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The uncertainty of hydrological forecasts is strongly related to the uncertainty of the rainfall field due to the nonlinear relationship between the spatio-temporal pattern of rainfall and runoff. Rain gauges are typically considered to provide reference data to rebuild precipitation fields. However, due to the density and the distribution variability of the rain gauge network, the rebuilding of the precipitation field can be affected by severe errors which compromise the hydrological simulation output. On the other hand, retrievals obtained from remote sensing observations provide spatially resolved precipitation fields, improving their representativeness. In this regard, the comparison between simulated and observed river flow discharge is crucial for assessing the effectiveness of merged precipitation data in enhancing the model's performance and its ability to realistically simulate hydrological processes. This paper aims to investigate the hydrological impact of using the merged rainfall fields from the Italian rain gauge network and the NASA Global Precipitation Measurement (GPM) IMERG precipitation product. One aspect is to highlight the benefits of applying the cellular automata algorithm to pre-process input data in order to merge them and reconstruct an improved version of the precipitation field. The cellular automata approach is evaluated in the Tanaro River basin, one of the tributaries of the Po River in Italy. As this site is characterized by the coexistence of a variety of natural morphologies, from mountain to alluvial environments, as well as the presence of significant civil and industrial settlements, it makes it a suitable case study to apply the proposed approach. The latter has been applied over three different flood events that occurred from November to December 2014. The results confirm that the use of merged gauge–satellite data using the cellular automata algorithm improves the performance of the hydrological simulation, as also confirmed by the statistical analysis performed for 17 selected quality scores.

The need for faster and more accessible alternatives to laboratory microscopy is driving many innovations throughout the image and data acquisition chain in the biomedical field. Benchtop microscopes are bulky, lack communications capabilities, and require trained personnel for analysis. New technologies, such as compact 3D-printed devices integrated with the Internet of Things (IoT) for data sharing and cloud computing, as well as automated image processing using deep learning algorithms, can address these limitations and enhance the conventional imaging workflow. This review reports on recent advancements in microscope miniaturization, with a focus on emerging technologies such as photoacoustic microscopy and more established approaches like smartphone-based microscopy. The potential applications of IoT in microscopy are examined in detail. Furthermore, this review discusses the evolution of image processing in microscopy, transitioning from traditional to deep learning methods that facilitate image enhancement and data interpretation. Despite numerous advancements in the field, there is a noticeable lack of studies that holistically address the entire microscopy acquisition chain. This review aims to highlight the potential of IoT and artificial intelligence (AI) in combination with portable microscopy, emphasizing the importance of a comprehensive approach to the microscopy acquisition chain, from portability to image analysis.

This study aims to precisely characterize the use of magnetoelectric nanoparticles (MENPs) for stimulating peripheral nerves. Numerical methods were employed to quantify the interaction between MENPs and nervous tissue. The influence of MENPs’ orientation, concentration and distance was assessed in terms of the external potential distribution exerted by the MENPs, the amplification of the exerted MENPs’ stimulation required to excite the neural fibers and the current injected into the intracellular space. The results highlight the significance of MENPs’ concentration for stimulation accuracy and efficiency, the impact of MENPs’ orientation on the electric potential distribution sensed by the nervous tissue, as well as the importance of the MENPs’ distance over the fibers’ recruitment. Given the considerable variability in the interaction between MENPs and nerves, our research provides a crucial step towards understanding this interaction, offering quantitative support for the application of MENPs in nervous tissue stimulation.

[This corrects the article DOI: 10.1371/journal.pone.0274676.].

Abstract Floods are among natural disasters which cause the largest damages worldwide each year, inducing fatalities of human lives, destruction of infrastructure and economical losses. Consequently, forecasting this type of events through hydro‐meteorological models is still of great importance from a civil protection point of view since it allows to reduce hydrological risk by means of early warning systems. Nevertheless, hydrological model initialization in ungauged basins, where there is lack of direct measurements of meteorological information, is a known issue affecting the entire prediction chain. The present study evaluates the possibility of using forecasts provided by the meteorological model MOLOCH developed by CNR‐ISAC forcing the FEST‐WB hydrological model developed by Politecnico di Milano to perform discharge simulations assuming that the forecasting errors are negligible when using the first 24 h of time horizon. The study is carried out in the urban catchments of Milan city, the Seveso‐Olona‐Lambro (SOL) river basins, located in northern Italy. The main hydro‐meteorological variables are analysed by comparing the spatialized and observed meteorological data, provided by an official regional network of weather stations plus a citizen scientists' contribution with the meteorological model forecasts. Moreover, a sensitivity analysis following the well‐known one‐factor‐at‐a‐time methodology is accomplished with the aim of defining which atmospheric forcing, beyond rainfall, mostly affects flowrate forecasts. Results generally show satisfactory correspondences between forecasts and observed data for the discharge variable at daily scale, although an underestimation of precipitation, particularly for severe events in summer, is present. Therefore, using meteorological forecasts to create daily initial conditions for hydrological model, instead of ground observations, might be a reliable and valuable approach, even if some considerations should be borne in mind when coupling the two models.

