• Integration Strategy for Heterogeneously Integrated Wearable and Implantable Electronics

      Hussain, Muhammad Mustafa (IEEE, 2019-01-09)
      We live in a world where electronics play critical enabling role. Specifically, matured and advanced CMOS technology with its arts and science of miniaturization has propelled variety of CMOS devices to a level where their lofty performance over cost benefit has ushered into a wide range of application spectrum ranging from computers to display to today's home automation. Going forward we may want to ask ourselves a few important questions: 1. Can CMOS technology be expanded further to add new functionalities to CMOS devices while retaining their existing attributes in tact? 2. Whether this exercise will have a better functionalities over cost metric? 3. If the first two questions are addressed well, whether the existing applications will be strengthened and/or diversified? Whether new applications may emerge?
    • Uncertainty quantification of groundwater contamination

      Litvinenko, Alexander; Logashenko, Dmitry (2018-10-08)
      In many countries, groundwater is the strategic reserve, which is used as drinking water and as an irrigation resource. Therefore, accurate modeling of the pollution of the soil and groundwater aquifer is highly important. As a model, we consider a density-driven groundwater flow problem with uncertain porosity and permeability. This problem may arise in geothermal reservoir simulation, natural saline-disposal basins, modeling of contaminant plumes and subsurface flow. This strongly non-linear problem describes how salt or polluted water streams down building ''fingers". The solving process requires a very fine unstructured mesh and, therefore, high computational resources. Consequently, we run the parallel multigrid solver UG4 (https://github.com/UG4/ughub.wiki.git) on Shaheen II supercomputer. The parallelization is done in both - the physical space and the stochastic space. The novelty of this work is the estimation of risks that the pollution will achieve a specific critical concentration. Additionally, we demonstrate how the multigrid UG4 solver can be run in a black-box fashion for testing different scenarios in the density-driven flow. We solve Elder's problem in 2D and 3D domains, where unknown porosity and permeability are modeled by random fields. For approximations in the stochastic space, we use the generalized polynomial chaos expansion. We compute different quantities of interest such as the mean, variance and exceedance probabilities of the concentration. As a reference solution, we use the solution, obtained from the quasi-Monte Carlo method.
    • Ultraviolet FSO to laser-based VLC – the role of group-III-nitride devices

      Ooi, Boon S.; Sun, Xiaobin; Shen, Chao; Guo, Yujian; Liu, Guangyu; Ng, Tien Khee (2018-10-04)
    • Overview of Low-rank and Sparse Techniques in Spatial Statistics and Parameter Identification

      Litvinenko, Alexander (2018-10-03)
      Motivation: improve statistical model by implementing more efficient numerical tools Major Goal: Develop new statistical tools to address new problems. Overview: Low-rank matrices, Sparse matrices, Hierarchical matrices. Approximation of Matern covariance functions and joint Gaussian likelihood, Identification of unknown parameters via maximizing Gaussian log-likelihood, Low-rank tensor methods
    • Multilevel Monte Carlo Acceleration of Seismic Wave Propagation under Uncertainty

      Ballesio, Marco; Beck, Joakim; Pandey, Anamika; Parisi, Laura; von Schwerin, Erik; Tempone, Raul (2018-09-06)
      We consider forward seismic wave propagation in an inhomogeneous linear viscoelastic media with random wave speeds and densities, subject to deterministic boundary and initial conditions. We study this forward problem as a first step towards the treatment of inverse problems. There the goal is to determine, for example, earthquake source locations from seismograms recorded in a small number of seismic sensors at the Earth’s surface. Existing results on earthquake source inversion for a given event show a large variability, which indicates that the inherent uncertainty of the Earth parameters should be taken into account. Here this uncertainty is modeled through random parameters. We propose multilevel Monte Carlo simulations for computing statistics of quantities of interest which are motivated by the choice of loss function for the corresponding inverse problem, presenting a case study based on experimental seismic data from a passive experiment in Tanzania. This work provides a benchmark for the implementation of multilevel algorithms to accelerate seismic inversion addressing earthquake source estimation as well as inferring Earth structure.
    • Multilevel ensemble Kalman filtering for spatio-temporal processes

