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There has been continuous progress in diabetes management over the last few decades, not least due to the widespread dissemination of continuous glucose monitoring (CGM) and automated insulin delivery systems. These technological advances have radically changed the daily lives of people living with diabetes, improving the quality of life of both children and their families. Despite this, hypoglycemia remains the primary side-effect of insulin therapy. Based on a systematic review of the available scientific evidence, this paper aims to provide evidence-based recommendations for recognizing, risk stratifying, treating, and managing patients with hypoglycemia. The objective of these recommendations is to unify the behavior of pediatric diabetologists with respect to the timely recognition and prevention of hypoglycemic episodes and the correct treatment of hypoglycemia, especially in patients using CGM or advanced hybrid closed-loop systems. All authors have long experience in the specialty and are members of the Italian Society of Pediatric Endocrinology and Diabetology. The goal of treating hypoglycemia is to raise blood glucose above 70 mg/dL (3.9 mmol/L) and to prevent further decreases. Oral glucose at a dose of 0.3 g/kg (0.1 g/kg for children using “smart pumps” or hybrid closed loop systems in automated mode) is the preferred treatment for the conscious individual with blood glucose

Social competence—defined as the ability to optimize social behaviour according to available social information—can be influenced by the social environment experienced in early life. In cooperatively breeding vertebrates, the current group size influences behavioural phenotypes, but it is not known whether the group size experienced in early life influences behavioural phenotypes generally or social competence specifically. We tested whether being reared in large versus small groups for the first two months of life affects social behaviours, and associated life-history traits, in the cooperatively breeding cichlid Neolamprologus pulcher between the ages of four and twelve months. As we predicted, fish raised in larger and more complex groups showed higher social competence later in life. This was shown in several ways: they exhibited more, and earlier, submissive behaviour in response to aggression from a dominant conspecific, and—in comparison to fish raised in small groups—they exhibited more flexibility in the expression of submissive behaviour. By contrast, there was no evidence that early social complexity, as captured by the group size, affects aggression or exploration behaviour nor did it influence the propensity to disperse or show helping behaviour. Our results emphasize the importance of early-life social complexity for the development of social competence.

ABSTRACT The affective state of animals, that is, their mood and emotions, is altered by stressful (negative) or enriching (positive) experiences. In turn, the affective state influences decision making, thereby helping animals when coping with environmental challenges and opportunities. However, it is largely unknown how social experiences modulate the affective state. Here, we performed a judgement bias test to study the effects of rearing group‐size and experimentally assigned current rank on the affective state of the cooperatively‐breeding cichlid fish Neolamprologus pulcher. To assess affective state, we developed and validated a judgement bias test for this species. Fish learned to discriminate between a positive and a negative stimulus as shown by different latencies to approach the stimulus. Furthermore, the response curves to the stimuli conformed to the ones expected in judgement bias tests: fish showed an intermediate latency to approach an ambiguous stimulus, which significantly differed from the latencies to approach the positive and the negative stimulus. Unexpectedly, there were no significant effects of rearing group size and current social rank on the affective state of N. pulcher, despite known effects of these two social parameters on behaviours and physiology of this species. This may mean that observed behavioural and physiological differences in the treatment environments do not allow valid predictions about the affective state elicited by these environments. Alternatively, it may need more socioecologically relevant testing paradigms when evaluating the valence of social environments. [ABSTRACT FROM AUTHOR]

In the last few years, some regions of the Mediterranean area have witnessed a progressive increase in extreme events, such as urban and flash floods, as a response to the increasingly frequent and severe extreme rainfall events, which are often exacerbated by the ever-growing urbanization. In such a context, the urban drainage systems may not be sufficient to convey the rainwater, thus increasing the risk deriving from the occurrence of such events. This study focuses on a particularly intense urban flood that occurred in Palermo (Italy) on 15 July 2020; it represents a typical pluvial flood due to extreme rainfall on a complex urban area that many cities have experienced in recent years, especially in the Mediterranean region. A conceptual hydrological model and a 2D hydraulic model, particularly suitable for simulations in a very complex urban context, have been used to simulate the event. Results have been qualitatively validated by means of crowdsourced information and satellite images. The experience of Palermo, which has highlighted the urgent need for a shift in the way stormwater in urban settlements is managed, can be assumed to be a paradigm for modeling pluvial floods in complex urban areas under extreme rainfall conditions. Although the approaches and the related policies cannot be identical for all cities, the modeling framework used here to assess the impacts of the event under study and some conclusive remarks could be easily transferred to other, different urban contexts.

