5,137 research outputs found
Offloading through Opportunistic Networks with Dynamic Content Requests
No full textOffloading is gaining momentum as a technique to overcome the cellular capacity crunch due to the surge of mobile data traffic demand. Multiple offloading techniques are currently under investigation, from modifications inside the cellular network architecture, to integration of multiple wireless broadband infrastructures, to exploiting direct communications between mobile devices. In this paper we focus on the latter type of offloading, and specifically on offloading through opportunistic networks. As opposed to most of the literature looking at this type of offloading, in this paper we consider the case where requests for content are non-synchronised, i.e. users request content at random points in time. We support this scenario through a very simple offloading scheme, whereby no epidemic dissemination occurs in the opportunistic network. Thus our scheme is minimally invasive for users’ mobile devices, as it uses only minimally their
resources. Then, we provide an analysis on the efficiency of our offloading mechanism (in terms of percentage of offloaded traffic) in representative vehicular settings, where content needs to be delivered to (subsets of the) users in specific geographical areas.
Depending on various parameters, we show that a simple and resource-savvy offloading scheme can nevertheless offload a very large fraction of the traffic (up to more than 90%, and always
more than 20%). We also highlight configurations where such a technique is less effective, and therefore a more aggressive use of mobile nodes resources would be needed
Robust Adaptive Modulation and Coding (AMC) Selection in LTE Systems using Reinforcement Learning
No full textAdaptive Modulation and Coding (AMC) in LTE networks is commonly employed to improve system throughput by ensuring more reliable transmissions. Most of existing AMC methods select the modulation and coding scheme (MCS) using
pre-computed mappings between MCS indexes and channel quality indicator (CQI) feedbacks that are periodically sent by the receivers. However, the effectiveness of this approach heavily depends on the assumed channel model. In addition CQI feedback delays may cause throughput losses. In this paper
we design a new AMC scheme that exploits a reinforcement learning algorithm to adjust at run-time the MCS selection rules based on the knowledge of the effect of previous AMC decisions.
The salient features of our proposed solution are: i) the lowdimensional
space that the learner has to explore, and ii) the use of direct link throughput measurements to guide the decision process. Simulation results obtained using ns3 demonstrate the robustness of our AMC scheme that is capable of discovering the best MCS even if the CQI feedback provides a poor prediction of the channel performance
Analysis of MAC-level throughput in LTE systems with link rate adaptation and HARQ protocols
No full textLTE is rapidly gaining momentum for building future 4G cellular systems, and real operational networks are under deployment worldwide. To achieve high throughput performance, in addition to an advanced physical layer design LTE exploits a combination of sophisticated mechanisms at the radio resource management layer. Clearly, this makes difficult to develop analytical tools to accurately assess and optimise the user perceived throughput under realistic channel assumptions. Thus, most existing studies focus only on link-layer throughput or consider individual mechanisms in isolation. The main contribution of this paper is a unified modelling framework of the MAC-level downlink throughput of a sigle LTE cell, which caters for wideband CQI feedback schemes, AMC and HARQ protocols as defined in the LTE standard. We have validated the accuracy of the proposed model through detailed LTE simulations carried out with the ns-3 simulator extended with the LENA module for LTE
Facing antibiotic resistance
No full textThe cell wall of most Gram-negative and Gram-positive bacteria is composed of peptidoglycan (PG), a mesh-like structure of repeating glycan chains cross-linked by small peptides. Peptidoglycan is essential for growth, division and viability of the microorganism. Any disruption of its biosynthesis results in bacterial cell lysis or cessation of growth, making it a major target for antibiotics.
It was suggested that many proteins involved in PG synthesis, from the cytoplasmic enzymes that synthesize the precursor Lipid II to the extracellular enzymes that are responsible for its polymerization, function in vivo as part of a multi- protein complex “machinery”. In particular, recent evidence suggests that the core of the PG biosynthetic complex consists of the class B penicillin binding proteins (PBPs) such as PBP2 and PBP3 that work together with membrane inserted shape, elongation, division and sporulation (SEDs) proteins, FtsW and RodA, respectively. These synthetic machines provide for cell division (FtsW-PBP3) and cell elongation (RodA-PBP2) and are also the key targets of most clinically used ß-lactam compounds.
