Agarwal, Gaurav; Saade, Stephanie; Shahid, Mohammad; Tester, Mark A.; Sun, Ying(BMC Plant Biology, Springer Science and Business Media LLC, 2019-11-28)[Article]
Background: In plant science, the study of salinity tolerance is crucial to improving plant growth and productivity under saline conditions. Since quantile regression is a more robust, comprehensive and flexible method of statistical analysis than the commonly used mean regression methods, we applied a set of quantile analysis methods to barley field data. We use univariate and bivariate quantile analysis methods to study the effect of plant traits on yield and salinity tolerance at different quantiles. Results: We evaluate the performance of barley accessions under fresh and saline water using quantile regression with covariates such as flowering time, ear number per plant, and grain number per ear. We identify the traits affecting the accessions with high yields, such as late flowering time has a negative impact on yield. Salinity tolerance indices evaluate plant performance under saline conditions relative to control conditions, so we identify the traits affecting the accessions with high values of indices using quantile regression. It was observed that an increase in ear number per plant and grain number per ear in saline conditions increases the salinity tolerance of plants. In the case of grain number per ear, the rate of increase being higher for plants with high yield than plants with average yield. Bivariate quantile analysis methods were used to link the salinity tolerance index with plant traits, and it was observed that the index remains stable for earlier flowering times but declines as the flowering time decreases. Conclusions: This analysis has revealed new dimensions of plant responses to salinity that could be relevant to salinity tolerance. Use of univariate quantile analyses for quantifying yield under both conditions facilitates the identification of traits affecting salinity tolerance and is more informative than mean regression. The bivariate quantile analyses allow linking plant traits to salinity tolerance index directly by predicting the joint distribution of yield and it also allows a nonlinear relationship between the yield and plant traits.
Peng, Chi-Han; Jiang, Caigui; Wonka, Peter; Pottmann, Helmut(ACM Transactions on Graphics, Association for Computing Machinery (ACM), 2019-11-08)[Article]
Checkerboard patterns with black rectangles can be derived from quad meshes with orthogonal diagonals. First, we present an initial theoretical analysis of these quad meshes. The analysis reveals many possible applications in geometry processing and also motivates the numerical optimization for aesthetic and functional checkerboard pattern design. Second, we describe an optimization algorithm that transforms initial 2D and 3D quad meshes into quad meshes with orthogonal diagonals. Third, we present a 2D checkerboard pattern design framework based on integer programming inspired by the logo design of the 2020 Olympic games. Our results show a variety of 2D and 3D checkerboard patterns that can be derived from 2D or 3D quad meshes with orthogonal diagonals.
Detecting anomalies in a robot swarm play a core role in keeping the desired performance, and meeting requirements and specifications. This letter deals with the problem of detecting anomalies in a robot swarm. In this regards, an unsupervised monitoring approach based on principal component analysis and k-nearest neighbor is proposed. The principal component analysis model is employed to generate residuals for anomaly detection. Then, the residuals are examined by computing the proposed exponentially smoothed k-nearest neighbor statistic for the purpose of anomaly detection. Here, instead of using parametric thresholds derived based on the Gaussian distribution, a nonparametric decision threshold is computed using the kernel density estimation method. This provides more flexibility to the proposed detector by relaxing assumption on the distribution underlying the data. Tests on data from ARGoS simulator show efficient performance of the proposed mechanism in monitoring a robot swarm.
Sun, Rui; Subramanian, Aneesh C.; Miller, Arthur J.; Mazloff, Matthew R.; Hoteit, Ibrahim; Cornuelle, Bruce D.(Geoscientific Model Development, Copernicus GmbH, 2019-10-08)[Article]
A new regional coupled ocean-atmosphere model is developed and its implementation is presented in this paper. The coupled model is based on two open-source community model components: the MITgcm ocean model and the Weather Research and Forecasting (WRF) atmosphere model. The coupling between these components is performed using ESMF (Earth System Modeling Framework) and implemented according to National United Operational Prediction Capability (NUOPC) protocols. The coupled model is named the Scripps-KAUST Regional Integrated Prediction System (SKRIPS). SKRIPS is demonstrated with a real-world example by simulating a 30 d period including a series of extreme heat events occurring on the eastern shore of the Red Sea region in June 2012. The results obtained by using the coupled model, along with those in forced stand-alone oceanic or atmospheric simulations, are compared with observational data and reanalysis products. We show that the coupled model is capable of performing coupled ocean-atmosphere simulations, although all configurations of coupled and uncoupled models have good skill in modeling the heat events. In addition, a scalability test is performed to investigate the parallelization of the coupled model. The results indicate that the coupled model code scales well and the ESMF/NUOPC coupler accounts for less than 5% of the total computational resources in the Red Sea test case. The coupled model and documentation are available at https://library.ucsd.edu/dc/collection/bb1847661c (last access: 26 September 2019), and the source code is maintained at https://github.com/iurnus/scripps-kaust-model (last access: 26 September 2019).
