597 research outputs found
Magnetic Properties of Uranium Based Ferromagnetic Superconductors
No full textFerromagnetism and superconductivity have long been thought to be mutually exclusive. Recently however it was found that the compounds UGe2, URhGe and UIr belong to a class of materials in which ferromagnetisme and superconductivity appear simultaneously. One characteristic property of these compounds is the existence of strong correlations between the magnetic moments of the uranium ions and the conduction electrons. These correlations lead to unusual magnetic properties at low temperatures. By applying external pressure the magnetic correlations can be varied. The fact that superconductivity in these materials is found only for those pressures, at which the magnetic correlations are strongest, indicates that the effective attracting force between the conduction electrons responsible for superconductivity has a magnetic origin. In this research the magnetic correlations of the ferromagnetic superconductors are investigated in order to better understand the unusual coexistence of ferromagnetism and superconductivity. Besides the dilatometry, specific heat, magnetization, and three-dimensional neutron depolarization techniques, the muon spin relaxation (muSR) technique is frequently used in the study of de magnetic properties of the ferromagnetic superconductors. The muon experiments indicate that unusual excitations exist in these materials which are possibly responsible for the superconductivity.Applied Science
Policy Compression for Intelligent Continuous Control on Low-Power Edge Devices
No full textInterest in deploying deep reinforcement learning (DRL) models on low-power edge devices, such as Autonomous Mobile Robots (AMRs) and Internet of Things (IoT) devices, has seen a significant rise due to the potential of performing real-time inference by eliminating the latency and reliability issues incurred from wireless communication and the privacy benefits of processing data locally. Deploying such energy-intensive models on power-constrained devices is not always feasible, however, which has led to the development of model compression techniques that can reduce the size and computational complexity of DRL policies. Policy distillation, the most popular of these methods, can be used to first lower the number of network parameters by transferring the behavior of a large teacher network to a smaller student model before deploying these students at the edge. This works well with deterministic policies that operate using discrete actions. However, many real-world tasks that are power constrained, such as in the field of robotics, are formulated using continuous action spaces, which are not supported. In this work, we improve the policy distillation method to support the compression of DRL models designed to solve these continuous control tasks, with an emphasis on maintaining the stochastic nature of continuous DRL algorithms. Experiments show that our methods can be used effectively to compress such policies up to 750% while maintaining or even exceeding their teacher’s performance by up to 41% in solving two popular continuous control tasks
Next generation of biologics for the treatment of Crohn’s disease: an evidence-based review on ustekinumab
No full textAranzazu Jauregui-Amezaga, Michael Somers, Heiko De Schepper, Elisabeth Macken Department of Gastroenterology, Universitair Ziekenhuis Antwerpen, University of Antwerp, Antwerp, Belgium Abstract: The limited efficacy of the currently available medical therapies in a proportion of patients with Crohn’s disease has led to the research and development of molecules that can block new inflammatory pathways. Ustekinumab is a fully human IgG1 monoclonal antibody which targets the common p40 subunit of the cytokines interleukin-12 as well as interleukin-23. Consequently, the Th1 and Th17 inflammatory responses are inhibited. Ustekinumab has been recently approved for its use in patients with Crohn’s disease. Its efficacy and safety was initially proved in patients with psoriasis and psoriatic arthritis. More recently, three Phase III trials have confirmed its efficacy in patients with Crohn’s disease refractory to anti-tumor necrosis factor therapy. This biologic agent appears safe, with no increased risk of infectious or malignant complications, and a low immunogenic profile. Keywords: ustekinumab, interleukin-12, interleukin-23, biologic therapy, inflammatory bowel disease, Crohn’s diseas
De vergeten beeldentaal van Jheronimus Bosch : de symboliek van de Hooiwagen-triptiek en de Rotterdamse Marskramer-tondo verklaard vanuit Middelnederlandse teksten /
No full textMet hs. opdracht van Stephan PasLeeseditie van het gelijknamige proefschrift, 2001.De Schepper, MarcusOorspr. proefschrift o.d.t. "Half zot, half vroed. Half kwaad, half goed.", Katholieke Universiteit Brussel, 2000
De diversiteit van darmmacrofagen herbekeken: van transcriptoom naar functie
No full textIntestinal macrophages are essential components of the gastrointestinal tract and exhibit highly specific functions depending on their anatomical location within the gut. Lamina propria macrophages face the gut lumen and are involved in bacterial clearance, initiation of adaptive immunity and installing oral tolerance. In contract, macrophages residing in the muscularis externa regulate intestinal peristaltic activity through direct crosstalk with enteric neurons. Increasing evidence from our group and others indeed suggests that the enteric nervous system (ENS) provides signals that account for the gut-specific macrophage phenotype. This tolerogenic transcriptome is characterized by an immunological quiescent state and linked to the prominent expression of the chemokine receptor CX3CR1 and other unique signature genes.
