This work presents the experimental characterization and modeling of a power GaN-on-Si enhancement-mode High Electron Mobility Transistor (eHEMT) provided by STMicroelectronics (SGT120R65AL). A dedicated electro-thermal DC-RF bench and a custom Transistor Test Fixture (TTF) were developed to ensure precise biasing, thermal control, and RF measurements of the Device Under Test (DUT). The DC characterization encompassed a systematic measurement campaign over 24 bias points and various temperature conditions, with subsequent parameter extraction via an approximate Statz model. Bench-induced parasitic resistances were quantified and corrected, allowing accurate derivation of the output characteristics. For the RF analysis, raw scattering parameters were acquired up to 1 GHz and processed through a de-embedding procedure based on auxiliary boards and lossy transmission line models. From the de-embedded S-parameters, several Figures of Merit (FoMs) and parameters were derived, including transition frequency and maximum oscillation frequency. Starting from the de-embedded Y-parameters in the 1–100 MHz range, a linear model of the device was then identified and optimized, presenting a good agreement with experimental data and enabling reliable extraction of capacitances, gain, and stability factors. The results provide insight into the temperature-dependent RF behavior of GaN-on-Si power eHEMTs and establish a validated measurement and modeling methodology.

The biologically based dynamic (BBD) model was used to study the concentration dynamics of methylmercury (MeHg) and its inorganic metabolites (IHg) in the human body. The study focused on the populations residing close to an industrial site characterized by mercury (Hg) pollution, with the main objective of supporting public health decision-making. The BBD model was modified to introduce some novelties compared to previous investigations. First, the BBD model considered the estimated weekly intake of methylmercury (EWI) and the body weight (BDW) as a function of age. Second, the calibration procedure of the BBD model parameters was based on the human biomonitoring data published in previous studies, and metabolism differences between the two genders was considered. Third, the theoretical Hg burdens in major organs and excreta were converted into Hg concentrations to compare the numerical results with the experimental data. The total mercury concentrations in biological matrices were theoretically reproduced for the Italian population, showing a reasonable agreement with values measured in blood (U2= 1.507 for men and for U2 = 0.778 for women), urine (U2= 0.202 for men and for U2 = 0.364 for women) and hair (U2 = 0.425 for men and for U2 = 0.067 for women) of the adult population residing in Augusta Bay between October 2012 and April 2013. Furthermore, the BBD model simulated the methylmercury and inorganic mercury concentrations in major organs, i.e. brain, kidney and liver, of local foodstuff consumers residing in highly polluted areas, showing an acceptable agreement with values measured in cadavers from Hyogo Prefecture (Japan) between November 1971 and May 1972. The model results depended strongly on the diet preferences of the investigated population and the mercury content in consumed foodstuffs. The BBD model can be improved by considering the variations of some biological parameters as a function of age, even if this would require a lot of experimental data on the main organs, which are difficult to obtain. By introducing these improvements, the BBD model could become a useful tool for assessing mercury chronic exposure risks near industrial areas and for improving policies aimed at preventing diseases associated with mercury pollution.

Stochastic resonance (SR) is a phenomenon where noise enhances the detection of weak signals in nonlinear systems. In this study, we investigate the role of environmental noise in facilitating acoustic communication during mating in the southern green stink bug, Nezara viridula (L.), a globally distributed and highly polyphagous pest species. Using behavioral experiments and the source-direction movement (SDM) ratio as a metric, we demonstrate that environmental noise can significantly improve signal recognition between individuals of opposite sex. Notably, the SDM ratio exhibits a nonmonotonic response with two distinct peaks, indicating the presence of a double behavioral stochastic resonance -a phenomenon previously predicted theoretically but not observed in biological systems. The noise intensity levels used in laboratory experiments closely match those recorded in natural habitats, reinforcing the ecological relevance of our findings. These results suggest that environmental noise may play a constructive role in enhancing mating communication in N. viridula, offering new insights into pest control strategies based on acoustic signaling.