      Hoel, Hakon; Chernov, Alexey; Law, Kody; Nobile, Fabio; Tempone, Raul (2018-07-04)
      The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of the classical Monte Carlo method, which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this talk I will present ideas on combining MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite and infinite dimensional state spaces. Theoretical results and numerical studies of the performance gain of MLEnKF over EnKF will also be presented. (Joint work with Alexey Chernov, Kody J. H. Law, Fabio Nobile, and Raul Tempone.) References: [1] H. Hoel, K. Law, and R. lTempone(2016). Multilevelensemble Kalman filtering. SIAM J. Numer. Anal. 54(3), 1813–1839. [2] A. Chernov, H. Hoel, K. Law, F. Nobile, and R. Tempone (2016). Multilevel ensemble Kalman filtering for spatially extended models. ArXiv e-prints. arXiv: 1608.08558 [math.NA].
    • Integrative Approach Toward Revealing and Understanding Complexity of Root System Architecture in Date Palm

      Blilou, Ikram (2018-06-22)
      The evolution from the primordial aquatic organisms to vascular terrestrial plants has been accompanied by increasing complexity in the structure and functions of their vegetative and reproductive organs. Plants have undergone dramatic changes in their root systems to adapt to terrestrial life. The development of complex diverse root architectures gave plants the advantage ability to colonize new and particularly arid and dry environments. Date palm Phoenix dactylifera fruits are known for their high nutritive, economic and social values. In arid and semi-arid areas, it plays an impor-tant role in affecting the microclimate by creating a microsystem allowing desert farming. Understanding the properties of growth and development in date palm is an essential step towards gaining insights as to how plants have evolved their strategies to cope with changes in their surrounding and survive in chal-lenged habitats like the desert. To unravel the under-lying mechanisms of date palm adaptation to desert conditions we conducted a detailed analysis of date palm anatomy during different stages of develop-ment from germination to adult plants. Using the art of state imaging technologies, we unraveled new devel-opmental mechanisms in date palm occurring during germination, plant growth and development. MicroCT Xray imaging technology combined with high resolu-tion microscopy revealed that date palm roots bear structures that have not been previously described. Some of these structures are conserved only among desert palm species. In addition, a comparative stud-ies of date palm cultivars originated from different geographical habitat, Tunisia, UAE and KSA and hav-ing distinct levels of tolerance to soil salinity revealed substantial differences in root system architecture.
    • Adaptive Strategies in Date Palm Revealed by Confocal Imaging Technologies

      Xiao, Ting Ting; Blilou, Ikram (2018-06-22)
      Date palm are confronted by harsh environmental conditions and have therefore adapted various strat-egies to survive the hostile environment. To unravel the underlying mechanisms of adaptation to desert conditions we conducted a detailed analysis of date palm tissue anatomy at different developmental stag-es. Using confocal imaging we reveal new anatomical features and complex structures in roots, shoot and leaves explaining strategies of adaptation of date palm to desert conditions.
    • Role of library's subscription licenses in promoting open access to scientific research

      Buck, Stephen (2018-04-30)
      This presentation, based on KAUST’’s experience to date, will attempt to explain the different ways of bringing Open Access models to scientific Publisher’s licenses. Our dual approach with offset pricing is to redirect subscription money to publishing money and embed green open access deposition terms in understandable language in our license agreements. Resolving the inherent complexities in open access publishing, repository depositions and offsetting models will save libraries money and also time wasted on tedious and unnecessary administration work. Researchers will also save their time with overall clarity and transparency. This will enable trust and, where mistakes are made, and there inevitably will be with untried models, we can learn from these mistakes and make better, more robust services with auto deposition of our articles to our repository fed by Publishers’ themselves. The plan is to cover all Publishers with OA license terms for KAUST author’s right while continuing our subscription to them. There are marketing campaigns, awareness sessions are planned, in addition to establishing Libguides to help researchers, in addition to manage offset pricing models.
    • Tucker tensor analysis of Matern functions in spatial statistics

      Litvinenko, Alexander (2018-04-20)
      Low-rank Tucker tensor methods in spatial statistics 1. Motivation: improve statistical models 2. Motivation: disadvantages of matrices 3. Tools: Tucker tensor format 4. Tensor approximation of Matern covariance function via FFT 5. Typical statistical operations in Tucker tensor format 6. Numerical experiments
    • Application of Parallel Hierarchical Matrices in Spatial Statistics and Parameter Identification

      Litvinenko, Alexander (2018-04-20)
      Parallel H-matrices in spatial statistics 1. Motivation: improve statistical model 2. Tools: Hierarchical matrices [Hackbusch 1999] 3. Matern covariance function and joint Gaussian likelihood 4. Identification of unknown parameters via maximizing Gaussian log-likelihood 5. Implementation with HLIBPro
    • Exploring off-set pricing models and article deposit terms at King Abdullah University of Science & Technology (KAUST)

