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Stimuli Responsive Dye-Containing PEG-PLA Block Copolymer Micelles and Computationally Assisted Design of a Stapled Peptide Bundle
No full textIn this thesis, I report the preparation and characterization of dye-containing PEG-b-PLA block copolymer micelles and the computational design of a novel coiled-coil peptide bundle. The PEG-b-PLA micelles encapsulate hydrophobic molecules into their core and have strong potential as nanocontainers or delivery vesicles. In theory, these internalized molecules can be released upon exposure to mechanical forces that disrupt the micellar structures. This force-responsive nature is one of the inherent properties of micellar systems. However, there is a stark lack of research that utilize this property in applications. Along those lines, I have studied the behavior of dye-containing micelles upon exposure to mechanical stresses. In this work, two fluorescent dyes that undergo fluorescence resonance energy transfer (FRET) in close proximity have been used as reporters to gauge the structure of the micelles. Upon exposure to mechanical force via vortexing, the fluorescent signal of micelles decreases as a function of rotational speed and time of vortexing. In another project, I have worked on the design of a novel coiled-coil peptide bundle. Coiled-coil peptides have been widely used as templates for protein design. The specific goal of this project was to develop a photo-responsive hexameric coiled-coil bundle that can incorporate hydrophobic molecules into the interior core and reversibly catch and release small molecules. The azobenzene derivative, BSBCA was chosen as the linker to impart the photo-responsive properties to the peptide bundle. Using the PyRosetta computational suite, I have identified 3 top candidates of the mutated peptides that contain two cysteine residues to be linked with BSBCA and are anticipated to form stable hexamer bundles in aqueous environment
Fiscal Decentralization, Intergovernmental Transfer Reform and Conflict in Colombian Municipalities
No full textIn this paper, we examine how conflict in Colombia responded differentially to a fiscal decentralization reform in 2001 for the regions with different presence of armed militia groups, namely the Revolutionary Armed Force of Colombia (FARC), the National Liberation Army (ELN), and the United Self-Defense Group of Colombia (AUC). We also examine the differential impact on municipalities with and without oil reserves. We are using municipal-level data on general characteristics of municipalities, fiscal variables, and variables related to conflict. While there is a rich literature on the economic drivers and impacts of conflicts, the literature that examines the relationship between fiscal decentralization and conflicts is relatively small. We are contributing to the literature by examining this relationship at the local (municipal) level, which has not been explored widely or conclusively in other studies. We are also addressing spatial dependence among municipalities. This is important because it is likely that conflict and other economic variables lead to spillovers that impact municipalities in close proximity. We employ spatial econometric techniques, particularly Spatial Durbin Model (SDM), to account for spatial dependence in the data. Our results show a decrease in conflict in response to the intergovernmental transfer reform, but the exact response vary by conflict region. Oil reserves in some municipalities seem to have played a role in the conflict outcomes as well
The γ-Brass Type Cu–rich Complex Intermetallic Phase Cu\u3csub\u3e41\u3c/sub\u3eSn\u3csub\u3e11\u3c/sub\u3e: Structure and Electrochemical Study
No full textγ-Brass type phase Cu41Sn11 in binary Cu–Sn system has been reinvestigated. The title phase was synthesized by the conventional high-temperature solid-state method, and structural characterization was carried out using X-ray diffraction. The compound crystallizes in F4‾3m space group (No 216). These structures are constructed of four independent 26-atom γ-clusters per primitive unit cells and centered at the four high symmetry points of the unit cell. The compound exists in a narrow homogeneity range. First-principles quantum mechanics computation was employed on the ordered model Cu41Sn11 shows that the phase is stabilized by the Hume-Rothery mechanism. The copper-rich binary stannide, Cu41Sn11 phase, displays excellent cycle stability during fast charging/discharging rates as an anode in Li-ion batteries. It shows charge/discharge retention capacities of 94.5% and 87.1%, respectively, from the 2nd cycle onwards. The excess Cu-content has successfully assisted in the stable interphase formation and subdued the mechanical stress evolving from volume expansion. The first time such a poly-crystalline Cu-rich, cubic, Cu41Sn11 phase has shown any Li-ion insertion activity for rechargeable Li-ion batteries at ambient temperature
