Swarm intelligence is a relatively novel field. It addresses the study of the collective behaviors of systems made by many components that coordinate using decentralized controls and ...self-organization. A large part of the research in swarm intelligence has focused on the reverse engineering and the adaptation of collective behaviors observed in natural systems with the aim of designing effective algorithms for distributed optimization. These algorithms, like their natural systems of inspiration, show the desirable properties of being adaptive, scalable, and robust. These are key properties in the context of network routing, and in particular of routing in wireless sensor networks. Therefore, in the last decade, a number of routing protocols for wireless sensor networks have been developed according to the principles of swarm intelligence, and, in particular, taking inspiration from the foraging behaviors of ant and bee colonies. In this paper, we provide an extensive survey of these protocols. We discuss the general principles of swarm intelligence and of its application to routing. We also introduce a novel taxonomy for routing protocols in wireless sensor networks and use it to classify the surveyed protocols. We conclude the paper with a critical analysis of the status of the field, pointing out a number of fundamental issues related to the (mis) use of scientific methodology and evaluation procedures, and we identify some future research directions.
The Orienteering Problem is a routing problem that commonly appears in mapping, transportation, distribution, and scheduling scenarios. The Orienteering Problem is a challenging NP-hard problem, such ...that obtaining optimal or near optimal solutions usually requires a significant amount of computation for large and even moderately large instances. As a result, existing algorithms cannot effectively be utilized for solving large Orienteering Problems in an online setting, which is often required in real-world applications where a plan has to be iteratively computed. For instance, a planner might need to adapt to changes in the scenario or in the environment (e.g., this is common in goods delivery, as well as in mobile robotic scenarios for coverage, monitoring, and surveillance). Motivated by these limitations, we propose a multi-stage clustering-based metaheuristic for tackling large Orienteering Problems in an effective, strategically controlled amount of computation time. The metaheuristic starts by decomposing the problem into smaller, independent sub-problems that are efficiently solved using an algorithm of choice, sequentially or in parallel. The obtained solutions are then merged to form a solution for the original problem, and then further optimized and processed to ensure feasibility. The metaheuristic aims to dramatically improve the computation time of a given Orienteering Problem algorithm without a significant decrease in the solution quality of that algorithm, especially for large Orienteering Problems. We have validated the effectiveness of the proposed metaheuristic design through a set of computational experiments. In particular, using a state-of-the-art heuristic and an exact algorithm, we have shown that it is significantly beneficial to use the Orienteering Problem algorithm plugged into our metaheuristic, as opposed to using it as a standalone algorithm. This was found to be especially true for large problems. As a result, large instances of Orienteering Problems can be effectively tackled within reasonable time bounds even for online application scenarios.
Ebola virus (EBOV) belongs to the Filoviridae family and is responsible for a severe disease characterized by the sudden onset of fever and malaise accompanied by other non-specific signs and ...symptoms; in 30-50% of cases hemorrhagic symptoms are present. Multiorgan dysfunction occurs in severe forms with a mortality up to 90%. The EBOV first attacks macrophages and dendritic immune cells. The innate immune reaction is characterized by a cytokine storm, with secretion of numerous pro-inflammatory cytokines, which induces a huge number of contradictory signals and hurts the immune cells, as well as other tissues. Other highly pathogenic viruses also trigger cytokine storms, but Filoviruses are thought to be particularly lethal because they affect a wide array of tissues. In addition to the immune system, EBOV attacks the spleen and kidneys, where it kills cells that help the body to regulate its fluid and chemical balance and that make proteins that help the blood to clot. In addition, EBOV causes liver, lungs and kidneys to shut down their functions and the blood vessels to leak fluid into surrounding tissues. In this review, we analyze the molecular mechanisms at the basis of Ebola pathogenesis with a particular focus on the cell death pathways induced by the virus. We also discuss how the treatment of the infection can benefit from the recent experience of blocking/modulating cell death in human degenerative diseases.
Laboratory-acquired infections due to a variety of bacteria, viruses, parasites, and fungi have been described over the last century, and laboratory workers are at risk of exposure to these ...infectious agents. However, reporting laboratory-associated infections has been largely voluntary, and there is no way to determine the real number of people involved or to know the precise risks for workers. In this study, an international survey based on volunteering was conducted in biosafety level 3 and 4 laboratories to determine the number of laboratory-acquired infections and the possible underlying causes of these contaminations. The analysis of the survey reveals that laboratory-acquired infections have been infrequent and even rare in recent years, and human errors represent a very high percentage of the cases. Today, most risks from biological hazards can be reduced through the use of appropriate procedures and techniques, containment devices and facilities, and the training of personnel.
•Italian Taste is a large-scale study aimed at exploring influences on food choice.•IT explores the complex interplay of factors contributing to food preferences.•Genetic, physiological, personality, ...sociocultural factors are considered.•Associations among personality, attitudes, PROP, familiarity and liking are shown.
Food choice is influenced by many interacting factors in humans. Its multidimensional and complex nature is well recognized, particularly within the sensory and consumer food science field. However, the vast majority of the studies aimed at understanding determinants of food choices, preferences, and eating behaviours are affected by important limitations: the limited number of factors that are considered at once and the sample size. Furthermore, sensory and hedonic responses to actual food stimuli are often not included in such studies.
