The pulse duration is a critical parameter of picosecond-petawatt laser systems because it directly affects the results of high-energy-density physics experiments. This study systematically investigated the effects of the spectral width, central wavelength and beam-pointing deviations on pulse duration stability at the SG-II facility. A theoretical analysis of the relationship between spectra and pulse duration is conducted to quantify the impact on pulse duration stability, and the results are further validated through experimental measurements. In addition, beam-pointing deviations at the stretcher significantly affect the pulse duration. For example, a 27 μrad deviation can induce a 30% pulse duration variation. In contrast, the compressor exhibits greater robustness. Based on simulation and experimental results, we identify operational tolerance ranges for spectral width and beam-pointing deviation to maintain pulse duration stability within 5% at the SG-II facility. These findings provide critical guidance for optimizing the performance and reliability of chirped-pulse amplification/optical parametric chirped-pulse amplification-based high-power laser systems.

Megacities around the world are increasingly confronted with conservation and restoration bottlenecks due to the competing demands of urban expansion and environmental conservation. This study investigates conservation prioritization strategies for balancing biodiversity protection, ecosystem service (ES) supply and landscape connectivity in rapidly urbanizing Beijing. By employing spatially explicit modelling and prioritization scenario techniques, we identify spatially heterogeneous priority zones. We demonstrate that high-value areas for ES supply, particularly carbon storage and water regulation, concentrate primarily in Beijing’s north-western mountainous regions, covering c. 62% of the city’s area. Conversely, critical habitats for threatened species and key connectivity corridors are dispersed, with 22.89% of critical habitats located within urban built-up areas. Gap analysis reveals limited alignment between Beijing’s current ecological security patterns, with only 9.6% coverage of the identified top 10% conservation priority zones, especially within the metropolitan core. The study underscores significant trade-offs among different ecological objectives and multi-criteria conservation strategies. We propose an optimized conservation framework based on zonation analysis to guide targeted landscape planning decisions. This approach provides actionable insights for urban policymakers to achieve comprehensive sustainability, emphasizing the importance of protecting critical ecological areas in both urban and rural landscapes amid ongoing urban expansion.

Background: We’ve adopted a novel approach that combines cellular barcoding with CRISPR/Cas-9 technology and single-cell RNA sequencing known as continuous lineage tracing to track the development, treatment and inevitable recurrence of glioblastoma. Methods: Patient derived glioma initiating cell lines were engineered with expressed DNA barcodes with CRISPR/Cas-9 targets and engrafted into NOD scid-mice. Clonal and relationships are surmised through identification of expressed barcodes, and cells were characterized by their transcriptional profiles. Phylogenetic lineage trees are created using lineage reconstructive algorithms to define cell fitness and expansion. Results: Our work has revealed a significant amount of intra-clonal cell state heterogeneity, suggesting that tumour cells engage in phenotype switching prior to therapeutic intervention. Phylogenetic lineage trees allowed us to define a gene signature of cell fitness. GBMs exist along a transcriptional gradient between undifferentiated but “high-fit” cells and terminally differentiated, “low-fit” cells, lending further evidence that these tumours consist of pools of cells that are capable of recapitulating the tumour microenvironment after treatment. Conclusions: We have successfully engineered a set of glioma initiating tumours with a novel lineage tracing technique, creating a powerful tool for real-time tracing of tumour growth through the analysis of highly detailed singe-cell RNA sequencing data with associated clonal and phylogenetic relationships.

Emission line galaxies (ELGs) are crucial for cosmological studies, particularly in understanding the large-scale structure of the Universe and the role of dark energy. ELGs form an essential component of the target catalogue for the Dark Energy Spectroscopic Instrument (DESI), a major astronomical survey. However, the accurate selection of ELGs for such surveys is challenging due to the inherent uncertainties in determining their redshifts with photometric data. In order to improve the accuracy of photometric redshift estimation for ELGs, we propose a novel approach CNN–MLP that combines convolutional neural networks (CNNs) with multilayer perceptrons (MLPs). This approach integrates both images and photometric data derived from the DESI Legacy Imaging Surveys Data Release 10. By leveraging the complementary strengths of CNNs (for image data processing) and MLPs (for photometric feature integration), the CNN–MLP model achieves a $\sigma_{\mathrm{NMAD}}$ (normalised median absolute deviation) of 0.0140 and an outlier fraction of 2.57%. Compared to other models, CNN–MLP demonstrates a significant improvement in the accuracy of ELG photometric redshift estimation, which directly benefits the target selection process for DESI. In addition, we explore the photometric redshifts of different galaxy types (Starforming, Starburst, AGN, and Broadline). Furthermore, this approach will contribute to more reliable photometric redshift estimation in ongoing and future large-scale sky surveys (e.g. LSST, CSST, and Euclid), enhancing the overall efficiency of cosmological research and galaxy surveys.