Mercury (Hg) contamination represents a significant environmental and public health challenge, particularly in heavily industrialized marine areas. The Augusta Bay, one of the most polluted marine ecosystems in Southern Italy, exemplifies the urgent need for integrated approaches to understand and mitigate Hg impacts. This study is the first to apply a multi-scale modelling framework to address Hg contamination in this region. By integrating environmental processes, food web dynamics and human health impacts, our analysis provides a comprehensive knowledge of Hg pathways and region-specific risks. The framework combines three advanced models. The HR3DHG model reproduces the transport and transformation of Hg species in seawater and sediments, with outputs validated through experimental data collected during extensive field campaigns. The HR3DHG model outputs are then used as inputs for the INTFISH model, which accurately reproduces Hg concentrations in marine organisms of the Augusta Bay while accounting for feeding habits and ecological interactions. Finally, the BBD model addresses the human health dimension by simulating the internal dynamics of methylmercury and its inorganic metabolites in the human body under chronic exposure scenarios. The experimental data coming from the Augusta Bay and their comparison with the values measured in the Hyogo Prefecture (Japan) allowed us to confirm the robustness and relevance of our results (model validation). This innovative framework devised for the Augusta Bay, offers a powerful tool for assessing ecosystem and human health risks associated with Hg contamination, and supports interventions targeted to mitigate the impacts of Hg pollution in coastal areas.

This paper presents a comprehensive investigation of the performance of an electric drive powered by an asymmetric cascaded H-bridge multilevel inverter coupled with an interior permanent magnet synchronous motor (IPMSM). Different modulation strategies are evaluated and compared with a proposed hybrid technique to investigate the advantages of each method. Simulation results are used to assess dynamic behavior and harmonic performance, with a focus on total harmonic distortion and waveform quality. The findings demonstrate that the hybrid modulation approach achieves a better balance between efficiency and harmonic content, making it particularly well-suited for applications requiring rapid dynamic response and high-power quality, such as electric mobility.

Human factors are the leading cause of road transportation accidents, primarily due to driver distractions, drowsiness, fatigue, stress and anxiety. Although significant progress has been made in developing driver monitoring and assistance systems, there is a pressing need for more reliable methodologies that can adapt vehicle safety settings in real-time based on the specific driver's condition. In this context, this paper proposes a low-cost, flexible and affordable system for the real-time monitoring of the driver's health status, through the synchronous acquisition of electrocardiographic (ECG) and photoplethysmographic (PPG) signals and the extraction of heart and breathing rate. Experimental tests are provided to verify the proper working of the developed system, together with its flexibility and reliability under different simulated driving conditions. Even if preliminary, the results are encouraging, suggesting in perspective the possibility of using the proposed system in real driving scenarios to prevent potential accidents due to undesired conditions of either stress or tiredness.

A novel integrated dynamic model, the Integrated Fish Model (INTFISH), incorporating mercury (Hg) dynamics at non-steady state in marine organisms, is presented and is applied to the benthic food web in a polluted area. The integrated Fish model represents the dynamics of inorganic mercury (HgII) and methyl‑mercury (MeHg) in a real marine ecosystem including environmental (seawater and sediments) and biota compartments. Mercury concentration in fish is estimated using the INTFISH model coupled, in real-time, with results from i) the seawater and sediments modules computed using the HR3DHG model, ii) a dedicated Phytoplankton model and iii) six modules for Hg fluxes within the invertebrate compartment, incorporating the main organisms included in fish diet preferences, whose variations during the whole life cycle are also taken into account to verify the sensitivity of the integrated model to the core set of parameters. The simulated total mercury concentrations (HgTOT) in specimens of red mullet (Mullus barbatus), selected as target species for the Fish model, are in excellent agreement with field observations reported from the investigated area. The intrinsic modularity of the model offers the opportunity to extend simulations to other fish species (which are part of the diet of human populations of interest) and predict Hg concentration in food. A natural extension of the model will allow to evaluate the health risks related to human consumption of contaminated fish.

Although mathematical modelling of pressure-flow dynamics in the cardiocirculatory system has a lengthy history, readily finding the appropriate model for the experimental situation at hand is often a challenge in and of itself. An ideal model would be relatively easy to use and reliable, besides being ethically acceptable. Furthermore, it would address the pathogenic features of the cardiovascular disease that one seeks to investigate. No universally valid model has been identified, even though a host of models have been developed. The object of this review is to describe several of the most relevant mathematical models of the cardiovascular system: the physiological features of circulatory dynamics are explained, and their mathematical formulations are compared. The focus is on the whole-body scale mathematical models that portray the subject’s responses to hypovolemic shock. The models contained in this review differ from one another, both in the mathematical methodology adopted and in the physiological or pathological aspects described. Each model, in fact, mimics different aspects of cardiocirculatory physiology and pathophysiology to varying degrees: some of these models are geared to better understand the mechanisms of vascular hemodynamics, whereas others focus more on disease states so as to develop therapeutic standards of care or to test novel approaches. We will elucidate key issues involved in the modeling of cardiovascular system and its control by reviewing seven of these models developed to address these specific purposes.

