The matrix Kadomtsev--Petviashvili equation as a source of integrable nonlinear equations

A new integrable class of Davey--Stewartson type systems of nonlinear partial differential equations (NPDEs) in 2+1 dimensions is derived from the matrix Kadomtsev--Petviashvili equation by means of an asymptotically exact nonlinear reduction method based on Fourier expansion and spatio-temporal rescaling. The integrability by the inverse scattering method is explicitly demonstrated, by applying the reduction technique also to the Lax pair of the starting matrix equation and thereby obtaining the Lax pair for the new class of systems of equations. The characteristics of the reduction method suggest that the new systems are likely to be of applicative relevance. A reduction to a system of two interacting complex fields is briefly described.Comment: arxiv version is already officia

Improving P2P streaming in Wireless Community Networks

Wireless Community Networks (WCNs) are bottom-up broadband networks empowering people with their on-line communication means. Too often, however, services tailored for their characteristics are missing, with the consequence that they have worse performance than what they could. We present here an adaptation of an Open Source P2P live streaming platform that works efficiently, and with good application-level quality, over WCNs. WCNs links are normally symmetric (unlike standard ADSL access), and a WCN topology is local and normally flat (contrary to the global Internet), so that the P2P overlay used for video distribution can be adapted to the underlaying network characteristics. We exploit this observation to derive overlay building strategies that make use of cross-layer information to reduce the impact of the P2P streaming on the WCN while maintaining good application performance. We experiment with a real application in real WCN nodes, both in the Community-Lab provided by the CONFINE EU Project and within an emulation framework based on Mininet, where we can build larger topologies and interact more efficiently with the mesh underlay, which is unfortunately not accessible in Community-Lab. The results show that, with the overlay building strategies proposed, the P2P streaming applications can reduce the load on the WCN to about one half, also equalizing the load on links. At the same time the delivery rate and delay of video chunks are practically unaffected. (C) 2015 Elsevier B.V. All rights reserved

WIP: Analysis of feasible topologies for backhaul mesh networks

Mesh backhauls are getting attention for 5G networks, but not only. A backhaul mesh is attractive due to its multiple potential paths that grants redundancy and robustness. The real topology and its properties, however, is heavily influenced by the characteristics of the place where it is deployed, a fact that is rarely taken into account by scientific literature, mainly due to the lack of detailed topographic data. This WIP analyzes the impact of true topography on small backhaul meshes in nine different locations in Italy. Initial results stress how true data influence results and can help designing better networks and better services

Infective flooding in low-duty-cycle networks, properties and bounds

Flooding information is an important function in many networking applications. In some networks, as wireless sensor networks or some ad-hoc networks it is so essential as to dominate the performance of the entire system. Exploiting some recent results based on the distributed computation of the eigenvector centrality of nodes in the network graph and classical dynamic diffusion models on graphs, this paper derives a novel theoretical framework for efficient resource allocation to flood information in mesh networks with low duty-cycling without the need to build a distribution tree or any other distribution overlay. Furthermore, the method requires only local computations based on each node neighborhood. The model provides lower and upper stochastic bounds on the flooding delay averages on all possible sources with high probability. We show that the lower bound is very close to the theoretical optimum. A simulation-based implementation allows the study of specific topologies and graph models as well as scheduling heuristics and packet losses. Simulation experiments show that simple protocols based on our resource allocation strategy can easily achieve results that are very close to the theoretical minimum obtained building optimized overlays on the network

Keep it fresh: Reducing the age of information in V2X networks

The freshness of information is of the utmost importance in many contexts, including V2X networks and applications. One measure of this metric is the Age of Information (AoI), a notion recently introduced and explored by several authors, often with specific reference to vehicular networks. With this work, we explore the possibility of reducing the AoI of multi-hop information flooding in V2X networks exploiting the properties of the Eigenvector Centrality (EvC) of nodes in the topology, and the possibility that each node computes it exploiting only local information and very easy computations, so that each node can autonomously adapt its own networking parameters to redistribute information more efficiently. Starting from theoretical bounds and results, we explore how they hold in urban-constrained topologies and compare the AoI achieved exploiting EvC with the AoI achievable without this optimization of the nodes' behavior. Simulation results show a meaningful improvement without using additional resources and without the need of any global coordination

Validation of a bioanalytical method for the determination of synthetic and natural cannabinoids (New psychoactive substances) in oral fluid samples by means of hplc-ms/ms

