ASU Scholarship Showcase

This study dealt with emotional responses elicited by certain products, which helped to understand the attributes of the product leading to emotional responses. Emotional Design is a way of design that is using emotions generated by people as reference and measurement. Making good use of emotional design could let the user discover resonance in the interaction between user and product, which could help the product to be more attractive to users. This research proposes to apply qualitative research method to uncover the secrets of emotional bonds between users and products This study also offered an useful tool to examine the strength and weakness of a certain product from perspective of emotion, and the insights could help designers to refine the product to become emotional attractive, thus create better user experience and bigger opportunity for the product on the market in the future.

A structurally and compositionally well-defined and spectrally tunable artificial light-harvesting system has been constructed in which multiple organic dyes attached to a three-arm-DNA nanostructure serve as an antenna conjugated to a photosynthetic reaction center isolated from Rhodobacter sphaeroides 2.4.1. The light energy absorbed by the dye molecules is transferred to the reaction center, where charge separation takes place. The average number of DNA three-arm junctions per reaction center was tuned from 0.75 to 2.35. This DNA-templated multichromophore system serves as a modular light-harvesting antenna that is capable of being optimized for its spectral properties, energy transfer efficiency, and photostability, allowing one to adjust both the size and spectrum of the resulting structures. This may serve as a useful test bed for developing nanostructured photonic systems.

Time-resolved fluorescence spectroscopy was used to explore the pathway and kinetics of energy transfer in photosynthetic membrane vesicles (chromatophores) isolated from Rhodobacter (Rba.) sphaeroides cells harvested 2, 4, 6 or 24 hours after a transition from growth in high to low level illumination. As previously observed, this light intensity transition initiates the remodeling of the photosynthetic apparatus and an increase in the number of light harvesting 2 (LH2) complexes relative to light harvesting 1 (LH1) and reaction center (RC) complexes. It has generally been thought that the increase in LH2 complexes served the purpose of increasing the overall energy transmission to the RC. However, fluorescence lifetime measurements and analysis in terms of energy transfer within LH2 and between LH2 and LH1 indicate that, during the remodeling time period measured, only a portion of the additional LH2 generated are well connected to LH1 and the reaction center. The majority of the additional LH2 fluorescence decays with a lifetime comparable to that of free, unconnected LH2 complexes. The presence of large LH2-only domains has been observed by atomic force microscopy in Rba. sphaeroides chromatophores (Bahatyrova et al., Nature, 2004, 430, 1058), providing structural support for the existence of pools of partially connected LH2 complexes. These LH2-only domains represent the light-responsive antenna complement formed after a switch in growth conditions from high to low illumination, while the remaining LH2 complexes occupy membrane regions containing mixtures of LH2 and LH1–RC core complexes. The current study utilized a multi-parameter approach to explore the fluorescence spectroscopic properties related to the remodeling process, shedding light on the structure-function relationship of the photosynthetic assembles. Possible reasons for the accumulation of these largely disconnected LH2-only pools are discussed.

The image of “Shostakovich” and the relationships surrounding it in the West during the Cold War can be viewed from several angles. Selected Cold War encounters between the United States and the Soviet Union involving Shostakovich’s music—especially the 1959 New York Philharmonic tour to the USSR—offer insight into three perspectives on Shostakovich symphonies in the Cold War: (1) the direct, (2) the implicit, and (3) the micro/intimate. This heuristic hones our understanding of the various types of relationships cultivated with music during the Cold War, while also widening the discussion of Shostakovich’s symbolic presentation during the conflict.

An urban forest assessment is essential for developing a baseline from which to measure changes and trends. The most precise way to assess urban forests is to measure and record every tree on a site, but although this may work well for relatively small populations (e.g., street trees, small parks), it is prohibitively expensive for large tree populations. Thus, random sampling offers a cost-effective way to assess urban forest structure and the associated ecosystem services for large-scale assessments. The methodology applied to assess ecosystem services in this study can also be used to assess the ecosystem services provided by vacant land in other urban contexts and improve urban forest policies, planning, and the management of vacant land. The study’s findings support the inclusion of trees on vacant land and contribute to a new vision of vacant land as a valuable ecological resource by demonstrating how green infrastructure can be used to enhance ecosystem health and promote a better quality of life for city residents.

