PRISMA database machine: A distributed, main-memory approach

The PRISMA project is a large-scale research effort in the design and implementation of a highly parallel machine for data and knowledge processing. The PRISMA database machine is a distributed, main-memory database management system implemented in an object-oriented language that runs on top of a multi-computer system. A prototype that is envisioned consists of 64 processing elements

Modeling-Assisted Design of Thermostable Benzaldehyde Lyases from Rhodococcus erythropolis for Continuous Production of α-Hydroxy Ketones

Enantiopure α-hydroxy ketones are important building blocks of active pharmaceutical ingredients (APIs), which can be produced by thiamine-diphosphate-dependent lyases, such as benzaldehyde lyase. Here we report the discovery of a novel thermostable benzaldehyde lyase from Rhodococcus erythropolis R138 (ReBAL). While the overall sequence identity to the only experimentally confirmed benzaldehyde lyase from Pseudomonas fluorescens Biovar I (PfBAL) was only 65 %, comparison of a structural model of ReBAL with the crystal structure of PfBAL revealed only four divergent amino acids in the substrate binding cavity. Based on rational design, we generated two ReBAL variants, which were characterized along with the wild-type enzyme in terms of their substrate spectrum, thermostability and biocatalytic performance in the presence of different co-solvents. We found that the new enzyme variants have a significantly higher thermostability (up to 22 \ub0C increase in T50) and a different co-solvent-dependent activity. Using the most stable variant immobilized in packed-bed reactors via the SpyCatcher/SpyTag system, (R)-benzoin was synthesized from benzaldehyde over a period of seven days with a stable space-time-yield of 9.3 mmol ⋅ L-1 ⋅ d−1. Our work expands the important class of benzaldehyde lyases and therefore contributes to the development of continuous biocatalytic processes for the production of α-hydroxy ketones and APIs

Self-organizing tuple reconstruction in column-stores

Column-stores gained popularity as a promising physical de-sign alternative. Each attribute of a relation is physically stored as a separate column allowing queries to load only the required attributes. The overhead incurred is on-the-fly tuple reconstruction for multi-attribute queries. Each tu-ple reconstruction is a join of two columns based on tuple IDs, making it a significant cost component. The ultimate physical design is to have multiple presorted copies of each base table such that tuples are already appropriately orga-nized in multiple different orders across the various columns. This requires the ability to predict the workload, idle time to prepare, and infrequent updates. In this paper, we propose a novel design, partial side-ways cracking, that minimizes the tuple reconstruction cost in a self-organizing way. It achieves performance similar to using presorted data, but without requiring the heavy initial presorting step itself. Instead, it handles dynamic, unpredictable workloads with no idle time and frequent up-dates. Auxiliary dynamic data structures, called cracker maps, provide a direct mapping between pairs of attributes used together in queries for tuple reconstruction. A map is continuously physically reorganized as an integral part of query evaluation, providing faster and reduced data access for future queries. To enable flexible and self-organizing be-havior in storage-limited environments, maps are material-ized only partially as demanded by the workload. Each map is a collection of separate chunks that are individually reor-ganized, dropped or recreated as needed. We implemented partial sideways cracking in an open-source column-store. A detailed experimental analysis demonstrates that it brings significant performance benefits for multi-attribute queries

CIRQUID: complex information retrieval queries in a database

The CIRQUID project plans to design and build a DBMS that seemlessly integrates relevance-oriented querying of semi-structured data (XML) with traditional querying of this data. The project is funded by the Netherlands Organisation of Scientific Research

The Potential Impact of Heparanase Activity and Endothelial Damage in COVID-19 Disease

SARS-CoV-2 was first detected in 2019 in Wuhan, China. It has been found to be the most pathogenic virus among coronaviruses and is associated with endothelial damage resulting in respiratory failure. Determine whether heparanase and heparan sulfate fragments, biomarkers of endothelial function, can assist in the risk stratification and clinical management of critically ill COVID-19 patients admitted to the intensive care unit. We investigated 53 critically ill patients with severe COVID-19 admitted between March and April 2020 to the University Hospital RWTH Aachen. Heparanase activity and serum levels of both heparanase and heparan sulfate were measured on day one (day of diagnosis) and day three in patients with COVID-19. The patients were classified into four groups according to the severity of ARDS. When compared to baseline data (day one), heparanase activity increased and the heparan sulfate serum levels decreased with increasing severity of ARDS. The heparanase activity significantly correlated with the lactate concentration on day one (r = 0.34, p = 0.024) and on day three (r = 0.43, p = 0.006). Heparanase activity and heparan sulfate levels correlate with COVID-19 disease severity and outcome. Both biomarkers might be helpful in predicting clinical course and outcomes in COVID-19 patients

Single-Scale Natural SUSY

We consider the prospects for natural SUSY models consistent with current data. Recent constraints make the standard paradigm unnatural so we consider what could be a minimal extension consistent with what we now know. The most promising such scenarios extend the MSSM with new tree-level Higgs interactions that can lift its mass to at least 125 GeV and also allow for flavor-dependent soft terms so that the third generation squarks are lighter than current bounds on the first and second generation squarks. We argue that a common feature of almost all such models is the need for a new scale near 10 TeV, such as a scale of Higgsing or confinement of a new gauge group. We consider the question whether such a model can naturally derive from a single mass scale associated with supersymmetry breaking. Most such models simply postulate new scales, leaving their proximity to the scale of MSSM soft terms a mystery. This coincidence problem may be thought of as a mild tuning, analogous to the usual mu problem. We find that a single mass scale origin is challenging, but suggest that a more natural origin for such a new dynamical scale is the gravitino mass, m_{3/2}, in theories where the MSSM soft terms are a loop factor below m_{3/2}. As an example, we build a variant of the NMSSM where the singlet S is composite, and the strong dynamics leading to compositeness is triggered by masses of order m_{3/2} for some fields. Our focus is the Higgs sector, but our model is compatible with a light stop (with the other generation squarks heavy, or with R-parity violation or another mechanism to hide them from current searches). All the interesting low-energy mass scales, including linear terms for S playing a key role in EWSB, arise dynamically from the single scale m_{3/2}. However, numerical coefficients from RG effects and wavefunction factors in an extra dimension complicate the otherwise simple story.Comment: 32 pages, 3 figures; version accepted by JHE