      Buck, Stephen; Vijayakumar, J.K. (2018-04-09)
      In the ‘normal’ world of retail and commerce you pay for an item and receive the item. In the world of academic journals you prepay for the item and you might receive the item and you might get some money back depending on what journals you did or didn’t receive. In the world of offset pricing you prepay, then you pay again, you sometimes use vouchers, you might get a discount (the following year) then you might get money back, or you might not. Are publishers knowingly placing barriers to off-set models, and not transparently offsetting the APCs to the subscription cost, in order to raise more income? Whether by design or accident it is a complex world which needs a time commitment, which not all librarians can give, to understand fully. The new model of scholarly communication, which leading universities (including KAUST) want to introduce, is based on shifting the subscription costs to publishing costs, not to double the payment channels to the publishers. Can we get to a mutually beneficial position where the author can deposit the accepted version of the article into the Institutional Repository without any embargo period as the institute is agreeing to pay the subscription fee on an ongoing basis? The required model does not adversely affect the vendors’ revenue. This presentation, based on KAUST’’s experience to date, will attempt to explain the different models of offset pricing while outlining KAUST’s dual approach, redirecting subscription money to publishing money and embedding open access terms in understandable language in our license agreements, to the problem. Why we have accepted IoP’s offset offer and not Springer’s, though we were considered among the first timers and important Institutions? Why is this important? Resolving the inherent complexities in offsetting models will save libraries money and also time wasted on tedious and unnecessary administration work. Researchers do not want to know about offsetting agreements nor should they need to know. It is difficult enough to do and write up valuable research without having to do further research on offset pricing models. The authors of the articles without whom, as academic librarians or publishers, we would be redundant are often the neglected link in the chain. Finally, the Institutional Repository needs to know what we are up to. The current answer to many queries is that “it depends on the publisher,” isn’t good enough. There has to be a standard model. What is needed overall is clarity and transparency. This will enable trust and, where mistakes are made, and there inevitable will be with untried models, we can learn from these mistakes and make better, more robust services with auto deposition of our articles to our repository fed by Publishers’ themselves . If libraries can organize as groups at regional or (with more difficulty) international level more favorable licensing agreements, including standardized offset pricing model language, can be leveraged which will be advantageous to all parties; publishers, libraries and, most importantly, authors. It is incumbent that we familiarize ourselves with the pricing models, in all their complexity, and strive through collective organization to have these models simplified and standardized. Let’s turn that subscription money into publishing money.
    • Application of Parallel Hierarchical Matrices and Low-Rank Tensors in Spatial Statistics and Parameter Identification

      Litvinenko, Alexander (2018-03-12)
      Part 1: Parallel H-matrices in spatial statistics 1. Motivation: improve statistical model 2. Tools: Hierarchical matrices 3. Matern covariance function and joint Gaussian likelihood 4. Identification of unknown parameters via maximizing Gaussian log-likelihood 5. Implementation with HLIBPro. Part 2: Low-rank Tucker tensor methods in spatial statistics
    • Research Data Management - Building Service Infrastructure and Capacity

      Baessa, Mohamed A.; Mastoraki, Eirini; Grenz, Daryl M. (2018-03-07)
      Research libraries support the missions of their institutions by facilitating the flow of scholarly information to and from the institutions’ researchers. As research in many disciplines becomes more data and software intensive, libraries are finding that services and infrastructure developed to preserve and provide access to textual documents are insufficient to meet their institutions’ needs. In response, libraries around the world have begun assessing the data management needs of their researchers, and expanding their capacity to meet the needs that they find. This discussion panel will discuss approaches to building research data management services and infrastructure in academic libraries. Panelists will discuss international efforts to support research data management, while highlighting the different models that universities have adopted to provide a mix of services and infrastructure tailored to their local needs.
    • Uncertainty Quantification - an Overview

      Litvinenko, Alexander (2018-03-01)
      1. Introduction to UQ 2. Low-rank tensors for representation of big/high-dimensional data 3. Inverse Problem via Bayesian Update 4. R-INLA and advance numerics for spatio-temporal statistics 5. High Performance Computing, parallel algorithms
    • Multilevel ensemble Kalman filtering for spatially extended models