The estimation of energy demand (by power plants) has traditionally relied on historical energy use data for the region(s) that a plant produces for. Regression analysis, artificial neural network and Bayesian theory are the most common approaches for analysing these data. Such data and techniques do not generate reliable results. Consequently, excess energy has to be generated to prevent blackout; causes for energy surge are not easily determined; and potential energy use reduction from energy efficiency solutions is usually not translated into actual energy use reduction. The paper highlights the weaknesses of traditional techniques, and lays out a framework to improve the prediction of energy demand by combining energy use models of equipment, physical systems and buildings, with the proposed data mining algorithms for reverse engineering. The research team first analyses data samples from large complex energy data, and then, presents a set of computationally efficient data mining algorithms for reverse engineering. In order to develop a structural system model for reverse engineering, two focus groups are developed that has direct relation with cause and effect variables. The research findings of this paper includes testing out different sets of reverse engineering algorithms, understand their output patterns and modify algorithms to elevate accuracy of the outputs.

Small and medium office buildings consume a significant parcel of the U.S. building stock energy consumption. Still, owners lack resources and experience to conduct detailed energy audits and retrofit analysis. We present an eight-steps framework for an energy retrofit assessment in small and medium office buildings. Through a bottom-up approach and a web-based retrofit toolkit tested on a case study in Arizona, this methodology was able to save about 50% of the total energy consumed by the case study building, depending on the adopted measures and invested capital. While the case study presented is a deep energy retrofit, the proposed framework is effective in guiding the decision-making process that precedes any energy retrofit, deep or light.

Commercial buildings’ consumption is driven by multiple factors that include occupancy, system and equipment efficiency, thermal heat transfer, equipment plug loads, maintenance and operational procedures, and outdoor and indoor temperatures. A modern building energy system can be viewed as a complex dynamical system that is interconnected and influenced by external and internal factors. Modern large scale sensor measures some physical signals to monitor real-time system behaviors. Such data has the potentials to detect anomalies, identify consumption patterns, and analyze peak loads. The paper proposes a novel method to detect hidden anomalies in commercial building energy consumption system. The framework is based on Hilbert-Huang transform and instantaneous frequency analysis. The objectives are to develop an automated data pre-processing system that can detect anomalies and provide solutions with real-time consumption database using Ensemble Empirical Mode Decomposition (EEMD) method. The finding of this paper will also include the comparisons of Empirical mode decomposition and Ensemble empirical mode decomposition of three important type of institutional buildings.

There are an increasing variety of applications in which peptides are both synthesized and used attached to solid surfaces. This has created a need for high throughput sequence analysis directly on surfaces. However, common sequencing approaches that can be adapted to surface bound peptides lack the throughput often needed in library-based applications. Here we describe a simple approach for sequence analysis directly on solid surfaces that is both high speed and high throughput, utilizing equipment available in most protein analysis facilities. In this approach, surface bound peptides, selectively labeled at their N-termini with a positive charge-bearing group, are subjected to controlled degradation in ammonia gas, resulting in a set of fragments differing by a single amino acid that remain spatially confined on the surface they were bound to. These fragments can then be analyzed by MALDI mass spectrometry, and the peptide sequences read directly from the resulting spectra.

Communicating climate risks is crucial when engaging the public to support climate action planning and addressing climate justice. How does evidence-based communication influence local residents’ risk perception and potential behavior change in support of climate planning? Built upon our previous study of Climate Justice maps illustrating high scores of both social and ecological vulnerability in Michigan’s Huron River watershed, USA, a quasi-experiment was conducted to examine the effects of Climate Justice mapping intervention on residents’ perceptions and preparedness for climate change associated hazards in Michigan. Two groups were compared: residents in Climate Justice areas with high social and ecological vulnerability scores in the watershed (n=76) and residents in comparison areas in Michigan (n=69). Measurements for risk perception include perceived exposure, sensitivity, and adaptability to hazards. Results indicate that risk information has a significant effect on perceived sensitivity and level of preparedness for future climate extremes among participants living in Climate Justice areas. Findings highlight the value of integrating scientific risk assessment information in risk communication to align calculated and perceived risks. This study suggests effective risk communication can influence local support of climate action plans and implementation of strategies that address climate justice and achieve social sustainability in local communities.