Task Setup Research Articles

Supporting Peer Feedback at Scale

Schneider et al. (2017) conducted a systematic review of 38 meta-analyses investigating 105 variables linked to student performance. They reported peer assessment is the most influential factor in explaining students’ achievement. The benefits are even more significant when combined with self-assessment as students' meta-cognitive capacity is exercised as they calibrate their level of understanding and confidence to that of their peers (Power & Tanner, 2023). Assessing a peer digitally has been shown to be more effective than in-person settings (Li et al., 2020). Winstone & Boud (2022) recommend improving students’ learning by focusing on providing and receiving high-quality feedback rather than on grades. Despite the potential of technology to help students assess each other, there is sparse research in commerce studies, let alone on large-scale subjects, where technology use is essential to leverage students’ learning and encourage interaction, which otherwise would be limited. Such a study can shed light on students' learning and engagement benefits. Technology can also aid in creating a structured learning environment, with students being required to complete multiple tasks throughout the semester and engage with the platform repetitively, reinforcing improved curriculum retention (Schwerter et al., 2022). Our project involved implementing five tasks (a practice task and four assessed tasks) in a large-cohort first-year finance subject at a leading Australian university. The tasks contributed 15% to each student’s final mark and utilised the Feedback Fruits platform (integrated with Canvas LMS). For each task, students scanned their handwritten answers to two questions, uploaded them into the platform as a PDF file, completed self-assessment and reviewed a randomly assigned anonymous peer using a rubric designed to mimic the rubric used to mark final exam questions. We configured the system so that students had at least one week to upload their answers and another week to complete the self-assessment and peer review. Statistical analysis of the Feedback Fruits analytics files, which include completion rates and performance, involved regression analysis and propensity score matching and indicates a significant positive relationship between platform engagement (measured by time spent on the platform, provided comments length and task performance) and final exam performance, even after controlling for a student’s finance aptitude. The study also involved an end-of-semester survey and focus groups to capture students’ perceptions. Students indicated the positive learning benefits they gained from reviewing their peers, being reviewed, and reflecting on their performance. Furthermore, we found a high correlation between the number of comments and the average number of words per comment students left themselves and those left for their peers. The innovation of our research is in the scale, continuous use of the platform throughout the semester with multiple access points per task and better exam preparedness by simulating exam conditions utilising rubrics and handwriting requirements. This poster describes the project’s implementation process map, including task setup, timelines, and the support provided, which is the technical part of the bigger project. We review fundamental mechanisms to improve participation and the quality of the reviews. In addition, the poster presents the challenges faced and offers practical steps to overcome them.

AI translated task setup for non-native English speaking students

University classrooms are increasingly populated by students with diverse nationalities and native languages (L1). The growing number of students in English-led classrooms who speak English as a second or lower language (L2) may face added difficulties in understanding the specific task objectives or directions, as explained by native-English-speaking instructors. Emerging generative AI (genAI) technology offers new opportunities for native-English instructors to provide clear task setup in their students' L1. This single-class activity utilizes genAI software to translate English-language task setup into student L1 and enable L2 students to perform a complex and unfamiliar English comprehension task. The post-activity appraisal compares one cohort of students who performed the task with the genAI translated instructions to a cohort who performed the same task with English-language instructions. Courses English as Second Language (ESL), English Conversation, English Comprehension, and any courses in which groups of L2 students are present. Objectives L2 students will be able to perform complex, unfamiliar ESL comprehension tasks with confidence and clarity of direction. Instructors will be able to transfer this strategy to other tasks and communicate objectives and directions to their L2 students more clearly in the students' L1. This strategy may be transferred to any course with L2 learners.

Zero- and few-shot prompting of generative large language models provides weak assessment of risk of bias in clinical trials.

