Business cycle arithmetic: time variation measures and their relations

This paper tries to establish mathematical relationships between some of the most used concepts in the analysis of cyclical developments, such as the month-on-month and year-on-year percentage variations, or the annual rate of growth. Some of these relationships are already used in practice, but up to now never demonstrated in a formal way. The ultimate aim is to develop a set of precise analytical tools for the short term analysis of high frequency variables. Analytical derivations are followed by various empirical examples based on data on main Italian economic variables, both monthly (such as the consumer price index) and quarterly variables (like gross domestic product) for the most recent years, in order to illustrate the theoretical relationships and clarify their practical uselfuness.Strumenti matematici : ciclo economico

Detecting long-term occupancy changes in Californian odonates from natural history and citizen science records

In a world of rapid environmental change, effective biodiversity conservation and management relies on our ability to detect changes in species occurrence. While long-term, standardized monitoring is ideal for detecting change, such monitoring is costly and rare. An alternative approach is to use historical records from natural history collections as a baseline to compare with recent observations. Here, we combine natural history collection data with citizen science observations within a hierarchical Bayesian occupancy modeling framework to identify changes in the occupancy of Californian dragonflies and damselflies (Odonata) over the past century. We model changes in the probability of occupancy of 34 odonate species across years and as a function of climate, after correcting for likely variation in detection probability using proxies for recorder effort and seasonal variation. We then examine whether biological traits can help explain variation in temporal trends. Models built using only opportunistic records identify significant changes in occupancy across years for 14 species, with eight of those showing significant declines and six showing significant increases in occupancy in the period 1900–2013. These changes are consistent with estimates obtained using more standardized resurvey data, regardless of whether resurvey data are used individually or in conjunction with the opportunistic dataset. We find that species increasing in occupancy over time are also those whose occupancy tends to increase with higher minimum temperatures, which suggests that these species may be benefiting from increasing temperatures across California. Furthermore, these species are also mostly habitat generalists, whilst a number of habitat specialists display some of the largest declines in occupancy across years. Our approach enables more robust estimates of temporal trends from opportunistic specimen and observation data, thus facilitating the use of these data in biodiversity conservation and management

Effects of balloon injury on neointimal hyperplasia in steptozotocin-induced diabetes and in hyperinsulinemic nondiabetic pancreatic islet-transplanted rats.

BACKGROUND: The mechanisms of increased neointimal hyperplasia after coronary interventions in diabetic patients are still unknown. METHODS AND RESULTS: Glucose and insulin effects on in vitro vascular smooth muscle cell (VSMC) proliferation and migration were assessed. The effect of balloon injury on neointimal hyperplasia was studied in streptozotocin-induced diabetic rats with or without adjunct insulin therapy. To study the effect of balloon injury in nondiabetic rats with hyperinsulinemia, pancreatic islets were transplanted under the kidney capsule in normal rats. Glucose did not increase VSMC proliferation and migration in vitro. In contrast, insulin induced a significant increase in VSMC proliferation and migration in cell cultures. Furthermore, in VSMC culture, insulin increased MAPK activation. A reduction in neointimal hyperplasia was consistently documented after vascular injury in hyperglycemic streptozotocin-induced diabetic rats. Insulin therapy significantly increased neointimal hyperplasia in these rats. This effect of hyperinsulinemia was totally abolished by transfection on the arterial wall of the N17H-ras-negative mutant gene. Finally, after experimental balloon angioplasty in hyperinsulinemic nondiabetic islet-transplanted rats, a significant increase in neointimal hyperplasia was observed. CONCLUSIONS: In rats with streptozotocin-induced diabetes, balloon injury was not associated with an increase in neointimal formation. Exogenous insulin administration in diabetic rats and islet transplantation in nondiabetic rats increased both blood insulin levels and neointimal hyperplasia after balloon injury. Hyperinsulinemia through activation of the ras/MAPK pathway, rather than hyperglycemia per se, seems to be of crucial importance in determining the exaggerated neointimal hyperplasia after balloon angioplasty in diabetic animals

Beyond a warming fingerprint: individualistic biogeographic responses to heterogeneous climate change in California.

Understanding recent biogeographic responses to climate change is fundamental for improving our predictions of likely future responses and guiding conservation planning at both local and global scales. Studies of observed biogeographic responses to 20th century climate change have principally examined effects related to ubiquitous increases in temperature - collectively termed a warming fingerprint. Although the importance of changes in other aspects of climate - particularly precipitation and water availability - is widely acknowledged from a theoretical standpoint and supported by paleontological evidence, we lack a practical understanding of how these changes interact with temperature to drive biogeographic responses. Further complicating matters, differences in life history and ecological attributes may lead species to respond differently to the same changes in climate. Here, we examine whether recent biogeographic patterns across California are consistent with a warming fingerprint. We describe how various components of climate have changed regionally in California during the 20th century and review empirical evidence of biogeographic responses to these changes, particularly elevational range shifts. Many responses to climate change do not appear to be consistent with a warming fingerprint, with downslope shifts in elevation being as common as upslope shifts across a number of taxa and many demographic and community responses being inconsistent with upslope shifts. We identify a number of potential direct and indirect mechanisms for these responses, including the influence of aspects of climate change other than temperature (e.g., the shifting seasonal balance of energy and water availability), differences in each taxon's sensitivity to climate change, trophic interactions, and land-use change. Finally, we highlight the need to move beyond a warming fingerprint in studies of biogeographic responses by considering a more multifaceted view of climate, emphasizing local-scale effects, and including a priori knowledge of relevant natural history for the taxa and regions under study

