Profiling Power Consumption on Mobile Devices

The proliferation of mobile devices, and the migration of the information access paradigm to mobile platforms, motivate studies of power consumption behaviors with the purpose of increasing the device battery life. The aim of this work is to profile the power consumption of a Samsung Galaxy I7500 and a Samsung Nexus S, in order to understand how such feature has evolved over the years. We performed two experiments: the first one measures consumption for a set of usage scenarios, which represent common daily user activities, while the second one analyzes a context-aware application with a known source code. The first experiment shows that the most recent device in terms of OS and hardware components shows significantly lower consumption than the least recent one. The second experiment shows that the impact of different configurations of the same application causes a different power consumption behavior on both smartphones. Our results show that hardware improvements and energy-aware software applications greatly impact the energy efficiency of mobile device

How alternative food networks work in a metropolitan area? An analysis of Solidarity Purchase Groups in Northern Italy

Our paper focuses on Solidarity Purchase Group (SPG) participants located in a highly urbanized area, with the aim to investigate the main motivations underlining their participation in a SPG and provide a characterization of them. To this end, we carried out a survey of 795 participants involved in 125 SPGs in the metropolitan area of Milan (Italy). Taking advantage of a questionnaire with 39 questions, we run a factor analysis and a two-step cluster analysis to identify different profiles of SPG participants. Our results show that the system of values animating metropolitan SPG practitioners does not fully conform to that traditionally attributed to an alternative food network (AFN). In fact, considerations linked to food safety and healthiness prevail on altruistic motives such as environmental sustainability and solidarity toward small producers. Furthermore, metropolitan SPGs do not consider particularly desirable periurban and local food products. Observing the SPGs from this perspective, it emerges as such initiatives can flourish also in those places where the lack of connection with the surrounding territory is counterbalanced by the high motivation to buy products from trusted suppliers who are able to guarantee genuine and safe products, not necessarily located nearby

Quantum statistics and Altarelli-Parisi evolution equations

The phenomenological evidence of quantum statistical effects in parton physics is here briefly summarized, and the recent good results obtained by parameterizing the parton distributions in terms of Fermi-Dirac and Bose-Einstein statistical functions are discussed. In this framework we study the modification of the scaling behaviour of parton distributions due to quantum statistical effects. In particular, by following a well-known formal analogy which holds between the Altarelli-Parisi evolution equations, at leading-log approximation, and a set of Boltzmann equations, we suggest a generalization of evolution equations to take into account Pauli exclusion principle and gluon induced emission

A ricardian analysis of the impact of climate change on permanent crops in a mediterranean region

This is the first study which explores the impact of climate change in Sicily, a small Mediterranean region of Southern Europe. According to research, Mediterranean area has shown large climate shifts in the last century and it has been identified as one of the most prominent “Hot-Spots” in future climate change projections. Since agriculture is an economic activity which strongly depends on climate setting and is particularly responsive to climate changes, it is important to understand how such changes may affect agricultural profitability in the Mediterranean region. The aim of the present study is to assess the expected impact of climate change on permanent crops cultivated in Sicilian region (Southern Italy). By using data from Farm Accountancy Data Network and Ensembles climatic projections for 2021-2050 period, we showed that the impact of climate change is prominent in this region. However, crops respond to climatic variations in a different manner, highlighting that unlike the strong reduction in profitability of grapevine and citrus tree, the predicted average Net Revenue of olive tree is almost the same as in the reference period (1961-1990)

The ACM property for unions of lines in P1×P2

This paper examines the Arithmetically Cohen-Macaulay (ACM) property for certain codimension 2 varieties in P1×P2 called sets of lines in P1×P2 (not necessarily reduced). We discuss some obstacles to finding a general characterization. We then consider certain classes of such curves, and we address two questions. First, when are they themselves ACM? Second, in a non-ACM reduced configuration, is it possible to replace one component of a primary (prime) decomposition by a suitable power (i.e. to “fatten” one line) to make the resulting scheme ACM? Finally, for our classes of such curves, we characterize the locally Cohen-Macaulay property in combinatorial terms by introducing the definition of a fully v-connected configuration. We apply some of our results to give analogous ACM results for sets of lines in P3

