Moral alchemy: How love changes norms

We discuss a process by which non-moral concerns (that is concerns agreed to be non-moral within a particular cultural context) can take on moral content. We refer to this phenomenon as moral alchemy and suggest that it arises because moral obligations of care entail recursively valuing loved ones’ values, thus allowing propositions with no moral weight in themselves to become morally charged. Within this framework, we predict that when people believe a loved one cares about a behavior more than they do themselves, the moral imperative to care about the loved one's interests will raise the value of that behavior, such that people will be more likely to infer that third parties will see the behavior as wrong (Experiment 1) and the behavior itself as more morally important (Experiment 2) than when the same behaviors are considered outside the context of a caring relationship. The current study confirmed these predictions. Keywords: Moral learning, Ethics of care, Recursive value, UtilityNational Science Foundation (U.S.) (STC Award CCF-1231216

Catch Crops in Organic Farming Systems without Livestock Husbandry - Model Simulations

During the last years, an increasing number of stockless farms in Europe converted to organic farming practice without re-establishing a livestock. Due to the lack of animal manure as a nutrient input, the relocation and the external input of nutrients is limited in those organic cropping systems. The introduction of a one-year green manure fallow in a 4-year crop rotation, including clover-grass mixtures as a green manure crop is the classical strategy to solve at least some of the problems related to the missing livestock. The development of new crop rotations, including an extended use of catch crops and annual green manure (legumes) may be another possibility avoiding the economical loss during the fallow year. Modelling of the C and N turnover in the soil-plant-atmosphere system using the soil-plant-atmosphere model DAISY is one of the tools used for the development of new organic crop rotations. In this paper, we will present simulations based on a field experiment with incorporation of different catch crops. An important factor for the development of new crop rotations for stockless organic farming systems is the expected N mineralisation and immobilisation after incorporation of the plant materials. Therefore, special emphasise will be put on the simulation of N-mineralisation/-immobilisation and of soil microbial biomass N. Furthermore, particulate organic matter C and N as an indicator of remaining plant material under decomposition will be investigated

Sparse 3D Point-cloud Map Upsampling and Noise Removal as a vSLAM Post-processing Step: Experimental Evaluation

The monocular vision-based simultaneous localization and mapping (vSLAM) is one of the most challenging problem in mobile robotics and computer vision. In this work we study the post-processing techniques applied to sparse 3D point-cloud maps, obtained by feature-based vSLAM algorithms. Map post-processing is split into 2 major steps: 1) noise and outlier removal and 2) upsampling. We evaluate different combinations of known algorithms for outlier removing and upsampling on datasets of real indoor and outdoor environments and identify the most promising combination. We further use it to convert a point-cloud map, obtained by the real UAV performing indoor flight to 3D voxel grid (octo-map) potentially suitable for path planning.Comment: 10 pages, 4 figures, camera-ready version of paper for "The 3rd International Conference on Interactive Collaborative Robotics (ICR 2018)

Posttraumatic stress disorder and psychiatric co-morbidity following stroke: The role of alexithymia

More research is needed to further our understanding of posttraumatic stress disorder symptoms (PTSD) and psychiatric co-morbidity following stroke, especially the trajectories of such symptoms over time. Previous studies suggest that exposure to a traumatic experience such as stroke is not sufficient to explain the etiology of PTSD. Alexithymia may be involved, but its relationships with PTSD and psychiatric co-morbidity following stroke remains unclear. This study aims to address these knowledge gaps. While in hospital, stroke patients (n = 90) completed questionnaires assessing PTSD symptoms, psychiatric co-morbidity, alexithymia and physical disability. PTSD symptoms and psychiatric co-morbidity were re-assessed approximately 3. months post-stroke (n = 78). The severity of post-stroke PTSD did not change significantly over time, while psychiatric co-morbidity reduced significantly. Alexithymia, in particular difficulty in identifying feelings, was associated with severity of post-stroke PTSD and psychiatric co-morbidity at baseline, but after adjusting for these, there was no significance 3. months post-stroke. We suggest that patients\u27 difficulty in identifying feelings had a role to play in influencing relatively short-term rather than long-term PTSD and co-morbid psychiatric symptoms. Alternatively, PTSD could be interpreted as driving the alexithymic characteristics. © 2010 Elsevier Ltd

Towards heterogeneous robot team path planning: Acquisition of multiple routes with a modified spline-based algorithm

© 2017 The Authors. Our research focuses on operation of a heterogeneous robotic group that carries out point-to point navigation in GPS-denied dynamic environment, applying a combined local and global planning approach. In this paper, we introduce a homotopy-based high-level planner, which uses a modified splinebased path-planning algorithm. The algorithm utilizes Voronoi graph for global planning and a set of optimization criteria for local improvements of selected paths. The simulation was implemented in Matlab environment

