DIMENSION REDUCTION FOR POWER SYSTEM MODELING USING PCA METHODS CONSIDERING INCOMPLETE DATA READINGS

Principal Component Analysis (PCA) is a popular method for dimension reduction that can be used in many fields including data compression, image processing, exploratory data analysis, etc. However, traditional PCA method has several drawbacks, since the traditional PCA method is not efficient for dealing with high dimensional data and cannot be effectively applied to compute accurate enough principal components when handling relatively large portion of missing data. In this report, we propose to use EM-PCA method for dimension reduction of power system measurement with missing data, and provide a comparative study of traditional PCA and EM-PCA methods. Our extensive experimental results show that EM-PCA method is more effective and more accurate for dimension reduction of power system measurement data than traditional PCA method when dealing with large portion of missing data set.

DEVELOPMENT OF THE ECOCAR 3 PROPOSAL AND GUIDELINES FOR MODELING AND DESIGN IN YEAR ONE OF ECOCAR 3

This report summarizes the work done for the Vehicle Powertrain Modeling and Design Problem Proposal portion of the EcoCAR3 proposal as specified in the Request for Proposal from Argonne National Laboratory. The results of the modeling exercises presented in the proposal showed that: An average conventional vehicle powered by a combustion engine could not meet the energy consumption target when the engine was sized to meet the acceleration target, due the relatively low thermal efficiency of the spark ignition engine. A battery electric vehicle could not meet the required range target of 320 km while keeping the vehicle weight below the gross vehicle weight rating of 2000 kg. This was due to the low energy density of the batteries which necessitated a large, and heavy, battery pack to provide enough energy to meet the range target. A series hybrid electric vehicle has the potential to meet the acceleration and energy consumption parameters when the components are optimally sized. A parallel hybrid electric vehicle has less energy conversion losses than a series hybrid electric vehicle which results in greater overall efficiency, lower energy consumption, and less emissions. For EcoCAR3, Michigan Tech proposes to develop a plug-in parallel hybrid vehicle (PPHEV) powered by a small Diesel engine operating on B20 Bio-Diesel fuel. This architecture was chosen over other options due to its compact design, lower cost, and its ability to provide performance levels and energy efficiency that meet or exceed the design targets. While this powertrain configuration requires a more complex control system and strategy than others, the student engineering team at Michigan Tech has significant recent experience with this architecture and has confidence that it will perform well in the events planned for the EcoCAR3 competition.

A Surface Displacement Analysis for Volcan Pacaya from October 2001 through March 2013 by Means of 3-D Modeling of Precise Position GPS Data

Volcán Pacaya is one of three currently active volcanoes in Guatemala. Volcanic activity originates from the local tectonic subduction of the Cocos plate beneath the Caribbean plate along the Pacific Guatemalan coast. Pacaya is characterized by generally strombolian type activity with occasional larger vulcanian type eruptions approximately every ten years. One particularly large eruption occurred on May 27, 2010. Using GPS data collected for approximately 8 years before this eruption and data from an additional three years of collection afterwards, surface movement covering the period of the eruption can be measured and used as a tool to help understand activity at the volcano. Initial positions were obtained from raw data using the Automatic Precise Positioning Service provided by the NASA Jet Propulsion Laboratory. Forward modeling of observed 3-D displacements for three time periods (before, covering and after the May 2010 eruption) revealed that a plausible source for deformation is related to a vertical dike or planar surface trending NNW-SSE through the cone. For three distinct time periods the best fitting models describe deformation of the volcano: 0.45 right lateral movement and 0.55 m tensile opening along the dike mentioned above from October 2001 through January 2009 (pre-eruption); 0.55 m left lateral slip along the dike mentioned above for the period from January 2009 and January 2011 (covering the eruption); -0.025 m dip slip along the dike for the period from January 2011 through March 2013 (post-eruption). In all bestfit models the dike is oriented with a 75° westward dip. These data have respective RMS misfit values of 5.49 cm, 12.38 cm and 6.90 cm for each modeled period. During the time period that includes the eruption the volcano most likely experienced a combination of slip and inflation below the edifice which created a large scar at the surface down the northern flank of the volcano. All models that a dipping dike may be experiencing a combination of inflation and oblique slip below the edifice which augments the possibility of a westward collapse in the future.

