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We present a novel configuration for an axial virtual cathode oscillator (Vircator) operating in the C-band and designed for high output power applications. In order to enhance the efficiency, we have employed a geometry with up to seven reflectors along the drift space. While in previous research works this optimization process has been performed only varying the reflectors radii while using a fixed distance between reflectors,in our work we propose an optimization in terms of both reflectors radii and distances. Our optimized structure for the axial Vircator is able to provide an efficiency up to 15.6% and an output power of 1.6 GW in the C-band, with a working voltage of 510 kV and a cathodic current of 24 kA.

In this work, we study ultra-short term (UST) complexity of Heart Rate Variability (HRV) and its agreement with analysis of standard short-term (ST) HRV recordings obtained at rest and during orthostatic stress. Conditional Entropy (CE) measures have been computed using both a linear Gaussian approximation and a more accurate model-free approach based on nearest neighbors. The agreement between UST and ST indices has been compared via statistical tests and correlation analysis, suggesting the feasibility of exploiting faster algorithms and shorter time series for detecting changes in cardiovascular control during various states.

This paper proposes a control system for a quadratic boost DC/DC converter in a wide range of operations, based on an inner loop with a sliding mode controller, for reaching a desired equilibrium state, and an outer loop with integral-type controller, for assuring robustness against load and input voltage variations and converter parameter uncertainties. The sliding mode controller is designed with the extended linearization method and assures local asymptotic stability, whereas the integral controller is designed using classical frequency methods, and assures input–output stability. It is shown that the proposed controller also deals with the sudden changes in the nominal operating conditions; thus, if a change of the operating conditions takes place, the proposed control scheme automatically creates a sliding regime which stabilizes the converter trajectories to the new equilibrium point. Experimental results carried out on a suitably developed test set up show the effectiveness of the proposed approach.

The growing attention towards healthcare and the constant technological innovations in the field of semiconductor components have allowed a widespread availability of smaller devices, suitable to be worn and able to continuously acquire physiological signals. Wearable devices are, however, more prone to yield signals corrupted by artifacts caused by movement. This issue is particularly relevant in photoplethysmographic (PPG) applications where also, to exploit the whole dynamic range of the acquisition device, the DC component of the signal should be removed and the AC component amplified. In this context, we have designed and realized an analog front-end (AFE) suitable to be integrated within PPG wearable devices able to minimize these problems by reducing the ambient light and the factors that can vary the average value of the current output from a silicon photomultiplier in a PPG system using a green LED. DC component elimination is pursued by a signal conditioning circuit realized by the design and the implementation of a transimpedance amplifier and a Miller integrator capable of following and subsequently subtracting the average value of the acquired signal, so as to obtain an output signal that fluctuates around zero. The step response of the feedback circuit was studied carrying out a PPG acquisition on wrist with promising preliminary results.

Nowadays, the ever-growing interest to health and quality of life of individuals and the advancements in electronic devices technology are pushing the development of portable and wearable biomedical devices able to pursue a minimally invasive monitoring of physiological parameters in daily-life conditions. Such devices can now carry out a real-time assessment of the subjects’ overall health status and possibly even detect ongoing diseases. In this context, we have designed and implemented a multisensor portable system able to perform synchronous real-time acquisitions of electrocardiographic (ECG), photoplethysmographic (PPG) and airflow breathing signals. We investigated cardiorespiratory interactions between heart period and respiratory time series, extracted from combined ECG and breathing signals (considered as the reference), or using the PPG signal only, through Granger Causality measures in time and frequency domain. The aim was to assess to what extent the non-invasive and cost-effective PPG technique can be employed alone to assess cardiorespiratory interactions, thus avoiding the simultaneous acquisitions of ECG or breathing signals with more bulky or uncomfortable devices. The analysis was carried out on 6 healthy young subjects, undergoing a two-phase protocol consisting in spontaneous and controlled breathing phases. Our findings show that linear interactions measures behave similarly if ECG or PPG are used for detecting the heart period and sampling the airflow respiratory signal, while the utilization of a respiratory signal extracted through filtering or as the envelope of the PPG waveform could lead to causality underestimates and must be further investigated.

