Determinants of fibrinogen in an Italian population suffering from claudication. Lower fibrinogen in the south compared to middle and north of Italy. The ADEP Group.

Prospective studies have shown that high plasma levels of fibrinogen are independently associated with the risk of cardiovascular complications. In patients suffering from peripheral vascular disease (PVD) fibrinogen has been shown to be an independent predictor of cardiovascular disease but its determinants have never been examined in this clinical setting. DESIGN AND METHODS: Fibrinogen levels were related to clinical and laboratory variables in 2,111 patients suffering from PVD. We also analyzed whether there was a regional distribution of risk factors. RESULTS: The median values of fibrinogen was 312 mg/dL. The clinical variables examined did not differentiate patients with elevated or normal fibrinogen levels. In particular, patients with ankle/arm pressure ratio < 0.8 did not show a higher prevalence of fibrinogen > 312 mg/dL. Conversely, white blood cell (WBC) count and serum cholesterol levels were significantly associated with high fibrinogen levels (p < 0.0001). Multiple logistic regression analysis demonstrated that areas of Italy were differently associated with high plasma fibrinogen levels (p < 0.03): subjects in the north and middle of Italy having significantly higher values of fibrinogen than subjects in the south of Italy (p < 0.01). A similar regional distribution was observed for WBC count and serum cholesterol levels. INTERPRETATION AND CONCLUSIONS: The regional distribution of risk factors raises the question as to whether the already reported large variability of cardiovascular events so in PVD may be attributed to a non homogeneous distribution of risk factors

Orographic Precipitation Extremes: An Application of LUME (Linear Upslope Model Extension) over the Alps and Apennines in Italy

Critical hydrometeorological events are generally triggered by heavy precipitation. In complex terrain, precipitation may be perturbed by the upslope raising of the incoming humid airflow, causing in some cases extreme rainfall. In this work, the application of LUME-Linear Upslope Model Extension-to a group of extreme events that occurred across mountainous areas of the Central Alps and Apennines in Italy is presented. Based on the previous version, the model has been "extended" in some aspects, proposing a methodology for physically estimating the time-delay coefficients as a function of precipitation efficiency. The outcomes of LUME are encouraging for the cases studied, revealing the intensification of precipitation due to the orographic effect. A comparison between the reference rain gauge data and the results of the simulations showed good agreement. Since extreme precipitation is expected to increase due to climate change, especially across the Mediterranean region, LUME represents an effective tool to investigate more closely how these extreme phenomena originate and evolve in mountainous areas that are subject to potential hydrometeorological risks

Phenotypical and Functional Characterization of Mesenchymal Stem Cells Derived From Patients Affected by Schwachman-Diamond Syndrome

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APPLICATION OF LUCAS-KANADE DENSE FLOW FOR TERRAIN MOTION IN LANDSLIDE MONITORING APPLICATION

Landslides are natural hazards that can cause severe damage and loss of life. Optical cameras are a low-cost and high-resolution alternative among many monitoring systems, as their size and capabilities can vary, allowing for flexible implementation and location. Computer vision is a branch of artificial intelligence that can analyze and understand optical images, using techniques such as optical flow, image correlation and machine learning. The application of such techniques can estimate the motion vectors, displacement fields, providing valuable information for landslide detection, monitoring and prediction. However, computer vision also faces some challenges such as illumination changes, occlusions, image quality, and computational complexity. In this work, a computer vision approach based on Lucas-Kanade optical dense flow was applied to estimate the motion vectors between consecutive images obtained during landslide simulations in a laboratory environment. The approach is applied to two experiments that vary in their illumination and setup parameters to test its applicability. We also discuss the application of this methodology to images from Sentinel-2 satellite optical sensors for landslide monitoring in real-world scenarios

A Comparison Between Machine Learning and Functional Geostatistics Approaches for Data-Driven Analyses of Sediment Transport in a Pre-Alpine Stream

The problem of providing data-driven models for sediment transport in a pre-Alpine stream in Italy is addressed. This study is based on a large set of measurements collected from real pebbles, traced along the stream through radio-frequency identification tags after precipitation events. Two classes of data-driven models based on machine learning and functional geostatistics approaches are proposed and evaluated to predict the probability of movement of single pebbles within the stream. The first class built upon gradient-boosting decision trees allows one to estimate the probability of movement of a pebble based on the pebbles' geometrical features, river flow rate, location, and subdomain types. The second class is built upon functional kriging, a recent geostatistical technique that allows one to predict a functional profile-that is, the movement probability of a pebble, as a function of the pebbles' geometrical features or the stream's flow rate-at unsampled locations in the study area. Although grounded in different perspectives, both models aim to account for two main sources of uncertainty, namely, (1) the complexity of a river's morphological structure and (2) the highly nonlinear dependence between probability of movement, pebble size and shape, and the stream's flow rate. The performance of the two methods is extensively compared in terms of classification accuracy. The analyses show that despite the different perspectives, the overall performance is adequate and consistent, which suggests that both approaches can provide modeling frameworks for sediment transport. These data-driven approaches are also compared with physics-based ones that are classically used in the hydrological literature. Finally, the use of the developed models in a bottom-up strategy, which starts with the prediction/classification of a single pebble and then integrates the results into a forecast of the grain-size distribution of mobilized sediments, is discussed

impact of coccidiosis control program and feeding plan on white striping prevalence and severity degree on broiler breast fillets evaluated at three growing ages