Topological Descriptors in Modeling the HIV Inhibitory Activity of 2-Aryl-3-pyridyl-thiazolidin-4-ones

The HIV-1 RT inhibitory activity of 2-(2,6-dihalophenyl)-3-(substituted pyridin-2-yl)-thiazolidin-4-ones has been analyzed with different topological descriptors obtained from DRAGON software. Here, simple topological descriptors (TOPO), Galvez topological charge indices (GVZ) and 2D autocorrelation descriptors (2DAUTO) have been found to yield good predictive models for the activity of these compounds. The correlations obtained from the TOPO class descriptors suggest that less extended or compact saturated structural templates would be better for the activity. The participating GVZ class descriptors suggest that they have same degree of influence on the activity. In 2DAUTO class, the large participation of descriptors of lags seven and three indicate the association of activity information with the seven and three centered structural fragments of these compounds. The physicochemical weighting components of these descriptors suggest homogeneous influence of mass, volume, electronegativity and/ or polarizability on the activity.

Reductase inhibitory activity of some flavones: Topological descriptors in modeling the activity

In healthy people, glucose is metabolized through Embden-Meyerhoff pathway. In cases of diabetes mellitus, with the increased levels of glucose in insulin-insensitive tissues the Aldose Reductase (AR) in polyol pathway facilitates the conversion of glucose to sorbitol. In this cascade of events the accumulated sorbitol is attributed to be responsible for cataract, neuropathy and retinopathy in diabetic cases.1,2 Thus, the inhibition of AR in polyol pathway may prevent and lead to the cure of the complications arising out of the diabetes mellitus. In this background, Matsuda and coworkers3 studied the AR inhibitory activity of large number of flavones and related compounds from traditional antidiabetic remedies. Here, many of these compounds shared 2-Aryl-benzpyran-4-one as scaffold for different chemical groups surrounding this moiety. This offers scope to investigate the AR inhibitory activity of these compounds in relation to the functional group environment surrounding this core

Age modeling of young non-varved lake sediments: methods and limits. Examples from two lakes in Central Chile

High-resolution and highly precise age models for recent lake sediments (last 100–150 years) are essential for quantitative paleoclimate research. These are particularly important for sedimentological and geochemical proxies, where transfer functions cannot be established and calibration must be based upon the relation of sedimentary records to instrumental data. High-precision dating for the calibration period is most critical as it determines directly the quality of the calibration statistics. Here, as an example, we compare radionuclide age models obtained on two high-elevation glacial lakes in the Central Chilean Andes (Laguna Negra: 33°38′S/70°08′W, 2,680 m a.s.l. and Laguna El Ocho: 34°02′S/70°19′W, 3,250 m a.s.l.). We show the different numerical models that produce accurate age-depth chronologies based on 210Pb profiles, and we explain how to obtain reduced age-error bars at the bottom part of the profiles, i.e., typically around the end of the 19th century. In order to constrain the age models, we propose a method with five steps: (i) sampling at irregularly-spaced intervals for 226Ra, 210Pb and 137Cs depending on the stratigraphy and microfacies, (ii) a systematic comparison of numerical models for the calculation of 210Pb-based age models: constant flux constant sedimentation (CFCS), constant initial concentration (CIC), constant rate of supply (CRS) and sediment isotope tomography (SIT), (iii) numerical constraining of the CRS and SIT models with the 137Cs chronomarker of AD 1964 and, (iv) step-wise cross-validation with independent diagnostic environmental stratigraphic markers of known age (e.g., volcanic ash layer, historical flood and earthquakes). In both examples, we also use airborne pollutants such as spheroidal carbonaceous particles (reflecting the history of fossil fuel emissions), excess atmospheric Cu deposition (reflecting the production history of a large local Cu mine), and turbidites related to historical earthquakes. Our results show that the SIT model constrained with the 137Cs AD 1964 peak performs best over the entire chronological profile (last 100–150 years) and yields the smallest standard deviations for the sediment ages. Such precision is critical for the calibration statistics, and ultimately, for the quality of the quantitative paleoclimate reconstruction. The systematic comparison of CRS and SIT models also helps to validate the robustness of the chronologies in different sections of the profile. Although surprisingly poorly known and under-explored in paleolimnological research, the SIT model has a great potential in paleoclimatological reconstructions based on lake sediments

