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1. Contributions of spatial and temporal control of step length symmetry in the transfer of locomotor adaptation from a motorized to a non-motorized split-belt treadmill

   https://doi.org/10.1098/rsos.202084  

   Gregory, Daniel L.; Sup, Frank C.; Choi, Julia T. (February 2021, Royal Society Open Science)

   null (Ed.)

   Walking requires control of where and when to step for stable interlimb coordination. Motorized split-belt treadmills which constrain each leg to move at different speeds lead to adaptive changes to limb coordination that result in after-effects (e.g. gait asymmetry) on return to normal treadmill walking. These after-effects indicate an underlying neural adaptation. Here, we assessed the transfer of motorized split-belt treadmill adaptations with a custom non-motorized split-belt treadmill where each belt can be self-propelled at different speeds. Transfer was indicated by the presence of after-effects in step length, foot placement and step timing differences. Ten healthy participants adapted on a motorized split-belt treadmill (2 : 1 speed ratio) and were then assessed for after-effects during subsequent non-motorized treadmill and motorized tied-belt treadmill walking. We found that after-effects in step length difference during transfer to non-motorized split-belt walking were primarily associated with step time differences. Conversely, residual after-effects during motorized tied-belt walking following transfer were associated with foot placement differences. Our data demonstrate decoupling of adapted spatial and temporal locomotor control during transfer to a novel context, suggesting that foot placement and step timing control can be independently modulated during walking. 

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2. A network-based discrete choice model for decision-based design

   https://doi.org/10.1017/dsj.2023.4  

   Sha, Zhenghui; Cui, Yaxin; Xiao, Yinshuang; Stathopoulos, Amanda; Contractor, Noshir; Fu, Yan; Chen, Wei (January 2023, Design Science)

   Abstract Customer preference modelling has been widely used to aid engineering design decisions on the selection and configuration of design attributes. Recently, network analysis approaches, such as the exponential random graph model (ERGM), have been increasingly used in this field. While the ERGM-based approach has the new capability of modelling the effects of interactions and interdependencies (e.g., social relationships among customers) on customers’ decisions via network structures (e.g., using triangles to model peer influence), existing research can only model customers’ consideration decisions, and it cannot predict individual customer’s choices, as what the traditional utility-based discrete choice models (DCMs) do. However, the ability to make choice predictions is essential to predicting market demand, which forms the basis of decision-based design (DBD). This paper fills this gap by developing a novel ERGM-based approach for choice prediction. This is the first time that a network-based model can explicitly compute the probability of an alternative being chosen from a choice set. Using a large-scale customer-revealed choice database, this research studies the customer preferences estimated from the ERGM-based choice models with and without network structures and evaluates their predictive performance of market demand, benchmarking the multinomial logit (MNL) model, a traditional DCM. The results show that the proposed ERGM-based choice modelling achieves higher accuracy in predicting both individual choice behaviours and market share ranking than the MNL model, which is mathematically equivalent to ERGM when no network structures are included. The insights obtained from this study further extend the DBD framework by allowing explicit modelling of interactions among entities (i.e., customers and products) using network representations. 

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3. Expanding and Refining a Decision-Making Competency Inventory for Undergraduate Engineering Students

   https://doi.org/10.1109/FIE43999.2019.9028391  

   Ehlert, Katherine M.; Rucks, Maya; Martin, Baker A.; Desselles, Mitzi L.; Grigg, Sarah J.; Orr, Marisa K. (October 2019, 2019 IEEE Frontiers in Education Conference (FIE))

   null (Ed.)

   This Full Research Paper discusses ongoing work to develop a survey instrument to reliably assess undergraduate engineering student self-regulated decision-making. This work focuses on a second round of item expansion and refinement to the Decision-Making Competency Inventory (DMCI) to develop items related to learning from past decisions. The refined instrument was distributed to first-year engineering students enrolled in a large, public, land-grant institution located in the southeastern United States in the Fall of 2018. Of the approximately 1,200 students in first-year engineering courses, 883 valid surveys were randomly split into two separate samples for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). EFA results indicated a viable four-factor solution, which was explored with the CFA. The CFA results also indicated a four-factor model was appropriate. Improving this instrument will help researchers document and understand students’ decision-making skills and how they relate to observed decisions like initial choice of major or change of major. A decision-making instrument will also be valuable in evaluating the effectiveness of interventions to help students build their decision-making competency and make adaptive choices. 

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4. Towards demand-oriented flexible rerouting of public transit under uncertainty

   https://doi.org/10.1145/3313237.3313302  

   Nannapaneni, Saideep; Dubey, Abhishek (January 2019, Proceedings of the Fourth Workshop on International Science of Smart City Operations and Platforms Engineering)

   This paper proposes a flexible rerouting strategy for the public transit to accommodate the spatio-temporal variation in the travel demand. Transit routes are typically static in nature, i.e., the buses serve well-defined routes; this results in people living in away from the bus routes choose alternate transit modes such as private automotive vehicles resulting in ever-increasing traffic congestion. In the flex-transit mode, we reroute the buses to accommodate high travel demand areas away from the static routes considering its spatio-temporal variation. We perform clustering to identify several flex stops; these are stops not on the static routes, but with high travel demand around them. We divide the bus stops on the static routes into critical and non-critical bus stops; critical bus stops refer to transfer points, where people change bus routes to reach their destinations. In the existing static scheduling process, some slack time is provided at the end of each trip to account for any travel delays. Thus, the additional travel time incurred due to taking flexible routes is constrained to be less than the available slack time. We use the percent increase in travel demand to analyze the effectiveness of the rerouting process. The proposed methodology is demonstrated using real-world travel data for Route 7 operated by the Nashville Metropolitan Transit Authority (MTA). 

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5. Split-Belt walking induces changes in active, but not passive, perception of step length

   https://doi.org/10.1038/s41598-019-52860-9  

   Sombric, Carly; Gonzalez-Rubio, Marcela; Torres-Oviedo, Gelsy (December 2019, Scientific Reports)

   null (Ed.)

   Abstract Successful motor control requires accurate estimation of our body in space for planning, executing, and evaluating the outcome of our actions. It has been shown that the estimation of limb position is susceptible to motor adaptation. However, a similar effect has not been found in locomotion, possibly due to how it was tested. We hypothesized that split-belt walking with the legs moving at different speeds changes the estimation of the legs’ position when taking a step. Thus, we assessed young subjects’ perception of step length (i.e., inter-feet distance at foot landing) when they moved their legs (active perception) or when the legs were moved by the experimenter (passive perception). We found that the active perception of step length was substantially altered following split-belt walking, whereas passive perception exhibited minor changes. This suggests that split-belt walking induced the adaptation of efferent signals, without altering sensory signals. We also found that active perceptual shifts were sensitive to how they were tested: they were most salient in the trailing leg and at short step lengths. Our results suggest that split-belt walking could modulate the deficient perception of step length post-stroke, which may contribute to gait asymmetries impairing patients’ mobility. 

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