Core-shell magnetoelectric nanoparticles (MENPs) have recently gained popularity thanks to their capability in inducing a local electric polarization upon an applied magnetic field and vice versa. This work estimates the magnetoelectrical behavior, in terms of magnetoelectric coupling coefficient (αME), via finite element analysis of MENPs with different shapes under either static (DC bias) and time-variant (AC bias) external magnetic fields. With this approach, the dependence of the magnetoelectrical performance on the MENPs geometrical features can be directly derived. Results show that MENPs with a more elongated morphology exhibits a superior αME if compared with spherical nanoparticles of similar volume, under both stimulation conditions analyzed. This response is due to the presence of a larger surface area at the interface between the magnetostrictive core and piezoelectric shell, and to the MENP geometrical orientation along the direction of the magnetic field. These findings pave a new way for the design of novel high-aspect ratio magnetic nanostructures with an improved magnetoelectric behaviour.

Abstract Background Type 2 Diabetes Mellitus (T2DM) patients are twice as likely to develop dementia. The study’s goal was to evaluate cognitive performance and risk factors for cognitive decline in this population. Methods Prospective observational study was conducted with 400 T2DM adults, of whom, during routine baseline and follow-up appointments, had socio-demographic, clinical, and laboratory data collected, and underwent physical examination, screening for depression symptoms (Patient Health Questionaire-9-PHQ-9), and cognitive tests: Mini-Mental State Examination (MMSE), Semantic Verbal Fluency Test, Trail Making Test A/B, and Word Memory Tests. Each cognitive test score was converted to a z-score and its average resulted in a new variable called Global Cognitive z-Score [GCS(z)]. Averages of the cognitive test scores and GCS(z) at both moments were compared by the Student’s T-Test for paired samples. Multivariate binary logistic regression models were built to assess the association of GCS(z)

The purpose of this study is to quantify the distributions of the electric field induced by CoFe2O4 core - BaTiO3 shell magneto-electric nanoparticles (MENPs) when localized in deep brain structures. These fields can be used for deep brain stimulation (DBS), and their effect is compared to the fields induced by conventional DBS electrodes in monopolar and bipolar configuration. A computational approach based on finite element method was applied, along with the use of a highly detailed anatomical model of the brain structures. Different MENPs configurations were investigated and compared to conventional DBS electrode configuration. The activation of nervous fibers was quantified by calculating the Activation Function (AF) defined as the second derivative of the electric potential along the fiber. Electric field amplitudes obtained by MENPs were much lower than the ones obtained by the monopolar and bipolar electrode configurations. The AF values showed that MENPs were able to obtain very localized activation patterns along the fibers. In addition to the minimal invasiveness and proven biocompatibility of the MENPs, the results show that the proposed approach represents an important step towards a selective and minimally invasive strategy for DBS. All these findings are essential in identifying the unique characteristics that MENPs could provide for nervous system stimulation, and how the use of MENPs could improve the development of a new generation of DBS techniques.

Future vehicles will be increasingly connected to enable new applications and improve safety, traffic efficiency and comfort, through the use of several wireless access technologies, ranging from vehicle-to-everything (V2X) connectivity to automotive radar sensing and Internet of Things (IoT) technologies for intra-car wireless sensor networks. These technologies span the radiofrequency (RF) range, from a few hundred MHz as in intra-car network of sensors to hundreds of GHz as in automotive radars used for in-vehicle occupant detection and advanced driver assistance systems. Vehicle occupants and road users in the vicinity of the connected vehicle are thus daily immersed in a multi-source and multi-band electromagnetic field (EMF) generated by such technologies. This paper is the first comprehensive and specific survey about EMF exposure generated by the whole ensemble of connectivity technologies in cars. For each technology we describe the main characteristics, relevant standards, the application domain, and the typical deployment in modern cars. We then extensively describe the EMF exposure scenarios resulting from such technologies by resuming and comparing the outcomes from past studies on the exposure in the car. Results from past studies suggested that in no case EMF exposure was above the safe limits for the general population. Finally, open challenges for a more realistic characterization of the EMF exposure scenario in the connected car are discussed.