Modeling Calcium Concentration and Biochemical Reactions

Almost all regions of the brain receive one or more neuromodulatory inputs, and disrupting these inputs produces deficits in neuronal function. Neuromodulators act through intracellular second messenger pathways to influence the electrical properties of neurons, integration of synaptic inputs, spatio-temporal firing dynamics of neuronal networks, and, ultimately, systems behavior. Second messengers pathways consist of series of bimolecular reactions, enzymatic reactions, and diffusion. Calcium is the second messenger molecule with the most effectors, and thus is highly regulated by buffers, pumps and intracellular stores. Computational modeling provides an innovative, yet practical method to evaluate the spatial extent, time course and interaction among second messenger pathways, and the interaction of second messengers with neuron electrical properties. These processes occur both in compartments where the number of molecules are large enough to describe reactions deterministically (e.g. cell body), and in compartments where the number of molecules is small enough that reactions occur stochastically (e.g. spines). – In this tutorial, I explain how to develop models of second messenger pathways and calcium dynamics. The first part of the tutorial explains the equations used to model bimolecular reactions, enzyme reactions, calcium release channels, calcium pumps and diffusion. The second part explains some of the GENESIS, Kinetikit and Chemesis objects that implement the appropriate equations. In depth explanation of calcium and second messenger models is provided by reviewing code, both in XPP, Chemesis and Kinetikit, that implements simple models of calcium dynamics and second messenger cascades.

The MIRELA framework: modeling and analyzing mixed reality applications using timed automata

Mixed Reality (MR) aims to link virtual entities with the real world and has many applications such as military and medical domains [JBL+00, NFB07]. In many MR systems and more precisely in augmented scenes, one needs the application to render the virtual part accurately at the right time. To achieve this, such systems acquire data related to the real world from a set of sensors before rendering virtual entities. A suitable system architecture should minimize the delays to keep the overall system delay (also called end-to-end latency) within the requirements for real-time performance. In this context, we propose a compositional modeling framework for MR software architectures in order to specify, simulate and validate formally the time constraints of such systems. Our approach is first based on a functional decomposition of such systems into generic components. The obtained elements as well as their typical interactions give rise to generic representations in terms of timed automata. A whole system is then obtained as a composition of such defined components. To write specifications, a textual language named MIRELA (MIxed REality LAnguage) is proposed along with the corresponding compilation tools. The generated output contains timed automata in UPPAAL format for simulation and verification of time constraints. These automata may also be used to generate source code skeletons for an implementation on a MR platform. The approach is illustrated first on a small example. A realistic case study is also developed. It is modeled by several timed automata synchronizing through channels and including a large number of time constraints. Both systems have been simulated in UPPAAL and checked against the required behavioral properties.

Impacts of changing climate and land use on vegetation dynamics in a Mediterranean ecosystem: insights from paleoecology and dynamic modeling

Forests near the Mediterranean coast have been shaped by millennia of human disturbance. Consequently, ecological studies relying on modern observations or historical records may have difficulty assessing natural vegetation dynamics under current and future climate. We combined a sedimentary pollen record from Lago di Massacciucoli, Tuscany, Italy with simulations from the LandClim dynamic vegetation model to determine what vegetation preceded intense human disturbance, how past changes in vegetation relate to fire and browsing, and the potential of an extinct vegetation type under present climate. We simulated vegetation dynamics near Lago di Massaciucoli for the last 7,000 years using a local chironomid-inferred temperature reconstruction with combinations of three fire regimes (small infrequent, large infrequent, small frequent) and three browsing intensities (no browsing, light browsing, and moderate browsing), and compared model output to pollen data. Simulations with low disturbance support pollen-inferred evidence for a mixed forest dominated by Quercus ilex (a Mediterranean species) and Abies alba (a montane species). Whereas pollen data record the collapse of A. alba after 6000 cal yr bp, simulated populations expanded with declining summer temperatures during the late Holocene. Simulations with increased fire and browsing are consistent with evidence for expansion by deciduous species after A. alba collapsed. According to our combined paleo-environmental and modeling evidence, mixed Q. ilex and A. alba forests remain possible with current climate and limited disturbance, and provide a viable management objective for ecosystems near the Mediterranean coast and in regions that are expected to experience a mediterranean-type climate in the future.

