A cell outage management framework for dense heterogeneous networks

In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks with split control and data planes-a candidate architecture for meeting future capacity, quality-of-service, and energy efficiency demands. In such an architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, whereas the data BSs handle UE data. An implication of this split architecture is that an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large-scale minimization-of-drive-test report data and detects an outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly-detecting algorithms, i.e., k-nearest-neighbor- and local-outlier-factor-based anomaly detectors, within the control COD. On the other hand, for data cell COD, we propose a heuristic Grey-prediction-based approach, which can work with the small number of UE in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity and by receiving a periodic update of the received signal reference power statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of the residual error that is inherent to a Grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm that can be applied to both planes. Our COC solution utilizes an actor-critic-based reinforcement learning algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage and compensate for the detected outage in a reliable manner

Ametryn removal by Metarhizium brunneum: Biodegradation pathway proposal and metabolic background revealed

Ametryn is a representative of a class of s-triazine herbicides absorbed by plant roots and leaves and characterized as a photosynthesis inhibitor. It is still in use in some countries in the farming of pineapples, soybean, corn, cotton, sugar cane or bananas; however, due to the adverse effects of s-triazine herbicides on living organisms use of these pesticides in the European Union has been banned. In the current study, we characterized the biodegradation of ametryn (100 mg L-1) by entomopathogenic fungal cosmopolite Metarhizium brunneum. Ametryn significantly inhibited the growth and glucose uptake in fungal cultures. The concentration of the xenobiotic drops to 87.75 mg L-1 at the end of culturing and the biodegradation process leads to formation of four metabolites: 2-hydroxy atrazine, ethyl hydroxylated ametryn, S-demethylated ametryn and deethylametryn. Inhibited growth is reflected in the metabolomics data, where significant differences in concentrations of L-proline, gamma-aminobutyric acid, L-glutamine, 4-hydroxyproline, L-glutamic acid, ornithine and L-arginine were observed in the presence of the xenobiotic when compared to control cultures. The metabolomics data demonstrated that the presence of ametryn in the fungal culture induced oxidative stress and serious disruptions of the carbon and nitrogen metabolism. Our results provide deeper insights into the microorganism strategy for xenobiotic biodegradation which may result in future enhancements to ametryn removal by the tested strain.National Science Center, Poland (Project No. 2015/19/B/NZ9/00167

A rapid stability-indicating, fused-core HPLC method for simultaneous determination of β-artemether and lumefantrine in anti-malarial fixed dose combination products

Background: Artemisinin-based fixed dose combination (FDC) products are recommended by World Health Organization (WHO) as a first-line treatment. However, the current artemisinin FDC products, such as beta-artemether and lumefantrine, are inherently unstable and require controlled distribution and storage conditions, which are not always available in resource-limited settings. Moreover, quality control is hampered by lack of suitable analytical methods. Thus, there is a need for a rapid and simple, but stability-indicating method for the simultaneous assay of beta-artemether and lumefantrine FDC products. Methods: Three reversed-phase fused-core HPLC columns (Halo RP-Amide, Halo C18 and Halo Phenyl-hexyl), all thermostated at 30 degrees C, were evaluated. beta-artemether and lumefantrine (unstressed and stressed), and reference-related impurities were injected and chromatographic parameters were assessed. Optimal chromatographic parameters were obtained using Halo RP-Amide column and an isocratic mobile phase composed of acetonitrile and 1mM phosphate buffer pH 3.0 (52:48; V/V) at a flow of 1.0 ml/min and 3 mu l injection volume. Quantification was performed at 210 nm and 335 nm for beta-artemether and for lumefantrine, respectively. In-silico toxicological evaluation of the related impurities was made using Derek Nexus v2.0 (R). Results: Both beta-artemether and lumefantrine were separated from each other as well as from the specified and unspecified related impurities including degradants. A complete chromatographic run only took four minutes. Evaluation of the method, including a Plackett-Burman robustness verification within analytical QbD-principles, and real-life samples showed the method is suitable for quantitative assay purposes of both active pharmaceutical ingredients, with a mean recovery relative standard deviation (+/- RSD) of 99.7 % (+/- 0.7%) for beta-artemether and 99.7 % (+/- 0.6%) for lumefantrine. All identified beta-artemether-related impurities were predicted in Derek Nexus v2.0 (R) to have toxicity risks similar to beta-artemether active pharmaceutical ingredient (API) itself. Conclusions: A rapid, robust, precise and accurate stability-indicating, quantitative fused-core isocratic HPLC method was developed for simultaneous assay of beta-artemether and lumefantrine. This method can be applied in the routine regulatory quality control of FDC products. The in-silico toxicological investigation using Derek Nexus (R) indicated that the overall toxicity risk for beta-artemether-related impurities is comparable to that of beta-artemether API

