ASU Scholarship Showcase

Perchloroethylene (PCE) is a highly utilized solvent in the dry cleaning industry because of its cleaning effectiveness and relatively low cost to consumers. According to the 2006 U.S. Census, approximately 28,000 dry cleaning operations used PCE as their principal cleaning agent. Widespread use of PCE is problematic because of its adverse impacts on human health and environmental quality. As PCE use is curtailed, effective alternatives must be analyzed for their toxicity and impacts to human health and the environment. Potential alternatives to PCE in dry cleaning include dipropylene glycol n-butyl ether (DPnB) and dipropylene glycol tert-butyl ether (DPtB), both promising to pose a relatively smaller risk. To evaluate these two alternatives to PCE, we established and scored performance criteria, including chemical toxicity, employee and customer exposure levels, impacts on the general population, costs of each system, and cleaning efficacy. The scores received for PCE were 5, 5, 3, 5, 3, and 3, respectively, and DPnB and DPtB scored 3, 1, 2, 2, 4, and 4, respectively. An aggregate sum of the performance criteria yielded a favorably low score of “16” for both DPnB and DPtB compared to “24” for PCE. We conclude that DPnB and DPtB are preferable dry cleaning agents, exhibiting reduced human toxicity and a lesser adverse impact on human health and the environment compared to PCE, with comparable capital investments, and moderately higher annual operating costs.

We investigate near-field radiative heat transfer between Indium Tin Oxide (ITO) nanowire arrays which behave as type 1 and 2 hyperbolic metamaterials. Using spatial dispersion dependent effective medium theory to model the dielectric function of the nanowires, the impact of filling fraction on the heat transfer is analyzed. Depending on the filling fraction, it is possible to achieve both types of hyperbolic modes. At 150 nm vacuum gap, the heat transfer between the nanowires with 0.5 filling fraction can be 11 times higher than that between two bulk ITOs. For vacuum gaps less than 150 nm the heat transfer increases as the filling fraction decreases. Results obtained from this study will facilitate applications of ITO nanowires as hyperbolic metamaterials for energy systems.

The objective of this study was to find out the impact of environmental conditions on the survival of intestinal parasites on environmental surfaces commonly implicated in the transmission of these parasites. The study was performed by incubating Cryptosporidium and Giardia (oo)cysts on environmentally relevant surfaces such as brushed stainless steel, formica, ceramic, fabric, and skin. Parallel experiments were conducted using clean and soiled coupons incubated under three temperatures. The die-off coefficient rates (K) were calculated using first-order exponential formula. For both parasites, the fastest die-off was recorded on fabric, followed by ceramic, formica, skin, and steel. Die-off rates were directly correlated to the incubation temperatures and surface porosity. The presence of organic matter enhanced the survivability of the resting stages of test parasites. The decay rates calculated in this study can be used in models for public health decision-making process and highlights the mitigation role of hand hygiene agents in their prevention and control.

The projected changes in the downward solar radiation at the surface over North America for late 21st century are deduced from global climate model simulations with greenhouse-gas (GHG) forcing. A robust trend is found in winter over the United States, which exhibits a simple pattern of a decrease of sunlight over Northern USA. and an increase of sunlight over Southern USA. This structure was identified in both the seasonal mean and the mean climatology at different times of the day. It is broadly consistent with the known poleward shift of storm tracks in winter in climate model simulations with GHG forcing. The centennial trend of the downward shortwave radiation at the surface in Northern USA. is on the order of 10% of the climatological value for the January monthly mean, and slightly over 10% at the time when it is midday in the United States. This indicates a nonnegligible influence of the GHG forcing on solar energy in the long term. Nevertheless, when dividing the 10% by a century, in the near term, the impact of the GHG forcing is relatively minor such that the estimate of solar power potential using present-day climatology will remain useful in the coming decades.