The Italian Taste project is a large-scale study (three thousand respondents in three years) launched by the Italian Sensory Science Society aimed at addressing these limitations by exploring the associations among a variety of measures – biological, genetic, physiological, psychological and personality-related, socio-cultural – describing the dimensions of food liking, preference, behaviour and choice, and their relevance in determining individual differences within a given food culture framework. In addition, the study includes also the collection of sensory and hedonic responses to actual food stimuli commonly consumed in Italy and prepared to elicit a variation in the strength (from weak to strong) of bitterness, sweetness, saltiness, sourness, pungency, umami and astringency.
The aims of the present paper are twofold. Firstly, the paper is aimed to illustrate the variables selected to explore the different dimensions of food choice and to report the experimental procedure adopted for data collection. Secondly, the paper is aimed at showing the potential of the Italian Taste dataset on the basis of the data collected in the first year of the project. For the purpose, we selected a small number of variables known to influence food choices from data collected in the first year of the project on 1225 individuals.
This work is about mission planning in teams of mobile autonomous agents. We consider tasks that are spatially distributed, non-atomic, and provide an utility for integral and also partial task ...completion. Agents are heterogeneous, therefore showing different efficiency when dealing with the tasks. The goal is to define a system-level plan that assigns tasks to agents to maximize mission performance. We define the mission planning problem through a model including multiple sub-problems that are addressed jointly: task selection and allocation, task scheduling, task routing, control of agent proximity over time. The problem is proven to be NP-hard and is formalized as a mixed integer linear program (MILP). Two solution approaches are proposed: one heuristic and one exact method. Both combine a generic MILP solver and a genetic algorithm, resulting in efficient anytime algorithms. To support performance scalability and to allow the effective use of the model when online continual replanning is required, a decentralized and fully distributed architecture is defined top-down from the MILP model. Decentralization drastically reduces computational requirements and shows good scalability at the expenses of only moderate losses in performance. Lastly, we illustrate the application of the mission planning framework in two demonstrators. These implementations show how the framework can be successfully integrated with different platforms, including mobile robots (ground and aerial), wearable computers, and smart-phone devices.
In networked multi-robot systems, communication plays a major role defining system’s dynamics and performance. Unfortunately, existing multi-robot simulators do not provide advanced communication ...models. Therefore, given the intrinsic unreliability of wireless communications, significant differences might be observed between simulation and real-world results.
Addressing these issues, we present RoboNetSim, an integrated simulation framework for communication-realistic simulation of networked multi-robot systems. RoboNetSim integrates multi-robot simulators with network simulators. We present two model implementations based on ARGoS at the robotic side, and NS-2 and NS-3 as network simulators. We evaluate the framework in terms of accuracy and computational performance, showing that it can efficiently simulate systems consisting of hundreds of robots.
Using the Stage simulator as an example, we also show the integration of a robotic simulator with RoboNetSim by only adapting robot controllers, without the need to adapt the general code of the simulator.
Finally, we demonstrate the effects of communication on mobile multi-robot systems. We consider two different case studies: a distributed coordination and task assignment scenario, and a coordinated mobility scenario. We compare realistic network simulation with simplified communication models and algorithms, and we study the resulting behavior and performance of the multi-robot system and the impact of different parameters.
Friction stir welding (FSW) is a solid state welding process used to weld difficult to be welded or unweldable materials as aluminium alloys. In the last years, other materials have been successfully ...tested as magnesium, titanium and nickel based alloys. Dissimilar joints can be obtained by FSW, but issues arise concerning the correct choice of the process parameters. In the paper, the results of an experimental and numerical campaign aimed to produce dissimilar AZ31-AA6016-T6 butt joints are presented. The effect of sheet mutual position and main process parameters was investigated. It was found that intermetallics are the main cause of the poor quality of the joints. Sound joints can be produced only if the magnesium alloy is in the advancing side.
Multidrug-resistant tuberculosis (MDR-TB) is a major burden to public health in low incidence countries in Europe. The aim of this study was to attempt to have a better insight into the trends of ...MDR-TB in the metropolitan area of Rome, within the Italian and the foreign-born population, based on microbiological and demographic data.
We performed a prospective study, collecting microbiological data based on phenotypic drug-resistant testing (DST) of TB strains consecutively isolated in a referral hospital in Rome, the capital city of a low TB incidence country, over a 6-year period, and correlated them to the geographical origin of patients. This study was carried out in a referral hospital for patients with drug-resistant TB from the whole region.
Drug-resistance data from 926 patients with a microbiological diagnosis of TB from 2011 to 2016 show a 5.5% rate of MDR-TB, mostly occurring in patients born in a single East European country, that has a high incidence of MDR-TB. The strains isolated from these patients frequently carry additional resistances, leading to an increased risk of developing extensively drug-resistant (XDR) TB.
In the great metropolitan area of Rome, MDR-TB more frequently occurs in patients who were born in a single country from Eastern Europe known to have high rates of MDR-TB and long-time residents in Italy. Recent immigrants from non-European countries do not appear to contribute to the rates of MDR-TB reported in this article. This knowledge of local TB trends could help improve the measures of surveillance and prevention of disease.
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