Integer Lattice Gas with Monte Carlo collision operator recovers the entropic lattice Boltzmann method with Poisson distributed fluctuations

We are examining a new kind of lattice gas that closely resembles modern lattice Boltzmann methods. This new kind of lattice gas, that we call a Monte Carlo Lattice Gas, has interesting properties that shed light on the origin of the multi-relaxation time collision operator and it derives the equilibrium distribution for entropic lattice Boltzmann. Furthermore these lattice gas methods have Galilean invariant fluctuations given by a Poisson statistics, giving further insight into the properties that we should expect for fluctuating lattice Boltzmann methods.Comment: 17 pages, 10 figure

Most Likely to Succeed: Which Factors Influence College Students in Completing Their Two-Year Computer Degree and Graduating from College

For many individuals, researching and finding a college to attend is a wonderful experience. Many students explore college and take multiple courses, but do not finish their intended degree. Past and current studies have identified factors and reasons to why students dropout from college. Two well-known theories include A.W. Astin’s student involvement theory (1984) and Tinto’s (1993) model of college student attrition. The purpose of this study was to identify factors amongst students who graduated and students who did not graduate from a two-year computer degree program. The data derived from the collective stories of those who had experienced it. This qualitative study had a research method that was exploratory in nature. The epistemology component falls under subjectivism as the meaning resides in the students who experienced it. This phenomenological study interviewed seven individuals and investigated the personal educational journeys of four computer program graduates and three computer program non-completers. Prospective participants were emailed to gain interest in the study, and seven participants were recruited using purposeful sampling. After interviewing the individuals, the researcher took the semi-structured data and structured it into codes, themes, and patterns for analysis. This study aimed to find factors of college student success and attrition from non-completers. A sense of belonging and an understanding the purpose of being in college were important factors that were revealed by the participants

The 1.2 A resolution crystal structure of TcpG, the Vibrio cholerae DsbA disulfide-forming protein required for pilus and cholera-toxin production

The enzyme TcpG is a periplasmic protein produced by the Gram-negative pathogen Vibrio cholerae. TcpG is essential for the production of ToxR-regulated proteins, including virulence-factor pilus proteins and cholera toxin, and is therefore a target for the development of a new class of anti-virulence drugs. Here, the 1.2 Å resolution crystal structure of TcpG is reported using a cryocooled crystal. This structure is compared with a previous crystal structure determined at 2.1 Å resolution from data measured at room temperature. The new crystal structure is the first DsbA crystal structure to be solved at a sufficiently high resolution to allow the inclusion of refined H atoms in the model. The redox properties of TcpG are also reported, allowing comparison of its oxidoreductase activity with those of other DSB proteins. One of the defining features of the Escherichia coli DsbA enzyme is its destabilizing disulfide, and this is also present in TcpG. The data presented here provide new insights into the structure and redox properties of this enzyme, showing that the binding mode identified between E. coli DsbB and DsbA is likely to be conserved in TcpG and that the [beta]5-[alpha]7 loop near the proposed DsbB binding site is flexible, and suggesting that the tense oxidized conformation of TcpG may be the consequence of a short contact at the active site that is induced by disulfide formation and is relieved by reduction

Steady-state properties of multi-orbital systems using quantum Monte Carlo

A precise dynamical characterization of quantum impurity models with multiple interacting orbitals is challenging. In quantum Monte Carlo methods, this is embodied by sign problems. A dynamical sign problem makes it exponentially difficult to simulate long times. A multi-orbital sign problem generally results in a prohibitive computational cost for systems with multiple impurity degrees of freedom even in static equilibrium calculations. Here, we present a numerically exact inchworm method that simultaneously alleviates both sign problems, enabling simulation of multi-orbital systems directly in the equilibrium or nonequilibrium steady-state. The method combines ideas from the recently developed steady-state inchworm Monte Carlo framework [Phys. Rev. Lett. 130, 186301 (2023)] with other ideas from the equilibrium multi-orbital inchworm algorithm [Phys. Rev. Lett. 124, 206405 (2020)]. We verify our method by comparison with analytical limits and numerical results from previous methods

A Multispecies Hierarchical Model to Integrate Count and Distance-Sampling Data

Integrated community models—an emerging framework in which multiple data sources for multiple species are analyzed simultaneously—offer opportunities to expand inferences beyond the single-species and single-data-source approaches common in ecology. We developed a novel integrated community model that combines distance sampling and single-visit count data; within the model, information is shared among data sources (via a joint likelihood) and species (via a random-effects structure) to estimate abundance patterns across a community. Parameters relating to abundance are shared between data sources, and the model can specify either shared or separate observation processes for each data source. Simulations demonstrated that the model provided unbiased estimates of abundance and detection parameters even when detection probabilities varied between the data types. The integrated community model also provided more accurate and more precise parameter estimates than alternative single-species and single-data-source models in many instances. We applied the model to a community of 11 herbivore species in the Masai Mara National Reserve, Kenya, and found considerable interspecific variation in response to local wildlife management practices: Five species showed higher abundances in a region with passive conservation enforcement (median across species: 4.5× higher), three species showed higher abundances in a region with active conservation enforcement (median: 3.9× higher), and the remaining three species showed no abundance differences between the two regions. Furthermore, the community average of abundance was slightly higher in the region with active conservation enforcement but not definitively so (posterior mean: higher by 0.20 animals; 95% credible interval: 1.43 fewer animals, 1.86 more animals). Our integrated community modeling framework has the potential to expand the scope of inference over space, time, and levels of biological organization, but practitioners should carefully evaluate whether model assumptions are met in their systems and whether data integration is valuable for their applications

