We consider a Darcy flow model with saturation-pressure relation extended
with a dynamic term, namely, the time derivative of the saturation.
This model was proposed in works of J.Hulshof and J.R.King (1998), S.M.Hassanizadeh and W.G.Gray (1993),
We restrict ourself to one spatial dimension and strictly positive
initial saturation. For this case we transform the initial-boundary value
problem into combination of elliptic boundary-value problem and initial
value problem for abstract Ordinary Differential Equation. This splitting
is rather helpful both for theoretical aspects and numerical methods.
The sink location problem is a combination of network flow and location problems: From a given set of nodes in a flow network a minimum cost subset \(W\) has to be selected such that given supplies can be transported to the nodes in \(W\). In contrast to its counterpart, the source location problem which has already been studied in the literature, sinks have, in general, a limited capacity. Sink location has a decisive application in evacuation planning, where the supplies correspond to the number of evacuees and the sinks to emergency shelters.
We classify sink location problems according to capacities on shelter nodes, simultaneous or non-simultaneous flows, and single or multiple assignments of evacuee groups to shelters. Resulting combinations are interpreted in the evacuation context and analyzed with respect to their worst-case complexity status.
There are several approaches to tackle these problems: Generic solution methods for uncapacitated problems are based on source location and modifications of the network. In the capacitated case, for which source location cannot be applied, we suggest alternative approaches which work in the original network. It turns out that latter class algorithms are superior to the former ones. This is established in numerical tests including random data as well as real world data from the city of Kaiserslautern, Germany.
Building interoperation among separately developed software units requires checking their conceptual assumptions and constraints. However, eliciting such assumptions and constraints is time consuming and is a challenging task as it requires analyzing each of the interoperating software units. To address this issue we proposed a new conceptual interoperability analysis approach which aims at decreasing the analysis cost and the conceptual mismatches between the interoperating software units. In this report we present the design of a planned controlled experiment for evaluating the effectiveness, efficiency, and acceptance of our proposed conceptual interoperability analysis approach. The design includes the study objectives, research questions, statistical hypotheses, and experimental design. It also provides the materials that will be used in the execution phase of the planned experiment.
A new algorithm for optimization problems with three objective functions is presented which computes a representation for the set of nondominated points. This representation is guaranteed to have a desired coverage error and a bound on the number of iterations needed by the algorithm to meet this coverage error is derived. Since the representation does not necessarily contain nondominated points only, ideas to calculate bounds for the representation error are given. Moreover, the incorporation of domination during the algorithm and other quality measures are discussed.
A positive affection of human health by nutrition is of high interest, especially for bioactive compounds which are consumed daily in high amounts. This is the case for chlorogenic acids (CGA) ingested by coffee. This molecule class is associated with several possible beneficial health effects observed in vitro that strongly depend on their bioavailability. So far factors influencing bioavailability of CGA such as dose, molecule structure and site of absorption haven´t been investigated sufficiently.
Therefore we performed an in vivo dose-response study with ileostomists, who consumed three different nutritional doses of CGA ingested as instant coffee (4,525 (HIGH); 2,219 (MEDIUM); 1,053 (LOW) μmol CGA). CGA concentrations were determined in ileal fluid, urine and plasma. Furthermore, we conducted an ex vivo study with pig jejunal mucosa using the Ussing chamber model to confirm the in vivo observations. Individual transfer rates of CGA from coffee were investigated, namely: caffeoylquinic acid (CQA), feruloylquinic acid (FQA), caffeic acid (CA), dicaffeoylquinic acid (diCQA) and QA at physiological concentrations (0.2–3.5 mM). Samples were analyzed by HPLC-DAD, -ESI-MS and -ESI-MS/MS.
About ⅔ of the ingested CGA by coffee consumption were available in the colon dose independent. Nevertheless, the results showed that the consumption of higher CGA doses leads to a faster ileal excretion. This corresponds to a plasma AUC0-8h for CGA and metabolites of 4,412 ± 751 nM*h0-8-1 (HIGH), 2,394 ± 637 nM*h0-8-1 (MEDIUM) and 1,782 ± 731 nM*h0-8-1 (LOW) respectively, and a renal excretion of 8.0 ± 4.9% (HIGH), 12.1 ± 6.7% (MEDIUM) and 14.6 ± 6.8% (LOW). Moreover interindividual differences in gastrointestinal transit times were related to differences in total CGA absorption. Thus the variety of patient´s physiology is a decisive bioavailability factor for CGA uptake. This is corroborated ex vivo by a direct proportional relationship of incubation time with absorbed CGA amount.
The consumption of high CGA doses influences the metabolism pattern as an increasing glucuronidation was observed with consumption of increasing CGA doses. However, the different CGA doses have only minor effects on the overall bioavailability which was confirmed ex vivo by a non-saturable passive diffusion of 5-CQA. Furthermore, we identified in the Ussing chamber an active efflux secretion for 5-CQA that decreases its bioavailability and the physicochemical properties of the CGA subgroups as an important bioavailability factor. Transferred amount in increasing order: diCQA, trace amounts; CQA ≈ 1%; CA ≈ 1.5%; FQA ≈ 2%; and QA ≈ 4%.