Jaber, Nizar; Ilyas, Saad; Younis, Mohammad I.(IEEE, 2019-08-22)[Conference Paper]
Performing Boolean operations using conventional CMOS-based computers requires the wiring of multiple transistors. Hence, the processors of these computers are composed of millions of transistors, which increase the device size and power consumption. Here, we present a single MEMS resonator that can execute in parallel multiple logic gates. The concept is based on simultaneously encoding the binary information at different modes of vibration of a microplate. The proposed novel method allows the device not only to perform as a fully integrated logic gate but also as a parallel logic processor for which the same device can perform multiple logic gates simultaneously. The proposed method decreases the device footprint and reduces the power consumption required to perform multiple Boolean functions.
Ahmed, Waqas Waseem; Herrero, Ramon; Botey, Muriel; Wu, Ying; Staliunas, Kestutis(Optics Letters, OSA - The Optical Societycustserv@osa.org, 2019-08-06)[Article]
We propose a novel physical mechanism based on periodic non-Hermitian potentials to efficiently control the complex spatial dynamics of broad-area lasers, particularly in vertical-cavity surface-emitting lasers (VCSELs), achieving a stable emission of maximum brightness. A radially dephased periodic refractive index and gain-loss modulations accumulate the generated light from the entire active layer and concentrate it around the structure axis to emit narrow, bright beams. The effect is due to asymmetric inward radial coupling between transverse wave vectors for particular phase differences of the refractive index and gain-loss modulations. Light is confined into a central beam with large intensity, opening the path to design compact, bright, and efficient broad-area light sources. We perform a comprehensive analysis to explore the maximum central intensity enhancement and concentration regimes. This Letter reveals that the optimum schemes are those holding unidirectional inward coupling, but not fulfilling a perfect local PT-symmetry.
Ferreira, Rita; Gomes, Diogo A.; Tada, Teruo(Proceedings of the American Mathematical Society, American Mathematical Society (AMS), 2019-07-24)[Article]
In this paper, we study first-order stationary monotone meanfield games (MFGs) with Dirichlet boundary conditions. Whereas Dirichlet conditions may not be satisfied for Hamilton-Jacobi equations, here we establish the existence of solutions to MFGs that satisfy those conditions. To construct these solutions, we introduce a monotone regularized problem. Applying Schaefer's fixed-point theorem and using the monotonicity of the MFG, we verify that there exists a unique weak solution to the regularized problem. Finally, we take the limit of the solutions of the regularized problem and, using Minty's method, we show the existence of weak solutions to the original MFG.
Boukaram, Wagih Halim; Turkiyyah, George; Keyes, David E.(SIAM Journal on Scientific Computing, Society for Industrial & Applied Mathematics (SIAM), 2019-07-09)[Article]
Randomized algorithms for the generation of low rank approximations of large dense matrices have become popular methods in scientific computing and machine learning. In this paper, we extend the scope of these methods and present batched GPU randomized algorithms for the efficient generation of low rank representations of large sets of small dense matrices, as well as their generalization to the construction of hierarchically low rank symmetric H2 matrices with general partitioning structures. In both cases, the algorithms need to access the matrices only through matrix-vector multiplication operations which can be done in blocks to increase the arithmetic intensity and substantially boost the resulting performance. The batched GPU kernels are adaptive, allow nonuniform sizes in the matrices of the batch, and are more effective than SVD factorizations on matrices with fast decaying spectra. The hierarchical matrix generation consists of two phases, interleaved at every level of the matrix hierarchy. A first phase adaptively generates low rank approximations of matrix blocks through randomized matrix-vector sampling. A second phase accumulates and compresses these blocks into a hierarchical matrix that is incrementally constructed. The accumulation expresses the low rank blocks of a given level as a set of local low rank updates that are performed simultaneously on the whole matrix allowing high-performance batched kernels to be used in the compression operations. When the ranks of the blocks generated in the first phase are too large to be processed in a single operation, the low rank updates can be split into smaller-sized updates and applied in sequence. Assuming representative rank k, the resulting matrix has optimal O(kN) asymptotic storage complexity because of the nested bases it uses. The ability to generate an H2 matrix from matrix-vector products allows us to support a general randomized matrix-matrix multiplication operation, an important kernel in hierarchical matrix computations. Numerical experiments demonstrate the high performance of the algorithms and their effectiveness in generating hierarchical matrices to a desired target accuracy.