Parallel use of shake flask and microtiter plate online measuring devices (RAMOS and BioLector) reduces the number of experiments in laboratory-scale stirred tank bioreactors

Background Conventional experiments in small scale are often performed in a Black Box fashion, analyzing only the product concentration in the final sample. Online monitoring of relevant process characteristics and parameters such as substrate limitation, product inhibition and oxygen supply is lacking. Therefore, fully equipped laboratory-scale stirred tank bioreactors are hitherto required for detailed studies of new microbial systems. However, they are too spacious, laborious and expensive to be operated in larger number in parallel. Thus, the aim of this study is to present a new experimental approach to obtain dense quantitative process information by parallel use of two small-scale culture systems with online monitoring capabilities: Respiration Activity MOnitoring System (RAMOS) and the BioLector device. Results The same mastermix (medium plus microorganisms) was distributed to the different small-scale culture systems: 1) RAMOS device; 2) 48-well microtiter plate for BioLector device; and 3) separate shake flasks or microtiter plates for offline sampling. By adjusting the same maximum oxygen transfer capacity (OTRmax), the results from the RAMOS and BioLector online monitoring systems supplemented each other very well for all studied microbial systems (E. coli, G. oxydans, K. lactis) and culture conditions (oxygen limitation, diauxic growth, auto-induction, buffer effects). Conclusions The parallel use of RAMOS and BioLector devices is a suitable and fast approach to gain comprehensive quantitative data about growth and production behavior of the evaluated microorganisms. These acquired data largely reduce the necessary number of experiments in laboratory-scale stirred tank bioreactors for basic process development. Thus, much more quantitative information is obtained in parallel in shorter time.Cluster of Excellence “Tailor-Made Fuels from Biomass”, which is funded by the Excellence Initiative by the German federal and state governments to promote science and research at German universities

A Tensor Train Continuous Time Solver for Quantum Impurity Models

The simulation of strongly correlated quantum impurity models is a significant challenge in modern condensed matter physics that has multiple important applications. Thus far, the most successful methods for approaching this challenge involve Monte Carlo techniques that accurately and reliably sample perturbative expansions to any order. However, the cost of obtaining high precision through these methods is high. Recently, tensor train decomposition techniques have been developed as an alternative to Monte Carlo integration. In this study, we apply these techniques to the single-impurity Anderson model at equilibrium by calculating the systematic expansion in power of the hybridization of the impurity with the bath. We demonstrate the performance of the method in a paradigmatic application, examining the first-order phase transition on the infinite dimensional Bethe lattice, which can be mapped to an impurity model through dynamical mean field theory. Our results indicate that using tensor train decomposition schemes allows the calculation of finite-temperature Green's functions and thermodynamic observables with unprecedented accuracy. The methodology holds promise for future applications to frustrated multi-orbital systems, using a combination of partially summed series with other techniques pioneered in diagrammatic and continuous-time quantum Monte Carlo

Protein Structure Initiative Material Repository: an open shared public resource of structural genomics plasmids for the biological community

The Protein Structure Initiative Material Repository (PSI-MR; http://psimr.asu.edu) provides centralized storage and distribution for the protein expression plasmids created by PSI researchers. These plasmids are a resource that allows the research community to dissect the biological function of proteins whose structures have been identified by the PSI. The plasmid annotation, which includes the full length sequence, vector information and associated publications, is stored in a freely available, searchable database called DNASU (http://dnasu.asu.edu). Each PSI plasmid is also linked to a variety of additional resources, which facilitates cross-referencing of a particular plasmid to protein annotations and experimental data. Plasmid samples can be requested directly through the website. We have also developed a novel strategy to avoid the most common concern encountered when distributing plasmids namely, the complexity of material transfer agreement (MTA) processing and the resulting delays this causes. The Expedited Process MTA, in which we created a network of institutions that agree to the terms of transfer in advance of a material request, eliminates these delays. Our hope is that by creating a repository of expression-ready plasmids and expediting the process for receiving these plasmids, we will help accelerate the accessibility and pace of scientific discovery

The Center for Eukaryotic Structural Genomics

The Center for Eukaryotic Structural Genomics (CESG) is a “specialized” or “technology development” center supported by the Protein Structure Initiative (PSI). CESG’s mission is to develop improved methods for the high-throughput solution of structures from eukaryotic proteins, with a very strong weighting toward human proteins of biomedical relevance. During the first three years of PSI-2, CESG selected targets representing 601 proteins from Homo sapiens, 33 from mouse, 10 from rat, 139 from Galdieria sulphuraria, 35 from Arabidopsis thaliana, 96 from Cyanidioschyzon merolae, 80 from Plasmodium falciparum, 24 from yeast, and about 25 from other eukaryotes. Notably, 30% of all structures of human proteins solved by the PSI Centers were determined at CESG. Whereas eukaryotic proteins generally are considered to be much more challenging targets than prokaryotic proteins, the technology now in place at CESG yields success rates that are comparable to those of the large production centers that work primarily on prokaryotic proteins. We describe here the technological innovations that underlie CESG’s platforms for bioinformatics and laboratory information management, target selection, protein production, and structure determination by X-ray crystallography or NMR spectroscopy