Representation growth of some torsion-free finitely generated 22-nilpotent groups

We devise a method for computing representation zeta functions of torsion-free finitely generated $2$-nilpotent groups whose associated Lie lattices have an extra smoothness condition. This method is used first to derive intrinsic formulae for the abscissa of convergence of such representation zeta functions; and secondly, as a practical application, to compute global, local and topological representation zeta functions of groups within an infinite family containing the Heisenberg group over rings of integers in number fields.Comment: 12 page

Rate-Distortion Classification for Self-Tuning IoT Networks

Many future wireless sensor networks and the Internet of Things are expected to follow a software defined paradigm, where protocol parameters and behaviors will be dynamically tuned as a function of the signal statistics. New protocols will be then injected as a software as certain events occur. For instance, new data compressors could be (re)programmed on-the-fly as the monitored signal type or its statistical properties change. We consider a lossy compression scenario, where the application tolerates some distortion of the gathered signal in return for improved energy efficiency. To reap the full benefits of this paradigm, we discuss an automatic sensor profiling approach where the signal class, and in particular the corresponding rate-distortion curve, is automatically assessed using machine learning tools (namely, support vector machines and neural networks). We show that this curve can be reliably estimated on-the-fly through the computation of a small number (from ten to twenty) of statistical features on time windows of a few hundreds samples

Circadian Rhythm Abnormalities in Parkinson's Disease from Humans to Flies and Back

Clinical and research studies have suggested a link between Parkinson\u2019s disease (PD) and alterations in the circadian clock. Drosophila melanogaster may represent a useful model to study the relationship between the circadian clock and PD. Apart from the conservation of many genes, cellular mechanisms, signaling pathways, and neuronal processes, Drosophila shows an organized central nervous system and well-characterized complex behavioral phenotypes. In fact, Drosophila has been successfully used in the dissection of the circadian system and as a model for neurodegenerative disorders, including PD. Here, we describe the fly circadian and dopaminergic systems and report recent studies which indicate the presence of circadian abnormalities in some fly PD genetic models. We discuss the use of Drosophila to investigate whether, in adults, the disruption of the circadian system might be causative of brain neurodegeneration. We also consider approaches using Drosophila, which might provide new information on the link between PD and the circadian clock. As a corollary, since PD develops its symptomatology over a large part of the organism\u2019s lifespan and given the relatively short lifespan of fruit flies, we suggest that genetic models of PD could be used to perform lifelong screens for drug-modulators of general and/or circadian-related PD traits

SolarStat: Modeling Photovoltaic Sources through Stochastic Markov Processes

In this paper, we present a methodology and a tool to derive simple but yet accurate stochastic Markov processes for the description of the energy scavenged by outdoor solar sources. In particular, we target photovoltaic panels with small form factors, as those exploited by embedded communication devices such as wireless sensor nodes or, concerning modern cellular system technology, by small-cells. Our models are especially useful for the theoretical investigation and the simulation of energetically self-sufficient communication systems including these devices. The Markov models that we derive in this paper are obtained from extensive solar radiation databases, that are widely available online. Basically, from hourly radiance patterns, we derive the corresponding amount of energy (current and voltage) that is accumulated over time, and we finally use it to represent the scavenged energy in terms of its relevant statistics. Toward this end, two clustering approaches for the raw radiance data are described and the resulting Markov models are compared against the empirical distributions. Our results indicate that Markov models with just two states provide a rough characterization of the real data traces. While these could be sufficiently accurate for certain applications, slightly increasing the number of states to, e.g., eight, allows the representation of the real energy inflow process with an excellent level of accuracy in terms of first and second order statistics. Our tool has been developed using Matlab(TM) and is available under the GPL license at[1].Comment: Submitted to IEEE EnergyCon 201

EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design

The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application

Geografia e a cartografia escolar no ensino básico: uma relação complexa – percursos e possibilidades

Esta pesquisa tem o intuito de diagnosticar possíveis deficiências dos alunos em relação à alfabetização cartográfica. Traz um olhar da construção do conhecimento escolar, através das contribuições da Epistemologia Genética e da Epistemologia da Complexidade. Discute o trabalho interdisciplinar entre a Geografia e a Cartografia. Tem como objetivo principal: estudar a construção do conhecimento cartográfico e as suas implicações na educação básica do componente curricular Geografia a partir das práticas existentes em escolas da rede pública e privada. É uma pesquisa qualitativa e apoia-se no Paradigma da Complexidade. Foram realizadas oficinas enquanto atividades investigativas