Forecasting Industrial Production and the Early Detection of Turning Points

In this paper we propose a simple model to forecast industrial production in Italy up to 6 months ahead. We show that the forecasts produced using the model outperform some popular forecasts as well as those stemming from an ARIMA model used as a benchmark and those from some single equation alternative models. We show how the use of these forecasts can improve the estimate of a cyclical indicator and the early detection of turning points for the manufacturing sector. This is of paramount importance for short-term economic analysis.Forecasting, VAR Models, Industrial production, Cyclical indicators.

Measuring the impact of the Italian CFL programme on the job opportunities for the youths

The CFL programme has been introduced in 1985 to improve the youths occupational chances. It provides the employers some incentive to recruit young workers by reducing both the labour and the firing costs relative to those they would bear by recruiting older workers. Following the literature, the expected impact of the programme is to increase the eligibles chance to work during the eligibility period as well as to improve their chance to work after the eligibility period thanks to the longer work experience obtained during the eligibility period. A substitution effect might emerge since as subjects get out of eligibility employers might find convenient to replace them by younger still eligible workers. To measure the impact of the programme we exploit the variation over time and across geographical areas of the incentive to hire eligible workers induced by several reforms of the programme as well as its interaction with other incentive schemes.targeted wage subsidy, firing costs, substitution effect

Modelling of browning kinetics of bread crust during baking

Abstract A mathematical model was set up to predict browning kinetics of bread crust during baking. A bread dough was placed into a cylindrical steel mould and baked in a pilot forced-convection oven at 200 and 250°C. The sample surface temperature was measured using both a type J thermocouple and an infrared thermometer. Surface browning (ΔE) of bread crust during baking was measured by a tristimulus colorimeter. The kinetic model for bread crust browning was obtained by instant heating of dried crumb on contact with a refractory plate at 140, 150, 165, 185, 210, 235 and 250°C. At all temperatures ΔE tended asymptotically to ΔE∞ = 52, which corresponded to the burnt sample. The colour difference varies as a function of first-order kinetics. The rate constant k depends on temperature according to the Arrhenius equation (ko = 42,000 s−1; Ea = 64,151 J/mol). Kinetics was validated under dynamic temperature conditions: the experimental results were compared with those obtained from a mathematical model for heat and mass transfer during baking connected to the kinetic model for browning

Anopheline salivary protein genes and gene families: an evolutionary overview after the whole genome sequence of sixteen Anopheles species

Background: Mosquito saliva is a complex cocktail whose pharmacological properties play an essential role in blood feeding by counteracting host physiological response to tissue injury. Moreover, vector borne pathogens are transmitted to vertebrates and exposed to their immune system in the context of mosquito saliva which, in virtue of its immunomodulatory properties, can modify the local environment at the feeding site and eventually affect pathogen transmission. In addition, the host antibody response to salivary proteins may be used to assess human exposure to mosquito vectors. Even though the role of quite a few mosquito salivary proteins has been clarified in the last decade, we still completely ignore the physiological role of many of them as well as the extent of their involvement in the complex interactions taking place between the mosquito vectors, the pathogens they transmit and the vertebrate host. The recent release of the genomes of 16 Anopheles species offered the opportunity to get insights into function and evolution of salivary protein families in anopheline mosquitoes. Results: Orthologues of fifty three Anopheles gambiae salivary proteins were retrieved and annotated from 18 additional anopheline species belonging to the three subgenera Cellia, Anopheles, and Nyssorhynchus. Our analysis included 824 full-length salivary proteins from 24 different families and allowed the identification of 79 novel salivary genes and re-annotation of 379 wrong predictions. The comparative, structural and phylogenetic analyses yielded an unprecedented view of the anopheline salivary repertoires and of their evolution over 100 million years of anopheline radiation shedding light on mechanisms and evolutionary forces that contributed shaping the anopheline sialomes. Conclusions: We provide here a comprehensive description, classification and evolutionary overview of the main anopheline salivary protein families and identify two novel candidate markers of human exposure to malaria vectors worldwide. This anopheline sialome catalogue, which is easily accessible as hyperlinked spreadsheet, is expected to be useful to the vector biology community and to improve the capacity to gain a deeper understanding of mosquito salivary proteins facilitating their possible exploitation for epidemiological and/or pathogen-vector-host interaction studies

Evidence on the prevalence and geographic distribution of major cardiovascular risk factors in Italy

Objective: To assess the prevalence and geographic distribution of major cardiovascular risk factors in a large community-wide sample of the Italian population. Design: A cross-sectional survey. Standardized methods were used to collect and measure cardiovascular risk factors. Data were adjusted for survey weightings. Qualitative and quantitative variables were compared with parametric and non-parametric tests, as appropriate. Setting: Towns (n 193) across different Italian regions. Subjects: Unselected adults (n 24 213; 12 626 men; 11 587 women) aged 18–98 years (mean age 56·9 (sd 15·3) years), who volunteered to participate in a community-wide screening programme over a 2 d period in 2007. Results: Overall, the prevalence of major cardiovascular risk factors was: obesity, 22·7 % (women 18·9 %, men 26·1 %); overweight, 44·7 % (women 31·6 %, men 56·7 %); hypertension, 59·6 % (women 48·3 %, men 70·0 %); dyslipidaemia, 59·1 % (women 57·7 %, men 60·3 %); diabetes, 15·3 % (women 11·2 %, men 19·0 %) and smoking, 19·8 % (women 14·0 %, men 25·2 %). We found a high prevalence of unhealthy eating habits; fruit and vegetable consumption was below the recommended range in 60 % of the study population. Ninety per cent of the study population had more than one cardiovascular risk factor and 84 % had between two and five cardiovascular risk factors. There were differences among Italian macro-areas mainly for obesity, hypertension, dyslipidaemia and diabetes. Conclusions: The study provides alarming evidence on current prevalence data for major cardiovascular risk factors in a large sample of the Italian population. Particularly, obesity and hypertension represent a relevant public health problem. There is a pressing need for effective preventive health measures which must also take into account the differences among Italian macro-areas

Forecasting Industrial Production and the Early Detection of Turning Points

In this paper we propose a simple model to forecast industrial production in Italy. We show that the forecasts produced using the model outperform some popular forecasts as well as those stemming from a trading days- and outlier-robust ARIMA model used as a benchmark. We show that the use of appropriately selected leading variables allows to produce up to twelve-step ahead reliable forecasts. We show how and why the use of these forecasts can improve the estimate of a cyclical indicator and the early detection of turning points for the manufacturing sector. This is of paramount importance for short-term economic analysis.Forecasting, Forecast Encompassing, VAR Models, Industrial Production, Cyclical Indicators