In recent years, the attention to the health and comfort of the individual, together with the electronic miniaturization progress, have led to an increased interest in the development of biomedical devices that are able to acquire a multitude of biomedical signals. Such devices should be wearable and comfortable during daily use, to be thus suitable for continuously monitoring psychophysical health states. In this context, we have designed and realized a portable biomedical device capable of real-time acquisition of electrocardiographic (ECG), photoplethysmographic (PPG), breathing and galvanic skin response (GSR) signals, for a noninvasive monitoring of multiple physiological parameters. This work shows the architecture of our system, which integrates a Bluetooth module for wireless communication with the central computer and novel analog sensors capable of carrying out breathing and GSR measurements. Preliminary measurements carried out using our system during a controlled breathing protocol illustrated how the simultaneous measurement of ECG, PPG, GSR and respiration allows tracking changes not only in heart rate, but also in epidermal tissue sweating, thus confirming that the device can be successfully employed for monitoring health status and, in perspective, also for assessing the individual’s stress level.

The amount of information exchanged per unit of time between two dynamic processes is an important concept for the analysis of complex systems. Theoretical formulations and data-efficient estimators have been recently introduced for this quantity, known as the mutual information rate (MIR), allowing its continuous-time computation for event-based data sets measured as realizations of coupled point processes. This work presents the implementation of MIR for point process applications in Network Physiology and cardiovascular variability, which typically feature short and noisy experimental time series. We assess the bias of MIR estimated for uncoupled point processes in the frame of surrogate data, and we compensate it by introducing a corrected MIR (cMIR) measure designed to return zero values when the two processes do not exchange information. The method is first tested extensively in synthetic point processes including a physiologically-based model of the heartbeat dynamics and the blood pressure propagation times, where we show the ability of cMIR to compensate the negative bias of MIR and return statistically significant values even for weakly coupled processes. The method is then assessed in real point-process data measured from healthy subjects during different physiological conditions, showing that cMIR between heartbeat and pressure propagation times increases significantly during postural stress, though not during mental stress. These results document that cMIR reflects physiological mechanisms of cardiovascular variability related to the joint neural autonomic modulation of heart rate and arterial compliance.

Background and objective: Recently, various algorithms have been introduced using wrist-worn photo-plethysmography (PPG) to provide high accuracy of instantaneous heart rate (HR) estimation, including during high-intensity exercise. Most studies focus on using acceleration and/or gyroscope signals for the motion artifact (MA) reference, which attenuates or cancels out noise from the MA-corrupted PPG signals. We aim to open and pave the path to find an appropriate MA reference selection for MA cancelation in PPG.Methods: We investigated how the acceleration and gyroscope reference signals correlate with the MAs of the distorted PPG signals and derived both mathematically and experimentally an adaptive MA reference selection approach. We applied our algorithm to five state-of-the-art (SOTA) methods for the performance evaluation. In addition, we compared the four MA reference selection approaches, i.e. with acceleration signal only, with gyroscope signal only, with both signals, and using our proposed adaptive selection.Results: When applied to 47 PPG recordings acquired during intensive physical exercise from two differ-ent datasets, our proposed adaptive MA reference selection method provided higher accuracy than the other MA selection approaches for all five SOTA methods.Conclusion: Our proposed adaptive MA reference selection approach can be used in other MA cancelation methods and reduces the HR estimation error.Significance: We believe that this study helps researchers to address acceleration and gyroscope signals as accurate MA references, which eventually improves the overall performance for estimating HRs through the various algorithms developed by research groups.

In recent years, new efficient power devices have been implemented. Silicon Carbide has replaced silicon as regards the production and the utilization of many devices, such as MOSFETs, diodes, IGBTs and many others. SiC devices are characterized by a low reverse recovery charge, high carrier saturation velocity, by which it is possible to work at high frequency, and high breakdown voltage. Thanks to the great thermal conductivity and the wide bandgap, these devices can operate at high temperature and reach high voltages and currents. What is important to stress is the fact that power losses in SiC devices are lower than the silicon ones. These are the reasons why these devices are utilized in a wide range of technological applications, including power electronics. In this paper, power losses in Si and SiC devices are evaluated in simulation and compared to each other. In order to demonstrate the remarkable advantages of the SiC devices over the silicon ones, a study which makes use of an isolated DC-DC converter has been conducted. As regards the proposed full-bridge converter, SiC and silicon MOSFETs and diodes, of whom some static and dynamic parameters are defined, are used in order to transfer power from a DC voltage supply to a load.