Existing systems for automating the assessment of risk-of-bias (RoB) in medical studies are supervised approaches that require substantial training data to work well. However, recent revisions to RoB guidelines have resulted in a scarcity of available training data. In this study, we investigate the effectiveness of generative large language models (LLMs) for assessing RoB. Their application requires little or no training data and, if successful, could serve as a valuable tool to assist human experts during the construction of systematic reviews. Following Cochrane's latest guidelines (RoB2) designed for human reviewers, we prepare instructions that are fed as input to LLMs, which then infer the risk associated with a trial publication. We distinguish between two modelling tasks: directly predicting RoB2 from text; and employing decomposition, in which a RoB2 decision is made after the LLM responds to a series of signalling questions. We curate new testing data sets and evaluate the performance of four general- and medical-domain LLMs. The results fall short of expectations, with LLMs seldom surpassing trivial baselines. On the direct RoB2 prediction test set (n = 5993), LLMs perform akin to the baselines (F1: 0.1-0.2). In the decomposition task setup (n = 28,150), similar F1 scores are observed. Our additional comparative evaluation on RoB1 data also reveals results substantially below those of a supervised system. This testifies to the difficulty of solving this task based on (complex) instructions alone. Using LLMs as an assisting technology for assessing RoB2 thus currently seems beyond their reach.

Self-initiated self-repairs of connected speech and novel vocabulary learning during the first year of recovery from aphasia: four longitudinal case studies

ABSTRACT Background Self-initiated self-repair of problems in speech production has been suggested to be associated with aphasia treatment gains and recovery, but the topic has been little studied. Similarly, the ability to learn novel words has been associated with anomia treatment benefits, although longitudinal data on such learning is lacking. Aims The present study’s aim was to examine whether and how self-initiated self-repairs in connected speech and the ability to learn novel vocabulary reflected recovery from aphasia as measured with cognitive-linguistic tests. Additionally, our aim was to explore whether self-initiated repair and novel word learning changed in parallel during recovery. Methods & Procedures Four people with aphasia (PWA) (2 anomic, 1 Wernicke, and 1 global aphasia) were tested in the subacute (11 to 68 days post stroke) and chronic (12 months post stroke) phases of recovery with cognitive-linguistic tests, connected speech tasks, and a computerized learning task. In the learning task, PWA associated 6 pseudowords with 6 unfamiliar referents. The associations were learned from an ambiguous setup with feedback. At both time points, learning was measured as correct immediate recognition of the items and recognition maintenance one week post-training. The proportion of self-initiated self-repairs and the proportion of unrepaired problems in connected speech were used as measures of self-repair behavior. Outcomes & Results All participants initiated self-repairs both in the subacute and chronic phases, and their self-repairs were most often related to aphasic difficulties in speech production. Between the subacute and chronic phases, self-repairs changed both in quality and quantity. The proportion of self-repair elements decreased in 4/4 participants and the proportion of unrepaired problem segments decreased in 3/4 participants. Of the participants, 3/4 showed significant novel word learning and/or maintenance already in the subacute phase and 4 /4 in the chronic phase. Conclusion Reduction in self-initiated self-repairs of speech reflected recovery from aphasia. Novel word learning improved during aphasia recovery from the subacute to the chronic phase. Novel word learning was possible even in subacute, severe aphasia and even in an ambiguous task set-up with no explicitly provided word-referent connections. Novel word learning and self-initiated self-repairs did not change in a clearly parallel manner; however, these findings need to be tested with a larger sample.

Data-Driven Decision Support Tool Co-Development with a Primary Health Care Practice Based Learning Network

Background The Alliance for Healthier Communities is a learning health system that supports Community Health Centres (CHCs) across Ontario, Canada to provide team-based primary health care to people who otherwise experience barriers to care. This case study describes the ongoing process and lessons learned from the first Alliance for Healthier Communities’ Practice Based Learning Network (PBLN) data-driven decision support tool co-development project. Methods We employ an iterative approach to problem identification and methods development for the decision support tool, moving between discussion sessions and case studies with CHC electronic health record (EHR) data. We summarize our work to date in terms of six stages: population-level descriptive-exploratory study, PBLN team engagement, decision support tool problem selection, sandbox case study 1: individual-level risk predictions, sandbox case study 2: population-level planning predictions, project recap and next steps decision. Results The population-level study provided an initial point of engagement to consider how clients are (not) represented in EHR data and to inform problem selection and methodological decisions thereafter. We identified three initial meaningful types of decision support, with target application areas: risk prediction/screening, triaging specialized program referrals, and identifying care access needs. Based on feasibility and expected impact, we started with the goal to support earlier identification of mental health decline after diabetes diagnosis. As discussions deepened around clinical use cases associated with example prediction task set ups, the target problem evolved towards supporting the upstream task of organizational planning and advocacy for adequate mental health care service capacity to meet incoming needs. Conclusions This case study contributes towards a tool to support diabetes and mental health care, as well as lays groundwork for future CHC EHR-based decision support tool initiatives. We share lessons learned and reflections from our process that other primary health care organizations may use to inform their own co-development initiatives.