Though structures of both RodA (a SEDS protein involved in bacterial growth and elongation) and type b PBPs are available, the interaction between these proteins and their joint enzymatic activity is poorly characterized.
Here, the preliminary structural characterization of a RodA-PBP2 protein complex by single-particle cryogenic electron microscopy (cryo-EM) is presented, aiming at a better understanding of these incredibly important enzymes that could enlighten the future of antibiotics research and development.The spread of multidrug resistance (MDR) Gram-negative bacterial pathogens and the paucity of new drugs prompted the medical community to re-use the old polymyxin antibiotic colistin.
Unfortunately, reintroduction of colistin in clinical practice led inevitably to the emergence of colistin-resistant isolates (Jeannot, K. et al. 2017), such as P. aeruginosa.
Gram-negative bacteria acquire colistin resistance mostly through mutations of genes responsible for remodeling of the lipopolysaccharide (LPS), primarily via the enzymatic addition of 4-amino-4-deoxy-L-arabinose (L-Ara4N) to lipid A by the aminoarabinose transferase ArnT. The resulting positive charge reduces LPS affinity for colistin, leading to resistance (Olaitan, A.O. et al., 2014; Baron, S. et al., 2016). Accordingly, the pharmacological inhibition of L-Ara4N biosynthetic pathway could represent a suitable approach to extend the clinical lifetime of colistin for the treatment of P. aeruginosa infections.
Here, in the attempt to identify potential inhibitors of L-Ara4N-dependent colistin resistance, a docking-based virtual screening of a unique in house library of natural products was carried out within the catalytic site of ArnT (Petrou, V.I. et al., 2016). This led to the identification of a natural diterpene (14) able to potentiate colistin activity against colistin-resistant P. aeruginosa isolates.
A series of semi-synthetic analogs were further synthesized and tested in vitro aiming at outlining the structure-activity relationship (SARs) and improving their activity. Currently, all these compounds are covered by Italian patent
NMR spectroscopy: a versatile tool for the investigation of organic reaction mechanisms and metabolomics analyses
No full textOlefin metathesis has become a powerful tool for the formation of carbon-carbon bonds and, therefore, for the synthesis of a number of molecules. This progress was recognized in 2005 with the award of NOBEL Prize in Chemistry to Yves Chauvin, Robert Grubbs and Richard Schrock for their work in this area. While the series of [2+2]cycloadditions and retro[2+2]cycloadditions that make up the pathways of ruthenium-catalysed metathesis reactions is wellestablished, the exploration of mechanistic aspects of alkene metathesis is going on. At first, we reported the tetramerization of (E)-2,4-dimethoxycinnamic acid ω-undecenyl ester with ethereal BF3. The reaction gave three stereoisomers 1a, 1b, and 1c, which were assigned as the chair, cone, and 1,2-alternate conformations, respectively. Undecenyl resorc[4]arene 1a, which featured the simplest pattern of substituent, was submitted to olefin metathesis using the second generation Grubbs complex as the catalyst. Depending on the reaction conditions, different products were isolated: a bicyclic alkene 2a, a linear dimer 3a, and a cross-linked homopolymer P1a. Moreover, we detected for the first time the formation of a ruthenium-carbene resorc[4]arene complex during the metathesis reaction of resorc[4]arene olefin 2a with the first generation Grubbs catalyst in CDCl3. We developed an NMR analytical protocol which proved capable of yielding both qualitative and quantitative information. In the first case, we were able to identify the complex 3a[Ru] as a key intermediate in the ROM-CM sequence of reactions, giving us a definitive proof of the previously hypothesized mechanism. As a further feedback of the pathway, we performed a quantitative analysis using benzene in the place of CDCl3, due to the poor stability of the catalyst in such a solvent. The reaction allowed the isolation of decomposition products of the ruthenium-carbene-resorc[4]arene complex 2a[Ru] such as compound 4a, which, due to the presence of still reactive alkene functions, proved to behave as propagating alkylidene species leading to further decomposition products.Metabolomics provides a direct measure of the state of the cell or biological system, where changes in the metabolome capture how the system responds to environmental or genetic stress. Specifically, a drug or an active chemical lead would be expected to perturb the
metabolome of a cell or tissue upon treatment. The two leading analytical approaches to metabolomics are mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. In particular, NMR technique accounts for high reproducibility, quantitative determination of a wide dynamic range, and the capability to determine the structure of unknown metabolites. Cells of high-grade tumors, including medulloblastoma (MB) and glioblastoma (GBM), must similarly balance energy metabolism with the need to synthesize the macromolecules essential for tumor growth. Cells with large ATP requirements are likely to be disadvantaged by aerobic glycolysis because glycolysis generates less ATP per molecule of glucose than oxidative phosphorylation. Proliferating cells, however, may use aerobic glycolysis to satisfy the competing needs for both energy generation and the accumulation of biomass. Recently, it has been demonstrated that Sonic Hedgehog (SHH) pathway activation in granule cell progenitors (GCPs), responsible of MB development, induces transcription of hexokinase 2 (HK2) and pyruvate kinase M2 (PKM2), two key gatekeepers of glycolysis. The process is mediated by the canonical activation of the GLI transcription factors and causes a robust increase of extracellular lactate concentration.
