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The evolving focus in statistics and data science education highlights the growing importance of computing. This paper presents the Data Jamboree, a live event that combines computational methods with traditional statistical techniques to address real-world data science problems. Participants, ranging from novices to experienced users, followed workshop leaders in using open-source tools like Julia, Python, and R to perform tasks such as data cleaning, manipulation, and predictive modeling. The Jamboree showcased the educational benefits of working with open data, providing participants with practical, hands-on experience. We compared the tools in terms of efficiency, flexibility, and statistical power, with Julia excelling in performance, Python in versatility, and R in statistical analysis and visualization. The paper concludes with recommendations for designing similar events to encourage collaborative learning and critical thinking in data science. 

Subsampling is a practical strategy for analyzing vast survival data, which are progressively encountered across diverse research domains. While the optimal subsampling method has been applied to inferences for Cox models and parametric accelerated failure time (AFT) models, its application to semi‐parametric AFT models with rank‐based estimation have received limited attention. The challenges arise from the non‐smooth estimating function for regression coefficients and the seemingly zero contribution from censored observations in estimating functions in the commonly seen form. To address these challenges, we develop optimal subsampling probabilities for both event and censored observations by expressing the estimating functions through a well‐defined stochastic process. Meanwhile, we apply an induced smoothing procedure to the non‐smooth estimating functions. As the optimal subsampling probabilities depend on the unknown regression coefficients, we employ a two‐step procedure to obtain a feasible estimation method. An additional benefit of the method is its ability to resolve the issue of underestimation of the variance when the subsample size approaches the full sample size. We validate the performance of our estimators through a simulation study and apply the methods to analyze the survival time of lymphoma patients in the surveillance, epidemiology, and end results program. 

The delafossites are a class of layered metal oxides that are notable for being able to exhibit optical transparency alongside an in-plane electrical conductivity, making them promising platforms for the development of transparent conductive oxides. Pressure-induced polymorphism offers a direct method for altering the electrical and optical properties in this class, and although the copper delafossites have been studied extensively under pressure, the silver delafossites remain only partially studied. We report two new high-pressure polymorphs of silver ferrite delafossite, AgFeO2, that are stabilized above ∼6 and ∼14 GPa. In situ X-ray diffraction and vibrational spectroscopy measurements are used to examine the structural changes across the two phase transitions. The high-pressure structure between 6 and 14 GPa is assigned as a monoclinic C2/c structure that is analogous to the high-pressure phase reported for AgGaO2. Nuclear resonant forward scattering reveals no change in the spin state or valence state at the Fe3+ site up to 15.3(5) GPa. 

Abstract Vanadium (V) pollution potentially threatens human health. Here, it is found thatnsp1andnsp2,Rhizobiumsymbiosis defective mutants ofMedicago truncatula, are sensitive to V. Concentrations of phosphorus (P), iron (Fe), and sulfur (S) with V are negatively correlated in the shoots of wild‐type R108, but not in mutantnsp1andnsp2shoots. Mutations in the P transporterPHT1,PHO1, andVPTfamilies, Fe transporterIRT1, and S transporterSULTR1/3/4family confer varying degrees of V tolerance on plants. Among these gene families,MtPT1,MtZIP6,MtZIP9, andMtSULTR1; 1in R108 roots are significantly inhibited by V stress, whileMtPHO1; 2,MtVPT2, andMtVPT3are significantly induced. Overexpression ofArabidopsis thaliana VPT1orM. truncatula MtVPT3increases plant V tolerance. However, the response of these genes to V is weakened innsp1ornsp2and influenced by soil microorganisms. Mutations inNSPsreduce rhizobacterial diversity under V stress and simplify the V‐responsive operational taxonomic unit modules in co‐occurrence networks. Furthermore, R108 recruits more beneficial rhizobacteria related to V, P, Fe, and S than doesnsp1ornsp2. Thus, NSPs can modulate the accumulation and tolerance of legumes to V through P, Fe, and S transporters, ion homeostasis, and rhizobacterial community responses.