The Impact of Task Set-up in Algorithm Design: Regression versus Classification

The Impact of Task Set-up in Algorithm Design: Regression versus Classification

TDCS over PPC or DLPFC does not improve visual working memory capacity

Non-invasive brain stimulation has been highlighted as a possible intervention to induce cognitive benefits, including on visual working memory (VWM). However, findings are inconsistent, possibly due to methodological issues. A recent high-profile study by Wang et al.1 reported that anodal transcranial direct current stimulation (tDCS) over posterior parietal cortex (PPC), but not over dorsolateral prefrontal cortex (DLPFC), selectively improved VWM capacity but not precision, especially at a high VWM load. Thus, in the current pre-registered conceptual replication study, we accounted for the key potential methodological issues in the original study and tested an adequate number of participants required to demonstrate the previously reported effects (n = 48 compared to n = 20). Participants underwent counterbalanced PPC, DLPFC and sham stimulation before completing 360 trials of a continuous orientation-reproduction task with a slight variation of task stimuli and setup. We found no evidence for the selective effect of PPC stimulation. Instead, our results showed that tDCS effects were absent regardless of stimulation region and VWM load, which was largely supported by substantial to strong Bayesian evidence. Therefore, our results challenge previously reported benefits of single-session anodal PPC-tDCS on VWM.

The Effects of Drop Vertical Jump Task Variation on Landing Mechanics: Implications for Evaluating Limb Asymmetry

Limb asymmetry is an important consideration when evaluating rehabilitation progress or re-injury risk. The drop vertical jump (DVJ) task is commonly used to assess landing mechanics; however, the extent to which task setup influences limb asymmetry is unknown. Our purpose was to examine limb asymmetries across DVJ variations. We hypothesized that more demanding variations involving greater jump distance and target use would elicit greater landing asymmetries. Participants performed six DVJ variations while lower extremity joint kinematics and kinetics were collected. Joint angles and internal moments of the hip, knee and ankle were computed at initial contact and over the decent phase of the initial landing. The horizontal jump distance and the verbal instructions provided on how to jump off the box influenced limb asymmetries. The DVJ variation without a horizontal jump distance resulted in significant differences at the hip and knee; specifically, greater hip and knee flexion asymmetry (7.0° and 15.2° differences, respectively) were observed between limbs at initial contact. Instructions restricting take-off and landing strategies reduced asymmetry; this indicates that verbal instructions are critical to avoid altering natural landing mechanics. To best utilize DVJ as a tool, study protocols should be standardized to allow for more generalizable research and clinical findings.

Exploratory behavior is associated with the cognitive speed in male chestnut thrushes

Abstract Intra-individual variation in cognitive abilities has been widely reported in animals. Recent studies have found that individual cognitive performance varies with personality traits in a wide range of animal taxa, with a speed-accuracy trade-off between cognition and personality traits. Few studies investigated whether these relationships change depending on different contexts. Here we investigate whether the personality trait (as measured by exploratory behavior in a novel environment) is associated with cognition (novel skill learning and spatial memory) in wild male chestnut thrushes Turdus rubrocanus. Using an experimental novel skill-learning task set-up, we found that fast-exploring individuals explored the experimental device (a cardboard with 8 opaque cups) sooner than slow-exploring individuals. Exploratory behavior was not associated with individual spatial memory performances or an individual’s capacity to learn the novel skill. Learning speed was positively associated with the difficulty of learning phases, and fast-exploring individuals used less trials to meet the learning criterion. In addition, fast-exploring individuals took less time to complete the 24-h spatial memory test, but the accuracy of the test was not significantly different between individuals who were more or less exploratory. We suggest that variation in personality traits associates with individual learning speed in cognitive tasks and that this relationship is context-dependent.

