Arguing Using Opponent Models

Peer reviewedPostprin

Synthesis and Characterization of New Probes for use in Fluorescence and X-ray CT Bioimaging

The pursuit of more suitable drugs intended for possible biological applications are a continuously growing topic of research within the scientific community. One of these suitable qualities includes the need for hydrophilicity and or some appropriate delivery system for the drug to enter into biological systems. A system of analyzing and following these compounds would then, however, be necessary to conduct any kind of mechanistic or interaction studies for he said drug within the biological system. Just to name a few, fluorescence and X-ray computed tomography (CT) methods allow for imaging of biological systems but require the need of compounds with specific qualities. Finally, even with a means of entering and following a oaded drug, it would not be complete without a way of targeting its intended location. Herein, the first chapter reports the synthesis and characterization of a fluorene-based pyridil bis-?-diketone compound with suitable one- and two-photon fluorescent properties and its encapsulation into Pluronic F127 micelles for the possible application of tracking lysosomes. Next the synthesis and characterization of a BODIPY-based fluorophore with excellent fluorescence ability is reported. This compound was conjugated to two triphenylphosphine (TPP) groups and is shown as a potential mitochondria probe within HCT-116 cells. Finally, the synthesis and characterization of diatrizoic acid (DA) based derivatives conjugated to silica nanoparticles, as well as unconjugated, are reported as potential CT contrast agents. The derivatives were also functionalized with maleimide moieties facilitating subsequent potential bioconjugation of a targeting protein via a thiol group

Viscoelastic Characterization of Murine Articular Cartilage through Nondestructive Dynamic Microindentation

Transgenic and biochemical mouse models of osteoarthritis have become increasingly popular. However, the microscale thickness of mouse cartilage complicates mechanical characterization of these models. Existing methods are time-prohibitive and difficult, especially for life scientists. We developed a rapid, nondestructive method for viscoelastically characterizing murine articular cartilage, and validated it. We dissected tibial plateaus from adult mouse knees, and subjected them to trypsination and ribosylation treatments. Dynamic mechanical testing was performed using a BioDent testing apparatus (ActiveLife Scientific, Santa Barbara, CA). Viscoelastic parameters were extracted, and repeat testing was conducted to check for testing-induced damage. This protocol demonstrated significant mechanical differences between the control and osteoarthritic models. Additionally, we verified results using histology and finite element analysis

MSMEs (Microsoft, Small and Medium Enterprises) and Democracy, a Panel Data Model

This paper focuses on different national economic development structures, such as microsmall-medium-enterprises (MSMEs) vs. big or state-owned enterprises and their relations with political development. A well-established literature argues that MSMEs are conducive to economic growth. Existing literature does not tell us much about the relationship between MSMEs and democracy. This dissertation examines the relationship between economic development structure and democracy. I demonstrate that we observe a negative correlation between high concentration of MSMEs and political development in the early stages of a country’s economic development (pre-takeoff or takeoff states stages), ceteris paribus. I provide a theoretical framework and causal mechanism that link MSMEs to limited political development due to collective action problems in a decentralized economy. This collection action problem encourages corrupt transactions between MSMEs and government officials that undermine prospects for functioning democracy. I use extensive quantitative analysis and detailed case studies to explain the mechanisms whereby MSME’s appear inimical to democratic governance, and under what conditions MSMEs may advance democratic decision-making

Intracellular application of an asparaginyl endopeptidase for producing recombinant head-to-tail cyclic proteins

Peptide backbone cyclization is commonly observed in nature and is increasingly applied to proteins and peptides to improve thermal and chemical stability and resistance to proteolytic enzymes and enhance biological activity. However, chemical synthesis of head-to-tail cyclic peptides and proteins is challenging, is often low yielding, and employs toxic and unsustainable reagents. Plant derived asparaginyl endopeptidases such as OaAEP1 have been employed to catalyze the head-to-tail cyclization of peptides in vitro, offering a safer and more sustainable alternative to chemical methods. However, while asparaginyl endopeptidases have been used in vitro and in native and transgenic plant species, they have never been used to generate recombinant cyclic proteins in live recombinant organisms outside of plants. Using dihydrofolate reductase as a proof of concept, we show that a truncated OaAEP1 variant C247A is functional in the Escherichia coli physiological environment and can therefore be coexpressed with a substrate protein to enable concomitant in situ cyclization. The bacterial system is ideal for cyclic protein production owing to the fast growth rate, durability, ease of use, and low cost. This streamlines cyclic protein production via a biocatalytic process with fast kinetics and minimal ligation scarring, while negating the need to purify the enzyme, substrate, and reaction mixtures individually. The resulting cyclic protein was characterized in vitro, demonstrating enhanced thermal stability compared to the corresponding linear protein without impacting enzyme activity. We anticipate this convenient method for generating cyclic peptides will have broad utility in a range of biochemical and chemical applications.</p

Navigational Context Recognition for an Autonomous Robot in a Simulated Tree Plantation

