Comparing Fixed-amount and Progressive-amount DRO Schedules for Tic Suppression in Youth with Chronic Tic Disorders

Chronic tic disorders (CTDs) involve motor and/or vocal tics that often cause substantial distress and impairment. Differential reinforcement of other behavior (DRO) schedules of reinforcement produce robust, but incomplete, reductions in tic frequency in youth with CTDs; however, a more robust reduction may be needed to affect durable clinical change. Standard, fixed‐amount DRO schedules have not commonly yielded such reductions, so we evaluated a novel, progressive‐amount DRO schedule, based on its ability to facilitate sustained abstinence from functionally similar behaviors. Five youth with CTDs were exposed to periods of baseline, fixed‐amount DRO (DRO‐F), and progressive‐amount DRO (DRO‐P). Both DRO schedules produced decreases in tic rate and increases in intertic interval duration, but no systematic differences were seen between the two schedules on any dimension of tic occurrence. The DRO‐F schedule was generally preferred to the DRO‐P schedule. Possible procedural improvements and other future directions are discussed

The Climate Crisis: How Communication and Norms Interact with Attitudes and Actions

The present study investigated the effect of communication strategies and social norms on peoples’ self-reported environmental attitudes and actions. Communication strategies that cause high-fear levels in viewers can often cause distress, thereby increasing the likelihood that viewers will disregard a message in favor of protecting themselves (Clayton, 2020; Hornsey et al., 2015). Communication strategies that cause low-fear can serve as healthy motivators for action (Nestler & Egloff, 2012). Social norms are powerful, and people are likely to follow the same behavior pattern as others. In the current study, participants (N=71) watched a Public Service Announcement (PSA) video and either had social norms made salient to them or not to examine their self-reported environmental attitudes and actions. Participants then completed two scales from Milfont and Duckitt (2010) designed to measure pro-environmental attitudes and action. There was no significant effect of Fear Levels, Salience, nor an interaction. The political affiliations of participants were analyzed, and Democrat participants (n = 43) scored significantly higher than Republican participants (n = 10) on the pro-environmental attitudes scale. However, no significant difference was observed between Republican and Democrat participants on the pro-environmental actions scale. These results are discussed in light of cognitive dissonance theory and the concept of Basking in the Glory of Others (Bernache-Assollant et al., 2007; Festinger, 1957; Gollwitzer et al., 2009)

Employee risk due to ergonomic exposure during adhesive application process

Includes bibliographical references

Designing gamified rewards to encourage repeated app selection: Effect of reward placement

Designers commonly use gamification to improve the frequency of engagement with apps, but often fail to consider the impact of placement on reward value. As rewards tend to depreciate if delayed (termed temporal discounting), placing a reward further into the future can significantly affect its ability to motivate behaviour. We examine the most effective placement of gamified rewards so as to reduce discounting and to increase the frequency an application is used. In two online studies, users were asked to choose between fictional budget tracking applications that varied in the placement of either monetary (N=70) or gamified (N=70) rewards. In both experiments we found that people more frequently used the application that provided rewards before, rather than after, the task. As predicted by temporal discounting, our work suggests that placing rewards early in the interaction sequence leads to an improvement in the perceived value of that reward, motivating further selection. We discuss the findings in the context of designing effective reward structures to encourage more frequent app engagement