Condition-based Design of Variable Impedance Controllers from User Demonstrations

This paper presents an approach to ensure conditions on Variable Impedance Controllers through the off-line tuning of the parameters involved in its description. In particular, we prove its application to term modulations defined by a Learning from Demonstration technique. This is performed through the assessment of conditions regarding safety and performance, which encompass heuristics and constraints in the form of Linear Matrix Inequalities. Latter ones allow to define a convex optimisation problem to analyse their fulfilment, and require a polytopic description of the VIC, in this case, obtained from its formulation as a discrete-time Linear Parameter Varying system. With respect to the current state-of-art, this approach only limits the term definition obtained by the Learning from Demonstration technique to be continuous and function of exogenous signals, i.e. external variables to the robot. Therefore, using a solution-search method, the most suitable set of parameters according to assessment criteria can be obtained. Using a 7-DoF KinovaGen3 manipulator, validation and comparison against solutions with relaxed conditions are performed. The method is applied to generate Variable Impedance Controllers for a pulley belt looping task, inspired by the Assembly Challenge for Industrial Robotics in World Robot Summit 2018, to reduce the exerted force with respect to a standard (constant) Impedance Controller. These controllers fulfil a set of safety constraints, namely stability, bounds on task variables and maximum response overshooting; and their performance is determined by the User Preference heuristic, which allows to intuitively define the desired compliant behaviour along the task. In the context of the task, this is used to generate new controllers for one-off modifications of the nominal belt looping task setup without new demonstrations.

Zero-Shot Relation Triple Extraction with Prompts for Low-Resource Languages

Although low-resource relation extraction is vital in knowledge construction and characterization, more research is needed on the generalization of unknown relation types. To fill the gap in the study of low-resource (Uyghur) relation extraction methods, we created a zero-shot with a quick relation extraction task setup. Each triplet extracted from an input phrase consists of the subject, relation type, and object. This paper suggests generating structured texts by urging language models to provide related instances. Our model consists of two modules: relation generator and relation and triplet extractor. We use the Uyghur relation prompt in the relation generator stage to generate new synthetic data. In the relation and triple extraction stage, we use the new data to extract the relation triplets in the sentence. We use multi-language model prompts and structured text techniques to offer a structured relation prompt template. This method is the first research that extends relation triplet extraction to a zero-shot setting for Uyghur datasets. Experimental results show that our method achieves a maximum weighted average F1 score of 47.39%.

No conclusive evidence for number-induced attentional shifts in a temporal order judgement task.

The Spatial Numerical Association of Response Codes (SNARC) effect refers to the observation that relatively small (e.g., 1) and large numbers (e.g., 9) elicit faster left- and right-sided manual responses, respectively. In a variation known as the attentional SNARC effect, merely looking at numbers caused a left- or right-ward shift in covert spatial attention, depending on the number's magnitude. In our study, we probed the notion that numbers induce shifts of spatial attention in accordance with their position on a mental number line (MNL). Critically, we removed any putative spatial response code that may contaminate the responses. We used a square and a tilted square as targets, thereby situating the decisive response dimension in the ventral, non-spatial processing stream. In two experiments where numbers were used as non-informative cues preceding a temporal order judgement (TOJ) task, we did not observe a deflection of the locus of spatial attention as a function of the numerical magnitude of the cue. In a third experiment, finding a significant modulation of TOJ performance as a function of the pointing direction of arrow cues allowed us to rule out the possibility that the absence of any significant modulation in Experiments 1 and 2 was due to a lack of sensitivity of our task set-up. We conclude from the current findings that the spatial codes that the perception and naming of numbers potentially elicit are not in and by themselves sufficient to elicit deflections of spatial attention.