Capturing the ‘ome’ : the expanding molecular toolbox for RNA and DNA library construction

All sequencing experiments and most functional genomics screens rely on the generation of libraries to comprehensively capture pools of targeted sequences. In the past decade especially, driven by the progress in the field of massively parallel sequencing, numerous studies have comprehensively assessed the impact of particular manipulations on library complexity and quality, and characterized the activities and specificities of several key enzymes used in library construction. Fortunately, careful protocol design and reagent choice can substantially mitigate many of these biases, and enable reliable representation of sequences in libraries. This review aims to guide the reader through the vast expanse of literature on the subject to promote informed library generation, independent of the application

DeSyRe: on-Demand System Reliability

The DeSyRe project builds on-demand adaptive and reliable Systems-on-Chips (SoCs). As fabrication technology scales down, chips are becoming less reliable, thereby incurring increased power and performance costs for fault tolerance. To make matters worse, power density is becoming a significant limiting factor in SoC design, in general. In the face of such changes in the technological landscape, current solutions for fault tolerance are expected to introduce excessive overheads in future systems. Moreover, attempting to design and manufacture a totally defect and fault-free system, would impact heavily, even prohibitively, the design, manufacturing, and testing costs, as well as the system performance and power consumption. In this context, DeSyRe delivers a new generation of systems that are reliable by design at well-balanced power, performance, and design costs. In our attempt to reduce the overheads of fault-tolerance, only a small fraction of the chip is built to be fault-free. This fault-free part is then employed to manage the remaining fault-prone resources of the SoC. The DeSyRe framework is applied to two medical systems with high safety requirements (measured using the IEC 61508 functional safety standard) and tight power and performance constraints

The rna-binding ubiquitin ligase mex3a affects glioblastoma tumorigenesis by inducing ubiquitylation and degradation of rig-i

Glioblastoma multiforme (GB) is the most malignant primary brain tumor in humans, with an overall survival of approximatively 15 months. The molecular heterogeneity of GB, as well as its rapid progression, invasiveness and the occurrence of drug-resistant cancer stem cells, limits the efficacy of the current treatments. In order to develop an innovative therapeutic strategy, it is mandatory to identify and characterize new molecular players responsible for the GB malignant phenotype. In this study, the RNA-binding ubiquitin ligase MEX3A was selected from a gene expression analysis performed on publicly available datasets, to assess its biological and still-unknown activity in GB tumorigenesis. We find that MEX3A is strongly up-regulated in GB specimens, and this correlates with very low protein levels of RIG-I, a tumor suppressor involved in differentiation, apoptosis and innate immune response. We demonstrate that MEX3A binds RIG-I and induces its ubiquitylation and proteasome-dependent degradation. Further, the genetic depletion of MEX3A leads to an increase of RIG-I protein levels and results in the suppression of GB cell growth. Our findings unveil a novel molecular mechanism involved in GB tumorigenesis and suggest MEX3A and RIG-I as promising therapeutic targets in GB