An epistemological foundation of conceptual modeling

In a business environment, making the right decisions is vital for the success of a company. Making right decisions is inevitably bound to the availability and provision of relevant information. Information systems are supposed to be able to provide this information in an efficient way. Thus, within information systems development a detailed analysis of information supply and information demands has to prevail. Based on Szyperski’s information set and subset-model we will give an epistemological foundation of information modeling in general and show, why conceptual modeling in particular is capable of developing effective and efficient information systems. Furthermore, we derive conceptual modeling requirements based on our findings.

An optimized online secondary path modeling method for single-channel feedback ANC systems

This paper proposes a new method for online secondary path modeling in feedback active noise control (ANC) systems. In practical cases, the secondary path is usually time varying. For these cases, online modeling of secondary path is required to ensure convergence of the system. In literature the secondary path estimation is usually performed offline, prior to online modeling, where in the proposed system there is no need for using offline estimation. The proposed method consists of two steps: a noise controller which is based on an FxLMS algorithm, and a variable step size (VSS) LMS algorithm which is used to adapt the modeling filter with the secondary path. In order to increase performance of the algorithm in a faster convergence and accurate performance, we stop the VSS-LMS algorithm at the optimum point. The results of computer simulation shown in this paper indicate effectiveness of the proposed method.

A potential role for lamellar insulin-like growth factor-1 receptor in the pathogenesis of hyperinsulinaemic laminitis

The reason why a sustained high concentration of insulin induces laminitis in horses remains unclear. Cell proliferation occurs in the lamellae during insulin-induced laminitis and in other species high concentrations of insulin can activate receptors for the powerful cell mitogen, insulin-like growth factor (IGF)-1. The first aim of this study was to determine if IGF-1 receptors (IGF-1R) are activated in the hoof during insulin-induced laminitis. Gene expression for IGF-1R and the insulin receptor (InsR) was measured using qRT-PCR, in lamellar tissue from control horses and from horses undergoing a prolonged euglycaemic, hyperinsulinaemic clamp (p-EHC), during the mid-developmental (24 h) and acute (46 h) phases of insulin-induced laminitis. Gene expression for both receptors was decreased 13–32-fold (P < 0.05) at both time-points in the insulin-treated horses. A second aim was to determine if the down-regulation of the receptor genes could be accounted for by an increase in circulating IGF-1. Serum IGF-1 was measured at 0, 10, 25 and 46 h post-treatment in horses given a p-EHC for approximately 46 h, and in matched controls administered a balanced, electrolyte solution. There was no increase in serum IGF-1 concentrations during the p-EHC, consistent with down-regulation of both receptors by insulin. Stimulation of the IGF-1R by insulin may lead to inappropriate lamellar epidermal cell proliferation and lamellar weakening, a potential mechanism for hyperinsulinaemic laminitis. Targeting this receptor may provide insights into the pathogenesis or identify a novel therapy for hyperinsulinaemic laminitis.

Integrating crowd-behavior modeling into military simulation using game technology

Crowds of noncombatants play a large and increasingly recognized role in modern military operations and often create substantial difficulties for the combatant forces involved. However, realistic models of crowds are essentially absent from current military simulations. To address this problem, the authors are developing a crowd simulation capable of generating crowds of noncombatant civilians that exhibit a variety of realistic individual and group behaviors at differing levels of fidelity. The crowd simulation is interoperable with existing military simulations using a standard, distributed simulation architecture. Commercial game technology is used in the crowd simulation to model both urban terrain and the physical behaviors of the human characters that make up the crowd. The objective of this article is to present the design and development process of a simulation that integrates commercially available game technology with current military simulations to generate realistic and believable crowd behavior.

Changes in neutrophil surface receptor expression, degranulation, and respiratory burst activity after moderate- and high-intensity exercise

Intense exercise stimulates the systemic release of a variety of factors that alter neutrophil surface receptor expression and functional activity. These alterations may influence resistance to infection after intense exercise. The aim of this study was to examine the influence of exercise intensity on neutrophil receptor expression, degranulation (measured by plasma and intracellular myeloperoxidase concentrations), and respiratory burst activity. Ten well-trained male runners ran on a treadmill for 60 min at 60% [moderate-intensity exercise (MI)] and 85% maximal oxygen consumption [high-intensity exercise (HI)]. Blood was drawn immediately before and after exercise and at 1 h postexercise. Immediately after HI, the expression of the neutrophil receptor CD16 was significantly below preexercise values (P < 0.01), whereas MI significantly reduced CD35 expression below preexercise values (P < 0.05). One hour after exercise at both intensities, there was a significant decline in CD11b expression (P < 0.05) and a further decrease in CD16 expression compared with preexercise values (P < 0.01). CD16 expression was lower 1 h after HI than 1 h after MI (P < 0.01). Immediately after HI, intracellular myeloperoxidase concentration was less than preexercise values (P < 0.01), whereas plasma myeloperoxidase concentration was greater (P < 0.01), indicating that HI stimulated neutrophil degranulation. Plasma myeloperoxidase concentration was higher immediately after HI than after MI (P < 0.01). Neutrophil respiratory burst activity increased after HI (P < 0.01). In summary, both MI and HI reduced neutrophil surface receptor expression. Although CD16 expression was reduced to a greater extent after HI, this reduction did not impair neutrophil degranulation and respiratory burst activity.

