Ambient Ionization Mass Spectrometry Analysis Pertaining To Biofuel Process Development

Mass spectrometry (MS) has undergone a revolution with the introduction of a new group of desorption/ionization (DI) techniques known collectively as Ambient Ionization mass spectrometry. Ambient ionization mass spectrometry allows for direct analysis of analytes and typically requires little or no sample preparation. Specifically, Direct Analysis in Real Time (DART) has developed rapidly and allowed investigations to occur with the analysis of biomass after various pretreatments to determine the pretreatment biomass degradation efficiency. The degradation of the initial biomass structure is a very important step before other chemical treatments can occur to generate needed sugars. Since generated sugars aid in algae production, the pretreatment process is also important in relation to the overall process in producing biofuels. In addition to biomass analysis, analysis of specific biofuels from various feedstocks by the DART-MS is also presented demonstrating this ambient ionization method can be a rapid verification of the biofuel production. Biofuels generated from renewable resources have the potential to be a valuable substitute for, or complement to conventional gasoline

Nonlinear Dimensionality Reduction for the Thermodynamics of Small Clusters of Particles

This work employs tools and methods from computer science to study clusters comprising a small number N of interacting particles, which are of interest in science, engineering, and nanotechnology. Specifically, the thermodynamics of such clusters is studied using techniques from spectral graph theory (SGT) and machine learning (ML). SGT is used to define the structure of the clusters and ML is used on ensembles of cluster configurations to detect state variables that can be used to model the thermodynamic properties of the system. While the most fundamental description of a cluster is in 3N dimensions, i.e., the Cartesian coordinates of the particles, the ML results demonstrate that sub-spaces of much lower dimension can describe the observed structural motifs. Furthermore, these sub-spaces correlate with meaningful physical variables such as radius of gyration r g and discrete connectivity c, which can be used as state variables in thermodynamic property descriptions. The overarching theme of this thesis is to develop the practice of utilizing data-driven computational techniques to solve problems in natural sciences. Code for this project can be found at https://github.com/AdityaDendukuri/DimReductionThermodynamics

Validity of electron beam computed tomography for coronary artery disease: asystematic review and meta-analysis

Background: Electron beam computed tomography (EBCT) is a method for measuring coronary calcification and has been promoted as a possible non-invasive screening/diagnostic tool for coronary artery disease (CAD). Our objective was to carry out a systematic review and meta-analysis of EBCT for the screening of asymptomatic patients and the diagnosis of symptomatic patients for CAD. Methods: Studies were identified from the PUBMED, MEDLINE, EMBASE, Current Contents, INAHTA and Cochrane Collaboration databases. We identified studies published in English evaluating EBCT using: (1) a prospective design among asymptomatic patients where CAD was measured in terms of clinical outcomes (e.g. myocardial infarction, death, revascularization); and (2)a cross-sectional design among symptomatic patients where CAD was measured by coronary angiography. We compared the risk of CAD in EBCT score categories defined as low (0-10), moderate (11-400) and high (>400). A hierarchical meta-analysis was used to pool risk ratios comparing categories across studies. Results: We identified 9 studies of asymptomatic patients and 10 studies of symptomatic patients. In both types of studies, we found variability in EBCT category distribution and risk of CAD within categories. For studies of asymptomatic patients we estimated the following risk ratios (95% credible intervals): moderate versus low 3.5 (2.4, 5.1) and high versus low 9.9 (5.3, 17.6). Similar results were obtained for studies of symptomatic patients. Ratios comparing the risk of no CAD among symptomatic patients were as follows: moderate versus low 0.5 (0.3, 0.8) and high versus low 0.12 (0.05, 0.2). Conclusion: Increasing EBCT scores indicate higher risk for CAD in both asymptomatic and symptomatic patients. In general, asymptomatic patients with EBCT scores in the high category can perhaps be considered for preventive medical therapy and risk factor modification. Symptomatic patients with EBCT scores in the low category can perhaps, at least temporarily, avoid invasive coronary angiography. However, the non-uniform quality of studies and the lack of availability of individual-level data preclude the extension of our results to individual patients. © 2007 Dendukuri et al; licensee BioMed Central Ltd

Extraction of Voiced Regions of Speech from Emotional Speech Signals Using Wavelet-Pitch Method