This study focuses on one of the most impacted human aspects of digital transformation in contemporary organizations: the development of the affective commitment of newcomers in hybrid work contexts. Specifically, this study addresses a research gap related to the factors that influence the affective commitment of newcomers in hybrid work contexts. First, it investigates the role of two drawbacks of the remote component of hybrid work contexts inhibiting affective commitment: workplace social isolation and technostress. Second, it explores the role of two factors that were previously investigated in in-presence contexts and proved to enhance affective commitment: perceived organizational support and perceived supervisor support. Moreover, this study considers the possible mediating role of newcomer adjustment, intended as a proximal outcome of successful onboarding and an antecedent of newcomer affective commitment. In order to examine enhancing and inhibiting factors and the mediating role of newcomer adjustment, a quantitative study was carried out involving newcomers who began to work in their current organization after January 2021 and who still do remote work at least 1 day a week. Results confirm the inhibiting role of workplace social isolation and the enhancing role of perceived organizational support and perceived supervisor support on affective commitment in hybrid work contexts. Furthermore, they support the mediating role of newcomer adjustment in the relationship between workplace social isolation and affective commitment. While contributing to theory advancement in understanding newcomer affective commitment in current hybrid work contexts, these results also suggest important managerial implications in the field of human resources management, specifically the need to pay greater attention to strategies devoted to increasing newcomers' perception of organizational and supervisor support.

In this study, different methods were compared in order to determine the soil hydraulic conductivity at the saturation (Ks) of two heavily anthropized soils in northern Italy: an irrigated field and a landfill cover. In situ, laboratory measurements (falling head and evaporation method) and pedotransfer functions (ROSETTA and HYPRES) were used for the Ks estimation. In accordance with scientific literature, the results have shown that Ks is largely dependent on the type of technique used in taking the measurements. The ROSETTA and HYPRES pedotransfer functions show quite similar performances, while their easiness and convenient use make them potential alternative techniques for the Ks estimation in comparison with the in situ and laboratory measurements. The Ks estimate is sensitive to the selected method and this sensitivity affects the hydrological model simulations. Therefore, none of the tested methods can be considered as a benchmark, but the results found in this study confirm that the applied method for the determination of Ks, may provide a first estimate of Ks to be subsequently optimised after the simulations.

The recent development of core-shell nanoparticles which combine strain coupled magnetostrictive and piezoelectric phases, has attracted a lot of attention due to their ability to yield strong magnetoelectric effect even at room temperature, thus making them a promising tool to enable biomedical applications. To fully exploit their potentialities and to adapt their use to in vivo applications, this study analyzes, through a numerical approach, their magnetoelectric behavior, shortly quantified by the magnetoelectric coupling coefficient (αME), thus providing an important milestone for the characterization of the magnetoelectric effect at the nanoscale. In view of recent evidence showing that αME is strongly affected by both the applied magnetic field DC bias and AC frequency, this study implements a nonlinear model, based on magnetic hysteresis, to describe the responses of two different core-shell nanoparticles to various magnetic field excitation stimuli. The proposed model is also used to evaluate to which extent realistic variables such as core diameter and shell thickness affect the electric output. Results prove that αME of 80 nm cobalt ferrite-barium titanate (CFO-BTO) nanoparticles with a 60:40 ratio is equal to about 0.28 V/cm∙Oe corresponding to electric fields up to about 1000 V/cm when a strong DC bias is applied. However, the same electric output can be obtained even in absence of DC field with very low AC fields, by exploiting the hysteretic characteristics of the same composites. The analysis of core and shell dimension is as such to indicate that, to maximize αME, larger core diameter and thinner shell nanoparticles should be preferred. These results, taken together, suggest that it is possible to tune magnetoelectric nanoparticles electric responses by controlling their composition and their size, thus opening the opportunity to adapt their structure on the specific application to pursue.

Soil erosion is addressed as one of the main hydrogeological risks in the European Union. Since the average annual soil loss rate exceeds the annual average formation rate, soil is considered as a non-renewable resource. Besides, human activities, human-induced forces and climate change have further accelerated the erosion processes. Therefore, understanding soil erosion spatial and temporal trends could provide important information for supporting government land-use policies and strategies for its reduction. This paper describes the Dynamic Revised Universal Soil Loss Equation (D-RUSLE) model, a modified version of the well-known RUSLE model. The RUSLE model formulation was modified to include variations in rainfall erosivity and land-cover to provide more accurate estimates of the potential soil erosion in the Italian Alps. Specifically, the modelling of snow occurrence and the inclusion of Earth Observation data allow dynamic estimation of both spatial and temporal land-cover changes. Results obtained in Val Camonica (Italy) show that RUSLE model tends to overestimate erosion rates in Autumn/Winter because not considering snow cover and vegetation dynamics. The assimilation of satellite-derived information in D-RUSLE allows a better representation of soil erosion forcing, thus proving a more accurate erosion estimate for supporting government land-use policies and strategies for reducing this phenomenon.