We present a high-power mid-infrared single-frequency pulsed fiber laser (SFPFL) with a tunable wavelength range from 2712.3 to 2793.2 nm. The single-frequency operation is achieved through a compound cavity design that incorporates a germanium etalon and a diffraction grating, resulting in an exceptionally narrow seed linewidth of approximately 780 kHz. Employing a master oscillator power amplifier configuration, we attain a maximum average output power of 2.6 W at 2789.4 nm, with a pulse repetition rate of 173 kHz, a pulse energy of 15 μJ and a narrow linewidth of approximately 850 kHz. This achievement underscores the potential of the mid-infrared SFPFL system for applications requiring high coherence and high power, such as high-resolution molecular spectroscopy, precision chemical identification and nonlinear frequency conversion.

This paper presents a millimeter-wave end-fire dual-polarized (DP) array antenna with symmetrical radiation patterns and high isolation. The DP radiation element is formed by integrating a quasi-Yagi antenna (providing horizontal polarization) into a pyramidal horn antenna (providing vertical polarization), resulting in a DP radiation element with a symmetrical radiation aperture. To efficiently feed the DP element while maintaining high isolation, a mode-composite full-corporate-feed network is employed, comprising substrate-integrated waveguide supporting the TE10 mode and substrate-integrated coaxial line supporting the TEM mode. This design eliminates the need for additional transition structures, achieving excellent mode isolation and a reduced substrate layer number. A 1 × 4-element DP array prototype operating at 26.5–29.5 GHz using low temperature co-fired ceramic technology was designed, fabricated, and measured. The test results indicate that the prototype achieves an average gain exceeding 10 dBi for both polarizations within the operating band. Thanks to the symmetrical DP radiation element and mode-composite full-corporate-feed network, symmetrical radiation patterns for both polarizations are observed in both the horizontal and vertical planes, along with a high cross-polarization discrimination of 22 dB and polarization port isolation of 35 dB.

Objectives/Goals: Identifying and indexing rare disease studies is labor intensive, especially in research centers with a large number of trials. To address this gap, we applied natural language processing (NLP) and visualization techniques to develop an efficient pipeline and user-friendly web interface. Our goal is to offer the rare disease study identification (RDSI) tool for adoption by other sites. Methods/Study Population: The RDSI retrieves study information (short and long titles, study abstract) from the IRB system. These descriptive fields are then processed by the MetaMap Lite NLP program for identifying disease terms and standardizing them to UMLS concepts. By terminology identifier mapping, the diseases intersecting with concepts in rare disease databases (Genetic and Rare Disease program and Orphanet) are further scored to pinpoint studies that focus on a rare disease. The web interface displays a scatter bubble chart as an overview of all the rare diseases, with each bubble size proportional to the number of studies for that disease. In addition to the visual navigation, users can search studies by disease name, PI, or IRB number. Search results contain detailed study information as well as the evidence used by algorithms of the pipeline. Results/Anticipated Results: The RDSI identification results and functions were verified manually and spot-checked by several study investigators. The web interface is a self-contained solution available to our staff for various use cases like reporting or environment scan. We have built in a versioning mechanism that logs the date of each major result in the process. Therefore, even as the rare disease data sources evolve over time, we will be able to preserve any historical context or perform updates as needed. The RDSI outputs are replicated to Mayo Clinic’s enterprise data warehouse daily, allowing tech-savvy users to leverage any useful intermediate results at the backend. We anticipate the performance of the rare disease identification to be further enhanced by employing the advancements in AI technology. Discussion/Significance of Impact: The RDSI represents an informatics solution that offers efficiency in identifying and navigating rare disease clinical studies. It features the use of public databases and open-source tools, manifesting return on investment from the broad translational science ecosystem. These considerations are informative and adoptable by other institutions.

