Deterministic Digital Clustering of Wireless Ad Hoc Networks

We consider deterministic distributed communication in wireless ad hoc networks of identical weak devices under the SINR model without predefined infrastructure. Most algorithmic results in this model rely on various additional features or capabilities, e.g., randomization, access to geographic coordinates, power control, carrier sensing with various precision of measurements, and/or interference cancellation. We study a pure scenario, when no such properties are available. As a general tool, we develop a deterministic distributed clustering algorithm. Our solution relies on a new type of combinatorial structures (selectors), which might be of independent interest. Using the clustering, we develop a deterministic distributed local broadcast algorithm accomplishing this task in $O(\Delta \log^*N \log N)$ rounds, where $\Delta$ is the density of the network. To the best of our knowledge, this is the first solution in pure scenario which is only polylog$(n)$ away from the universal lower bound $\Omega(\Delta)$, valid also for scenarios with randomization and other features. Therefore, none of these features substantially helps in performing the local broadcast task. Using clustering, we also build a deterministic global broadcast algorithm that terminates within $O(D(\Delta + \log^* N) \log N)$ rounds, where $D$ is the diameter of the network. This result is complemented by a lower bound $\Omega(D \Delta^{1-1/\alpha})$, where $\alpha > 2$ is the path-loss parameter of the environment. This lower bound shows that randomization or knowledge of own location substantially help (by a factor polynomial in $\Delta$) in the global broadcast. Therefore, unlike in the case of local broadcast, some additional model features may help in global broadcast

POINT CLOUD EXPLOITATION FOR STRUCTURAL MODELING AND ANALYSIS: A RELIABLE WORKFLOW

none4noThe digitization and geometric knowledge of the historical built heritage is currently based on point cloud, that rarely or only partially is used as digital twin for structural analysis. The present work deals with historical artefacts survey, with particular reference to masonry structures, aimed to their structural analysis and assessment. In detail, the study proposes a methodology capable of employing semi-directly the original data obtained from the 3D digital survey for the generation of a Finite Element Model (FEM), used for structural analysis of masonry buildings. The methodology described presents a reliable workflow with twofold purpose: the improvement of the transformation process of the point cloud in solid and subsequently obtain a high-quality and detailed model for structural analyses. Through the application of the methodology to a case study, the method consistency was assessed, regarding the smoothness of the whole procedure and the dynamic characterization of the Finite Element Model. The main improvement in respect with similar or our previous workflows is obtained by the introduction of the retopology in data processing, allowing the transformation of the raw data into a solid model with optimal balancing between Level of Detail (LOD) and computational weight. Another significant aspect of the optimized process is undoubtedly the possibility of faithfully respecting the semantics of the structure, leading to the discretization of the model into different parts depending on the materials. This work may represent an excellent reference for the study of masonry artefacts belonging to the existing historical heritage, starting from surveys and with the purpose to structural and seismic evaluations, in the general framework of knowledge-based preservation of heritage.openLucidi, A.; Giordano, E.; Clementi, F.; Quattrini, R.Lucidi, A.; Giordano, E.; Clementi, F.; Quattrini, R

Finding a Bounded-Degree Expander Inside a Dense One

It follows from the Marcus-Spielman-Srivastava proof of the Kadison-Singer conjecture that if $G=(V,E)$ is a $\Delta$-regular dense expander then there is an edge-induced subgraph $H=(V,E_H)$ of $G$ of constant maximum degree which is also an expander. As with other consequences of the MSS theorem, it is not clear how one would explicitly construct such a subgraph. We show that such a subgraph (although with quantitatively weaker expansion and near-regularity properties than those predicted by MSS) can be constructed with high probability in linear time, via a simple algorithm. Our algorithm allows a distributed implementation that runs in $\mathcal O(\log n)$ rounds and does \bigO(n) total work with high probability. The analysis of the algorithm is complicated by the complex dependencies that arise between edges and between choices made in different rounds. We sidestep these difficulties by following the combinatorial approach of counting the number of possible random choices of the algorithm which lead to failure. We do so by a compression argument showing that such random choices can be encoded with a non-trivial compression. Our algorithm bears some similarity to the way agents construct a communication graph in a peer-to-peer network, and, in the bipartite case, to the way agents select servers in blockchain protocols

Naringenin is a powerful inhibitor of SARS-CoV-2 infection in vitro

Recently, an interesting review appeared in Pharmacological Research presented a list of candidate drugs against SARS-CoV-2 and COVID-19 [1]. In the present insight, we highlight novel experimental evidence that the flavanone Naringenin, targeting the endo-lysosomal Two-Pore Channels (TPCs), could be added to the list of potential weapons against SARS-CoV-2 infection and COVID-19 disease

Consensus Needs Broadcast in Noiseless Models but can be Exponentially Easier in the Presence of Noise