Carnitine palmitoyltransferase II (CPTII) deficiency is the most frequent inherited disorder regarding muscle fatty acid metabolism, resulting in a reduced mitochondrial long-chain fatty acid oxidation during endurance exercise. This condition leads to a clinical syndrome characterized by muscle fatigue and/or muscle pain with a variable annual frequency of severe rhabdomyolytic episodes. While since the CPTII deficiency discovery remarkable scientific advancements have been reached in genetic analysis, pathophysiology and diagnoses, the same cannot be said for the methods of treatments. The current recommendations remain those of following a carbohydrates-rich diet with a limited fats intake and reducing, even excluding, physical activity, without, however, taking into account the long-term consequences of this approach. Suggestions to use carnitine and medium chain triglycerides remain controversial; conversely, other potential dietary supplements able to sustain muscle metabolism and recovery from exercise have never been taken into consideration. The aim of this review is to clarify biochemical mechanisms related to nutrition and physiological aspects of muscle metabolism related to exercise in order to propose new theoretical bases of treatment which, if properly tested and validated by future trials, could be applied to improve the quality of life of these patients.

This paper presents a system for supporting hydropower production on mountainous areas. The system couples the outputs of a numerical weather prediction model and a snow melting and accumulation temperature-based model. Several procedures are presented for interpolating meteorological variables and calibrating and validating model parameters that can be generalized to any other mountainous area where the estimation of current and forecasted snow water equivalent and melting amount is required. The system reliability has been assessed through the validation of three components: spatial interpolation of meteorological data, mathematical modeling, and quantitative meteorological forecast. The results show that good accuracy of meteorological data spatial interpolation can be achieved when the data from snow gauges are used for assessing the precipitation lapse rate at higher altitudes, and the temperature lapse rate is computed from data at each time step. The temperature-based hydrological model proved to be effective in simulating lake inflow water volume and energy production. No clear result has been found for snow melt forecast due to the difficulties in providing reliable quantitative weather forecast in complex alpine area.

Oral cancer is among the deadliest types of malignancy due to the late stage at which it is usually diagnosed, leaving the patient with an average five-year survival rate of less than 50%. The booming field of biosensing and point of care diagnostics can, in this regard, play a major role in the early detection of oral cancer. Saliva is gaining interest as an alternative biofluid for non-invasive diagnostics, and many salivary biomarkers of oral cancer have been proposed. While these findings are promising for the application of salivaomics tools in routine practice, studies on larger cohorts are still needed for clinical validation. This review aims to summarize the most recent development in the field of biosensing related to the detection of salivary biomarkers commonly associated with oral cancer. An introduction to oral cancer diagnosis, prognosis and treatment is given to define the clinical problem clearly, then saliva as an alternative biofluid is presented, along with its advantages, disadvantages, and collection procedures. Finally, a brief paragraph on the most promising salivary biomarkers introduces the sensing technologies commonly exploited to detect oral cancer markers in saliva. Hence this review provides a comprehensive overview of both the clinical and technological advantages and challenges associated with oral cancer detection through salivary biomarkers.

The presence of road ice has always been a key issue during winter months. A reliable forecast system capable of predicting the Land Surface Temperature (LST) and, consequently, its formation is one of the best strategies to operate towards reducing both vehicles accidents and waste of chemical solvents used for prevention which have a significant economic and environmental impact. Hence, the Meteo Expert Centre (MEC) has developed an algorithm for LST forecasts able to issue ice risk warnings as well. This algorithm operationally works every day in real-time and it is here tested, first, on a paved area of the Pedemontana Lombarda motorway and the Milano Linate airport airstrip, and, afterwards, since the LST plays a crucial role in understanding phenomena of energy exchange between soil, vegetation, and atmosphere, its knowledge and prediction becomes relevant also for other purposes such as agricultural management and irrigation system control, further experiments are carried out over two agricultural fields, one in the North and the other in the South of Italy during the SIM (Smart Irrigation Management) project. All LST analyses showed encouraging results with reasonable high values of statistical scores, in both applications on asphalted and different vegetated terrains, demonstrating that the developed algorithm has a high versatility even on completely different types of surfaces, and it can be applied as a valid tool for road ice risk warnings too.