New psychoactive substances (NPS) represent an important focus nowadays and are continually produced with minimal structural modifications in order to circumvent the law and increase the difficulty of identifying them. Moreover, since there are a high number of different compounds, it is arduous to develop analytical screening and/or confirmation methods that allow the identification and quantification of these compounds. The aim of this work is to develop and validate a bioanalytical method for detecting new synthetic drugs in biological samples, specifically oral fluid, using high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS/MS) with minimal sample pretreatment. Oral fluid samples were simply centrifuged and denaturized with different rapid procedures before injection into the LC-MS/MS system. Calibration curves covered a linear concentration range from LOQ to 100 ng/mL. Validation parameters such as linearity, precision, accuracy, selectivity, matrix effect and thermal stability were evaluated and showed satisfactory results, in accordance with US Food & Drug Administration guidelines. The inter-day analytical bias and imprecision at two levels of quality control (QC) were within ±15% for most compounds. This method was able to identify and calculate the concentration of 10 NPS validated in this biological sample, even in the presence of matrix effect

Exact Distributed Load Centrality Computation: Algorithms, Convergence, and Applications to Distance Vector Routing

Many optimization techniques for networking protocols take advantage of topological information to improve performance. Often, the topological information at the core of these techniques is a centrality metric such as the Betweenness Centrality (BC) index. BC is, in fact, a centrality metric with many well-known successful applications documented in the literature, from resource allocation to routing. To compute BC, however, each node must run a centralized algorithm and needs to have the global topological knowledge; such requirements limit the feasibility of optimization procedures based on BC. To overcome restrictions of this kind, we present a novel distributed algorithm that requires only local information to compute an alternative similar metric, called Load Centrality (LC). We present the new algorithm together with a proof of its convergence and the analysis of its time complexity. The proposed algorithm is general enough to be integrated with any distance vector (DV) routing protocol. In support of this claim, we provide an implementation on top of Babel, a real-world DV protocol. We use this implementation in an emulation framework to show how LC can be exploited to reduce Babel's convergence time upon node failure, without increasing control overhead. As a key step towards the adoption of centrality-based optimization for routing, we study how the algorithm can be incrementally introduced in a network running a DV routing protocol. We show that even when only a small fraction of nodes participate in the protocol, the algorithm accurately ranks nodes according to their centrality

Classical Lie symmetries and reductions of a nonisospectral Lax pair

The classical Lie method is applied to a nonisospectral problem associated with a system of partial differential equations in 2+1 dimensions (Maccari A, J. Math. Phys. 39, (1998), 6547-6551). Identification of the classical Lie symmetries provides a set of reductions that give rise to different nontrivial spectral problems in 1+1 dimensions. The form in which the spectral parameter of the 1+1 Lax pair is introduced is carefully described.Comment: 11 pages (v2: A typo corrected in the authors' names

The Role of Meningioma-1 (Mn1) Gene as Marker for Prognosis and Minimal Residual Disease Monitoring in Acute Myeloid Leukemia: A Concise Review

Molecular markers are necessary for prognostic stratification and monitoring of Minimal Residual Disease (MRD) in Acute Myeloid Leukemia (AML) [1,2]. Cytogenetic aberrations have long been recognized as the most important prognostic variable in AML, and are still the major determinant for post-remission therapy [3]. Unfortunately, only 50-60% of AML patients present an abnormal karyotype at diagnosis, while the remaining cases display a Normal Karyotype (NK). NK AML patients are generally included in an “intermediate risk” prognostic group, that is however characterized by a heterogeneous clinical course. To stratify prognosis of NK AML patients, numerous studies have led, in the last decade, to the introduction of different molecular markers such as FLT3, NPM1, BAALC and CEBPA [4-7]. Still, their use to monitor disease, either defining remission status and detecting relapse as early as possible, is still somehow controversial, due to fluctuations during disease course, low incidence rates in AML and sensitivity of the technologies detecting the single marker [8-10]. These limitations have, to date, precluded a timely and precise quantification of disease in NK AML patients, thus preventing from a complete individualization of post-remission therapy and early treatment in case of impending relapse. In other words, in NK AML it has not been reached the precision achieved in BCR/ABL-positive chronic myeloid leukemia and PML/RAR alpha mutated acute promyelocytic leukemia