Bayesian online learning for energy-aware resource orchestration in virtualized RANs

Proceedings of: IEEE International Conference on Computer Communications, 10-13 May 2021, Vancouver, BC, Canada.Radio Access Network Virtualization (vRAN) will spearhead the quest towards supple radio stacks that adapt to heterogeneous infrastructure: from energy-constrained platforms deploying cells-on-wheels (e.g., drones) or battery-powered cells to green edge clouds. We perform an in-depth experimental analysis of the energy consumption of virtualized Base Stations (vBSs) and render two conclusions: (i) characterizing performance and power consumption is intricate as it depends on human behavior such as network load or user mobility; and (ii) there are many control policies and some of them have non-linear and monotonic relations with power and throughput. Driven by our experimental insights, we argue that machine learning holds the key for vBS control. We formulate two problems and two algorithms: (i) BP-vRAN, which uses Bayesian online learning to balance performance and energy consumption, and (ii) SBP-vRAN, which augments our Bayesian optimization approach with safe controls that maximize performance while respecting hard power constraints. We show that our approaches are data-efficient and have provably performance, which is paramount for carrier-grade vRANs. We demonstrate the convergence and flexibility of our approach and assess its performance using an experimental prototype.This work was supported by the European Commission through Grant No. 856709 (5Growth) and Grant No. 101017109 (DAEMON); and by SFI through Grant No. SFI 17/CDA/4760

Orchestrating energy-efficient vRANs: Bayesian learning and experimental results

Virtualized base stations (vBS) can be implemented in diverse commodity platforms and are expected to bring unprecedented operational flexibility and cost efficiency to the next generation of cellular networks. However, their widespread adoption is hampered by their complex configuration options that affect in a non-traditional fashion both their performance and their power consumption requirements. Following an in-depth experimental analysis in a bespoke testbed, we characterize the vBS power cost profile and reveal previously unknown couplings between their various control knobs. Motivated by these findings, we develop a Bayesian learning framework for the orchestration of vBSs and design two novel algorithms: (i) BP-vRAN, which employs online learning to balance the vBS performance and energy consumption, and (ii) SBP-vRAN, which augments our optimization approach with safe controls that maximize performance while respecting hard power constraints. We show that our approaches are data-efficient, i.e., converge an order of magnitude faster than state-of-the-art Deep Reinforcement Learning methods, and achieve optimal performance. We demonstrate the efficacy of these solutions in an experimental prototype using real traffic traces.This work has been supported by the European Commission through Grant No. 101017109 (DAEMON project), and the CERCA Programme/Generalitat de Catalunya

The Effect of Natural Mulches on Crop Performance, Weed Suppression and Biochemical Constituents of Catnip and St. John\u27s Wort

Because of expanding markets for high-value niche crops, opportunities have increased for the production of medicinal herbs in the USA. An experiment was conducted in 2001 and 2002 near Gilbert, IA, to study crop performance, weed suppression, and environmental conditions associated with the use of several organic mulches in the production of two herbs, catnip (Nepeta cataria L.) and St. John\u27s wort (Hypericum perforatum L. ‘Helos’). Treatments were arranged in a completely randomized design and included a positive (hand-weeded) control, a negative (nonweeded) control, oat straw, a flax straw mat, and a nonwoven wool mat. Catnip plant height was significantly greater in the oat straw than the other treatments at 4 wk through 6 wk in 2001; at 4 to 8 wk in 2002, catnip plant height and width was significantly lower in the negative control compared with the other treatments. Catnip yield was significantly higher in the flax straw mat than all other treatments in 2001. In 2002, St. John\u27s wort yields were not statistically different in any treatments. All weed management treatments had significantly fewer weeds than the non-weeded rows in 2002. Total weed density comparisons in each crop from 2 yr showed fewer weeds present in the flax straw and wool mat treatments compared with positive control plots. There was no significant weed management treatment effect on the concentration of the target compounds, nepetalactone in catnip and pseudohypericin–hypericin in St. John\u27s wort, although there was a trend toward higher concentrations in the flax straw treatment

CART cells are prone to Fas- and DR5-mediated cell death.

Adoptive transfer of T cells transduced with Chimeric Antigen Receptors (CAR) are now FDA-approved for the treatment of B-cell malignancies. Yet, the functionality of the endogenous TCR in CART cells has not been fully assessed. Here, we demonstrate that CART cells progressively upregulate Fas, FasL, DR5 and TRAIL, which result in their programmed cell death, independently of antigen-mediated TCR or CAR activation. CART cell apoptosis occurs even when the CAR contains a single (co-)activatory domain such as CD3ζ, CD28 or 4-1BB. Importantly, the dominant role of the Fas and DR5 pathways in CART cell apoptosis is demonstrated by the significant rescue of CART cells upon in vivo blockade by combined Fas-Fc and DR5-Fc recombinant proteins. These observations are of crucial importance for the long-term persistence of CART cells and for the development of new applications including the combined TCR and CAR activation against solid tumors

MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation

MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision based on multiresolution analysis and separated representations. Underpinning the numerical capabilities is a powerful petascale parallel programming environment that aims to increase both programmer productivity and code scalability. This paper describes the features and capabilities of MADNESS and briefly discusses some current applications in chemistry and several areas of physics

Hippocampal long-term potentiation is disrupted during expression and extinction but is restored after reinstatement of morphine place preference

