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Botrytis cinerea is a major plant pathogen infecting more than 1400 plant species. During invasion, the fungus rapidly kills host cells, which is believed to be supported by induction of programmed plant cell death. To comprehensively evaluate the contributions of most of the currently known plant cell death inducing proteins (CDIPs) and metabolites for necrotrophic infection, an optimized CRISPR/Cas9 protocol was established which allowed to perform serial marker-free mutagenesis to generate multiple deletion mutants lacking up to 12 CDIPs. Whole genome sequencing of a 6x and 12x deletion mutant revealed a low number of off-target mutations which were unrelated to Cas9-mediated cleavage. Secretome analyses confirmed the loss of secreted proteins encoded by the deleted genes. Infection tests with the mutants revealed a successive decrease in virulence with increasing numbers of mutated genes, and varying effects of the knockouts on different host plants. Comparative analysis of mutants confirmed significant roles of two polygalacturonases (PG1, PG2) and the phytotoxic metabolites botrydial and botcinins for infection, but revealed no or only weak effects of deletion of the other CDIPs. Nicotiana benthamiana plants with mutated or silenced coreceptors of pattern recognition receptors, SOBIR1 and BAK1, showed similar susceptibility as control plants to infection by B. cinerea wild type and a 12x deletion mutant. These results raise doubts about a major role of manipulation of these plant defence regulators for B. cinerea infection. Despite the loss of most of the known phytotoxic compounds, the on planta secretomes of the multiple mutants retained substantial phytotoxic activity, proving that further, as yet unknown CDIPs contribute to necrosis and virulence. Our study has addressed for the first time systematically the functional redundancy of fungal virulence factors, and demonstrates that B. cinerea releases a highly redundant cocktail of proteins to achieve necrotrophic infection of a wide variety of host plants.
By mapping the boundaries of Kant’s categorical imperative to the point where it permits the committing of a crime against Hume’s three principles of justice, it shall be demonstrated how far the area is in which these two concepts persist alongside each other and how narrow the border zone is in which they do not. Indeed, the latter is a forbidden place that can only be accessed through destiny and never by choice. Whoever is witnessed to stay there, must wish for Justice to draw her sword against him, and whoever dares to try reaching it, will only wander about a deserted land where both justice and morality are left behind.
This paper presents a method for classifying traffic participants based on high-resolution automotive radar sensors for autonomous driving applications. The major classes of traffic participants addressed in this work are pedestrians, bicyclists and passenger cars. The preprocessed radar detections are first segmented into distinct clusters using density-based spatial clustering of applications with noise (DBSCAN) algorithm. Each cluster of detections would typically have different properties based on the respective characteristics of the object that they originated from. Therefore, sixteen distinct features based on radar detections, that are suitable for separating pedestrians, bicyclists and passenger car categories are selected and extracted for each of the cluster. A support vector machine (SVM) classifier is constructed, trained and parametrised for distinguishing the road users based on the extracted features. Experiments are conducted to analyse the classification performance of the proposed method on real data.
In this paper a modified version of dynamic network
ows is discussed. Whereas dynamic network flows are widely analyzed already, we consider a dynamic flow problem with aggregate arc capacities called Bridge
Problem which was introduced by Melkonian [Mel07]. We extend his research to integer flows and show that this problem is strongly NP-hard. For practical relevance we also introduce and analyze the hybrid bridge problem, i.e. with underlying networks whose arc capacity can limit aggregate flow (bridge problem) or the flow entering an arc at each time (general dynamic flow). For this kind of problem we present efficient procedures for
special cases that run in polynomial time. Moreover, we present a heuristic for general hybrid graphs with restriction on the number of bridge arcs.
Computational experiments show that the heuristic works well, both on random graphs and on graphs modeling also on realistic scenarios.
In retail, assortment planning refers to selecting a subset of products to offer that maximizes profit. Assortments can be planned for a single store or a retailer with multiple chain stores where demand varies between stores. In this paper, we assume that a retailer with a multitude of stores wants to specify her offered assortment. To suit all local preferences, regionalization and store-level assortment optimization are widely used in practice and lead to competitive advantages. When selecting regionalized assortments, a tradeoff between expensive, customized assortments in every store and inexpensive, identical assortments in all stores that neglect demand variation is preferable.
