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Many datasets in real life are complex and dynamic, that is, their key densities are varied over the whole key space and their key distributions change over time. It is challenging for an index structure to efficiently support all key operations for data management, in particular, search, insert, and scan, for such dynamic datasets. In this article, we present DyTIS (Dynamic dataset Targeted Index Structure), an index that targets dynamic datasets. DyTIS, although based on the structure of Extendible hashing, leverages the CDF of the key distribution of a dataset, and learns and adjusts its structure as the dataset grows. The key novelty behind DyTIS is to group keys by the natural key order and maintain keys in sorted order in each bucket to support scan operations within a hash index. We also define what we refer to as a dynamic dataset and propose a means to quantify its dynamic characteristics. Our experimental results show that DyTIS provides higher performance than the state-of-the-art learned index for the dynamic datasets considered. We also analyze the effects of the dynamic characteristics of datasets, including sequential datasets, as well as the effect of multiple threads on the performance of the indexes. 

Accurate determination of high strain rate (>103 1/s) constitutive properties of soft materials remains a formidable challenge. Albeit recent advancements among experimental techniques, in particular inertial microcavitation rheometry (IMR), the intrinsic requirement to visualize the bubble cavitation dynamics has limited its application to nominally transparent materials. Here, in an effort to address this challenge and to expand the experimental capability of IMR to optically opaque materials, we investigated whether one could use the acoustic signature of the time interval between the bubble's maximum radius and first collapse time point, characterized as the bubble collapse time, to infer the viscoelastic material properties without being able to image the bubble directly in the tissue. By introducing a modified Rayleigh collapse time for soft materials, which is strongly dependent on the stiffness of the material at hand, we show that, in principle, one can obtain an order of magnitude or better estimate of the viscoelastic material properties of the soft material under investigation. Using a newly developed energy-based theoretical framework, we show that for materials stiffer than 10 kPa the bubble collapse time during a single bubble cavitation event can provide quantitative and meaningful information about the constitutive properties of the material at hand. For very soft materials (i.e., shear modulus less than 10 kPa), our theory shows that unless the collapse time measurement has very high precision and low uncertainties, the material property estimates based on the bubble collapse time only will not be accurate and require visual resolution of the full cavitation kinematics. 

We investigate fermionic Mott insulators in a geometrically frustrated triangular lattice, a paradigm model system for studying spin liquids and spontaneous time-reversal symmetry breaking. Our study demonstrates the preparation of triangular Mott insulators and reveals antiferromagnetic spin-spin correlations among all nearest neighbors. We employ a real-space triangular-geometry quantum gas microscope to measure density and spin observables. Comparing experimental results with calculations based on numerical linked cluster expansions and quantum Monte Carlo techniques, we demonstrate thermometry in the frustrated system. Our experimental platform introduces an alternative approach to frustrated lattices which paves the way for future investigations of exotic quantum magnetism which may lead to a direct detection of quantum spin liquids in Hubbard systems. 

Diadenosine tetraphosphate (Ap4A) is a putative second messenger molecule that is conserved from bacteria to man. Nevertheless, its physiological role, and the underlying molecular mechanisms, are poorly characterized. We investigated the molecular mechanism by which Ap4A regulates inosine-5’-monophosphate dehydrogenase (IMPDH, a key branching point enzyme for the biosynthesis of adenosine or guanosine nucleotides) in Bacillus subtilis. We solved the crystal structure of BsIMPDH bound to Ap4A at a resolution of 2.45 Å to show that Ap4A binds to the interface between two IMPDH subunits, acting as the glue that switches active IMPDH tetramers into less active octamers. Guided by these insights, we engineered mutant strains of B. subtilis that bypass Ap4A-dependent IMPDH regulation without perturbing intracellular Ap4A pools themselves. We used metabolomics suggesting that these mutants have a dysregulated purine, and in particular GTP, metabolome and phenotypic analysis showing increased sensitivity of B. subtilis IMPDH mutant strains to heat compared with wild-type. Our study identifies a central role for IMPDH in remodelling metabolism and heat resistance, and provides evidence that Ap4A can function as an alarmone.