Future projections provided by climate models suggest that the occurrence of extreme rainfall events will increase and this is evidence that the climate is changing. Because the design of urban drainage systems is based on the statistical analysis of past events, variations in the intensity and frequency of extreme rainfall represent a critical issue for the estimation of rainfall. For this reason, the design criteria of drainage systems should take into account the trends in the past and the future climate changes projections. To this end, a Bayesian procedure was proposed to update the parameters of depth–duration–frequency (DDF) curves to assess the uncertainty related to the estimation of these values, once the evidence of annual maximum rainfall trends was verified. Namely, in the present study, the historical extreme rainfall series with durations of 1, 3, 6, 12 and 24 h for the period of 1950–2008, recorded by the rain gauges located near the Paceco urban area (southern Italy), were analyzed to detect statistically significant trends using the non‐parametric Mann‐Kendall test. Based on the rainfall trends, the parameters of the DDF curves for a five‐year return period were updated to define some climate scenarios. Finally, the implications of the uncertainty related to the DDF parameters estimation on the design of a real urban drainage system was assessed to provide an evaluation of its performance under the assumption of climate change. Results showed that the future increase of annual maximum precipitation in the area of study would affect the analyzed drainage system, which could face more frequent episodes of surcharge.

Among the indirect estimation approaches of soil water content in the upper layer of the soil, the “triangle method” is one of the most common that relies on the simple relationship between the optical and thermal features sensed via Earth Observation. These features are controlled by water content at the surface and within the root zone but also by meteorological forcing including air temperature and humidity, as well as solar radiation. Night- and day-time MODIS composites of land-surface temperature (LST) allowed applying a version of the triangle method that takes into account the temporal admittance of the soil. In this study, it has been applied to a long time-series of pair images to analyze the seasonal influence of the meteorological forcing on a triangle method index (or temperature−vegetation index, TVX), as well as to discuss extra challenges of the diachronic approach including seasonality effects and the variability of environmental forcing. The Imera Meridionale basin (Sicily, Italy) has been chosen to analyze the method over a time-series of 12 years. The analysis reveals that, under these specific environmental and climatic conditions (strong seasonality and rainfall out of phase with vegetation growth), Normalized Difference Vegetation Index (NDVI) and LST pairs move circularly in time within the optical vs. thermal feature space. Concordantly, the boundaries of the triangle move during the seasons. Results showed a strong correlation between TVX and rainfall normalized amplitudes of the power spectra (r2 ~0.8) over the range of frequencies of the main harmonics.

Knowledge of soil water content plays a key role in water management efforts to improve irrigation efficiency. Among the indirect estimation methods of soil water content via Earth Observation data is the triangle method, used to analyze optical and thermal features because these are primarily controlled by water content within the near-surface evaporation layer and root zone in bare and vegetated soils. Although the soil-vegetation-atmosphere transfer theory describes the ongoing processes, theoretical models reveal limits for operational use. When applying simplified empirical formulations, meteorological forcing could be replaced with alternative variables when the above-canopy temperature is unknown, to mitigate the effects of calibration inaccuracies or to account for the temporal admittance of the soil. However, if applied over a limited area, a characterization of both dry and wet edges could not be properly achieved; thus, a multi-temporal analysis can be exploited to include outer extremes in soil water content. A diachronic empirical approach introduces the need to assume a constancy of other meteorological forcing variables that control thermal features. Airborne images were acquired on a Sicilian vineyard during most of an entire irrigation period (fruit-set to ripening stages, vintage 2008), during which in situ soil water content was measured to set up the triangle method. Within this framework, we tested the triangle method by employing alternative thermal forcing. The results were inaccurate when air temperature at airborne acquisition was employed. Sonic and aerodynamic air temperatures confirmed and partially explained the limits of simultaneous meteorological forcing, and the use of proxy variables improved model accuracy. The analysis indicates that high spatial resolution does not necessarily imply higher accuracies.