In this work, we report on a comparison among graphene field-effect transistors (GFETs) employing different dielectrics as gate layers to evaluate their microwave response. In particular, aluminum oxide (Al$_{2}$O$_{3}$), titanium oxide (TiO$_{2}$), and hafnium oxide (HfO$_{2}$) have been tested. GFETs have been fabricated on a single chip and a statistical analysis has been performed on a set of 24 devices for each type of oxide. Direct current and microwave measurements have been carried out on such GFETs and short circuit current gain and maximum available gain have been chosen as quality factors to evaluate their microwave performance. Our results show that all of the devices belonging to a specific group (i.e., with the same oxide) have a well-defined performance curve and that the choice of hafnium oxide represents the best trade-off in terms of dielectric properties. Graphene transistors employing HfO$_{2}$ as the dielectric layer, in fact, exhibit the best performance in terms of both the cutoff frequency and the maximum frequency of oscillation.

In this work, we report on the design, fabrication and characterization of Metal-Oxide Graphene Field-effect Transistors (MOGFETs) exploiting novel clamped gate geometries aimed at enhancing the device transconductance. The fabricated devices employ clamped metal contacts also for source and drain, as well as an optimized graphene meandered pattern for source contacting, in order to reduce parasitic resistance. Our experimental results demonstrate that MOGFETs with the proposed structure show improved high frequency performance, in terms of maximum available gain and transition frequency values, as a consequence of the higher equivalent transconductance obtained.

In this work, we extend to the multivariate case the classical correlation analysis used in the field of network physiology to probe dynamic interactions between organ systems in the human body. To this end, we define different correlation-based measures of the multivariate interaction (MI) within and between the brain and body subnetworks of the human physiological network, represented, respectively, by the time series of delta, theta, alpha, and beta electroencephalographic (EEG) wave amplitudes, and of heart rate, respiration amplitude, and pulse arrival time (PAT) variability. MI is computed: (i) considering all variables in the two subnetworks to evaluate overall brain–body interactions; (ii) focusing on a single target variable and dissecting its global interaction with all other variables into contributions arising from the same subnetwork and from the other subnetwork; and (iii) considering two variables conditioned to all the others to infer the network topology. The framework is applied to the time series measured from the EEG, electrocardiographic (ECG), respiration, and blood volume pulse (BVP) signals recorded synchronously via wearable sensors in a group of healthy subjects monitored at rest and during mental arithmetic and sustained attention tasks. We find that the human physiological network is highly connected, with predominance of the links internal of each subnetwork (mainly heart rate-respiration and delta-theta, theta-alpha, alpha-beta), but also statistically significant interactions between the two subnetworks (mainly heart rate-beta and heart rate-delta). MI values are often spatially heterogeneous across the scalp and are modulated by the physiological state, as indicated by the decrease of cardiorespiratory interactions during sustained attention and by the increase of brain–heart interactions and of brain–brain interactions at the frontal scalp regions during mental arithmetic. These findings illustrate the complex and multi-faceted structure of interactions manifested within and between different physiological systems and subsystems across different levels of mental stress.

The objective of this study is to present a new method to assess in the frequency domain the directed interactions between the spontaneous variability of systolic arterial pressure (SAP) and heart period (HP) from their linear model representation, and to apply it for studying the baroreflex control of arterial pressure in healthy physiological states and after acute myocardial infarction (AMI). The method is based on pole decomposition of the model transfer function and on the following evaluation of causal measures of coupling and gain from the poles associated to low frequency (0.04−0.15 Hz) oscillatory components. It is compared with traditional non-causal approaches for the spectral analysis of the baroreflex gain, and with causal approaches based on the directed coherence, in a group of AMI patients and in Young and Old healthy controls studied at rest and during head-up tilt. Analysis of feedforward interactions from RR to SAP is also performed. Our results support the importance of using local causal approaches to quantify separately baroreflex and feedforward interactions between RR and SAP, allowing both to confirm known physiological behaviors (e.g., weaker baroreflex effectiveness and lower sensitivity after AMI) and to suggest novel findings (e.g., preserved low frequency baroreflex response to postural stress after AMI). We also find that the postural stress alters feedforward interactions selectively across groups, being related to decreased coupling only in Young and to increased gain mostly in AMI. These results have a significance for the clinical assessment of the baroreflex and the physiological evaluation of cardiovascular interactions.