As Diretrizes Curriculares Nacionais direcionam a educação para mudanças no processo ensino-aprendizagem, buscam a valorização da formação quando estabelecem em sua estrutura, competências gerais e específicas, enfatizando a importância do acompanhamento pela avaliação sistemática e permanente visando à melhoria na graduação. A presente pesquisa teve por objetivo avaliar o desenvolvimento das competências gerais em graduandos de nutrição. Trata-se de um estudo analítico com abordagem quantitativa e método transversal onde se utilizou um questionário, elaborado e validado por Matia e Coelho (2015) composto por 44 questões, aplicado em estudantes e professores de quatro instituições de ensino por meio do Software Google forms. Para análise descritiva dos dados foram utilizadas medidas de tendência central e medidas de variabilidade e os testes Mann Whitney, Tukey e Teste- t com nível de significância de p < 0,05, realizadas por meio do Software livre R versão 3.1.1. Obteve-se um total de 210 respostas, sendo 110 de estudantes de ambos os sexos e 100 de professores. A média de idade de estudantes foi de 24,66 ± 7,41 anos. A amostra foi composta por predominância de participantes do gênero feminino (87,3%). Na visão dos professores, os estudantes avaliados parecem estar desenvolvendo mais competências e habilidades de Gestão em saúde e Educação em saúde e na visão dos estudantes houve pequeno destaque apenas na Educação em saúde. Conclui-se que os estudantes dos cursos de nutrição envolvidos na pesquisa não estão desenvolvendo as competências profissionais gerais necessárias a formação, apontadas nas diretrizes, em sua totalidade

Nuestra práctica como docentes de educación primaria nos ha llevado a transitar por distintos niveles de actuación docente: aula, dirección e inspección. Esta actuación nos ha posibilitado asimismo investigar y a estudiar con mayor detenimiento aspectos de la didáctica de la lengua, sensibilizadas por las diferencias de rendimiento escolar y de actuación social derivadas del uso del lenguaje que registran los alumnos provenientes de los contextos socioculturales favorecidos, en relación con los provenientes de contextos no favorecidos socioculturalmente. Esta actividad nuestra también nos ha hecho incursionar en la organización de cursos y jornadas de actualización docente en el área de Lengua.

Human exposure to extremely low frequency magnetic fields (ELF-MF) at 50 Hz is still a topic of great interest due to the possible correlation with childhood leukaemia. The estimation of induced electric fields in human tissues exposed to electromagnetic fields (EMFs) strictly depends on several variables which include the dielectric properties of the tissues. In this paper, the influence of the conductivity assignment to foetal tissues at different gestational ages on the estimation of the induced electric field due to ELF-MF exposure at 50 Hz has been quantified by means of a stochastic approach using polynomial chaos theory. The range of variation in conductivity values for each foetal tissue at each stage of pregnancy have been defined through three empirical approaches and the induced electric field in each tissue has been modelled through stochastic dosimetry. The main results suggest that both the peak and median induced electric fields in foetal fat vary by more than 8% at all gestational ages. On the contrary, the electric field induced in foetal brain does not seem to be significantly affected by conductivity data changes. The maximum exposure levels, in terms of the induced electric field found in each specific tissue, were found to be significantly below the basic restrictions indicated in the ICNIRP Guidelines, 2010.

Food sold in bars, which sometimes do not have adequate sanitary conditions for producing, handling and selling them, end up being contaminated by microorganisms that may be harmful to health, causing infections and food poisoning. The main objective of the study is to identify the presence of total and fecal coliforms in fried pastels sold in bars in downtown Curitiba-PR, Brazil. The study had quantitative approach and included 20 randomly chosen establishments. Microbiological analyzes were performed using the Petrifilm method for counting colony-forming units and identification of microorganisms. There were total coliforms in 17 samples, and the sample with the highest contamination presented 41 colony-forming units. None of the 20 samples showed fecal coliform, which makes ground-beef pastels in accordance with the standards established by Resolution RDC 12 / 2001. Based on the results, the high concentration of total coliforms suggests greater caution in good manufacturing practices and handling to avoid spoilage and disease spread by food. DOI: http://dx.doi.org/10.12957/demetra.2015.14142

