PNNL-13501 - Pacific Northwest National Laboratory

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Source Building Release Observed release Predicted release Speculated release Retrospective release Detection & Characterization Is it there? What is it? How much is there? Walton GN. 1997. CONTAM96--User Manual, NISTIR 5385, <strong>National</strong> Institute of Standards and Technology. Numerous open literature publications on building air flow design and measurement (a specific list is available upon request) Numerous publications on properties and health effects of sarin and anthrax primarily from the Defense Technical Dispersion Persistence Exposure Health Effects W here is it? W here does it go? W hat/where conc.? Measure Model calibrate models with measurements How long does it last? Conditions affecting its persistence? Information Center (DTIC) Unclassified Information (a specific list is available upon request). Publication W ho is exposed? How long are they exposed? Delivered Dose? Effective Dose? Exposure settings? W hat are its health effects? Any anti-bodies to kill it? Emergency medical treatment? Preventive measures? Exposure Management How much can be safely tolerated? How long can it be tolerated? Are there levels of effect? Figure 1. Components and overall design of the nuclear, biological, and chemical health assessment system for indoor air Figure 2. Churchville test facility – measured and simulated responses to 10-min release (solid=measured, dotted=simulated – concentration trajectory legend is keyed to room number) – Note outdoor air intakes near right end of long facing wall Figure 3. FRAMES system layout for model and health effect database integration 0.1 0.01 0.001 0.0001 CHVCC01B.XLS 1 2 3 8 13 15 3up 1 8 15 2 13 0:00 0:05 0:10 0:15 0:20 0:25 0:30 0:35 0:40 0:45 0:50 Tim e from release (m in utes) Figure 4. FRAMES output format for system results Armstrong PR, DL Hadley, RD Stenner, and MC Janus. Whole-Building Airflow Network Characterization by Inverse Modeling, TC4.10 Symposium: Nodal IAQ/Dispersion Model Validation, Paper submitted to ASHRAE for publication in the ASHRAE Transactions. Human Health and Safety 293
Mechanistic Modeling of Early Genotoxic Events for Chemicals and Radiation Study Control Number: PN00064/1471 Robert D. Stewart Mechanistic models are needed to improve our understanding of, and ability to predict and mitigate, the human health effects of exposure to hazardous agents found at many DOE facilities, such as tritium, beryllium, and organic solvents. Our project will advance the state of the art in mechanistic modeling of early biophysical events involved in the development of cancer. Project Description This project has two main goals: 1) develop a scalable and extensible modeling framework to bridge the gap between dosimetry and early events involved in the pathogenesis of cancer, and 2) perform the initial work needed to demonstrate the feasibility of using detailed molecular and cellular models to predict dose-response effects at the organ and tissue levels. A calculational framework to integrate molecular and cellular dose-response models into three-dimensional tissue constructs has been developed. As a high-impact way to illustrate how such modeling tools might be used to study the effects of complicated workplace or environmental exposures, we used our modeling tools to examine ways that the temporal and spatial delivery of radiation to a tumor could be manipulated to improve treatment outcome. Introduction Genotoxic chemical agents and ionizing radiation create a multitude of different types of DNA damages. Regardless of the process or agent that initially creates the DNA damage, the same basic physiochemical and biochemical processes either correctly repair the damage or convert the damage into a lethal or nonlethal point mutation or chromosome aberration. Because of cellular adaptations in damage repair and effects associated with, for example, the mitotic cell cycle, the expected number of point mutations and chromosome aberrations created in a cell is a complicated and generally nonlinear function of a cell’s exposure history. Two fundamental questions that must be answered in order to quantitate the health risks associated with human exposure to man-made physical and chemical agents are: “How many and what kinds of abnormal genetic 294 FY 2000 <strong>Laboratory</strong> Directed Research and Development Annual Report alterations are created in a cell per unit dose of the agent?” and “How many of these randomly created genetic alterations does it take to transform a normal cell into one capable of producing a cancer?” The central aim of this project is to help answer these questions by advancing the state of the art in mechanistic modeling of DNA damage formation, repair, and misrepair processes. Moreover, this project aims to better link these fundamental processes to cell transformation and killing effects in vitro and in vivo. Results and Accomplishments A major focus of the project this year has been to develop the scalable and extensible software tools needed to integrate molecular and cellular models into more realistic three-dimensional organ, tissue, and tumor models. We have also further refined our model calibration and testing strategy. From Molecules to Man: Three-Dimensional Tissue Modeling In our modeling approach, an organ, tissue, or tumor is first subdivided into a large number of smaller, rectangular tissue regions. Then, we use a molecular and cellular dose-response model to simulate the life history of a large number of cells (and their progeny) in each tissue region. Biophysical response quantities of interest such as the yield of lethal and nonlethal genetic alterations in critical subpopulations (stem cells) or in certain regions of the tissue can then be computed from the life histories of the individual cells. The main advantage of this ab initio approach is that the degree of realism in the tissue model is ultimately only limited by our computing capabilities, our understanding of intra- and intercellular biophysical processes, and the availability of appropriate experimental datasets for use as model inputs and in model testing.
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Laboratory Directed Research and De
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Laboratory Directed Research and De
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Computational Science and Engineeri
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Policy and Management Sciences Asse
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Introduction Department of Energy O