We formulate a stylized model for the regionalized assortment planning problem (APP) with capacity constraints and given demand. In our approach, a 'common assortment' that is supplemented by regionalized products is selected. While products in the common assortment are offered in all stores, products in the local assortments are customized and vary from store to store.
Concerning the computational complexity, we show that the APP is strongly NP-complete. The core of this hardness result lies in the selection of the common assortment. We formulate the APP as an integer program and provide algorithms and methods for obtaining approximate solutions and solving large-scale instances.
Lastly, we perform computational experiments to analyze the benefits of regionalized assortment planning depending on the variation in customer demands between stores.
In this paper we introduce a binary autoregressive model. In contrast to the typical autoregression framework, we allow the conditional distribution of the observed process to depend on past values of the time series and some exogenous variables. Such processes have
potential applications in econometrics, medicine and environmental sciences. In this
paper, we establish stationarity and geometric ergodicity of these
processes under suitable conditions on the parameters of the model. Such properties are
important for understanding the stability properties of the model as well as for deriving the
asymptotic behavior of the parameter estimators.
Capital budgeting or investment decisions have an essential influence on companies’ performance. Instead of a rational choice, capital budgeting might be regarded as a process of reality construction. Research suggests that decision makers have only limited control over their own cognitive biases in this construction process. It is in this perspective that this paper intends to answer the following research question: What are behavioral determinants for a successful capital-budgeting decision process? The authors identify and discuss three behavioral success factors (reflective prudence, critical communication and outcome independence) for five stages of the capital budgeting process against the backdrop of the findings of the managerial and organizational cognition theory and cognitive psychology.
Noughts and Crosses
(2008)
The Comparative Manifesto Project (CMP) dataset is the only dataset providing information about the positions of parties for comparative researchers across time and countries. This article evaluates its structure and finds a peculiarity: A high number of zeros and their unequal distribution across items, countries and time. They influence the results of any procedure to build a scale, but especially those using factor analyses. The article shows that zeroes have different meanings: Firstly, there are substantial zeroes in line with saliency theory. Secondly, zeroes exist for non-substantial reasons: The length of a manifesto and the percentage of uncoded sentences, both strongly varying across time and country. We quantify the problem and propose a procedure to identify data points containing non-substantial zeroes. For the future comparative use of the dataset we plead for a theoretical selection of items combined with the information about the likelihood that zeroes are substantially meaningful.
Ion energy spectra of a laser-produced Ta plasma have been investigated as a function of the flight distance from the focus. The laser (Nd:YAG, 20 ns, 210 mJ) is incident obliquely (45°) and focused to an intensity of about 10^11 W cm-2. The changes in the ion distributions have been analysed for the Ta+ to Ta6+ ions in an expansion range 64 - 220 cm. With increasing distance from the target, a weak but monotonic decrease is observed for the total number of ions, which is essentially due to the decrease in the number of the more highly charged species. For the Ta+ and Ta2+ ions the net changes approximately cancel. A more sophisticated picture of the recombination dynamics is obtained, however, if the changes within individual groups of ions expanding with different velocities are compared. Here, in the same spectrum, both increasing and decreasing ion numbers can be observed. This can be interpreted as direct evidence of recombination and its dependence on temperature, density and charge.
The particle flux produced by an obliquely incident Nd Q-switched pulse (20 ns) on a Ta target has been analysed with regard to its angular distribution resolved for both its neutral and ion components. The laser intensity has been varied in the range between about 10^10 - 10^11 W cm-2, which is appropriate for many low-irradiance applications. It is observed that, at all emission angles and for the whole range of laser intensities, the number of neutral species clearly dominates the composition of the particles. At 1.3 x 10^10 W cm-2 the total number of emitted particles is 4 x 10^14, scaling as E_L^¾ with the laser energy. While for relatively low laser energies the angular distribution shows the usual smooth cos-behaviour, an additional strong directive emission cone, superimposed upon the cos-distribution, develops if the laser energy is enhanced. Both the strength and the width strongly depend on the laser intensity. While at lower intensities a fit by a cos^n function with n ~ 10 seems appropriate, n increases to 26 at an intensity of 10^11 W cm-2 . It can be assumed that secondary energy transfer processes that are not yet fully understood are responsible for this anomalous emission.