However, the mediator(s) released by the enteric neurons determining the tolerogenic phenotype are unexplored. Moreover, revealing this neuro-modulated macrophage population has been complicated by the heterogeneity of hematopoietic cells within the gastrointestinal tract. This dissertation is focused on the comprehensive characterization of the intestinal macrophage population involved in the communication with enteric neurons. ENS-derived signals that shape macrophage identity will be explored and we will investigate how the macrophage-enteric neuronal crosstalk reflects in both physiological (such as intestinal motility) and disease contexts (such as DSS colitis and post-operative ileus).status: Publishe
Transition probabilities for diffusion equations by means of path integrals.
No full textIn this paper, we investigate the transition probabilities for diffusion processes. In a first part, we show how transition probabilities for rather general diffusion processes can always be expressed by means of a path integral. For several classical models, an exact calculation is possible, leading to analytical expressions for the transition probabilities and for the maximum probability paths. A second part consists of the derivation of an analytical approximation for the transition probability, which is useful in case the path integral is too complex to be calculated. The approximation we present is based on a convex combination of a new analytical upper and lower bound for the transition probabilities. The fact that the approximation is analytical has some important advantages, e.g. for the investigation of Asian options. Finally, we demonstrate the accuracy of the approximation by means of a few graphical illustrationsAdvantages; Comonotonicity; Diffusion processes; Models; Option; Path integral;
Model simulations unveil the structure-function-dynamics relationship of the cerebellar cortical microcircuit
No full textThe cerebellar network is renowned for its regular architecture that has inspired foundational computational theories. However, the relationship between circuit structure, function and dynamics remains elusive. To tackle the issue, we developed an advanced computational modeling framework that allows us to reconstruct and simulate the structure and function of the mouse cerebellar cortex using morphologically realistic multi-compartmental neuron models. The cerebellar connectome is generated through appropriate connection rules, unifying a collection of scattered experimental data into a coherent construct and providing a new model-based ground-truth about circuit organization. Naturalistic background and sensory-burst stimulation are used for functional validation against recordings in vivo, monitoring the impact of cellular mechanisms on signal propagation, inhibitory control, and long-term synaptic plasticity. Our simulations show how mossy fibers entrain the local neuronal microcircuit, boosting the formation of columns of activity travelling from the granular to the molecular layer providing a new resource for the investigation of local microcircuit computation and of the neural correlates of behavior
A Bayesian copula model for stochastic claims reserving
No full textWe present a full Bayesian model for assessing the reserve requirement of multiline Non-Life insurance companies. Bayesian models for claims reserving allow to account for expert knowledge in the evaluation of Outstanding Loss Liabilities, allowing the use of additional information at a low cost. This paper combines a standard Bayesian approach for the estimation of marginal distribution for the single Lines of Business for a Non-Life insurance company and a Bayesian copula procedure for the estimation of aggregate reserves. The model we present allows to "mix" own-assessments of dependence between LoBs at a company level and market-wide estimates provided by regulators. We illustrate results for the single lines of business and we compare standard copula aggregation for different copula choices and the Bayesian copula approach
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