PNNL-13501 - Pacific Northwest National Laboratory

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CFU-S Stem Cell Assay - Benzene Metabolites % of Control 100 10 1 Phenol HQ 0 10 20 Dose (uM) 30 40 phenol treatments were 51, 60, and about 1% of control, respectively. However, the chemical treatments of CFU- S cells in the presence of the radiation did not appear to shift the dose-response beyond what the chemicals accomplished by themselves. These preliminary in vitro studies suggest that the cytotoxic effects of benzene metabolites and radiation on bone marrow stem progenitor cells may be independent. Future studies are needed to determine if a similar response is seen following in vivo exposure to benzene and radiation. Summary and Conclusions An in vitro bone marrow stem cell culture assay for evaluation of chemical and radionuclide interactions was established. Preliminary experiments demonstrated that the colony-forming assay was sensitive to dose-dependent radiation effects. The benzene metabolites phenol and hydroquinone produced a dose-dependent inhibition of stem cell colony formation (CFU-S). The metabolite combination effect was multiplicative (greater than % of Control 100% 10% 1% 50.73% 16.87% Treatment Groups 40 FY 2000 <strong>Laboratory</strong> Directed Research and Development Annual Report 1.13% HQ (10 uM) Phenol (40 uM) Phenol (40uM) + HQ (10uM) Figure 3. CFU-S cell colony formation response following in vitro exposure to phenol, hydroquinone, and phenol plus hydroquinone % of Control 120 100 80 60 40 20 0 CFU-S Stem Cell Assay - Radiation/Benzene Metabolites Co-Exposure 100 86 60 51 45 43 34 13 23 15 19 12 1.1 1.6 1.0 0.3 0 0.01 0.1 1 Radiation Dose (Gy) Radiation Only Radiation + 10 uM HQ Radiation + 40 uM Phenol Radiation + 40 uM Phenol/10 uM HQ Figure 4. CFU-S cell colony formation response following in vitro exposure to both radiation (0 to 1 Gy) and phenol, hydroquinone, and phenol plus hydroquinone. Percent of control values for each treatment are presented over the bar graphs. additive). Under in vitro exposure conditions, radiation did not shift the dose-response beyond what the benzene metabolites could accomplish independent of radiation. Future studies will determine if a similar response is obtained in mice following in vivo mixed chemical and radiation exposures. The approaches developed in this project will form the experimental cornerstone for pharmacodynamic model development for chemical and radiation interactions on bone marrow cells. References Corti M and CA Snyder. 1998. “Gender- and agespecific cytotoxic susceptibility to benzene metabolites in vitro.” Tox. Sci. 41:42-43. Cox, Jr. LA. 1996. “Reassessing benzene risks using internal doses and Monte-Carlo uncertainty analysis.” Environ. Health Perspect. 104 (Suppl. 6):1413-1429. Farris G M and SA Benjamin. 1993. “Inhibition of myelopoiesis by conditioned medium from cultured canine thymic cells exposed to estrogen.” Am. J. Vet Res. 54:1366-1373. Farris GM, SN Robinson, KW Gaido, BA Wong, VA Wong, WP Hahn, and RS Shah. 1997. “Benzeneinduced hematotoxicity and bone marrow compensation in B6C3F1 mice.” Fundam. Appl. Toxicol. 36:119-129. Green JD, CA Snyder, J LoBue, BD Goldstein, and RE Albert. 1981. “Acute and chronic dose/response effects of inhaled benzene on multipotential hematopoietic stem (CFU-S) and granulocyte/macrophage progenitor (GM- CFU-C) cells in CD-1 mice.” Toxicol. Appl. Pharmacol. 58:492-503. Scheding S, M Loeffler, S Schmitz, HJ Seidel, and HE Wichmann. 1992. “Hematotoxic effects of benzene analysed by mathematical modeling.” Toxicol. 72:265- 279. Timchalk C, JE Morris, and RA Corley. 2000. “Effects of co-exposure of benzene and radiation (Yttrium-90) on hematopoiesis in CBA/CA mice.” Tox Sci. 54(1):1649. Publication Timchalk C, JE Morris, and RA Corley. 2000. “Effects of co-exposure of benzene and radiation (Yttrium-90) on hematopoiesis in CBA/CA mice.” Tox Sci. 54(1):1649.
