ASU Scholarship Showcase

Significance: Modification of cysteine thiols dramatically affects protein function and stability. Hence, the abilities to quantify specific protein sulfhydryl groups within complex biological samples and map disulfide bond structures are crucial to gaining greater insights into how proteins operate in human health and disease. Recent Advances: Many different molecular probes are now commercially available to label and track cysteine residues at great sensitivity. Coupled with mass spectrometry, stable isotope-labeled sulfhydryl-specific reagents can provide previously unprecedented molecular insights into the dynamics of cysteine modification. Likewise, the combined application of modern mass spectrometers with improved sample preparation techniques and novel data mining algorithms is beginning to routinize the analysis of complex protein disulfide structures. Critical Issues: Proper application of these modern tools and techniques, however, still requires fundamental understanding of sulfhydryl chemistry as well as the assumptions that accompany sample preparation and underlie effective data interpretation. Future Directions: The continued development of tools, technical approaches, and corresponding data processing algorithms will, undoubtedly, facilitate site-specific protein sulfhydryl quantification and disulfide structure analysis from within complex biological mixtures with ever-improving accuracy and sensitivity. Fully routinizing disulfide structure analysis will require an equal but balanced focus on sample preparation and corresponding mass spectral dataset reproducibility.

To date, little research has been performed regarding the planning and management of “small” projects – those projects typically differentiated from “large” projects due to having lower costs. In 2013, The Construction Industry Institute (CII) set out to develop a front end planning tool that will provide practitioners with a standardized process for planning small projects in the industrial sector. The research team determined that data should be sought from industry regarding small industrial projects to ensure applicability, effectiveness and validity of the new tool. The team developed and administered a survey to determine (1) the prevalence of small projects, (2) the planning processes currently in use for small projects, and (3) current metrics used by industry to differentiate between small and large projects. The survey data showed that small projects make up a majority of projects completed in the industrial sector, planning of these projects varies greatly across the industry, and the metrics posed in the survey were mostly not appropriate for use in differentiating between small and large projects. This study contributes to knowledge through adding to the limited research surrounding small projects, and suggesting future research regarding using measures of project complexity to differentiate between small and large projects.

For the past three decades, the Saudi construction industry (SCI) has exhibited poor performance. Many research efforts have tried to identify the problem and the potential causes but there have been few publications identifying ways to mitigate the problem and describing testing to validate the proposed solution. This paper examines the research and development (R&D) approach in the SCI. A literature research was performed identifying the impact that R&D has had on the SCI. A questionnaire was also created for surveying industry professionals and researchers. The results show evidence that the SCI practice and the academic research work exist in separate silos. This study recommends a change of mindset in both the public and private sector on their views on R&D since cooperation is required to create collaboration between the two sectors and improve the competitiveness of the country's economy.

The principles of a new project management model have been tested for the past 20 years. This project management model utilizes expertise instead of the traditional management, direction, and control (MDC). This new project management model is a leadership-based model instead of a management model. The practice of the new model requires a change in paradigm and project management structure. Some of the practices of this new paradigm include minimizing the flow of information and communications to and from the project manager [including meetings, emails and documents], eliminating technical communications, reducing client management, direction, and control of the vendor, and the hiring of vendors or personnel to do specific tasks. A vendors is hired only after they have clearly shown that they know what they are doing by showing past performance on similar projects, that they clearly understand how to create transparency to minimize risk that they do not control, and that they can clearly outline their project plan using a detailed milestone schedule including time, cost, and tasks all communicated in the language of metrics.

Load associated fatigue cracking is one of the major distress types occurring in flexible pavements. Flexural bending beam fatigue laboratory test has been used for several decades and is considered an integral part of the Superpave advanced characterization procedure. One of the most significant solutions to sustain the fatigue life for an asphaltic mixture is to add sustainable materials such as rubber or polymers to the asphalt mixture. A laboratory testing program was performed on three gap-graded mixtures: unmodified, Asphalt Rubber (AR) and polymer-modified. Strain controlled fatigue tests were conducted according to the AASHTO T321 procedure. The results from the beam fatigue tests indicated that the AR and polymer-modified gap graded mixtures would have much longer fatigue lives compared to the reference (unmodified) mixture. In addition, a mechanistic analysis using 3D-Move software coupled with a cost-effectiveness analysis study based on the fatigue performance on the three mixtures were performed. Overall, the analysis showed that the AR and polymer-modified asphalt mixtures exhibited significantly higher cost-effectiveness compared to unmodified HMA mixture. Although AR and polymer-modification increases the cost of the material, the analysis showed that they are more cost effective than the unmodified mixture.

As gesture interfaces become more main-stream, it is increasingly important to investigate the behavioral characteristics of these interactions – particularly in three-dimensional (3D) space. In this study, Fitts’ method was extended to such input technologies, and the applicability of Fitts’ law to gesture-based interactions was examined. The experiment included three gesture-based input devices that utilize different techniques to capture user movement, and compared them to conventional input technologies like touchscreen and mouse. Participants completed a target-acquisition test and were instructed to move a cursor from a home location to a spherical target as quickly and accurately as possible. Three distances and three target sizes were tested six times in a randomized order for all input devices. A total of 81 participants completed all tasks. Movement time, error rate, and throughput were calculated for each input technology. Results showed that the mean movement time was highly correlated with the target's index of difficulty for all devices, providing evidence that Fitts’ law can be extended and applied to gesture-based devices. Throughputs were found to be significantly lower for the gesture-based devices compared to mouse and touchscreen, and as the index of difficulty increased, the movement time increased significantly more for these gesture technologies. Error counts were statistically higher for all gesture-based input technologies compared to mouse. In addition, error counts for all inputs were highly correlated with target width, but little impact was shown by movement distance. Overall, the findings suggest that gesture-based devices can be characterized by Fitts’ law in a similar fashion to conventional 1D or 2D devices.