Over the last two decades residential exposure to extremely low frequency magnetic fields (ELF MF) has been associated with childhood leukaemia relatively consistently in epidemiological studies, though causality is still under investigation.We aimed to estimate the cases of childhood leukaemia that might be attributable to exposure to ELF MF in the European Union (EU27), if the associations seen in epidemiological studies were causal.We estimated distributions of ELF MF exposure using studies identified in the existing literature. Individual distributions of exposure were integrated using a probabilistic mixture distribution approach. Exposure–response functions were estimated from the most recently published pooled analysis of epidemiological data. Probabilistic simulation was used to estimate population attributable fractions (AFP) and attributable cases of childhood leukaemia in the EU27.By assigning the literature review-based exposure distribution to all EU27 countries, we estimated the total annual number of cases of leukaemia attributable to ELF MF at between ~50 (95% CIs: −14, 132) and ~60 (95% CIs: −9, 610), depending on whether exposure–response was modelled categorically or continuously, respectively, for a non-threshold effect. This corresponds to between ~1.5% and ~2.0% of all incident cases of childhood leukaemia occurring annually in the EU27. Considerable uncertainties are due to scarce data on exposure and the choice of exposure–response model, demonstrating the importance of further research into better understanding mechanisms of the potential association between ELF MF exposure and childhood leukaemia and the need for improved monitoring of residential exposures to ELF MF in Europe. Keywords: Cancer, Childhood leukaemia, Electromagnetic fields, Low frequency, Magnetic fields, Risk assessment

In recent years the interest in the forecast and prevention of natural hazards related to hydro-meteorological events has increased the challenge for numerical weather modelling, in particular for limited area models, to improve the quantitative precipitation forecasts (QPF) for hydrological purposes. After the encouraging results obtained in the MAP D-PHASE Project, we decided to devote further analyses to show recent improvements in the operational use of hydro-meteorological chains, and above all to better investigate the key role played by temperature during snowy precipitation. In this study we present a reanalysis simulation of one meteorological event, which occurred in November 2008 in the Piedmont Region. The attention is focused on the key role of air temperature, which is a crucial feature in determining the partitioning of precipitation in solid and liquid phase, influencing the quantitative discharge forecast (QDF) into the Alpine region. This is linked to the basin ipsographic curve and therefore by the total contributing area related to the snow line of the event. In order to assess hydrological predictions affected by meteorological forcing, a sensitivity analysis of the model output was carried out to evaluate different simulation scenarios, considering the forecast effects which can radically modify the discharge forecast. Results show how in real-time systems hydrological forecasters have to consider also the temperature uncertainty in forecasts in order to better understand the snow dynamics and its effect on runoff during a meteorological warning with a crucial snow line over the basin. The hydrological ensemble forecasts are based on the 16 members of the meteorological ensemble system COSMO-LEPS (developed by ARPA-SIMC) based on the non-hydrostatic model COSMO, while the hydrological model used to generate the runoff simulations is the rainfall–runoff distributed FEST-WB model, developed at Politecnico di Milano.

Recent studies have shown that the specific application of transcranial direct current stimulation (tDCS) over the cerebellum can modulate cerebellar activity. In parallel, transcutaneous spinal DC stimulation was found to be able to modulate conduction along the spinal cord and spinal cord functions. Of particular interest is the possible use of these techniques in paediatric age, since many pathologies and injuries, which affect the cerebellar cortex as well as spinal cord circuits, are diffuse in adults as well as in children. Up to now, experimental studies of cerebellar and spinal DC stimulation on children are completely missing and therefore there is a lack of information about the safety of this technique as well as the appropriate dose to be used during the treatment. Therefore, the knowledge of electric quantities induced into the cerebellum and over the spinal cord during cerebellar tDCS and transcutaneous spinal DCS, respectively, is required.This work wants to address this issue by estimating, through computational techniques, the electric field distributions induced in the target tissues during the two stimulation techniques applied to different models of children of various ages and gender. In detail, we used four voxel child models, aged between 5- and 8-years.Results revealed that, despite inter-individual differences, the cerebellum is the structure mainly involved by cerebellar tDCS, whereas the electric field generated by transcutaneous spinal direct current stimulation can reach the spinal cord also in children. Moreover, it was found that there is a considerable spread toward the anterior area of the cerebellum and the brainstem region for cerebellar tDCS and in the spinal nerve for direct current spinal stimulation. Our study therefore predicts that the electric field spreads in complex patterns that strongly depend on individual anatomy, thus giving further insight into safety issues and informing data for paediatric investigations of these stimulation techniques.

Integrated water resources management at the catchment scale, considering the full water cycle as manageable, is a primary approach to improve water use efficiency and promote sustainable water management solutions. To this purpose, advanced modelling tools are required to quantify the physical and economic effects of alternative land management options. This work presents an application of a spatially distributed physically based hydrological model to the Bonis experimental watershed located in the mountain area of Sila Greca (southern Italy). Different infiltration models were tested to better reproduce discharge observations at basin outlet. The model will be used for evaluating different land use/management scenarios, combined with climate change forcing, to quantify the effect of alternative management options on the land-water cycle. This work is part of the INNOMED project (Innovative Options for Integrated Water Resources Management in the Mediterranean) funded by ERA-NET COFUND WATERWORKS 2015 call.

