ABSTRACT. DC resistivity combined with pH and Eh measured in soil samples, were used for evaluation of the geochemical behavior of buried solid waste, during the degradation process of organic matter. The studied area is a controlled landfill, characterized by the disposition of domestics waste in ditches, of which closed

We present a graph neural network to learn graph coloring heuristics using reinforcement learning. Our learned deterministic heuristics give better solutions than classical degree-based greedy heuristics and only take seconds to evaluate on graphs with tens of thousands of vertices. As our approach is based on policygradients, it also learns a probabilistic policy as well. These probabilistic policies outperform all greedy coloring baselines and a machine learning baseline. Our approach generalizes several previous machine-learning frameworks, which applied to problems like minimum vertex cover. We also demonstrate that our approach outperforms two greedy heuristics on minimum vertex cover. * Equal contribution Preprint. Under review.

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Taking patients' medical history correctly is the basis of diagnosis and therapy. Medical students as a vulnerable group may perceive patient–physician interactions as stressful. This study examines stress among medical students in different degrees of fidelity when taking a patient's medical history. In this longitudinal study, students' stress levels were assessed during scenarios with different degrees of fidelity (role‐play, simulated patient encounters and real patient encounters) using standardised questionnaires (State‐Trait Anxiety Inventory and a distress scale) and the physiological measurement of heart rate variability. The stress level of participating medical students (N = 128) was expected to significantly increase during scenarios of increasing fidelity (Mroleplay = 2.08 ± 0.92; SPEs: Msimulatedpatient = 2.68 ± 1.08; RPEs: Mrealpatient = 3.35 ± 1.08; p < 0.001). Whereas physiological stress was significantly higher with real patients (N = 106), psychological stress was not affected by the fidelity of the scenarios (N = 85). Medical students experienced stress when taking patients' medical history. Medical students might be unaware of their perceived stress based on the results. Thus, they should know how to cope with stress in such situations.