446 research outputs found

    Evolutionary Algorithms with Self-adjusting Asymmetric Mutation

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    Evolutionary Algorithms (EAs) and other randomized search heuristics are often considered as unbiased algorithms that are invariant with respect to different transformations of the underlying search space. However, if a certain amount of domain knowledge is available the use of biased search operators in EAs becomes viable. We consider a simple (1+1) EA for binary search spaces and analyze an asymmetric mutation operator that can treat zero- and one-bits differently. This operator extends previous work by Jansen and Sudholt (ECJ 18(1), 2010) by allowing the operator asymmetry to vary according to the success rate of the algorithm. Using a self-adjusting scheme that learns an appropriate degree of asymmetry, we show improved runtime results on the class of functions OneMaxa_a describing the number of matching bits with a fixed target a{0,1}na\in\{0,1\}^n.Comment: 16 pages. An extended abstract of this paper will be published in the proceedings of PPSN 202

    Non-Parametric Approximations for Anisotropy Estimation in Two-dimensional Differentiable Gaussian Random Fields

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    Spatially referenced data often have autocovariance functions with elliptical isolevel contours, a property known as geometric anisotropy. The anisotropy parameters include the tilt of the ellipse (orientation angle) with respect to a reference axis and the aspect ratio of the principal correlation lengths. Since these parameters are unknown a priori, sample estimates are needed to define suitable spatial models for the interpolation of incomplete data. The distribution of the anisotropy statistics is determined by a non-Gaussian sampling joint probability density. By means of analytical calculations, we derive an explicit expression for the joint probability density function of the anisotropy statistics for Gaussian, stationary and differentiable random fields. Based on this expression, we obtain an approximate joint density which we use to formulate a statistical test for isotropy. The approximate joint density is independent of the autocovariance function and provides conservative probability and confidence regions for the anisotropy parameters. We validate the theoretical analysis by means of simulations using synthetic data, and we illustrate the detection of anisotropy changes with a case study involving background radiation exposure data. The approximate joint density provides (i) a stand-alone approximate estimate of the anisotropy statistics distribution (ii) informed initial values for maximum likelihood estimation, and (iii) a useful prior for Bayesian anisotropy inference.Comment: 39 pages; 8 figure

    Feller Processes: The Next Generation in Modeling. Brownian Motion, L\'evy Processes and Beyond

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    We present a simple construction method for Feller processes and a framework for the generation of sample paths of Feller processes. The construction is based on state space dependent mixing of L\'evy processes. Brownian Motion is one of the most frequently used continuous time Markov processes in applications. In recent years also L\'evy processes, of which Brownian Motion is a special case, have become increasingly popular. L\'evy processes are spatially homogeneous, but empirical data often suggest the use of spatially inhomogeneous processes. Thus it seems necessary to go to the next level of generalization: Feller processes. These include L\'evy processes and in particular Brownian motion as special cases but allow spatial inhomogeneities. Many properties of Feller processes are known, but proving the very existence is, in general, very technical. Moreover, an applicable framework for the generation of sample paths of a Feller process was missing. We explain, with practitioners in mind, how to overcome both of these obstacles. In particular our simulation technique allows to apply Monte Carlo methods to Feller processes.Comment: 22 pages, including 4 figures and 8 pages of source code for the generation of sample paths of Feller processe

    Isotopic and molecular distributions of biochemicals from fresh and buried Rhizophora mangle leaves†

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    Rhizophora mangle L. (red mangrove) is the dominant species of mangrove in the Americas. At Twin Cays, Belize (BZ) red mangroves are present in a variety of stand structures (tall >5 m in height, transition ~2–4 m and dwarf ~1–1.5 m). These height differences are coupled with very different stable carbon and nitrogen isotopic values[1] (mean tall δ(13)C = -28.3‰, δ(15)N = 0‰; mean tall δ(13)C = -25.3‰, δ(15)N = -10‰). To determine the utility of using these distinct isotopic compositions as 'biomarkers' for paleoenvironmental reconstruction of mangrove ecosystems and nutrient availability, we investigated the distribution and isotopic (δ(13)C and δ(15)N) composition of different biochemical fractions (water soluble compounds, free lipids, acid hydrolysable compounds, individual amino acids, and the residual un-extractable compounds) in fresh and preserved red mangrove leaves from dwarf and tall trees. The distribution of biochemicals are similar in dwarf and tall red mangrove leaves, suggesting that, regardless of stand structure, red mangroves use nutrients for biosynthesis and metabolism in a similar manner. However, the δ(13)C and δ(15)N of the bulk leaf, the biochemical fractions, and seven amino acids can be used to distinguish dwarf and tall trees at Twin Cays, BZ. The data support the theory that the fractionation of carbon and nitrogen occurs prior to or during uptake in dwarf and tall red mangrove trees. Stable carbon and nitrogen isotopes could, therefore, be powerful tools for predicting levels of nutrient limitation at Twin Cays. The δ(13)C and δ(15)N of biochemical fractions within preserved leaves, reflect sedimentary cycling and nitrogen immobilization. The δ(15)N of the immobilized fraction reveals the overlying stand structure at the time of leaf deposition. The isotopic composition of preserved mangrove leaves could yield significant information about changes in ecosystem dynamics, nutrient limitation and past stand structure in mangrove paleoecosystems

