Characterization and stability for Cottonwood riverbank-a reliability study for BSTEM

Master of ScienceDepartment of Civil EngineeringMajor Professor Not ListedRiverbank slope failure due to excessive rainfall and flooding can be costly; however, riverbank slopes may also fail due to upstream engineering structures as an unintended consequence. Many methods and models can be used for slope stability analysis to evaluate how upstream engineered structures impact downstream riverbanks. The objective of this study is to determine an efficient implementation of soil properties for the Bank Stability and Toe Erosion Model (BSTEM), which is commonly used for riverbank stability analysis in Kansas. The stability of a bank along the Cottonwood River in Kansas was evaluated using soil properties obtained from various complex test methods. Soil properties were determined from the consolidated undrained and unconsolidated undrained triaxial tests. Correlations based on the soil type, BSTEM default soil data, and empirical correlations based on measured soil properties were also used to obtain the required BSTEM soil properties. The results of this study indicate that the soil properties obtained from an effective stress analysis, as required by BSTEM, using the consolidated undrained triaxial test provide the most accurate factor of safety. Soil properties obtained using total stress analysis and based on soil classification led to more conservative, yet reasonable factors of safety. The use of numerically-correlated soil properties was not appropriate, nor were some built-in soil properties within BSTEM. Thus, while BSTEM calls for effective stress parameters, a slightly more conservative and more simplified analysis can be conducted using either measured total stress parameters, or mean values based on soil classification. Ultimately, researchers must evaluate the appropriate risk when selecting the type of data to use for evaluating riverbank stability using BSTEM. This study recommends that BSTEM include an option for total stress analysis for future model development to represent a more critical failure case and to be more conservative

Physical origin of color changes in lutetium hydride under pressure

Recently, near-ambient superconductivity was claimed in nitrogen-doped lutetium hydride (LuH$_{3-\delta}$N$_{\epsilon}$) . Unfortunately, all follow-up research still cannot find superconductivity signs in successfully synthesized lutetium dihydride (LuH$_2$) and N-doped LuH$_{2\pm x}$N$_y$. However, a similar intriguing observation was the pressure-induced color changes (from blue to pink and subsequent red). The physical understanding of its origin and the correlation between the color, crystal structure, and chemical composition of Lu-H-N is still lacking. In this work, we theoretically study the optical properties of LuH$_2$, LuH$_3$, and some potential N-doped compounds using the first-principles calculations by considering both interband and intraband contributions. Our results show that LuH$_2$ has an optical reflectivity peak around blue light up to 10 GPa. Under higher pressure, the reflectivity of red light gradually becomes dominant. This evolution is driven by changes in the direct band gap and the Fermi velocity of free electrons under pressure. In contrast, LuH$_3$ exhibits gray and no color change up to 50 GPa. Furthermore, we considered different types of N-doped LuH$_2$ and LuH$_3$. We find that N-doped LuH$_2$ with the substitution of a hydrogen atom at the tetrahedral position maintains the color change when the N-doping concentration is low. As the doping level increases, this trend becomes less obvious. While other N-doped structures do not show significant color change. Our results can clarify the origin of the experimental observed blue-to-red color change in lutetium hydride and also provide a further understanding of the potential N-doped lutetium dihydride

Pharmacological Basis for Use of Armillaria mellea

Armillaria mellea, an edible fungus, exhibits various pharmacological activities, including antioxidant and antiapoptotic properties. However, the effects of A. mellea on Alzheimer’s disease (AD) have not been systemically reported. The present study aimed to explore the protective effects of mycelium polysaccharides (AMPS) obtained from A. mellea, especially AMPSc via 70% ethanol precipitation in a L-glutamic acid- (L-Glu-) induced HT22 cell apoptosis model and an AlCl3 plus D-galactose- (D-gal-) induced AD mouse model. AMPSc significantly enhanced cell viability, suppressed nuclear apoptosis, inhibited intracellular reactive oxygen species accumulation, prevented caspase-3 activation, and restored mitochondrial membrane potential (MMP). In AD mice, AMPSc enhanced horizontal movements in an autonomic activity test, improved endurance times in a rotarod test, and decreased escape latency time in a water maze test. Furthermore, AMPSc reduced the apoptosis rate, amyloid beta (Aβ) deposition, oxidative damage, and p-Tau aggregations in the AD mouse hippocampus. The central cholinergic system functions in AD mice improved after a 4-week course of AMPSc administration, as indicated by enhanced acetylcholine (Ach) and choline acetyltransferase (ChAT) concentrations, and reduced acetylcholine esterase (AchE) levels in serum and hypothalamus. Our findings provide experimental evidence suggesting A. mellea as a neuroprotective candidate for treating or preventing neurodegenerative diseases

Gyroscope Pivot Bearing Dimension and Surface Defect Detection

Because of the perceived lack of systematic analysis in illumination system design processes and a lack of criteria for design methods in vision detection a method for the design of a task-oriented illumination system is proposed. After detecting the micro-defects of a gyroscope pivot bearing with a high curvature glabrous surface and analyzing the characteristics of the surface detection and reflection model, a complex illumination system with coaxial and ring lights is proposed. The illumination system is then optimized based on the analysis of illuminance uniformity of target regions by simulation and grey scale uniformity and articulation that are calculated from grey imagery. Currently, in order to apply the Pulse Coupled Neural Network (PCNN) method, structural parameters must be tested and adjusted repeatedly. Therefore, this paper proposes the use of a particle swarm optimization (PSO) algorithm, in which the maximum between cluster variance rules is used as fitness function with a linearily reduced inertia factor. This algorithm is used to adaptively set PCNN connection coefficients and dynamic threshold, which avoids algorithmic precocity and local oscillations. The proposed method is used for pivot bearing defect image processing. The segmentation results of the maximum entropy and minimum error method and the one described in this paper are compared using buffer region matching, and the experimental results show that the method of this paper is effective

Atomic-layered Au clusters on α-MoC as catalysts for the low-temperature water-gas shift reaction

The water-gas shift (WGS) reaction (where carbon monoxide plus water yields dihydrogen and carbon dioxide) is an essential process for hydrogen generation and carbon monoxide removal in various energy-related chemical operations. This equilibrium-limited reaction is favored at a low working temperature. Potential application in fuel cells also requires a WGS catalyst to be highly active, stable, and energy-efficient and to match the working temperature of on-site hydrogen generation and consumption units. We synthesized layered gold (Au) clusters on a molybdenum carbide (α-MoC) substrate to create an interfacial catalyst system for the ultralow-temperature WGS reaction. Water was activated over α-MoC at 303 kelvin, whereas carbon monoxide adsorbed on adjacent Au sites was apt to react with surface hydroxyl groups formed from water splitting, leading to a high WGS activity at low temperatures