Disentangling go/no-go from motivational orientation to foods: Approaching is more than just responding

BackgroundTraining motor responses to food images can influence subsequent evaluations of the food and even consumption. One important question in the literature is whether training people to approach versus avoid food items is different from training people to respond (‘go’) versus not responding (‘no go’) to food items. Therefore, we systematically investigated whether mere action, i.e., withholding responses vs go responses, and motivational orientation, i.e., approach and avoidance, differentially change stimulus valence. MethodsIn 60 healthy participants, we contrasted approach, avoidance, and non-responses with the same neutral go response in their potential to change food liking ratings and affective facial responses. ResultsTraining approach responses to stimuli increased their valence compared to mere go responses to stimuli as was evident from explicit liking ratings and facial corrugator activity. Unexpectedly, not responding to stimuli or avoiding stimuli did not decrease their valence relative to go stimuli. ConclusionThe current results suggest that approach responses may be more effective to increase the valence of food items than mere go responses. They further suggest that the devaluation of non-responded stimuli that is often found in the literature may not become visible in the current task set-up where the Go/No-go training is administered on a touchscreen.

Integration of sub-task scheduling and logistics in cloud manufacturing systems under setup time and different task arrival times

ABSTRACT With the development of new technologies, cloud manufacturing system allows users to request different services by providing a customer-oriented structure with the possibility of access to distributed manufacturing resources. By departing from literature, this study relaxes the unreasonable assumption that all tasks are available at the first moment of scheduling. In addition, two factors are considered to get the model closer to reality: (1) The time/cost of sub-tasks transfer among different services of enterprises in diverse geographical locations; and (2) Service setup time/cost to perform diverse sub-tasks on a given service consecutively. Taking into account these characteristics, a model including three objects of cost imposed on the cloud manufacturing system, task completion time and service quality is developed. The results confirm the importance of considering task arrival time, logistics time/cost and setup time/cost to get more realistic solutions. GAMS software is employed to solve the problems with small and medium scales while a solution approach method based on a genetic algorithm is developed to solve the problems on a large scale. And finally, a sensitivity analysis is undertaken to gain insight into the impact of time, cost and user’s requirements on the final solution.

How Findings from a Multi-Annual International Modeling Initiative Are Implemented in a Nuclear Waste Management Organization

In the present paper, we discuss various aspects of the SKB Task Force on Modeling of Groundwater Flow and Transport of Solutes (TFGWFTS). The TFGWTS is a multi-lateral forum for modeling of groundwater flow and solute transport, focusing on issues of relevance for disposal of nuclear waste. We discuss the objectives and set-up of the different tasks performed during the last 30 years, and specifically how the results of the modeling have informed performance and safety assessment applications within SKB (Swedish Nuclear Fuel and Waste Management Company, Solna, Sweden). We conclude that the TFGWFTS has been instrumental in developing modeling methodologies and tools, and in training and fostering modelers. While the early tasks were related to the construction of the Äspö Hard Rock Laboratory in Sweden and developed general modeling competence, the later tasks have served performance and safety assessment purposes in a more substantial manner.

Task-based profiles of language impairment and their relationship to cognitive dysfunction in Parkinson's disease.

ObjectiveParkinson’s Disease (PD) is associated with both motor and non-motor problems, such as cognitive impairment. Particular focus in this area has been on the relationship between language impairment and decline in other cognitive functions, with the literature currently inconclusive on how the nature and degree of language impairment relate to cognition or other measures of disease severity. In addition, little information is available on how language problems identified in experimental task set-ups relate to competency in self-generated language paradigms such as picture description, monologues or conversations. This study aimed to inform clinical management of language impairment in PD by exploring (1) language performance across a range of experimental as well as self-generated language tasks, (2) how the relationship between these two aspects might be affected by the nature of the cognitive and language assessment; and (3) to what degree performance can be predicted across the language tasks.Methods22 non-demented people with PD (PwPD) and 22 healthy control participants performed a range of cognitive and language tasks. Cognitive tasks included a screening assessment in addition to tests for set shifting, short term memory, attention, as well as letter and category fluency. Language was investigated in highly controlled grammar tasks as well as a Sentence Generation and a Narrative.ResultsThe study highlighted impaired ability in set-shifting and letter fluency in the executive function tasks, and a higher rate of grammatical and lexical errors across all language tasks in the PD group. The performance in the grammar task was linked to set shifting ability, but error rates in Sentence Generation and Narrative were independent of this. There was no relevant relationship between performances across the three language tasks.ConclusionsOur results suggest that there is a link between executive function and language performance, but that this is task dependent in non-demented PwPD. This has implications for the management of language impairment in PD, both for assessment and for designing effective interventions.