We present an innovative implementation of the solid-state-biased coherent detection (SSBCD) technique, which we have recently introduced for the reconstruction of both amplitude and phase of ultra-broadband terahertz pulses. In our previous works, the SSBCD method has been operated via a heterodyne scheme, which involves demanding square-wave voltage amplifiers, phase-locked to the THz pulse train, as well as an electronic circuit for the demodulation of the readout signal. Here, we demonstrate that the SSBCD technique can be operated via a very simple homodyne scheme, exploiting plain static bias voltages. We show that the homodyne SSBCD signal turns into a bipolar transient when the static field overcomes the THz field strength, without the requirement of an additional demodulating circuit. Moreover, we introduce a differential configuration, which extends the applicability of the homodyne scheme to higher THz field strengths, also leading a two-fold improvement of the dynamic range compared to the heterodyne counterpart. Finally, we demonstrate that, by reversing the sign of the static voltage, it is possible to directly retrieve the absolute THz pulse polarity. The homodyne configuration makes the SSBCD technique of much easier access, leading to a vast range of field-resolved applications.

Il monitoraggio di pazienti tramite segnali fotopletismografici (PhotoPlethysmoGram, PPG) acquisiti sul polso, arteria radiale, piuttosto che sulla punta dell’indice, permette di ottenere un segnale più stabile e con maggiori informazioni, come la gittata cardiaca, la durata della contrazione ventricolare e la chiusura dell’aorta. In questo lavoro è presentata un’attività preliminare per rilevare condizioni come l’ostruzione polmonare e le apnee notturne. Si è indagato l’andamento dell’aritmia respiratoria in relazione ad eventuali difficoltà respiratorie. Per il momento ci si è limitati ad osservare soggetti sani e l’ostruzione è stata simulata facendo respirare i soggetti attraverso una cannuccia.

The human body can be seen as a functional network depicting the dynamical interactions between different organ systems. This exchange of information is often evaluated with information-theoretic approaches which comprise the use of vector autoregressive (VAR) and state space (SS) models, normally identified with the Ordinary Least Squares (OLS). However, the number of time series to be included in the model is strictly related to the length of data recorded thus limiting the use of the classical approach. In this work, a new method based on penalized regressions, the so-called LASSO, was compared with OLS on physiological time-series extracted from 18 subjects during different stress conditions. Results show similarities between the brain-body interactions estimated by both methodologies, highlighting a greater intepretability of patterns estimated with LASSO especially in the subnetwork of brain-brain interactions.

The recent advances in multiparametric monitoring of biosignals and management of big data prompt for the development of devices and techniques for the extraction of indicators with physiological relevance. In this context, we have designed and realized a portable electronic system, equipped with simple biomedical sensors, able to synchronously record multiple electrocardiographic (ECG), photoplethysmographic (PPG) and breathing signals, for carrying out a non-invasive monitoring of several cardiovascular parameters. In this work, we show the results of preliminary measurements performed following a specific physiological protocol (i.e., deep breathing with 10 s per cycle). The system allows to monitor specific physiological behaviors, such as the decrease of the R-R interval (increase of the heart rate) during inhalation and the increase of the stroke volume increases during exhalation. The high quality of the ECG/PPG/breath waveforms acquired by our probes, sensors and system allows an improvement in the accuracy of the extraction of noteworthy cardiovascular parameters.

Baroreflex response consists of cardiac chronotropic (effect on heart rate), cardiac inotropic (on contractility), venous (on venous return) and vascular (on vascular resistance) arms. Because of its measurement simplicity, cardiac chronotropic arm is most often analysed. The aim was to introduce a method to assess vascular baroreflex arm, and to characterize its changes during stress. We evaluated the effect of orthostasis and mental arithmetics (MA) in 39 (22 female, median age: 18.7 yrs.) and 36 (21 female, 19.2 yrs.) healthy volunteers, respectively. We recorded systolic and mean blood pressure (SBP and MBP) by volume-clamp method and R-R interval (RR) by ECG. Cardiac output (CO) was recorded using impedance cardiography. From MBP and CO, peripheral vascular resistance (PVR) was calculated. The directional spectral coupling and gain of cardiac chronotropic (SBP to RR) and vascular arms (SBP to PVR) were quantified. The strength of the causal coupling from SBP to PVR was significantly higher than SBP to RR coupling during whole protocol (P < 0.001). Along both arms, the coupling was higher during orthostasis compared to supine (P < 0.001 and P = 0.006), no MA effect was observed. No significant changes in the spectral gain (ratio of RR or PVR change to a unit SBP change) across all phases were found (0.111 ≤ P ≤ 0.907). We conclude that changes in PVR are tightly coupled with SBP oscillations via the baroreflex providing an approach for the baroreflex vascular arm analysis with a potential to reveal new aspects of blood pressure dysregulation.