A variety of mathematical models of the cardiovascular system have been suggested over several years in order to describe the time-course of a series of physiological variables (i.e. heart rate, cardiac output, arterial pressure) relevant for the compensation mechanisms to perturbations, such as severe haemorrhage. The current study provides a simple but realistic mathematical description of cardiovascular dynamics that may be useful in the assessment and prognosis of hemorrhagic shock. The present work proposes a first version of a differential-algebraic equations model, the model dynamical ODE model for haemorrhage (dODEg). The model consists of 10 differential and 14 algebraic equations, incorporating 61 model parameters. This model is capable of replicating the changes in heart rate, mean arterial pressure and cardiac output after the onset of bleeding observed in four experimental animal preparations and fits well to the experimental data. By predicting the time-course of the physiological response after haemorrhage, the dODEg model presented here may be of significant value for the quantitative assessment of conventional or novel therapeutic regimens. The model may be applied to the prediction of survivability and to the determination of the urgency of evacuation towards definitive surgical treatment in the operational setting.

Hemorrhagic shock is a form of hypovolemic shock determined by rapid and large loss of intravascular blood volume and represents the first cause of death in the world, whether on the battlefield or in civilian traumatology. For this, the ability to prevent hemorrhagic shock remains one of the greatest challenges in the medical and engineering fields. The use of mathematical models of the cardiocirculatory system has improved the capacity, on one hand, to predict the risk of hemorrhagic shock and, on the other, to determine efficient treatment strategies. In this paper, a comparison between two mathematical models that simulate several hemorrhagic scenarios is presented. The models considered are the Guyton and the Zenker model. In the vast panorama of existing cardiovascular mathematical models, we decided to compare these two models because they seem to be at the extremes as regards the complexity and the detail of information that they analyze. The Guyton model is a complex and highly structured model that represents a milestone in the study of the cardiovascular system; the Zenker model is a more recent one, developed in 2007, that is relatively simple and easy to implement. The comparison between the two models offers new prospects for the improvement of mathematical models of the cardiovascular system that may prove more effective in the study of hemorrhagic shock.

Hemorrhagic shock is the number one cause of death on the battlefield and in civilian trauma as well. Mathematical modeling has been applied in this context for decades; however, the formulation of a satisfactory model that is both practical and effective has yet to be achieved. This paper introduces an upgraded version of the 2007 Zenker model for hemorrhagic shock termed the ZenCur model that allows for a better description of the time course of relevant observations. Our study provides a simple but realistic mathematical description of cardiovascular dynamics that may be useful in the assessment and prognosis of hemorrhagic shock. This model is capable of replicating the changes in mean arterial pressure, heart rate, and cardiac output after the onset of bleeding (as observed in four experimental laboratory animals) and achieves a reasonable compromise between an overly detailed depiction of relevant mechanisms, on the one hand, and model simplicity, on the other. The former would require considerable simulations and entail burdensome interpretations. From a clinical standpoint, the goals of the new model are to predict survival and optimize the timing of therapy, in both civilian and military scenarios.

We report on the design, development and operation of a portable, low cost, battery-operated, multi-channel, functional Near Infrared Spectroscopy embedded system, hosting up to 64 optical sources and 128 Silicon PhotoMultiplier optical detectors. The system is realized as a scalable architecture, whose elementary leaf consists of a probe board provided with 16 SiPMs, 4 couples of bi-color LED, and a temperature sensor, built on a flexible stand. The hardware structure is very versatile because it is possible to handle both the switching time of the LED and the acquisition of the photodetectors, via an ARM based microcontroller.