Explicit encoding vs. fast mapping of novel spoken words: Electrophysiological and behavioural evidence of diverging mechanisms

It has been claimed that two major neurocognitive mechanisms – instruction-based explicit encoding (EE) and inference-driven fast mapping (FM) may be involved in rapid acquisition of novel words, but their exact neural underpinnings remain poorly understood. To address this, we trained 36 adult participants with 20 novel spoken words in an audio-visual task, carefully balanced between the EE and FM conditions for physical, psycholinguistic and pragmatic properties as well as the overall task setup. To assess the neural dynamics associated with novel word acquisition, we recorded event-related potentials (ERPs) elicited by these words before and after training, and analysed their relationship with the behavioural learning outcomes, measured in a semantic matching task. Both learning regimes led to successful acquisition, which was somewhat more efficient for EE than FM, as indicated by higher accuracy in the behavioural task. We also found that, whereas words learnt via both EE and FM protocols elicited most pronounced ERP peaks at ∼196 and ∼280 ms, these two phases of activity diverged with respect to the learning type. Multiple linear regression and correlation analyses indicated that the learning-induced amplitude dynamics in the earlier peak was significantly related to behavioural performance for FM-learned items, which may possibly be explained by FM's stronger reliance on early automatic mechanisms of word processing. Performance on EE words was, in turn, significantly linked to the amplitude of the second peak only, potentially due to the involvement of later, top-down controlled processes in this type of word acquisition. Grand-average ERP-based source analysis indicated a left-lateralised activity in the anterior-temporal lobe for FM learning, and a bilateral activation for EE. The results confirm the existence of partially diverging neurocognitive systems for word acquisition and suggest that the configuration of newly established word memory circuits depends on the mode of their acquisition.

Differences in Lower Extremity Kinematics Based On Drop Vertical Jump Task Variations

Background: More advanced measures of movement quality may be necessary to better estimate return-to-play readiness. This emphasizes the need for a standardized motion analysis protocol to capture patients’ biomechanics during dynamic tasks, such as the drop vertical jump (DVJ). Given that the DVJ elicits a dynamic, game-like movement, it is commonly used in return-to-play functional testing and injury-risk research. However, the task procedure is not consistent across treatment and/or research centers. Hypothesis/Purpose: The purpose of this study was to determine whether variations in jump distance, verbal instructions, or target use would influence mechanics during a DVJ task. Methods: Fourteen healthy subjects (7 female, aged 22.7±3.7 years) were asked to perform six DVJ tasks from a 31cm plyo-box. Lower extremity kinematics were collected during the first landing/takeoff phase. Three tasks varied by jump distance (distance from box to center of force plates): zero distance (DROP), one-third (THIRD) and one-half (HALF) subject height. Additional verbal instructions were provided for the DROP task. Specifically, subjects were asked to first “drop off the box onto the force plates” (DROP), and then to “slightly bend their knees to ‘pop-off’ the box with both feet at the same time” (POP). Lastly, a target was positioned above the force plates for the HALF (H-TAR). Wilcoxon signed-rank tests were performed to assess differences between tasks ( α=0.05). Results: At initial contact (IC), knee flexion increased in the DROP (24.0˚±18.4˚, p=0.011) and THIRD (16.3˚±7.9, p=0.005) compared to the HALF (12.0˚±6.8˚). During the landing phase, maximum hip flexion increased in the HALF (106.0˚±27.5˚) compared to the DROP (100.6˚±25.0˚, p=0.011). Average pelvic tilt decreased in the DROP (32.1˚±4.8) compared to both the POP (37.8˚±5.7˚, p=0.009) and THIRD (34.5˚±6.2˚, p=0.008). When using a target, knee flexion increased at IC during the H-TAR (H-TAR:18.8˚±8.8˚, HALF:12.0˚±6.8˚, p=0.004). Conclusion: These findings emphasize the importance of understanding movement strategies associated with different variations of the DVJ. Specifically, a shift in landing strategy was seen as box distance increased. Therefore, the DROP may be more appropriate early in rehabilitation given that maximum hip flexion was reduced. In contrast, the HALF may be more appropriate for return-to-sport testing given that patients would exhibit improved neuromuscular motor control. These findings also highlight the need for standardized instructions and task setup. While this pilot data was collected in young adults, future work will need to focus on evaluating these task variations in a youth population. [Table: see text]