First steps towards modeling a multi-scale Earth system

Recent advances in computational geodynamics are applied to explore the link between Earth’s heat, its chemistry and its mechanical behavior. Computational thermal-mechanical solutions are now allowing us to understand Earth patterns by solving the basic physics of heat transfer. This approach is currently used to solve basic convection patterns of terrestrial planets. Applying the same methodology to smaller scales delivers promising similarities between observed and predicted structures which are often the site of mineral deposits. The new approach involves a fully coupled solution to the energy, momentum and continuity equations of the system at all scales, allowing the prediction of fractures, shear zones and other typical geological patterns out of a randomly perturbed initial state. The results of this approach are linking a global geodynamic mechanical framework over regional-scale mineral deposits down to the underlying micro-scale processes. Ongoing work includes the challenge of incorporating chemistry into the formulation.

How collaborative technology supports cognitive processes in collaborative process modeling : a capabilities-gains-outcome model

We examine which capabilities technologies provide to support collaborative process modeling. We develop a model that explains how technology capabilities impact cognitive group processes, and how they lead to improved modeling outcomes and positive technology beliefs. We test this model through a free simulation experiment of collaborative process modelers structured around a set of modeling tasks. With our study, we provide an understanding of the process of collaborative process modeling, and detail implications for research and guidelines for the practical design of collaborative process modeling.

Construct Redundancy in Process Modeling Grammars: Improving the Explanatory Power of Ontological Analysis

Conceptual modelling supports developers and users of information systems in areas of documentation, analysis or system redesign. The ongoing interest in the modelling of business processes has led to a variety of different grammars, raising the question of the quality of these grammars for modelling. An established way of evaluating the quality of a modelling grammar is by means of an ontological analysis, which can determine the extent to which grammars contain construct deficit, overload, excess or redundancy. While several studies have shown the relevance of most of these criteria, predictions about construct redundancy have yielded inconsistent results in the past, with some studies suggesting that redundancy may even be beneficial for modelling in practice. In this paper we seek to contribute to clarifying the concept of construct redundancy by introducing a revision to the ontological analysis method. Based on the concept of inheritance we propose an approach that distinguishes between specialized and distinct construct redundancy. We demonstrate the potential explanatory power of the revised method by reviewing and clarifying previous results found in the literature.

Deposition of hydrocarbon molecules on diamond (001) surfaces : atomic scale modeling

The impact induced chemisorption of hydrocarbon molecules (CH3 and CH2) on H-terminated diamond (001)-(2x1) surface was investigated by molecular dynamics simulation using the many-body Brenner potential. The deposition dynamics of the CH3 radical at impact energies of 0.1-50 eV per molecule was studied and the energy threshold for chemisorption was calculated. The impact-induced decomposition of hydrogen atoms and the dimer opening mechanism on the surface was investigated. Furthermore, the probability for dimer opening event induced by chemisorption of CH, was simulated by randomly varying the impact position as well as the orientation of the molecule relative to the surface. Finally, the energetic hydrocarbons were modeled, slowing down one after the other to simulate the initial fabrication of diamond-like carbon (DLC) films. The structure characteristic in synthesized films with different hydrogen flux was studied. Our results indicate that CH3, CH2 and H are highly reactive and important species in diamond growth. Especially, the fraction of C-atoms in the film having sp(3) hybridization will be enhanced in the presence of H atoms, which is in good agreement with experimental observations. (C) 2002 Elsevier Science B.V. All rights reserved.

The benefit of modeling jumps in realized volatility for risk prediction : evidence from Chinese mainland stocks

Recent literature has focused on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.

