ASU Scholarship Showcase

Of particular interest to the neuroscience and robotics communities is the understanding of how two humans could physically collaborate to perform motor tasks such as holding a tool or moving it across locations. When two humans physically interact with each other, sensory consequences and motor outcomes are not entirely predictable as they also depend on the other agent’s actions. The sensory mechanisms involved in physical interactions are not well understood. The present study was designed (1) to quantify human–human physical interactions where one agent (“follower”) has to infer the intended or imagined—but not executed—direction of motion of another agent (“leader”) and (2) to reveal the underlying strategies used by the dyad. This study also aimed at verifying the extent to which visual feedback (VF) is necessary for communicating intended movement direction. We found that the control of leader on the relationship between force and motion was a critical factor in conveying his/her intended movement direction to the follower regardless of VF of the grasped handle or the arms. Interestingly, the dyad’s ability to communicate and infer movement direction with significant accuracy improved (>83%) after a relatively short amount of practice. These results indicate that the relationship between force and motion (interpreting as arm impedance modulation) may represent an important means for communicating intended movement direction between biological agents, as indicated by the modulation of this relationship to intended direction. Ongoing work is investigating the application of the present findings to optimize communication of high-level movement goals during physical interactions between biological and non-biological agents.

Three-dimensional models of human intestinal epithelium mimic the differentiated form and function of parental tissues often not exhibited by two-dimensional monolayers and respond to Salmonella in key ways that reflect in vivo infections. To further enhance the physiological relevance of three-dimensional models to more closely approximate in vivo intestinal microenvironments encountered by Salmonella, we developed and validated a novel three-dimensional co-culture infection model of colonic epithelial cells and macrophages using the NASA Rotating Wall Vessel bioreactor. First, U937 cells were activated upon collagen-coated scaffolds. HT-29 epithelial cells were then added and the three-dimensional model was cultured in the bioreactor until optimal differentiation was reached, as assessed by immunohistochemical profiling and bead uptake assays. The new co-culture model exhibited in vivo-like structural and phenotypic characteristics, including three-dimensional architecture, apical-basolateral polarity, well-formed tight/adherens junctions, mucin, multiple epithelial cell types, and functional macrophages. Phagocytic activity of macrophages was confirmed by uptake of inert, bacteria-sized beads. Contribution of macrophages to infection was assessed by colonization studies of Salmonella pathovars with different host adaptations and disease phenotypes (Typhimurium ST19 strain SL1344 and ST313 strain D23580; Typhi Ty2). In addition, Salmonella were cultured aerobically or microaerobically, recapitulating environments encountered prior to and during intestinal infection, respectively. All Salmonella strains exhibited decreased colonization in co-culture (HT-29-U937) relative to epithelial (HT-29) models, indicating antimicrobial function of macrophages. Interestingly, D23580 exhibited enhanced replication/survival in both models following invasion. Pathovar-specific differences in colonization and intracellular co-localization patterns were observed. These findings emphasize the power of incorporating a series of related three-dimensional models within a study to identify microenvironmental factors important for regulating infection.

This study is an attempt to use group information collected on climate change from farmers in eastern Uttar Pradesh, India to address a key question related to climate change policy: How to encourage farmers to adapt to climate change? First, we investigate farmers’ perception of and adaptation to climate change using content analysis and group information. The findings are then compared with climatic and agriculture information collected through secondary sources. Results suggest that though farmers are aware of long-term changes in climatic factors (temperature and rainfall, for example), they are unable to identify these changes as climate change. Farmers are also aware of risks generated by climate variability and extreme climatic events. However, farmers are not taking concrete steps in dealing with perceived climatic changes, although we find out that farmers are changing their agricultural and farming practices. These included changing sowing and harvesting timing, cultivation of crops of short duration varieties, inter-cropping, changing cropping pattern, investment in irrigation, and agroforestry. Note that these changes may be considered as passive response or adaptation strategies to climate change. Perhaps farmers are implicitly taking initiatives to adapt climate change. Finally, the paper suggests some policy interventions to scale up adaptation to climate change in Indian agriculture.

Buyers often make supplier selection decisions under conditions of uncertainty. Although the analytical aspects of supplier selection are well developed, the psychological aspects are less so. This article uses supply chain management and behavioral decision theories to propose that attributes of the purchasing situation (category difficulty, category importance, and contingent pay) affect cognition that, in turn, affects a supply manager's choice. We conducted a supplier selection behavioral experiment with practicing managers to test the model's hypotheses. When the context involves an important or difficult sourcing category, higher risk perceptions exist that increase preference for a supplier with more certain outcomes, even when that choice has a lower expected payoff. However, the presence of contingent pay decreases risk perceptions through higher perceived supplier control. We also find that a manager's risk propensity increases preferences for a supplier with less certain outcomes regardless of perceived risk. Our model and results provide a theoretical framework for further study into the cognitive aspects of supplier selection behavior and provide insight into biases that influence practicing supply chain managers.

This study examined the impact of three alternative types of goals (specific learning, general “do your best” learning, and specific performance) on team performance. Eighty-four-person teams engaged in an interdependent command and control simulation in which the team goal and task complexity were manipulated. Contrary to research at the individual level, teams with specific learning goals performed worse than did teams with general “do your best” learning goals or specific performance goals. The negative effects of specific learning goals relative to general “do your best” learning goals and specific performance goals were amplified under conditions of increased task complexity and were explained by the amount of coordination in the teams.

Purpose: The purpose of this paper is to review what we know - and don't know - about Generation Y's use of social media and to assess the implications for individuals, firms and society.

