Predicting a cyclic Poisson process

We construct and investigate a (1−α)-upper prediction bound for a future observation of a cyclic Poisson process using past data. A normal based confidence interval for our upper prediction bound is established. A comparison of the new prediction bound with a simpler nonparametric prediction bound is also given.     

Impact of Positional Isomerism on Pathway Complexity in Aqueous Media

Pathway complexity has become an important topic in recent years due to its relevance in the optimization of molecular assembly processes, which typically require precise sample preparation protocols. Alternatively, competing aggregation pathways can be controlled by molecular design, which primarily rely on geometrical changes of the building blocks. However, understanding how to control pathway complexity by molecular design remains elusive and new approaches are needed. Herein, we exploit positional isomerism as a new molecular design strategy for pathway control in aqueous self‐assembly. We compare the self‐assembly of two carboxyl‐functionalized amphiphilic BODIPY dyes that solely differ in the relative position of functional groups. Placement of the carboxyl group at the 2‐position enables efficient pairwise H‐bonding interactions into a single thermodynamic species, whereas meso‐substitution induces pathway complexity due to competing hydrophobic and hydrogen bonding interactions. Our results show the importance of positional engineering for pathway control in aqueous self‐assembly.     

Development of bacteria-based bioassays for arsenic detection in natural waters

Arsenic contamination of natural waters is a worldwide concern, as the drinking water supplies for large populations can have high concentrations of arsenic. Traditional techniques to detect arsenic in natural water samples can be costly and time-consuming; therefore, robust and inexpensive methods to detect arsenic in water are highly desirable. Additionally, methods for detecting arsenic in the field have been greatly sought after. This article focuses on the use of bacteria-based assays as an emerging method that is both robust and inexpensive for the detection of arsenic in groundwater both in the field and in the laboratory. The arsenic detection elements in bacteria-based bioassays are biosensor–reporter strains; genetically modified strains of, e.g., Escherichia coli, Bacillus subtilis, Staphylococcus aureus, and Rhodopseudomonas palustris. In response to the presence of arsenic, such bacteria produce a reporter protein, the amount or activity of which is measured in the bioassay. Some of these bacterial biosensor–reporters have been successfully utilized for comparative in-field analyses through the use of simple solution-based assays, but future methods may concentrate on miniaturization using fiberoptics or microfluidics platforms. Additionally, there are other potential emerging bioassays for the detection of arsenic in natural waters including nematodes and clams.     

Estimating the intensity of a cyclic Poisson process in the presence of linear trend

We construct and investigate a consistent kernel-type nonparametric estimator of the intensity function of a cyclic Poisson process in the presence of linear trend. It is assumed that only a single realization of the Poisson process is observed in a bounded window. We prove that the proposed estimator is consistent when the size of the window indefinitely expands. The asymptotic bias, variance, and the mean-squared error of the proposed estimator are also computed. A simulation study shows that the first order asymptotic approximations to the bias and variance of the estimator are not accurate enough. Second order terms for bias and variance were derived in order to be able to predict the numerical results in the simulation. Bias reduction of our estimator is also proposed.     

Simulation-based optimisation of wastewater flow and composition for on-site treatment in the food and beverage industry utilising reference nets in combination with genetic algorithms

This study introduces the concept of computer modelling and simulation of complex bioprocesses and systems using an approach that combines the reference net formalism with machine learning and optimisation techniques. Reference nets are an extension of high level Petri Nets, which can be used as a central visualisation and modelling tool. The net-in-net paradigm used by reference nets makes it possible to model complex processes, such as those found in the food and beverage industry. A plugin/interface system based on the java programming language allows implementation of advanced mathematical modelling techniques at specific points in entire system simulations. Separate optimisation tools can also run and modify existing reference net models for fast solutions to efficiency problems. We present an example system that simulates a specific section of a beer brewery using the reference net formalism, which is optimised using a genetic algorithm. We show in detail how the different software packages can be combined for a simulation based optimisation approach. The optimisation technique specifically addresses the wastewater pollution load in regard to its chemical oxygen demand. A beer brewery was chosen as an example for this study due to the constantly increasing requirements to lower energy and water consumption in this industry. One possibility to lower the energy and water demands is to effectively treat wastewater produced by the brewery, which can introduce cost savings by providing recycled water and biogas. Most approaches to wastewater treatment are end-of-pipe solutions that do not consider the brewery as a whole. A brewery contains many processes that can be running concurrently and interacting with one another (e.g. brewing, clean-in-place and bottling) with each process producing varying amounts of wastewater with different pollution loads. Optimisation of the scheduling of the different processes with respect to the wastewater production will allow for more effective wastewater treatment, and therefore cost and energy savings. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

From PCA's to equilibrium systems and back

Stationary measures for probabilistic cellular automata (PCA's) ind dimensions give rise to space-time histories whose statistics may naturally be described by Gibbs states ind+1 dimensions for an interaction energy ? obtained from the PCA. In this note we study the converse question: Do all Gibbs states for this ? correspond to statistical space-time histories for the PCA? Our main result states that the answer is yes, at least for translation invariant or periodic Gibbs states. Thus ergodicity questions for PCA's can, at least partially, be formulated as questions of uniqueness of Gibbs states.     

Speciation of cadmium in seawater — a direct voltammetric approach

The present report deals with differential pulse anodic stripping voltammetry (DPASV) applied for the analysis of cadmium in open ocean seawater. Evaluation of different Cd species can generate information about distribution and speciation of Cd in the open ocean. Distribution of Cd was investigated in surface waters of the Atlantic Ocean over a wide geographical range as well as in the water column. Surface water sampling on board the research vessel Polarstern was performed from the bow boom of the ship as well as with a snorkel system which allowed continuous sample-taking. Two different Cd species could be differentiated in the voltammograms. UV-irradiation experiments allowed the identification of an inorganic and organic Cd form, the latter caused by the association between Cd and organic matter as e.g. humic substances (HS). Atlantic ocean surface seawater normally contains between 2 and 4 ng organically complexed Cd/kg and no detectable inorganic Cd. Some areas however showed readings of up to 14 ng inorganic Cd/kg in addition. Water column samples exhibited an enrichment of inorganic Cd by depth. Occurrence of inorganic Cd at the surface could be related to specific oceanographical conditions. Together with analytical results of trace metal contents in the particulate phases of surface seawater, new aspects could be established about the biogeochemical cycling of Cd in the sea.     

SAR study of 1-aryl-4-(phenylarylmethyl)piperazines as ligands for both dopamine D2 and serotonin 5-HT1A receptors showing varying degrees of (Ant)agonism. Selection of a potential atypical antipsychotic

The syntheses of several 1-aryl-4-(arylpyridylmethyl)piperazines (4) and their affinities for dopamine D(2) and serotonin 5-HT(1A) receptors are described. The compounds were evaluated both in vitro and in vivo, resulting in the identification of the drug candidate SLV313 (4e) with equipotent and full D(2) receptor antagonism and 5-HT(1A) receptor agonism. Minor structural modifications in SLV313 revealed the possibility of designing compounds possessing varying degrees of partial agonism on one or both target receptors.     

Bestimmung von Cholesterin in Wollwachs

Ohne Zusammenfassung