Objectives/Goals: The operation of a clinical trials unit involves multifaceted tasks and stakeholders. A competent information system is critical to daily operations while ensuring smooth conduct of clinical research. We share 15 years of experience in the design and implementation of such a system at Mayo Clinic to inform other institutions with similar interests. Methods/Study Population: The Informatics team collaborated closely with nurse leaders and elicited input from additional stakeholders including nurse unit coordinators, lab managers, schedulers, investigators, study coordinators, and regulatory specialists throughout the phases of system design, development and continuous enhancements, and expansion. The stakeholders offered insights on the corresponding requirements throughout the study life cycle, from engaging with the study sponsor, operational review for protocol execution, development of study budgets, human subject protection and risk mitigation, data management and integration, to outcome monitoring, and regulatory reporting. The activities were then translated into functional components and implemented as a seamless and effective solution. Results/Anticipated Results: Patient safety, scientific rigor, operation automation, efficiency, and regulatory requirements were all considered in developing an integrated system, or the clinical research trials unit (CRTU) Tools. Our institution has leveraged the system for essential tasks from the study start-up, visit scheduling and execution, specimen collection and tracking, to individual protocol metrics and billing. We adopted a measure-as-we-go methodology so that data such as visit census, resource usage, and protocol deviation are tracked and collected during routine use of the system. Specifically, an issues/concerns/exceptions (ICE) tool is used for quality control and patient safety. Moreover, data quality greatly benefits from a task dictionary, standardizing the study activities that can be ordered and executed. Discussion/Significance of Impact: The implementation of a well-rounded clinical trials unit information system not only improves the operation efficiency and team productivity but also ensures scientific rigor and contributes to patient safety. We believe the experience can be informative to other institutions. More details will be shared in the poster.

The proposed Thermal Sidewall Ice Corer (TSIC) is designed to accurately sample horizontal ice layers of scientific interest, such as tephra layers, basal ice and shear zones, and retrieve ice cores back to the surface. The system features a bending core barrel with a thermal coring head, which bends as it extends from the drill body, enabling it to penetrate horizontal interlayers while maintaining a horizontal position until the ice core is extracted. The bending core barrel is driven by screw pairs, powered by a motor, to apply drilling load and pulling force. As the barrel bends, the ice cores are broken inside and transported to the surface along with the drill via a winch. A camera system has been incorporated into the TSIC to precisely locate the target layer. The corer is suitable for ice boreholes with diameters ranging from 135 to 170 mm, capable of retrieving ice cores with a diameter of 20–30 mm, and achieving a maximum penetration rate of 2 m h−1. The maximum length of ice samples that can be retrieved in a single drilling run is 500 mm. The coring performance for horizontal sampling has been validated through the development and testing of a prototype in the laboratory.

Ramsey’s theorem guarantees for every graph H that any 2-edge-coloring of a sufficiently large complete graph contains a monochromatic copy of H. In 1962, Erdős conjectured that the random 2-edge-coloring minimizes the number of monochromatic copies of $K_k$, and the conjecture was extended by Burr and Rosta to all graphs. In the late 1980s, the conjectures were disproved by Thomason and Sidorenko, respectively. A classification of graphs whose number of monochromatic copies is minimized by the random 2-edge-coloring, which are referred to as common graphs, remains a challenging open problem. If Sidorenko’s conjecture, one of the most significant open problems in extremal graph theory, is true, then every 2-chromatic graph is common and, in fact, no 2-chromatic common graph unsettled for Sidorenko’s conjecture is known. While examples of 3-chromatic common graphs were known for a long time, the existence of a 4-chromatic common graph was open until 2012, and no common graph with a larger chromatic number is known.