    Nutrient Enrichment Increases Mortality of Mangroves

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    Nutrient enrichment of the coastal zone places intense pressure on marine communities. Previous studies have shown that growth of intertidal mangrove forests is accelerated with enhanced nutrient availability. However, nutrient enrichment favours growth of shoots relative to roots, thus enhancing growth rates but increasing vulnerability to environmental stresses that adversely affect plant water relations. Two such stresses are high salinity and low humidity, both of which require greater investment in roots to meet the demands for water by the shoots. Here we present data from a global network of sites that documents enhanced mortality of mangroves with experimental nutrient enrichment at sites where high sediment salinity was coincident with low rainfall and low humidity. Thus the benefits of increased mangrove growth in response to coastal eutrophication is offset by the costs of decreased resilience due to mortality during drought, with mortality increasing with soil water salinity along climatic gradients

    Successful new product development by optimizing development process effectiveness in highly regulated sectors: the case of the Spanish medical devices sector

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    Rapid development and commercialization of new products is of vital importance for small and medium sized enterprises (SME) in regulated sectors. Due to strict regulations, competitive advantage can hardly be achieved through the effectiveness of product concepts only. If an SME in a highly regulated sector wants to excell in new product development (NPD) performance, the company should focus on the flexibility, speed, and productivity of its NPD function: i.e. the development process effectiveness. Our main research goals are first to explore if SMEs should focus on their their development process effectiveness rather than on their product concept effectiveness to achieve high NPD performance; and second, to explore whether a shared pattern in the organization of the NPD function can be recognized to affect NPD performance positively. The medical devices sector in Spain is used as an example of a\ud highly regulated sector. A structured survey among 11 SMEs, of which 2 were studied also as in in-depth case studies, led to the following results. First of all, indeed the companies in the dataset which focused on the effectiveness of their development process, stood out in NPD performance. Further, the higher performing companies did have a number of commonalities in the organisation of their NPD function: 1) The majority of the higher performing firms had an NPD strategy characterized by a predominantly incremental project portfolio.\ud 2) a) Successful firms with an incremental project portfolio combined this with a functional team structure b) Successful firms with a radical project portfolio combined this with a heavyweight or autonomous team structure.\ud 3) A negative reciprocal relationship exists between formalization of the NPD processes and the climate of the NPD function, in that a formalized NPD process and an innovative climate do not seem to reinforce each other. Innovative climate combined with an informal NPD process does however contribute positively to NPD performance. This effect was stronger in combination with a radical project portfolio. The highest NPD performance was measured for companies focusing mainly on incremental innovation. It is argued that in highly regulated sectors, companies with an incremental product portfolio would benefit from employing a functional structure. Those companies who choose for a more radical project portfolio in highly regulated sectors should be aware\ud that they are likely to excell only in the longer term by focusing on strategic flexibility. In their NPD organization, they might be well advised to combine informal innovation processes with an innovative climate

    Substrate binding and translocation of the serotonin transporter studied by docking and molecular dynamics simulations

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    The serotonin (5-HT) transporter (SERT) plays an important role in the termination of 5-HT-mediated neurotransmission by transporting 5-HT away from the synaptic cleft and into the presynaptic neuron. In addition, SERT is the main target for antidepressant drugs, including the selective serotonin reuptake inhibitors (SSRIs). The three-dimensional (3D) structure of SERT has not yet been determined, and little is known about the molecular mechanisms of substrate binding and transport, though such information is very important for the development of new antidepressant drugs. In this study, a homology model of SERT was constructed based on the 3D structure of a prokaryotic homologous leucine transporter (LeuT) (PDB id: 2A65). Eleven tryptamine derivates (including 5-HT) and the SSRI (S)-citalopram were docked into the putative substrate binding site, and two possible binding modes of the ligands were found. To study the conformational effect that ligand binding may have on SERT, two SERT–5-HT and two SERT–(S)-citalopram complexes, as well as the SERT apo structure, were embedded in POPC lipid bilayers and comparative molecular dynamics (MD) simulations were performed. Our results show that 5-HT in the SERT–5-HTB complex induced larger conformational changes in the cytoplasmic parts of the transmembrane helices of SERT than any of the other ligands. Based on these results, we suggest that the formation and breakage of ionic interactions with amino acids in transmembrane helices 6 and 8 and intracellular loop 1 may be of importance for substrate translocation

    Calcium-Dependent Increases in Protein Kinase-A Activity in Mouse Retinal Ganglion Cells Are Mediated by Multiple Adenylate Cyclases

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    Neurons undergo long term, activity dependent changes that are mediated by activation of second messenger cascades. In particular, calcium-dependent activation of the cyclic-AMP/Protein kinase A signaling cascade has been implicated in several developmental processes including cell survival, axonal outgrowth, and axonal refinement. The biochemical link between calcium influx and the activation of the cAMP/PKA pathway is primarily mediated through adenylate cyclases. Here, dual imaging of intracellular calcium concentration and PKA activity was used to assay the role of different classes of calcium-dependent adenylate cyclases (ACs) in the activation of the cAMP/PKA pathway in retinal ganglion cells (RGCs). Surprisingly, depolarization-induced calcium-dependent PKA transients persist in barrelless mice lacking AC1, the predominant calcium-dependent adenylate cyclase in RGCs, as well as in double knockout mice lacking both AC1 and AC8. Furthermore, in a subset of RGCs, depolarization-induced PKA transients persist during the inhibition of all transmembrane adenylate cyclases. These results are consistent with the existence of a soluble adenylate cyclase that plays a role in calcium-dependent activation of the cAMP/PKA cascade in neurons
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