A Tool-Supported Approach for Concurrent Execution of Heterogeneous Models

International audienceIn the software and systems modeling community, research on domain-specific modeling languages (DSMLs) is focused on providing technologies for developing languages and tools that allow domain experts to develop system solutions efficiently. Unfortunately, the current lack of support for explicitly relating concepts expressed in different DSMLs makes it very difficult for software and system engineers to reason about information spread across models describing different system aspects [4]. As a particular challenge, we investigate in this paper relationships between, possibly heterogeneous, behavioral models to support their concurrent execution. This is achieved by following a modular executable metamodeling approach for behavioral semantics understanding, reuse, variability and composability [5]. This approach supports an explicit model of concurrency (MoCC) [6] and domain-specific actions (DSA) [10] with a well-defined protocol between them (incl., mapping, feedback and callback) reified through explicit domain-specific events (DSE) [12]. The protocol is then used to infer a relevant behavioral language interface for specifying coordination patterns to be applied on conforming executable models [17]. All the tooling of the approach is gathered in the GEMOC studio, and outlined in the next section. Currently, the approach is experienced on a systems engineering language provided by Thales, named Capella 7. The goal and current state of the case study are exposed in this paper. 7 Cf. https://www.polarsys.org/capella

A Mathematical Bias

Any Mathematical framework inside which we formalize explanations limits the scope of behaviors we may consider and the type of explanations we might provide. The problem is even more acute when a model provides accurate predictions. This naturally leads us to restrict our investigation within the chosen framework, making us blind to alternatives

Weighted Scheduling of Time-Sensitive Coflows

Datacenter networks commonly facilitate the transmission of data in distributed computing frameworks through coflows, which are collections of parallel flows associated with a common task. Most of the existing research has concentrated on scheduling coflows to minimize the time required for their completion, i.e., to optimize the average dispatch rate of coflows in the network fabric. Nevertheless, modern applications often produce coflows that are specifically intended for online services and mission-crucial computational tasks, necessitating adherence to specific deadlines for their completion. In this paper, we introduce \wdcoflow,~ a new algorithm to maximize the weighted number of coflows that complete before their deadline. By combining a dynamic programming algorithm along with parallel inequalities, our heuristic solution performs at once coflow admission control and coflow prioritization, imposing a $\sigma$-order on the set of coflows. With extensive simulation, we demonstrate the effectiveness of our algorithm in improving up to $3\times$ more coflows that meet their deadline in comparison the best SoA solution, namely $\mathtt{CS\text{-}MHA}$. Furthermore, when weights are used to differentiate coflow classes, \wdcoflow~ is able to improve the admission per class up to $4\times$, while increasing the average weighted coflow admission rate.Comment: Submitted to IEEE Transactions on Cloud Computing. Parts of this work have been presented at IFIP Networking 202

Topology of communities for the collaborative recommendations to groups

International audienceMore and more systems allow user personalization and provide item recommendations, intended to fit individual user interests. In a traditional VoD system, for example, the recommendations are oriented towards a single user even though he is not watching the video alone. Hence, there is a need to have recommendations for a set of users, a group. Collaborative filtering techniques are traditionally used to make a recommendation for a single user. Usage traces or user ratings are used to deduce their profile and to select an appropriate recommendation that way. Performing recommendation for groups is considerably more difficult because the retrieval of a group's traces of usage or ratings is complicated. As the individual profile for each member of the group is usually available, the recommendation for a group can be based on these individual profiles. This paper explores this approach and is the first step of the construction of a software toolkit for computing recommendations in function of the group composition and the chosen strategies

Staphylococcal entertotoxins of the enterotoxin gene cluster (egcSEs) induce nitrous oxide- and cytokine dependent tumor cell apoptosis in a broad panel of human tumor cells

International audienceThe egcSEs comprise five genetically linked staphylococcal enterotoxins, SEG, SEI, SElM, SElN, and SElO and two pseudotoxins which constitute an operon present in up to 80% of Staphylococcus aureus isolates. A preparation containing these proteins was recently used to treat advanced lung cancer with pleural effusion. We investigated the hypothesis that egcSEs induce nitrous oxide (NO) and associated cytokine production and that these agents may be involved in tumoricidal effects against a broad panel of clinically relevant human tumor cells. Preliminary studies showed that egcSEs and SEA activated T cells (range: 11-25%) in a concentration dependent manner. Peripheral blood mononuclear cells (PBMCs) stimulated with equimolar quantities of egcSEs expressed NO synthase and generated robust levels of nitrite (range: 200-250 μM), a breakdown product of NO; this reaction was inhibited by NG-monomethyl-L-arginine (L-NMMA) (0.3 mM), an NO synthase antagonist. Cell free supernatants (CSFs) of all egcSE-stimulated PBMCs were also equally effective in inducing concentration dependent tumor cell apoptosis in a broad panel of human tumor cells. The latter effect was due in part to the generation of NO and TNF-α since it was significantly abolished by L-NMMA, anti-TNF-α antibodies, respectively, and a combination thereof. A hierarchy of tumor cell sensitivity to these CFSs was as follows: lung carcinoma > osteogenic sarcoma > melanoma > breast carcinoma >neuroblastoma. Notably, SEG induced robust activation of NO/TNFα-dependent tumor cell apoptosis comparable to the other egcSEs and SEA despite TNF-α and IFN-γ levels that were 2 and 8 fold lower, respectively, than the other egcSEs and SEA. Thus, egcSEs produced by S. aureus induce NO synthase and the increased NO formation together with TNF-α appear to contribute to egcSE-mediated apoptosis against a broad panel of human tumor cells

Domain Globalization: Using Languages to Support Technical and Social Coordination

International audienceWhen a project is realized in a globalized environment, multiple stakeholders from different organizations work on the same system. Depending on the stakeholders and their organizations, various (possibly overlapping) concerns are raised in the development of the system. In this context a Domain Specific Language (DSL) supports the work of a group of stakeholders who are responsible for addressing a specific set of concerns. This chapter identifies the open challenges arising from the coordination of globalized domain-specific languages. We identify two types of coordination: technical coordination and social coordination. After presenting an overview of the current state of the art, we discuss first the open challenges arising from the composition of multiple DSLs, and then the open challenges associated to the collaboration in a globalized environment

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

Peer reviewe

An embedding technique to determine ττ backgrounds in proton-proton collision data

An embedding technique is presented to estimate standard model tau tau backgrounds from data with minimal simulation input. In the data, the muons are removed from reconstructed mu mu events and replaced with simulated tau leptons with the same kinematic properties. In this way, a set of hybrid events is obtained that does not rely on simulation except for the decay of the tau leptons. The challenges in describing the underlying event or the production of associated jets in the simulation are avoided. The technique described in this paper was developed for CMS. Its validation and the inherent uncertainties are also discussed. The demonstration of the performance of the technique is based on a sample of proton-proton collisions collected by CMS in 2017 at root s = 13 TeV corresponding to an integrated luminosity of 41.5 fb(-1).Peer reviewe