METROPOLITAN AGRICULTURE, SOCIO-DEMOGRAPHIC DYNAMICS AND THE FOOD-CITY RELATIONSHIP IN SOUTHERN EUROPE

Peri-urban agriculture is a pivotal issue in the debate on sustainable management of land in metropolitan regions worldwide. Multiple socioeconomic and environmental solutions introduced by new models of peri-urban agriculture are playing an important role in planning and management of fringe land. The recent development of peri-urban agriculture in Southern European cities was supposed to reflect latent, crisis-driven processes of 'coming back to land': new land has been extensively cultivated, and new relations have been created between farmers, communities and territories within peri-urban areas. This study describes some relevant experiences of peri-urban farming in 6 metropolitan regions (Lisbon, Barcelona, Marseille, Rome, Athens, Istanbul) representative of different socioeconomic contexts in Southern Europe, outlining strengths and weaknesses in the use of fringe land for cropping, and evidencing relevant implications for urban sustainability

Small area estimation based on M-quantile models in presence of outliers in auxiliary variables

When using small area estimation models, the presence of outlying observations in the response and/or in the auxiliary variables can severely affect the estimates of the model parameters, which can in turn affect the small area estimates produced using these models. In this paper we propose an M-quantile estimator of the small area mean that is robust to the presence of outliers in the response variable and in the continuous auxiliary variables. To estimate the variability of this estimator we propose a non-parametric bootstrap estimator. The performance of the proposed estimator is evaluated by means of model- and design-based simulations and by an application to real data. In these comparisons we also include the extension of the Robust EBLUP able to down-weight the outliers in the auxiliary variables. The results show that in the presence of outliers in the auxiliary variables the proposed estimator outperforms its traditional version that takes into account the presence of outliers only in the response variable

Novel Modality of Endoluminal Anastomotic Integrity Assessment with Fluoroangiography After Left-sided Colorectal Resections

Background Several methods have been described for the intraoperative evaluation of colorectal anastomotic integrity. Technological evolution has allowed to progress from basic mechanical methods to the use of more sophisticated techniques. This study describes a novel endoluminal modality of colorectal anastomotic assessment through the use of a Disposable Rigid Scope Introducer (DRSI) also allowing for intraoperative endoluminal perfusion evaluation by indocyanine green (ICG) fluoroangiography in patients undergoing left-sided colorectal resection. Methods The DRSI consists of an endoluminal introducer device made up of an insertion tube and port connected to an insufflation bulb to manually insufflate the sigmoid and rectum and is compatible with any laparoscopic camera, also allowing for ICG fluoroangiography for perfusion purposes. Results The DRSI was successfully used to assess anastomotic integrity after left-sided colorectal resections performed in 16 consecutive patients. The DRSI allowed to visualize by fluoroangiography the quality of tissue perfusion at the anastomotic site in all cases, contributing to the decision of avoiding loop ileostomies in low rectal resections. In 2 cases, the DRSI showed the presence of significant anastomotic bleeding which was successfully controlled by laparoscopic suture placement. No adverse event resulted from the use of this device. Conclusions The DRSI combines direct endoluminal visualization of the anastomosis together with real-time evaluation of its blood flow. This device holds great potential for prompt intraoperative detection of anastomotic alterations, possibly reducing the risk of postoperative anastomotic bleeding or leaks related to mechanical construction/perfusion issues. Potential advantages of this device warrant larger cohort studies and prospective randomized trials

Predictive value of dynamic renal resistive index (DRIN) for renal outcome in type 2 diabetes and essential hypertension: a prospective study

BACKGROUND: Hypertension (EH) and type 2 diabetes (T2DM) are major causes of chronic kidney disease (CKD) and identification of predictors of CKD onset is advisable. We aimed to assess whether dynamic renal resistive index (DRIN), as well as other markers of systemic vascular damage, are able to predict albuminuria onset and estimated glomerular filtration rate (eGFR) decline in patients with T2DM or EH. METHODS: In this prospective observational cohort study, 27 T2DM and 43 EH patients, free of CKD at baseline, were followed-up for 4.1 ± 0.6 years. Resistive Index (RI), endothelium-dependent (FMD) and independent vasodilation in the brachial artery (after glyceryl trinitrate - GTN - 25 μg s.l.), carotid-femoral Pulse Wave Velocity (PWV), Augmentation Index (AIx), DRIN (%RI change after GTN 25 μg s.l.) were evaluated. RESULTS: Patients developing microalbuminuria were older, more frequently T2DM, with higher UACR at baseline, and showed higher DRIN (-2.8 ± 6.7 vs -10.6 ± 6.4 %, p = 0.01) and PWV (9.9 ± 1.3 vs 7.9 ± 1.5 m/s, p = 0.004) at baseline. The best predictors of microalbuminuria onset were DRIN > -5.16 % in T2DM (sensitivity 0.83, specificity 0.80) and PWV > 8.6 m/s in EH (sensitivity 0.96, specificity 1.00). Individuals whose eGFR declined (n = 27) had higher eGFR at baseline, but similar vascular characteristics; however in EH showing eGFR decline, baseline DRIN and PWV were higher. PWV showed a steeper progression during follow-up in patients developing albuminuria (Visit-outcome interaction: p = 0.01), while DRIN was early compromised but no further impaired (Visit-outcome interaction: p = 0.04). CONCLUSIONS: PWV and DRIN are able to predict microalbuminuria onset in newly diagnosed EH and T2DM. DRIN is early compromised in T2DM patients developing microalbuminuria