Assessing response bias from missing quality of life data: The Heckman method

BACKGROUND: The objective of this study was to demonstrate the use of the Heckman two-step method to assess and correct for bias due to missing health related quality of life (HRQL) surveys in a clinical study of acute coronary syndrome (ACS) patients. METHODS: We analyzed data from 2,733 veterans with a confirmed diagnosis of acute coronary syndromes (ACS), including either acute myocardial infarction or unstable angina. HRQL outcomes were assessed by the Short-Form 36 (SF-36) health status survey which was mailed to all patients who were alive 7 months following ACS discharge. We created multivariable models of 7-month post-ACS physical and mental health status using data only from the 1,660 survey respondents. Then, using the Heckman method, we modeled survey non-response and incorporated this into our initial models to assess and correct for potential bias. We used logistic and ordinary least squares regression to estimate the multivariable selection models. RESULTS: We found that our model of 7-month mental health status was biased due to survey non-response, while the model for physical health status was not. A history of alcohol or substance abuse was no longer significantly associated with mental health status after controlling for bias due to non-response. Furthermore, the magnitude of the parameter estimates for several of the other predictor variables in the MCS model changed after accounting for bias due to survey non-response. CONCLUSION: Recognition and correction of bias due to survey non-response changed the factors that we concluded were associated with HRQL seven months following hospital admission for ACS as well as the magnitude of some associations. We conclude that the Heckman two-step method may be a valuable tool in the assessment and correction of selection bias in clinical studies of HRQL

Changing minds: Children's inferences about third party belief revision

By the age of 5, children explicitly represent that agents can have both true and false beliefs based on epistemic access to information (e.g., Wellman, Cross, & Watson, 2001). Children also begin to understand that agents can view identical evidence and draw different inferences from it (e.g., Carpendale & Chandler, 1996). However, much less is known about when, and under what conditions, children expect other agents to change their minds. Here, inspired by formal ideal observer models of learning, we investigate children's expectations of the dynamics that underlie third parties' belief revision. We introduce an agent who has prior beliefs about the location of a population of toys and then observes evidence that, from an ideal observer perspective, either does, or does not justify revising those beliefs. We show that children's inferences on behalf of third parties are consistent with the ideal observer perspective, but not with a number of alternative possibilities, including that children expect other agents to be influenced only by their prior beliefs, only by the sampling process, or only by the observed data. Rather, children integrate all three factors in determining how and when agents will update their beliefs from evidence.National Science Foundation (U.S.). Division of Computing and Communication Foundations (1231216)National Science Foundation (U.S.). Division of Research on Learning in Formal and Informal Settings (0744213)National Science Foundation (U.S.) (STC Center for Brains, Minds and Machines Award CCF-1231216)National Science Foundation (U.S.) (0744213

Voronoi-based trajectory optimization for UGV path planning

© 2017 IEEE. Optimal path planning in dynamic environments for an unmanned vehicle is a complex task of mobile robotics that requires an integrated approach. This paper describes a path planning algorithm, which allows to build a preliminary motion trajectory using global information about environment, and then dynamically adjust the path in real-time by varying objective function weights. We introduce a set of key parameters for path optimization and the algorithm implementation in MATLAB. The developed algorithm is suitable for fast and robust trajectory tuning to a dynamically changing environment and is capable to provide efficient planning for mobile robots

Changing minds: Children’s inferences about third party belief revision

By the age of 5, children explicitly represent that agents can have both true and false beliefs based on epistemic access to information (e.g., Wellman, Cross, & Watson, 2001). Children also begin to understand that agents can view identical evidence and draw different inferences from it (e.g., Carpendale & Chandler, 1996). However, much less is known about when, and under what conditions, children expect other agents to change their minds. Here, inspired by formal ideal observer models of learning, we investigate children’s expectations of the dynamics that underlie third parties’ belief revision. We introduce an agent who has prior beliefs about the location of a population of toys and then observes evidence that, from an ideal observer perspective, either does, or does not justify revising those beliefs. We show that children’s inferences on behalf of third parties are consistent with the ideal observer perspective, but not with a number of alternative possibilities, including that children expect other agents to be influenced only by their prior beliefs, only by the sampling process, or only by the observed data. Rather, children integrate all three factors in determining how and when agents will update their beliefs from evidence.Young children use others’ prior beliefs and data to predict when third parties will retain their beliefs and when they will change their minds.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142970/1/desc12553_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142970/2/desc12553.pd

Humanoid robot kinematic calibration using industrial manipulator

© 2017 IEEE. Kinematic calibration is a crucial task for humanoid robot locomotion. The paper proposes a novel technique for joint offset calibration using industrial manipulator. Corresponding procedure uses position and orientation data from the manipulator and requires fixing of robots bases and end-effectors with respect to each other. The full pose information is obtaining as the humanoid limbs are moved through predefined configurations. To find joint offsets the least-squares optimization problem is solved. The proposed method is accurate since the industrial manipulator provides high precision. The proposed approach was validated on the calibration of AR601M humanoid robot using Kuka iiwa 14 industrial manipulator