Anode-respiring bacteria (ARB) generate electric current in microbial electrochemical cells (MXCs) by channeling electrons from the oxidation of organic substrates to an electrode. Production of high current densities by monocultures in MXCs has resulted almost exclusively from the activity of Geobacter sulfurreducens, a neutrophilic freshwater Fe(III)-reducing bacterium and the highest-current-producing member documented for the Geobacteraceae family of the Deltaproteobacteria. Here we report high current densities generated by haloalkaliphilic Geoalkalibacter spp., thus broadening the capability for high anode respiration rates by including other genera within the Geobacteraceae. In this study, acetate-fed pure cultures of two related Geoalkalibacter spp. produced current densities of 5.0 to 8.3 and 2.4 to 3.3 A m^-2 under alkaline (pH 9.3) and saline (1.7% NaCl) conditions, respectively. Chronoamperometric studies of halophilic Glk. subterraneus DSM 23483 and alkaliphilic Glk. ferrihydriticus DSM 17813 suggested that cells performed long-range electron transfer through electrode-attached biofilms and not through soluble electron shuttles. Glk. ferrihydriticus also oxidized ethanol directly to produce current, with maximum current densities of 5.7 to 7.1 A m^-2 and coulombic efficiencies of 84 to 95%. Cyclic voltammetry (CV) elicited a sigmoidal response with characteristic onset, midpoint, and saturation potentials, while CV performed in the absence of an electron donor suggested the involvement of redox molecules in the biofilm that were limited by diffusion. These results matched those previously reported for actively respiring Gb. sulfurreducens biofilms producing similar current densities (~5 to 9 A m^-2).

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.

A typical building construction process runs through three main consecutive phases: design, construction and operation. Currently, architects and engineers both engage in the creation of environmental designs that adequately reflect high performance through sustainability and energy efficiency in new buildings. Occupants of buildings have also recently demonstrated a dramatic increase in awareness regarding building operation, energy usage, and indoor air quality. The process of building construction is chronologically located between both the design and the operation phases. However, this phase has not yet been addressed in either understanding contractor behavior or developing innovative sustainable techniques. These two vital aspects have the potential to levy a dramatic impact on enhancing building performance and operational costs.

Repeatedly causing apprehension to the construction industry is a question that posits, “Why is there a gap/delta/inconsistency between the designed EUI, Energy Use Intensity, and the operational EUI”? Building occupants shall not be the only party that bears blame for the delta in energy. It is true, nonetheless, that occupants are part of the reason, but the contractor – as well as the entire construction phase - also remain prime suspects worth investigating. In the present time, research is predominantly focused on occupants (post-occupancy) and designers to educate and control the gap between designed and operational EUI. This research has succeeded in the identification of the construction phase, in conjunction with contractor behavior, as another main factor for initiating this energy gap. Therefore, not only is the coupling of sustainable strategies to the construction drivers crucial to attaining a sustainable project, but also it is integral to analyzing contractor behavior within each of the construction phases that play a vital role in successfully serving sustainability. Various techniques and approaches will assist contractors in amending their method statements to ensure a sustainable project.

This research correlates an existing project to the two proposed sustainable concepts: 1) Identify cost-saving strategies that may have been implemented or avoided during the construction process, and 2) Evaluate the impacts of implementing these strategies on overall performance. The adopted contexts are to partially foster sustainable architecture concepts to the Contractor process, and then proceed to analyze its cost implication on overall project performance. Results of the validation of this approach verify that when contractors embrace a sustainable construction process the overall project will yield various financial savings. A mixed-use project was utilized to validate these concepts, which indicated three outcomes: firstly, a 25% decrease in manpower for tiling while maintaining the same productivity, thus reflecting a saving of $3,500; next, increasing the productivity of concrete activity, which would shorten the duration of the construction by 45 days and reflect a saving of $1.5 million, and last of all, reducing the overhead costs of labor camps by efficiently orienting temporary shelters, which reveals a reduction in cooling and heating that returned a saving of approximately $10,000. This research develops a comprehensive evidence-based study that addresses the above-mentioned gap in the construction phase, which targets to yield a multi-dimensional tool that will allow: 1) integrating critical thinking and decision-making approaches regarding contractor behavior, and 2) adopting innovative sustainable construction methods that reflect reduction in operating costs.

Research has shown that construction projects in Saudi Arabia have exhibited poor performance for the past three decades. The traditional risk management practices have been ineffective at helping contractors deliver projects on time and within budget while meeting quality expectations. Studies have identified that client decision making is one of the main causes of risks that occur on projects in Saudi Arabia. This paper proposes a new risk management model that can minimize client decision making, and enable the client to utilize expertise, thereby improving project quality and performance. The model is derived from the Information Measurement Theory (IMT) and Performance Information Procurement System (PIPS), both developed at Arizona State University in the United States (U.S.). The model has been tested over 1800 times in both construction and non-construction projects, showing a decrease in required management by owner by up to 80% and an increase in efficiency up to 40%.