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5. After reviews by the Technical a
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• The Technical Council peer revi
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methods applicable to combustion, s
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Summary Each national laboratory mu
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Study Control Number: PN0004/1411 A
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Table 1. Positive and negative ions
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m/z Arbitrary Units Figure 1. Mass
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introduce low-volatility compounds
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arrangement, but the charge is reta
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two liquid chromatographic gradient
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Integrated Microfabricated Devices
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Matrix Assisted Laser Desorption/Io
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Molecular Beam Synthesis and Charac
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temperature distribution of the des
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expected to result in significant a
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Study Control Number: PN99069/1397
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Seuss DT and KA Prather. 1999. “M
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Analysis of Receptor-Modulated Ion
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laboratory (Lu and Xie 1997; Lu et
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Automated DNA Fingerprinting Microa
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Comparison of 4 Xanthomonas Isolate
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Approach Hematopoietic (bone marrow
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Anti-Human lgG Human lgG Protein G
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Characterization of Global Gene Reg
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PCR products for immobilization on
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identify novel proteins of importan
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Immunoprecipitaton of tyrosinephosp
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Coupled NMR and Confocal Microscopy
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In the optical microscopy image, th
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Development and Applications of a M
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Figure 3. Hepa-1 cells undergoing a
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cellular processing (such as post-t
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8. Initial demonstration of an off-
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expression systems for several year
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accumulation of protein products, i
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Fungal Conversion of Agricultural W
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Fungal Conversion of Waste Glucose/
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Summary and Conclusions We demonstr
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are shown in Figure 1(a) and 1(b),
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Anchorage-Independent Growth (% con
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selection of seedlings demonstratin
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NMR-Based Structural Genomics Micha
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Solution-State Structure and Fold-C
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Plant Root Exudates and Microbial G
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98 99 100 6 7 10 3 1 12 11 15 16 17
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Summary and Conclusions • The gre
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Jones-Oliveira JB, JS Oliveira, HE
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• securely moves files to a targe
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Plenary invited lecture, “The Ele
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Figure 1. X3DGEN tetrahedral mesh o
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Figure 5a. OSO volume rendering of
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Development of Models of Cell-Signa
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SOS p 23 EGFR Professor Rodland at
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Oliveira JS, JB Jones-Oliveira, and
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Figure 2. Associating a dataset mar
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to 1) incorporate three-dimensional
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shown in Figure 1. Simulated result
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HostBuilder: A Tool for the Combina
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Invariant Discretization Methods fo
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Graphics, Inc., workstation. The co
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Mixed Hamiltonian Methods for Geoch
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guyanaite, and grimaldiite (see Fig
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in the Environmental Molecular Scie
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Simulation and Modeling of Electroc
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Summary and Conclusions We implemen
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Since the implementation of the gen
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asis of previous performance, perce
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Bioinformatics for High-Throughput
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Summary and Conclusions In previous
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User Cat - Supervisor (client) Anal
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The second goal was to research way
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Figure 1. A visualization technique
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and interactions. The flexibility o
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Figure 4. A filtered version of Fig
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Development of Modeling Tools for J
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Figure 2. Schematic of experimental
