Protecting the environment: A multi-agent approach to environmental monitoring

In this paper we discuss a transition model from commonly adopted models of data gathering, transfer and management for environmental monitoring towards more sophisticated ones based on Artificial Intelligence and IoT. The transition model is based on the paradigm of multiple agent systems. The adoption of this transition model is motivated by the need to improve effectiveness, efficiency and interoperability of environmental monitoring by simultaneously guaranteeing its sustainability in economic term

A knowledge-intensive methodology for explainable sales prediction

Sales prediction in food market is a complex issue that has been addressed in the recent past with machine learning techniques. Although some promising results, an experimental work that we describe in this paper shows some drawbacks of the above mentioned data-driven method and habilitates the definition of a novel methodology, strongly involving a piori knowledg

Lipid peroxidation and protein oxidation in patients affected by Hodgkin's lymphoma.

A dysregulation of the redox homoeostasis has been reported in various neoplastic disorders. Malondialdehyde/4-hydroxy-2,3-nonenal (MDA/HNE) and protein carbonyl groups represent in vivo indexes of lipid peroxidation and protein oxidation, respectively, suitable to investigate radical-mediated physio-pathological conditions. We evaluated MDA/HNE and protein carbonyl groups in sera of untreated Hodgkin's lymphoma (HL) patients in advanced disease stages, in order to quantify the oxidative stress. HL patients displayed significantly higher levels of both MDA/HNE and protein carbonyl groups as compared with healthy controls. This is the first evidence that a strong increase in HL is one of the most common haematological malignancies, representing approximately 30% of all lymphomas in the circulating protein carbonyl content in HL. These findings may contribute to a better definition of the redox homoeostasis dysregulation in HL

Organic vs conventional stockless arable systems: a multidisciplinary approach to soil quality evaluation

Soil quality in Mediterranean conventional and organic stockless arable systems was assessed by a multidisciplinary approach. At the end of the first cycle of a 5-year crop rotation (2002–2006) in the Mediterranean Arable Systems Comparison Trial (MASCOT) long-term experiment, the effects of organic and conventional management systems were evaluated by using soil chemical, biochemical and biological parameters. Chemical and biochemical parameters linked to soil C cycle, arbuscular mycorrhizal fungi (AMF) and microarthropod communities were analysed according to a comparative approach. Results suggested a higher soil carbon sequestration in the organic respect to the conventional system, as shown by the values of total organic C (9.5 and 7.8 g kg1, for organic and conventional system, respectively) and potentially mineralisable C (277 and 254 mg kg1, for organic and conventional system, respectively). AMF population, AMF root colonisation and diversity of microarthropod population were slightly influenced by management system. On the other hand, mites/collembolans ratio was higher in conventionally than in organically managed soil (2.67 and 1.30, respectively), indicating as organic managed soils were more disturbed than conventional ones, probably as the consequence of the more frequent soil tillage performed for mechanical weeds control. The overall results demonstrated that, even in the short-term, the implementation of organically managed stockless systems in Mediterranean areas determined significant changes of some attributes for soil quality evaluation

Dynamics of Crossover from a Chaotic to a Power Law State in Jerky Flow

We study the dynamics of an intriguing crossover from a chaotic to a power law state as a function of strain rate within the context of a recently introduced model which reproduces the crossover. While the chaotic regime has a small set of positive Lyapunov exponents, interestingly, the scaling regime has a power law distribution of null exponents which also exhibits a power law. The slow manifold analysis of the model shows that while a large proportion of dislocations are pinned in the chaotic regime, most of them are pushed to the threshold of unpinning in the scaling regime, thus providing insight into the mechanism of crossover.Comment: 5 pages, 3 figures. In print in Phy. Rev. E Rapid Communication

Auditory dialog analysis and understanding by generative modelling of interactional dynamics

In the last few years, the interest in the analysis of human behavioral schemes has dramatically grown, in particular for the interpretation of the communication modalities called social signals. They represent well defined interaction patterns, possibly unconscious, characterizing different conversational situations and behaviors in general. In this paper, we illustrate an automatic system based on a generative structure able to analyze conversational scenarios. The generative model is composed by integrating a Gaussian mixture model and the (observed) influence model, and it is fed with a novel kind of simple low-level auditory social signals, which are termed steady conversational periods (SCPs). These are built on duration of continuous slots of silence or speech, taking also into account conversational turn-taking. The interactional dynamics built upon the transitions among SCPs provide a behavioral blueprint of conversational settings without relying on segmental or continuous phonetic features. Our contribution here is to show the effectiveness of our model when applied on dialogs classification and clustering tasks, considering dialogs between adults and between children and adults, in both flat and arguing discussions, and showing excellent performances also in comparison with state-of-the-art frameworks

SHREC 2022 track on online detection of heterogeneous gestures

This paper presents the outcomes of a contest organized to evaluate methods for the online recognition of heterogeneous gestures from sequences of 3D hand poses. The task is the detection of gestures belonging to a dictionary of 16 classes characterized by different pose and motion features. The dataset features continuous sequences of hand tracking data where the gestures are interleaved with non-significant motions. The data have been captured using the Hololens 2 finger tracking system in a realistic use-case of mixed reality interaction. The evaluation is based not only on the detection performances but also on the latency and the false positives, making it possible to understand the feasibility of practical interaction tools based on the algorithms proposed. The outcomes of the contest's evaluation demonstrate the necessity of further research to reduce recognition errors, while the computational cost of the algorithms proposed is sufficiently low

SHREC 2022 Track on Online Detection of Heterogeneous Gestures

This paper presents the outcomes of a contest organized to evaluate methods for the online recognition of heterogeneous gestures from sequences of 3D hand poses. The task is the detection of gestures belonging to a dictionary of 16 classes characterized by different pose and motion features. The dataset features continuous sequences of hand tracking data where the gestures are interleaved with non-significant motions. The data have been captured using the Hololens 2 finger tracking system in a realistic use-case of mixed reality interaction. The evaluation is based not only on the detection performances but also on the latency and the false positives, making it possible to understand the feasibility of practical interaction tools based on the algorithms proposed. The outcomes of the contest's evaluation demonstrate the necessity of further research to reduce recognition errors, while the computational cost of the algorithms proposed is sufficiently low.Comment: Accepted on Computer & Graphics journa