On enabling integrated process compliance with semantic constraints in process management systems

Key to broad use of process management systems (PrMS) in practice is their ability to foster and ease the implementation, execution, monitoring, and adaptation of business processes while still being able to ensure robust and error-free process enactment. To meet these demands a variety of mechanisms has been developed to prevent errors at the structural level (e.g., deadlocks). In many application domains, however, processes often have to comply with business level rules and policies (i.e., semantic constraints) as well. Hence, to ensure error-free executions at the semantic level, PrMS need certain control mechanisms for validating and ensuring the compliance with semantic constraints. In this paper, we discuss fundamental requirements for a comprehensive support of semantic constraints in PrMS. Moreover, we provide a survey on existing approaches and discuss to what extent they are able to meet the requirements and which challenges still have to be tackled. In order to tackle the particular challenge of providing integrated compliance support over the process lifecycle, we introduce the SeaFlows framework. The framework introduces a behavioural level view on processes which serves a conceptual process representation for constraint specification approaches. Further, it provides general compliance criteria for static compliance validation but also for dealing with process changes. Altogether, the SeaFlows framework can serve as formal basis for realizing integrated support of semantic constraints in PrMS.     

An illusion of memory: False recognition influenced by unconscious perception.

The results of two experiments showed that an illusion of memory can be produced by unconscious perception. In a first phase of those experiments, a long list of words was presented for study. For the test of recognition memory given in the second phase of each experiment, presentation of a "context" word preceded that of most recognition test words. Ss were to judge whether or not the test words had been presented during the earlier study phase of the experiment. Effects of a context word on this recognition memory decision were opposite when Ss were aware vs. unaware of its presentation. For example, as compared to a condition in which no context word was presented, the probability of false recognition was increased when Ss were unaware but decreased when Ss were aware of the presentation of a context word that matched the recognition test word. Results are discussed in terms of unconscious influences on an attribution process. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Novel Volume-Stable Collagen Matrix Induces Changes in the Behavior of Primary Human Oral Fibroblasts,Periodontal Ligament,and Endothelial Cells

The aim of the present study was to investigate the influence of a novel volume-stable collagen matrix (vCM) on early wound healing events including cellular migration and adhesion, protein adsorption and release, and the dynamics of the hemostatic system. For this purpose, we utilized transwell migration and crystal violet adhesion assays, ELISAs for quantification of adsorbed and released from the matrix growth factors, and qRT-PCR for quantification of gene expression in cells grown on the matrix. Our results demonstrated that primary human oral fibroblasts, periodontal ligament, and endothelial cells exhibited increased migration toward vCM compared to control cells that migrated in the absence of the matrix. Cellular adhesive properties on vCM were significantly increased compared to controls. Growth factors TGF-β1, PDGF-BB, FGF-2, and GDF-5 were adsorbed on vCM with great efficiency and continuously delivered in the medium after an initial burst release within hours. We observed statistically significant upregulation of genes encoding the antifibrinolytic thrombomodulin, plasminogen activator inhibitor type 1, thrombospondin 1, and thromboplastin, as well as strong downregulation of genes encoding the profibrinolytic tissue plasminogen activator, urokinase-type plasminogen activator, its receptor, and the matrix metalloproteinase 14 in cells grown on vCM. As a general trend, the stimulatory effect of the vCM on the expression of antifibrinolytic genes was synergistically enhanced by TGF-β1, PDGF-BB, or FGF-2, whereas the strong inhibitory effect of the vCM on the expression of profibrinolytic genes was reversed by PDGF-BB, FGF-2, or GDF-5. Taken together, our data strongly support the effect of the novel vCM on fibrin clot stabilization and coagulation/fibrinolysis equilibrium, thus facilitating progression to the next stages of the soft tissue healing process.     

The Effects of Insulin-Like Growth Factor I and BTP-2 on Acute Lung Injury

Acute lung injury (ALI) afflicts approximately 200,000 patients annually and has a 40% mortality rate. The COVID-19 pandemic has massively increased the rate of ALI incidence. The pathogenesis of ALI involves tissue damage from invading microbes and, in severe cases, the overexpression of inflammatory cytokines such as tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β). This study aimed to develop a therapy to normalize the excess production of inflammatory cytokines and promote tissue repair in the lipopolysaccharide (LPS)-induced ALI. Based on our previous studies, we tested the insulin-like growth factor I (IGF-I) and BTP-2 therapies. IGF-I was selected, because we and others have shown that elevated inflammatory cytokines suppress the expression of growth hormone receptors in the liver, leading to a decrease in the circulating IGF-I. IGF-I is a growth factor that increases vascular protection, enhances tissue repair, and decreases pro-inflammatory cytokines. It is also required to produce anti-inflammatory 1,25-dihydroxyvitamin D. BTP-2, an inhibitor of cytosolic calcium, was used to suppress the LPS-induced increase in cytosolic calcium, which otherwise leads to an increase in proinflammatory cytokines. We showed that LPS increased the expression of the primary inflammatory mediators such as toll like receptor-4 (TLR-4), IL-1β, interleukin-17 (IL-17), TNF-α, and interferon-γ (IFN-γ), which were normalized by the IGF-I + BTP-2 dual therapy in the lungs, along with improved vascular gene expression markers. The histologic lung injury score was markedly elevated by LPS and reduced to normal by the combination therapy. In conclusion, the LPS-induced increases in inflammatory cytokines, vascular injuries, and lung injuries were all improved by IGF-I + BTP-2 combination therapy.     