Multiprojective spaces and the arithmetically Cohen-Macaulay property

In this paper we study the arithmetically Cohen-Macaulay (ACM) property for sets of points in multiprojective spaces. Most of what is known is for P1 × P1 and, more recently, in (P1)^r . In P1 × P1 the so called inclusion property characterises the ACM property. We extend the definition in any multiprojective space and we prove that the inclusion property implies the ACM property in P m × P n . In such an ambient space it is equivalent to the so-called (∗)-property. Moreover, we start an investigation of the ACM property in P1 × Pn . We give a new construction that highlights how different the behavior of the ACM property is in this setting

Resonant effects in a SQUID qubit subjected to non adiabatic changes

By quickly modifying the shape of the effective potential of a double SQUID flux qubit from a single-well to a double-well condition, we experimentally observe an anomalous behavior, namely an alternance of resonance peaks, in the probability to find the qubit in a given flux state. The occurrence of Landau-Zener transitions as well as resonant tunneling between degenerate levels in the two wells may be invoked to partially justify the experimental results. A quantum simulation of the time evolution of the system indeed suggests that the observed anomalous behavior can be imputable to quantum coherence effects. The interplay among all these mechanisms has a practical implication for quantum computing purposes, giving a direct measurement of the limits on the sweeping rates possible for a correct manipulation of the qubit state by means of fast flux pulses, avoiding transitions to non-computational states.Comment: 6 pages and 6 figures. The paper, as it is, has been accepted for publication on PRB on March 201

The Value of Organic plus. Analysing Consumers’ Preference for Additional Ethical Attributes of Organic food Products

Organic Plus attributes strengthen the sustainability of the organic products and differentiate them from the 'conventionalized' organic ones. Products with Organic Plus attributes seem appreciated by organic consumers. However, research on consumers' preference for Organic Plus is still scarce, leaving gaps in the understanding of the consumers' characteristics of organic products with Plus attributes. In order to enrich the knowledge of consumers' preference for organic products with Plus attributes, the present study aims to achieve three Objectives: (1) identifying which Plus attributes, among fair prices to local farmers, integration of people with disabilities and eco-friendliness, are most sought after among Italian consumers of organic products (2) measuring, through the willingness to pay elicitation techniques, the level of preference for the various plus attributes; (3) determine which psychological, socio-demographic and contextual factors influence the purchasing choice of organic consumers for the three Plus attributes. Better knowledge of consumers' preference for organic Plus attributes, as well as the psychological and socio-demographic characteristic can provide useful indications to better-tailored marketing strategies on specific consumers' profiles

NeuronAlg: An Innovative Neuronal Computational Model for Immunofluorescence Image Segmentation

Background: Image analysis applications in digital pathology include various methods for segmenting regions of interest. Their identification is one of the most complex steps and therefore of great interest for the study of robust methods that do not necessarily rely on a machine learning (ML) approach. Method: A fully automatic and optimized segmentation process for different datasets is a prerequisite for classifying and diagnosing indirect immunofluorescence (IIF) raw data. This study describes a deterministic computational neuroscience approach for identifying cells and nuclei. It is very different from the conventional neural network approaches but has an equivalent quantitative and qualitative performance, and it is also robust against adversative noise. The method is robust, based on formally correct functions, and does not suffer from having to be tuned on specific data sets. Results: This work demonstrates the robustness of the method against variability of parameters, such as image size, mode, and signal-to-noise ratio. We validated the method on three datasets (Neuroblastoma, NucleusSegData, and ISBI 2009 Dataset) using images annotated by independent medical doctors. Conclusions: The definition of deterministic and formally correct methods, from a functional and structural point of view, guarantees the achievement of optimized and functionally correct results. The excellent performance of our deterministic method (NeuronalAlg) in segmenting cells and nuclei from fluorescence images was measured with quantitative indicators and compared with those achieved by three published ML approaches