In this work, we investigate the possibility of employing graphene field effect transistors, specifically designed for microwave applications, as infrared detectors for telecom applications. Our devices have been fabricated on a sapphire substrate employing CVD-grown transferred graphene. The roles of both the gate dielectric and the DC bias conditions have been evaluated in order to maximize the infrared generated signal through an experimental investigation of the signal-to-noise ratio dependence on the transistor operating point.

The sustainable development of our planet is considerably related to a relevant reduction of CO2 global emissions, with building consumption contributing more than 40%. In this scenario, new technological conceptions, such as building-integrated photovoltaic technology, emerged in order to satisfy the requirements of sustainability imposed by the European Union. Therefore, the aim of this work is to provide a technical and economical comparison of the performances of different vertical-mounted innovative photovoltaic systems, potentially integrated on a building instead of on traditional windows or glass walls. The proposed investigation was carried out by means of experimental tests on three different next-generation vertical structures. The related results are described and discussed, highlighting the advantages and the drawbacks of the proposed technologies.

Heart rate variability (HRV, variability of the RR interval of the electrocardiogram) results from the activity of several coexisting control mechanisms, which involve the influence of respiration (RESP) and systolic blood pressure (SBP) oscillations operating across multiple temporal scales and changing in different physiological states. In this study, multiscale information decomposition is used to dissect the physiological mechanisms related to the genesis of HRV in 78 young volunteers monitored at rest and during postural and mental stress evoked by head-up tilt (HUT) and mental arithmetics (MA). After representing RR, RESP and SBP at different time scales through a recently proposed method based on multivariate state space models, the joint information transfer T RESP , SBP &rarr, RR is decomposed into unique, redundant and synergistic components, describing the strength of baroreflex modulation independent of respiration ( U SBP &rarr, RR ), nonbaroreflex ( U RESP &rarr, RR ) and baroreflex-mediated ( R RESP , SBP &rarr, RR ) respiratory influences, and simultaneous presence of baroreflex and nonbaroreflex respiratory influences ( S RESP , SBP &rarr, RR ), respectively. We find that fast (short time scale) HRV oscillations&mdash, respiratory sinus arrhythmia&mdash, originate from the coexistence of baroreflex and nonbaroreflex (central) mechanisms at rest, with a stronger baroreflex involvement during HUT. Focusing on slower HRV oscillations, the baroreflex origin is dominant and MA leads to its higher involvement. Respiration influences independent on baroreflex are present at long time scales, and are enhanced during HUT.

Heart rate variability (HRV) analysis represents an important tool for the characterization of complex cardiovascular control. HRV indexes are usually calculated from electrocardiographic (ECG) recordings after measuring the time duration between consecutive R peaks, and this is considered the gold standard. An alternative method consists of assessing the pulse rate variability (PRV) from signals acquired through photoplethysmography, a technique also employed for the continuous noninvasive monitoring of blood pressure. In this work, we carry out a thorough analysis and comparison of short-term variability indexes computed from HRV time series obtained from the ECG and from PRV time series obtained from continuous blood pressure (CBP) signals, in order to evaluate the reliability of using CBP-based recordings in place of standard ECG tracks. The analysis has been carried out on short time series (300 beats) of HRV and PRV in 76 subjects studied in different conditions: resting in the supine position, postural stress during 45° head-up tilt, and mental stress during computation of arithmetic test. Nine different indexes have been taken into account, computed in the time domain (mean, variance, root mean square of the successive differences), frequency domain (low-to-high frequency power ratio LF/HF, HF spectral power, and central frequency), and information domain (entropy, conditional entropy, self entropy). Thorough validation has been performed using comparison of the HRV and PRV distributions, robust linear regression, and Bland–Altman plots. Results demonstrate the feasibility of extracting HRV indexes from CBP-based data, showing an overall relatively good agreement of time-, frequency-, and information-domain measures. The agreement decreased during postural and mental arithmetic stress, especially with regard to band-power ratio, conditional, and self-entropy. This finding suggests to use caution in adopting PRV as a surrogate of HRV during stress conditions.