Consensus and Broadcast are two fundamental problems in distributed computing, whose solutions have several applications. Intuitively, Consensus should be no harder than Broadcast, and this can be rigorously established in several models. Can Consensus be easier than Broadcast? In models that allow noiseless communication, we prove a reduction of (a suitable variant of) Broadcast to binary Consensus, that preserves the communication model and all complexity parameters such as randomness, number of rounds, communication per round, etc., while there is a loss in the success probability of the protocol. Using this reduction, we get, among other applications, the first logarithmic lower bound on the number of rounds needed to achieve Consensus in the uniform GOSSIP model on the complete graph. The lower bound is tight and, in this model, Consensus and Broadcast are equivalent. We then turn to distributed models with noisy communication channels that have been studied in the context of some bio-inspired systems. In such models, only one noisy bit is exchanged when a communication channel is established between two nodes, and so one cannot easily simulate a noiseless protocol by using error-correcting codes. An $\Omega(\epsilon^{-2} n)$ lower bound on the number of rounds needed for Broadcast is proved by Boczkowski et al. [PLOS Comp. Bio. 2018] in one such model (noisy uniform PULL, where $\epsilon$ is a parameter that measures the amount of noise). In such model, we prove a new $\Theta(\epsilon^{-2} n \log n)$ bound for Broadcast and a $\Theta(\epsilon^{-2} \log n)$ bound for binary Consensus, thus establishing an exponential gap between the number of rounds necessary for Consensus versus Broadcast

Kappa-deformed random-matrix theory based on Kaniadakis statistics

We present a possible extension of the random-matrix theory, which is widely used to describe spectral fluctuations of chaotic systems. By considering the Kaniadakis non-Gaussian statistics, characterized by the index {\kappa} (Boltzmann-Gibbs entropy is recovered in the limit {\kappa}\rightarrow0), we propose the non-Gaussian deformations ({\kappa} \neq 0) of the conventional orthogonal and unitary ensembles of random matrices. The joint eigenvalue distributions for the {\kappa}-deformed ensembles are derived by applying the principle maximum entropy to Kaniadakis entropy. The resulting distribution functions are base invarient as they depend on the matrix elements in a trace form. Using these expressions, we introduce a new generalized form of the Wigner surmise valid for nearly-chaotic mixed systems, where a basis-independent description is still expected to hold. We motivate the necessity of such generalization by the need to describe the transition of the spacing distribution from chaos to order, at least in the initial stage. We show several examples about the use of the generalized Wigner surmise to the analysis of the results of a number of previous experiments and numerical experiments. Our results suggest the entropic index {\kappa} as a measure for deviation from the state of chaos. We also introduce a {\kappa}-deformed Porter-Thomas distribution of transition intensities, which fits the experimental data for mixed systems better than the commonly-used gamma-distribution.Comment: 18 pages, 8 figure

Inequality, mobility and the financial accumulation process: A computational economic analysis

Our computational economic analysis investigates the relationship between inequality, mobility and the financial accumulation process. Extending the baseline model by Levy et al., we characterise the economic process trough stylised return structures generating alternative evolutions of income and wealth through historical time. First we explore the limited heuristic contribution of one and two factors models comprising one single stock (capital wealth) and one single flow factor (labour) as pure drivers of income and wealth generation and allocation over time. Then we introduce heuristic modes of taxation in line with the baseline approach. Our computational economic analysis corroborates that the financial accumulation process featuring compound returns plays a significant role as source of inequality, while institutional configurations including taxation play a significant role in framing and shaping the aggregate economic process that evolves over socioeconomic space and time

Molecular-orbital theory for the stopping power of atoms in the low velocity regime:the case of helium in alkali metals

A free-parameter linear-combination-of-atomic-orbitals approach is presented for analyzing the stopping power of slow ions moving in a metal. The method is applied to the case of He moving in alkali metals. Mean stopping powers for He present a good agreement with local-density-approximation calculations. Our results show important variations in the stopping power of channeled atoms with respect to their mean values.Comment: LATEX, 3 PostScript Figures attached. Total size 0.54

Structural and Electronic Properties of Small Neutral (MgO)n Clusters

Ab initio Perturbed Ion (PI) calculations are reported for neutral stoichiometric (MgO)n clusters (n<14). An extensive number of isomer structures was identified and studied. For the isomers of (MgO)n (n<8) clusters, a full geometrical relaxation was considered. Correlation corrections were included for all cluster sizes using the Coulomb-Hartree-Fock (CHF) model proposed by Clementi. The results obtained compare favorably to the experimental data and other previous theoretical studies. Inclusion of correlaiotn is crucial in order to achieve a good description of these systems. We find an important number of new isomers which allows us to interpret the experimental magic numbers without the assumption of structures based on (MgO)3 subunits. Finally, as an electronic property, the variations in the cluster ionization potential with the cluster size were studied and related to the structural isomer properties.Comment: 24 pages, LaTeX, 7 figures in GIF format. Accepted for publication in Phys. Rev.