The olive tree is one of the most characteristic rainfed trees in the Mediterranean region. Observed and forecasted climate modifications in this region, such as the CO2 concentration and temperature increase and the net radiation, rainfall and wind speed decrease, will likely alter vegetation water stress and modify productivity. In order to simulate how climatic change could alter soil moisture dynamic, biomass growth and fruit productivity, a water-driven crop model has been used in this study. The numerical model, previously calibrated on an olive orchard located in Sicily (Italy) with a satisfactory reproduction of historical olive yield data, has been forced with future climate scenarios generated using a stochastic weather generator and a downscaling procedure of an ensemble of climate model outputs. The stochastic downscaling is carried out using simulations of some General Circulation Models adopted in the fourth Intergovernmental Panel on Climate Change (IPCC) assessment report (4AR) for future scenarios. The outcomes state that climatic forcings driving potential evapotranspiration compensate for each other, resulting in a slight increase of this water demand flux; moreover, the increase of CO2 concentration leads to a potential assimilation increase and, consequently, to an overall productivity increase in spite of the growth of water stress due to the rainfall reduction.

Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles that can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood-prone areas. In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends, while for longer durations the trends are mainly negative. Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the nonparametric Mann–Kendall test. In particular, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration, while daily rainfall properties have been analyzed in terms of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations, especially for 1 h rainfall duration. Conversely, precipitation events of long durations have exhibited a decreased trend. Increase in short-duration precipitation has been observed especially in stations located along the coastline; however, no clear and well-defined spatial pattern has been outlined by the results. Outcomes of analysis for daily rainfall properties have showed that heavy–torrential precipitation events tend to be more frequent at regional scale, while light rainfall events exhibited a negative trend at some sites. Values of total annual precipitation events confirmed a significant negative trend, mainly due to the reduction during the winter season.

In systems experiencing water scarcity and consequent intermittent supply, users often adopt private tanks that collect water during service periods and supply users when the service is not available. The tank may be fed by gravity or by private pumping stations depending on the network pressure level. Once water resources are collected, the tank can supply users by gravity if it is located on the rooftop or by additional pumping if underground. Private tanks thus increase the energy cost of the water supply service for users by introducing several small pumping structures inside the network. The present paper aims to evaluate this users’ energy cost for different private tank configurations. A real case study was analysed, and the results showed that intermittent distribution causes inequalities not only in users’ access to water resource but also costs that users have to bear to have access to water.

Flow duration curves are simple and powerful tools to deal with many hydrological and environmental problems related to water quality assessment, water-use assessment and water allocation. Unfortunately the scarcity of streamflow data enables the use of these instruments only for gauged basins. A regional model is developed here for estimating flow duration curves at ungauged basins in Sicily, Italy. Due to the complex ephemeral behavior of the examined region, this study distinguishes dry periods, when flows are zero, from wet periods using a three parameters power law to describe the frequency distribution of flows. A large dataset of streamflows has been analyzed and the parameters of flow duration curves have been derived for about fifty basins. Regional regression equations have been developed to derive flow duration curves starting from morphological basin characteristics.

