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Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during the execution of a process. These event data can be used to analyze the process using process mining techniques to discover the real process, measure conformance to a given process model, or to enhance existing models with performance information. Mapping the produced events to activities of a given process model is essential for conformance checking, annotation and understanding of process mining results. In order to accomplish this mapping with low manual effort, we developed a semi-automatic approach that maps events to activities using insights from behavioral analysis and label analysis. The approach extracts Declare constraints from both the log and the model to build matching constraints to efficiently reduce the number of possible mappings. These mappings are further reduced using techniques from natural language processing, which allow for a matching based on labels and external knowledge sources. The evaluation with synthetic and real-life data demonstrates the effectiveness of the approach and its robustness toward non-conforming execution logs.
The new N-heterocyclic carbene (NHC) complex [PdCl2{(CN)(2)IMes}(PPh3)] (2) ({(CN)(2)IMes}: 4,5-dicyano-1,3-dimesitylimidazol-2-ylidene) and the NHC palladacycle [PdCl(dmba){(CN)(2)IMes}] (3) (dmba: N,N-dimethylbenzylamine) have been synthesized by thermolysis of 4,5-dicyano-1,3-dimesityl-2-(pentafluorophenyl) imidazoline (1) in the presence of suitable palladium(II) precursors. The acyclic complex 2 was formed by ligand exchange using the mononuclear precursor [PdCl2(PPh3)(2)] and the palladacycle 3 was formed by cleavage of the dinuclear chloro-bridged precursor [Pd(mu-Cl)(dmba)](2). The new NHC precursor 1-benzyl-4,5-dicyano-2-(pentafluorophenyl)-3-picolylimidazoline (5) was formed by condensation of pentafluorobenzaldehyde with N-benzyl-N'-picolyldiaminomaleonitrile (4). The NHC palladacycle [PdCl2{(CN)(2)IBzPic}] (6) ({(CN)(2)IBzPic}: 1-benzyl-4,5-dicyano-3-picolylimidazol-2-ylidene) was prepared by in situ thermolysis of 5 in the presence of [PdCl2(PhCN)(2)]. The three palladium(II) complexes were characterized by NMR and IR spectroscopy, mass spectrometry and elemental analysis. In addition, the molecular structures of 2 and 3 were determined by X-ray diffraction. The pi-acidity of (CN)(2)IBzPic was compared with (CN)(2)IMes and perviously reported pi-acidic imidazol-2-ylidenes by NBO analysis. The Mizoroki-Heck (MH) reactions of various aryl halides with n-butyl acrylate were performed in the presence of complexes 2, 3 and 6. The new precatalysts showed high activity in the MH reactions giving good-to-excellent product yields with 0.1 mol-% pre-catalyst. The nature of the catalytically active species of 2, 3 and 6 was investigated by poisoning experiments with mercury and transmission electron microscopy. It was found that palladium nanoparticles formed from the precatalysts were involved in the catalytic process.
While the maturity of process mining algorithms increases and more process mining tools enter the market, process mining projects still face the problem of different levels of abstraction when comparing events with modeled business activities. Current approaches for event log abstraction try to abstract from the events in an automated way that does not capture the required domain knowledge to fit business activities. This can lead to misinterpretation of discovered process models. We developed an approach that aims to abstract an event log to the same abstraction level that is needed by the business. We use domain knowledge extracted from existing process documentation to semi-automatically match events and activities. Our abstraction approach is able to deal with n:m relations between events and activities and also supports concurrency. We evaluated our approach in two case studies with a German IT outsourcing company. (C) 2014 Elsevier Ltd. All rights reserved.
Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during process execution. Aiming at a better process understanding and improvement, this event data can be used to analyze processes using process mining techniques. Process models can be automatically discovered and the execution can be checked for conformance to specified behavior. Moreover, existing process models can be enhanced and annotated with valuable information, for example for performance analysis. While the maturity of process mining algorithms is increasing and more tools are entering the market, process mining projects still face the problem of different levels of abstraction when comparing events with modeled business activities. Mapping the recorded events to activities of a given process model is essential for conformance checking, annotation and understanding of process discovery results. Current approaches try to abstract from events in an automated way that does not capture the required domain knowledge to fit business activities. Such techniques can be a good way to quickly reduce complexity in process discovery. Yet, they fail to enable techniques like conformance checking or model annotation, and potentially create misleading process discovery results by not using the known business terminology.
In this thesis, we develop approaches that abstract an event log to the same level that is needed by the business. Typically, this abstraction level is defined by a given process model. Thus, the goal of this thesis is to match events from an event log to activities in a given process model. To accomplish this goal, behavioral and linguistic aspects of process models and event logs as well as domain knowledge captured in existing process documentation are taken into account to build semiautomatic matching approaches. The approaches establish a pre--processing for every available process mining technique that produces or annotates a process model, thereby reducing the manual effort for process analysts. While each of the presented approaches can be used in isolation, we also introduce a general framework for the integration of different matching approaches.
The approaches have been evaluated in case studies with industry and using a large industry process model collection and simulated event logs. The evaluation demonstrates the effectiveness and efficiency of the approaches and their robustness towards nonconforming execution logs.
Background
In cystic fibrosis (CF), acute respiratory exacerbations critically enhance pulmonary destruction. Since these mainly occur outside regular appointments, they remain unexplored. We previously elaborated a protocol for home-based upper airway (UAW) sampling obtaining nasal-lavage fluid (NLF), which, in contrast to sputum, does not require immediate processing. The aim of this study was to compare UAW inflammation and pathogen colonization during stable phases and exacerbations in CF patients and healthy controls.
Methods
Initially, we obtained NLF by rinsing 10 ml of isotonic saline/nostril during stable phases. During exacerbations, subjects regularly collected NLF at home. CF patients directly submitted one aliquot for microbiological cultures. The remaining samples were immediately frozen until transfer on ice to our clinic, where PCR analyses were performed and interleukin (IL)-1 beta/IL-6/IL-8, neutrophil elastase (NE), matrix metalloproteinase (MMP)-9, and tissue inhibitor of metalloproteinase (TIMP)-1 were assessed.
Results
Altogether, 49 CF patients and 38 healthy controls (HCs) completed the study, and 214 NLF samples were analyzed. Of the 49 CF patients, 20 were at least intermittently colonized with P. aeruginosa and received azithromycin and/or inhaled antibiotics as standard therapy. At baseline, IL-6 and IL-8 tended to be elevated in CF compared to controls. During infection, inflammatory mediators increased in both cohorts, reaching significance only for IL-6 in controls (p=0.047). Inflammatory responses tended to be higher in controls [1.6-fold (NE) to 4.4-fold (MMP-9)], while in CF, mediators increased only moderately [1.2-1.5-fold (IL-6/IL-8/NE/TIMP-1/MMP-9)]. Patients receiving inhalative antibiotics or azithromycin (n=20 and n=15, respectively) revealed lower levels of IL-1 beta/IL-6/IL-8 and NE during exacerbation compared to CF patients not receiving those antibiotics. In addition, CF patients receiving azithromycin showed MMP-9 levels significantly lower than CF patients not receiving azithromycin at stable phase and exacerbation. Altogether, rhinoviruses were the most frequently detected virus, detected at least once in n=24 (49.0%) of the 49 included pwCF and in n=26 (68.4%) of the 38 healthy controls over the 13-month duration of the study. Remarkably, during exacerbation, rhinovirus detection rates were significantly higher in the HC group compared to those in CF patients (65.8% vs. 22.4%; p<0.0001).
Conclusion
Non-invasive and partially home-based UAW sampling opens new windows for the assessment of inflammation and pathogen colonization in the unified airway system.