Detecting Data-Flow Errors in BPMN 2.0

Data-flow errors in BPMN 2.0 process models, such as missing or unused data, lead to undesired process executions. In particular, since BPMN 2.0 with a standardized execution semantics allows specifying alternatives for data as well as optional data, identifying missing or unused data systematically is difficult. In this paper, we propose an approach for detecting data-flow errors in BPMN 2.0 process models. We formalize BPMN process models by mapping them to Petri Nets and unfolding the execution semantics regarding data. We define a set of anti-patterns representing data-flow errors of BPMN 2.0 process models. By employing the anti-patterns, our tool performs model checking for the unfolded Petri Nets. The evaluation shows that it detects all data-flow errors identified by hand, and so improves process quality

Improved Hardness of Approximation for Stackelberg Shortest-Path Pricing

We consider the Stackelberg shortest-path pricing problem, which is defined as follows. Given a graph G with fixed-cost and pricable edges and two distinct vertices s and t, we may assign prices to the pricable edges. Based on the predefined fixed costs and our prices, a customer purchases a cheapest s-t-path in G and we receive payment equal to the sum of prices of pricable edges belonging to the path. Our goal is to find prices maximizing the payment received from the customer. While Stackelberg shortest-path pricing was known to be APX-hard before, we provide the first explicit approximation threshold and prove hardness of approximation within 2−o(1). We also argue that the nicely structured type of instance resulting from our reduction captures most of the challenges we face in dealing with the problem in general and, in particular, we show that the gap between the revenue of an optimal pricing and the only known general upper bound can still be logarithmically large

Assessing the effects of chemical mixtures using a Bayesian network-relative risk model (BN-RRM) integrating adverse outcome pathways (AOPs) in three Puget Sound watersheds

Chemical mixtures are difficult to assess at the individual level, but more challenging at the population level. There is still little insight of the molecular pathway for numerous chemical mixtures. We have conducted a regional-scale ecological risk assessment by evaluating the effects chemical mixtures to populations with a Bayesian Network- Relative Risk Model (BN-RRM) incorporating a molecular pathway. We used this BN-RRM framework in a case study with organophosphate pesticide (OP) mixtures (diazinon, chlorpyrifos, and malathion) in three watersheds (Lower Skagit, Nooksack, Cedar) in the state of Washington (USA). Puget Sound Chinook salmon (Oncorhynchus tshawytscha) Evolutionary Significant Units (ESU) were chosen as population endpoints. These populations are a valuable ecosystem service in the Pacific Northwest because they benefit the region as a species that provide protection of biodiversity and are spiritually and culturally treasured by the local tribes. Laetz et al. (2009, 2013) indicated that organophosphate pesticide mixtures act synergistically to salmon and impair neurological molecular activity which leads to a change in swimming behavior and mortality, which then leads to changes in population productivity. Exposure response curves were generated for OP mixtures to connect the molecular pathway. Ecological stressors from dissolved oxygen and temperature were also included in our risk analysis. Synergism within the mixtures as well as increasing temperature and decreasing dissolve oxygen content lead to increasing risk to Puget Sound Chinook salmon populations. This research demonstrates a probabilistic approach with a multiple stressor framework to estimate the effects of mixtures through a molecular pathway and predict impacts to these valuable ecosystem services

Geologische Untersuchungen an Sedimenten des indisch-pakistanischen Kontinentalrandes (Arabischs Meer)

From the R./V. "Meteor" and the Pakistan F./V. "Machhera" sediments from the Indian-Pakistan continental margin habe been investigated in order to delineate the facies distribution of the recent deposits. One of the several objectives of this study was to find out how far the suspended matter of the Indus River is being transported into the Arabian Sea. A close genetic relationship was recognised between the oceanographic conditions of the water masses (chemistry and currents) and the characteristics of the sediments. The activity of the monsoons is reflected by the rhythmic lamination of the sediments of the upper continental slope. The suspended matter from the Indus River can be traced far into the Arabian Sea. The clay minerals show the following tendenciey from litoral to abyssal regions and from the top ot the cores downward: detrital clay minerals (chlorite, muscovite, illite) - degraded clay minerals (montmorillonite, mixed-layer minerals) - "re-formational" minerals (illite). The biostratigraphic investigations of the sedimentds combined with several C14-dates results in sedimentation rates from >50 cm/1000 years at the upper continental slope decreasing to about 1 cm/1000 years inhe faunal composition proves the existende of a climatic optimum during part of the Holocene. The geochemical investigation of the recent pore fluids demonstrates that their composition very soon assumes the characteristics of fossil inerstitial waters (cf. V. Marchig, in this vol.). The results will be published in Meteor-Forschungsergebnisse, Reihe C

Solving ill-posed bilevel programs

This paper deals with ill-posed bilevel programs, i.e., problems admitting multiple lower-level solutions for some upper-level parameters. Many publications have been devoted to the standard optimistic case of this problem, where the difficulty is essentially moved from the objective function to the feasible set. This new problem is simpler but there is no guaranty to obtain local optimal solutions for the original optimistic problem by this process. Considering the intrinsic non-convexity of bilevel programs, computing local optimal solutions is the best one can hope to get in most cases. To achieve this goal, we start by establishing an equivalence between the original optimistic problem an a certain set-valued optimization problem. Next, we develop optimality conditions for the latter problem and show that they generalize all the results currently known in the literature on optimistic bilevel optimization. Our approach is then extended to multiobjective bilevel optimization, and completely new results are derived for problems with vector-valued upper- and lower-level objective functions. Numerical implementations of the results of this paper are provided on some examples, in order to demonstrate how the original optimistic problem can be solved in practice, by means of a special set-valued optimization problem

Anodic stripping voltammetry with graphite felt electrodes for the trace analysis of silver

Graphite felt (GF) is a mass produced porous carbon electrode material commonly used in redox flow batteries. Previous studies have suggested GF may have valuable applications in electroanalysis as a low cost disposable carbon electrode material, although most GF sensors have used flow cell arrangements. In this work, an elegant wetting technique is employed that allows GF electrodes to be used in quiescent solution to detect trace levels of silver in water via anodic stripping voltammetry. GF electrodes display good repeatability and a limit of detection of 25 nM of Ag+ in 0.1 M HNO3, with a linear range spanning two orders of magnitude. This compares to a value of around 140 nM when using conventional carbon electrodes. Combined with their low cost and disposable nature, the results suggest GF electrodes can make a valuable contribution to electroanalysis