Severity of Coronary Atherosclerosis and Risk of Diabetes Mellitus

Cardio-vascular target organ damage predicts the onset of type 2 diabetes mellitus (DM) in hypertensive patients. Whether an increased incidence of DM is also in relation to the severity of coronary atherosclerosis is unknown

Dispersal and extrapolation on the accuracy of temporal predictions from distribution models for the Darwin's frog

Indexación: Web of Science; Scopus.Climate change is a major threat to biodiversity; the development of models that reliably predict its effects on species distributions is a priority for conservation biogeography. Two of the main issues for accurate temporal predictions from Species Distribution Models (SDM) are model extrapolation and unrealistic dispersal scenarios. We assessed the consequences of these issues on the accuracy of climate-driven SDM predictions for the dispersal-limited Darwin's frog Rhinoderma darwinii in South America. We calibrated models using historical data (1950-1975) and projected them across 40 yr to predict distribution under current climatic conditions, assessing predictive accuracy through the area under the ROC curve (AUC) and True Skill Statistics (TSS), contrasting binary model predictions against temporal-independent validation data set (i.e., current presences/absences). To assess the effects of incorporating dispersal processes we compared the predictive accuracy of dispersal constrained models with no dispersal limited SDMs; and to assess the effects of model extrapolation on the predictive accuracy of SDMs, we compared this between extrapolated and no extrapolated areas. The incorporation of dispersal processes enhanced predictive accuracy, mainly due to a decrease in the false presence rate of model predictions, which is consistent with discrimination of suitable but inaccessible habitat. This also had consequences on range size changes over time, which is the most used proxy for extinction risk from climate change. The area of current climatic conditions that was absent in the baseline conditions (i.e., extrapolated areas) represents 39% of the study area, leading to a significant decrease in predictive accuracy of model predictions for those areas. Our results highlight (1) incorporating dispersal processes can improve predictive accuracy of temporal transference of SDMs and reduce uncertainties of extinction risk assessments from global change; (2) as geographical areas subjected to novel climates are expected to arise, they must be reported as they show less accurate predictions under future climate scenarios. Consequently, environmental extrapolation and dispersal processes should be explicitly incorporated to report and reduce uncertainties in temporal predictions of SDMs, respectively. Doing so, we expect to improve the reliability of the information we provide for conservation decision makers under future climate change scenarios.http://onlinelibrary.wiley.com/doi/10.1002/eap.1556/abstract;jsessionid=1E2084FF99600D0EEC9FA358A3DBC2A3.f02t0

Un semplice modello univariato per la previsione a breve termine dell'inflazione italiana

The aim of this paper is to build a tool for performing forecasting exercises, allowing to obtain a reliable estimate of Italian consumer price inflation. To reach this goal we estimate a simple three-equation model for the short term forecasting of twelve-month percentage variations of the Italian consumer price index. The starting point of the model is the decomposition of the general index in a main component, the so-called core inflation, capturing longer term tendencies and two additional volatile components, those of unprocessed food and energy prices. The idea is that it is exactly core inflation which is possible to explain and forecast with a set of basic economic variables acting as leading indicators

L'aritmetica del congiunturalista: misure di confronto temporale e loro relazioni

This paper tries to establish mathematical relationships between some of the most used concepts in the analysis of cyclical developments, such as the month-on-month and year-on-year percentage variations, or the annual rate of growth. Some of these relationships are already used in practice, but up to now never demonstrated in a formal way. The ultimate aim is to develop a set of precise analytical tools for the short term analysis of high frequency variables. Analytical derivations are followed by various empirical examples based on data on main Italian economic variables, both monthly (such as the consumer price index) and quarterly variables (like gross domestic product) for the most recent years, in order to illustrate the theoretical relationships and clarify their practical uselfuness

Un semplice modello univariato per la previsione a breve termine dell'inflazione italiana

The aim of this paper is to build a tool for performing forecasting exercises, allowing to obtain a reliable estimate of Italian consumer price inflation. To reach this goal we estimate a simple three-equation model for the short term forecasting of twelve-month percentage variations of the Italian consumer price index. The starting point of the model is the decomposition of the general index in a main component, the so-called core inflation, capturing longer term tendencies and two additional volatile components, those of unprocessed food and energy prices. The idea is that it is exactly core inflation which is possible to explain and forecast with a set of basic economic variables acting as leading indicators