Study Control Number: PN99005/1333 Biomolecular Interaction Assay System Jay W. Grate, Cynthia Bruckner-Lea Understanding protein-protein and protein-DNA interactions is integral to understanding the function of living organisms and how organisms respond to insults such as environmental exposure to chemicals and radiation. Methods are being developed on this project to rapidly measure the interactions between these biomolecules. Project Description The purpose of this project was to build and test a device for rapidly measuring the interactions between biomolecules (proteins and DNA) and multiple protein complexes. We constructed two different renewable microcolumn devices with on-column optical detection, and wrote computer control programs to automate the experimental systems. The renewable microcolumn systems were then used to monitor the binding of several model proteins (antibodies) and measure the interaction between proteins and DNA fragments. This project advances our ability to rapidly measure biomolecular interactions and therefore understand biological systems. Introduction A number of sensor technologies have been adapted to monitoring biomolecular interactions. Acoustic wave devices such as flexural plate wave devices, surface transverse waves, and quartz crystal microbalances detect the mass increase observed upon binding of a solution biomolecule to a surface bound biomolecule. However, these devices also respond to changes in viscosity, temperature, liquid density, and viscoelastic effects, which may confound the interpretation of observed signals. In addition, nonspecific binding is often indistinguishable from specific binding. Several techniques for refractive index sensing, such as planar wave guides and surface plasmon resonance, can also be used to observe biomolecular interactions localized at a surface. Again, nonspecific binding is indistinguishable from specific binding, and the derivatized surface must be very thin and uniform to obtain adequate sensitivity and reproducibility. All of these techniques use planar surfaces that must be derivatized with the first biomolecule. These surfaces are difficult to prepare and characterize, and must be prepared fresh for each assay. In addition, these techniques cannot measure the binding of multiple proteins to form large protein complexes. Therefore, there is the need for the development of new techniques for conducting many rapid, automated measurements of biomolecular binding events, including the formation of multiple protein complexes. Approach This project will develop renewable surface sensing techniques for monitoring biomolecule binding events. In this approach, a suspension of surface derivatized beads is introduced into a flow system and then automatically trapped by a barrier that stops the beads but allows the fluid to proceed (Bruckner-Lea et al. 1999, 2000; Chandler et al. 1999, 2000; Ruzicka and Hansen 2000; Ruzicka and Scampavia 1999; Ruzicka 1998). This produces a small microcolumn of beads (only about a microliter in volume) in a location for observation. The beads can then be automatically perfused with reagent or sample solutions to perform separations or surface reactions. Detection methods can be used to observe optical changes (absorbance or fluorescence) on the bead surfaces. At the completion of the observation, the beads can be flushed from the observation area and disposed. A new bed of beads can then be packed for the next assay. This new bead bed has a fresh surface, hence the name renewable surface sensing. The renewable surface approach has a number of advantages over planar formats, and over the surface plasmon resonance method. The flow injection system is far more flexible for delivering solutions to the observation area. This feature may become particularly important when attempting to create and observe assemblies of more than two components. The spectral detection, as opposed to a single refractive index change, provides more selective detection by providing more information for observing particular species and zeroing out undesirable contributions to signals. In addition, the column format is compatible with typical measurements by affinity chromatography for obtaining thermodynamic Biosciences and Biotechnology 41
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Laboratory Directed Research and De
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Laboratory Directed Research and De
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Page 9 and 10: Introduction Department of Energy O
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Page 17 and 18: Summary Each national laboratory mu
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Page 21 and 22: Table 1. Positive and negative ions
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Page 25 and 26: introduce low-volatility compounds
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Page 41 and 42: Study Control Number: PN99069/1397
Page 45 and 46: Seuss DT and KA Prather. 1999. “M
Page 47 and 48: Analysis of Receptor-Modulated Ion
Page 49 and 50: laboratory (Lu and Xie 1997; Lu et
Page 51 and 52: Automated DNA Fingerprinting Microa
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Plant Root Exudates and Microbial G
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Study Control Number: PN00077/1484
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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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Application of a Crop Model The res
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The Nature, Occurrence, and Origin
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Particle number concentration, 1/cm
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geometry optimized AlOOH and FeOOH
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allowable parameters using thermody
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TCE + 3H + + 3Fe 2+ Fe)=> acetylene
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Use of Shear-Thinning Fluids for In
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concentration of 0.5% AMX was the m
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Roberts AL, LA Totten, WA Arnold, D
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tetra-scale computing, envisioned a
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Energy Technology and Management
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Figure 2. Setup for the second expe
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phase. The algorithms will be teste
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[Pb-212]/[Pb-212] final 100 10 1 0.
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Plasma Particle Dielectric Fiber El
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(species, sub-species, and sex), sp
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Figure 3. Relative risk of bone and
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Development of a Preliminary Physio
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Development of a Virtual Respirator
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Figure 3. Use of the chest cavity a
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Examination of the Use of Diazolumi
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Indoor Air Pathways to Nuclear, Che
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Source Building Release Observed re
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To illustrate the potential impact
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Non-Invasive Biological Monitoring
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Materials Science and Technology
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Figure 1. (a) - (c) Successive magn
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Component Fabrication and Assembly
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Development of a Low-Cost Photoelec
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elaxations, indicating the adequacy
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Promising chemical durability, as m
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Study Control Number : PN98028/1274
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High Power Density Solid Oxide Fuel
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Hybrid Plasma Process for Vacuum De
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Matson DW, PM Martin, WD Bennett, J
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We showed the proof-of-principle ap
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Bandgap Energy (eV) 2.9 2.85 2.8 2.
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Ultrathin Electrolyte Test Results
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Detailed Investigations on Hydrogen
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identified low energy step structur
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Development of Novel Photo-Catalyst
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-2 -1 Energy (eV) 0 1 2 Cu2O SrTiO3
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Here, we perform adsorption and des
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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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