We construct connected k-chromatic common graphs for every k. This answers a question posed by Hatami et al. [Non-three-colourable common graphs exist, Combin. Probab. Comput. 21 (2012), 734–742], and a problem listed by Conlon et al. [Recent developments in graph Ramsey theory, in Surveys in combinatorics 2015, London Mathematical Society Lecture Note Series, vol. 424 (Cambridge University Press, Cambridge, 2015), 49–118, Problem 2.28]. This also answers in a stronger form the question raised by Jagger et al. [Multiplicities of subgraphs, Combinatorica 16 (1996), 123–131] whether there exists a common graph with chromatic number at least four.

Accurate channel characterization is extremely helpful in channel estimation, channel coding, and many other parts of communication system design and can effectively reduce overhead. Ray tracing (RT) shows accurate channel reconstruction for specific maps, but the multipath propagation in indoor scenes is far more complex than in outdoor scenes leading to a challenge for RT. This work presents and validates an RT tool for a massive multiple-input multiple-output (MIMO) system in the millimeter-wave frequency bands with the associated channel beamforming algorithm and provides ideas for channel estimation algorithm in subsequent MIMO systems. The impact of the order of interactions, e.g. reflections and diffractions on the channel impulse response reconstruction are analyzed in the RT simulation. The comparison between RT simulated and measured results shows a reasonable level of agreement. The presented RT tool that can provide complete and accurate channel information is of high value for the design of reliable communication systems.

For the pulse shaping system of the SG-II-up facility, we propose a U-shaped convolutional neural network that integrates multi-scale feature extraction capabilities, an attention mechanism and long short-term memory units, which effectively facilitates real-time denoising of diverse shaping pulses. We train the model using simulated datasets and evaluate it on both the simulated and experimental temporal waveforms. During the evaluation of simulated waveforms, we achieve high-precision denoising, resulting in great performance for temporal waveforms with frequency modulation-to-amplitude modulation conversion (FM-to-AM) exceeding 50%, exceedingly high contrast of over 300:1 and multi-step structures. The errors are less than 1% for both root mean square error and contrast, and there is a remarkable improvement in the signal-to-noise ratio by over 50%. During the evaluation of experimental waveforms, the model can obtain different denoised waveforms with contrast greater than 200:1. The stability of the model is verified using temporal waveforms with identical pulse widths and contrast, ensuring that while achieving smooth temporal profiles, the intricate details of the signals are preserved. The results demonstrate that the denoising model, trained utilizing the simulation dataset, is capable of efficiently processing complex temporal waveforms in real-time for experiments and mitigating the influence of electronic noise and FM-to-AM on the time–power curve.

In this study, direct numerical simulation of the particle dispersion and turbulence modulation in a sonic transverse jet injected into a supersonic cross-flow with a Mach number of 2 was carried out with the Eulerian–Lagrangian point-particle method. One single-phase case and two particle-laden cases with different particle diameters were simulated. The jet and particle trajectories, the dispersion characteristics of particles, and the modulation effect of particles on the flow were investigated systematically. It was found that large particles primarily accumulate around shear layer structures situated on the windward side of the jet trajectory. In contrast, small particles exhibit radial transport, accessing both upstream and downstream recirculation zones. Moreover, small particles disperse extensively within the boundary layer and large-scale shear layers, evidently influenced by the streamwise vortices. The particles increase the mean wall-normal velocity near the wall in the wake region of the transverse jet, while reducing the mean streamwise and wall-normal velocities in outer regions. Particles significantly alter the flow velocity adjacent to shock fronts. In particular, the turbulent fluctuations near the windward barrel shock and bow shock are reduced, while those around the leeward barrel shock are increased. An upward displacement of the bow shock in the wall-normal direction is also observed due to particles. In the regions away from the shocks, small particles tend to amplify the Reynolds stress, while large particles attenuate the turbulent kinetic energy.

The associations between obesity and liver diseases are complex and diverse. To explore the causal relationships between obesity and liver diseases, we applied two-sample Mendelian randomisation (MR) and multivariable MR analysis. The data of exposures (BMI and WHRadjBMI) and outcomes (liver diseases and liver function biomarker) were obtained from the open genome-wide association study database. A two-sample MR study revealed that the genetically predicted BMI and WHRadjBMI were associated with non-alcoholic fatty liver disease, liver fibrosis and autoimmune hepatitis. Obesity was not associated with primary biliary cholangitis, liver failure, liver cell carcinoma, viral hepatitis and secondary malignant neoplasm of liver. A higher WHRadjBMI was associated with higher levels of biomarkers of lipid accumulation and metabolic disorders. These findings indicated independent causal roles of obesity in non-alcoholic fatty liver disease, liver fibrosis and impaired liver metabolic function rather than in viral or autoimmune liver disease.

