In silico activity and ADMET profiling of phytochemicals from Ethiopian indigenous aloes using pharmacophore models

In silico profiling is used in identification of active compounds and guide rational use of traditional medicines. Previous studies on Ethiopian indigenous aloes focused on documentation of phytochemical compositions and traditional uses. In this study, ADMET and drug-likeness properties of phytochemicals from Ethiopian indigenous aloes were evaluated, and pharmacophore-based profiling was done using Discovery Studio to predict therapeutic targets. The targets were examined using KEGG pathway, gene ontology and network analysis. Using random-walk with restart algorithm, network propagation was performed in CODA network to find diseases associated with the targets. As a result, 82 human targets were predicted and found to be involved in several molecular functions and biological processes. The targets also were linked to various cancers and diseases of immune system, metabolism, neurological system, musculoskeletal system, digestive system, hematologic, infectious, mouth and dental, and congenital disorder of metabolism. 207 KEGG pathways were enriched with the targets, and the main pathways were metabolism of steroid hormone biosynthesis, lipid and atherosclerosis, chemical carcinogenesis, and pathways in cancer. In conclusion, in silico target fishing and network analysis revealed therapeutic activities of the phytochemicals, demonstrating that Ethiopian indigenous aloes exhibit polypharmacology effects on numerous genes and signaling pathways linked to many diseases

Final design report: Spoiler Alert! Active aero for Formula SAE, Senior Design Spring 2022

The purpose of this Senior Design Project was to design and build an actively actuated front wing for the Oklahoma State Formula SAE competition car. This was accomplished using multiple engineering analysis and design methods, as well as multiple methods of product manufacturing and testing. The Aerodynamics, Mechanical, Electrical, and Testing sub-teams worked together to design and build a carbon fiber multi-tier actively actuated front wing. The results of testing showed that the wing decreased overall lap time, translating to up to an 8-place improvement in the skid pad competition, as well as up to a 12-place improvement in the autocross competition

Essays in empirical macroeconomics

This dissertation is going to empirically study household inflation expectations and inflation. Inflation expectations and inflation play a central role in economic dynamics. For example, when households expect future price increases, households will try to purchase goods now than later at higher prices which is eventually going to push prices even higher. Chapter 1 contributes to the literature on inflation expectations by showing a channel that can significantly bias the central banks' aggregate inflation expectations measures. This chapter is joint work with Carola Binder. We show that when inflation expectations surveys rely on repeat survey participants, survey participation itself may affect future responses. Because the central bank's survey asks about future prices and inflation, it prompts information acquisition between survey waves for survey respondents. These "Learning-through-Survey" effects are particularly large for household inflation expectations. For example, after participating twelve consecutive times in the SCE, respondents end up with a 2.6 percentage point lower inflation forecast and 34% lower inflation uncertainty on average than in the first interview, with most of the decline happening in the first two months of participation. Consequently, repeat participants may be more informed, and not be representative of the broader population of the economy. Chapter 2 estimates three components of household inflation expectations of the SCE using a dynamic factor model: Common, Learning, and Long-run factor. Using the estimated common inflation expectation factor shared by all survey participants, I recover the household inflation expectations less the learning effect of the SCE without discarding repeat survey participants' data which could have been wasteful otherwise. It successfully corrects for the bias due to the learning effects of repeat survey participants and is significantly less noisy than the raw data. In addition, the estimated learning factor and long-run factor of inflation expectations suggest that inflation expectations of households are largely influenced by news coverage on inflation and oil prices. Finally, Chapter 3 studies the product life cycle effects on prices and inflation inequality in the U.S. The annual inflation rate of lower-income households has been higher than that of higher-income households in general, a finding termed in extensive literature as "inflation inequality." Using barcode-level retail sales data and household spending data in the U.S, I show that the product life cycle channel can account for a significant portion of this inflation inequality among households. The prices of new products are initially high but steadily decrease after then as it goes out of fashion. Because rich households tend to be early adopters preferring new goods to old goods, those rich early adopters experience a sharp price decrease or lower inflation than poor late-adopters who buy goods when the price decreasing phase has stopped or got less steep.Economic

Phase-Redundant-Based Reliable Direct AC/AC Converter Drive for Series Hybrid Off-Highway Heavy Electric Vehicles

