PcrG protects the two long helical oligomerization domains of PcrV, by an interaction mediated by the intramolecular coiled-coil region of PcrG

PcrV is a hydrophilic translocator of type three secretion system (TTSS) and a structural component of the functional translocon. C-terminal helix of PcrV is essential for its oligomerization at the needle tip. Conformational changes within PcrV regulate the effector translocation. PcrG is a cytoplasmic regulator of TTSS and forms a high affinity complex with PcrV. C-terminal residues of PcrG control the effector secretion

A Formal Account of the Open Provenance Model

On the Web, where resources such as documents and data are published, shared, transformed, and republished, provenance is a crucial piece of metadata that would allow users to place their trust in the resources they access. The Open Provenance Model (OPM) is a community data model for provenance that is designed to facilitate the meaningful interchange of provenance information between systems. Underpinning OPM is a notion of directed graph, where nodes represent data products and processes involved in past computations, and edges represent dependencies between them; it is complemented by graphical inference rules allowing new dependencies to be derived. Until now, however, the OPM model was a purely syntactical endeavor. The present paper extends OPM graphs with an explicit distinction between precise and imprecise edges. Then a formal semantics for the thus enriched OPM graphs is proposed, by viewing OPM graphs as temporal theories on the temporal events represented in the graph. The original OPM inference rules are scrutinized in view of the semantics and found to be sound but incomplete. An extended set of graphical rules is provided and proved to be complete for inference. The paper concludes with applications of the formal semantics to inferencing in OPM graphs, operators on OPM graphs, and a formal notion of refinement among OPM graphs

Golden Trail: Retrieving the Data History that Matters from a Comprehensive Provenance Repository

Experimental science can be thought of as the exploration of a large research space, in search of a few valuable results. While it is this “Golden Data” that gets published, the history of the exploration is often as valuable to the scientists as some of its outcomes. We envision an e-research infrastructure that is capable of systematically and automatically recording such history – an assumption that holds today for a number of workflow management systems routinely used in e-science. In keeping with our gold rush metaphor, the provenance of a valuable result is a “Golden Trail”. Logically, this represents a detailed account of how the Golden Data was arrived at, and technically it is a sub-graph in the much larger graph of provenance traces that collectively tell the story of the entire research (or of some of it).In this paper we describe a model and architecture for a repository dedicated to storing provenance traces and selectively retrieving Golden Trails from it. As traces from multiple experiments over long periods of time are accommodated, the trails may be sub-graphs of one trace, or they may be the logical representation of a virtual experiment obtained by joining together traces that share common data.The project has been carried out within the Provenance Working Group of the Data Observation Network for Earth (DataONE) NSF project. Ultimately, our longer-term plan is to integrate the provenance repository into the data preservation architecture currently being developed by DataONE

The PBase Scientific Workflow Provenance Repository

Scientific workflows and their supporting systems are becoming increasingly popular for compute-intensive and data-intensive scientific experiments. The advantages scientific workflows offer include rapid and easy workflow design, software and data reuse, scalable execution, sharing and collaboration, and other advantages that altogether facilitate “reproducible science”. In this context, provenance – information about the origin, context, derivation, ownership, or history of some artifact – plays a key role, since scientists are interested in examining and auditing the results of scientific experiments. However, in order to perform such analyses on scientific results as part of extended research collaborations, an adequate environment and tools are required. Concretely, the need arises for a repository that will facilitate the sharing of scientific workflows and their associated execution traces in an interoperable manner, also enabling querying and visualization. Furthermore, such functionality should be supported while taking performance and scalability into account. With this purpose in mind, we introduce PBase: a scientific workflow provenance repository implementing the ProvONE proposed standard, which extends the emerging W3C PROV standard for provenance data with workflow specific concepts. PBase is built on the Neo4j graph database, thus offering capabilities such as declarative and efficient querying. Our experiences demonstrate the power gained by supporting various types of queries for provenance data. In addition, PBase is equipped with a user friendly interface tailored for the visualization of scientific workflow provenance data, making the specification of queries and the interpretation of their results easier and more effective

YesWorkflow:A User-Oriented, Language-Independent Tool for Recovering Workflow Information from Scripts

Scientific workflow management systems offer features for composing complex computational pipelines from modular building blocks, for executing the resulting automated workflows, and for recording the provenance of data products resulting from workflow runs. Despite the advantages such features provide, many automated workflows continue to be implemented and executed outside of scientific workflow systems due to the convenience and familiarity of scripting languages (such as Perl, Python, R, and MATLAB), and to the high productivity many scientists experience when using these languages. YesWorkflow is a set of software tools that aim to provide such users of scripting languages with many of the benefits of scientific workflow systems. YesWorkflow requires neither the use of a workflow engine nor the overhead of adapting code to run effectively in such a system. Instead, YesWorkflow enables scientists to annotate existing scripts with special comments that reveal the computational modules and dataflows otherwise implicit in these scripts. YesWorkflow tools extract and analyze these comments, represent the scripts in terms of entities based on the typical scientific workflow model, and provide graphical renderings of this workflow-like view of the scripts. Future versions of YesWorkflow also will allow the prospective provenance of the data products of these scripts to be queried in ways similar to those available to users of scientific workflow systems

Dynamics of Hot QCD Matter -- Current Status and Developments

The discovery and characterization of hot and dense QCD matter, known as Quark Gluon Plasma (QGP), remains the most international collaborative effort and synergy between theorists and experimentalists in modern nuclear physics to date. The experimentalists around the world not only collect an unprecedented amount of data in heavy-ion collisions, at Relativistic Heavy Ion Collider (RHIC), at Brookhaven National Laboratory (BNL) in New York, USA, and the Large Hadron Collider (LHC), at CERN in Geneva, Switzerland but also analyze these data to unravel the mystery of this new phase of matter that filled a few microseconds old universe, just after the Big Bang. In the meantime, advancements in theoretical works and computing capability extend our wisdom about the hot-dense QCD matter and its dynamics through mathematical equations. The exchange of ideas between experimentalists and theoreticians is crucial for the progress of our knowledge. The motivation of this first conference named "HOT QCD Matter 2022" is to bring the community together to have a discourse on this topic. In this article, there are 36 sections discussing various topics in the field of relativistic heavy-ion collisions and related phenomena that cover a snapshot of the current experimental observations and theoretical progress. This article begins with the theoretical overview of relativistic spin-hydrodynamics in the presence of the external magnetic field, followed by the Lattice QCD results on heavy quarks in QGP, and finally, it ends with an overview of experiment results.Comment: Compilation of the contributions (148 pages) as presented in the `Hot QCD Matter 2022 conference', held from May 12 to 14, 2022, jointly organized by IIT Goa & Goa University, Goa, Indi

D-PROV: Extending the PROV Provenance Model with Workflow Structure

This paper presents an extension to the W3C PROV1 provenance model, aimed at representing process structure. Although the modelling of process structure is out of the scope of the PROV specification, it is beneficial when capturing and analyzing the provenance of data that is produced by programs or other formally encoded processes. In the paper, we motivate the need for such and extended model in the context of an ongoing large data federation and preservation project, DataONE2, where provenance traces of scientific workflow runs are captured and stored alongside the data products. We introduce new provenance relations for modelling process structure along with their usage patterns, and present sample queries that demonstrate their benefit