Two versions of a PPG/ECG combined system have been realized and tested. In a first version a multisite system has been equipped by integrating 3 PPG optodes and 3 ECG leads, whereas in another setup a portable version has been carried out. Both versions have been realized by equipping the optical probes with SiPM detectors. SiPM technology is expected to bring relevant advantages in PPG systems and overcome the limitations of physiological information extracted by state of the art PPG, such as poor sensitivity of detectors used for backscattered light detection and motion artifacts seriously affecting the measurements repeatability and pulse waveform stability. This contribution presents the intermediate results of development in the frame of the European H2020-ECSEL Project ASTONISH (n. 692470), including SiPM based PPG optodes, and the acquisition electronic components used for simultaneous recording of both PPG/ECG signals. The accurate monitoring of dynamic changes of physiological data through a non-invasive integrated system, including hemodynamic parameters (e.g. heart rate, tissue perfusion etc.) and heart electrical activity can play an important role in a wide variety of applications (e.g. healthcare, fitness and cardiovascular disease). In this work we describe also a method to process PPG waveform according to a PPG process pipeline for pattern recognition. Some examples of PPG waveform signal analysis and the preliminary results of acquisitions obtained through the intermediate demonstrator systems have been reported.

We present a new method to quantify in the frequency domain the strength of directed interactions between linear stochastic processes. This issue is traditionally addressed by the directed coherence (DC), a popular causality measure derived from the spectral representation of vector autoregressive (AR) processes. Here, to overcome intrinsic limitations of the DC when it needs to be objectively quantified within specific frequency bands, we propose an approach based on spectral decomposition, which allows to isolate oscillatory components related to the pole representation of the vector AR process in the Z-domain. Relating the causal and non-causal power content of these components we obtain a new spectral causality measure, denoted as pole-specific spectral causality (PSSC). In this study, PSSC is compared with DC in the context of cardiovascular variability analysis, where evaluation of the spectral causality from arterial pressure to heart period variability is of interest to assess baroreflex modulation in the low frequency band (0.04-0-15 Hz). Using both a theoretical example in which baroreflex interactions are simulated, and real cardiovascular variability series measured from a group of healthy subjects during a postural challenge, we show that - compared with DC- PSSC leads to a frequency-specific evaluation of spectral causality which is more objective and more focused on the frequency band of interest.

The development of connected health technologies for the continuous monitoring of the psychophysical state of individuals performing daily life activities requires the aggregation of non-intrusive sensors and the availability of methods and algorithms for extracting the relevant physiological information. The present study proposes an integrated approach for the objective assessment of mental stress which combines wirelessly connected low invasive biosensors with multivariate physiological time series analysis. In a group of 18 healthy subjects monitored in a relaxed resting state and during two experimental conditions inducing mental stress and sustained attention (respectively, mental arithmetic and serious game), we collected simultaneously multichannel EEG, one lead ECG, respiration and blood volume pulse. From these signals, synchronous physiological time series were extracted measuring the $\delta$, $\theta$, $\alpha$, and $\beta$ EEG amplitudes, the heart period, the sampled respiratory activity and the pulse arrival time. For each condition, five minute windows of each of these seven time series were characterized with measures in the time domain (mean, standard deviation) and in the information domain (self entropy, measuring time series regularity). We show that the dynamical activity of the different physiological systems is affected in a different way by the alteration of the psychophysical state of the subjects induced by stress, and that the measures in the two domains can elicit complementary information about mental stress and sustained attention. These results advocate the feasibility of connected health technology for minimally invasive, automatic classifiers of different levels of mental stress in real life scenarios.

Information storage, reflecting the capability of a dynamical system to keep predictable information during its evolution over time, is a key element of intrinsic distributed computation, useful for the description of the dynamical complexity of several physical and biological processes. Here we introduce a parametric approach which allows one to compute information storage across multiple timescales in stochastic processes displaying both short-term dynamics and long-range correlations (LRC). Our analysis is performed in the popular framework of multiscale entropy, whereby a time series is first "coarse grained" at the chosen timescale through low-pass filtering and downsampling, and then its complexity is evaluated in terms of conditional entropy. Within this framework, our approach makes use of linear fractionally integrated autoregressive (ARFI) models to derive analytical expressions for the information storage computed at multiple timescales. Specifically, we exploit state space models to provide the representation of lowpass filtered and downsampled ARFI processes, from which information storage is computed at any given timescale relating the process variance to the prediction error variance. This enhances the practical usability of multiscale information storage, as it enables a computationally reliable quantification of a complexity measure which incorporates the effects of LRC together with that of short-term dynamics. The proposed measure is first assessed in simulated ARFI processes reproducing different types of autoregressive dynamics and different degrees of LRC, studying both the theoretical values and the finite sample performance. We find that LRC alter substantially the complexity of ARFI processes even at short timescales, and that reliable estimation of complexity can be achieved at longer timescales only when LRC are properly modeled. Then, we assess multiscale information storage in physiological time series measured in humans during resting state and postural stress, revealing unprecedented responses to stress of the complexity of heart period and systolic arterial pressure variability, which are related to the different role played by LRC in the two conditions. published

