Slow relaxation in the Ising model on a small-world network with strong long-range interactions

We consider the Ising model on a small-world network, where the long-range interaction strength $J_2$ is in general different from the local interaction strength $J_1$, and examine its relaxation behaviors as well as phase transitions. As $J_2/J_1$ is raised from zero, the critical temperature also increases, manifesting contributions of long-range interactions to ordering. However, it becomes saturated eventually at large values of $J_2/J_1$ and the system is found to display very slow relaxation, revealing that ordering dynamics is inhibited rather than facilitated by strong long-range interactions. To circumvent this problem, we propose a modified updating algorithm in Monte Carlo simulations, assisting the system to reach equilibrium quickly.Comment: 5 pages, 5 figure

Learning robust policies for object manipulation with robot swarms

Swarm robotics investigates how a large population of robots with simple actuation and limited sensors can collectively solve complex tasks. One particular interesting application with robot swarms is autonomous object assembly. Such tasks have been solved successfully with robot swarms that are controlled by a human operator using a light source. In this paper, we present a method to solve such assembly tasks autonomously based on policy search methods. We split the assembly process in two subtasks: generating a high-level assembly plan and learning a low-level object movement policy. The assembly policy plans the trajectories for each object and the object movement policy controls the trajectory execution. Learning the object movement policy is challenging as it depends on the complex state of the swarm which consists of an individual state for each agent. To approach this problem, we introduce a representation of the swarm which is based on Hilbert space embeddings of distributions. This representation is invariant to the number of agents in the swarm as well as to the allocation of an agent to its position in the swarm. These invariances make the learned policy robust to changes in the swarm and also reduce the search space for the policy search method significantly. We show that the resulting system is able to solve assembly tasks with varying object shapes in multiple simulation scenarios and evaluate the robustness of our representation to changes in the swarm size. Furthermore, we demonstrate that the policies learned in simulation are robust enough to be transferred to real robots

Robust learning of object assembly tasks with an invariant representation of robot swarms

— Swarm robotics investigates how a large population of robots with simple actuation and limited sensors can collectively solve complex tasks. One particular interesting application with robot swarms is autonomous object assembly. Such tasks have been solved successfully with robot swarms that are controlled by a human operator using a light source. In this paper, we present a method to solve such assembly tasks autonomously based on policy search methods. We split the assembly process in two subtasks: generating a high-level assembly plan and learning a low-level object movement policy. The assembly policy plans the trajectories for each object and the object movement policy controls the trajectory execution. Learning the object movement policy is challenging as it depends on the complex state of the swarm which consists of an individual state for each agent. To approach this problem, we introduce a representation of the swarm which is based on Hilbert space embeddings of distributions. This representation is invariant to the number of agents in the swarm as well as to the allocation of an agent to its position in the swarm. These invariances make the learned policy robust to changes in the swarm and also reduce the search space for the policy search method significantly. We show that the resulting system is able to solve assembly tasks with varying object shapes in multiple simulation scenarios and evaluate the robustness of our representation to changes in the swarm size. Furthermore, we demonstrate that the policies learned in simulation are robust enough to be transferred to real robots

Development of a multivariate spectral emissivity model for an advanced high strength steel alloy through factorial design-of-experiments

The final publication is available at Elsevier via https://doi.org/10.1016/j.jqsrt.2021.107693. © 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Variations in the spectral emissivity of advanced high strength steels (AHSS) during intercritical annealing leads to errors in pyrometry measurements, which, in turn, cause thermal excursions that impact the mechanical properties of the steel. This paper presents an empirical approach for modelling the spectral emissivity of advanced high strength steel. Samples of two dual-phase steel (DP980) alloys, having Si/Mn ratios of 0.04 and 0.23, are heated within a galvanizing simulator in atmospheres of 95%/5% N2/H2 and dew points of 10°C and −30°C. The spectral hemispherical reflectance of the annealed samples was measured with an FTIR spectrometer. The variation of the spectral emissivity with dew point, alloy composition, pre-annealed surface state, and wavelength is analyzed using full factorial designs. The significant main and interaction effects vary across the spectral range, with the ratio of alloy components and pre-annealed surface state dominating at shorter and longer wavelengths, respectively. The predicted spectral emissivity values obtained from the model fitted for a three-channel pyrometer shows good agreement with the measurements. This study shows response surface methods (RSM) to be a viable approach for developing spectral emissivity models for pyrometry applications.NSERC CRD 521291-17, Galvanized Autobody Partnershi

