Declarative process modeling in BPMN

Traditional business process modeling notations, including the standard Business Process Model and Notation (BPMN), rely on an imperative paradigm wherein the process model captures all allowed activity flows. In other words, every flow that is not specified is implicitly disallowed. In the past decade, several researchers have exposed the limitations of this paradigm in the context of business processes with high variability. As an alternative, declarative process modeling notations have been proposed (e.g., Declare). These notations allow modelers to capture constraints on the allowed activity flows, meaning that all flows are allowed provided that they do not violate the specified constraints. Recently, it has been recognized that the boundary between imperative and declarative process modeling is not crisp. Instead, mixtures of declarative and imperative process modeling styles are sometimes preferable, leading to proposals for hybrid process modeling notations. These developments raise the question of whether completely new notations are needed to support hybrid process modeling. This paper answers this question negatively. The paper presents a conservative extension of BPMN for declarative process modeling, namely BPMN-D, and shows that Declare models can be transformed into readable BPMN-D models. © Springer International Publishing Switzerland 2015

Bubbling with L2L^2-almost constant mean curvature and an Alexandrov-type theorem for crystals

A compactness theorem for volume-constrained almost-critical points of elliptic integrands is proven. The result is new even for the area functional, as almost-criticality is measured in an integral rather than in a uniform sense. Two main applications of the compactness theorem are discussed. First, we obtain a description of critical points/local minimizers of elliptic energies interacting with a confinement potential. Second, we prove an Alexandrov-type theorem for crystalline isoperimetric problems

Predictive Monitoring of Business Processes

Modern information systems that support complex business processes generally maintain significant amounts of process execution data, particularly records of events corresponding to the execution of activities (event logs). In this paper, we present an approach to analyze such event logs in order to predictively monitor business goals during business process execution. At any point during an execution of a process, the user can define business goals in the form of linear temporal logic rules. When an activity is being executed, the framework identifies input data values that are more (or less) likely to lead to the achievement of each business goal. Unlike reactive compliance monitoring approaches that detect violations only after they have occurred, our predictive monitoring approach provides early advice so that users can steer ongoing process executions towards the achievement of business goals. In other words, violations are predicted (and potentially prevented) rather than merely detected. The approach has been implemented in the ProM process mining toolset and validated on a real-life log pertaining to the treatment of cancer patients in a large hospital

The essential oil of Thymbra capitata and its application as a biocide on stone and derived surfaces

Many chemicals used nowadays for the preservation of cultural heritage pose a risk to both human health and the environment. Thus, it is desirable to find new and eco-friendly biocides that can replace the synthetic ones. In this regard, plant essential oils represent effective alternatives to synthetic substances for the preservation of historical monuments. Thymbra capitata (syn. Thymus capitatus) is a medicinal and aromatic plant growing in the Mediterranean area and endowed with important pharmacological properties related to its essential oil. Among them, the antimicrobial ones make the T. capitata essential oil an ideal candidate for industrial applications; for instance, as biocide for the inhibition and elimination of biological patinas of cyanobacteria and green algae on historical monuments. In the present work, we studied the chemical composition of the essential oil from T. capitata growing in Malta by gas chromatography-mass spectrometry (GC/MS). The major volatile component is the phenolic monoterpene carvacrol (73.2%), which is capable of damaging the cytoplasmic membrane and to interfere both in the growth curve and in the invasive capacity, though the contribution of minor components γ-terpinene and p-cymene cannot be disregarded. For the oil application on the stone surface, Pickering emulsions systems were prepared with an essential oil/water 1:3 mass ratio stabilized with kaolinite at 4 mass% in the presence of Laponite®; this allowed to limit the fast volatility of the oil and guaranteed a better application and an easier removal from the artefacts attacked by biodeteriogens both indoor and outdoor. This formulation caused the elimination of biodeteriogens from treated surfaces without residuals or films on artworks surface, and the effect was retained up to four months

Interestingness of traces in declarative process mining: The janus LTLPf Approach