Glabrescione B (GlaB), an isoflavone naturally found in the seeds of Derris glabrescens (Leguminosae), turned out to be an efficient inhibitor of the growth of HH/GLI-dependent tumors and cancer stem cells in vitro and in vivo. Here, we reported the GlaB activity on
both human MB DAOY and murine glioma GL261 cell models in vitro and in vivo. In order to evaluate how the GlaB-treatment affects cell metabolism as a consequence of GLI1 inhibition, untargeted NMR metabolomics analyses of cellular lysates and conditioned media were performed in both cell lines. For this purpose, a simple, fast, and reproducible sample preparation protocol was developed. To reduce bias in the interpretation of the experiments, it was decided to produce from five to seven biological replicates for each treated and untreated group. The 1D 1H NMR spectra were acquired to determine the metabolic fingerprints of the treated and untreated cancer cells. Notably, the NMR metabolomics approach revealed a typical endo-metabolic phenotype of the cells under investigation. Both the exo- and endo-metabolome of the DAOY and GL261 cell lines resulted to be completely changed after 24 h and 48 h of GlaB administration, respectively. The levels of most metabolites decreased after treatment, consistently with possible apoptosis phenomenon
Introducing “La fabrique du droit”. A Conversation with Bruno Latour
No full textBruno Latour talks with Paolo Landri about his book on the Conseil d'Etat (La Fabrique du droit). The conversation was held in 2006 at the time of the Italian translation of the book and illustrates the research project and the difficulties the author had in the field. At the same time, it clarifies the trajectories of Bruno Latour's work and theoretical framework of his program of study with respect to sociology, anthropology, and philosophy of law. The conversation helps to understand the open-ended character of Bruno Latour's research and reflection including STS as well as sociological, anthropological and philosophical themes
Metrological Aspects in Approximate Computing: Fourier Transform in Polluted Water Spectroscopy
No full textEnvironmental measurements need high accuracy and precision for delivering results necessary for authorities for making decisions. In particular, for water characterization, it is necessary to perform fast analysis in order to delivery immediate results, especially in online conditions. To do that, in some circumstances it is compulsory to accept deliberate low accuracy and precision as compromise for quick results. Approximate computing could be an innovating approach on the proviso that results should be realistic. This research illustrates findings regarding application of approximate computing in the field of spectroscopy measurements related to water characterization using an experimental instrumentation based on interferometry and spectroscopy
Retrospective analysis: A validation procedure for the redesign of an environmental monitoring network
No full textMonitoring networks are essential tools for the effective management of vulnerable or limited environmental
resources. Cost and logistics constraints often suggest to reduce the number of monitoring sites while minimizing
the loss of information determined by these changes. The problem can be rigorously addressed through the
optimization of one or more objective functions that represent the managerial goals associated to the network.
However, the use of objective functions is based on assumptions that in practical cases can be inaccurate. To
overcome this problem, we have developed a retrospective analysis procedure that validates the degree of acceptability
of the optimal reduced configuration at a local and global level. The procedure has been applied to a
case study in Apulia, Italy, finding that the optimal reduced network was unable to recover the measured values
of the monitored parameter of two discarded locations, making it unable to accomplish its monitoring goals
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