Computer modeling of diffusion in biological tissues

Molecular-level computer simulations of restricted water diffusion can be used to develop models for relating diffusion tensor imaging measurements of anisotropic tissue to microstructural tissue characteristics. The diffusion tensors resulting from these simulations can then be analyzed in terms of their relationship to the structural anisotropy of the model used. As the translational motion of water molecules is essentially random, their dynamics can be effectively simulated using computers. In addition to modeling water dynamics and water-tissue interactions, the simulation software of the present study was developed to automatically generate collagen fiber networks from user-defined parameters. This flexibility provides the opportunity for further investigations of the relationship between the diffusion tensor of water and morphologically different models representing different anisotropic tissues.

Business process variability modeling : A survey

It is common for organizations to maintain multiple variants of a given business process, such as multiple sales processes for different products or multiple bookkeeping processes for different countries. Conventional business process modeling languages do not explicitly support the representation of such families of process variants. This gap triggered significant research efforts over the past decade leading to an array of approaches to business process variability modeling. This survey examines existing approaches in this field based on a common set of criteria and illustrates their key concepts using a running example. The analysis shows that existing approaches are characterized by the fact that they extend a conventional process mod- eling language with constructs that make it able to capture customizable process models. A customizable process model represents a family of process variants in a way that each variant can be derived by adding or deleting fragments according to configuration parameters or according to a domain model. The survey puts into evidence an abundance of customizable process modeling languages, embodying a diverse set of con- structs. In contrast, there is comparatively little tool support for analyzing and constructing customizable process models, as well as a scarcity of empirical evaluations of languages in the field.

Modeling obligations with event-calculus

Time plays an important role in norms. In this paper we start from our previously proposed classification of obligations, and point out some shortcomings of Event Calculus (EC) to represent obligations. We proposed an extension of EC that avoids such shortcomings and we show how to use it to model the various types of obligations.

Association study of the calcitonin gene-related polypeptide-alpha (CALCA) and the receptor activity modifying 1 (RAMP1) genes with migraine

Migraine is a common neurovascular brain disorder characterised by recurrent attacks of severe headache that may be accompanied by various neurological symptoms. Migraine is thought to result from activation of the trigeminovascular system followed by vasodilation of pain-producing intracranial blood vessels and activation of second-order sensory neurons in the trigeminal nucleus caudalis. Calcitonin gene-related peptide (CGRP) is a mediator of neurogenic inflammation and the most powerful vasodilating neuropeptide, and has been implicated in migraine pathophysiology. Consequently, genes involved in CGRP synthesis or CGRP receptor genes may play a role in migraine and/or increase susceptibility. This study investigates whether variants in the gene that encodes CGRP, calcitonin-related polypeptide alpha (CALCA) or in the gene that encodes a component of its receptor, receptor activity modifying protein 1 (RAMP1), are associated with migraine pathogenesis and susceptibility. The single nucleotide polymorphisms (SNPs) rs3781719 and rs145837941 in the CALCA gene, and rs3754701 and rs7590387 at the RAMP1 locus, were analysed in an Australian Caucasian population of migraineurs and matched controls. Although we find no significant association of any of the SNPs tested with migraine overall, we detected a nominally significant association (p = 0.031) of the RAMP1 rs3754701 variant in male migraine subjects, although this is non-significant after Bonferroni correction for multiple testing.

The human μ-opioid receptor gene polymorphism (A118G) is associated with head pain severity in a clinical cohort of female migraine with aura patients

Migraine is a painful and debilitating, neurovascular disease. Current migraine head pain treatments work with differing efficacies in migraineurs. The opioid system plays an important role in diverse biological functions including analgesia, drug response and pain reduction. The A118G single nucleotide polymorphism (SNP) in exon 1 of the μ-opioid receptor gene (OPRM1) has been associated with elevated pain responses and decreased pain threshold in a variety of populations. The aim of the current preliminary study was to test whether genotypes of the OPRM1 A118G SNP are associated with head pain severity in a clinical cohort of female migraineurs. This was a preliminary study to determine whether genotypes of the OPRM1 A118G SNP are associated with head pain severity in a clinical cohort of female migraineurs. A total of 153 chronic migraine with aura sufferers were assessed for migraine head pain using the Migraine Disability Assessment Score instrument and classified into high and low pain severity groups. DNA was extracted and genotypes obtained for the A118G SNP. Logistic regression analysis adjusting for age effects showed the A118G SNP of the OPRM1 gene to be significantly associated with migraine pain severity in the test population (P = 0.0037). In particular, G118 allele carriers were more likely to be high pain sufferers compared to homozygous carriers of the A118 allele (OR = 3.125, 95 % CI = 1.41, 6.93, P = 0.0037). These findings suggest that A118G genotypes of the OPRM1 gene may influence migraine-associated head pain in females. Further investigations are required to fully understand the effect of this gene variant on migraine head pain including studies in males and in different migraine subtypes, as well as in response to head pain medication.