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Integrated Modeling and Simulation
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(a) (b) (c) (d) Figure 1. Results o
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Thurman DA. August 2000. Collaborat
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MARC Input initial m esh and result
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(Johnson 1999; Colligan 1999; Gould
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Modeling of High-Velocity Forming f
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Global divergence error 1 10 -14 0
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that users were unlikely to appreci
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Earth System Science
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the lateral extent of the plume so
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Biogeochemical Processes and Microb
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Analyses of populations of viable a
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The first task was to establish fiv
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purged for 2 minutes. The gas sampl
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developing code architecture to min
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Berkowitz, CM. June 2000. “Atmosp
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environmental monitoring, 2) portab
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corresponded to a current density o
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Enhancing Emissions Pre-Processing
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Environmental Fate and Effects of D
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nitrogen and unpredictable eutrophi
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Figure 1. Ordinary kriging of 2 m d
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precipitation of calcite occurred i
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Interrelationships Between Processe
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phenanthrene resistant fraction con
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injection of an immiscible gas phas
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still some key kinetic issues that
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Page 250 and 251: Application of a Crop Model The res
Page 252 and 253: The Nature, Occurrence, and Origin
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Page 260 and 261: allowable parameters using thermody
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Page 264 and 265: Use of Shear-Thinning Fluids for In
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Page 276 and 277: Figure 2. Setup for the second expe
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Page 284 and 285: Plasma Particle Dielectric Fiber El
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Page 296 and 297: Examination of the Use of Diazolumi
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Page 310 and 311: Figure 1. (a) - (c) Successive magn
Page 312 and 313: Component Fabrication and Assembly
Page 314 and 315: Development of a Low-Cost Photoelec
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exceed those in the all-metal devic
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Intensity (a.u.) 0 100 200 300 400
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integrated voltage (V) 0.10 0.08 0.
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The first step was to implement thi
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Spontaneous Formation of Cu2O Nano-
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Actinide Chemistry at the Aqueous-M
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Figure 5. Close-up atomic force mic
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to 300°C and 400°C. Unfortunately
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Summary and Conclusions Transmutati
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Advanced Calibration/Registration T
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Figure 1a. Violet filter Figure 1b.
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Autonomous Ultrasonic Probe for Pro
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containing nitrous oxide, an optica
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Chemical Detection Using Cavity Enh
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Figure 3 is a color rendered simula
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appropriate study has been performe
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Exploitation of Conventional Chemic
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Figures 3 and 4 illustrate the impa
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enefits of using a modified spread-
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Single Channel Signal 0.0025 0.0020
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Therefore, in order to extract the
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A next-generation technology is nee
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Wind Dir. Figure 2. Negative ion co
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Volumetric Imaging of Materials by
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amplitude and peak frequency change
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Figure 3. 13 C NMR spectrum of corn
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Approach Two flow loops, one that o
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Modification of Ion Exchange Resins
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Permanganate Treatment for the Deco
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minimized by medium exchange. After
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Figure 1. Thermogravimetric analysi
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Validation and Scale-Up of Monosacc
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Concentration (g/100g solution) Con
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Analysis of High-Volume, Hyper-Dime
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ecent figure of merit values. Shoul
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Probabilistic Methods Development f
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a) Traditional PCA-based process co
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Acronyms and Abbreviations 2-D two-
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