Declarative process mining is the set of techniques aimed at extracting behavioural constraints from event logs. These constraints are inherently of a reactive nature, in that their activation restricts the occurrence of other activities. In this way, they are prone to the principle of ex falso quod libet: they can be satisfied even when not activated. As a consequence, constraints can be mined that are hardly interesting to users or even potentially misleading. In this paper, we build on the observation that users typically read and write temporal constraints as if-statements with an explicit indication of the activation condition. Our approach is called Janus, because it permits the specification and verification of reactive constraints that, upon activation, look forward into the future and backwards into the past of a trace. Reactive constraints are expressed using Linear-time Temporal Logic with Past on Finite Traces (LTLp f). To mine them out of event logs, we devise a time bi-directional valuation technique based on triplets of automata operating in an on-line fashion. Our solution proves efficient, being at most quadratic w.r.t. trace length, and effective in recognising interestingness of discovered constraints

Clinical Processes - The Killer Application for Constraint-Based Process Interactions?

For more than a decade, the interest in aligning information systems in a process-oriented way has been increasing. To enable operational support for business processes, the latter are usually specified in an imperative way. The resulting process models, however, tend to be too rigid to meet the flexibility demands of the actors involved. Declarative process modeling languages, in turn, provide a promising alternative in scenarios in which a high level of flexibility is demanded. In the scientific literature, declarative languages have been used for modeling rather simple processes or synthetic examples. However, to the best of our knowledge, they have not been used to model complex, real-world scenarios that comprise constraints going beyond control-flow. In this paper, we propose the use of a declarative language for modeling a sophisticated healthcare process scenario from the real world. The scenario is subject to complex temporal constraints and entails the need for coordinating the constraint-based interactions among the processes related to a patient treatment process. As demonstrated in this work, the selected real process scenario can be suitably modeled through a declarative approach.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-RMinisterio de Economía y Competitividad TIN2015-71938-RED

XMM-Newton study of 30 Dor C and a newly identified MCSNR J0536-6913 in the Large Magellanic Cloud

Aims: We present a study of the superbubble (SB) 30 Dor C and the newly identified MCSNR J0536-6913 in the LMC. Methods: All available XMM-Newton data (exposure times of 420 ks EPIC-pn, 556 ks EPIC-MOS1, 614 ks EPIC-MOS2) were used to characterise the thermal X-ray emission in the region. An analysis of the non-thermal X-rays is also presented and discussed in the context of emission mechanisms previously suggested in the literature. These data are supplemented by X-ray data from Chandra, optical data from the MCELS, and radio data from ATCA and MOST. Results: The brightest thermal emission was found to be associated with a new supernova remnant, MCSNR J0536-6913. X-ray spectral analysis of MCSNR J0536-6913 suggested an ejecta-dominated remnant with lines of O, Ne, Mg, and Si, and a total 0.3-10 keV luminosity of ~8E+34 erg/s. Based on derived ejecta abundance ratios, we determined the mass of the stellar progenitor to be either ~18 M_sun or as high as >40 M_sun, though the spectral fits were subject to assumptions (e.g., uniform temperature and well-mixed ejecta). The thermal emission from the SB exhibited enrichment by alpha-process elements, evidence for a recent core-collapse SNR interaction with the SB shell. We detected non-thermal X-ray emission throughout 30 Dor C, with the brightest regions being highly correlated with the H-alpha and radio shells. We created a non-thermal spectral energy distribution for the north-eastern shell of 30 Dor C which was best-fit with an exponentially cut-off synchrotron model. Conclusions: Thermal X-ray emission from 30 Dor C is very complex, consisting of a large scale SB emission at the eastern shell wall with the brightest emission due to MCSNR J0536-6913. The fact that the non-thermal spectral energy distribution of the SB shell was observed to roll-off is further evidence that the non-thermal X-rays from 30 Dor C are synchrotron in origin.Comment: 22 pages, 21 figures, accepted for publication in Astronomy and Astrophysic