Hybrid electric vehicle (HEV) technology has numerous advantages over conventional vehicles, from standpoints of fuel economy, energy independence, and environmental concerns. Effective solutions for HEVs have been expanding their applications over highway vehicles, such as sedans and sport utility vehicles, into a variety of traditional vehicles. HEV systems applied to off-highway heavy-duty vehicles, which are operated by an engine, a generator, and traction motors, are investigated in this paper. This paper explores the use of a direct ac/ac converter for off-highway heavy-duty HEVs, which can directly drive traction motors from the generator with no intermediate dc conversion. In addition, a phase-redundant matrix converter structure with a backup leg and a control scheme is proposed to guarantee reliable and safe vehicle operations by providing continuous disturbance-free operations against converter faults. Fault-diagnosis techniques using line-to-line and phase voltages are presented not only to detect system malfunctions but to locate a failed switching device among 18 switching components as well. Appropriate reconfiguration structure and control actions with accurate knowledge about fault occurrence can avoid propagation of fault, which may lead to a catastrophic system failure. © 2006 IEEE.

Research on Digital Forensic Readiness Design in a Cloud Computing-Based Smart Work Environment

Recently, the work environments of organizations have been in the process of transitioning into smart work environments by applying cloud computing technology in the existing work environment. The smart work environment has the characteristic of being able to access information assets inside the company from outside the company through cloud computing technology, share information without restrictions on location by using mobile terminals, and provide a work environment where work can be conducted effectively in various locations and mobile environments. Thus, in the cloud computing-based smart work environment, changes are occurring in terms of security risks, such as an increase in the leakage risk of an organization’s information assets through mobile terminals which have a high risk of loss and theft and increase the hacking risk of wireless networks in mobile environments. According to these changes in security risk, the reactive digital forensic method, which investigates digital evidence after the occurrence of security incidents, appears to have a limit which has led to a rise in the necessity of proactive digital forensic approaches wherein security incidents can be addressed preemptively. Accordingly, in this research, we design a digital forensic readiness model at the level of preemptive prevention by considering changes in the cloud computing-based smart work environment. Firstly, we investigate previous research related to the cloud computing-based smart work environment and digital forensic readiness and analyze a total of 50 components of digital forensic readiness. In addition, through the analysis of the corresponding preceding research, we design seven detailed areas, namely, outside the organization environment, within the organization guideline, system information, terminal information, user information, usage information, and additional function. Then, we design a draft of the digital forensic readiness model in the cloud computing-based smart work environment by mapping the components of digital forensic readiness to each area. To verify the draft of the designed model, we create a survey targeting digital forensic field-related professionals, analyze their validity, and deduce a digital forensic readiness model of the cloud computing-based smart work environment consisting of seven detailed areas and 44 components. Finally, through an analytic hierarchy process analysis, we deduce the areas that should be emphasized compared to the existing work environment to heighten the forensic readiness in the cloud computing-based smart work environment. As a result, the weightings of the terminal information Universal Subscriber Identity Module(USIM) card, collect/gain virtual machine image, etc.), user information (user account information analysis, analysis of user’s used service, etc.), and usage information (mobile OS artifact timeline analysis, action analysis through timeline, etc.) appear to be higher than those of the existing work environment. This is analyzed for each organization to preemptively prepare for the components of digital forensic readiness in the corresponding areas

Unassisted overall water splitting with a solar‐to‐hydrogen efficiency of over 10% by coupled lead halide perovskite photoelectrodes

Abstract Hydrogen is a promising future sustainable fuel candidate with boundless opportunities. Research into photoelectrochemical (PEC) water splitting based on a lead halide perovskite (LHP) has progressed significantly with the aim of more efficient solar hydrogen production. Herein, we unite a well‐known photo‐absorbing LHP with cost‐effective water‐splitting catalysts, and we introduce two types of monolithic LHP‐based PEC devices that act as a photocathode and a photoanode for the hydrogen evolution reaction and oxygen evolution reaction, leading to efficient unbiased overall water splitting. Through the integration of these two monolithic LHP‐based photoelectrodes, an unbiased solar‐to‐hydrogen conversion efficiency of 10.64% and a photocurrent density of 8.65 mA cm−2 are achieved