Noise through its interaction with the nonlinearity of the living systems can give rise to counter-intuitive phenomena. In this paper we shortly review noise induced effects in different ecosystems, in which two populations compete for the same resources. We also present new results on spatial patterns of two populations, while modeling real distributions of anchovies and sardines. The transient dynamics of these ecosystems are analyzed through generalized Lotka-Volterra equations in the presence of multiplicative noise, which models the interaction between the species and the environment. We find noise induced phenomena such as quasi-deterministic oscillations, stochastic resonance, noise delayed extinction, and noise induced pattern formation. In addition, our theoretical results are validated with experimental findings. Specifically the results, obtained by a coupled map lattice model, well reproduce the spatial distributions of anchovies and sardines, observed in a marine ecosystem. Moreover, the experimental dynamical behavior of two competing bacterial populations in a meat product and the probability distribution at long times of one of them are well reproduced by a stochastic microbial predictive model.

In this paper, we present the measurements performed on a free space optics (FSO) communications link using an indoor atmospheric chamber. In particular, we have generated several different optical turbulence conditions, demonstrating how even the weak turbulence regime can strongly affect the FSO link performance. We have carried out an in-depth analysis of the data collected during the measurements, and calculated the turbulence strength (i.e. scintillation index and Rytov variance) and the important performance metrics (i.e., the Q-factor and bit error rate) to evaluate the FSO link quality. Moreover, we have tested, for the first time, an appositely developed temporally-correlated Gamma-Gamma channel model to generate the temporal irradiance fluctuations observed at the receiver. This has been accomplished by using a complete analysis tool that enables us to fully simulate the experimental FSO link. Finally, we compare the generated time-series with the collected experimental data, showing a good agreement and thus proving the effectiveness of our model.

We demonstrate an innovative CIGS-based solar cells model with a graded doping concentration absorber profile, capable of achieving high efficiency values. In detail, we start with an in-depth discussion concerning the parametrical study of conventional CIGS solar cells structures. We have used the wxAMPS software in order to numerically simulate cell electrical behaviour. By means of simulations, we have studied the variation of relevant physical and chemical parameters—characteristic of such devices—with changing energy gap and doping density of the absorber layer. Our results show that, in uniform CIGS cell, the efficiency, the open circuit voltage, and short circuit current heavily depend on CIGS band gap. Our numerical analysis highlights that the band gap value of 1.40 eV is optimal, but both the presence of Molybdenum back contact and the high carrier recombination near the junction noticeably reduce the crucial electrical parameters. For the above-mentioned reasons, we have demonstrated that the efficiency obtained by conventional CIGS cells is lower if compared to the values reached by our proposed graded carrier concentration profile structures (up to 21%).

In this study, the authors present the measurements performed on a free space optics (FSO) communications link using an indoor atmospheric chamber. In particular, the authors have generated several different optical turbulence conditions, demonstrating how even the weak turbulence regime can strongly affect the FSO link performance. The authors have carried out an in‐depth analysis of the data collected during the measurements, and calculated the turbulence strength (i.e. scintillation index and Rytov variance) and the important performance metrics (i.e. the Q‐factor and bit error rate) to evaluate the FSO link quality. Moreover, the authors have tested, for the first time, an appositely developed temporally‐correlated gamma–gamma channel model to generate the temporal irradiance fluctuations observed at the receiver. This has been accomplished by using a complete analysis tool that enables the authors to fully simulate the experimental FSO link. Finally, the authors compare the generated time‐series with the collected experimental data, showing a good agreement and thus proving the effectiveness of the model.

We report on the design and the electro-optical characterization of new classes of 4H-SiC Schottky UV detectors, fabricated employing Ni2Si interdigitated strips. We have measured, in dark conditions, the forward and reverse I-V characteristics as a function of temperature and C-V characteristics. Responsivity measurements of the devices, as function of wavelength in the UV range, of package temperature and of applied reverse bias are reported. We also compared devices featuring different strip pitch sizes, discussing their performances, and found the device exhibiting best results.

We report on signal-to-noise ratio measurements carried out in the continuous wave regime, at different bias voltages, frequencies, and temperatures, on a class of silicon photomultipliers fabricated in planar technology on silicon p-type substrate. Signal-to-noise ratio has been measured as the ratio of the photogenerated current, filtered and averaged by a lock-in amplifier, and the root mean square deviation of the same current. The measured noise takes into account the shot noise, resulting from the photocurrent and the dark current. We have also performed a comparison between our SiPMs and a photomultiplier tube in terms of signal-to-noise ratio, as a function of the temperature of the SiPM package and at different bias voltages. Our results show the outstanding performance of this class of SiPMs even without the need of any cooling system.