Differential effects of anodal and dual tDCS on sensorimotor functions in chronic hemiparetic stroke patients

Background and purposePrevious tDCS studies in chronic stroke patients reported highly inconsistent effects on sensorimotor functions. Underlying reasons could be the selection of different kinematic parameters across studies and for different tDCS setups. We reasoned that tDCS may not simply induce global changes in a beneficial-adverse dichotomy, but rather that different sensorimotor kinematics are differentially affected. Furthermore, the often-postulated higher efficacy of bilateral-dual (bi-tDCS) over unilateral-anodal (ua-tDCS) could not yet be demonstrated consistently either. We investigated the effects of both setups on a wider range of kinematic parameters from standardized robotic tasks in patients with chronic stroke. MethodsTwenty-four patients with arm hemiparesis received tDCS (20min, 1 mA) concurrent to kinematic assessments in a sham-controlled, cross-over and double-blind clinical trial. Performance was measured on four sensorimotor tasks (reaching, proprioception, cooperative and independent bimanual coordination) from which 30 parameters were extracted. On the group-level, the patterns of changes relative to sham were assessed using paired-samples t-tests and classified as (1) performance increases, (2) decreases and (3) non-significant differences. Correlations between parametric change scores were calculated for each task to assess effects on the individual-level. ResultsBoth setups induced complex effect patterns with varying proportions of performance increases and decreases. On the group-level, more increases were induced in the reaching and coordination tasks while proprioception and bimanual cooperation were overall negatively affected. Bi-tDCS induced more performance increases and less decreases compared to ua-tDCS. Changes across parameters occurred more homogeneously under bi-tDCS than ua-tDCS, which induced a larger proportion of performance trade-offs. ConclusionsOur data demonstrate profound tDCS effects on sensorimotor functions post-stroke, lending support for more pronounced and favorable effects of bi-tDCS compared to ua-tDCS. However, no uniformly beneficial pattern was identified. Instead, the modulations varied depending on the task and electrode setup, with increases in certain parameters occurring at the expense of decreases in others.

VDBFusion: Flexible and Efficient TSDF Integration of Range Sensor Data.

Mapping is a crucial task in robotics and a fundamental building block of most mobile systems deployed in the real world. Robots use different environment representations depending on their task and sensor setup. This paper showcases a practical approach to volumetric surface reconstruction based on truncated signed distance functions, also called TSDFs. We revisit the basics of this mapping technique and offer an approach for building effective and efficient real-world mapping systems. In contrast to most state-of-the-art SLAM and mapping approaches, we are making no assumptions on the size of the environment nor the employed range sensor. Unlike most other approaches, we introduce an effective system that works in multiple domains using different sensors. To achieve this, we build upon the Academy-Award-winning OpenVDB library used in filmmaking to realize an effective 3D map representation. Based on this, our proposed system is flexible and highly effective and, in the end, capable of integrating point clouds from a 64-beam LiDAR sensor at 20 frames per second using a single-core CPU. Along with this publication comes an easy-to-use C++ and Python library to quickly and efficiently solve volumetric mapping problems with TSDFs.