For open orchard and vineyard canopies containing significant fractions of exposed soil (>50%), typical of Mediterranean agricultural regions, the energy balance of the vegetation elements is strongly influenced by heat exchange with the bare soil/substrate. For these agricultural systems a "two-source" approach, where radiation and turbulent exchange between the soil and canopy elements are explicitly modelled, appears to be the only suitable methodology for reliably assessing energy fluxes. In strongly clumped canopies, the effective wind speed profile inside and below the canopy layer can strongly influence the partitioning of energy fluxes between the soil and vegetation components. To assess the impact of in-canopy wind profile on model flux estimates, an analysis of three different formulations is presented, including algorithms from Goudriaan (1977), Massman (1987) and Lalic et al. (2003). The in-canopy wind profile formulations are applied to the thermal-based two-source energy balance (TSEB) model developed by Norman et al. (1995) and modified by Kustas and Norman (1999). High resolution airborne remote sensing images, collected over an agricultural area located in the western part of Sicily (Italy) comprised primarily of vineyards, olive and citrus orchards, are used to derive all the input parameters needed to apply the TSEB. The images were acquired from June to October 2008 and include a relatively wide range of meteorological and soil moisture conditions. A preliminary sensitivity analysis of the three wind profile algorithms highlights the dependence of wind speed just above the soil/substrate to leaf area index and canopy height over the typical range of canopy properties encountered in these agricultural areas. It is found that differences among the models in wind just above the soil surface are most significant under sparse and medium fractional cover conditions (15–50%). The TSEB model heat flux estimates are compared with micro-meteorological measurements from a small aperture scintillometer and an eddy covariance tower collected over an olive orchard characterized by moderate fractional vegetation cover (≈35%) and relatively tall crop (≈3.5 m). TSEB fluxes for the 7 image acquisition dates generated using both the Massman and Goudriaan in-canopy wind profile formulations give close agreement with measured fluxes, while the Lalic et al. equations yield poor results. The Massman wind profile scheme slightly outperforms that of Goudriaan, but it requires an additional parameter accounting for the roughness sub-layer of the underlying vegetative surface. The analysis also suggests that within-canopy wind profile model discrepancies become important, in terms of impact on modelled sensible heat flux, only for sparse canopies with moderate vegetation coverage.

Remote sensing allowed monitoring the reservoir water level by estimating its surface extension. Surface extension has been estimated using different approaches, employing both optical (Landsat 5 TM, Landsat 7 ETM+ SLC-Off, Landsat 8 OLI-TIRS and ASTER images) and Synthetic Aperture Radar (SAR) images (Cosmo SkyMed and TerraSAR-X). Images were characterized by different acquisition modes, geometric and spectral resolutions, allowing the evaluation of alternative and/or complementary techniques. For each kind of image, two techniques have been tested: The first based on an unsupervised classification and suitable to automate the process, the second based on visual matching with contour lines with the aim of fully exploiting the dataset. Their performances were evaluated by comparison with water levels measured in situ (r2 = 0.97 using the unsupervised classification, r2 = 0.95 using visual matching) demonstrating that both techniques are suitable to quantify reservoir surface extension. However ~90% of available images were analyzed using the visual matching method, and just 37 images out of 58 using the other method. The evaluation of the water level from the water surface, using both techniques, could be easily extended to un-gauged reservoirs to manage the variations of the levels during normal operation. In addition, during the period of investigation, the use of Global Navigation Satellite System (GNSS) allowed the estimation of dam displacements. The advantage of using as reference a GNSS permanent station positioned relatively far from the dam, allowed the exclusion of any interaction with the site deformations. By comparing results from both techniques, relationships between the orthogonal displacement component via GNSS, estimated water levels via remote sensing and in situ measurements were investigated. During periods of changing water level (April 2011–September 2011 and October 2011–March 2012), the moving average of displacement time series (middle section on the dam crest) shows a range of variability of ±2 mm. The dam deformation versus reservoir water level behavior differs during the reservoir emptying and filling periods indicating a hysteresis-kind loop.

Actual evapotranspiration is assessed via surface energy balance at an hourly rate. However, a robust estimation of daily evapotranspiration from hourly values is required. Outcomes of surface energy balance are frequently determined via measures of eddy covariance latent heat flux. Surface energy balance can be applied on images acquired at different times and spatial resolutions. In addition, hourly actual evapotranspiration needs to be integrated at a daily rate for operational uses. Questions arise whether the validation of surface energy balance models can benefit from complementary in situ measures of latent heat flux and sap flow transpiration. Here, validation was driven by image acquisition time, spatial resolution, and temporal integration. Thermal and optical images were collected with a proximity-sensing platform on an olive orchard at different acquisition times. Actual latent heat fluxes from canopy and sap flux at tree trunks were measured with a flux tower and heat dissipation probes. The latent heat fluxes were then further analyzed. A surface energy balance was applied over proximity sensing images re-sampled at different spatial resolutions with resulting latent heat fluxes compared to in situ ones. A time lag was observed and quantified between actual latent heat fluxes from canopy and sap flux at the tree trunk. Results also indicate that a pixel resolution comparable to the average canopy size was suitable for estimating the actual evapotranspiration via a single source surface energy balance model. Images should not be acquired at the beginning or the end of the diurnal period. Findings imply that sap flow transpiration can be used to measure surface energy balance at a daily rate or when images are found at an hourly rate near noon, and the existing time lag between the latent heat flux at the canopy and the sap flow at the trunk does not need to be taken into account.