Design/Methodology/Approach: The paper distinguishes Generation Y from other cohorts in terms of systematic differences in values, preferences and behavior that are stable over time (as opposed to maturational or other differences). It describes their social media use and highlights evidence of intra-generational variance arising from environmental factors (including economic, cultural, technological and political/legal factors) and individual factors. Individual factors include stable factors (including socio-economic status, age and lifecycle stage) and dynamic, endogenous factors (including goals, emotions, and social norms). The paper discusses how Generation Y's use of social media influences individuals, firms and society. It develops managerial implications and a research agenda.

Findings: Prior research on the social media use of Generation Y raises more questions than it answers. It: focuses primarily on the USA and/or (at most) one other country, ignoring other regions with large and fast-growing Generation Y populations where social-media use and its determinants may differ significantly; tends to study students whose behaviors may change over their life cycle stages; relies on self-reports by different age groups to infer Generation Y's social media use; and does not examine the drivers and outcomes of social-media use. This paper's conceptual framework yields a detailed set of research questions.

Originality/Value: This paper provides a conceptual framework for considering the antecedents and consequences of Generation Y's social media usage. It identifies unanswered questions about Generation Y's use of social media, as well as practical insights for managers.

Information systems research is replete with examples of the importance of business processes defining IT adoption. Business processes are influenced by both organizational and operational concerns. We evaluate the comparative importance of operational and organizational influences for complementary IT systems. In the context of acute-care hospitals the analysis shows that an organizational approach to automating a process is related to different financial outcomes than an operational approach. Six complementary systems supporting a three-stage medication management process are studied: prescribing, dispensing, and administration. The analysis uses firm-level, panel data extracted from the HIMSS Analytics database spanning ten years of IT adoption for 140 hospitals. We have augmented the HIMSS dataset with matching demographic and financial details from the American Hospital Association and the Centers for Medicare and Medicaid Services. Using event sequence analysis we explore whether organizations are more likely to adopt organization boundary spanning systems and if the sequence of adoption follows the temporal ordering of the business process steps. The research also investigates if there is a relationship between the paths to IT adoption and financial performance. Comparison of the two measures suggests that the organizational model of adoption is observed more often in the data. Following the organizational model of adoption is associated with approximately $155 dollar increase in net income per patient day; whereas the operational model of adoption is associated with approximately $225 dollars decrease in net income per patient day. However, this effect diminishes with the adoption of each additional system thus demonstrating that the adoption path effects may only be relevant in the short-term.

With the advent of high-dimensional stored big data and streaming data, suddenly machine learning on a very large scale has become a critical need. Such machine learning should be extremely fast, should scale up easily with volume and dimension, should be able to learn from streaming data, should automatically perform dimension reduction for high-dimensional data, and should be deployable on hardware. Neural networks are well positioned to address these challenges of large scale machine learning. In this paper, we present a method that can effectively handle large scale, high-dimensional data. It is an online method that can be used for both streaming and large volumes of stored big data. It primarily uses Kohonen nets, although only a few selected neurons (nodes) from multiple Kohonen nets are actually retained in the end; we discard all Kohonen nets after training. We use Kohonen nets both for dimensionality reduction through feature selection and for building an ensemble of classifiers using single Kohonen neurons. The method is meant to exploit massive parallelism and should be easily deployable on hardware that implements Kohonen nets. Some initial computational results are presented.

Humans are able to intuitively exploit the shape of an object and environmental constraints to achieve stable grasps and perform dexterous manipulations. In doing that, a vast range of kinematic strategies can be observed. However, in this work we formulate the hypothesis that such ability can be described in terms of a synergistic behavior in the generation of hand postures, i.e., using a reduced set of commonly used kinematic patterns. This is in analogy with previous studies showing the presence of such behavior in different tasks, such as grasping. We investigated this hypothesis in experiments performed by six subjects, who were asked to grasp objects from a flat surface. We quantitatively characterized hand posture behavior from a kinematic perspective, i.e., the hand joint angles, in both pre-shaping and during the interaction with the environment. To determine the role of tactile feedback, we repeated the same experiments but with subjects wearing a rigid shell on the fingertips to reduce cutaneous afferent inputs. Results show the persistence of at least two postural synergies in all the considered experimental conditions and phases. Tactile impairment does not alter significantly the first two synergies, and contact with the environment generates a change only for higher order Principal Components. A good match also arises between the first synergy found in our analysis and the first synergy of grasping as quantified by previous work. The present study is motivated by the interest of learning from the human example, extracting lessons that can be applied in robot design and control. Thus, we conclude with a discussion on implications for robotics of our findings.

The concept of postural synergies of the human hand has been shown to potentially reduce complexity in the neuromuscular control of grasping. By merging this concept with soft robotics approaches, a multi degrees of freedom soft-synergy prosthetic hand [SoftHand-Pro (SHP)] was created. The mechanical innovation of the SHP enables adaptive and robust functional grasps with simple and intuitive myoelectric control from only two surface electromyogram (sEMG) channels. However, the current myoelectric controller has very limited capability for fine control of grasp forces. We addressed this challenge by designing a hybrid-gain myoelectric controller that switches control gains based on the sensorimotor state of the SHP. This controller was tested against a conventional single-gain (SG) controller, as well as against native hand in able-bodied subjects. We used the following tasks to evaluate the performance of grasp force control: (1) pick and place objects with different size, weight, and fragility levels using power or precision grasp and (2) squeezing objects with different stiffness. Sensory feedback of the grasp forces was provided to the user through a non-invasive, mechanotactile haptic feedback device mounted on the upper arm. We demonstrated that the novel hybrid controller enabled superior task completion speed and fine force control over SG controller in object pick-and-place tasks. We also found that the performance of the hybrid controller qualitatively agrees with the performance of native human hands.