Dual-task tests can identify gait characteristics peculiar to fallers and nonfallers. Understanding the relationship between gait performance and dual-task related cognitive-motor interference is important for fall prevention. Dual-task adapted changes in gait instability/variability can adversely affect fall risks. Although implicated, it is unclear if healthy participants’ fall risks are modified by dual-task walking conditions. Seven healthy young and seven healthy older adults were randomly assigned to normal walking and dual-task walking sessions with a slip perturbation. In the dual-task session, the participants walked and simultaneously counted backwards from a randomly provided number. The results indicate that the gait changes in dual-task walking have no destabilizing effect on gait and slip responses in healthy individuals. We also found that, during dual-tasking, healthy individuals adopted cautious gait mode (CGM) strategy that is characterized by reduced walking speed, shorter step length, increased step width, and reduced heel contact velocity and is likely to be an adaptation to minimize attentional demand and decrease slip and fall risk during limited available attentional resources. Exploring interactions between gait variability and cognitive functions while walking may lead to designing appropriate fall interventions among healthy and patient population with fall risk.

Health systems are heavily promoting patient portals. However, limited health literacy (HL) can restrict online communication via secure messaging (SM) because patients’ literacy skills must be sufficient to convey and comprehend content while clinicians must encourage and elicit communication from patients and match patients’ literacy level. This paper describes the Employing Computational Linguistics to Improve Patient-Provider Secure Email (ECLIPPSE) study, an interdisciplinary effort bringing together scientists in communication, computational linguistics, and health services to employ computational linguistic methods to (1) create a novel Linguistic Complexity Profile (LCP) to characterize communications of patients and clinicians and demonstrate its validity and (2) examine whether providers accommodate communication needs of patients with limited HL by tailoring their SM responses. We will study >5 million SMs generated by >150,000 ethnically diverse type 2 diabetes patients and >9000 clinicians from two settings: an integrated delivery system and a public (safety net) system. Finally, we will then create an LCP-based automated aid that delivers real-time feedback to clinicians to reduce the linguistic complexity of their SMs. This research will support health systems’ journeys to become health literate healthcare organizations and reduce HL-related disparities in diabetes care.

Background: This paper introduces a tool for streamlining data integration in rehabilitation science, the Centralized Open-Access Rehabilitation database for Stroke (SCOAR), which allows researchers to quickly visualize relationships among variables, efficiently share data, generate hypotheses, and enhance clinical trial design.

Methods: Bibliographic databases were searched according to inclusion criteria leaving 2,892 titles that were further screened to 514 manuscripts to be screened by full text, leaving 215 randomized controlled trials (RCTs) in the database (489 independent groups representing 12,847 patients). Demographic, methodological, and statistical data were extracted by independent coders and entered into SCOAR.

Results: Trial data came from 114 locations in 27 different countries and represented patients with a wide range of ages, 62 year [41; 85] [shown as median (range)] and at various stages of recovery following their stroke, 141 days [1; 3372]. There was considerable variation in the dose of therapy that patients received, 20 h [0; 221], over interventions of different durations, 28 days [10; 365]. There was also a lack of common data elements (CDEs) across trials, but this lack of CDEs was most pronounced for baseline assessments of patient impairment and severity of stroke.

Conclusion: Data integration across hundreds of RCTs allows clinicians and researchers to quickly visualize data from the history of the field and lays the foundation for making SCOAR a living database to which researchers can upload new data as trial results are published. SCOAR is a useful tool for clinicians and researchers that will facilitate data visualization, data sharing, the finding of relevant past studies, and the design of clinical trials by enabling more accurate and comprehensive power analyses. Furthermore, these data speak to the need for CDEs specific to stroke rehabilitation in randomized controlled trials.

Myoelectric artificial limbs can significantly advance the state of the art in prosthetics, since they can be used to control mechatronic devices through muscular activity in a way that mimics how the subjects used to activate their muscles before limb loss. However, surveys indicate that dissatisfaction with the functionality of terminal devices underlies the widespread abandonment of prostheses. We believe that one key factor to improve acceptability of prosthetic devices is to attain human likeness of prosthesis movements, a goal which is being pursued by research on social and human–robot interactions. Therefore, to reduce early abandonment of terminal devices, we propose that controllers should be designed so as to ensure effective task accomplishment in a natural fashion. In this work, we have analyzed and compared the performance of three types of myoelectric controller algorithms based on surface electromyography to control an underactuated and multi-degrees of freedom prosthetic hand, the SoftHand Pro.