Altogether, the consumption of increasing CGA doses by coffee had a minor effect on oral bioavailability in ileostomists, such as a slightly increased glucuronidation. Thus, the consumption of high amounts of CGA from coffee in the daily diet is not limiting the CGA concentrations at the site of possible health effects in the human body. However, according to the patient´s physiology the interindividual gastrointestinal transit time which is possibly influenced by dose is influencing CGA bioavailability. Moreover, ex vivo CGA absorption is governed by diffusion as an absorption mechanism corroborating an unsaturable uptake in vivo and by the individual physicochemical properties of CGA.
The ordered weighted averaging objective (OWA) is an aggregate function over multiple optimization criteria which received increasing attention by the research community over the last decade. Different to the ordered weighted sum, weights are attached to ordered objective functions (i.e., a weight for the largest value, a weight for the second-largest value and so on). As this contains max-min or worst-case optimization as a special case, OWA can also be considered as an alternative approach to robust optimization.
For linear programs with OWA objective, compact reformulations exist, which result in extended linear programs. We present new such reformulation models with reduced size. A computational comparison indicates that these formulations improve solution times.
We consider an uncertain traveling salesman problem, where distances between nodes are not known exactly, but may stem from an uncertainty set of possible scenarios. This uncertainty set is given as intervals with an additional bound on the number of distances that may deviate from their expected, nominal value.
A recoverable robust model is proposed, that allows a tour to change a bounded number of edges once a scenario becomes known. As the model contains an exponential number of constraints and variables, an iterative algorithm is proposed, in which tours and scenarios are computed alternately.
While this approach is able to find a provably optimal solution to the robust model, it also needs to solve increasingly complex subproblems. Therefore, we also consider heuristic solution procedures based on local search moves using a heuristic estimate of the actual objective function. In computational experiments, these approaches are compared.
Finally, an alternative recovery model is discussed, where a second-stage recovery tour is not required to visit all nodes of the graph. We show that the previously NP-hard evaluation of a fixed solution now becomes solvable in polynomial time.
We argue that the concepts of resilience in engineering science and robustness in mathematical optimization are strongly related. Using evacuation planning as an example application, we demonstrate optimization techniques to improve solution resilience. These include a direct modelling of the uncertainty for stochastic or robust optimization, as well as taking multiple objective functions into account.
Glioma is a common type of primary brain tumor, with a strongly invasive potential, often exhibiting nonuniform, highly irregular growth. This makes it difficult to assess
the degree of extent of the tumor, hence bringing about a supplementary challenge for the treatment. It is therefore necessary to understand the
migratory behavior of glioma in greater detail.
In this paper we propose a multiscale model for glioma growth and migration. Our model couples the microscale dynamics (reduced to the binding of surface receptors to the
surrounding tissue) with a kinetic transport equation for the cell density on the mesoscopic level of individual cells. On the latter scale we also include the
proliferation of tumor cells via effects of interaction with the tissue. An adequate parabolic scaling yields a convection-diffusion-reaction equation, for which the coefficients
can be explicitly determined from the information about the tissue obtained by diffusion tensor imaging. Numerical simulations relying on DTI measurements confirm the biological
findings that glioma spreads
along white matter tracts.
As the complexity of embedded systems continuously rises, their development becomes more and more challenging. One technique to cope with this complexity is the employment of virtual prototypes. The virtual prototypes are intended to represent the embedded system’s properties on different levels of detail like register transfer level or transaction level. Virtual prototypes can be used for different tasks throughout the development process. They can act as executable specification, can be used for architecture exploration, can ease system integration, and allow for pre- and post-silicon software development and verification. The optimization objectives for virtual prototypes and their creation process are manifold. Finding an appropriate trade-off between the simulation accuracy, the simulation performance, and the implementation effort is a major challenge, as these requirements are contradictory.
In this work, two new and complementary techniques for the efficient creation of accurate and high-performance SystemC based virtual prototypes are proposed: Advanced Temporal Decoupling (ATD) and Transparent Transaction Level Modeling (TTLM). The suitability for industrial environments is assured by the employment of common standards like SystemC TLM-2.0 and IP-XACT.
Advanced Temporal Decoupling enhances the simulation accuracy while retaining high simulation performance by allowing for cycle accurate simulation in the context of SystemC TLM-2.0 temporal decoupling. This is achieved by exploiting the local time warp arising in SystemC TLM-2.0 temporal decoupled models to support the computation of resource contention effects. In ATD, accesses to shared resource are managed by Temporal Decoupled Semaphores (TDSems) which are integrated into the modeled shared resources. The set of TDSems assures the correct execution order of shared resource accesses and incorporates timing effects resulting from shared resource access execution and resource conflicts. This is done by dynamically varying the data granularity of resource accesses based on information gathered from the local time warp. ATD facilitates modeling of a wide range of resource and resource access properties like preemptable and non-preemptable accesses, synchronous and asynchronous accesses, multiport resources, dynamic access priorities, interacting and cascaded resources, and user specified schedulers prioritizing simultaneous resource accesses.
Transparent Transaction Level Modeling focuses on the efficient creation of virtual prototypes by reducing the implementation effort and consists of a library and a code generator. The TTLM library adds a layer of convenience functions to ATD comprising various application programming interfaces for inter module communication, virtual prototype configuration and run time information extraction. The TTLM generator is used to automatically generate the structural code of the virtual prototype from the formal hardware specification language IP-XACT.
The applicability and benefits of the presented techniques are demonstrated using an image processing centric automotive application. Compared to an existing cycle accurate SystemC model, the implementation effort can be reduced by approximately 50% using TTLM. Applying ATD, the simulation performance can be increased by a factor of up to five while retaining cycle accuracy.