Inference for big data assisted by small area methods: an application to OBEC (on-line based enterprise characteristics)

Nowadays, the availability of a huge amount of data produced by a wide range of new technologies, so-called big data, is increasing. However, data obtain- able from big data sources are often the result of a non-probability sampling process and adjusting for the selection bias is an important practical problem. In this paper, we propose a novel method of reducing the selection bias associated with the big data source in the context of Small Area Estimation (SAE). Our approach is based on data integration and the combination of a big data sample and a probability sam- ple. An application on OBEC (on-line based enterprise characteristics) combining Istat sampling survey and web scraping data has been proposed

Modeling Spatio-Temporal Divergence in Land Vulnerability to Desertification with Local Regressions

Taken as a classical issue in applied economics, the notion of ‘convergence’ is based on the concept of path dependence, i.e., from the previous trajectory undertaken by the system during its recent history. Going beyond social science, a ‘convergence’ perspective has been more recently adopted in environmental studies. Spatial convergence in non-linear processes, such as desertification risk, is a meaningful notion since desertification represents a (possibly unsustainable) development trajectory of socio-ecological systems towards land degradation on a regional or local scale. In this study, we test—in line with the classical convergence approach—long-term equilibrium conditions in the evolution of desertification processes in Italy, a European country with significant socioeconomic and environmental disparities. Assuming a path-dependent development of desertification risk in Italy, we provided a diachronic analysis of the Environmental Sensitive Area Index (ESAI), estimated at a disaggregated spatial resolution at three times (1960s, 1990s, and 2010s) in the recent history of Italy, using a spatially explicit approach based on geographically weighted regressions (GWRs). The results of local regressions show a significant path dependence in the first time interval (1960–1990). A less significant evidence for path-dependence was observed for the second period (1990–2010); in both cases, the models’ goodness-of-fit (global adjusted R2) was satisfactory. A strong polarization along the latitudinal gradient characterized the first observation period: Southern Italian land experienced worse conditions (e.g., climate aridity, urbanization) and the level of land vulnerability in Northern Italy remained quite stable, alimenting the traditional divergence in desertification risk characteristic of the country. The empirical analysis delineated a more complex picture for the second period. Convergence (leading to stability, or even improvement, of desertification risk) in some areas of Southern Italy, and a more evident divergence (leading to worse environmental conditions because of urban sprawl and crop intensification) in some of the land of Northern Italy, were observed, leading to an undesired spatial homogenization toward higher vulnerability levels. Finally, this work suggests the importance of spatially explicit approaches providing relevant information to design more effective policy strategies. In the case of land vulnerability to degradation in Italy, local regression models oriented toward a ‘convergence’ perspective, may be adopted to uncover the genesis of desertification hotspots at both the regional and local scale

Small area model-based estimators using big data sources

The timely, accurate monitoring of social indicators, such as poverty or inequality, on a fine- grained spatial and temporal scale is a crucial tool for understanding social phenomena and policymaking, but poses a great challenge to official statistics. This article argues that an interdisciplinary approach, combining the body of statistical research in small area estimation with the body of research in social data mining based on Big Data, can provide novel means to tackle this problem successfully. Big Data derived from the digital crumbs that humans leave behind in their daily activities are in fact providing ever more accurate proxies of social life. Social data mining from these data, coupled with advanced model-based techniques for fine-grained estimates, have the potential to provide a novel microscope through which to view and understand social complexity. This article suggests three ways to use Big Data together with small area estimation techniques, and shows how Big Data has the potential to mirror aspects of well-being and other socioeconomic phenomena

Recent results and perspectives on cosmology and fundamental physics from microwave surveys