Modified Dynamic Physical Model of Valence Change Mechanism Memristors

© 2022 American Chemical Society.Valence change-type resistance switching behaviors in oxides can be understood by well-established physical models describing the field-driven oxygen vacancy distribution change. In those models, electroformed residual oxygen vacancy filaments are crucial as they work as an electric field concentrator and limit the oxygen vacancy movement along the vertical direction. Therefore, their movement outward by diffusion is negligible. However, this situation may not be applicable in the electroforming-free system, where the field-driven movement is less prominent, and the isotropic oxygen vacancy diffusion by concentration gradient is more significant, which has not been given much consideration in the conventional model. Here, we propose a modified physical model that considers the change in the oxygen vacancies' charged state depending on their concentrations and the resulting change in diffusivity during switching to interpret the electroforming-free device behaviors. The model suggests formation of an hourglass-shaped filament constituting a lower concentration of oxygen vacancies due to the fluid oxygen diffusion in the thin oxide. Consequently, the proposed model can explain the electroforming-free device behaviors, including the retention failure mechanism, and suggest an optimized filament configuration for improved retention characteristics. The proposed model can plausibly explain both the electroformed and the electroforming-free devices. Therefore, it can be a standard model for valence change memristors.N

Unraveling the Significance of Li+/e−/O2 Phase Boundaries with a 3D-Patterned Cu Electrode for Li–O2 Batteries

The reaction kinetics at a triple-phase boundary (TPB) involving Li+, e−, and O2 dominate their electrochemical performances in Li–O2 batteries. Early studies on catalytic activities at Li+/e−/O2 interfaces have enabled great progress in energy efficiency; however, localized TPBs within the cathode hamper innovations in battery performance toward commercialization. Here, the effects of homogenized TPBs on the reaction kinetics in air cathodes with structurally designed pore networks in terms of pore size, interconnectivity, and orderliness are explored. The diffusion fluxes of reactants are visualized by modeling, and the simulated map reveals evenly distributed reaction areas within the periodic open structure. The 3D air cathode provides highly active, homogeneous TPBs over a real electrode scale, thus simultaneously achieving large discharge capacity, unprecedented energy efficiency, and long cyclability via mechanical/electrochemical stress relaxation. Homogeneous TPBs by cathode structural engineering provide a new strategy for improving the reaction kinetics beyond controlling the intrinsic properties of the materials. © 2023 Wiley-VCH GmbH.FALS

Synapse-Enriched m6A-Modified Malat1 Interacts with the Novel m6A Reader, DPYSL2, and Is Required for Fear-Extinction Memory.

The RNA modification N6-methyladenosine (m6A) regulates the interaction between RNA and various RNA binding proteins within the nucleus and other subcellular compartments and has recently been shown to be involved in experience-dependent plasticity, learning, and memory. Using m6A RNA-sequencing, we have discovered a distinct population of learning-related m6A- modified RNAs at the synapse, which includes the long noncoding RNA metastasis-associated lung adenocarcinoma transcript 1 (Malat1). RNA immunoprecipitation and mass spectrometry revealed 12 new synapse-specific learning-induced m6A readers in the mPFC of male C57/BL6 mice, with m6A-modified Malat1 binding to a subset of these, including CYFIP2 and DPYSL2. In addition, a cell type- and synapse-specific, and state-dependent, reduction of m6A on Malat1 impairs fear-extinction memory; an effect that likely occurs through a disruption in the interaction between Malat1 and DPYSL2 and an associated decrease in dendritic spine formation. These findings highlight the critical role of m6A in regulating the functional state of RNA during the consolidation of fear-extinction memory, and expand the repertoire of experience-dependent m6A readers in the synaptic compartment.SIGNIFICANCE STATEMENT We have discovered that learning-induced m6A-modified RNA (including the long noncoding RNA, Malat1) accumulates in the synaptic compartment. We have identified several new m6A readers that are associated with fear extinction learning and demonstrate a causal relationship between m6A-modified Malat1 and the formation of fear-extinction memory. These findings highlight the role of m6A in regulating the functional state of an RNA during memory formation and expand the repertoire of experience-dependent m6A readers in the synaptic compartment