In this work, we report on the modelling of light soaking effect on Ruthenium-based Dye Sensitized Solar cells (DSSCs). Such a phenomenon can be detected when exposing the cells at increasing hours of illumination and produces a reversible performance increase. Starting from the results obtained through the electro-optical characterization of the cells, we applied a one-diode circuital-model. Our results show a good agreement between the experimental and the simulated data, with a mean square error in the order of 10−12 and a maximum error in current lower than 0.6%. Finally such results allowed us to infer some precise trends followed by the cells main electrical parameters and of their equivalent one-diode electrical model due to light soaking effect.

The authors report on an in-depth statistical and parametrical investigation on the microwave performance of graphene FETs on sapphire substrate. The devices differ for the gate-drain/source distance and for the gate length, having kept instead the gate width constant. Microwave S -parameters have been measured for the different devices. Their results demonstrate that the cut-off frequency does not monotonically increase with the scaling of the device geometry and that it exists an optimal region in the gate-drain/source and gate-length space which maximises the microwave performance.

In the domain of Earth Explorer satellites nanoengineered nonlinear crystals can optimize UV tunable solid-state laser converters. Lightweight sources can be based on Lithium Niobate (LN) domain engineering by electric field poling and guided wave interactions. In this Communication we report the preliminary experimental results and the very first demonstration of UltraViolet second-harmonic generation by first-order quasi-phase-matching in a surface-periodically-poled proton-exchanged LN waveguide. The pump source was a Ti-Sapphire laser with a tunability range of 700- 980 nm and a 40 GHz linewidth. We have measured UV continuous-wave light at 390 nm by means of a lock-in amplifier and of a photodiode with enhanced response in the UV. Measured conversion efficiency was about 1%W-1cm-2. QPM experiments show good agreement with theory and pave the way for a future implementation of the technique in materials less prone to photorefractive damage and wider transparency in the UV, such as Lithium Tantalate.

We report on the electrical and optical characterization, in continuous wave regime, of a novel class of silicon photomultipliers fabricated in standard planar technology on a silicon p-type substrate. Responsivity measurements, performed with an incident optical power down to tenths of picowatts, at different reverse bias voltages and on a broad (340–820 nm) spectrum, will be shown and discussed. The device temperature was monitored, allowing us to give a physical interpretation of the measurements. The obtained results demonstrate that such novel silicon photomultipliers are suitable as sensitive power meters for low photon fluxes.

Free Space Optics (FSO) links are affected by several impairments: optical turbulence, scattering, absorption, and pointing. In particular, atmospheric optical turbulence generates optical power fluctuations at the receiver that can degrade communications with fading events, especially in high data rate links. Innovative solutions require an improvement of FSO link performances, together with testing models and appropriate channel codes. In this paper, we describe a high-resolution time-correlated channel model able to predict random temporal fluctuations of optical signal irradiance caused by optical turbulence. Concerning the same channel, we also report simulation results on the error mitigation performance of Luby Transform, Raptor, and RaptorQ codes.

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.

We present a novel class of CMOS-compatible devices aimed to perform the solid-state-biased coherent detection of ultrashort terahertz pulses, i.e., featuring a gap-free bandwidth at least two decades-wide. Such a structure relies on a 1-µm-wide slit aperture located between two parallel aluminum pads, embedded in a 1-µm-thick layer of silicon nitride, and deposited on a quartz substrate. We show that this device can detect ultra-broadband terahertz pulses by employing unprecedented low optical probe energies of only a few tens of nanojoules. This is due to the more than one order of magnitude higher nonlinear coefficient of silicon nitride with respect to silica, the nonlinear material employed in the previous generations. In addition, due to the reduced distance between the aluminum pads, very high static electric fields can be generated within the slit by applying extremely low external bias voltages (in the order of few tens of volts), which strongly enhance the dynamic range of the detected THz waveforms. These results pave the way to the integration of solid-state ultra-broadband detection in compact and miniaturized terahertz systems fed by high repetition-rate laser oscillators and low-noise, low-voltage generators.

