable. In this study, we introduce a variational learning approach to explore quantum query complexity. Our method employs an efficient parameterization of the unitary operations and utilizes a loss function derived from the algorithm’s error probability. We apply this technique to various quantum query complexities, notably devising a new algorithm that resolves the 5-bit Hamming modulo problem with four queries, addressing an open question from Cornelissen et al (2021 arXiv: 2112.14682 ). This finding is corroborated by a semidefinite programming (SDP) approach. Our numerical method exhibits superior memory efficiency compared to SDP and can identify quantum query algorithms (QQAs) that require a smaller workspace register dimension, an aspect not optimized by SDP. These advancements present a significant step forward in the practical application and understanding of QQAs.

Quantum resource theories (QRTs) provide a comprehensive and practical framework for the analysis of diverse quantum phenomena. A fundamental task within QRTs is the quantification of resources inherent in a given quantum state. In this work, we introduce a unified computational framework for a class of widely utilized quantum resource measures, derived from convex roof extensions. We establish that the computation of these convex roof resource measures can be reformulated as an optimization problem over a Stiefel manifold, which can be further unconstrained through polar projection. Compared to existing methods employing semi-definite programming (SDP), gradient-based techniques or seesaw strategy, our approach not only demonstrates satisfying computational efficiency but also maintains applicability across various scenarios within a unified framework. We substantiate the efficacy of our method by applying it to several key quantum resources, including entanglement, coherence, and magic states. Moreover, our methodology can be readily extended to other convex roof quantities beyond the domain of resource theories, suggesting broad applicability in the realm of quantum information theory.

Invariant tensors are states in the SU(2) tensor product representation that are invariant under SU(2) action. They play an important role in the study of loop quantum gravity. On the other hand, perfect tensors are highly entangled many-body quantum states with local density matrices maximally mixed. Recently, the notion of perfect tensors has attracted a lot of attention in the fields of quantum information theory, condensed matter theory, and quantum gravity. In this work, we introduce the concept of an invariant perfect tensor (IPT), which is an n-valent tensor that is both invariant and perfect. We discuss the existence and construction of IPTs. For bivalent tensors, the IPT is the unique singlet state for each local dimension. The trivalent IPT also exists and is uniquely given by Wigner's 3 j symbol. However, we show that, surprisingly, 4-valent IPTs do not exist for any identical local dimension d. On the contrary, when the dimension is large, almost all invariant tensors are asymptotically perfect, which is a consequence of the phenomenon of the concentration of measure for multipartite quantum states.