Quantum Criticality in Heavy Fermion Metals

Quantum criticality describes the collective fluctuations of matter undergoing a second-order phase transition at zero temperature. Heavy fermion metals have in recent years emerged as prototypical systems to study quantum critical points. There have been considerable efforts, both experimental and theoretical, which use these magnetic systems to address problems that are central to the broad understanding of strongly correlated quantum matter. Here, we summarize some of the basic issues, including i) the extent to which the quantum criticality in heavy fermion metals goes beyond the standard theory of order-parameter fluctuations, ii) the nature of the Kondo effect in the quantum critical regime, iii) the non-Fermi liquid phenomena that accompany quantum criticality, and iv) the interplay between quantum criticality and unconventional superconductivity.Comment: (v2) 39 pages, 8 figures; shortened per the editorial mandate; to appear in Nature Physics. (v1) 43 pages, 8 figures; Non-technical review article, intended for general readers; the discussion part contains more specialized topic

Exposure to Moderate Air Pollution during Late Pregnancy and Cord Blood Cytokine Secretion in Healthy Neonates

Ambient air pollution can alter cytokine concentrations as shown in vitro and following short-term exposure to high air pollution levels in vivo. Exposure to pollution during late pregnancy has been shown to affect fetal lymphocytic immunophenotypes. However, effects of prenatal exposure to moderate levels of air pollutants on cytokine regulation in cord blood of healthy infants are unknown. In a birth cohort of 265 healthy term-born neonates, we assessed maternal exposure to particles with an aerodynamic diameter of 10 µm or less (PM₁₀), as well as to indoor air pollution during the last trimester, specifically the last 21, 14, 7, 3 and 1 days of pregnancy. As a proxy for traffic-related air pollution, we determined the distance of mothers' homes to major roads. We measured cytokine and chemokine levels (MCP-1, IL-6, IL-10, IL-1ß, TNF-α and GM-CSF) in cord blood serum using LUMINEX technology. Their association with pollution levels was assessed using regression analysis, adjusted for possible confounders. Mean (95%-CI) PM₁₀ exposure for the last 7 days of pregnancy was 18.3 (10.3-38.4 µg/m³). PM₁₀ exposure during the last 3 days of pregnancy was significantly associated with reduced IL-10 and during the last 3 months of pregnancy with increased IL-1ß levels in cord blood after adjustment for relevant confounders. Maternal smoking was associated with reduced IL-6 levels. For the other cytokines no association was found. Our results suggest that even naturally occurring prenatal exposure to moderate amounts of indoor and outdoor air pollution may lead to changes in cord blood cytokine levels in a population based cohort

The Cross-Talk between Spirochetal Lipoproteins and Immunity

Spirochetal diseases such as syphilis, Lyme disease and leptospirosis are major threats to public health. However the immunopathogenesis of these diseases has not been fully elucidated. Spirochetes interact with the host through various structural components such as lipopolysaccharides (LPS), surface lipoproteins and glycolipids. Although spirochetal antigens such as LPS and glycolipids may contribute to the inflammatory response during spirochetal infections, spirochetes such as Treponema pallidum and Borrelia burgdorferi lack LPS. Lipoproteins are most abundant proteins that are expressed in all spirochetes and often determine how spirochetes interact with their environment. Lipoproteins are proinflammatory, may regulate responses from both innate and adaptive immunity and enable the spirochetes to adhere to the host or the tick midgut or to evade the immune system. However, most of the spirochetal lipoproteins have unknown function. Herein, the immunomodulatory effects of spirochetal lipoproteins are reviewed and are grouped into two main categories: effects related to immune evasion and effects related to immune activation. Understanding lipoprotein-induced immunomodulation will aid in elucidating innate immunopathogenesis processes and subsequent adaptive mechanisms potentially relevant to spirochetal disease vaccine development and to inflammatory events associated with spirochetal diseases

A Simulation Enabled Procedure for Eco-efficiency Optimization in Production Systems

Part III: Sustainable ServicesInternational audienceEnvironmental sustainability in manufacturing has been experiencing increasing attention in practice and academia over the last decades. Manufacturing companies strive to improve their eco-efficiency, which is commonly understood as delivering high value products at lower cost and environmental impact. They need tools and methods to translate this strategic goal onto the operational shop floor level. This paper presents a procedure for optimizing the eco-efficiency of production systems, supported by a discrete-event material flow simulation model. Its application is shown in a case with a company from the Swiss consumer goods industry

Tabula smaragdina medico-pharmaceutica ...

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A simulation-based decision support system for industrial field service network planning

Technical field services for industrial machinery and equipment have become increasingly important for original equipment manufacturers. To deliver services to their customers, companies have to build up new core competencies and infrastructure, a challenge due to the high complexity and dynamics of this business. To assist companies in the strategic design of their network and the planning of resources for delivering industrial field services, we present a model-driven decision support system that uses discrete event simulation to support decision makers in various aspects of strategic design and tactical planning. The benefits of the decision support system include the creation of a generic framework that makes it possible to create simulation models of different field service networks for multiple purposes. Specifically, the system can be used to support various tactical planning and strategic design decisions while keeping investments low in terms of time consumption and money spending. In addition, the paper closes an identified gap involving a lack of decision support for the management of field service networks. An application of the decision support system in an exemplary case is used to illustrate potential applications and benefits

Fairness and Bias in Robot Learning

Machine learning has significantly enhanced the abilities of robots, enabling them to perform a wide range of tasks in human environments and adapt to our uncertain real world. Recent works in various domains of machine learning have highlighted the importance of accounting for fairness to ensure that these algorithms do not reproduce human biases and consequently lead to discriminatory outcomes. With robot learning systems increasingly performing more and more tasks in our everyday lives, it is crucial to understand the influence of such biases to prevent unintended behavior toward certain groups of people. In this work, we present the first survey on fairness in robot learning from an interdisciplinary perspective spanning technical, ethical, and legal challenges. We propose a taxonomy for sources of bias and the resulting types of discrimination due to them. Using examples from different robot learning domains, we examine scenarios of unfair outcomes and strategies to mitigate them. We present early advances in the field by covering different fairness definitions, ethical and legal considerations, and methods for fair robot learning. With this work, we aim at paving the road for groundbreaking developments in fair robot learning