Hawerkamp, Heike C; Kislat, Andreas; Gerber, Peter A; Pollet, Marius; Rolfes, Katharina M; Soshilov, Anatoly A; Denison, Michael S; Momin, Afaque Ahmad Imtiyaz; Arold, Stefan T.; Datsi, Angeliki; Braun, Stephan A; Oláh, Péter; Lacouture, Mario E; Krutmann, Jean; Haarmann-Stemmann, Thomas; Homey, Bernhard; Meller, Stephan(Allergy, Wiley, 2019-07-03)[Article]
BACKGROUND:In recent years, the BRAF-inhibitor vemurafenib has been successfully established in the therapy of advanced melanoma. Despite its superior efficacy, the use of vemurafenib is limited by frequent inflammatory cutaneous adverse events that affect patients' quality of life and may lead to dose reduction or even cessation of anti-tumor therapy. To date, the molecular and cellular mechanisms of vemurafenib-induced rashes have remained largely elusive. METHODS:In this study we deployed immunohistochemistry, RT-qPCR, flow cytometry, lymphocyte activation tests and different cell-free protein-interaction assays. RESULTS:We here demonstrate that vemurafenib inhibits the downstream signaling of the canonical pathway of aryl hydrocarbon receptor (AhR) in vitro, thereby inducing the expression of proinflammatory cytokines (e.g. TNF) and chemokines (e.g. CCL5). In line with these results we observed an impaired expression of AhR regulated genes (e.g. CYP1A1) and an upregulation of the corresponding proinflammatory genes in vivo. Moreover, results of lymphocyte activation tests showed the absence of drug-specific T cells in respective patients. CONCLUSION:Taken together, we obtained no hint of an underlying sensitization against vemurafenib but found evidence suggesting that vemurafenib enhances proinflammatory responses by inhibition of canonical AhR signaling. Our findings contribute to our understanding of the central role of the AhR in skin inflammation and may point towards a potential role for topical AhR agonists in supportive cancer care. This article is protected by copyright. All rights reserved.
Acinas, Silvia G.; Sánchez, Pablo; Salazar, Guillem; Cornejo-Castillo, Francisco M.; Sebastián, Marta; Logares, Ramiro; Sunagawa, Shinichi; Hingamp, Pascal; Ogata, Hiroyuki; Lima-Mendez, Gipsi; Roux, Simon; González, José M.; Arrieta, Jesús M.; Alam, Intikhab S.; Kamau, Allan; Bowler, Chris; Raes, Jeroen; Pesant, Stéphane; Bork, Peer; Agusti, Susana; Gojobori, Takashi; Bajic, Vladimir B.; Vaqué, Dolors; Sullivan, Matthew B.; Pedrós-Alió, Carlos; Massana, Ramon; Duarte, Carlos M.; Gasol, Josep M.(Cold Spring Harbor Laboratory, 2019-05-14)[Preprint]
The deep sea, the largest compartment of the ocean, is an essential component of the Earth system, but the functional exploration of its microbial communities lags far behind that of other marine realms. Here we analyze 58 bathypelagic microbial metagenomes from the Atlantic, Indian, and Pacific Oceans in an unprecedented sampling effort from the Malaspina Global Expedition, to resolve the metabolic architecture of the deep ocean microbiome. The Malaspina Deep-Sea Gene Collection, 71% of which consists of novel genes, reveals a strong dichotomy between the functional traits of free-living and particle-attached microorganisms, and shows relatively patchy composition challenging the paradigm of a uniform dark ocean ecosystem. Metagenome Assembled Genomes uncovered 11 potential new phyla, establishing references for deep ocean microbial taxa, and revealed mixotrophy to be a widespread trophic strategy in the deep ocean. These results expand our understanding of the functional diversity, metabolic versatility, and carbon cycling in the largest ecosystem on Earth.
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