The knowledge of spatial and temporal variability of soil water content and others soil-vegetation variables (leaf area index, fractional cover) assumes high importance in crop management. Where and when the cloudiness limits the use of optical and thermal remote sensing techniques, synthetic aperture radar (SAR) imagery has proven to have several advantages (cloud penetration, day/night acquisitions and high spatial resolution). However, measured backscattering is controlled by several factors including SAR configuration (acquisition geometry, frequency and polarization), and target dielectric and geometric properties. Thus, uncertainties arise about the more suitable configuration to be used. With the launch of the ALOS Palsar, Cosmo-Skymed and Sentinel 1 sensors, a dataset of multi-frequency (X, C, L) and multi-polarization (co- and cross-polarizations) images are now available from a virtual constellation; thus, significant issues concerning the retrieval of soil-vegetation variables using SAR are: (i) identifying the more suitable SAR configuration; (ii) understanding the affordability of a multi-frequency approach. In 2006, a vast dataset of both remotely sensed images (SAR and optical/thermal) and in situ data was collected in the framework of the AgriSAR 2006 project funded by ESA and DLR. Flights and sampling have taken place weekly from April to August. In situ data included soil water content, soil roughness, fractional coverage and Leaf Area Index (LAI). SAR airborne data consisted of multi-frequency and multi-polarized SAR images (X, C and L frequencies and HH, HV, VH and VV polarizations). By exploiting this very wide dataset, this paper, explores the capabilities of SAR in describing four of the main soil-vegetation variables (SVV). As a first attempt, backscattering and SVV temporal behaviors are compared (dynamic analysis) and single-channel regressions between backscattering and SVV are analyzed. Remarkably, no significant correlations were found between backscattering and soil roughness (over both bare and vegetated plots), whereas it has been noticed that the contributions of water content of soil underlying the vegetation often did not influence the backscattering (depending on canopy structure and SAR configuration). Most significant regressions were found between backscattering and SVV characterizing the vegetation biomass (fractional cover and LAI). Secondly, the effect of SVV changes on the spatial correlation among SAR channels (accounting for different polarization and/or frequencies) was explored. An inter-channel spatial/temporal correlation analysis is proposed by temporally correlating two-channel spatial correlation and SVV. This novel approach allowed a widening in the number of significant correlations and their strengths by also encompassing the use of SAR data acquired at two different frequencies.

Turbulent flow characteristics were investigated in laboratory flume studies of a ligulate plant canopy interrupted by a gap representing discontinuities observed in seagrass prairies. The reliability of velocity measurements obtained using an acoustic Doppler velocimeter within the canopy was shown using specifically designed experiments. In relatively fast flow (mean velocity 5.5 cm [s.sup.-1]), the mean flow profile was logarithmic above the canopy, had an inflection point near its top, and uniformly low values within it. Within the gap, a recirculation cell formed. Reynolds stress maxima were approximately coincident with the mean flow inflection point. Quadrant analysis revealed an ejection-dominated upper layer, a sweep-dominated region around the top of the canopy and within the gap, and no dominant quadrant within the canopy. In slower flow (mean velocity 1.7 cm [s.sup.-1]) the plants were quasiemergent and the flow fields more uniform. Sweeps similarly dominated the region near the top of the canopy and within the gap. In both flows, autocorrelation of longitudinal velocity fluctuations showed a Lagrangian time scale maximum at the downstream end of the gap. DOI: 10.1061/(ASCE)0733-9429(2007)133:7(750) CE Database subject headings: Aquatic plants; Turbulent flow; Velocity; Reynolds stress.