Validity of Wearable Electromyographical Compression Shorts to Predict Lactate Threshold During Incremental Exercise in Healthy Subjects
No full textDetermination of lactate threshold (LT) is an important variable in improving cardiovascular endurance and performance. Unfortunately, monitoring LT during exercise uses a costly, invasive blood analysis. Recently, electromyography (EMG) has been deemed a potential method of monitoring exercise intensity and may provide a noninvasive technique to monitor lactate during exercise. The purpose of this investigation was to determine if wearable surface EMG technology, acquired from specialized compression shorts, could estimate the LT work rate during incremental cycling. Thirteen men (n = 9) and women (n = 4) completed a maximal exercise test on a cycle ergometer. Blood lactate was measured every minute, whereas EMG was recorded throughout at the site of the vastus lateralis. Lactate and EMG thresholds were calculated using the Dmax method and compared using a Wilcoxon matched-pairs signed-rank test. Results demonstrated no significant differences between lactate and EMG thresholds in regards to work output (p = 0.83), percent maximal heart rate (p = 0.13; Cohen\u27s d = 0.43), or percent peak oxygen consumption (p = 0.64; Cohen\u27s d = 0.09). This confirms that both lactate and EMG exhibit similar properties (i.e., increasing exponential values) during incremental exercise. A possible mechanism includes the rise in blood lactate concentration, which increases motor unit recruitment in an attempt to maintain proper cadence and force output during incremental exercise. Thus, a coincidental, exponential increase in EMG amplitude may occur. Therefore, wearable EMG compression gear may provide a viable field tool for monitoring training intensity and predicting LT work rates
Teaching Teams: The Roles of Lead Teachers, Teaching Assistants, and Curriculum Demand in Pre-kindergarten Instruction
No full textTeaching assistants are a common presence in pre-kindergarten programs, but their role and the dynamics between lead teachers and their assistants are understudied. The classroom behaviors of lead teachers and assistants from 80 public prekindergarten classrooms were examined for similarities and differences in their roles and to determine how they functioned as teams. Lead teachers spent more of their time instructing and worked more often with the whole class. Assistants working in classrooms with a demanding curriculum spent more time instructing than assistants in less demanding classrooms. Latent class analysis of behavior patterns suggests that the adults adopt similar rather than complementary roles. Two groups of teaching teams emerged: one with both teachers and assistants spending time more time on instruction, and a second with both teachers and assistants spending more time on management. Despite lower pay and credentials, assistant teachers contributed in substantive ways to the instruction in these classrooms. It appears that the lead teacher likely determines how the team functions. Helping teachers know how to establish a well-functioning team should be part of early childhood training. Additionally, consideration to be given to offering direct and ongoing professional development to assistants
Deep features for training support vector machines
No full textFeatures play a crucial role in computer vision. Initially designed to detect salient elements by means of handcrafted algorithms, features now are often learned using different layers in convo-lutional neural networks (CNNs). This paper develops a generic computer vision system based on features extracted from trained CNNs. Multiple learned features are combined into a single structure to work on different image classification tasks. The proposed system was derived by testing several approaches for extracting features from the inner layers of CNNs and using them as inputs to support vector machines that are then combined by sum rule. Several dimensionality reduction techniques were tested for reducing the high dimensionality of the inner layers so that they can work with SVMs. The empirically derived generic vision system based on applying a discrete cosine transform (DCT) separately to each channel is shown to significantly boost the performance of standard CNNs across a large and diverse collection of image data sets. In addition, an ensemble of different topologies taking the same DCT approach and combined with global mean thresholding pooling obtained state-of-the-art results on a benchmark image virus data set