In recent years there has been considerable interest in the study of glucose-induced dielectric property variations of human tissues as a possible approach for non-invasive glycaemia monitoring. We have developed an electromagnetic sensor, and we tested in vitro its ability to estimate variations in glucose concentration of different solutions with similarities to blood (sodium chloride and Ringer-lactate solutions), differing though in the lack of any cellular components. The sensor was able to detect the effect of glucose variations over a wide range of concentrations (~78–5,000 mg/dL), with a sensitivity of ~0.22 mV/(mg/dL). Our proposed system may thus be useful in a new approach for non-invasive and non-contact glucose monitoring.

Two-dimensional hydraulic modeling is fundamental to simulate flood events in urban area. Key factors to reach optimal results are detailed information about domain geometry and utility of hydrodynamic models to integrate the full or simplified Saint Venant equations in complex geometry. However, in some cases, detailed topographic datasets that represent the domain geometry are not available, so approximations—such as diffusive wave equation—is introduced whilst representing urban area with an adjusted roughness coefficient. In the present paper, different methods to represent buildings and approximation of the Saint Venant equations are tested by performing experiments on a scale physical model of urban district in laboratory. Simplified methods are tested for simulation of a real flood event which occurred in 2013 in the city of Olbia, Italy. Results show that accuracy of simulating flow depth with a detailed geometry is comparable to the one achieved with an adjusted roughness coefficient.

The most widely used method for snow dynamic simulation relies on temperature index approach, that makes snow melt and accumulation processes depend on air temperature related parameters. A recently used approach to calibrate these parameters is to compare model results with snow coverage retrieved from satellite images. In area with complex topography and heterogeneous land cover, snow coverage may be affected by the presence of shaded area or dense forest that make pixels to be falsely classified as uncovered. These circumstances may have, in turn, an influence on calibration of model parameters. In this paper we propose a simple procedure to correct snow coverage retrieved from satellite images. We show that using raw snow coverage to calibrate snow model may lead to parameter values out of the range accepted by literature, so that the timing of snow dynamics measured at two ground stations is not correctly simulated. Moreover, when the snow model is implemented into a continuous distributed hydrological model, we show that calibration against corrected snow coverage reduces the error in the simulation of river flow in an Alpine catchment.

A hydrological model for real time flood forecasting to Civil Protection services requires reliability and rapidity. At present, computational capabilities overcome the rapidity needs even when a fully distributed hydrological model is adopted for a large river catchment as the Upper Po river basin closed at Ponte Becca (nearly 40 000 km2). This approach allows simulating the whole domain and obtaining the responses of large as well as of medium and little sized sub-catchments. The FEST-WB hydrological model (Mancini, 1990; Montaldo et al., 2007; Rabuffetti et al., 2008) is implemented. The calibration and verification activities are based on more than 100 flood events, occurred along the main tributaries of the Po river in the period 2000–2003. More than 300 meteorological stations are used to obtain the forcing fields, 10 cross sections with continuous and reliable discharge time series are used for calibration while verification is performed on about 40 monitored cross sections. Furthermore meteorological forecasting models are used to force the hydrological model with Quantitative Precipitation Forecasts (QPFs) for 36 h horizon in "operational setting" experiments. Particular care is devoted to understanding how QPF affects the accuracy of the Quantitative Discharge Forecasts (QDFs) and to assessing the QDF uncertainty impact on the warning system reliability. Results are presented either in terms of QDF and of warning issues highlighting the importance of an "operational based" verification approach.

In recent years, the interest in the prediction and prevention of natural hazards related to hydrometeorological events has grown due to the increased frequency of extreme rainstorms. Several research projects have been developed to test hydrometeorological models for real-time flood forecasting. However, flood forecasting systems are still not widespread in operational context. Real-world examples are mainly dedicated to the use of flood routing model, best suited for large river basins. For small basins, it is necessary to take advantage of the lag time between the onset of a rainstorm and the beginning of the hydrograph rise, with the use of rainfall-runoff transformation models. Nevertheless, when the lag time is very short, a rainfall predictor is required, as a result, meteorological models are often coupled with hydrological simulation. While this chaining allows floods to be forecasted on small catchments with response times ranging from 6 to 12 h it, however, causes new problems for the reliability of Quantitative Precipitation Forecasts (QPF) and also creates additional accuracy problems for space and time scales. The aim of this work is to evaluate the degree to which uncertain QPF affects the reliability of the whole hydro-meteorological alert system for small catchments. For this purpose, a distributed hydrological model (FEST-WB) was developed and analysed in operational setting experiments, i.e. the hydrological model was forced with rain observation until the time of forecast and with the QPF for the successive period, as is usual in real-time procedures. Analysis focuses on the AMPHORE case studies in Piemonte in November 2002.