Solution of Abel's integral equation using Tikhonov regularization

Peer reviewed: YesNRC publication: Ye

Transparent p-type conducting CuScO₂₊ₓ films

Transparent films of CuScO₂₊ₓ have been prepared which show p-type electrical conductivity. The temperature dependence of the conductivity indicates semiconducting behavior with an apparent room temperature activation energy of 0.11 eV. The highest room temperature conductivity observed was 30 S cm⁻1. Films 110 nm thick show 40% transparency in most of the visible spectrum and become much more transparent in the infrared spectrum. The p-type behavior was confirmed by the Seebeck effect

Report From the American Society of Transplantation Conference on Donor Heart Selection in Adult Cardiac Transplantation in the United States

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138918/1/ajt14354.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138918/2/ajt14354_am.pd

Combined In Silico, In Vivo, and In Vitro Studies Shed Insights into the Acute Inflammatory Response in Middle-Aged Mice

We combined in silico, in vivo, and in vitro studies to gain insights into age-dependent changes in acute inflammation in response to bacterial endotoxin (LPS). Time-course cytokine, chemokine, and NO2-/NO3- data from "middle-aged" (6-8 months old) C57BL/6 mice were used to re-parameterize a mechanistic mathematical model of acute inflammation originally calibrated for "young" (2-3 months old) mice. These studies suggested that macrophages from middle-aged mice are more susceptible to cell death, as well as producing higher levels of pro-inflammatory cytokines, vs. macrophages from young mice. In support of the in silico-derived hypotheses, resident peritoneal cells from endotoxemic middle-aged mice exhibited reduced viability and produced elevated levels of TNF-α, IL-6, IL-10, and KC/CXCL1 as compared to cells from young mice. Our studies demonstrate the utility of a combined in silico, in vivo, and in vitro approach to the study of acute inflammation in shock states, and suggest hypotheses with regard to the changes in the cytokine milieu that accompany aging. © 2013 Namas et al

Cost analysis of depression using the national insurance system in South Korea: a comparison of depression and treatment-resistant depression

The incidence and burden of depressive disorders are increasing in South Korea. There are many differences between pharmaceutically treated depression (PTD) and treatment-resistant depression (TRD), including the economic consequences; however, to our knowledge, the economic burden of depression is understudied in South Korea. Therefore, the objective of the present study was to calculate the different economic costs of PTD and TRD in South Korea, specifically by comparing several aspects of medical care. This study comprised patients aged 18 and over who were newly prescribed antidepressants for more than 28 days with a depression code included from January 1, 2012, to December 31, 2012, by the Health Insurance Review and Assessment Service (HIRA). TRD was classified as more than two antidepressant regimen failures in PTD patients. The cost was calculated based on the cost reflected on the receipt registered with HIRA. Of the 834,694 patients with PTD, 34,812 patients (4.17%) were converted to TRD. The cost of medical care for TRD (6,610,487 KRW, 5881 USD) was approximately 5 times higher than the cost of non-TRD (1,273,045 KRW, 1133 USD) and was significantly higher for patients with or without depression and suicide codes. Medical expenses incurred by non-psychiatrists were roughly 1.7 times higher than those incurred by psychiatrists. TRD patients had significantly higher healthcare costs than PTD patients. Identifying these financial aspects of care for depression can help to establish a more effective policy to reduce the burden on mentally ill patients.This study was funded by the Janssen Korea Ltd. (RRA-17716), and also confirms that Jansen has the author of the study. Two authors (G.J.C. and M.K.2) and the Janssen Korea contributed for conceptualization, investigation, funding acquisition and wrting original draft. However, the funder (Jansen and its employees) had no possibilities to influence the analyses, interpretation of data and and in writing the manuscript