      Hoel, Hakon; Chernov, Alexey; Law, Kody JH; Nobile, Fabio; Tempone, Raul (2018-01-10)
      The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of the classical Monte Carlo method, which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this talk I will present ideas on combining MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite and infinite dimensional state spaces. Theoretical results and numerical studies of the performance gain of MLEnKF over EnKF will also be presented. (Joint work with Alexey Chernov, Kody J. H. Law, Fabio Nobile, and Raul Tempone.)
    • Functional consequences of brain glycogen deficiency on the sleep-wake cycle regulation in PTG-KO mice

      Burlet-Godinot, S.; Allaman, I.; Grenningloh, G.; Roach, P.J.; Depaoli-Roach, A.A.; Magistretti, Pierre J.; Petit, J.-M. (Elsevier BV, 2017-12-31)
      Introduction: In the CNS, glycogen is mainly localized in astrocytes where its levels are linked to neuronal activity. Astrocytic glycogen synthesis is regulated by glycogen synthase (GS) activity that is positively controlled by protein targeting to glycogen (PTG) expression levels. Although the role of glycogen in sleep/wake regulation is still poorly understood, we have previously demonstrated that, following a 6 hour gentle sleep deprivation (GSD), PTG mRNA expression and GS activity increased in the brain in mice while glycogen levels were paradoxically maintained and not affected. In order to gain further insight on the role of PTG in this process, we studied the sleep/wake cycle parameters in PTG knockout (PTG-KO) mice under baseline conditions and after a 6 hour GSD. Glycogen levels as well as mRNAs expression of genes related to energy metabolism were also determined in several brain areas. Materials and methods: Adult male C57BL/6J (WT) and PTG-KO mice were sleep-recorded under baseline conditions (24 h recordings, 12 h light/dark cycle) and following 6 hours GSD from ZT00 to ZT06. Vigilance states were visually scored (4 s temporal window). Spectral analysis of the EEG signal was performed using a discrete Fourier transformation. Glycogen measurements and gene expression analysis were assessed using a biochemical assay and quantitative RT-PCR respectively, on separate cohorts in WT vs PTG-KO mice at the end of the 6 hours GSD or in control animals (CTL) in different brain structures. Results: Quantitative analysis of the sleep/wake cycle under baseline conditions did not reveal major differences between the WT and the PTG-KO mice. However, during the dark period, the PTG-KO mice showed a significant increase in the number of wake and slow wave sleep episodes (respectively +26.5±8% and +26.1±8%; p< 0.05) together with a significant shortening in their duration (-21.6±7.2% and -14.3±2.8%; p< 0.01). No such quantitative changes were observed during paradoxical sleep (PS). However, the spectral analysis of PS indicated that there was a significant increase of the spectral power between 7 and 8.5 Hz in PTG-KO compared to WT mice. As expected, SD did not affect brain glycogen content in WT mice even though a 20 to 90% increase in PTG mRNA expression was measured depending on the brain structure analyzed. PTG KO mice displayed an 80% decrease in brain glycogen content compared to WT under control conditions with no further decrease after GSD. Conclusions: Although, it is unlikely that PTG contributes to the maintenance of glycogen levels during SD, the deletion of its gene resulted in EEG modifications of the theta band during the PS under baseline conditions and the absence of a significant PS rebound after GSD. The results provide the first evidence for a role of PTG in sleep and wakefulness, specifically in the regulation of PS, which warrants further investigation.
    • Strategies for the design of functional MOFs: addressing energy-intensive separations

      Eddaoudi, Mohamed (International Union of Crystallography (IUCr), 2017-12-19)
      Metal Organic Frameworks (MOFs) are a promising class of crystalline solid-state materials amenable to tailoring their porosity and functionality towards various applications. MOF reticular chemistry using the Molecular Building Block (MBB) approach offers potential to construct robust made-to-order MOFs, where desired structural and geometrical information are incorporated into the building blocks prior to the assembly process. We will discuss two recently implemented conceptual approaches facilitating the design and deliberate construction of metal–organic frameworks (MOFs), namely supermolecular building block (SBB) and supermolecular building layer (SBL) approaches. Additionally, the concept of net-coded building units (net-cBUs), where precise embedded geometrical information codes uniquely and matchlessly a selected net, as a compelling route for the rational design of MOFs will be presented. Our progress in the development of functional metal-organic frameworks (MOFs) to address some energy-intensive separations will be discussed. Namely, the successful practice of reticular chemistry affording the fabrication of various stable MOFs with controlled pore-aperture size and allowing effective separation of various gas or vapors pairs.