Do robotic and non-robotic arm movement training drive motor recovery after stroke by a common neural mechanism? Experimental evidence and a computational model.

Different dose-matched, upper extremity rehabilitation training techniques, including robotic and non-robotic techniques, can result in similar improvement in movement ability after stroke, suggesting they may elicit a common drive for recovery. Here we report experimental results that support the hypothesis of a common drive, and develop a computational model of a putative neural mechanism for the common drive. We compared weekly motor control recovery during robotic and unassisted movement training techniques after chronic stroke (n = 27), as assessed with quantitative measures of strength, speed, and coordination. The results showed that recovery in both groups followed an exponential time course with a time constant of about 4-5 weeks. Despite the greater range and speed of movement practiced by the robot group, motor recovery was very similar between the groups. The premise of the computational model is that improvements in motor control are caused by improvements in the ability to activate spared portions of the damaged corticospinal system, as learned by a biologically plausible search algorithm. Robot-assisted and unassisted training would in theory equally drive this search process

Descriptive and Substantive Representation in Congress: Evidence from 80,000 Congressional Inquiries

A vast literature debates the efficacy of descriptive representation in legislatures. Though studies argue it influences how communities are represented through constituency service, they are limited since legislators’ service activities are unobserved. Using Freedom of Information Act (FOIA) requests, we collected 88,000 records of communication between members of the U.S. Congress and federal agencies during the 108th–113th Congresses. These legislative interventions allow us to examine members’ “follow‐through” with policy implementation. We find that women, racial/ethnic minorities, and veterans are more likely to work on behalf of constituents with whom they share identities. Including veterans offers leverage in understanding the role of political cleavages and shared experiences. Our findings suggest that shared experiences operate as a critical mechanism for representation, that a lack of political consensus is not necessary for substantive representation, and that the causal relationships identified by experimental work have observable implications in the daily work of Congress.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150606/1/ajps12443-sup-0001-SuppMat.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150606/2/ajps12443.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150606/3/ajps12443_am.pd

Multi Agent System for Machine Learning Under Uncertainty in Cyber Physical Manufacturing System

Recent advancement in predictive machine learning has led to its application in various use cases in manufacturing. Most research focused on maximising predictive accuracy without addressing the uncertainty associated with it. While accuracy is important, focusing primarily on it poses an overfitting danger, exposing manufacturers to risk, ultimately hindering the adoption of these techniques. In this paper, we determine the sources of uncertainty in machine learning and establish the success criteria of a machine learning system to function well under uncertainty in a cyber-physical manufacturing system (CPMS) scenario. Then, we propose a multi-agent system architecture which leverages probabilistic machine learning as a means of achieving such criteria. We propose possible scenarios for which our architecture is useful and discuss future work. Experimentally, we implement Bayesian Neural Networks for multi-tasks classification on a public dataset for the real-time condition monitoring of a hydraulic system and demonstrate the usefulness of the system by evaluating the probability of a prediction being accurate given its uncertainty. We deploy these models using our proposed agent-based framework and integrate web visualisation to demonstrate its real-time feasibility

Competing for the Platform: How Organized Interests affect Party Positioning in the United States

What explains which groups are included in a party coalition in any given election cycle? Recent advances in political party theory suggest that policy demanders comprise parties, and that the composition of a party coalition varies from election to election. We theorize three conditions under which parties articulate an interest group?s preferred positions in its quadrennial platform: when groups are ideologically proximate to the party median, when groups display party loyalty, and when groups are flush with resources. Using computer-assisted content analysis on a unique and rich data source, we examine three cycles of testimony that 80 organized groups provided to the Democratic Party. The analysis compares group requests with the content of Democratic and Republican National Committee platforms in 1996, 2000, and 2004. Results show that parties reward loyal groups and those that are ideologically proximate to the party, but offer no confirmation of a resource effect

Feminist allies and strategic partners: Exploring the relationship between the women’s movement and political parties

Western political parties have been in decline in recent decades and they continue to be viewed as male institutions. Despite this, electoral politics is important to the women’s movement as a means by which to advance feminist interests. This article builds upon feminist critiques of political parties by analyzing original qualitative data undertaken with feminists in the United States and United Kingdom in order to explore how activists view political parties. The research finds that although many hold negative views, in line with broader debates concerning disengagement, they also recognize the importance of electoral politics and the need to work with individual politicians. Party and feminist ideology shapes those views, whereby politicians on the left are viewed as feminist allies and those on the right are framed as strategic partners