Learned associations between environmental cues and morphine use play an important role in the maintenance and/or relapse of opioid addiction. Although previous studies suggest that context-dependent morphine treatment alters glutamatergic transmission and synaptic plasticity in the hippocampus, their role in morphine conditioned place preference (CPP) and reinstatement remains unknown. We investigated changes in synaptic plasticity and NMDAR expression in the hippocampus after the expression, extinction, and reinstatement of morphine CPP. Here we report that morphine CPP is associated with increased basal synaptic transmission, impaired hippocampal long-term potentiation (LTP), and increased synaptic expression of the NR1 and NR2b NMDAR subunits. Changes in synaptic plasticity, synaptic NR1 and NR2b expression, and morphine CPP were absent when morphine was not paired with a specific context. Furthermore, hippocampal LTP was impaired and synaptic NR2b expression was increased after extinction of morphine CPP, indicating that these alterations in plasticity may be involved in the mechanisms underlying the learning of drug–environment associations. After extinction of morphine CPP, a priming dose of morphine was sufficient to reinstate morphine CPP and was associated with LTP that was indistinguishable from saline control groups. In contrast, morphine CPP extinguished mice that received a saline priming dose did not show CPP and had disrupted hippocampal LTP. Finally, we found that reinstatement of morphine CPP was prevented by the selective blockade of the NR2b subunit in the hippocampus. Together, these data suggest that alterations in synaptic plasticity and glutamatergic transmission play an important role in the reinstatement of morphine CPP

Towards a Proof Theory of G\"odel Modal Logics

Analytic proof calculi are introduced for box and diamond fragments of basic modal fuzzy logics that combine the Kripke semantics of modal logic K with the many-valued semantics of G\"odel logic. The calculi are used to establish completeness and complexity results for these fragments

Community-Based Participatory Research: Lessons Learned from the Centers for Children’s Environmental Health and Disease Prevention Research

Over the past several decades there has been growing evidence of the increase in incidence rates, morbidity, and mortality for a number of health problems experienced by children. The causation and aggravation of these problems are complex and multifactorial. The burden of these health problems and environmental exposures is borne disproportionately by children from low-income communities and communities of color. Researchers and funding institutions have called for increased attention to the complex issues that affect the health of children living in marginalized communities—and communities more broadly—and have suggested greater community involvement in processes that shape research and intervention approaches, for example, through community-based participatory research (CBPR) partnerships among academic, health services, public health, and community-based organizations. Centers for Children’s Environmental Health and Disease Prevention Research (Children’s Centers) funded by the National Institute of Environmental Health Sciences and U.S. Environmental Protection Agency were required to include a CBPR project. The purpose of this article is to provide a definition and set of CBPR principles, to describe the rationale for and major benefits of using this approach, to draw on the experiences of six of the Children’s Centers in using CBPR, and to provide lessons learned and recommendations for how to successfully establish and maintain CBPR partnerships aimed at enhancing our understanding and addressing the multiple determinants of children’s health

European HYdropedological Data Inventory (EU-HYDI)

There is a common need for reliable hydropedological information in Europe. In the last decades research institutes, universities and government agencies have developed local, regional and national datasets containing soil physical, chemical, hydrological and taxonomic information often combined with land use and landform data. A hydrological database for western European soils was also created in the mid-1990s. However, a comprehensive European hydropedological database, with possible additional information on chemical parameters and land use is still missing. A comprehensive joint European hydropedological inventory can serve multiple purposes, including scientific research, modelling and application of models on different geographical scales. The objective of the joint effort of the participants is to establish the European Hydropedological Data Inventory (EU-HYDI). This database holds data from European soils focusing on soil physical, chemical and hydrological properties. It also contains information on geographical location, soil classification and land use/cover at the time of sampling. It was assembled with the aim of encompassing the soil variability in Europe. It contains data from 18 countries with contributions from 29 institutions. This report presents an overview of the database, details the individual contributed datasets and explains the quality assurance and harmonization process that lead to the final database

X-ray spectra of XMM-Newton serendipitous medium flux sources

We report on the results of a detailed analysis of the X-ray spectral properties of a large sample of sources detected serendipitously with the XMM-Newton observatory in 25 selected fields. The survey covers a total solid angle of ~3.5 deg2 and contains 1137 sources with ~10E-15 < S0.5-10 < 10E-12 erg cm-2 s-1. We find evidence for hardening of the average X-ray spectra of the sources towards fainter fluxes. We interpret this as indicating a higher degree of photoelectric absorption amongst the fainter population. Absorption is detected at 95% confidence in 20% of the sources, but it could certainly be present in many other sources below our detection capabilities. For Broad Line AGNs (BLAGNs), we detect absorption in ~10% of the sources with column densities in the range 10E21 - 10E22 cm-2. The fraction of absorbed Narrow Emission Line galaxies (NELGs, most with intrinsic X-ray luminosities >10E43 erg s-1, and therefore classified as type 2 AGNs) is significantly higher (40%), with a hint of moderately higher columns. We do not find evidence for a redshift evolution of the underlying power law index of BLAGNs, which stays roughly constant at Gamma ~1.9, with intrinsic dispersion of 0.4. A small fraction (~7%) of BLAGNs and NELGs require the presence of a soft excess, that we model as a black body with temperature ranging from 0.1 to 0.3 keV. Comparing our results on absorption to popular X-ray background synthesis models, we find absorption in only ~40% of the sources expected. This is due to a deficiency of heavily absorbed sources (with NH ~10E22 - 10E24 cm-2) in our sample in comparison with the models. We therefore conclude that the synthesis models require some revision in their specific parameters.Comment: 20 pages, 30 Postscript figures, A&A in pres