Modeling the stratospheric warming following the Mt. Pinatubo eruption: uncertainties in aerosol extinctions

In terms of atmospheric impact, the volcanic eruption of Mt. Pinatubo (1991) is the best characterized large eruption on record. We investigate here the model-derived stratospheric warming following the Pinatubo eruption as derived from SAGE II extinction data including recent improvements in the processing algorithm. This method, termed SAGE_4λ, makes use of the four wavelengths (385, 452, 525 and 1024 nm) of the SAGE II data when available, and uses a data-filling procedure in the opacity-induced "gap" regions. Using SAGE_4λ, we derived aerosol size distributions that properly reproduce extinction coefficients also at much longer wavelengths. This provides a good basis for calculating the absorption of terrestrial infrared radiation and the resulting stratospheric heating. However, we also show that the use of this data set in a global chemistry–climate model (CCM) still leads to stronger aerosol-induced stratospheric heating than observed, with temperatures partly even higher than the already too high values found by many models in recent general circulation model (GCM) and CCM intercomparisons. This suggests that the overestimation of the stratospheric warming after the Pinatubo eruption may not be ascribed to an insufficient observational database but instead to using outdated data sets, to deficiencies in the implementation of the forcing data, or to radiative or dynamical model artifacts. Conversely, the SAGE_4λ approach reduces the infrared absorption in the tropical tropopause region, resulting in a significantly better agreement with the post-volcanic temperature record at these altitudes.

Kinetic modeling of sodium in the lunar exosphere

Our knowledge about the lunar environment is based on a large volume of ground-based, remote, and in situ observations. These observations have been conducted at different times and sampled different pieces of such a complex system as the surface-bound exosphere of the Moon. Numerical modeling is the tool that can link results of these separate observations into a single picture. Being validated against previous measurements, models can be used for predictions and interpretation of future observations results. In this paper we present a kinetic model of the sodium exosphere of the Moon as well as results of its validation against a set of ground-based and remote observations. The unique characteristic of the model is that it takes the orbital motion of the Moon and the Earth into consideration and simulates both the exosphere as well as the sodium tail self-consistently. The extended computational domain covers the part of the Earth’s orbit at new Moon, which allows us to study the effect of Earth’s gravity on the lunar sodium tail. The model is fitted to a set of ground-based and remote observations by tuning sodium source rate as well as values of sticking, and accommodation coefficients. The best agreement of the model results with the observations is reached when all sodium atoms returning from the exosphere stick to the surface and the net sodium escape rate is about 5.3 × 1022 s−1.

Building a soil spectral library for Tajikistan comparing local and global modeling approaches

Over the last ~20 years, soil spectral libraries storing near-infrared reflectance (NIR) spectra from diverse soil samples have been built for many places, since almost 10 years also for Tajikistan. Many calibration approaches have been reported and used for prediction from large and heterogeneous libraries, but most are hampered by the high diversity of the soils, where the mineral background is heavily influencing spectral features. In such cases, local learning strategies have the advantage of building locally adapted calibrations, which can deal better with nonlinearities. Therefore, it was our major aim to identify the most efficient approach to develop an accurate and stable locally weigthed calibration model using a spectral library compiled over the past years. Keywords: Tajikistan, Near-Infrared spectroscopy (NIRS), soil organic carbon, locally weighted regression, regional and local spectral library.

Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies.

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.

MODELING REACTIVE GAS UPTAKE, TRANSPORT, AND TRANSFORMATION IN AGGREGATED SOILS

Gas diffusion research in soils covers, to a large extent, the transport behavior of practically insoluble gases. We extend the mathematical description of gas transport to include reactive gaseous components that hydrolyze in water such as SO2 and CO2. The path between the free atmosphere and the microporous niches is modeled by assuming penetration through gas-filled macropores, air-water phase transfer, and diffusion and speciation in the liquid phase. For hydrolyzable gases, the rate of mass transfer into and the total absorption capacity of the soil solution may be high. Both the capacity and the transfer rate are influenced by the soil-solution pH; for high pH, they become extremely high for SO2. The soil absorption of such gases is also influenced by soil structure. Well-aerated, near-neutral soils are a potentially important sink for SO2.