The politics of heroes through the prism of popular heroism

This is the author accepted manuscript. The final version is available from Palgrave Macmillan via the DOI in this record.In modern day Britain, the discourse of national heroification is routinely utilised by politicians, educationalists and cultural industry professionals, whilst also being a popular concept to describe deserving ‘do-gooders’ who contribute to British society in a myriad of ways. We argue that although this heroification discourse is enacted as a discursive device of encouraging politically and morally desirable behaviour, it is dissociated from the largely under-explored facets of contemporary popular heroism. To compensate for this gap, this paper explores public preferences for heroes using survey data representative of British adults. This analysis demonstrates a conceptual stretching in the understanding of heroism, and allows identifying age- and gender-linked dynamics which effect public choices of heroes. In particular, we demonstrate that age above all determines the preference for having a hero, but does not explain preferences for specific hero-types. The focus on gender illustrates that the landscape of popular heroism reproduces a male-dominated bias which exists in the wider political and cultural heroification discourse. Simultaneously, our study shows that if national heroification discourse in Britain remains male-centric, the landscape of popular heroism is characterised by a gendered trend towards privatisation of heroes being particularly prominent amongst women. In the conclusion, this paper argues for a conceptual revision and re-gendering of the national heroification discourse as a step towards both empirically grounded, and age- and gender-sensitive politics of heroes and heroines.AHR

Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training

ABSTRACT: BACKGROUND: Manual body weight supported treadmill training and robot-aided treadmill training are frequently used techniques for the gait rehabilitation of individuals after stroke and spinal cord injury. Current evidence suggests that robot-aided gait training may be improved by making robotic behavior more patient-cooperative. In this study, we have investigated the immediate effects of patient-cooperative versus non-cooperative robot-aided gait training on individuals with incomplete spinal cord injury (iSCI). METHODS: Eleven patients with iSCI participated in a single training session with the gait rehabilitation robot Lokomat. The patients were exposed to four different training modes in random order: During both non-cooperative position control and compliant impedance control, fixed timing of movements was provided. During two variants of the patient-cooperative path control approach, free timing of movements was enabled and the robot provided only spatial guidance. The two variants of the path control approach differed in the amount of additional support, which was either individually adjusted or exaggerated. Joint angles and torques of the robot as well as muscle activity and heart rate of the patients were recorded. Kinematic variability, interaction torques, heart rate and muscle activity were compared between the different conditions. RESULTS: Patients showed more spatial and temporal kinematic variability, reduced interaction torques, a higher increase of heart rate and more muscle activity in the patient-cooperative path control mode with individually adjusted support than in the non-cooperative position control mode. In the compliant impedance control mode, spatial kinematic variability was increased and interaction torques were reduced, but temporal kinematic variability, heart rate and muscle activity were not significantly higher than in the position control mode. CONCLUSIONS: Patient-cooperative robot-aided gait training with free timing of movements made individuals with iSCI participate more actively and with larger kinematic variability than non-cooperative, position-controlled robot-aided gait training

The problem of constitutional legitimation: what the debate on electoral quotas tells us about the legitimacy of decision-making rules in constitutional choice

Proponents of electoral quotas have a ‘dependent interpretation’ of democracy, i.e. they have formed an opinion on which decision-making rules are fair on the basis of their prior approval of the outcomes these rules are likely to generate. The article argues that this position causes an irresolvable problem for constitutional processes that seek to legitimately enact institutional change. While constitutional revision governed by formal equality allows the introduction of electoral quotas, this avenue is normatively untenable for proponents of affirmative action if they are consistent with their claim that formal equality reproduces biases and power asymmetries at all levels of decision-making. Their critique raises a fundamental challenge to the constitutional revision rule itself as equally unfair. Without consensus on the decision-making process by which new post-constitutional rules can be legitimately enacted, procedural fairness becomes an issue impossible to resolve at the stage of constitutional choice. This problem of legitimation affects all instances of constitutional choice in which there are opposing views not only about the desired outcome of the process but also about the decision-making rules that govern constitutional choice

Robotic Assistance for Training Finger Movement Using a Hebbian Model: A Randomized Controlled Trial.

BackgroundRobots that physically assist movement are increasingly used in rehabilitation therapy after stroke, yet some studies suggest robotic assistance discourages effort and reduces motor learning.ObjectiveTo determine the therapeutic effects of high and low levels of robotic assistance during finger training.MethodsWe designed a protocol that varied the amount of robotic assistance while controlling the number, amplitude, and exerted effort of training movements. Participants (n = 30) with a chronic stroke and moderate hemiparesis (average Box and Blocks Test 32 ± 18 and upper extremity Fugl-Meyer score 46 ± 12) actively moved their index and middle fingers to targets to play a musical game similar to GuitarHero 3 h/wk for 3 weeks. The participants were randomized to receive high assistance (causing 82% success at hitting targets) or low assistance (55% success). Participants performed ~8000 movements during 9 training sessions.ResultsBoth groups improved significantly at the 1-month follow-up on functional and impairment-based motor outcomes, on depression scores, and on self-efficacy of hand function, with no difference between groups in the primary endpoint (change in Box and Blocks). High assistance boosted motivation, as well as secondary motor outcomes (Fugl-Meyer and Lateral Pinch Strength)-particularly for individuals with more severe finger motor deficits. Individuals with impaired finger proprioception at baseline benefited less from the training.ConclusionsRobot-assisted training can promote key psychological outcomes known to modulate motor learning and retention. Furthermore, the therapeutic effectiveness of robotic assistance appears to derive at least in part from proprioceptive stimulation, consistent with a Hebbian plasticity model