A sensor fusion technique was developed for estimating the navigational posture of a skid-steered mobile robot in a simulated tree plantation nursery. Real-time kinematic GPS (RTK-GPS) and dynamic measurement unit (DMU) sensors were used to determine the position and orientation of the robot, while a laser range finder was used to locate the tree positions within a selected range. The RTK-GPS error was modeled by a second-order autoregressive model, and error states were incorporated into extended Kalman filter (EKF) design. Through EKF filtering, the mean and standard deviation of error in the easting direction decreased from 4.05 to 2.21 cm and from 8.27 to 1.89 cm, respectively, while in the northing direction, they decreased from 4.64 to 1.81 cm and from 11 to 2.16 cm, respectively. The geo-referenced tree positions along the navigational paths were also recovered by using a K-means clustering algorithm, achieving an average error of tree position estimates of 4.4 cm. The developed sensor fusion algorithm was proven to be capable of recognizing and reconstructing the navigational environment of a simulated tree plantation, which offers a great potential in improving the applicability of an autonomous robot to operate in nursery tree plantations for operations such as intra-row mechanical weeding

Distributed Learning over Unreliable Networks

Most of today's distributed machine learning systems assume {\em reliable networks}: whenever two machines exchange information (e.g., gradients or models), the network should guarantee the delivery of the message. At the same time, recent work exhibits the impressive tolerance of machine learning algorithms to errors or noise arising from relaxed communication or synchronization. In this paper, we connect these two trends, and consider the following question: {\em Can we design machine learning systems that are tolerant to network unreliability during training?} With this motivation, we focus on a theoretical problem of independent interest---given a standard distributed parameter server architecture, if every communication between the worker and the server has a non-zero probability $p$ of being dropped, does there exist an algorithm that still converges, and at what speed? The technical contribution of this paper is a novel theoretical analysis proving that distributed learning over unreliable network can achieve comparable convergence rate to centralized or distributed learning over reliable networks. Further, we prove that the influence of the packet drop rate diminishes with the growth of the number of \textcolor{black}{parameter servers}. We map this theoretical result onto a real-world scenario, training deep neural networks over an unreliable network layer, and conduct network simulation to validate the system improvement by allowing the networks to be unreliable

T1ρ-based fibril-reinforced poroviscoelastic constitutive relation of human articular cartilage using inverse finite element technology

BackgroundMapping of T1ρ relaxation time is a quantitative magnetic resonance (MR) method and is frequently used for analyzing microstructural and compositional changes in cartilage tissues. However, there is still a lack of study investigating the link between T1ρ relaxation time and a feasible constitutive relation of cartilage which can be used to model complicated mechanical behaviors of cartilage accurately and properly.MethodsThree-dimensional finite element (FE) models of ten in vitro human tibial cartilage samples were reconstructed such that each element was assigned by material-level parameters, which were determined by a corresponding T1ρ value from MR maps. A T1ρ-based fibril-reinforced poroviscoelastic (FRPE) constitutive relation for human cartilage was developed through an inverse FE optimization technique between the experimental and simulated indentations.ResultsA two-parameter exponential relationship was obtained between the T1ρ and the volume fraction of the hydrated solid matrix in the T1ρ-based FRPE constitutive relation. Compared with the common FRPE constitutive relation (i.e., without T1ρ), the T1ρ-based FRPE constitutive relation indicated similar indentation depth results but revealed some different local changes of the stress distribution in cartilages.ConclusionsOur results suggested that the T1ρ-based FRPE constitutive relation may improve the detection of changes in the heterogeneous, anisotropic, and nonlinear mechanical properties of human cartilage tissues associated with joint pathologies such as osteoarthritis (OA). Incorporating T1ρ relaxation time will provide a more precise assessment of human cartilage based on the individual in vivo MR quantification

Role of Family, Culture, and Peers in the Success of First-Generation Cambodian American College Students

Cambodian American college students are often overlooked in academe because of the model minority myth. The stereotype overshadows the challenges and heterogeneity in the Asian American and Pacific Islander population. This exploratory study examined the experiences of 13 first-generation Cambodian American college students at a large, public institution in California. Findings revealed that, despite obstacles of being first-generation with limited cultural capital, students were transformed into successful leaners when they received validation from their parents and peers and felt a sense of belonging to the college community through their involvement in an ethnic-based student organization

Metaheuristics and Chaos Theory

Chaos theory is a novelty approach that has been widely used into various applications. One of the famous applications is the introduction of chaos theory into optimization. Note that chaos theory is highly sensitive to initial condition and has the feature of randomness. As chaos theory has the feature of randomness and dynamical properties, it is easy to accelerate the optimization algorithm convergence and enhance the capability of diversity. In this work, we integrated 10 chaotic maps into several metaheuristic algorithms in order to extensively investigate the effectiveness of chaos theory for improving the search capability. Extensive experiments have been carried out and the results have shown that chaotic optimization can be a very promising tool for solving optimization algorithms