Purple nutsedge (Cyperus rotundus L.) is one of the world’s resilient upland weeds, primarily spreading through its tubers. Its emergence in rice (Oryza sativa L.) fields has been increasing, likely due to changing paddy-farming practices. This study aimed to investigate how C. rotundus, an upland weed, can withstand soil flooding and become a problematic weed in rice fields. The first comparative analysis focused on the survival and recovery characteristics of growing and mature tubers of C. rotundus exposed to soil-flooding conditions. Notably, mature tubers exhibited significant survival and recovery abilities in these environments. Based on this observation, further investigation was carried out to explore the morphological structure, nonstructural carbohydrates, and respiratory mechanisms of mature tubers in response to prolonged soil flooding. Over time, the mature tubers did not form aerenchyma but instead gradually accumulated lignified sclerenchymal fibers, with lignin content also increasing. After 90 d, the lignified sclerenchymal fibers and lignin contents were 4.0 and 1.1 times higher than those in the no soil-flooding treatment. Concurrently, soluble sugar content decreased while starch content increased, providing energy storage, and alcohol dehydrogenase activity rose to support anaerobic respiration via alcohol fermentation. These results indicated that mature tubers survived in soil-flooding conditions by adopting a low-oxygen quiescence strategy, which involves morphological adaptations through the development of lignified sclerenchymal fibers, increased starch reserves for energy storage, and enhanced anaerobic respiration. This mechanism likely underpins the flooding tolerance of mature C. rotundus tubers, allowing them to endure unfavorable conditions and subsequently germinate and grow once flooding subsides. This study provides a preliminary explanation of the mechanism by which mature tubers of C. rotundus from the upland areas confer flooding tolerance, shedding light on the reasons behind this weed’s increasing presence in rice fields.

Rayleigh–Bénard convection in a rotating spherical shell provides a simplified model for convective dynamics of planetary and stellar interiors. Over the past decades, the problem has been studied extensively via numerical simulations, but most previous simulations set the Prandtl number $Pr$ to unity. In this study we build more than 200 numerical models of rotating convection in a spherical shell over a wide range of $Pr$ ($10^{-2}\le Pr \le 10^2$). By increasing the Rayleigh number $Ra$, we characterise four different flow regimes, starting from the linear onset to multiple modes, then transitioning to the geostrophic turbulence and eventually approaching the weakly rotating regime. In the multiple modes regime, we show evidence of triadic resonances in numerical models with different $Pr$, which may provide a generic mechanism for the transition from laminar to turbulence in rotating convection. We analyse scaling behaviours of the heat transfer and convective flow speeds in numerical simulations, paying particular attention to the $Pr$ dependence. We find that the so-called diffusion-free scaling for the heat transfer cannot reconcile all numerical models with different $Pr$ in the geostrophic turbulence regime. However, the characteristic flow speeds at different $Pr$ roughly follow a unified scaling that can be described by visco-Archimedean–Coriolis force balances, though the scaling tends to approach the Coriolis-inertial-Archimedean force balance at low $Pr$. We also show that transition behaviours from rotating to non-rotating convection depend on $Pr$. The transition criteria based on heat transfer and flow morphology would be rather different when $Pr>1$, but the two criteria are consistent for cases with $Pr\le 1$. Both scaling behaviours and transition behaviours suggest that the heat transfer is controlled by the boundary layers while the convective flow speeds are mainly determined by the force balance in the bulk for cases with $Pr>1$, which is in line with recent experimental results with moderate to high $Pr$. For cases with $Pr \le 1$, both the heat transfer and convective velocities are approaching the inviscid dynamics in the bulk. We also briefly analysed the magnitude and scaling of zonal flows at different $Pr$, showing that the zonal flow amplitude rapidly increases as $Pr$ decreases.