Ricerc@Sapienza

Forest health is currently assessed in Europe (ICP Forests monitoring program). Crown defoliation and dieback, tree mortality, and pathogenic damage are the main aspects considered in tree health assessment. The worsening of environmental conditions (i.e., increase of temperature and drought events) may cause large-spatial scale tree mortality and forest decline. However, the role of stand features, including tree species assemblage and diversity as factors that modify environmental impacts, is poorly considered.

Tree diversity is found to enhance ecosystem functions in forests and increase the resistance and resilience of trees subjected to environmental stress, including climate change. This effect, however, can be different depending on tree species assemblages and ecological contexts. The pan-European programme for monitoring forest health (ICP Forests) considers crown defoliation as an indicator of tree vitality. Only a few studies have analysed the role of tree diversity in crown defoliation, with contrasting results.

This work investigates whether different demand sources (i.e. demand for the firms’ output from households, other firms and the public sector) have different effects on firms’ employment growth and whether the growth effects of the demand sources vary by the firms’ innovation/knowledge characteristics. Relying on a representative sample of Italian companies observed between 2012 and 2017, we find that companies serving prevalently other firms or the government as their main demand source tend to grow faster than firms selling final goods to households.

Heroin is one of the most frequently seized drugs in Southeastern Europe. Due to the position in the Balkan route, the Republic of Serbia keeps important role in suppression of the trafficking of heroin for domestic and foreign illegal market. This research is aimed to provide a good scientific approach in the field of seized heroin analysis. Two different forms of heroin are present in the illegal market, mostly in mixtures with typical "cutting" agents: caffeine, paracetamol, and sugars.

Fuzzy clustering methods discover fuzzy partitions where observations can be softly assigned to more than one cluster. The package fclust is a toolbox for fuzzy clustering in the R programming language. It not only implements the widely used fuzzy k-means (FkM) algorithm, but also many FkM variants. Fuzzy cluster similarity measures, cluster validity indices and cluster visualization tools are also offered. In the current version, all the functions are rewritten in the C++ language allowing their application in large-size problems.

This paper analyzes the connection between innovation activities of
companies – implemented before crisis – and their performance –
measured at time of crisis. The companies listed in the STAR Market
Segment of the Italian Stock Exchange are analyzed. Innovation is
measured through the level of investments in total tangible and
intangible fixed assets in 2006–2007, while performance is captured
through growth – expressed by variations of sales, total assets and
employees – profitability – through ROI or ROS – and productivity –

Purpose of Review: Modified risk products (MRP) are promoted as a safer alternative to traditional combustion cigarettes (TCC) in chronic smokers. Evidence for their lower hazardous profile is building, despite several controversies. Yet, it is unclear whether individual responses to MRP differ among consumers. We hypothesized that different clusters of subjects exist in terms of acute effects of MRP.

Finite mixture models are an important tool in the statistical analysis of data, for example in data clustering. The optimal parameters of a mixture model are usually computed by maximizing the log-likelihood functional via the Expectation-Maximization algorithm. We propose an alternative approach based on the theory of Mean Field Games, a class of differential games with an infinite number of agents. We show that the solution of a finite state space multi-population Mean Field Games system characterizes the critical points of the log-likelihood functional for a Bernoulli mixture.

In the last two decades, scientific research has explored the problematic use of internet, videogames and mobile phones. However, there is still little consistent knowledge regarding the co‐occurrence of problematic technology use and the role of maladaptive personality characteristics in adolescence. The present study aimed to investigate adolescents' styles of technology use with a cluster analysis approach focusing on personality functioning. The sample comprised 408 Italian adolescents (46.3% males) aged 11 to 18 years (M age = 13.80; SD = 2.08).

For the first time, the cluster analysis (k-means) has been applied on long time series of temperature and relative humidity measurements to identify the thermo-hygrometric features in a museum. Based on ASHRAE (2011) classification, 84% of time all rooms in the Napoleonic Museum in Rome (case study) were found in the class of control B. This result was obtained by analyzing all recorded data in 10 rooms of the museum as well as using the cluster aggregation.