RACIONAL: Estudos recentes têm sugerido possível associação entre infecção pelo vírus da hepatite C (VHC) e diabetes melito tipo 2, relatando prevalência elevada de infecção pelo vírus C nessa população. OBJETIVO: Verificar a prevalência de infecção pelo VHC em adultos portadores de diabetes melito em nosso meio. MÉTODOS: Foram avaliados consecutivamente 145 adultos com diabetes melito tipo 2 e 104 com diabetes melito tipo 1, em acompanhamento no ambulatório de diabetes de um hospital universitário, quanto à presença de anticorpos contra VHC (anti-VHC) por método ELISA de quarta geração, utilizando como grupo controle 16 720 doadores de sangue da cidade de Curitiba, PR, no período em que foi realizada a pesquisa. Os pacientes diabéticos foram também avaliados quanto a dados demográficos, clínicos, bioquímicos (níveis séricos de aminotransferases) e exposição prévia a fatores de risco para infecção pelo VHC. RESULTADOS: Maior prevalência de positividade do anti-VHC foi observada em pacientes com diabetes melito tipo 2, em comparação aos doadores de sangue. A prevalência de anti-VHC naqueles com diabete melito tipo 2 foi superior à encontrada no tipo 1, embora não tenha alcançado significância estatística. Nos dois grupos de diabéticos houve predomínio do sexo feminino, sendo que os do tipo 2 apresentavam idade média superior aos do tipo 1. A distribuição de cor, tempo de diagnóstico do diabetes e a freqüência de exposição a fatores de risco foram semelhantes nos dois grupos. A mediana da taxa de alanina aminotransferase dos pacientes com diabetes tipo 2 foi superior à observada nos do tipo 1. CONCLUSÕES: Encontrou-se maior prevalência de infecção pelo VHC em diabéticos tipo 2 se comparado à população saudável de Curitiba, corroborando publicações prévias em outras populações.BACKGROUND: Recently, a possible epidemiological association between hepatitis C virus infection and diabetes mellitus has been suggested and a higher prevalence of HCV antibodies has been found among type 2 diabetic when compared with normal controls. AIM: To evaluate the prevalence of hepatitis C infection in diabetic patients in Curitiba, PR, Brazil. PATIENTS AND METHODS: A total of 145 type 2 and 104 type 1 diabetic patients attending the outpatient diabetic unit of an university hospital were consecutively tested for anti-HCV, using a fourth-generation enzyme-linked immunosorbent assay (ELISA). The control group was constituted by 16,720 volunteer blood donors attending the blood bank of the same hospital during the period of the study. Diabetic patients were also evaluated for clinical, biochemical (aminotransferase levels) and demographic variables and previous exposure to risk factors for hepatitis C infection. RESULTS: A higher prevalence of hepatitis C infection was observed in type 2 diabetic patients in comparison with blood donors. Although anti-HCV prevalence in type 2 diabetic patients was higher than found in type 1, it did not reach statistical significance. Both diabetic groups were predominantly female, and as expected, type 2 diabetic were older than type 1. Race distribution, duration of the disease, and previous exposure to hepatitis C risk factors were similar in both groups, but type 2 diabetic subjects had higher median levels of alanine aminotransferase than type 1. CONCLUSIONS: A higher prevalence of hepatitis C infection was detected in type 2 diabetic patients in comparison with blood donors in our region, in accordance with study data from different populations. If all type 2 diabetic patients should undergo regular screening for hepatitis C infection remains a question.

The Food and Agricultural Organization (FAO) method for potential evapotranspiration assessment is based on the crop coefficient, which allows one to relate the reference evapotranspiration of well irrigated grass to the potential evapotranspiration of specific crops. The method was originally developed for cultivated species based on lysimeter measurements of potential evapotranspiration. Not many applications to natural vegetated areas exist due to the lack of available data for these species. In this paper we investigate the potential of using evapotranspiration measurements acquired by micrometeorological stations for the definition of crop coefficient functions of natural vegetated areas and extrapolation to ungauged sites through remotely sensed data. Pastures, deciduous and evergreen forests have been considered and lower crop coefficient values are found with respect to FAO data.