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Molecular structure, a key concept of chemistry, has remained elusive from the perspective of all-particle quantum mechanics, despite many efforts. Viewing molecular structure as a manifestation of strong statistical correlation between nuclear positions, we propose a practical method based on Markov chain Monte Carlo sampling and unsupervised machine learning. Application to the D3+ molecule unambiguously shows that it possesses an equilateral triangular structure. These results provide a major step forward in our understanding of the molecular structure from fundamental quantum principles.
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Quantum random number generators promise perfectly unpredictable random numbers. A popular approach to quantum random number generation is homodyne measurements of the vacuum state, the ground state of the electro-magnetic field. Here we experimentally implement such a quantum random number generator, and derive a security proof that considers quantum side-information instead of classical side-information only. Based on the assumptions of Gaussianity and stationarity of noise processes, our security analysis furthermore includes correlations between consecutive measurement outcomes due to finite detection bandwidth, as well as analog-to-digital converter imperfections. We characterize our experimental realization by bounding measured parameters of the stochastic model determining the min-entropy of the system's measurement outcomes, and we demonstrate a real-time generation rate of 2.9 Gbit/s. Our generator follows a trusted, device-dependent, approach. By treating side-information quantum mechanically an important restriction on adversaries is removed, which usually was reserved to semi-device-independent and device-independent schemes.
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MOLCAS/OpenMolcas is an ab initio electronic structure program providing a large set of computational methods from Hartree-Fock and density functional theory to various implementations of multiconfigurational theory. This article provides a comprehensive overview of the main features of the code, specifically reviewing the use of the code in previously reported chemical applications as well as more recent applications including the calculation of magnetic properties from optimized density matrix renormalization group wave functions.
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Undefined mesophilic mixed (DL-type) starter cultures are composed of predominantly Lactococcus lactis subspecies and 1-10% Leuconostoc spp. The composition of the Leuconostoc population in the starter culture ultimately affects the characteristics and the quality of the final product. The scientific basis for the taxonomy of dairy relevant leuconostocs can be traced back 50 years, and no documentation on the genomic diversity of leuconostocs in starter cultures exists. We present data on the Leuconostoc population in five DL-type starter cultures commonly used by the dairy industry. The analyses were performed using traditional cultivation methods, and further augmented by next-generation DNA sequencing methods. Bacterial counts for starter cultures cultivated on two different media, MRS and MPCA, revealed large differences in the relative abundance of leuconostocs. Most of the leuconostocs in two of the starter cultures were unable to grow on MRS, emphasizing the limitations of culture-based methods and the importance of careful media selection or use of culture independent methods. Pan-genomic analysis of 59 Leuconostoc genomes enabled differentiation into twelve robust lineages. The genomic analyses show that the dairy-associated leuconostocs are highly adapted to their environment, characterized by the acquisition of genotype traits, such as the ability to metabolize citrate. In particular, Leuconostoc mesenteroides subsp. cremoris display telltale signs of a degenerative evolution, likely resulting from a long period of growth in milk in association with lactococci. Great differences in the metabolic potential between Leuconostoc species and subspecies were revealed. Using targeted amplicon sequencing, the composition of the Leuconostoc population in the five commercial starter cultures was shown to be significantly different. Three of the cultures were dominated by Ln. mesenteroides subspecies cremoris. Leuconostoc pseudomesenteroides dominated in two of the cultures while Leuconostoc lactis, reported to be a major constituent in fermented dairy products, was only present in low amounts in one of the cultures. This is the first in-depth study of Leuconostoc genomics and diversity in dairy starter cultures. The results and the techniques presented may be of great value for the dairy industry.
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The present study investigated the utility of in vitro lipolysis performance indicators drug solubilization and maximum supersaturation ratio (SR(M)) for their predictive use for the in vivo performance in a minipig model. The commercial Lipanthyl formulation and a series of LbDDS based on identical self-nanoemulsifying drug delivery systems (SNEDDS) containing 200 mg of fenofibrate, either dissolved or suspended, were subjected to combined gastric (pH 2) and intestinal (pH 6.5) in vitro lipolysis. Based on the solubilization profiles and SRM the rank-order SNEDDS (75% drug load) > super-SNEDDS (150% drug load, dissolved) = SNEDDS suspension (150% drug load, partially suspended) > Lipanthyl was established, with an increased likelihood of drug precipitation above SR(M) > 3. The in vitro performance, however, was not reproduced in vivo in a minipig model as the mean plasma concentration over time curves of all LbDDS were comparable, independent of the initial physical state of the drug. There was no correlation between the area under the solubilization-time curves (AUC(in vitro)) of the intestinal step and the AUC(in vivo). The study suggests careful interpretation of in vitro performance criteria and revision of LbDDS optimization towards increased solubilization.