Abstract This study investigated the impact of 2 coccidiosis control systems (vaccine vs anticoccidial) and 2 feeding plans (standard energy vs low energy content, the latter supplemented with threonine and enzymes in the second half of the production cycle) on white striping (WS) prevalence and severity in chicken broiler breasts at commercial slaughter age (51 d). The age of lesion onset was also investigated with the sacrifice of 80 chicks at 12, and 80 chicks at 25 d of age. Seven hundred and twenty ROSS 708 strain male chicks were divided into 4 groups: a non-vaccinated group fed with standard diet (CONTROL); two groups vaccinated against coccidiosis but fed either a standard diet (VACC) or a low-energy diet supplemented with threonine and enzymes (VACC–LE plus); and a fourth group fed a standard diet containing anticoccidial additive except during the finishing period (COX). After live performance, yields, and fillet pH were measured, the breasts were weighed and scored as level 0 (no WS), level 1 (moderate WS), and level 2 (severe WS) at each of the 3 ages; data were covariate for slaughter weight. The results suggest an ameliorative effect of coccidiosis control systems when compared to the control group in terms of live weight, breast yield, and whole breast weight, with heavier fillets characterized by higher pH values. WS appeared at 25 d of age with an average prevalence of 11.5% and with lesions of moderate severity. There were no statistically significant differences due to the experimental treatment at this age. At commercial slaughter age, total average prevalence was 96%, with COX birds showing higher level 2 prevalence (77.6%). This could be related to the higher slaughter weight reached by the COX group (

Long-term hydrogeophysical monitoring of the internal conditions of river levees

To evaluate the vulnerability of the earthen levee of an irrigation canal in San Giacomo delle Segnate, Italy, a customized electrical resistivity tomography (ERT) monitoring system was installed in September 2015 and has been continuously operating since then. Thanks to a meteorological station deployed at the study site, we could investigate the relationship between the inverted resistivity values and different parameters, namely air temperature, rainfall and water level in the canal. Air temperature seems to have a minor but not negligible influence on resistivity variations, especially at shallow depth. A model of soil temperature versus depth was used to correct resistivity sections for air temperature variations through the different seasons. Changes of the water level in the canal and rainfall significantly affect measured resistivity values. At the study site, the most important variations of resistivity are related to saturation and dewatering processes in the irrigation periods. Although we explored the effect of drawdown procedures on resistivity data, this process, causing rapid variations of resistivity values, is still not completely understood because the canal is rapidly emptied during rainfall events. Therefore, the effect of variations of the water level in the canal on levee resistivity cannot be distinguished from the effect of rainfalls. To study the effect of water level variations alone, we considered the beginning of the irrigation period when the dry canal is gradually filled and we observed a smooth trend of resistivity changes. The effect of rainfall on the data was studied during different periods of the year and at different depths of the levee so that the resistivity variations could be evaluated under different conditions. To convert the inverted resistivity sections into water content maps, an empirical and site-dependent relationship between resistivity and water content was obtained using core samples. Water content data can then be used for the implementation of stability analysis using custom modeling. This study introduces an efficient technique to monitor earthen levees and to control the evolution of seepage and water saturation in pseudo-real time. Such a technique can be exploited by Public Administrations to reduce hydrogeological risks significantly

SUSCEPTIBILITY MAPPING OF SHALLOW LANDSLIDES INDUCING DEBRIS FLOWS: A COMPARISON OF PHYSICS-BASED APPROACHES

The assessment of timing and potential locations of rainfallinduced shallow landslides through mathematical models represents a challenge for the assessment of landslide hazard, especially in cases with limited or not available data. In fact, modeling slope hydrological response and stability requires accurate estimates of unsaturated/saturated hydraulic and geotechnical properties of materials involved in landsliding, as well as climate and topography. Such aspect is relevant for the prediction of location and timing of landslide events, which is greatly needed to reduce their catastrophic effects in terms of economic losses and casualties. To such a scope, we present the comparison of results of two physics-based models applied to the assessment of susceptibility to shallow rainfall-induced landslides in Valtellina region (northern Italy). The analyses were carried out considering effects of availability, resolution and type of data concerning spatial distribution, thickness and properties of soils coverings. For such a scope, the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) and the Climatic Rainfall Hydrogeological Modeling Experiment (CHRyME) models were considered. The study emphasizes issues in performing distributed numerical slope stability modeling depending on the availability of spatially distributed soil properties which hamper the quality of physic-based models. Further analyses aimed at the probabilistic assessment of landslide spatial distribution, related to a specific value of rainfall threshold, can be considered as potentially applicable to multi-scale landslide hazard mapping and extendable to other similar mountainous frameworks

Geoelectrical characterization and monitoring of slopes on a rainfall-triggered landslide simulator

In this paper, we present the results of time-lapse electrical resistivity tomography (ERT) monitoring of rainfall-triggered shallow landslides reproduced on a laboratory-scale physical model. The main objective of our experiments was to monitor rainwater infiltration through landslide body in order to improve our understanding of the precursors of failure. Time-domain reflectometry (TDR) data were also acquired to obtain the volumetric water content. Knowing the porosity, water saturation was calculated from the volumetric water content and we could calibrate Archie's equation to calculate water saturation maps from inverted resistivity values. Time-lapse ERT images proved to be effective in monitoring the hydrogeological conditions of the slope as well as in detecting the development of fracture zones before collapse. We performed eight laboratory tests and the results show that the landslide body becomes unstable at zones where the water saturation exceeds 45%. It was also observed that instability could occur at the boundaries between areas with different water saturations. Our study shows that time-lapse ERT technique can be employed to monitor the hydrogeological conditions of landslide bodies and the monitoring strategy could be extended to field-scale applications in areas prone to the development of shallow landslides