Extraction of voiced regions of speech is one of the latest topics in speech domain for various speech applications. Emotional speech signals contain most of the information in voiced regions of speech. In this particular work, voiced regions of speech are extracted from emotional speech signals using wavelet-pitch method. Daubechies wavelet (Db4) is applied on the speech frames after downsampling the speech signals. Autocorrelation function is performed on the extracted approximation coefficients of each speech frame and corresponding pitch values are obtained. A local threshold is defined on obtained pitch values to extract voiced regions. The threshold values are different for male and female speakers, as male pitch values are low compared to the female pitch values in general. The obtained pitch values are scaled down and are compared with the thresholds to extract the voiced frames. The transition frames between the voiced and unvoiced frames are also extracted if the previous frame is voiced frame, to preserve the emotional content in extracted frames. The extracted frames are reshaped to have desired emotional speech signal. Signal to Noise Ratio (SNR), Normalized Root Mean Square Error (NRMSE) and statistical parameters are used as evaluation metrics. This particular work provides better SNR and Normalized Root Mean Square Error values compared to the zero crossing-energy and residual signal based methods in voiced region extraction. Db4 wavelet provides better results compared to Haar and Db2 wavelets in extracting voiced regions using wavelet-pitch method from emotional speech signals

Microfluidic approaches to the synthesis of complex polymeric particles

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2007.Includes bibliographical references (p. [119]-128).The synthesis of micron-sized polymeric particles with precise control over shape, monodispersity and chemistry is a technologically important objective. Varied applications including medical diagnostics. designer fabrics and optical devices could benefit from the availability of geometrically complex and chemically inhomogeneous particles. Microfluidics has recently emerged as an important alternative route to the synthesis of such complex particles. This thesis presents three new approaches to complex particle and structure synthesis in microfluidic devices. In the first approach. droplets formed by shearing a curable photopolymer. using a continuous water phase at a T-junction, were constrained to adopt non-spherical shapes by confining them using appropriate microchannel geometries. The non-spherical shapes formed were permanently preserved by photopolymerizing the constrained droplets in situ using focused ultraviolet (UV) light from an inverted microscope. The second and more general method called Continuous Flow Lithography (CFL) is a one-phase, projection photolithography based process to continuously synthesize polymeric microparticles in any 2-D extruded shape down to the colloidal length scale.(cont.) Polymerization was also performed across laminar. co-flowing streams to generate Janus particles containing different chemistries, whose relative proportions could be tuned easily. CFL was also used to synthesize 'particle surfactants' that assembled at the interface of oil-water emulsions or formed micelle-like structures in water. While CFL was able to synthesize particles in non-spherical shapes with chemical anisotropy, particle throughput and resolution was a concern. To mitigate these problems, a new setup called Stop Flow Lithography (SFL) was devised. In SFL, a flowing stream of oligomner is stopped before polymerizing an array of particles into it, providing for much improved resolution over particles synthesized in flow. The formed particles are then flushed out at high flow rates before the cycle of stop-polymerize-flow is repeated. The high flow rates enable orders-of-magnitude improvements in particle throughput over CFL. However, the deformation of the PDMS elastomer due to the imposed pressure restricts how quickly the flow can be stopped before each polymerization event. We have developed a simple model that captures the dependence of the time required to stop the flow on geometric parameters such as the height, length and width of the microchannel, as well as on the externally imposed pressure.(cont.) A third approach to synthesizing particles uses elastomeric phase masks to build all-PDMS devices. Coherent laser light passing through a phase mask generates a complex 3D distribution of intensity that selectively exposes certain regions while leaving out others. This results in the formation of 3-D structures whose features can be tuned at the micron scale and below. We have attempted the formation of 3-D structures in hydrogel polymers which could have important implications in the field of tissue engineering. Finally, we have developed a simple model of the oxygen inhibited polymerization that occurs in flow lithography. This model is able to qualitatively predict the presence of a thin, uncrosslinked layer of oligomer close to the walls of the PDMS device. This layer is critical to our ability to flow out particles in flow lithography. This thesis demonstrates that microfluidics is indeed a viable and promising route to the synthesis of complex polymeric particles and structures.by Dhananjay Dendukuri.Ph.D

Toward Assembly of Non-close-packed Colloidal Structures from Anisotropic Pentamer Particles

Particles combining multiple anisotropy dimensions offer possibilities for self-assembly that have not been extensively explored to date. The scope for assembly of microparticles in which the anisotropy dimensions of internal bond angle and chemical ordering have been varied is investigated. Colloidal assemblies with interesting open (i.e., non-close-packed) structures can be assembled from these building blocks. The structure of the assemblies formed is linked to the building block anisotropy because the steric constraints introduced induce deviations from close packing. Key challenges addressed in pursuit of these structures are parallelization of microfluidic synthesis methods, simulation to efficiently search the available anisotropy space, and methods that characterize the properties of the resulting assemblies. This combined program of synthesis, simulation, assembly, and characterization may be applied to develop design rules that guide efforts to fabricate microparticle building blocks and their assemblies.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64926/1/196_ftp.pd