We present a universal and rigorous approach to study difference frequency generation in the terahertz domain, keeping the number of degrees of freedom to a minimum, through the definition of a suitable figure of merit. The proposed method relies on suitably normalized charts, that enable to predict the optical-to-terahertz conversion efficiency of any system based on wave propagation in quadratic nonlinear materials. The predictions of our approach are found to be in good agreement with the best experimental results reported to date, enabling also to estimate the d22 nonlinear coefficient of high quality GaSe., 3 pages in 2 columns format, 3 figures. GaSe analysis has been corrected. Fig. 3 has been replaced

The surface plasmon resonance (SPR) technique is a well-known optical method that can be used to measure the refractive index of organic nano-layers adsorbed on a thin metal film. Although there are many configurations for measuring biomolecular interactions, SPR-based techniques play a central role in many current biosensing experiments, since they are the most suited for sensitive and quantitative kinetic measurements. Here we give some results from the analysis and numerical elaboration of SPR data from integrated optics experiments in a particular borosilicate glass, chosen for its composition offering the rather low refractive index of 1.4701 at 633 nm wavelength. These data regard the flow over the sensing region (metal window) of different solutions with refractive indexes in the range of interest (1.3÷1.5) for the detection of contaminants in aqueous solutions. After a discussion of the principles of SPR, of the metal window design optimization by means of optical interaction numerical modeling, and of waveguide fabrication techniques, we give a description of system setup and experimental results. Optimum gold film window thickness and width in this guided-wave configuration has been for the first time derived and implemented on an integrated optic prototype device. Its characterization is given by means of the real time waveguide output intensity measurements, which correspond to the interaction between the sensing gold thin film window and the flowing analyte. The SPR curve was subsequently inferred. Finally, a modified version of the device is reported, with channel waveguides arranged in a Y-junction optical circuit, so that laser source stability requirements are lowered by a factor of 85 dB, making possible the use of low cost sources in practical applications.

The compatibility of low concentration (alpha-phase) proton exchange channel waveguides with electric field surface periodic poling of congruent lithium niobate (SPPLN) crystals has been experimentally demonstrated. With such waveguides, we obtained ultraviolet second harmonic generation (SHG) by first order quasi-phase-matching (QPM), a result made possible by the fabrication, on Z-cut LN crystals, of periodic structures with a pitch down to 750 nm. Nonlinear copropagating QPM-SHG measurements have been carried out on such structures. The pump source was a Ti:sapphire laser with a tunability range of 700-980 nm and a 40 GHz linewidth. We have measured UV continuous wave light at 390 nm by means of a lock-in amplifier and a photodiode with an enhanced response in the UV. The measured conversion efficiency was about 1% W(-1) cm(-2).

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., This work was supported by the European Space Agency under grant no. 5401001020. We are very grateful to Dr. E. Armandillo for enlightening discussions. J. Perez's work was support by Spanish MINECO Juan de la Cierva Fellowship JCI-2012-14805. This research project falls within the frame of COST ICT Action IC1101 - Optical Wireless Communications - An Emerging Technology (OPTICWISE).

In free space optical (FSO) communications, several factors can strongly affect the link quality. Among them, one of the most important impairments that can degrade the FSO link quality and its reliability even under the clear sky conditions consists of optical turbulence. In this work, the authors investigate the generation of both weak and moderate turbulence regimes in an indoor environment to assess the FSO link quality. In particular, they show that, due to the presence of the turbulence, the link experiences both erasure errors and packet losses during transmission, and also compare the experimental statistical distribution of samples with the predicted Gamma Gamma model. Furthermore, the authors demonstrate that the application of the RaptorQ codes noticeably improves the link quality decreasing the packet error rate (PER) by about an order of magnitude, also offering in certain cases an error-free transmission with a PER of ∼10−2 at Rytov variance value of 0.5. The results show that the recovery rate increases with the redundancy, the packet length and the number of source packets, and it decreases with increasing data rates., This work was supported by the European Space Agency under grant no. 5401001020. We are very grateful to Dr. E. Armandillo for enlightening discussions. This research project also falls within the frame of COST ICT Action IC1101 - Optical Wireless Communications - An Emerging Technology (OPTICWISE). J. Perez's work is supported by Spanish MINECO Juan de la Cierva JCI-2012-14805.