An SDP Primal-Dual Algorithm for Approximating the Lovász-Theta Function

The Lovász ?-function (Lovász in IEEE Trans. Inf. Theory, 25:1–7, 1979) of a graph G=(V,E) can be defined as the maximum of the sum of the entries of a positive semidefinite matrix X, whose trace Tr(X) equals 1, and X _ij =0 whenever {i,j}∈E. This function appears as a subroutine for many algorithms for graph problems such as maximum independent set and maximum clique. We apply Arora and Kale’s primal-dual method for SDP to design an algorithm to approximate the ?-function within an additive error of δ>0, which runs in time $O(\frac{\vartheta ^{2} n^{2}}{\delta^{2}} \log n \cdot M_{e})$ , where ?=?(G) and M _e =O(n ³) is the time for a matrix exponentiation operation. It follows that for perfect graphs G, our primal-dual method computes ?(G) exactly in time O(? ² n ⁵logn). Moreover, our techniques generalize to the weighted Lovász ?-function, and both the maximum independent set weight and the maximum clique weight for vertex weighted perfect graphs can be approximated within a factor of (1+?) in time O(? ^?2 n ⁵logn).     

A Comparison of the Levels of Lutein and Zeaxanthin in Corn Germ Oil,Corn Fiber Oil and Corn Kernel Oil

All commercial corn oil is obtained by pressing corn germ and/or extracting the germ with hexane. In the current study, six types of corn oil were prepared by extracting corn germ, corn fiber and ground corn, each with hexane or with ethanol. The levels of lutein, zeaxanthin and other carotenoids were quantitatively analyzed in the six corn oils. The levels of lutein + zeaxanthin in the oil ranged from 2.3 μg/g for hexane-extracted corn germ oil to 220.9 μg/g for ethanol-extracted ground corn oil. These results indicate that a diet that includes 30 g (~2 tbsp) per day of the unrefined corn oil obtained by extracting ground corn with ethanol would provide ~6 mg of lutein + zeaxanthin, the daily dosage that is currently considered to be necessary to slow the progression of age-related macular degeneration. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.     

Toward seed-insensitive solutions to local community detection

Local community detection aims at finding a community structure starting from a seed which is a given vertex in a network without global information, such as online social networks that are too large and dynamic to ever be known fully. Nonetheless, the existing approaches to local community detection are usually sensitive to seeds, i.e., some seeds may lead to missing of some true communities. In this paper, we present a seed-insensitive method called GMAC and its variation iGMAC for local community detection. They estimate the similarity among vertices by investigating vertices’ neighborhoods, and reveal a local community by maximizing its internal similarity and minimizing its external similarity simultaneously. Extensive experimental results on both synthetic and real-world data sets verify the effectiveness of our algorithms.     

Summarizing high-level scene behavior

We present several novel techniques to summarize the high-level behavior in surveillance video. Our proposed methods can employ either optical flow or trajectories as input, and incorporate spatial and temporal information together, which improve upon existing approaches for summarization. To begin, we extract common pathway regions by performing graph-based clustering on similarity matrices describing the relationships between location/orientation states. We then employ the activities along the pathway regions to extract the aggregate behavioral patterns throughout scenes. We show how our summarization methods can be applied to detect anomalies, retrieve video clips of interest, and generate adaptive-speed summary videos. We examine our approaches on multiple complex urban scenes and present experimental results.     

Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Unorganized traffic is a generalized form of travel wherein vehicles do not adhere to any predefined lanes and can travel in-between lanes. Such travel is visible in a number of countries e.g. India, wherein it enables a higher traffic bandwidth, more overtaking and more efficient travel. These advantages are visible when the vehicles vary considerably in size and speed, in the absence of which the predefined lanes are near-optimal. Motion planning for multiple autonomous vehicles in unorganized traffic deals with deciding on the manner in which every vehicle travels, ensuring no collision either with each other or with static obstacles. In this paper the notion of predefined lanes is generalized to model unorganized travel for the purpose of planning vehicles travel. A uniform cost search is used for finding the optimal motion strategy of a vehicle, amidst the known travel plans of the other vehicles. The aim is to maximize the separation between the vehicles and static obstacles. The search is responsible for defining an optimal lane distribution among vehicles in the planning scenario. Clothoid curves are used for maintaining a lane or changing lanes. Experiments are performed by simulation over a set of challenging scenarios with a complex grid of obstacles. Additionally behaviours of overtaking, waiting for a vehicle to cross and following another vehicle are exhibited.