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.

Photosynthesis, a process catalysed by plants, algae and cyanobacteria converts sunlight to energy thus sustaining all higher life on Earth. Two large membrane protein complexes, photosystem I and II (PSI and PSII), act in series to catalyse the light-driven reactions in photosynthesis. PSII catalyses the light-driven water splitting process, which maintains the Earth’s oxygenic atmosphere. In this process, the oxygen-evolving complex (OEC) of PSII cycles through five states, S₀ to S₄, in which four electrons are sequentially extracted from the OEC in four light-driven charge-separation events. Here we describe time resolved experiments on PSII nano/microcrystals from Thermosynechococcus elongatus performed with the recently developed technique of serial femtosecond crystallography. Structures have been determined from PSII in the dark S₁ state and after double laser excitation (putative S₃ state) at 5 and 5.5 Å resolution, respectively. The results provide evidence that PSII undergoes significant conformational changes at the electron acceptor side and at the Mn₄CaO₅ core of the OEC. These include an elongation of the metal cluster, accompanied by changes in the protein environment, which could allow for binding of the second substrate water molecule between the more distant protruding Mn (referred to as the ‘dangler’ Mn) and the Mn₃CaO_x cubane in the S₂ to S₃ transition, as predicted by spectroscopic and computational studies. This work shows the great potential for time-resolved serial femtosecond crystallography for investigation of catalytic processes in biomolecules.

We present results from experiments at the Linac Coherent Light Source (LCLS) demonstrating that serial femtosecond crystallography (SFX) can be performed to high resolution (~2.5 Å) using protein microcrystals deposited on an ultra-thin silicon nitride membrane and embedded in a preservation medium at room temperature. Data can be acquired at a high acquisition rate using x-ray free electron laser sources to overcome radiation damage, while sample consumption is dramatically reduced compared to flowing jet methods. We achieved a peak data acquisition rate of 10 Hz with a hit rate of ~38%, indicating that a complete data set could be acquired in about one 12-hour LCLS shift using the setup described here, or in even less time using hardware optimized for fixed target SFX. This demonstration opens the door to ultra low sample consumption SFX using the technique of diffraction-before-destruction on proteins that exist in only small quantities and/or do not produce the copious quantities of microcrystals required for flowing jet methods.

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.

Previous proof-of-concept measurements on single-layer two-dimensional membrane-protein crystals performed at X-ray free-electron lasers (FELs) have demonstrated that the collection of meaningful diffraction patterns, which is not possible at synchrotrons because of radiation-damage issues, is feasible. Here, the results obtained from the analysis of a thousand single-shot, room-temperature X-ray FEL diffraction images from two-dimensional crystals of a bacteriorhodopsin mutant are reported in detail. The high redundancy in the measurements boosts the intensity signal-to-noise ratio, so that the values of the diffracted intensities can be reliably determined down to the detector-edge resolution of 4 Å. The results show that two-dimensional serial crystallography at X-ray FELs is a suitable method to study membrane proteins to near-atomic length scales at ambient temperature. The method presented here can be extended to pump–probe studies of optically triggered structural changes on submillisecond timescales in two-dimensional crystals, which allow functionally relevant large-scale motions that may be quenched in three-dimensional crystals.

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.