Progression of Wave Breaker Types on a Plane Impermeable Slope, Depending on Experimental Design

M. V. Moragues was supported by the research group TEP-209 (Junta de Andalucia) and by the following projects: "Protection of coastal urban fronts against global warming-PROTOCOL" (917PTE0538), "Integrated verification of the hydrodynamic and structural behavior of a breakwater and its implications on the investment project-VIVALDI" (BIA2015-65598-P). This work was funded by the projects PCI2019-103565-SUSME and PID2019-107509GB-I00-ROMPEOLAS (SRA (State Research Agency)/10.13039/501100011033). M. A. Losada was partially funded by the emeritus professorship mentoring program of the University of Granada. We would like to thank the three reviewers for providing helpful comments on earlier drafts of the manuscript.The objective of this research was to analyze the progression of breaker types on plane impermeable slopes. This study used dimensional analysis to demonstrate the relative water depth is a key explanatory quantity. The dominant breaker types depend on the incident wave characteristics at the foot of the slope. Accordingly, it is possible to combine values of H, T, and m. The physical experiments of Galvin, recent numerical results, and new experiments, performed on an impermeable 1:10 slope, were used to verify the result. It was thus possible to obtain the progression of breaker types in different sequences of pairs of combined wave H and T values. Once a sequence is defined, the expected progression of breaker types is predictable, and is well approximated by the log-transform of the alternate similarity parameter. Since the classification of breaker types is discontinuous, the data assigned to each type were placed in horizontal lines, based on the value of log(chi). Given that the breaking of a wave train on a slope should be considered a continuous process, the location of some data was corrected to satisfy this assumption. There is thus a functional relationship between the sets of the experimental space and of the breaker types. This research also derives the non-dimensional energy dissipation on the slope, considering the wave-reflected energy flux on the slope. It is proportional to a dimensionless bulk dissipation coefficient which depends on the breaker type and, therefore, on the value of chi at the toe of the slope.Junta de Andalucia 917PTE0538 BIA2015-65598-Pemeritus professorship mentoring program of the University of GranadaPCI2019-103565-SUSMEPID2019-107509GB-I00-ROMPEOLAS10.13039/50110001103

An upper limit on hypertriton production in collisions of Ar(1.76 AGeV)+KCl

A high-statistic data sample of Ar(1.76 AGeV)+KCl events recorded with HADES is used to search for a hypertriton signal. An upper production limit per centrality-triggered event of $1.04$ x $10^{-3}$ on the $3\sigma$ level is derived. Comparing this value with the number of successfully reconstructed $\Lambda$ hyperons allows to determine an upper limit on the ratio $N_{_{\Lambda}^3H}/N_{\Lambda}$, which is confronted with statistical and coalescence-type model calculations

Optimized parameter search for large datasets of the regularization parameter and feature selection for ridge regression

In this paper we propose mathematical optimizations to select the optimal regularization parameter for ridge regression using cross-validation. The resulting algorithm is suited for large datasets and the computational cost does not depend on the size of the training set. We extend this algorithm to forward or backward feature selection in which the optimal regularization parameter is selected for each possible feature set. These feature selection algorithms yield solutions with a sparse weight matrix using a quadratic cost on the norm of the weights. A naive approach to optimizing the ridge regression parameter has a computational complexity of the order with the number of applied regularization parameters, the number of folds in the validation set, the number of input features and the number of data samples in the training set. Our implementation has a computational complexity of the order . This computational cost is smaller than that of regression without regularization for large datasets and is independent of the number of applied regularization parameters and the size of the training set. Combined with a feature selection algorithm the algorithm is of complexity and for forward and backward feature selection respectively, with the number of selected features and the number of removed features. This is an order faster than and for the naive implementation, with for large datasets. To show the performance and reduction in computational cost, we apply this technique to train recurrent neural networks using the reservoir computing approach, windowed ridge regression, least-squares support vector machines (LS-SVMs) in primal space using the fixed-size LS-SVM approximation and extreme learning machines

Dynamics of Seed-Borne Rice Endophytes on Early Plant Growth Stages

Bacterial endophytes are ubiquitous to virtually all terrestrial plants. With the increasing appreciation of studies that unravel the mutualistic interactions between plant and microbes, we increasingly value the beneficial functions of endophytes that improve plant growth and development. However, still little is known on the source of established endophytes as well as on how plants select specific microbial communities to establish associations. Here, we used cultivation-dependent and -independent approaches to assess the endophytic bacterrial community of surface-sterilized rice seeds, encompassing two consecutive rice generations. We isolated members of nine bacterial genera. In particular, organisms affiliated with Stenotrophomonas maltophilia and Ochrobactrum spp. were isolated from both seed generations. PCR-based denaturing gradient gel electrophoresis (PCR-DGGE) of seed-extracted DNA revealed that approximately 45% of the bacterial community from the first seed generation was found in the second generation as well. In addition, we set up a greenhouse experiment to investigate abiotic and biotic factors influencing the endophytic bacterial community structure. PCR-DGGE profiles performed with DNA extracted from different plant parts showed that soil type is a major effector of the bacterial endophytes. Rice plants cultivated in neutral-pH soil favoured the growth of seed-borne Pseudomonas oryzihabitans and Rhizobium radiobacter, whereas Enterobacter-like and Dyella ginsengisoli were dominant in plants cultivated in low-pH soil. The seed-borne Stenotrophomonas maltophilia was the only conspicuous bacterial endophyte found in plants cultivated in both soils. Several members of the endophytic community originating from seeds were observed in the rhizosphere and surrounding soils. Their impact on the soil community is further discussed

Multiscale Engine Simulations using a Coupling of 0-D/1-DModel with a 3-D Combustion Code

Requirements for the reduction of both pollutant emissions and fuel consumption mean that there is a need to design of new engine concepts (e.g. HCCI, CAI, etc.). To reduce the time of the development loop for these concepts, 1D approaches can be used to simulate whole-engine behaviour. These approaches are based on phenomenological models that need to be fitted to experimental data. However these data are not always available. One way to solve this problem consists in combining 1D and 3D approaches: 1D simulations are used in the gas exchange system or for the fuel injection system and provide necessary inputs (e.g. volumetric efficiency, thermodynamic state, mixture composition, mass flow rate, etc.) for 3D simulations which are used in the combustion chamber to ensure an accurate description of the combustion process (especially pollutant emissions). This strategy allows us to obtain much more information and should improve the predictivity of the simulation. Two different approaches to carry out this coupling have been developed, the first one is based on the pre-processing of the 3D numerical results to generate combustion maps and the second one used a direct temporal coupling between the 1D and the 3D codes. The two methods are described in this paper. We also report on the relevant engine simulations which were carried out to demonstrate the capabilities of the two coupled approaches