Recent cosmic microwave background data in temperature and polarization have reached high precision in estimating all the parameters that describe the current so-called standard cosmological model. Recent results about the integrated Sachs-Wolfe effect from cosmic microwave background anisotropies, galaxy surveys, and their cross-correlations are presented. Looking at fine signatures in the cosmic microwave background, such as the lack of power at low multipoles, the primordial power spectrum and the bounds on non-Gaussianities, complemented by galaxy surveys, we discuss inflationary physics and the generation of primordial perturbations in the early Universe. Three important topics in particle physics, the bounds on neutrinos masses and parameters, on thermal axion mass and on the neutron lifetime derived from cosmological data are reviewed, with attention to the comparison with laboratory experiment results. Recent results from cosmic polarization rotation analyses aimed at testing the Einstein equivalence principle are presented. Finally, we discuss the perspectives of next radio facilities for the improvement of the analysis of future cosmic microwave background spectral distortion experiments.Comment: 27 pages, 9 figures. Review Article. International Journal of Modern Physics D, in press. [Will appear also on the proceedings of the Fourteenth Marcel Grossmann Meeting University of Rome "La Sapienza" - Rome, July 12-18, 2015 (http://www.icra.it/mg/mg14/), eds. Robert T. Jantzen, Kjell Rosquist, Remo Ruffini. World Scientific, Singapore

Role of Narrow Band Imaging Technology in the Diagnosis and Follow up of Laryngeal Lesions: Assessment of Diagnostic Accuracy and Reliability in a Large Patient Cohort

BACKGROUND: The aim of this study was to assess diagnostic accuracy and reliability of narrow band imaging (NBI) in the differential diagnosis of laryngeal premalignant lesion, early cancers and recurrences.MATERIAL AND METHODS: We enrolled 231 patients who underwent endoscopic examination with white light endoscopy (WLE) + NBI and divided them into two groups, group A, without previous radiochemotherapy and group B, with previous radiochemotherapy. When indicated, we performed surgical biopsies to evaluate sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy and likelihood of endoscopic examination comparing WLE alone and WLE + NBI.RESULTS: A positive NBI lesion, compared with a negative NBI lesion, had a 29.68 (group A) and 13.96 (group B) times higher probability to be histologically positive (i.e., confirmed) compared with WLE alone improving the diagnostic accuracy. In group A, the NBI mode showed excellent sensitivity (95.0%), which was higher than WLE 2 mode (77.5%). However, the greatest differences were recorded regarding specificity (96.8% vs. 40.6%). In group B, both NBI alone and WLE + NBI mode showed a 94.1% specificity compared with WLE alone, which had a maximum specificity of 85.3%. The mode comparison between NBI and WLE in both groups showed a statistically significant difference, with p-values <0.0001.CONCLUSIONS: NBI represents a reliable technology in challenging situations, especially in the context of post-radiotherapy or post-surgical mucosal changes showing a high NPV. NBI could reduce the number of unnecessary biopsies related to increased microvascular anomaly revelation, which could help to identify early-stage lesions suitable for minimally invasive surgery and, consequently, decrease hospital admissions

On the tracks of Nitrogen deposition effects on temperate forests at their southern European range - an observational study from Italy

We studied forest monitoring data collected at permanent plots in Italy over the period 2000\u20132009 to identify the possible impact of nitrogen (N) deposition on soil chemistry, tree nutrition and growth. Average N throughfall (N-NO3+N-NH4) ranged between 4 and 29 kg ha 1 yr 1, with Critical Loads (CLs) for nutrient N exceeded at several sites. Evidence is consistent in pointing out effects of N deposition on soil and tree nutrition: topsoil exchangeable base cations (BCE) and pH decreased with increasing N deposition, and foliar nutrient N ratios (especially N : P and N : K) increased. Comparison between bulk openfield and throughfall data suggested possible canopy uptake of N, levelling out for bulk deposition >4\u20136 kg ha 1 yr 1. Partial Least Square (PLS) regression revealed that - although stand and meteorological variables explained the largest portion of variance in relative basal area increment (BAIrel 2000\u20132009) - N-related predictors (topsoil BCE, C : N, pH; foliar N-ratios; N deposition) nearly always improved the BAIrel model in terms of variance explained (from 78.2 to 93.5%) and error (from 2.98 to 1.50%). N deposition was the strongest predictor even when stand, management and atmosphere-related variables (meteorology and tropospheric ozone) were accounted for. The maximal annual response of BAIrel was estimated at 0.074\u20130.085% for every additional kgN. This corresponds to an annual maximal relative increase of 0.13\u20130.14% of carbon sequestered in the above-ground woody biomass for every additional kgN, i.e. a median value of 159 kgC per kgN ha 1 yr 1 (range: 50\u2013504 kgC per kgN, depending on the site). Positive growth response occurred also at sites where signals of possible, perhaps recent N saturation were detected. This may suggest a time lag for detrimental N effects, but also that, under continuous high N input, the reported positive growth response may be not sustainable in the long-term