A source-destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks

Mobile wireless resources demand is rapidly growing due to the proliferation of bandwidth-hungry mobile devices and applications. This has resulted in congestion in mobile wireless networks (MWN) especially during the peak hours when user traffic can be as high as tenfold the average traffic. Mobile network operators (MNOs) have been trying to solve this problem in various ways. First, MNOs have tried to expand the network capacity but have still been unable to meet the peak hour demand. Focus has then shifted to economic and behavioral mechanisms. The widely used of these economic mechanisms is dynamic pricing which varies the MWN resources' price according to the congestion level in the MWN. This encourages users to shift their non-critical traffic from the busy hour, when the MWN is congested, to off-peak hours when the network is under-utilized. As a result, congestion of the MWN during the peak hours is reduced. At the same time, the MWN utilization during the off-peak hours is also increased. The current dynamic pricing schemes, however, only consider the congestion level in the call-originating cell and neglect the call-destination cell when computing the dynamic price. Due to this feature, we refer the current dynamic pricing schemes as source–based dynamic pricing (SDP) schemes in this work. The main problem with these schemes is that, when the majority of the users in a congested cell are callees, dynamic pricing is ineffective because callers and not callees pay for network services, and resources used by callers and callees are the same for symmetric services. For example, application of dynamic pricing does not deter a callee located in a congested cell from receiving a call, which originates from a caller located in an uncongested cell. Also, when the distribution of prospective callees is higher than that of callers in an underutilized cell, SDP schemes are ineffective as callees do not pay for a call and therefore low discounts do not entice them to increase utilization. In this distribution, dynamic pricing entices prospective callers to make calls but since their distribution is low, the MWN resource utilization does not increase by any significant margin. To address these problems, we have developed a source-destination based dynamic pricing (SDBDP) scheme, which considers congestion levels in both the call-originating and calldestination cells to compute the dynamic price to be paid by a caller. This SDBDP scheme is integrated with a load-based joint call admission control (JCAC) algorithm for admitting incoming service requests in to the least utilized radio access technology (RAT). The load-based JCAC algorithm achieves uniform traffic distribution in the heterogeneous wireless network (HWN). To test the SDBDP scheme, we have developed an analytical model based on M/M/m/m queuing model. New or handoff service requests, arriving when all the RATs in the HWN are fully utilized, lead to call blocking for new calls and call dropping for handoff calls. The call blocking probability, call dropping probability and percentage MWN utilization are used as the performance metrics in evaluating the SDBDP scheme. An exponential demand model is used to approximate the users' response to the presented dynamic price. The exponential demand model captures both the price elasticity of demand and the demand shift constant for different users. The matrix laboratory (MATLAB) tool has been used to carry out the numerical simulations. An evaluation scenario consisting of four groups of co-located cells each with three RATs is used. Both SDP and the developed SDBDP schemes have been subjected under the evaluation scenario. Simulation results show that the developed SDBDP scheme reduces both the new call blocking and handoff call dropping probabilities during the peak hours, for all callercallee distributions. On the other hand, the current SDP scheme only reduces new call blocking and handoff call dropping probabilities only under some caller –callee distributions (When the callers were the majority in the HWN). Also, the SDBDP scheme increases the percentage MWN utilization during the off-peak for all the caller-callee distributions in the HWN. On the other hand, the SDP scheme is found to increase the percentage MWN utilization only when the distribution of callers is higher than that of callees in the HWN. From analyzing the simulations results, we conclude that the SDBDP scheme achieves better congestion control and MWN resource utilization than the existing SDP schemes, under arbitrary caller-callee distribution

Enriching remote labs with computer vision and drones

165 p.With the technological advance, new learning technologies are being developed in order to contribute to better learning experience. In particular, remote labs constitute an interesting and a practical way that can motivate nowadays students to learn. The studen can at anytime, and from anywhere, access the remote lab and do his lab-work. Despite many advantages, remote tecnologies in education create a distance between the student and the teacher. Without the presence of a teacher, students can have difficulties, if no appropriate interventions can be taken to help them. In this thesis, we aim to enrich an existing remote electronic lab made for engineering students called "LaboREM" (for remote Laboratory) in two ways: first we enable the student to send high level commands to a mini-drone available in the remote lab facility. The objective is to examine the front panels of electronic measurement instruments, by the camera embedded on the drone. Furthermore, we allow remote student-teacher communication using the drone, in case there is a teacher present in the remote lab facility. Finally, the drone has to go back home when the mission is over to land on a platform for automatic recharge of the batteries. Second, we propose an automatic system that estimates the affective state of the student (frustrated/confused/flow) in order to take appropriate interventions to ensure good learning outcomes. For example, if the studen is having major difficulties we can try to give him hints or to reduce the difficulty level of the lab experiment. We propose to do this by using visual cues (head pose estimation and facil expression analysis). Many evidences on the state of the student can be acquired, however these evidences are incomplete, sometims inaccurate, and do not cover all the aspects of the state of the student alone. This is why we propose to fuse evidences using the theory of Dempster-Shafer that allows the fusion of incomplete evidence