The goal of the present study was to identify the myoelectric algorithm that best mimics the native hand movements. As a preliminary step, we first quantified the repeatability of the SoftHand Pro finger movements and identified the electromyographic recording sites for able-bodied individuals with the highest signal-to-noise ratio from two pairs of muscles, i.e., flexor digitorum superficialis/extensor digitorum communis, and flexor carpi radialis/extensor carpi ulnaris. Able-bodied volunteers were then asked to execute reach-to-grasp movements, while electromyography signals were recorded from flexor digitorum superficialis/extensor digitorum communis as this was identified as the muscle pair characterized by high signal-to-noise ratio and intuitive control. Subsequently, we tested three myoelectric controllers that mapped electromyography signals to position of the SoftHand Pro. We found that a differential electromyography-to-position mapping ensured the highest coherence with hand movements. Our results represent a first step toward a more effective and intuitive control of myoelectric hand prostheses.

Extensive literatures have shown approaches for decoding upper limb kinematics or muscle activity using multichannel cortical spike recordings toward brain machine interface (BMI) applications. However, similar topics regarding lower limb remain relatively scarce. We previously reported a system for training monkeys to perform visually guided stand and squat tasks. The current study, as a follow-up extension, investigates whether lower limb kinematics and muscle activity characterized by electromyography (EMG) signals during monkey performing stand/squat movements can be accurately decoded from neural spike trains in primary motor cortex (M1).

Two monkeys were used in this study. Subdermal intramuscular EMG electrodes were implanted to 8 right leg/thigh muscles. With ample data collected from neurons from a large brain area, we performed a spike triggered average (SpTA) analysis and got a series of density contours which revealed the spatial distributions of different muscle-innervating neurons corresponding to each given muscle. Based on the guidance of these results, we identified the locations optimal for chronic electrode implantation and subsequently carried on chronic neural data recordings. A recursive Bayesian estimation framework was proposed for decoding EMG signals together with kinematics from M1 spike trains.

Two specific algorithms were implemented: a standard Kalman filter and an unscented Kalman filter. For the latter one, an artificial neural network was incorporated to deal with the nonlinearity in neural tuning. High correlation coefficient and signal to noise ratio between the predicted and the actual data were achieved for both EMG signals and kinematics on both monkeys. Higher decoding accuracy and faster convergence rate could be achieved with the unscented Kalman filter. These results demonstrate that lower limb EMG signals and kinematics during monkey stand/squat can be accurately decoded from a group of M1 neurons with the proposed algorithms. Our findings provide new insights for extending current BMI design concepts and techniques on upper limbs to lower limb circumstances. Brain controlled exoskeleton, prostheses or neuromuscular electrical stimulators for lower limbs are expected to be developed, which enables the subject to manipulate complex biomechatronic devices with mind in more harmonized manner.

Increasing temperatures have been shown to impact soil biogeochemical processes, although the corresponding changes to the underlying microbial functional communities are not well understood. Alterations in the nitrogen (N) cycling functional component are particularly important as N availability can affect microbial decomposition rates of soil organic matter and influence plant productivity. To assess changes in the microbial component responsible for these changes, the composition of the N-fixing (nifH), and denitrifying (nirS, nirK, nosZ) soil microbial communities was assessed by targeted pyrosequencing of functional genes involved in N cycling in two major biomes where the experimental effect of climate warming is under investigation, a tallgrass prairie in Oklahoma (OK) and the active layer above permafrost in Alaska (AK). Raw reads were processed for quality, translated with frameshift correction, and a total of 313,842 amino acid sequences were clustered and linked to a nearest neighbor using reference datasets. The number of OTUs recovered ranged from 231 (NifH) to 862 (NirK). The N functional microbial communities of the prairie, which had experienced a decade of experimental warming were the most affected with changes in the richness and/or overall structure of NifH, NirS, NirK and NosZ. In contrast, the AK permafrost communities, which had experienced only 1 year of warming, showed decreased richness and a structural change only with the nirK-harboring bacterial community. A highly divergent nirK-harboring bacterial community was identified in the permafrost soils, suggesting much novelty, while other N functional communities exhibited similar relatedness to the reference databases, regardless of site. Prairie and permafrost soils also harbored highly divergent communities due mostly to differing major populations.